Unlocking a New Layer of Value: Pathology … › apps › docs › reference › new_layer...This information is intended for internal use only and shall not be reproduced, copied,

© 2013 College of American Pathologists. All rights reserved.This information is intended for internal use only and shall not be reproduced, copied, disclosed, transmitted, in whole or in part, without the express written consent of the CAP.

Unlocking a New Layer of Value: Pathology-Supported Decision Making

A Report for Health Care Executives

College of American Pathologists | 1 2 | College of American Pathologists

Executive Summary

Hospital executives are aggressively adopting initiatives to contain costs and

raise the value of the care they deliver. Many of the strategies being employed

are derived from nationally disseminated reform initiatives. This paper describes a

new strategy that offers hospitals multiplicative increases in value by upgrading

clinical decision-making through collaboration with pathologists. Ironically, the

rapid advancement of medical knowledge and technologies has created levels

of complexity that challenge the effectiveness of clinical decision-making.

Pathologists have the expertise, technologies, and data to manage this

complexity, help improve clinical decision making, and substantially elevate

hospitals’ value yields.

Under pressure from health care reform and demographic dynamics, hospital

leaders are devising strategies aimed at cost containment and value-based care

delivery. Lower reimbursement rates, volume to value payer initiatives, and rising

operating costs are converging to force unprecedented changes to provider

operations and delivery models.

In many hospitals, executives are pursuing nationally recommended best

practices for improving value generation. These include, for example, care

coordination, care management, provider integration, clinical pathways

adoption, and performance management with data analytics. These institutions

are achieving successes in increased efficiency and value in their care delivery.

But a one-time value increase is not enough. Perpetual improvements fuel

the new value-centered health care system. Payers and policy makers are

continually raising the performance bar, expecting higher levels and new types

of value. To stay competitive, hospital leaders need to identify what’s next in

terms of value-generating opportunities, especially now that payers are tying

compensation to peer-ranked performance metrics.

One option for hospitals seeking new sources of value involves a fundamental

process in care delivery: clinical decision making. Three factors suggest this

opportunity can yield high returns:

1. The impact of clinical decision making on value is often

pervasive and multiplicative. The quality and cost results of a

clinical decision (eg, diagnosis, treatment choice, admission,

discharge) become amplified as they ripple through

subsequent patient services.


2. The decision-making process is suboptimal, and this

performance gap results in lost value. Driven by the exponential

rise in new knowledge, tests, treatments, and technologies, the

complexity of clinical decision making has surpassed human

cognitive capacity, as reported recently by the Institute of

Medicine (IOM).

3. This lost value can be captured by more closely involving

pathologists in decision making. Pathologists uniquely possess the

expertise, information, and technologies to qualify as decision-

support experts. Their technical knowledge spans all diseases

and types of testing. Pathology and laboratory testing is the

primary driver of clinician decision making. Furthermore,

pathologists, and laboratory professionals are at the center of

genomic medicine, and thus they are increasingly involved in

therapeutic recommendations.

The challenges of clinical decision making have been increasingly recognized

in recent years. “[T]he complexity of modern health care is reaching levels that

challenge human cognitive capacity. Research in several areas has found that

complexity can have negative effects on people’s ability [to] make decisions,”

writes the IOM in a September 2012 report.1 In fact, the IOM report found that this high medical complexity clinical decision-making problem is one of two reasons the US health care system has not significantly improved its performance over the past decade.

Three aspects of health care complexity, in particular, are stressing clinicians’

decision making:

1. Complexity of digesting new clinical evidence — The

exponential rise in new medical publications surpasses clinicians’

abilities to stay current. The ever-growing reports on new tests

and treatments complicate clinicians’ decisions by adding more

choices and often contradictory evidence regarding efficacy.

2. Complexity of patient information management — The volume

and variety of patient information present clinicians with

information overload and signal to noise issues that complicate

decision making. This is despite, and sometimes because of,

health care information technology systems such as electronic

health records (EHRs).

3. Complexity of applying genomic medicine — Because of the

extremely rapid development and complex nature of genomic

medicine and data informatics tools, clinicians do not have the

needed knowledge to optimally use them in their decision

making. Providers are thus missing opportunities to make higher

value decisions through effective application of these tools.

College of American Pathologists |3 4|College of American Pathologists | 4

The process of clinical decision making needs to be updated for the new realities

of modern medicine and technology. Computers already play important roles in

supporting decision making, but studies show that technology is not a sufficient

solution.

Clinicians are overburdened in many ways and need greater support from a

process perspective if care delivery performance is expected to improve. They

need experts to guide them through the complexity and help select, access, and

interpret the best available decision-making information at the point of decision.

Pathologists and laboratory professionals are well equipped to be optimal clinical decision partners. They maintain a gold mine of information, technologies, and knowledge, and they can provide new types of decision-making tools and services that help optimize information selection and delivery for decision making.

Pathology-supported decision making represents a new generation of

pathology and laboratory services that extends beyond the analytic test and

report, reaching into the point of care to directly support and partner with

providers in value-generating ways. Pathology-supported decision-making

initiatives do not need to be implemented all at once, across the board. Rather,

they can be implemented incrementally for specific clinical disorders and

decision areas.

The results from pathology-supported decision-making initiatives addressing

particular hospital target areas include:

• Septicemia — 36% reduction in average septicemia hospital costs:

o For 200-400 bed hospitals, this could yield $5 million in savings.

• Blood product utilization programs:

o An average, nongovernment, acute care hospital might save

$1.06 million annually.

• Acute Kidney Injury (AKI) — ~32% reduction in hospital AKI/acute

renal failure cases:

o For 350–500 bed hospitals, this might represent $7.5 million in

cost savings.

The details of these initiatives will be described later in this report.

College of American Pathologists |3 4|College of American Pathologists | 4

This report will:

• Describe how the clinical decision-making process has been

negatively impacted by the explosion in medical information

and technologic advances over the past decade or so;

• Discuss the multiplicative impacts improved clinical decision

making can have on value creation and cost containment;

• Demonstrate how pathologists and new diagnostic technologies

are specially positioned to provide new approaches to

advancing clinical decision making;

• Detail hospital examples of pathology-supported

decision-making approaches, including quantified estimates

of generated value.

College of American Pathologists |5 6 |College of American Pathologists

Provider Decision Making: Value Critical But Complexity Burdened

Hospital executives are facing an unprecedented set of financial and strategic challenges. A report from Booz & Company predicts 15% to 25% declines in hospital revenue yields over the next 10 years. “Creating a sustainable cost structure will require an innovative, forward-looking approach that systematically establishes a much lower cost base as the ‘new normal,’” writes Curt Bailey, partner, Booz & Company.2

Health care leaders are redesigning operations and care delivery to achieve both a “new normal” cost base and a value-centered system. This initial phase of transformation is successfully generating value in a number of ways. Still, as the system moves toward value-based purchasing, new sources of value will need to be continuously identified, and correcting deficiencies will be vital.

A critical process at the foundation of value generation is provider decision making. These decisions, such as diagnoses, treatment selections, admissions, discharges, and referrals, strongly impact hospital resource expenditures, quality, and clinical outcomes—ie, value.

Yet, surprisingly, the process of provider decision making is suffering from the enormous burden of health care complexity. (See Evidence of Performance Gaps in Clinical Decision Making and Conclusions of the Institute of Medicine.) After increasing for decades, medical complexity has accelerated to critically high levels following an upsurge in new information, technologies, and interventions. However, processes for accessing and managing information for clinician decision making have not kept pace.

In other words, provider decision making is value critical, but it is burdened by the information complexity inherent to today’s medicine.

Evidence of Performance Gaps in Clinical Decision Making

Clinical decision errors are consequential and costly.

• The majority of diagnostic error cases are not due to pathology, laboratory, or radiology mistakes but to diagnostic errors in the clinics, where error rates average 15%. These errors include delayed, missed, and inaccurate diagnoses.3

• “Medical diagnoses that are wrong, missed, or delayed make up a large fraction of all medical errors and cause substantial suffering and injury,” writes Mark Graber, professor of medicine at State University of New York Stony Brook.4

• For example, in a study of rapid response teams, 31% of clinical deteriorations at an academic medical center were due to diagnostic and treatment errors.5

• The costs attributable to medical errors in the US in 2008 were estimated to total $19.5 billion, with a $13,000 price tag per error. Medical errors cause between 44,000 and 98,000 deaths annually.6


The clinical decision process often neglects evidence.

• Studies suggest that only 10% to 20% of clinical decisions are based on evidence.1

• Many clinical guidelines are not evidence based. For example, fewer than half of the guidelines for treatment of infectious diseases are based on clinical trials.7

• If providers could deliver care of the quality achieved by the highest- performing state in the US, an estimated 75,000 fewer deaths would have occurred across the country in 2005.1

Clinical decision making misses important information and opportunities.

• Missed follow up: Doctors in the US are failing to follow up on results of up to 62% of laboratory tests and up to 35% of radiology tests. As a result, they are missing critical diagnoses, including cancer, and causing delays in treatments for many conditions.8

• Failure to prevent adverse events: Nearly one in five hospital patients are harmed during a hospital stay, and nearly two-thirds of that harm is preventable.1

• An estimated 4.5 million preventable hospital-acquired conditions occur each year in the US, costing approximately $8.75 billion. An estimated 1.7 million hospital-associated infections lead to about 100,000 deaths.

Conclusions of the Institute of Medicine1

In the September 2012 report, “Best care at lower cost: The path to continuously learning health care in America,” the Institute of Medicine concluded:

• “The complexity of modern health care is reaching levels that challenge human cognitive capacity.”

• “Available evidence often is unused in clinical decision making.”

• “Preventable medical harm is pervasive, despite proven methods for its reduction.”

• “As the pace of knowledge generation accelerates, new approaches are needed to deliver the right information, in a clear and understandable format, to patients and clinicians as they partner to make clinical decisions.”

Health care complexity challenges the clinical decision-making process by impeding clinicians’ abilities to use the optimal information for their decisions. These information complexity challenges primarily fall into three categories (See Figure 1 on following page.):

1. Complexity of processing new clinical evidence

2. Complexity of patient information management

3. Complexity of implementing genomic medicine

College of American Pathologists |7

Figure 1: Modern Medicine’s Complexity Challenges to Clinical Decision Making

SUBOPTIMALDECISION-MAKING

PROCESS

1. Complexity of processing new clinical evidenceProvides overloaded withimmense and changingvolumes of new clinicalevidence, test, andtreatments

2. Complexity of patient information managementOverwhelming patientdata and e-messagessignal to noise problems,lost results, poor infocoordination

3. Complexity of implementing genomic medicineComplexity of genomicmedicine tools/informationexceeds many clinicians’capabilities to use in routine decision making

Figure 1: The clinical decision-making process is suboptimal due to the high levels of complexity in today’s health care. Three areas that particularly impact decision making are excessive volumes of clinical evidence, patient information overload and complexity, and the complexity of implementing genomic medicine.

Challenge 1: Complexity of processing new clinical evidence

The 2012 IOM report concluded that the problem of medical information complexity and overload was one of two reasons that our health care system has not significantly improved its performance over the past decade. The authors assert, “Today in health care, there is more to know, more to manage, and more to do than ever before. The rate at which new scientific knowledge is being produced outstrips the cognitive capacity of even the most adroit clinician to monitor and evaluate effectively.”1

Providers are struggling to keep current with the exponentially growing number of new medical publications and technical advancements for a number of reasons:

• Few providers have the bandwidth to digest their own clinical literature, not to mention the ever-evolving portfolio of new diagnostic tests.

• Genomics and proteomics are transforming medicine, yet the explosion of knowledge and tests surpass clinicians’ abilities to optimally implement them in care delivery.

• The health care system has not yet devised adequate solutions for delivering evidence and patient information to the point of decision making. In fact, most computerized clinical decision support systems are ineffective in improving surrogate patient outcomes.9


The “top-of-license” trend, whereby providers are utilized at their maximum responsibility levels, may exacerbate this problem as nurses and case managers may have greater needs for information support for decisions. The cognitive limits of providers will be pressed even further as the ratio of patients to providers increases with an aging population.

The consequences for hospitals stem from, for example, clinicians’ suboptimal decisions ordering tests, interpreting results, and selecting treatments. Complications, adverse events, and avoidable costs can result from diagnostic and treatment errors.

For example, hyponatremia is mismanaged about one-third of the time because providers do not order the tests that are required to guide treatment. Mismanagement nearly doubles the length of stay in the hospital, leading to higher costs, poor patient experiences, and lost value. (See Section 4 for details.)

