1. Survey of Medical Informatics CS 493 – Fall 2004 November 1, 2004 V. “Juggy” Jagannathan

2. Streamlining Patient Safety Reporting Part III: Patient Safety - Achieving a New Standard of Care. IOM Report

3. 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

4. Patient Safety Reporting Systems and Applications Chapter 8: Patient Safety - Achieving a New Standard of Care. IOM Report

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. Cycle of fear Figure 8-5 pg 266

13. 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.

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

15. Standardized Reporting Chapter 9: Patient Safety - Achieving a New Standard of Care. IOM Report

16. 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

17. 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

18. 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

19. 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

20. Australian approach Australian AIMS  Minimum data set of basic data  Detailed comprehensive information for events that resulted in harm to the patient

21. 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

22. 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.

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

24. Causal Analysis Root cause analysis on serious events VHA National Center for Patient Safety: http://www.patientsafety.gov/tools.html http://www.patientsafety.gov/tools.html Root cause analysis factors: (http://www.patientsafety.gov/concepts.html )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

25. 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

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

27. 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

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

29. 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

30. Example of improvement in care process Ensuring Correct surgery directive of VHA Child health Accountability Initiative  Table 9-5 page 312