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Driving Patient Safety with Predictive Assessments of Risk
Objectives
• Learn how organizations take preemptive action to intercept adverse events, improving outcomes, reducing lengths of stay, and lowering costs
• Learn how a prominent healthcare organization calculates a Modified Early Warning Score (MEWS) and identifies patients for early intervention before ICU transfer is required
• Learn how a leading healthcare organization uses Microsoft
Amalga to help manage a program that reduces DVTs
Learn how to extract insights from existing data to improve quality and patient safety
Hospital Safety A Huge Problem…and Not Getting Better
Estimated annual deaths due to medical errors: 98,000
Estimated annual deaths due to medical errors among
Medicare beneficiaries: 180,000
"The status quo is not acceptable and cannot be tolerated any longer... Must we wait another decade to be safe in our health system?“
-
Institute of Medicine, “To Err is Human”
“Hospital patients are being harmed by medical errors at an alarming rate”
-
U.S. HHS Office of Inspector General, “Adverse Events in Hospitals”
98,000180,000
1999 2010
The Financial Impact of Adverse Events
1
McNair, et al, “Medicare’s Policy Not to Pay for Treating Hospital-Acquired Conditions: The Impact”
Health Affairs, 28, no. 5 (2009): 1485-1493.2 Murray,R., “Setting Hospital Rates to Control Costs And Boost Quality: The Maryland Experience,”
Health Affairs, 28, no. 5 (2009): 1395-1405.
Complications of care account for 15% of inpatient costs (due to increased LOS, utilization of ICU services, etc.). Approximately 50% are estimated to be preventable1.
INCREASED COST TO THE SYSTEM
INCREASED COST FOR THE HOSPITAL
In a study of all inpatient hospital admissions in Maryland for 2008, there were $521 million of avoidable complications2.
A study¹ focused on the quality of care before patient transfer to intensive care found that:
of admissions to intensive care may have been avoidable if earlier intervention had occurred41%
of admissions to intensive care occurred late in the development of critical illness69%
of admissions had sub-optimal care prior to admission54%
¹McQuillan, Peter. “Confidential inquiry into quality of care before admission to intensive care.”
BMJ, 1998.
Why Is it So Hard to Solve Quality & Safety Challenges?
THE PROBLEMS
Do You Know Where to Focus?
MODIFIED EARLY WARNING SCORE VIEW
The MEWS view in Microsoft Amalga shows a Modified Early Warning Score (MEWS) for each inpatient. This score is calculated based on blood pressure, pulse, respiratory rate, temperature, and level of consciousness¹.
¹.Subbe CP, Kruger M, Rutherford P, and Gemmel L.
Validation of a modified Early Warning Score in medical admissions.
Q J Med 2001; 94:521-526.
Modified Early Warning System (MEWS) at Providence Health & Services
Providence Alaska Medical Center
Modified Early Warning System (MEWS)
MEWS helps providers manage patient safety and costly ICU admissions by focusing on patients with highest measured risk factors
OBJECTIVE CHALLENGE SOLUTION
• Affordably monitor early warning signals in patients to help prevent escalations to the ICU and fatalities
• Difficult to recognize early warning signs and intervene proactively because there are so many data points to track for each patient
• Missed early warning signs can cause unnecessary admissions to ICU and can compromise patient safety
• Identify the early warning signs of patients at risk for sepsis, ICU admission, and cardiac arrest
• Use a single numeric system for evaluating the risk of individual patients for these avoidable events
• Aggregate and present the data in timely, regular reports for response teams enabling them to focus resources on predicted highest risk patients
This view exposes recent MEWS values for a group of patients and enables clinicians to identify patients who need attention
Modified Early Warning Score View
Increased Rapid Response Calls to the Bedside
Pre MEWS Post MEWS
In the first two months of use, MEWS increased early, proactive clinician intervention by 145 percent at Providence Alaska Medical Center
Reduced “Code Blue”
Calls
Within the first two months of use, Providence Alaska saw a reduction in the number of “Code Blue” calls, suggesting
effective early intervention on the right patients
Post MEWS & PEAT Rounds
“[Providence Alaska Medical Center] really saw marked improvements in certain key outcomes that included decreased code blue events, increased rapid response team calls, decreased care escalation events, less frequent transitions of patients from standard inpatient units into the ICU because they caught impending inpatient problems earlier and were able to intervene.”
Paul Tittel, System Director, Enterprise Amalga and Data Services, Providence Health & Services
Monthly ICU admissions for Providence Alaska Hospital
Amalga Provides a Potential Cost Savings in a 300-Bed Hospital
35Admissions that
could be avoided
(McQuillan 1998)
14
$453,600Potential Annual Savings by Using MEWS
Average reimbursement shortfall for an ICU admission¹.
(HFMA July 2006)
$2,700
¹.“ICU stays having a significant impact on hospital margins.”
Healthcare Financial Management, July 2006.