Challenge 2: Complexity of patient information management

Providers’ decision making is also challenged by difficulties accessing or attending to patient-specific information needed for decision making, particularly diagnostic test results.

A number of factors are at play here—patient information overload, EHR-driven messaging overload, and test result management and coordination problems.

The volume of patient information providers must manage can be overwhelming. For instance, the IOM reports that an average of 229 doctors is involved in treating a primary care physician’s Medicare patients.1

EHRs and other Health IT systems are not solutions.8,10 In fact, EHRs can exacerbate information overload.

Automation of information and institutional connectivity has facilitated electronic messaging and alerts to clinicians. But those alerts contain both pertinent and less relevant information.

A signal to noise problem results, causing wasted time and mistakes:

• In one study, PCPs received a mean of 56.4 new electronic alerts each day, and spent nearly an hour processing them.11

• In another study, 7% of abnormal laboratory and imaging test result alerts were missed in EHR systems.11

Most health care systems lack processes and procedures for diagnostic test result management and sharing, despite the advent of EHRs. Even in systems with a sophisticated EHR, such as the Veterans Affairs Medical Center, missed test results were a significant problem that impacted outcomes, and e-alerting two providers with test results actually increased errors.12

Current hospital patient information flow is like busy airplane traffic without an air traffic controller. Errors and near misses abound:

• Doctors in the US are failing to follow up on results of up to 62% of laboratory tests and up to 35% of radiology tests. As a result, they are missing critical diagnoses, including cancer, and causing delays in treatments for many conditions.8

10 |College of American Pathologists College of American Pathologists| 9

• “Failure to follow-up on test results occurs frequently in ambulatory settings, and evidence of its impact demonstrates that it is an important patient safety issue, which needs urgent attention.”8

• Nearly one-half of primary care providers had encountered patients with missed diagnostic tests with clinically significant results in the prior two weeks of clinic.13

Coordination of patient information is also problematic. Information can be lost, poorly coordinated, or waylaid during transfers when patients move between providers and care settings:

• About 20% of patients reported that test results or medical records were not transferred from one place to another in time for their appointment.1

• Studies show that about 41% of medical patients leave the hospital with pending laboratory tests, and 9% are sufficiently abnormal to change care, yet most discharge summaries did not include documentation of the pending tests.14

Challenge 3: Complexity of implementing genomic medicine

“Genomic medicine is medical practice driven by genomic information for the care of individual patients, with the goal of improving the quality of care delivered and patient outcomes,” according to Debra G.B. Leonard, MD, PhD, FCAP, professor of pathology and laboratory medicine, Weill Cornell Medical College and Director of the Clinical Laboratories at New York-Presbyterian Hospital.

Genomic medicine, including molecular diagnostic testing, has begun to achieve real clinical advances in care improvement in a number of therapeutic areas. Some of genomic medicine’s most prominent successes to date are in the fields of hematology, oncology, infectious disease, and pharmacogenomics.

Genomic testing generates new types of information that are more potent drivers of high-value decisions. Kathryn A. Teng, MD, and colleagues from the Cleveland Clinic assert: “…True health care reform shifts current health care models from the practice of reactive medicine to the practice of proactive medicine, in which the tools of personalized health care (ie, genetics, genomics, and other molecular diagnostics) enable not only better quality of care but also less expensive care.”15

Specifically, genomic testing can direct decisions that

• Select better treatments and thus improve outcomes,

• Lower the risk of adverse events and complications,

• Reduce avoidable health care spending, and

• Facilitate shared decision making with patients by personalizing alternative treatment choices.

As costs of molecular testing and sequencing continue to fall, many more genomic medicine applications are likely to lower downstream spending.

All signs point to genomic medicine and testing being key enablers of value-based health care.

10 |College of American Pathologists College of American Pathologists| 9

Clinical sequencing has now entered the clinic, and it is projected to follow a rapid adoption curve as sequencing and informatics costs continue to drop over the next few years. New genomic testing applications are being introduced at exponential rates; and while some might not yet be cost-effective, others offer immediate opportunities for value generation.

Yet many providers are not optimally utilizing genomic testing in their clinical decision making. This can be attributed to genomic medicine’s complexity—the advanced and rapidly evolving nature of this field and the consequent provider knowledge gap.

The pace of technology and testing advancement is remarkable. For example, two new genomic diagnostic companies, Sequenta and Adaptive Biotechnologies, have nationally launched clinical sequencing tests that profile a patient’s immune repertoire—either T cells or B cells. Their new testing platform opens up an entirely new field of applications, including therapeutic management for cancer and autoimmune patients.

“The possible applications here are broad. You could, in theory, use such technologies to tell whether multiple sclerosis or rheumatoid arthritis patients are likely to respond to a given therapy. ... Essentially, anybody who studies or treats diseases of the immune system—and that’s a lot of people—could find this sort of technology handy,” writes the national biotech editor of Xconomy.16

The striking point about this new immune profiling technology is the timeline. In one year’s time, the technology concept itself, genomic immune profiling, went from virtually unknown to a clinical launch. Xconomy reports: “At last year’s ASH [American Society of Hematology], hardly anybody had heard of Adaptive or Sequenta or had the foggiest idea what they meant by ‘immune profiling.’”16

With this sort of break-neck pace and technical complexity, it is unreasonable to expect clinicians, without support, to keep sufficiently current with these technologies to employ them clinically.

Nonetheless, value is left on the table when providers fail to implement genomic and molecular testing to optimize their decision making.

College of American Pathologists | 11 12 |College of American Pathologists

Unlocking Value Through Pathology-Supported Decision Making

The pathology/laboratory domain is an untapped and rich source for unlocking decision-making value. Pathology and laboratory services:

• Span all disorders and care settings

• Generate the majority of the information flow that providers need to manage

• Drive precision diagnoses and therapeutic choices

• Provide powerful care and risk management analytics

• Lead the field of genomic medicine

Decades ago pathologists collaborated with their physician colleagues in just these sorts of ways, serving as the “doctor’s doctor.” In 1999 George Lundberg, a pathologist and past editor of JAMA, asserted: “Laboratory directors should make every effort to guide clinicians in appropriate laboratory test ordering, interpretation, and resulting actions.”17

More recently, the emergence of the value-based health care system has led to a new generation of pathology and laboratory services that expand beyond diagnostic test results to provide information services for individual patient management at the point of care. In fact, there is growing evidence for the effectiveness of new types of pathology and laboratory technologies, tests, and services for improving clinical value. (See Section 5 for details.)

By deploying pathologists as decision information experts that partner with clinicians to help optimally inform decisions, hospitals can address complexity challenges and increase the value of their care delivery. This approach is termed pathology-supported decision making.

The different pathology-supported decision-making strategies target one or more of the three information delivery complexity challenges clinicians face (ie, clinical evidence, patient information, and genomic medicine complexity).

Pathology-supported decision-making strategies entail pathologists sharing their expertise with clinicians through one or more of these three information delivery modalities. Pathologists’ knowledge support essentially navigates the clinical complexity for providers and guides them in:

• Selecting the optimal tests, including genomic tests, and treatments.

• Accessing and managing patient test results, ensuring results are not missed.

• Integrating and interpreting results across therapeutic areas and modalities.

• Planning treatment regimens and follow-up.

Pathology-supported decision-making strategies can be implemented using a range of tools and services, spanning hospital IT system applications, institutional programs, and consultative services. (See Figure 2.)

College of American Pathologists | 11 12 |College of American Pathologists

Figure 2: Implementation Categories for Pathology-Supported Decision-Making Strategies

HIT SystemsConsultative

Services

InstitutionalPrograms

• Multicomponent strategies –eg, consultative, HIT systems, instrumentation• Typical – launching new testing capabilities or quality programs

• Moderate complexity and more routine decisions and/or• Clinicians highly experienced with strategy

• High complexity and critial decisions and/or• Early training period for strategy

A particular pathology-supported decision-making strategy might be delivered using one or more of the three types of implementation categories. As shown in Figure 2, each category is particularly well suited to strategies with certain characteristics.

For example, a new decision-making strategy targeting an especially complex area would be best delivered in the early phase through consultative services, but HIT system applications might be included to support the strategy after the first phase. Eventually, after sufficient clinician experience with the decision-making approach, the entire implementation could be based on HIT systems.

Another appropriate match for an HIT systems implementation is a decision-making strategy that can be seamlessly inserted into clinician workflow by modifying existing HIT system content or functionality.

Some decision-making strategies will involve “programs” that involve in-person services, HIT systems, and perhaps instrumentation or laboratory testing. Again, these strategies may need to take a program format only for an initial period of time, later distilling to simpler services or HIT systems for delivery.

Figure 3 provides examples of the types of delivery vehicles that might be used for decision-making strategies.

College of American Pathologists | 13

Figure 3: Example Types of Implementations: Pathology-Supported Decision-Making Strategies

Example Types of Institutional Programs

Example Types ofHIT System Strategies

Example Types of Consultative Services

• Establishment of new polices and procedures to manage information – training programs, services and HIT systems

• Quality programs for point of care lab testing – services and instrumentation

• Establishment of new testing capabilities – training programs, services and HIT systems

• Real–time pathologist e–consults

• Scheduled consults with service lines

• Dedicated pathologist for clinicians in high risk settings

• “Diagnostic Management Teams” – service line specific team partnering

Figure 3: Examples of implementation vehicles for pathology-supported decision-making strategies within each category of the three main categories. “HIT” is health care information technology, “Dx” is diagnostic, “CPOE” is computerized physician order entry, “EHR” is electronic health record, and

“Rx” is therapeutics.

After developing multiple, individual pathology-supported decision-making strategies (P-S D-M), a hospital may move to systematize the P-S D-M creation process, thereby creating an infrastructure for decision-making improvement.

As shown in Figure 4, P-S D-M can be implemented in a continuous improvement cycle whereby a P-S D-M program or service is developed for a newly identified performance problem or value metric, then once it has been implemented and achieved success, the P-S D-M is translated into HIT applications and the pathologist resources are freed for the next problem.

The P-S D-M approach can thus serve as both a systematic method for optimizing the critical function of decision making and a platform strategy for continuously improving performance as market demands dictate.

Figure 4: Pathology-Supported Decision-Making Continuous Improvement Cycle

P–S D–Mimplemented through

HIT systems, freeingpathologist resources

“P–S D–M” / Pathology–Supported

Decision–MakingImprovement Cycle

New proformancetarget or problem

area identified

Develop P–S D–Mprogram or service

in collaboration with clinicians

Decision makingand performance

improvement

P–S D–Mimplemented

—>

—<

—<—<

—<

• New info for existing apps: o Add Dx testing to clinical Pathways

o Add Molecular Dxo CPOE – Dx test tools

• New EHR tools: o Decision–specific Dx test tools o Test algorithms to guide RX o Lab informatics for risk and care management


Generating Value from the Pathology-Supported Decision-Making Strategies

Example pathology-supported decision-making applications from each type of implementation category are presented to illustrate how these strategies address complexity challenges and generate new value. Many of these decision-making strategies are presented in more detail in Section 5.

Implementations Using Institutional Programs

Institutional programs can be used to deliver decision-making strategies that entail multiple components, such as hospital guidelines, quality processes, laboratory testing, and information technology applications.

Institutional programs are ideal vehicles for addressing two of the three primary decision-making complexity challenges:

• Complexity of patient information management

• Complexity of implementing genomic medicine

1. Institutional Program for Patient Test Information Management Complexity

The multiple, interrelated factors underlying patient test information complexity (including patient information overload, EHR-driven messaging overload, and test result management problems) have both human and technology elements, and thus call for a multicomponent solution, including:

• The establishment of “explicit policies, procedures and responsibilities for test follow-up.” The published literature indicates that workflow protocols for testing information are a critical missing ingredient behind mismanaged test results.

• HIT systems to optimize test result access for providers and reinforce the workflow solution.

Pathologists and laboratorians have the ideal experience and knowledge to develop this type of institutional program. This expertise comes from running quality programs in clinical laboratories that establish policies and procedures for clinical laboratory staff. In addition, many have training in quality engineering techniques such as Lean and Six Sigma.

Also, pathologists can leverage their laboratory information systems to provide monitoring and management services, such as monitoring for missed abnormal results, missed follow-ups, pending tests, undelivered results, and so on. (See Case Example: Test Information Management.)

Program benefits would include streamlined test information flow, corrected signal to noise EHR issues, tracking mechanisms to minimize lost test results, and greater efficiency throughout the system.

