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Back to the future: Can conversation analysis be used to judge physicians' malpractice history?
Abstract:
In its monograph Crossing the Quality Chasm, the Institute of Medicine asserted that 44,000 to 98,000 lives are lost every year due to avoidable medical errors, more than 80% of which involved breakdowns in communication. Medical malpractice claims also involve errors that cause harm, including death. Reasons for malpractice claims have been investigated using variables such as age, race, country of origin, and gender none of which are predictive. One promising area that has not systematically been studied is the role of face-to-face communication in malpractice claims. To better understand this phenomenon, we tape-recorded 125 doctors (divided equally between surgeons and primary care practitioners), each with 10 consecutive patients. Half of these doctors had been sued at least twice, while the rest had never been sued. We then did a qualitative analysis based on a single taped encounter per doctor using conversation analysis (CA), in order to try to identify which doctors had claims or no-claims histories. While we were able to identify two out of every three no-claims primary care doctors, we were much less successful in identifying those with claims. Surprisingly, in the surgeon group, predictions based on CA were worse than by chance probability. We discuss the implications of our findings for the field of outcome-based communication analysis.
Insights
Communication breakdowns contribute to medical errors and malpractice claims. This study used conversation analysis to examine doctor-patient interactions, finding limited success in predicting malpractice history based on communication patterns.
Area of Science:
- Medical communication
- Healthcare quality
- Patient safety
Background:
- Medical errors, often due to communication failures, lead to significant patient harm and mortality.
- Medical malpractice claims frequently involve preventable errors, yet traditional demographic predictors are ineffective.
- The role of direct, face-to-face communication in malpractice claims remains under-investigated.
Purpose of the Study:
- To investigate the relationship between doctor-patient communication patterns and medical malpractice claims.
- To determine if conversation analysis (CA) can differentiate between physicians with and without malpractice histories.
Main Methods:
- 125 physicians (surgeons and primary care practitioners) were audio-recorded with 10 consecutive patients each.
- Half of the physicians had a history of at least two malpractice claims; the other half had none.
- Qualitative analysis using conversation analysis (CA) was performed on one recorded encounter per physician.
Main Results:
- Conversation analysis successfully identified two-thirds of primary care physicians without malpractice claims.
- Predictive accuracy was significantly lower for identifying physicians with malpractice claims.
- In the surgeon group, CA predictions performed worse than chance.
Conclusions:
- Face-to-face communication analysis shows potential for identifying physicians at lower risk for malpractice, particularly in primary care.
- Further research is needed to refine CA methods for predicting malpractice risk, especially in surgical specialties.
- Findings suggest communication patterns may be a factor in malpractice claims, but not a universally predictive one.
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