Survey of Medical Informatics

CS 493 – Fall 2004

November 1, 2004

V. “Juggy” Jagannathan

Streamlining Patient Safety Reporting

Part III: Patient Safety - Achieving a New Standard of Care.

IOM Report

Patient Safety data applications Clinical Performance data

regulators for accountability purposes Individual or organizations for purchasing

decisions Care providers to improve care processes

IOM Recommendation To develop an event taxonomy and common

report format to submit data to national patient safety databases

Patient Safety Reporting Systems and Applications

Chapter 8: Patient Safety - Achieving a New Standard of Care.

IOM Report

Continuum of applications

Figure 8-1 Accountability

Figure 8-2 Incentives

Figure 8-3 Requires “transparent” data

“sufficiently complete, understandable information about clinical performance”

In a “transparent” environment – consumers “patients” can make appropriate decision

Valid, reliable and relevant for decision making by patients

Performance data

Public reporting of performance data – sparse

Focus currently on hospitals, nursing homes, some surgical interventions

Very little on medical groups and physicians (ambulatory care)

Data: process-of-care measures, patient perceptions of care and accreditation status

Performance data

Even when they are available, currently they are not impacting consumer choice

Probably because: Lack of awareness on the existence of the data Limitations placed on choice of health plans and

providers Overly complex performance data Trustworthiness of the data

Benefits of public reporting

Promoting safer care produces fewer injuries and reduces legal and malpractice exposure

Promotes health providers to set goals for improving quality

System Redesign

Figure 8-4: Page 260 & 261 Accountability approach

Address performance problems which falls below minimum standards

Learning approach Reduce variability of performance Focus on continuous process improvement

Case Study

1986-1992 HCFA release mortality outcomes across 5,500 hospitals

Labeled based on statistical analysis: High Mortality outliers [highest 5%] – bad outcomes Low mortality outliers [bottom 5%] – good outcomes

Goal of HCFA to increase awareness of poorly performing institutions

However, analysis of measures revealed that categorization had significant error rates

In 1993, HCFA discontinued practice of reporting mortality measures

Selection of measures

Box 8-1, 264 Outcome measures aggregated over

geographic region – more reliable Measures can be used to improve processes

better than to build accountability systems

Cycle of fear

Figure 8-5 pg 266

Concept of preventability

Preventable errors vs. unavoidable treatment consequences

Example: 28% of ADE in one hospital was allergic reaction with patients with no prior history of such reaction even in this case policies can provide mitigating strategies.

Implications for patient safety data systems Data system design Standardized data Patient safety data audits

Standardized Reporting

Chapter 9: Patient Safety - Achieving a New Standard of Care.

IOM Report

The need for standardized report format Reporting requirements of NY and FL:

Commonality Patient information Time/location of the incident Description of the adverse event with root cause

analysis Corrective action taken ICD-9 CM use

Differences Each state has it own taxonomy and what are

reportable events and when the reporting needs to be done

Potpourri of reporting formats State level FDA

MedDRA http://www.fda.gov/medwatch/report/meddra.htm

MedWatch http://www.fda.gov/medwatch/index.html

JCAHO

Essential elements of a standard report format Systems of interest:

AHRQ’s proposed taxonomy for integration of all DHHS patient safety reporting systems

VHA system Australian Patient Safety Foundation Advanced

Incident Monitoring System US Pharmacopeial Convention Medical Event Reporting System for Transfusion

Medicine Systems used by anesthesia, Emergency room

Reporting standards

Box 9-1 – page 285 Basic domains

Who - discovered the incident and their role How - the incident was discovered What – actually happened Where – in the care processes When – time frame Why – root cause analysis

Australian approach

Australian AIMS Minimum data set of basic data Detailed comprehensive information for events

that resulted in harm to the patient

Event-type taxonomy

Multiple taxonomies in existence – and none are comprehensive

ICD-9/10 CM External Causes and Injury Codes (E-codes) and LOINC codes

E-Codes problems Lack temporal information Ambiguous clinical content Cannot differentiate events that occurred prior to

hospitalization from those that occurred during hospitalization

Lack of ability to categorize degree of harm Lack of ability to capture near misses

Patient Safety Terminology

Anesthesia domain – available in SNOMED CT

Australia AIMS uses a Generic Reference Model (GRM)

Health Incident Type taxonomy of event categories: falls, medication etc.

Risk assessment index

Scale measuring risk from near miss to death USP MedMARx ranks medication events –

Table 9-1 – page 293 (http://www.usp.org/medmarx/index.html )

AIMS risk assessment based on VHA model – Table 9-2 – pg 294

MERS TM – risk assessment index – Table 9-3 pg – 294

(http://www.mers-tm.net/ )

Causal Analysis

Root cause analysis on serious events VHA National Center for Patient Safety:

http://www.patientsafety.gov/tools.html Root cause analysis factors: (http://www.patientsafety.gov/concepts.html )

Human factors communication Human factors training Human factors fatigue/scheduling Environment and equipment Rules, policies, and procedures Barriers (safeguards)

Figure 9-1 page 297

Causal analysis

Eindhoven Classification model – fig 9-2 pg 299 Technical factors – equipment, software Organizational factors – policies, procedures,

protocols Human factors

Table 9-4, pg 300

Summary of domain areas for a common report format Box 9-2 pg 303 WHO has contracted with JCAHO for defining

standard reports

Implementation of the report format AHRQ should be given the lead to implement

the report format HL7 Patient Safety Special Interest Group Tools such as the one made available from

AIMS

De-identification and data protection External reports need to be de-identified Fear of law suits abound

Primary and secondary uses of report data Primary use to improve care processes Secondary use – epidemiological research,

public health, drug safety surveillance, Health Insurance bonus to physicians

Example of improvement in care process Ensuring Correct surgery directive of VHA Child health Accountability Initiative

Table 9-5 page 312