College of American Pathologists |15 16 | College of American Pathologists

Case Example: Test Information Management

Terrence Dolan, MD, president of the Regional Medical Laboratory at St. John Health System in Tulsa, Oklahoma, is employing data warehousing as an information management center to solve the information overload problem in several ways. A data warehouse is a central repository of data that is created by integrating data from multiple disparate sources.

• Data warehousing allows his group to gather all of a patient’s information, analyze it, and present physicians with the actionable information.

• This information control system also allows his laboratory to provide laboratory exception reporting by reviewing patient data, picking out the information that is crucial to outcomes according to the physician, and sending the physician periodic lists containing critical information, which decreases the risk of missed results.

• Data monitoring and analytics from the warehouse also give pathologists a window into the patient’s condition, allowing the pathologist to direct and optimize the workup of some patient problems, such as endocrinology.

2. Institutional Programs for Genomic Medicine Complexity

Decision-making strategies addressing genomic medicine complexity may call for a new, broad institutional genomic capability requiring new technology, new HIT applications, and staff training.

Two examples are:

1. Pharmacogenomics for adverse drug event prevention

2. Rapid/near-care inpatient molecular testing to guide infectious disease therapy

An approach to integrating pharmacogenetic (PGx) prescribing into the clinical workflow, termed preemptive pharmacogenetics, can help reduce the rate of adverse events in a cost effective way by sequencing patients’ genetic variations before medications are prescribed and entering that information into EHRs. (See the Vanderbilt case study, Case Example: Preemptive Pharmacogenetics.)

Case Example: Preemptive Pharmacogenetics

For example, Vanderbilt University instituted a preemptive pharmacogenetic screening program that performs a one-time test of patients for a set of pharmacogenetic variants—now possible with modern genotyping technology—and gives providers easy access to results through electronic medical records. The program has the potential to change drug-prescribing behavior and significantly reduce adverse drug events.

The initial program focused on six medications (adverse effects): abacavir (skin/mucosal hypersensitivity), azathioprine (myelosuppression), clopidogrel (lack of efficacy to prevent major cardiovascular events, ie, myocardial infarction, stroke, or death), simvastatin (myopathy), tamoxifen (breast cancer recurrence), and warfarin (bleeding).

Researchers estimated that 64.8% of patients at Vanderbilt were exposed to at least one medication with a pharmacogenetic (PG) association. “With the plummeting costs of genomic testing, which could soon reach $100 for sets of common PG variants, such a program could prove to be highly cost effective in addition to benefiting patients.”18

16 | College of American Pathologists

As will be described further in Section 5, the potential value available with an effective rapid molecular testing program enabling clinicians to select antibiotics more precisely is substantial. This value will only increase as the molecular assays continue to increase in performance and decrease in costs. (See Spotlight.)

Spotlight: Step Change in Value: Molecular Infectious Testing

Pathology-supported decision strategy = near-point of care molecular testing

The new availability of this rapid, molecular infectious testing is significantly advancing treatment from empirical to pathogen identification-based antibiotic selection. The results are a step change increase in value with better clinical outcomes, shorter length of stay, lower costs.

Many payer value programs involve avoiding hospital-based infectious diseases: pneumonia readmissions, hospital-acquired conditions, health care-associated infections, and Prometheus payment for bundling. A significant share of avoidable costs involves infections.

Standard of care involves empirically selecting antibiotics. Cultures take too long to drive prescribing decisions, so antibiotics are chosen without knowing the precise identity of the pathogens. But this one-size-fits-all approach doesn’t work:

• The initial course of antibiotics fails frequently and can lead to complications.

• Inappropriate antibiotics can lead to higher resistance rates.

• Inappropriately treated infections increase the length of stay, rates of complications, and mortality.

Molecular testing for infectious organisms now has a turn-around time of a few hours, allowing it to guide prescriptions in any setting. (See Table 5.)

• “Awareness of pathogen identification via molecular analysis was almost three times more likely to change therapy to a more microbial-specific antibiotic (broader coverage or narrower spectrum) than empiric guidelines.”19

• One investigation that compared standard of care antibiotic selection to molecular diagnostic-guided selection for bacteremia found that the antibiotic regimen would have been changed with the molecular testing in 77% of patients.19

• A thorough literature review and economic, cost-effectiveness modeling of molecular testing for methicillin-resistant Staphylococcus aureus versus conventional techniques concluded that molecular testing was overall less expensive.20

• The Ohio State University Medical Center found that using rapid molecular testing for Staphylococcus aureus bacteremia produced a significant reduction in mean hospital costs by $21,387, a 30% drop.21

This represents a step change in improvement in clinical performance, reduction in costs, and generation of value. Hospitals that want to be at the leading edge of this movement need their pathologists to select the tests and instruments, perform training, and manage an institutional program that includes molecular testing.

College of American Pathologists |17

Figure 5 describes how an institutional program implementing a rapid molecular testing strategy can generate value by improving decision making.

Figure 5: Meningitis in the ER: Generating Value With a Pathology-Supported Institutional Program for Rapid Molecular Testing

• Enables clinicians to avoid unnecessary admissions of viral meningitis cases.• Estimated 59% reduction in viral meningitis admissions.

• Traditional lab tests to differentiate viral from bacterial meningitis take too long (days) or do not always differentiate.• Molecular tests are now rapid enough (2 hours or less) and inexpensive enough to use in the ER.

Pathology–SupportedApproach:Employ rapid near-caremolecular tests to differentiateviral form bacterial meningitis

Decision

Value Generated

• Whether or not to admit meningitis cases from the Emergency Room.

Implementations Using HIT Systems

A number of HIT platforms and applications can be used to deploy pathology-supported decision-making strategies. In all cases, the new decision-making process would be developed through pathologist-clinician collaboration.

With properly designed functionality, HIT systems such as EHRs and related applications provide an excellent platform for optimizing clinician decision-making information. The benefits include:

• HIT systems are already part of most providers’ workflow, so new approaches can seamlessly integrate.

• HIT systems supply much of the information providers rely on for decision making, so solutions can act at the root of problems.

• HIT applications can be scaled to reach providers across an institution, can be frequently updated as new evidence emerges, and can be easily customized for different specialties and particular decisions.

• HIT systems offer advanced functions important for some decisions, such as rapid information transfer, real-time algorithmic analytics, and graphic visualization.

18 |College of American Pathologists

Figure 6 describes how an HIT system implementation can generate value by improving decision making.

Figure 6: Venous Thromboembolism (VTE) Prevention: Generating Value With Computerized Physician Order Entry (CPOE)

Complexity Challenge

Decision

Pathology-SupportedApproach:Electronic lab test orderingtools for assessing risk of VTE

• Whether to administer venous thrombo-embolism (VTE) prevention therapies.

Generated Value• Hospitals implementing this type of strategy averaged a 21% reduction in VTEs.

• VTE prevention has been proven effective but at-risk patients don’t always receive prophylaxis because of the complexities of decision-making.

• The tool can also provide risk algorithms to guide interventions.• Pathologist keeps VTE tool current based on latest evidence and newest tests.

Implementations Using Consultative Services

Consultative services by pathologists, provided alone or in partnership with clinical colleagues, are a potent form of delivery for decision-making strategies. In-person partnering is particularly important for decisions that are diagnostically and/or therapeutically complex, as reflected by high error rates, for example, or for which the clinical consequences of an error are very high.

Pathologists may also leverage their laboratory test data, many times in conjunction with clinical and pharmacy data, to produce valuable predictive and precision medicine tools. (See Pathologist Case Example: Population-Generated, Personalized Test Reference Ranges and Pathologist Case Example: Finding Time Bombs With Laboratory Information System [LIS] Analysis.)

Other examples of decision-making strategies implemented as consultative services involve pathologists serving as regular resources with clinicians at the point of care. For example:

• Diagnostic specialty teams led by pathologists—See “Pathologist Case Example: Demonstrated Value of Diagnostic Management Teams”

• Rounding in the ER or ICU—See Figure 7: Managing Hyponatremia: Generating Value With Consultative Services


Pathologist Case Example: Population-Generated, Personalized Test Reference Ranges

A data warehouse consolidates information from sources across the hospital into a single database that can be queried to extract crucial information. Data warehousing also allows for population-based analysis to generate more personalized reference ranges.

“By using sophisticated IT tools such as data warehousing, we have an opportunity to change health care processes to improve outcomes, decrease unnecessary cost, and minimize errors in health care,” says Dolan.22

• Dolan and colleagues used a database of nearly 500,000, a larger patient cohort than that used to determine standard ranges, to generate age and gender-specific reference ranges for laboratory tests.

• Applying these more specific ranges and other probabilistic analyses enables Dolan’s laboratories to reduce false-positives tests, which can create unnecessary imaging procedures.

“By developing probabilities, by the analysis of multiple test results, we will be able to give the physician more actionable information and thus make a better determination of how extensively an abnormal result should be evaluated,” explains Dolan.22

Pathologist Case Example: Finding Time Bombs With Laboratory Information System (LIS) Analysis

Philip Chen, MD, PhD, a pathologist at University of Miami, analyzes his laboratory information system (LIS) to identify high-risk diabetics based on longitudinal test results. He found that 3% of the population each year went from the low spending groups to the highest spending group.

In other words, the 5% highest spending patients are not all chronically high spenders. This presents an opportunity for a laboratory to develop analytics to help identify these 3%, high-risk, “time bombs.”23 He has found these time bombs to frequently be poorly managed diabetics who go on to have myocardial infarctions.

Pathologist Case Example: Demonstrated Value of Diagnostic Management Teams

Michael Laposata, MD, PhD, FCAP, a pathologist at Vanderbilt University Medical Center, has been providing diagnostic management team services to various hospital service lines for a number of years. The diagnostic management teams assist clinicians in selecting diagnostic tests, and also deliver expert-driven, patient-specific, narrative interpretations of tests to improve diagnostic accuracy and support therapeutic recommendations.

A recent economic study at Vanderbilt found that the improvements in diagnostic accuracy resulting from the coagulation diagnostic management team produced a decrease in average length of stay from three to two days for pulmonary embolism cases.24


Figure 7: Managing Hyponatremia: Generating Value With Consultative Services

Complexity Challenge

Decision

Pathology-SupportedDecision Making:Diagnostic specialty teams

• Selecting appropriate treatment for hyponatremia based on its origin.

Generated Value• Appropriate and informed management of hyponatremia could yield a 50% reduction in bed days.

• Doctors offen don’t order tests that determine volume status, a key diagnostic, and thus choose inappropriate treatments.

• Diagnostic expert teams (led by pathologists) provide test ordering guidance, interpretation and treatment selection.• Consulting teams routinely consult on patients to manage hyponatremia.


Estimating Value Generation From Pathology-Supported Decision-Making Strategies: Hospital Examples

How much value can these pathology-supported decision-making examples unlock?

This section continues the descriptions of many of the decision-making examples from the last section, with an added dimension of estimating the value that can be generated, based on peer-reviewed, published evidence. (See Table 4.1.)

The example hospital settings/service areas were selected because they are of relatively high strategic interest and high value to hospitals. They include the emergency room, surgery, intensive care unit (ICU), readmissions, and hospital-acquired conditions.

The pathology-supported tests and services are all evidence based, though some are still quite new and in an early stage of adoption, so implementing them in a hospital is likely to generate additional value to the baseline. Many of these services are already being used by innovative hospitals in some manner.

These are only a selected sample of examples. As such, they do not represent the full potential value of pathology-supported decision-making approaches for hospitals. There are many other examples and service areas that can be implemented.

Table 4.1: Selected Examples of Pathology-Supported Decision-Making Strategies*

Emergency Room

Surgery Intensive Care Unit

CMS Readmissions and Hospital-Acquired Conditions

Sepsis: rapid molecular point of care testing to guide antibiotic selection:

36% reduction in sepsis costs.

For 200-400 bed hospitals, potential $5 million in savings.

Surgical Site Infections: Presurgical screening and prophylaxis + quality program to improve glycemic control:

32%t total reduction in surgical site infections.

For 350–500 bed hospitals, potential

$825,000 + $650,000= ~$1.5 million in savings.

Hyponatremia: patient-risk identification and management:

50% reduction in costs for hyponatremia cases that have declining sodium during hospital stay (occurs in 3.5% of hospital patients).

Estimated per hyponatremia case savings ~$5,800.

For 400 bed hospitals, total annual savings could be $2.4 million.

Pneumonia Readmissions:

1. Pathogen surveillance program:

21% reduction in health care-associated pneumonia costs.