Unreimbursed expenses can be limited by using data to avoid ICU admissions Help managing ICU capacity can reduce needs for capital investments
Hospital-Wide Program to Reduce Venous Thromboembolic Events
Economic Burden of Deep Vein Thrombosis and Pulmonary Embolisms
30 million
With an estimated incidence of 0.1%, these conditions impact
approximately 30 million Americans each year.
National (U.S.) annual expenditure on DVT events may amount to $1.5 billion.
1.5 billion
Economic Burden of Deep-vein Thrombosis, Pulmonary Embolism, and Post-thrombotic Syndrome, 12/08/2006; American Journal of Health-System Pharmacy.
2006;63(20):S5-S15.
©
2006
American Society of Health-System Pharmacists, David A. MacDougall; Anthony L. Feliu; Stephen J. Boccuzzi; Jay Lin
NewYork-Presbyterian
Reduce Venous Thromboembolic Events
Columbia, Weill Cornell Medical College and the NewYork-Presbyterian Hospital implemented a hospital-wide program to assure all patients have Deep Vein Thrombosis (DVT) risk and prevention addressed.
OBJECTIVE CHALLENGE SOLUTION
Assess DVT risk for all admitted patients and monitor prophylactic measures in near real-time to ensure that the appropriate therapy is provided.
• VTE predictive methods are significantly underutilized leading to a high incidence of pulmonary embolism
• Subjective assessment of risk can result in inadequate, or even, inappropriate prophylactic therapy
• Many data points have to be synthesized and tracked to systematically calculate risk of DVT. This makes it difficult for clinicians to manually calculate risk across their entire patient population.
• Standardize the method to identify patients at risk for DVT
• Track electronic order sets to determine level of prophylaxis
• Present the data in timely views that allow staff to see which patients are high risk or low risk and whether the appropriate level of prophylaxis has been provided
DVT Risk Calculation
SCORE CATEGORY
INDIVIDUAL SCORE
WEIGHTSCORE CRITERIA EXAMPLE
VALUESDVT RISK
SCORE
Age 1, 2, or 3 1: Age 41-60 2: Age 61-74 3: Age >=75 62 2
BMI 1 1: when BMI > 25 kg/m2 (except pregnancy) 19.2 kg/m2 0
Previous DVT 3 3: when previous NYP visit diagnosed with DVT at any time in the patient past history DVT in past 3
Previous AMI 1 1: when previous NYP visit within 30 days diagnosed with AMI 0
Previous CHF 1 1: when previous NYP visit within 30 days diagnosed with active CHF 0
Previous Fracture 3 3: when previous NYP visit within past 30 days diagnosed with a hip, pelvis or leg fracture 0
Previous Stroke 3 3: when previous NYP visit within past 30 days diagnosed with a stroke Stroke in past 30 days 3
Previous Cancer 2 2: when previous NYP visit diagnosed with Cancer in the past 12 months Cancer Dx in past year 2
Bedrest/OOB to Chair 1 1: Bedrest and Out of Bed to Chair order present OOB w / assistance 1
Total DVT Risk 18 Total of ALL Measured Risks 11
American College of Surgeons website ( Surgery News UPDATE --
http://www.facs.org/surgerynews/update/vtee0711.html
).
Improved Prophylaxis and Significantly Reduced VTEs
Pre Post
# of Pulmonary Embolism Events (very serious complication caused by DVT)
Columbia
1.08
0.80VTE Incidence (broader category than PE) # cases / 1,000 patient days
Columbia
24
15
Cornell
41
15
Cornell
1.19
0.84
Both Institutions
71%
98%% of eligible patients receiving
DVT prophylaxis therapy
Hospital-Wide Program Shows Reduction of VTEs
“…The AMALGA software allows real-time monitoring of risk and prophylaxis resulting in the ability to correct errors and provide appropriate prophylaxis when indicated.”
Nicholas J. Morrissey, MD, associate professor of clinical surgery at Columbia University College of Physicians and Surgeons in New York City
Insights for Clinical Transformation
Microsoft Amalga enables clinicians to gain valuable insights into an acute care population, by helping them:
• Rapidly identify patients who may be at elevated risk for near-term clinical deterioration for evaluation and intervention
• Gain deeper understanding by viewing the specific data that contributed to a risk score or other data on the patient
• Improve quality of care
• Take steps to reduce costs to the hospital from unplanned ICU transfers and VTEs
HOW DOES MICROSOFT AMALGA BENEFIT USERS?
• Tracking indwelling devices• Screening for catheter-associated UTIs• Screening for central line blood stream infections• Screening for sepsis risk• Tracking patient isolation indicators• Identifying patients at risk for pressure ulcers• Screening for glycemic
control• Screening for heparin induced thrombocytopenia• Screening for potential adverse drug events• Tracking abnormal results• Tracking key data for pharmacy rounds• Tracking patient transfer activity• Tracking IHI triggers
MICROSOFT AMALGA CUSTOMERS:
Sample Patient Safety Issues Being Addressed by
Questions & Answers
To learn more visit:
www.whatsnextinhealth.com/mews
To schedule a meeting/demo, email:
© 2011 Microsoft Corporation. All rights reserved. This material is provided for informational purposes only. Microsoft makes no warranties, express or implied.
