Inside the Medical Malpractice Claim File

1
Inside the Medical Malpractice Claim File

• David Studdert
• University of Melbourne
• November 2008

2
Overview

• MIMEPS approach
• General findings
• Lessons learned

3
Malpractice Insurers Medical Error Prevention
Study (MIMEPS) Impetus for Project

• What opportunities exist in the malpractice
  system to leverage constructive contributions to
  error prevention?

4
Overview

• Traditionally, malpractice claims files avoided
  as source of data on errors strictly
  confidential, time lag, negligence-focused, and
  biased
• Several notable exceptions
• American Society of Anesthesia Closed Claims
  Project (ASACCP)
• Physician Insurers Association of America (PIAA)
• Kern et al. - studies of surgical errors using
  jury verdicts
• Unrealized potential as a reporting system

5
Malpractice Insurers Medical Error Prevention
Study Project Team
Troyen Brennan, MD, JD Ilina Chaudhuri, BA Tejal
Gandhi, MD, MPH Atul Gawande, MD, MPH Allen
Kachalia, MD, JD Mary Kwaan, MD Karen Lifford,
MD, MPH Michelle Mello, JD, PhD Tom McElrath, MD,
PhD

• Allison Nagy, BA
• Martin November, MD, MBA
• John Orav, PhD
• Eric Poon, MD, MPH
• Ann Louise Puopolo, BSN, RN
• Selwyn Rogers, MD, MPH
• David Studdert, LLB, ScD (PI)
• Eric Thomas, MD, MPH
• Nancy Wilkinson, BSN, RN
• Cathy Yoon, MS

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Funding support for MIMEPS

• Agency for Healthcare Research Quality
• Harvard Risk Management Foundation

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Five Malpractice Liability Insurers Participated

• Locations 2 Northeast, 1 Mid-Atlantic, 1
  Southwest, 1 West
• Coverage 33,000 physicians, 61 acute care
  hospitals (31 academic, 26 non-academic), and 428
  outpatient facilities

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MIMEPS Sample

• Claims selected randomly in 4 clinical categories
  which collectively account for 80 of claims
• Operative
• Obstetrics
• Missed / delayed diagnosis
• Medication
• Target number at each site based on annual claims
  volume
• Claim defined as formal demand for compensation

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Sequence of Review
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Summarizing the Error Judgment Process in MIMEPS
1. Was there an adverse outcome?
2. What caused the adverse outcome?

Rate the likelihood that a failure of _____
contributed to the adverse outcome. o o o o
o 1----------------2-----------------3--------
--------4-----------------5 Highly
Unlikely Somewhat Likely
Highly Likely
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Key Human Factors Under Investigation

• System Factors
• Lack of supervision
• Failure to follow / break) a protocol
• Interruptions
• Technology/equipment problems
• Fatigue
• Workload/inadequate staffing
• Ergonomic problems
• Patient Factors
• Clinical factors (e.g. difficult anatomy)
• Non-clinical / behavioral factors
• (e.g. missed appointment)

• Cognitive Factors
• Vigilance or memory
• Error in judgment
• Lack of technical competence /
• knowledge
• Other failing of individual clinician
• Communication Issues
• Inadequate hand-off
• No clear lines of responsibility
• Conflict
• Other failure of communication

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Summarizing the Error Judgment Process in MIMEPS
1. Was there an adverse outcome?
2. What caused the adverse outcome?

Rate the likelihood that a failure of _____
contributed to the adverse outcome. o o o o
o 1----------------2-----------------3--------
--------4-----------------5 Highly
Unlikely Somewhat Likely
Highly Likely
3. Was the adverse outcome due to error?
In light of your responses to the above questions
and all other relevant information in the claim
file, indicate your confidence that the adverse
outcome resulted from one or more errors. o
Little or no evidence (END REVIEW) o Slight to
modest evidence (END REVIEW) o Not quite likely
less than 50-50 but close call (END REVIEW) o
More likely than not more than 50-50 but close
call o Moderate/strong evidence o Virtually
certain evidence
4. Clinical details of error
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Overview

• MIMEPS approach
• General findings
• Lessons learned

14
Injury Types
15
Litigation Outcomes in MIMEPS Sample
Mean payment 2004
472,738
854,170
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Overview

• MIMEPS approach
• General findings
• Lessons learned

18
Lessons Learned from MIMEPS about Using
Malpractice Claim Files to Study Error

• Limitations
• Not all claims have identifiable errors
• Time lags
• Factual disputes
• Unmeasurable contributing factors

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Key Human Factors Under Investigation

• System Factors
• Lack of supervision
• Failure to follow / break a protocol
• Interruptions
• Technology/equipment problems
• Fatigue
• Workload/inadequate staffing
• Ergonomic problems
• Patient Factors
• Clinical factors (e.g. difficult anatomy)
• Non-clinical / behavioral factors
• (e.g. missed appointment)

• Cognitive Factors
• Vigilance or memory
• Error in judgment
• Lack of technical competence /
• knowledge
• Other failing of individual clinician
• Communication Issues
• Inadequate hand-off
• No clear lines of responsibility
• Conflict
• Other failure of communication

Patient factors
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Lessons Learned from MIMEPS about Using
Malpractice Claim Files to Study Error

• Limitations
• Not all claims have identifiable errors
• Time lags
• Factual disputes
• Unmeasurable contributing factors
• Strengths
• Reliability

21
Inter-Reviewer Reliability of Adverse Outcome
and Error Determinations

22
Lessons Learned from MIMEPS about Using
Malpractice Claim Files to Study Error

• Limitations
• Not all claims have identifiable errors
• Time lags
• Factual disputes
• Unmeasurable contributing factors
• Strengths
• Reliability
• Richness source of data on error causality

23
Physician reviewers assessments of the
comparative value of medical records
malpractice claims files in making judgments
about contributing factors
Mean scores from a 5-point Likert scale ranging
from No value (1) to Somewhat valuable (3)
to Indispensable (5)