For hospitals with ~350–500 beds, this might yield ~$450,000 in annual savings.

2. Molecular point of care testing to guide antibiotic selection:

22% reduction in pneumonia readmission cases.

For 500+ bed size hospitals, this might save $550,000 annually.

22 | College of American Pathologists

Meningitis: rapid molecular testing to identify viral meningitis:

59% reduction in unnecessary viral meningitis admissions.

Average cost of viral meningitis stay is $8,360.

Blood Product Utilization: utilization management and transfusion consulting services:

15% to 25% reduction in blood product costs.

For nongovernment, acute care hospitals, one study estimates $1.06 million average annual savings per hospital.

Acute Renal Failure: biomarker for early detection and nephrologist intervention:

~32% reduction in hospital Acute Renal Failure cases.

For 350–500 bed hospitals, this might represent a $7.5 million cost savings.

Acute Myocardial Infarction and Congestive Heart Failure Readmissions:

27% readmissions due to avoidable compli-cations and infections – significant reduction in infections with molecular testing.

Pneumonia: biomarkers reduce diagnostic errors:

59% reduction in:

• ER admissions incorrectly diagnosed pneumonia

• Pneumonia cases with delays in correct diagnosis and lower profits

• Misdiagnosed pneumnia patients with adverse events

Venous Thromboembolic Embolism: automated laboratory testing tools:

21% reduction in preventable venous thromboembolisms.

For 300–450 bed hospitals, this could represent ~$580,000 in annual savings.

Hospital-Acquired Catheter Urinary Tract Infection: Molecular point of care testing to guide antibiotic selection:

17% reduction in hospital Urinary Tract Infection (UTI) costs.

Based on one cost estimate, this might yield ~$400 per patient savings.

*Dollar estimates of cost savings/value yields are generally gross savings, not net – ie, they do not include the costs of additional laboratory testing or other incremental resources. However, in comparison to the magnitude of the hospital savings yields, the laboratory testing costs are typically relatively minor. Costs are direct hospital costs, not charges.

Emergency Room

Surgery Intensive Care Unit

CMS Readmissions and Hospital-Acquired Conditions


Service Area: Emergency Room

Hospitals that want to reduce hospital costs and avoidable admissions through improved emergency room (ER) decisions need their pathologists to provide rapid testing for conditions with high-stakes value.

Two of the most prominent areas for pathology improvement in ER decision making are:

Providing information to prevent diagnostic errors. ER diagnostic errors are a significant source of return ER visits. Approximately 20% of unscheduled return visits to the ER within 72 hours of discharge stem back to mistaken ER diagnoses.25

This misdiagnosis can result when ER providers do not have the information needed to make the correct diagnoses or when ER providers are so swamped with ancillary information that they miss key results.

Rapid molecular testing to guide infectious disease management. Rapid molecular testing can help triage infectious disease and select appropriate antibiotics. This technology is advancing so rapidly that the cost and usability of these instruments will make point-of-care infectious molecular testing practical for a wide range of tests in the near future. (See Pathologist Case Example: Rapid Point-of-Care Molecular Testing.)

Table 4.2: Examples of Pathology-Supported Decision-Making for the Emergency Room

See Appendix 1 for more details and references.

Sepsis

Average 36% reduction in sepsis costs by shortening hospital stays.

Average cost for septicemia stay at 200–400 bed hospitals is $22,000.

Potential savings for 200–400 bed savings estimated at $5 milllion.

Pathology-Supported Approach: Rapid molecular pathogen analysis to guide antibiotic selection.

• Blood-stream culture results take days, so doctors prescribe broad-spectrum “empiric” antibiotics.

• Empiric antibiotics don’t work for one in three patients, raising mortality rates, costs and resistant pathogens.

• Given that infections that are difficult to treat can increase hospital costs by 26% due to longer hospital stays, providers need rapid molecular pathogen analysis.

• Two studies, one from Ohio State University and the other from The Methodist Hospital in Houston, reported significantly decreased hospital costs using rapid molecular testing in septicemia —30% and 43%, respectively, representing $21,000 and $19,000 per patient in savings.

• Hospitals with 200–400 beds might generate $5 million annually using this intervention


Meningitis

59% reduction in unnecessary viral meningitis admissions.

Average cost of a viral meningitis stay in 2012 is ~$8,360.

Pathology-Supported Approach: Rapid molecular testing to identify viral meningitis within two to four hours.

• Patients are often admitted through the ER for viral meningitis, even though they would recover on their own within seven to 10 days.

• Safety necessitates admission because it takes four to 10 days for a Cerebrospinal fluid culture to differentiate viral from bacterial meningitis, which requires early admission and antibiotics.

• Given that approximately 80% of meningitis cases in the ER are viral, providers need rapid identification of viral meningitis.

Rapid identification of a viral pathogen using molecular testing can reduce unnecessary viral meningitis admissions by 59%.

Pneumonia

59% reduction in:

* ER admissions incorrectly diagnosed pneumonia

* Cases with poor profit margins due to delays in correct diagnosis

* Patients with adverse events due to delayed treatment or unnecessary antibiotics

Pathology-Supported Approach: Biomarker testing to support differential diagnosis of pneumonia in the ER.

• ER doctors misdiagnose pneumonia ~30% of the time, failing to differentiate it from COPD, heart failure, or many other conditions.

• Most of these alternative diagnoses do not require antibiotics, and antibiotics can lead to adverse events, resistant organisms, and unnecessary spending.

• Admissions with incorrect pneumonia diagnoses receive unnecessary antibiotics:

o 25% experience a delay (at least 24 hours) in receiving the right diagnosis

o 4% experience adverse events from the antibiotics

o 4% morbidity or mortality from delay in diagnosis or treatment

• ER doctors need biomarker informing services that improve diagnostic accuracy, such as procalcitonin and CRP. These biomarkers can help reduce the pneumonia error rate for at least 59% of pneumonia cases misdiagnosed as other conditions.27

Pathologist Case Example: Rapid Point-of-Care Molecular Testing

Between 2008 and 2010, a health system in Marseille, France, demonstrated the feasibility of a rapid response, near point-of-care molecular testing laboratory located near an emergency room designed to support infectious disease management decisions.28 They found the molecular point-of-care laboratory to be very successful, providing benefits such as:

• Reduced mean length of stay of viral meningitis patients over 15 years old by 52% compared to years before the laboratory was established.

• Guided antibiotic therapy for the 50% of bacterial meningitis patients whose cultures were negative.

• Patients who received point of care tests were immediately discharged nearly three times as often as those who received conventional tests.

The authors concluded, “This strategy might represent a major evolution of decision making regarding the management of infectious diseases and patient care.”28


Service Area: Surgery

Hospitals that want to decrease surgical site infections, surgical venous thromboembolisms, and blood product costs need targeted programs that comprise pathology-supported decision-making tools and services. (See Table 4.3.)

The range of pathology-supported decision-making strategies includes:

• The application of pathologists’ expertise in quality control

• Implementation of pathogen surveillance and eradication programs

• Protocols for blood product usage

• Clinical decision support to guide prevention of complications such as thromboembolic events and infections

Table 4.3: Examples of Pathology-Supported Decision-Making Strategies for Surgery


Surgical Site Infections

32% reduction in surgical site infections (SSIs).

Each SSI adds ~$20,800 in costs, and 9.7 hospital days, on average.

For hospitals with 350–500 beds, the potential total savings represented by these solutions might be $1.5 million annually.

Pathology-Supported Approach: Advanced microbiology services to identify Staph carriers.

• Estimated 30% of surgical site infections (SSIs) from Staphylococcus aureus bacteria.

• Nasal screening and prophylactic treatment with an inexpensive drug clears most Staph and reduces drug-resistant Staph (MRSA) infections by 60%.

• Surgeons need diagnostics to identify patients who need presurgical prophylaxis to prevent MRSA among health care-associated infections.

• Prophylaxis among at-risk patients reduces MRSA SSIs for an 18% reduction in overall SSIs.

• On average, SSIs extend length of stay by 9.7 days while increasing cost by $20,842 per admission.

• Hospitals with 350-500 beds could save about $825,000 annually.

Pathology-Supported Approach: Pathologist-directed quality program for glucose monitoring.

• About 46% of patients with surgical site infections (SSIs) have elevated glucose.

• Keeping glucose in a restricted range reduces SSIs by 30%.

• Most handheld-glucose monitors aren’t accurate enough for tight control.

• High-quality diagnostic glucose monitoring in surgical units can reduce SSIs among at-risk patients for a 14% reduction in SSIs.

• Hospitals with 350-500 beds could save about $650,000 annually.


Blood Products

15% to 25% reduction in blood product usage.

For nongovernment, acute care hospitals, the average savings might be $1.06 million annually.

Pathology-Supported Approach: A pathologist-directed multidisciplinary blood utilization management program.

• Physician decisions about blood transfusions are typically subjective and tremendous variation in utilization exists.

• Unnecessary use of blood products and inappropriate transfusion orders result in significant waste of hospital resources.

• Each unit of RBC increases the risk of:

o nosocomial infection by 50%

o hospital bed days by 16% to 32%

• Blood utilization management programs typically reduce blood product usage 15% to 25%.

The Premier healthcare alliance conducted a study of blood product utilization variations at 464 hospitals across the country. The study found that if hospitals were able to perform equivalently to the top quartile, they would save on average $1.06 million annually.

Venous Thromboembolism

21% reduction in preventable venous thromboembolisms.

Average inpatiet cost of a VTE is about $9,000.

For 350–500 bed hospitals, this intervention could-represent ~$585,000 in annual savings.

Pathology-Supported Approach: Clinical decision support tools to automate venous thromboembolism (VTE) prophylaxis in surgical settings.

• Many at-risk patients receive suboptimal or no VTE prophylaxis, in some cases because of the complexity of the risk-benefit profiles of anti-coagulants.

• Clinicians need help assessing VTE risk and determining the best prophylaxis strategy, both of which can be greatly supported by specialized laboratory testing services.

• Electronic lab ordering support tools have shown a 21% reduction in hospital-acquired VTE events.

For hospitals with 300–450 beds, this intervention might avoid 64 VTEs annually. Given a cost of $9,130, this represents potential savings of $587K annually.


Service Area: Intensive Care Unit

Hospitals that need support in the Intensive Care Unit (ICU) to prevent complications and reduce length of stay need their pathologists to provide tools and services that bring diagnostic intelligence closer to clinicians. (See Table 4.4.)

The range of pathology-supported ICU services includes:

• Decision support systems that apply the latest biomarker research to support early intervention, such as acute renal failure

• Testing algorithms and expert interpretations to manage complicated conditions, such as fluid and electrolyte imbalances

• Quality control programs for critical but routine testing, such as glycemic management

• Molecular testing services to diagnose and treat infections

Table 4.4: Examples of Pathology-Supported Decision-Making Strategies for the Intensive Care Unit


Hyponatremia

50% reduction in costs for hyponatremia cases that has declining sodium during hospital stay (occurs in 3.5% of hospital patients).

Estimated per hyponatremia case savings ~$5,800.

For 400 bed hospitals, total annual savings could be $2.4 million.

Pathology-Supported Approach: Diagnostic testing decision support, electronic medical record tools and diagnostic management teams to aid understanding, management and treatment of hyponatremia.

• Clinically significant hyponatremia can extend length of stay by 42%, yet it is mismanaged or misdiagnosed over a third of the time.

• One mistake is a failure to order tests that determine a patient’s volume status, required information for treatment decisions.

• Pathology-supported decision-making could prevent these cases of hyponatremia mismanagement and yield a 50% reduction in bed days.

Acute Renal Failure

~32% reduction in hospital acute renal failure (AKI) cases.

For 350–500 bed hospitals, this might represent a $7.5 million cost savings.

Pathology-Supported Approach: Pathologist-led clinical decision support tools and expert consults to identify the need for early nephrologist intervention.

• Conventional testing methods diagnose acute kidney injury (AKI) too late.

• A new biomarker, NGAL, detected early acute kidney injury in 43% of patients who would otherwise have been missed, allowing early intervention.

• Early nephrologist intervention reduces progression to acute renal failure by 74%, resulting in a 32% reduction in late stage hospital acute renal failure/AKI cases.

• A study that estimated hospital costs by severity of AKI stage found a difference of $26,000 in 2012 dollars between early and late AKI stages.

• Based on these findings, for 350-500 bed hospitals this might generate $7.5 million in savings.


Reimbursement Area: Medicare Readmissions and Hospital-Acquired Conditions

Hospitals that want to lower readmission rates, avoid hospital-acquired conditions (HACs), and raise their institution’s quality performance level need their pathologists to provide a range of partnered decision-making strategies, the most important of which may be personalized, molecular testing for infectious conditions. (See Table 4.5.)

Table 4.5: Examples of Pathology-Supported Decision-Making Strategies for Medicare Readmissions and Hospital-Acquired Conditions


Readmissions:Drug-Resistant Pneumonia

21% decrease in overall hospital-acquired pneumonia (HAP) cases/costs.

This represents a potential savings of ~$2,300 per HAP case.

For hospitals with ~350–500 beds, this might yield ~$415,000 in annual savings.

Pathology-Supported Approach: Pathologist-directed pathogen surveillance program to prevent MRSA infections and reduce length of stay and poor outcomes.

• Two-thirds of pneumonia cases are hospital associated (HAP), and 47% of these are caused by methicillin-resistant staph (MRSA).

• MRSA HAPs have worse outcomes, higher costs and longer length of stay.

• Active surveillance cultures have been shown to decrease MRSA HAPs by 67%, resulting in a potential 21% decrease in overall hospital-acquired pneumonia costs.

Readmissions:Inappropriate Treatment of Pneumonia

22% decrease in pneumonia 30-day readmissions, based on rapid prescribing of targeted antibiotics.

For 500 bed hospitals, the potential savings is estimated to be $550,000 annually.

Pathology-Supported Approach: Rapid molecular pathogen identification for directing antibiotics can improve outcomes and reduce length of stay and resistance rates.

• Pneumonia treatment failures are an independent, significant predictor of pneumonia readmissions.

• Between 20% and 36% of 30-day pneumonia readmissions are due to pneumonia-related causes, most of which are treatment failures.

• Also, 23% of hospital pneumonia patients do not receive appropriate antibiotics within 24 hours of hospitalization.

• Rapid molecular testing has been shown to change clinicians’ antibiotics selection in pneumonia cases in 77% of cases.

• Immediate and informed antibiotic selection using rapid molecular diagnostic testing services could reduce pneumonia readmissions by 22%.

For 500 bed hospitals, the potential savings is estimated to be $550,000 annually.


Readmissions:Acute Myocardial Infarction and Congestive Heart Failure

27% readmissions due to avoidable complications and infections—many preventable with pathology-supported decision making.

• Among acute myocardial infarction and congestive heart failure 30-day readmissions, 27% to 28% are due to complications and infections - according to an analysis of an extensive database of 62,768 all-cause admissions to 44 acute care facilities in Pennsylvania.

• Many of these complications and infections can likely be prevented or lessened in severity through the pathology-supported decision-making described herein.

Health Care-Acquired Conditions:Urinary Tract Infections

17% reduction in hospital Urinary Tract Infection costs.

Based on one cost estimate, this might yield ~$400 per hospital UTI case in savings.

Pathology-Supported Approach: Molecular point of care testing to id pathogens, plus frequent antibiograms to guide antibiotic selection.

• Even though empiric antibiotics are ineffective in about 70% of urinary tract infection (UTI) cases, providers still must prescribe them during the 48-hour wait for culture results.

• Real-time molecular diagnostic tools can identify pathogens in four to five hours, allowing treatment decisions to be made based on pathogen specific information.

• Inappropriate antibiotics can increase costs by 24% by contributing to length of stay, for example.

• Choosing the right drugs for the inappropriately treated UTI cases using rapid molecular testing can result in a 17% reduction in costs.

Infectious Diseases: A Value Opportunity

The Centers for Medicare & Medicaid Services (CMS) value programs include 30-day readmissions and HACs.

One significant driver of both is infectious conditions:

• One of the three readmission diagnoses is pneumonia;

• HACs include catheter-associated urinary tract infection, vascular catheter-associated infection, surgical site infections, and Stage III and IV pressure ulcers, which are often chronically infected;

• Health care-associated infection (HAI) measures are reported to CMS and published on its public Hospital Compare website;

• Infectious complications comprise a significant share of the potentially avoidable costs (PACs) in the Prometheus payment model applied to a commercially insured population. PACs will represent the profit margin in CMS bundling programs when Prometheus completes implementation and CMS rolls them out.

These infectious disorders offer an unprecedented opportunity to capture new value, led by pathology and lab medicine and driven by molecular diagnostic testing. (See Section 4: Spotlight: Step Change in Value)


Hospital-Acquired Conditions: Stopping Value Loss

In addition, CMS has paid either nothing or reduced rates for a number of HACs. Pathology-supported strategies have the potential to positively influence value in eight of 11 HACs. (See Pathology-Supported Decision-Making Strategies for Hospital-Acquired Conditions.)

Pathology-Supported Decision-Making Strategies for Hospital-Acquired Conditions

Blood incompatibility: Services for improved blood utilization and consultations. (See Table 5.)

Stage III and IV ulcers: Molecular diagnostic testing prior to Stage III ulcers can detect chronic infections, identify biofilm pathogens, and guide treatment. Treating infections in ulcers has been shown to significantly accelerate healing, and molecular testing has been demonstrated to be far more effective than cultures for identifying pathogens when biofilms are present.

Catheter-associated urinary tract infection: Molecular testing and surveillance programs can lower rates of resistant pathogens, reducing costs. (See Table 5.)

Vascular catheter-associated infection: Molecular testing and surveillance programs can lower rates of resistant pathogens, reducing costs.

Poor glycemic control: Programs to correct inaccurate testing instruments and procedures for bedside glucose readings can provide tighter, more reliable controls. (See Table 3.)

Surgical site infections: Improved glycemic control and staph nasal screening and treatment. (See Table 3.)

VTE: Computer laboratory test ordering tools for prophylaxis. (See Table 3.)

Acute Renal Failure: New biomarker NGAL for pre-acute renal failure detection and nephrologist intervention arrests progression. (See Table 4.)

Focus on Prometheus Potentially Avoidable Costs

The College of American Pathologists performed a study that employed the Health Care Incentives Improvement Institute’s Prometheus bundled payment methodology29 and extensive literature reviews to assess the contributions pathology and laboratory services can make to reduce PACs.

The results indicated that new pathology and laboratory tests and services could reduce the target PACs by 30%, thus driving the generation of a 30% value increase. (LE Herriman, College of American Pathologists, unpublished data, September 2012)

The study:

• Used the Prometheus database, which covers a commercially insured population of 4.7 million adults.

• Analyzed PACs from 21 episodes of care across chronic and acute conditions as well as inpatient and outpatient procedures.

• Identified pathology-partnered tests and services in the peer-reviewed literature that had evidence of reducing PACs.

• Calculated percentage cost reductions that could be achieved through implementation of these solutions for various PAC categories.

Based on these findings, there are ample opportunities for pathology-supported decision-making strategies to reduce avoidable costs of care and, in turn, generate substantial value.


Conclusions

A lot rests on a hospital provider’s clinical decisions. In aggregate, they determine the hospital’s cost and quality performance. As the market continues to evolve toward value-based payments, optimizing the decision-making process will grow more critical.

Yet both our health care system and medicine have become so complex that the traditional decision-making process is strained, despite (and sometimes because of) the use of computer system support. Consider these statistics from the Institute of Medicine:1

• “The pace of research now averages 75 trials and 11 systematic reviews of trials per day (Bastian et al., 2010). The pace at which new knowledge is produced outstrips the ability of any individual clinician to read, remember, and manage information that could inform clinical practice.”

• Community physicians interact with as many as 229 other physicians in 117 different practices just for their Medicare patient population.

• ICU clinicians have 180 activities per patient per day.

• An estimated 21+ hours per day would be needed for a primary care clinician to meet all acute and preventive care recommendations for a panel of patients.

The IOM researchers summed it up well: “[T]he current complexity of clinical decision making challenges human cognitive capacity to manage information.”

These problems are clearly multidimensional in etiology, so a number of approaches might be taken to reengineering clinical decision making.

This paper introduces one such approach, Pathology-Supported Decision Making, which has demonstrated efficacy in improving decision making and generating value at a number of institutions and for multiple clinical decisions. The pathology-supported decision-making strategy provides clinicians with direct, point-of-care access to pathologists’ expertise, information, and technologies.

With pathologists’ breadth of diagnostic expertise, experience with quality systems engineering in clinical laboratories, centrality in genomic medicine, and readiness for “big data” applications via data warehousing, this strategy can address the multiple sources of complexity that are challenging decision making.

For instance:

• Addressing clinical evidence complexity — Pathologists apply their diagnostic knowledge base and technology resources to focus clinicians on the most current testing and interpretive algorithms for complex cases, such as hyponatremia or renal failure in the ICU.


• Addressing patient information complexity — Pathologists apply systems engineering techniques to develop new protocols, policies, and HIT applications for managing diagnostic test information workflow. This workflow simplifies the patient test result complexity and decreases errors.

• Addressing genomic medicine complexity — Pathologists introduce state-of-the art molecular and genomic testing for clinical decisions that are optimized by personalized medical guidance.

Given the degree to which the clinical decision-making process has been impaired by the overwhelming and multidimensional complexities of our health care system, optimized decision making can release substantial magnitudes of value.

Innovative hospital leaders are working with their pathologist groups to develop and implement these new pathology-supported decision-making approaches. For example, Vanderbilt University Medical Center has pathology-led initiatives termed diagnostic management teams (DMTs) that support clinicians in testing, diagnoses and treatment plans.24 These DMTs result in earlier diagnoses, fewer errors, more appropriate treatments, lower costs, and shorter lengths of stay. The results have been so impressive that Vanderbilt is rolling out DMTs across all service lines in the hospital.

The examples provided in this report are not an exhaustive list of services. They do not represent the full potential value of this decision-making strategy, but rather a selected sampling of new, evidence-based services that can generate significant value for hospitals. Since developing pathology-supported decision-making interventions to optimize the decision process is a new strategy, it may at first appear to be a piecemeal collection of opportunities for incremental value generation.

Instead, hospital leaders might view a strategy based on pathology-supported decision making as a value–generating engine for their institution in the long term.

This strategy not only generates near-term value, but also provides a means for continuous improvement as performance metrics rise and deficiencies are identified. This long-term view is essential as the emerging, value-based health care system is continuously raising the bar on quality and cost performance.


Appendices

Appendix 1: Evidence of Value Returns From Pathology-Informed Decisions: Emergency Room Decisions

Sepsis

Size of the problem: Thirty-four percent of hospital-acquired sepsis cases initially receive inadequate empiric antibiotics. Research has shown that the strongest survival predictor in sepsis is the time to initiation of effective antimicrobial therapy, with each hour of delay associated with a decrease survival of 7.6%. 30 However, selecting an effective antibiotic regimen in an emergent situation without knowing the identity of the pathogen, which is the state of current practice, is difficult and faulty, especially given today’s high rates of resistant organisms.

The Crux: Rapid molecular testing in septicemia can guide physicians to more appropriate initial antibiotic therapy. “Awareness of pathogen identification via molecular analysis was almost three times more likely to change therapy to a more microbial-specific antibiotic (broader coverage or narrower spectrum) than empiric guidelines. … The most important finding from this study is that therapy would remain the same in only 23% of patients, had the organism identification been known to Emergency Physicians.” 19

Appropriate initial antibiotics can improve survival and decrease length of stay, resulting in hospital cost savings.

Potential Value of Pathology-Supported Solution:

Pathology value services –

• Utilize rapid molecular testing to identify the pathogen and where possible resistance status

• Send these results stat to clinicians for antibiotic regimen guidance

Rapid detection of pathogens using molecular diagnostics resulted in shorter lengths of stay by 6.2 days and hospital costs reduced by $21,387 in a study at the Ohio State University Medical Center.21

Methodist Hospital study31 using Mass Spec for rapid pathogen testing of bacteremia cases found a significant reduction in LOS of 2.6 days, and a mean 43% decrease in hospital costs, of $19,547 per patients (direct hospital costs).

• Total impact = average of two studies reduction in hospital costs = (30+43)/2 = 36% average reduction in hospital costs

• Based on the cost savings model shown below, hospitals with 200–400 beds might generate $5 million annually using this intervention.


Septicemia – potential savings for 200-400 bed hospitals ~$5M per yr

Meningitis

Size of the problem: In one study, 80% of meningitis cases from ER were viral.33

The Crux: Standard care involves admission, culture tests, and empiric intravenous antibiotics. Cerebrospinal fluid bacterial culture takes three days, while CSF viral culture takes four to 10 days. Molecular results confirming viral meningitis take four hours.34 One study applied a molecular (polymerase chain reaction-based) prediction model for viral meningitis and showed a reduction in unnecessary hospitalization by 59%.35

Potential Value of Pathology-Supported Solution: Employing rapid molecular testing in the ER could reduce unnecessary viral meningitis admissions by 59%.In 2006, the average cost of a viral meningitis hospital stay was $6,800,36 in 2012 medical dollars that would be $8,360.

Pneumonia

Size of the problem: Doctors misdiagnose pneumonia 30% of the time, and 63% of patients misdiagnosed with pneumonia actually have chronic obstructive pulmonary disease (COPD), asthma, heart failure, or bronchitis.37

Average DRG rates for COPD exacerbations, ~$5,500, are 54% lower than for pneumonias, ~$12,000.

The Crux: Biomarkers (procalcitonin and CRP) can distinguish between COPD, asthma, heart failure, bronchitis, and pneumonia. These biomarkers can be used to lower the diagnostic error rate and direct appropriate antibiotic use in the ER. CRP has a sensitivity of 91% and specificity of 93% for identifying patients with pneumonia.38

Potential Value of Pathology-Supported Solution: ER doctors need biomarker services that improve diagnostic accuracy, such as procalcitonin and CRP. Procalcitonin can reduce antibiotic duration by a median of four days (AHRQ).

These biomarkers can help reduce the pneumonia error rate for at least 63% of the misdiagnoses (COPD, heart failure, bronchitis, asthma).

Model Input Value Source

Average number of annual discharges

12,780 American Hospital Directory

Septicemia cases are 4.2% of inpatients

805 Healthcare Cost and Utilization Project –HCUP Statistical Brief #122 (Elixhauser et al. 2011)

Percent of septicemia cases that are targets for rapid pathogen testing

75% M Morgan. Clinical Microbiology Newsletter 35:10,2013

Average hospital cost for septicemia

$22,000 HCUP Statistical Brief #146 (Pfuntner et al. 2013)

Cost reduction achieved with rapid pathogen testing services per case = 37%

$8,140 Average of results from Perez et al. 2012 and KA Bauer et al. 2010

Total Cost Reduction Per Year - Midsize Hospitals

~$5M = 805*75% * $8,140


Admissions with incorrect pneumonia diagnoses receive unnecessary antibiotics and:37

• 25% experience a delay (at least 24 hours) in receiving the right diagnosis

• 4% experience adverse events from the antibiotics

• 4% morbidity or mortality from delay in diagnosis or treatment

• 4% reduction in avoidable costs related to pneumonia ER cases

Overall, this biomarker decision-making strategy can potentially yield 93% biomarker accuracy*63% reduction in errors = 58.6% decrease in ER pneumonia diagnostic errors.


Appendix 2: Evidence of Value Returns from Pathology-Informed Decisions: Surgery

Surgical Site Infections (S. aureus)

Size of the problem: It is estimated that 30% of patients have S. aureus colonization, 60% of patients have S. aureus intermittently; and S. aureus causes approximately 30% of all hospital-acquired infections.39 Further, 85% of S. aureus surgical site infections (SSIs), be they drug-susceptible (MSSA) or resistant (MRSA), come from preoperative nasal colonization.40

The Crux: Mupirocin, an inexpensive drug with minimal side effects, clears colonization in 80% of carriers.40 Prophylaxis reduces MRSA infections by 60%.41

Potential Value of Pathology-Supported Solution: A 60% reduction in MRSA infections among 30% of SSIs caused by S. aureus = 18% reduction.On average, SSIs extend length of stay by 9.7 days while increasing cost by $20,842 per admission.42

For nongovernment, acute-care hospitals with bed sizes from 350–500, the average number of annual inpatient surgeries is 6,200 (American Hospital Directory). Taking a median rate of SSIs of 3.5% of inpatient surgeries, this represents about 220 SSIs per year.

By decreasing these infections by 18% (40 SSIs avoided) and applying a cost savings of $20,800 for each avoided SSI, pathology-supported solutions could yield a total savings of about $825,000 annually.

Surgical Site Infections (Glycemic control)

Size of the Problem: Of the risk factors for postoperative surgical site infection (SSI) (eg, diabetes, age, etc), postop high glucose (>110mg/dL 12 to 24 hours after surgery) alone is a significant predictor of SSI, and 46% of patients with SSI had elevated postop glucose.43

The Crux: Keeping glucose at 80–180mg/dL reduces SSI rates by 30%.43a However, handheld blood glucose monitors are not accurate enough for optimal control of glucose levels.

Potential Value of Pathology-Supported Solution: Implementing glucose testing instruments and procedures that are more accurate can result in improved glycemic control, which can reduce SSI rates. A 30% reduction in SSI rates among the 46% of patients with elevated postop glucose yields a potential 14% reduction in SSI rates.

Overall SSI Value of Pathology-Supported Solutions: On average, SSIs extend length of stay by 9.7 days while increasing cost by $20,842 per admission.42

According to the CDC, 2% to 5% of patients undergoing inpatient surgery experience SSIs.44

For nongovernment, acute-care hospitals with bed sizes from 350–500, the average number of annual inpatient surgeries is 6,200. (American Hospital Directory). Taking a median rate of SSIs of 3.5% of inpatient surgeries, this represents about 220 SSIs per year.


By decreasing these infections by 14% (31 SSIs avoided) and applying a cost savings of $20,800 for each avoided SSI, pathology-supported solutions could yield a total savings of about $650,000 annually.

Blood Product Utilization

Size of the problem: One study found rates of over 70% of inappropriate transfusion orders among staff at an academic hospital.45

Each unit of RBC increases the risk of:

• Nosocomial infection by 50%46

• Hospital bed days by 16% to 32%47

From 2004–2008 hospital blood and blood product expenses were:48

• $1.1 million for nonteaching hospitals over 150 beds

• $1.4 million for teaching hospitals from 150–300 beds

• $2 million for teaching hospitals/academic centers above 300 beds

The Crux: Pathologists can implement blood product utilization programs that can reduce inappropriate usage, save costs and improve outcomes.

Potential Value of Pathology-Supported Solutions:

Pathology-led blood product utilization programs are typically comprised of multiple components, including protocols for usage, test menus with algorithmic decision support, physician usage tracking and feedback, and pathologist consultation services.

To assess the potential value of these programs, the Premier healthcare alliance conducted a study of blood product utilization variations for the treatment of patients with similar conditions at 464 hospitals across the country. 48

The study found that if hospitals were able to perform equivalently to the top quartile, they would save on average $1.06 million annually.

Further, Premier’s “dashboard analysis” of savings opportunities for hospitals ranked blood utilization the eighth highest in terms of potential savings. Another study from Massachusetts General Hospital49 involved a program with multiple blood transfusion services, including evidence-based guidelines for high volume products and consultant-gatekeeper for low volume-high cost products. They estimated resulting cost savings of ~ $1.735 million annually (as of 2011).


Venous Thromboembolism Events

Size of the problem: As much as 86% of venous thromboembolisms (VTEs) are hospital acquired.50 Up to 15% of hospitalized medical patients may develop a VTE during or immediately following their hospitalization. In hip or knee replacement surgery patients, 40% or more are likely to develop a VTE without appropriate prophylaxis, and up to 40% of general surgery patients may develop a VTE unless appropriate prophylaxis is provided.51

• An average of 600,000 annual VTE events occur during hospitalizations.52

• There were 36 million discharges in short-stay, nonfederal US hospitals in 2009 (http://www.cdc.gov/nchs/fastats/hospital.htm).

• This gives an estimated 1.7% VTEs per discharge.

The Crux: Many at-risk patients receive suboptimal or no VTE prophylaxis53 despite the fact that VTE prophylaxis has been rigorously tested in clinical trials and has proven to be cost effective.54 Because identifying patients at risk of VTE and selecting appropriate prophylaxis can be complex, computer applications can play a valuable role in prevention.

In a meta-study of 387 hospitals, VTE events were reduced by 16.5% in hospitals using EHRs and by 38% in hospitals with electronic laboratory ordering.55

Potential Value of Pathology-Supported Solutions: The net, increased reduction in VTEs attributable to electronic laboratory ordering EHR tools above and beyond just using EHRs is 38%–16%, or 21%. Thus, adding EHR laboratory ordering tools could provide a 21% reduction in hospital-acquired VTEs.

A study reviewing hospital costs of VTEs found average cost of a VTE is $9,130.56

For hospitals with 300–450 beds, that have an average of 18,000 annual admis-sions (American Hospital Directory), this intervention might avoid 64 VTEs annually (21% * (1.7% * 18,000) = 64).

Given a cost of $9,130, this represents potential savings of $587K annually.


Appendix 3: Evidence of Value Returns From Pathology-Informed Decisions: Intensive Care Unit

Fluid and Electrolyte Disorders

Size of the problem: Hyponatremia is the most common fluid and electrolyte disorder and carries a substantial mortality and cost burden. “This analysis of more than 50,000 admissions to St Elizabeth’s Medical Center revealed that hospital-associated hyponatremia is a common occurrence with important consequences. Whether it is present on admission, exacerbated after admission, or develops during hospitalization, hyponatremia is independently associated with in-hospital mortality, prolongation of length of stay (LOS), and discharge to a facility. In this unselected population of hospitalized adults, CAH (community-acquired hyponatremia) and HAH (hospital-associated hyponatremia) each developed in approximately 38% of at-risk hospitalizations.”57

Another study found that physicians treating hyponatremia had diagnoses inconsistent with clinical data in 49% of cases, and in 33% significant management errors were made.58

Furthermore, other investigators have found that hyponatremia patients who experience declines in sodium during hospitalization, suggesting providers may be having difficulties managing the condition, are estimated to double the length of stay versus other hyponatremic cases, from 9.5 days to 19 days.59 This study also found statistically significant links between the adequacy of the clinicians’ laboratory testing for hyponatremia and mortality rates.

Finally, they found that 49% of severe hyponatremia cases experience a fall in their sodium levels during hospitalization, and 24% of these are surgical patients.59

The Crux: Determining the origin of the hyponatremia in the intensive care unit (ICU) can be complex, and it requires a number of key laboratory tests, such as serum and urine osmolality, which determine a patient’s volume status and help guide treatment.60 But urine osmolality is infrequently checked in patients with severe hyponatremia, suggesting that treatment is often not being guided, as it should, by the cause of hyponatremia.61

Potential Value of Pathology-Supported Solutions: Pathology-supported services, which may include diagnostic teams, test decision support, or electronic health record tools and algorithms for detecting, diagnosing, and managing hyponatre-mia, could reduce LOS for hospitalized cases experiencing declines during hospi-talization by 50%.

Based on a study from St. Elizabeth’s Medical Center, a 400-bed tertiary, near-to-very-severe hospital-acquired hyponatremia cases occur in about 3% of hospitalizations, or about 320 cases per year.57

In addition, this study also identified cases, “hospital-aggravated hyponatremia,” where patients had hyponatremia on admission but the condition worsened during their hospitalization. These occurred in about 2% of hospitalizations.

To estimate the total cases for which a pathology-supported solution could produce benefits, we add the 49% of severe hospital-acquired cases that show declines in sodium during hospitalization, or about 1.5% of hospitalizations (155 cases/year), to the 2% of hospitalizations that are “hospital aggravated, community-acquired hyponatremia cases” (265/year) (all rates taken from 400-bed hospital study).


We can apply a cost estimate for a hyponatremia hospital stay of $11,550 (adjusted to 2012 dollars), and per diem ICU costs of $1,815 to estimate potential savings.62

We estimate that pathology-supported solutions can reduce LOS by 50% for hyponatremia cases experiencing declining sodium during hospitalization.

Thus, for each hyponatremia case, the savings benefit would be about 50% of ~$11,550, or ~$5,800 per patient.

Based on the study from a 400 bed hospital, the potential annual savings from this program would be (265 + 155 cases) * $5,800 = $2.4 million. Acute Renal Failure

Size of the Problem: The incidence of acute renal failure, now called acute kidney injury (AKI), is believed to occur in at least 5% of hospitalizations.63 In a study in a Veterans Affairs Hospital, 8% of hospitalizations were found to have in-hospital AKI.64

Conventional AKI diagnosis uses serum creatinine (SCr) measures, but it may take hours to days for SCr to accumulate, and by then it might be too late. A new biomarker, NGAL, detected AKI early in 43% of AKI patients who would have been missed using SCr tests. NGAL together with SCR -dentified patients whose ICU and hospital stays were doubled compared to patients with negative SCr and NGAL.65

The Crux: NGAL, a urine test, may indicate tubular injury that precedes function loss,65 and it can be detected 36 to 48 hours earlier than SCr.66 Early intervention by a nephrologist allows a more precise diagnosis, the start of preventive measures and reduces progression in 74% of cases evaluated.

“With the advent of NGAL and the detection of AKI within a few hours of initiation, it is now conceivable to test preventive or immediate therapeutic interventions.”66

Potential Value of Pathology-Supported Solutions: A 74% reduction in progression to ARF/late stage AKI with early detection and nephrologist intervention applied to 43% of missed cases of AKI yields a potential 32% decrease in late stage AKI cases and costs.

Based on a study estimating hospital costs by severity of AKI stage, “the average difference in total postoperative costs between the three RIFLE categories is… ~$14,000 in 2002 dollars.” 63 Updated for 2012, the cost difference between stages is ~$26,000 (US Inflation Rate for Inpatient Hospital Services, US Bureau of Labor Statistics). This 2012 cost difference represents the differential savings per case when progression is stopped.

Assuming hospitals with 350–500 beds have an average of 18,089 admissions (American Hospital Directory data), and AKIs are 5% of admissions, these hospitals might have 904 AKI cases annually. Assuming the pathology-supported decision-making strategy reduces these cases by 32%, and applying the $26,000 differential cost savings to each case, the total, annual savings would be ~$7.5 million.


Appendix 4: Evidence of Value Returns from Pathology-Informed Decisions: Medicare Readmissions and Hospital-Acquired Conditions

Readmissions: Resistant Pathogen Pneumonia

Size of the problem: Health care-associated pneumonia (HAP) accounts for 67% of pneumonia admissions and HAP has higher resistant pathogen rates.67 In addition, 47% of health care-associated pneumonia cases are due to MRSA.68,69

The Crux: Adding active surveillance cultures for MRSA in ICUs to standard infection prevention protocols in community-based hospitals decreased MRSA infections by an average of 67%.

Potential Value of Pathology-Supported Solution: Of the 67% of pneumonia admissions that are HAPs and of the 47% of HAPs that are MRSA, a 67% decrease in MRSA through active surveillance cultures yields a potential 21% reduction in HAP pneumonia cases or costs.

Based on average hospital costs for pneumonia of $11,000, this represents savings of ~$2,310 per HAP pneumonia case (21% *$11,000).70

Given an estimated incidence for hospital-associated pneumonias of 10 cases per 1,000 hospital admissions,71 and applying the $2,310 savings per case, we have ~$23,100 in savings per 1,000 admissions.

For hospitals with 350–500 beds with an average of 18,089 admissions, this would represent potential savings of ~$415,000 per year (180*$2,310).

In addition, decreasing MRSA pneumonia cases mitigates the chances of readmissions, given that resistant cases are more likely to be treatment failures, which are a predictor of pneumonia readmissions.

Readmissions: Pneumonia Treatment Failures

Size of the problem: In 23% of pneumonia cases in one study, patients did not receive appropriate antibiotics within 24 hours of hospitalization.67 Pneumonia treatment failures have been identified as an independent, significant predictor of 30-day pneumonia readmissions.72 Between 20% and 36% of 30-day pneumonia readmissions are due to pneumonia-related causes.

Treatment failures can be largely attributed to the fact that empirically prescribed antibiotics for pneumonia are often inappropriate.

The Crux: Rapid molecular testing for infectious organisms has been shown to effectively change clinicians’ antibiotic prescribing regimens to more appropriate regimens, versus empirical choices; for example, using a drug that covers a newly identified pathogen or using a narrower range of antibiotics.19 In a study of bacteremic ER patients, 77% of patients would have had different antibiotic regimens if the molecular testing results had been available.19

Potential Value of Pathology-Supported Solution: Rapid molecular testing services for hospital pneumonia are likely to reduce the pneumonia treatment failure-related readmissions substantially. Based on the assumption that 28% of 30-day readmissions are due to treatment-related failures (midpoint between 20% and 36% for pneumonia-related causes), and that rapid molecular testing of pneumonia at admission/ER could reduce those treatment failures by ~77%19 of cases (based on rapid prescription of appropriate antibiotics), this solution might reduce pneumonia readmissions by ~22%.


Reducing pneumonia readmissions through utilization of rapid testing services can generate potential annual savings for a mid/large hospital (~ 500 beds) as follows:

• Pneumonia readmissions = 18% readmission rate for pneumonias • For 500 bed hospitals with about 42,315 discharges annually, there would be 1269 index cases of pneumonia per year (CDC data - ~3% of admissions are pneumonia) = ~229 readmitted cases76

• Pathology rapid testing services generate ~22% reduction in readmits, or 50 cases annually

• One estimate for hospital costs for a typical inpatient stay for pneumonia is ~$11.000. 70

Total potential cost savings for mid/large hospitals, ~$550,000.

Readmissions: Acute Myocardial Infarction and Congestive Heart Failure

Size of the Problem: Among acute myocardial infarction (AMI) and congestive heart failure 30-day readmissions, 27% to 28% is due to complications and infections according to an analysis of an extensive database of 62,768 all-cause admissions to 44 acute care facilities in Pennsylvania.73

The Crux: Many diabetics are not on statins or do not adhere to statin therapy, so they are not achieving optimal lipid levels and are at risk of AMI. Pathologists can test diabetics to monitor lipid levels and recommend statins for high-risk patients. Statin use reduced the risk of MI by 62% for both primary and secondary treatment of 6,697 diabetic patients.74 In another study, statins reduced cardiovascular events among diabetics by 37%.

Poor metabolizers of clopidogrel also have high rates of AMI after angioplasty pro-cedures. Pharmacogenetic testing for markers of clopidogrel metabolism levels could guide dosing and drug selection, potentially reducing AMI events among poor metabolizers. In a large meta-analysis, poor metabolizers of clopidogrel have 33% of all major angioplasty adverse cardiovascular events.

Potential Value of Pathology-Supported Solution: A potential 37% reduction in AMI rate with optimal statin use among diabetics plus a potential 33% reduction in AMI events among patients undergoing angioplasty.

Health Care-Acquired Conditions: Urinary Tract Infections (UTIs)

Size of the problem: Antibiotic resistant rates of biofilm-producing E. coli range from 70% to 100% for 10 drugs.75 In a study in a long-term care setting, empiric antibiotics for UTIs were ineffective in 69% of cases. Failed empiric antibiotics are also associated with more resistance and longer hospital stays.

The Crux: A study of cost differences between resistant and susceptible urinary tract infections (UTIs) showed an average length of stay increase of 2.24 days.32 This represents a ~24% cost increase.

Molecular point-of-care testing to guide antibiotic selection could reduce costs, as in a 2011 study that applied real-time PCR tool SeptiFast to UTI diagnosis and delivered results that helped guide antibiotic selection within four to five hours.76


Potential Value of Pathology-Supported Solution: The use of pathology-directed molecular testing to inform UTI prescribing decisions could reduce unnecessary hospital costs. Assuming failed empirical treatment cases have similar cost increases to resistant UTIs (24%), when we provide rapid molecular testing for hospital-aquired UTI pathogen identification we might see a 24% decrease in hospital costs for the 69% of the patients for whom empiric antibiotics are ineffective, yielding a potential 17% value impact/total cost reduction.

Research shows that nosocomial UTIs necessitate one extra hospital day per patient.77 According to the Healthcare Cost and Utilization Project, Dec 2010, Statistical Briefs 144 and 146, the average cost for one day of hospitalization updated to 2012 dollars is $2,400.

An overall estimate of potential savings for this pathology intervention for healthcare acquired UTIs would then be 17%*$2,400 = ~$400 per patient.


1 Institute of Medicine, 2012 “Best care at lower cost: the path to continuously learning health care in America.” Institute of Medicine of the National Academies website. http:// http://www.iom.edu/Reports/2012/Best-Care-at-Lower-Cost-The-Path-to-Continuously-Learning-Health-Care-in-America.aspx. Published September 2, 2012. Accessed February 11, 2013.

2 Bailey C. The cost reduction imperative. Becker’s Hospital Review website. http://www.beckershospitalreview.com/racs-/-icd-9-/-icd-10/ the-cost-reduction-imperative.html. Published October 11, 2012.

3 Plebani M. Exploring the iceberg of errors in laboratory medicine. Clinica Chimica Acta. 2009;404(1):16–23. doi:10.1016/j.cca.2009.03.022. Accessed February 11, 2013.

4 Graber M., Diagnostic errors in medicine: a case of neglect. Jt Comm J Qual Patient Saf. 2005;31(2):106–113.

5 Braithwaite RS, DeVita MA, Mahidhara R, et al. Use of medical emergency team (MET) responses to detect medical errors. Qual Saf Health Care. 2004;13(4):255–259.

6 US Department of Health & Human Services Agency for Health Research and Quality “2011 National Healthcare Quality & Disparities Reports.” Department of Health & Human Services website. http:// http://www.ahrq.gov/qual/qrdr11.htm. Published March 2012. Accessed February 11, 2013.

7 Lee DH, Vielemeyer O. Analysis of overall level of evidence behind Infectious Diseases Society of America practice guidelines. Arch Intern Med. 2011;171(1):18–22. doi:10.1001/archinternmed.2010.482.

8 Callen JL, Westbrook JI, Georgiou A, Li J. Failure to follow-up test results for ambulatory patients: a systematic review. J Gen Intern Med. 2012;27(10):1334–1348.

9 Roshanov PS, Misra S, Gerstein HC, et al; CCDSS Systematic Review Team. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6:92. doi:10.1186/1748-5908-6-92.

10 Singh H, Thomas EJ, Sittig DF, et al. Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? Am J Med. 2010;123(3):238–244. doi:10.1016/j.amjmed.2009.07.027.

11 Murphy DR, Reis B, Sittig DF, Singh H. Notifications received by primary care practitioners in electronic health records: a taxonomy and time analysis. Am J Med. 2012;125(2):209.e1–7. doi:10.1016/j.amjmed.2011.07.029.

12 Singh H, Thomas EJ, Mani S, et al. Timely follow-up of abnormal diagnostic imaging test results in an outpatient setting. Arch Intern Med. 2009;169(17):1578–1586. doi:10.1001/archinternmed.2009.263.

13 Wahls TL, Cram PM. The frequency of missed test results and associated treatment delays in a highly computerized health system. BMC Fam Pract. 2007;8:32

References


14 SE Walz, Smith M, Cox E, Sattin J, Kind AJ. Pending laboratory lests and the hospital discharge summary in patients discharged to sub-acute care. J Gen Intern Med. 2010;26(4):393–398. doi:10.1007/s11606-010-1583-7.

15 Teng K, Eng C, Hess CA, et al. Building an innovative model for personalized healthcare. Cleve Clin J Med. 2012;79 Suppl 1:S1–S9. doi:10.3949/ccjm.79.s1.01

16 Timmerman L. 2012: the year when genomic medicine started paying off. Xconomy. http://www.xconomy.com/national/2012/12/17/2012-the-year-when-genomic-medicine-started-paying-off/. Published December 17, 2012. Accessed February 12, 2013.

17 Lundberg GD. How clinicians should use the diagnostic laboratory in a changing medical world. Clini Chim Acta. 1999;280(1–2):3–11.

18 Schildcrout JS, Denny JC, Bowton E, et al. Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping. Clin Pharmacol Ther. 2012;92(2):235–242. doi:10.1038/clpt.2012.66.

19 Stoneking LR, Patanwala AE, Winkler JP, et al. Would earlier microbe identification alter antibiotic therapy in bacteremic emergency department patients? J Emerg Med. 2013;44(1);1–8. doi:10.1016/j.jemermed.2012.02.036.

20 Brown J, Paladino JA. Impact of rapid methicillin-resistant Staphylococcus aureus polymerase chain reaction testing on mortality and cost effectiveness in hospitalized patients with bacteraemia: a decision model. Pharmacoeconomics. 2010;28(7):567–575. doi:10.2165/ 11533020-000000000-00000.

21 Bauer KA, West JE, Balada-Llasat JM, Pancholi P, Stevenson KB, Goff DA. An antimicrobial stewardship program’s impact with rapid polymerase chain reaction methicillin-resistant Staphylococcus aureus/S. aureus blood culture test in patients with S. aureus bacteremia. Clin Infect Dis. 2010;51(9):1074–1080. doi:10.1086/656623.

22 Start spreading the news: Compass Group makes its case for lab’s value. CAP TODAY. 2008;22(5):73–77.

23 Chen P. Business of pathology: pathologists’ roles in the emerging healthcare delivery models. Presentation at: Practical Advances in Pathology, January 30, 2011.

24 Laposata M. Advising treating physicians on laboratory test selection and interpretation. Presentation at: Massachusetts Society of Pathologists Annual Dinner Meeting and CME Seminar; May 10, 2012; Waltham, MA.

25 Nunez S, Hexdall A, Aguirre-Jaime A. Unscheduled returns to the emergency department: an outcome of medical errors? Qual Saf Health Care. 2006;15(2):102–108.

26 AdvanDx. New study shows PNA FISH® test reporting dramatically decreased mortality and hospital costs for patients with bloodstream infections [press release]. New York, NY: PR Newswire; October 13, 2011.

27 Maisel A, Neath SX, Landsberg J, et al. Use of procalcitonin for the diagnosis of pneumonia in patients presenting with a chief complaint of dyspnoea: results from the BACH (Biomarkers in Acute Heart Failure) trial. Eur J Heart Fail. 2012;14(3):278–286. doi:10.1093/eurjhf/hfr177.

28 Cohen-Bacrie S, Ninove L, Nougairede A, et al. Revolutionizing clinical microbiology laboratory organization in hospitals with in situ point-of-care. PLoS One. 2011;6(7):e22403. doi:10.1371/journal.pone.0022403.


29 PROMETHEUS in practice: Evidence-informed Case Rate™ (ECR®). Health Care Incentives Improvement Institute (HCI3) website. http://www.hci3.org/what_is_prometheus/f.ramework/evidence_informed_case_rates/chronic_medical_ecrs. Accessed January 10, 2013.

30 Kumar A. Optimizing antimicrobial therapy in sepsis and septic shock. Crit Care Nurs Clin North Am. 2011; 23(1):79–97. doi:10.1016/j.ccell.2010.12.005.

31 Perez K.K., R. Olsen, W. Musick, P. Cernoch, J. Davis, G. Land, L. Peterson, and J. Musser. 2012. “Integrating rapid pathogen identification and antimicrobial stewardship significantly decreases hospital costs.” Arch Pathol Lab Med. Dec 6:1-8.

32 EE Eiland, Beyda N, Han J, et al. The utility of rapid microbiological and molecular techniques in optimizing antimicrobial therapy. Srx Pharm. 2010:1–7. doi:10.3814/2010/395215.

33 Magazzini S, Nazerian P, Vanni S, et al. Clinical picture of meningitis in the adult patient and its relationship with age. Intern Emerg Med. 2012;7(4):359–364. doi:10.1007/s11739-012-0765-1.

34 Paxton A. Antibiotic program supersizes impact of molecular testing. CAP TODAY. 2011;25(10):49–52.

35 Mohseni MM, Wilde JA. Which patients can be discharged from the emergency department? J Emerg Med. 2012;43(6):1181–1187. doi:10.1016/j.jemermed.2012.03.021.

36 Holmquist L, Russo CA, Elixhauser A. Meningitis-related hospitalizations in the United States, 2006: Statistical brief #57. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD: Agency for Healthcare Research and Quality; 2008.

37 Welker JA, Huston M, McCue JD. Antibiotic timing and errors in diagnosing pneumonia. Arch Intern Med. 2008;168(4):351–356. doi:10.1001/archinternmed.2007.84.

38 Bafadhel M, Clark TW, Reid C, et al. “Procalcitonin and C-reactive protein in hospitalized adult patients with community-acquired pneumonia or exacerbation of asthma or COPD.” Chest. 2011;139(6):1410–1418. doi:10.1378/chest.10-1747.

39 Perl TM, Cullen JJ, Wenzel RP, et al. Intranasal mupirocin to prevent postoperative Staphylococcus aureus infections. N Engl J Med. 2002; 346(24):1871–1877.

40 van Rijen MM, Bonten M, Wenzel RP, Kluytmans JA. Intranasal mupirocin for reduction of Staphylococcus aureus infections in surgical patients with nasal carriage: a systematic review. J Antimicrob Chemother. 2008;61(2):254–261. doi:10.1093/jac/dkm480.

41 Edmiston CE, Spencer M, Lewis BD, et al. Reducing the risk of surgical site infections: did we really think SCIP was going to lead us to the promised land? Surg Infect. 2011:12(3):169–177. doi:10.1089/sur.2011.036.

42 De Lissovoy G, Fraeman K, Hutchins V, Murphy D, Song D, Vaughn BB. Surgical site infection: incidence and impact on hospital utilization and treatment costs. Am J Infect Control. 2009;37(5):387–397.

43 Ata A, Lee J, Bestle SL, Desemone J, Stain SC. Postoperative hyperglycemia and surgical site infection in general surgery patients. Arch Surg. 2010;145(9):858–864. doi:10.1001/archsurg.2010.179.

43a Ena J, Casan R, Carratala MJ, and Leutscher E. “Effect of a program to control perioperative blood glucose on the incidence of nosocomial infections in patients with diabetes: A pilot study.” Ann Surg. 2008; 248(4):585–591.


44 Berríos-Torres SI; Surgical Site Infection (SSI) Toolkit [slidedeck]. Atlanta, GA: Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention; 2009.

45 Rothschild JM, McGurk S, Honour M, et al. Assessment of education and computerized decision support interventions for improving transfusion practice. Transfusion. 2007; 47(2):228–239. doi:10.1111/j.1537-995.2007.01093.x

46 Taylor RW, Manganaro L, O’Brien J, Trottier SJ, Parkar N, Veremakis C. Impact of allogenic packed red blood cell transfusion on nosocomial infection rates in the critically ill patient. Crit Care Med. 2002;30(10):2249–2254.

47 Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: Anemia and blood transfusion in the critically ill--current clinical practice in the United States. Crit Care Med. 2004;32(1)39–52.

48 Premier Healthcare Alliance. “Best Practices in healthcare utilization.” Fall 2012 Ecomomic Outlook.

49 JY Kim et al. “Utilization Management in a Large Urban Academic Medical Center: A 10-Year Experience.” Am J Clin Pathol 2011;135:108-118

50 Spencer FA, Lessard D, Emery C, Reed G, Goldberg RJ. Venous thromboembolism in the outpatient setting. Arch Intern Med. 2007 July 23; 167(14):1471–1475.

51 Barnes GD, Birkmeyer N, Flanders SA, et al. Venous thromboembolism:a collaborative quality improvement model for practitioners, hospitals, and insurers. J Thromb Thrombolysis. 2012;33(3):274–279. doi: 10.1007/s11239-012-0699-5.

52 Lefebvre P, Laliberte F, Nutescu EA, et al. All-cause and potentially disease-related health care costs associated with venous thromboembolism in commercial, Medicare, and Medicaid beneficiaries. J Manag Care Pharm. 2012;18(5):363–374.

53 Gray J, Razmus I. Improving venous thromboembolism prevention processes and outcomes at a community hospital. Jt Comm J Qual Patient Saf. 2012; 38(2)61–66.

54 Goldhaber SZ. “Venous thromboembolism risk among hospitalized patients: magnitude of the risk is staggering.” Am J Hematol. 2007; 82(9): 775-776.

55 Hu HM, Tzeng HM. A hospital’s adoption of information technology is associated with altered risks of hospital-acquired venous thromboembolism. Am J Med Qual. 2012;27(4): 305–312. doi:10.1177/1062860611426349.

56 Knight KK et al., “Economic and Utilization Outcomes Associated with Choice of Treatment for Venous Thromboembolism in Hospitalized Patients.” Value in Health. 2005; 8(3):191-200.

57 Wald R. Impact of hospital-associated hyponatremia on selected outcomes. Arch Intern Med. 2010;170(3):294–302. doi:10.1001/archinternmed.2009.513.

58 Huda MS, Boyd, Skagen K, et al. Investigation and management of severe hyponatraemia in a hospital setting. Postgrad Med J. 2006;82(965):216–219.

59 Whyte M, Down C, Miell J, Crook M. Lack of laboratory assessment of severe hyponatremia is associated with detrimental clinical outcomes in hospitalized patients. Int J Clin Pract. 2009;63(10):1451–1455. doi:10.1111/j.1742-1241.2009.02037.x.

60 Pokaharela M, Block CA. Dysnatremia in the ICU. Curr Opin Crit Care. 2011;17(6):581–593. doi:10.1097/MCC.0b013e32834cd388.

61 Crook M., The investigation and management of severe hyponatraemia. J Clin Pathol. 2002;55(12):883.


62 Boscoe A, Paramore c, Verbalis JG. Cost of illness of hyponatremia in the United States. Cost Eff Resour Alloc. 2006;4:10.

63 Dasta JF, Kane-Gill SL, Durtschi AJ, Pathak DS, Kellum JA. “Costs and out-comes of acute kidney injury (AKI) following cardiac surgery.” Nephrol Dial Transplant. 2008; 23: 1970–1974. doi: 10.1093/ndt/gfm908.

64 Balasubramanian G, Al-Aly Z, Moiz A, et al. “Early nephrologist involvement in hospital-acquired acute kidney injury: a pilot study.” Am J Kidney Dis. 2011;57(2):228–234. doi:10.1053/j.ajkd.2010.08.026.

65 Haase M, Haase-Fielitz A. Can novel biomarkers complement best possible clinical assessment for early acute kidney injury diagnosis? J Am Coll Cardiol. 2011;58(22):2310–2312. doi:10.1016/j.jacc.2011.08.014.

66 McCullough PA, El-Ghoroury M, Yamasaki H. Early detection of acute kidney injury with neutrophil gelatinase-associated lipocalin” J Am Coll Cardiol. 2011;57(17):1762–1764. doi:10.1016/j.jacc.2010.11.050.

67 Micek ST, Kollef KE, Reichley RM, Roubinian N, Kollef MH. Health care-asso-ciated pneumonia and community-acquired pneumonia: a single-center experience. Antimicrob Agents Chemother. 2007;51(10):3568–3573.

68 Kollef MH, Shorr A, Tabak YP, Gupta V, Liu LZ, Johannes RS. Epidemiology and outcomes of health-care-associated pneumonia: results from a large US da-tabase of culture-positive pneumonia. Chest. 2005;128(6):3854–3862.

69 Abrahamian FM, Deblieux PM, Emerman CL, et al. Health care-associated pneumonia: identification and initial management in the ED. Am J Emerg Med. 2008; 26(6 Suppl):1–11. doi: 10.1016/j.ajem.2008.03.015.

70 Office of Statewide Health Planning and Development, California. Preventable Hospitalizations in California: Statewide and County Trends in Access to and Quality of Outpatient Care, Measured with Prevention Quality Indicators 1999–2008; 2010.

71 American Thoracic Society; Infectious Diseases Society of America. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia. Am J Respir Crit Care Med. 2005;171(4):388–416.

72 Capelastegui A, España Yandiola PP Quintana JM, et al. Predictors of short-term rehospitalization following discharge of patients hospitalized with community-acquired pneumonia. Chest. 2009;136(4):1079–1085. doi:10.1378/chest.08-2950.

73 Kanel K, Elster S, Vrbin C.; Pittsburgh Regional Health Initiative. Brief: overview of six target chronic diseases. http://www.prhi.org/newspublications?task=sub&cat=7. Published March 19, 2010. Updated June 8, 2010. Accessed February 14, 2013.

74 Sheng X, Murphy MJ, MacDonald TM, Wei L. Effect of statins on total cholesterol concentrations and cardiovascular outcomes in patients with diabetes mellitus: a population-based cohort study. Eur J Clin Pharmacol. 2012;68(8):1201–1208. doi:10.1007/s00228-012-1234-5.

75 Lai EPC, Iqbal Z. Environmental microbiology meets chemical biotechnology. J Pet Environ Biotechnol. 2012;3:e106. doi:10.4172/2157-7463.1000e106.

76 Lehmann LE, Hauser S, Malinka T, et al. Rapid qualitative urinary tract infection pathogen identification by SeptiFast real-time PCR. PloS One. 2011; 6(2): e17146. doi:10.1371/journal.pone.0017146.

77 Foxman B. Epidemiology of Urinary Tract Infections: Incidence, Morbidity, and Economic Costs. Am J Med. 2002;Jul 8;113 Suppl 1A:5S–13S.

cap.org YourPathYourChoice.org Follow Us: @pathologists

College of American Pathologists325 Waukegan Rd.|Northfield, IL 60093

800-323-4040 | cap.org

Documents

Unlocking a New Layer of Value: Pathology … › apps › docs › reference › new_layer...This information is intended for internal use only and shall not be reproduced, copied,