Do Poor People Sue Doctors More Frequently? Confronting Unconscious Bias and the Role of Cultural Competency

McClellan, Frank M.; White, Augustus A.; Jimenez, Ramon L.; Fahmy, Sherin M.

doi:10.1007/s11999-012-2254-2

Cited by 32 publications

(15 citation statements)

References 10 publications

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“…Previous reports demonstrate that race and ethnicity are not correlated with increased risk of litigation. 27,28 In fact, patients of low socioeconomic status and the uninsured actually sue their doctors 5 to 10 times less than patients of higher socioeconomic status. 27,28 The majority of neurosurgeons, regardless of state, believe that their coverage is inadequate (65%-71%), even though they are paying 15% to 20% of their annual income in insurance premiums.…”

Section: Discussionmentioning

confidence: 99%

Defensive Medicine in Neurosurgery

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Defensive Medicine in Neurosurgery

et al. 2015

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“…[3][4][5][6][7] Multiple comorbidities (ie, obesity, diabetes), limited access to care, lower socioeconomic status, and minority race status have been identified as major risk factors for complications and readmission in the arenas of bariatric surgery, cardiac surgery, and cardiology. [8][9][10] Few analyses have been performed looking specifically at global risk for readmission following orthopedic surgery. [11][12][13] This report analyzes the overall incidence and risk factors for readmission at a high-volume specialty institution, with a primary focus on race and socioeconomic status.…”

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confidence: 99%

No Evidence for Race and Socioeconomic Status as Independent Predictors of 30-Day Readmission Rates Following Orthopedic Surgery

et al. 2014

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The Centers for Medicare & Medicaid Services considers readmissions within 30 days of discharge to be a quality indicator. Hospitals' and eventually physicians' readmission rates will be used to determine payment for services. It is imperative that health care providers understand which patients are at risk for readmission so that they can apply the appropriate preventive interventions. The research team analyzed all orthopedic admissions and readmissions at their institution from September 2008 to April 2011 in this study. Preparing for the next stage in health care reform, identifying any preoperative factors that may place certain patients into a "high-risk" category for readmission following an orthopedic procedure is of paramount importance. This data analysis of more than 13 000 patients noted that race-based and income-based risk factors did not translate into significant risk factors or predictors of 30-day readmission following orthopedic admission.

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“…These findings are consistent with previously reported findings on risk difference by SES. 50 Cultural trends in claim rates by ethnicity may emerge with a larger sample. 51 Given the link between claims and clinical outcomes, in future analyses, it would be beneficial to collect data on longer term sequelae, such as chronic pain, which has previously been identified as a risk factor for claims.…”

Section: Discussionmentioning

confidence: 99%

Using patient factors to predict obstetric complaints and litigation: A mixed methods approach to quality improvement

Nowotny

Loh

Davies‐Tuck

et al. 2018

Journal of Patient Safety and Risk Management

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Background: Traditionally, managing patient complaints and medicolegal claims has been largely a reactive process. However, attention has recently turned to systematically learning from complaints and litigation to prevent recurrence. Within a high-volume maternity service, we explored whether developing predictive tools for patient complaints and litigation to support proactive management was feasible. Objectives: To develop and assess two screening tools to predict the likelihood of (i) patient complaints and/or (ii) medicolegal claims arising from maternity care and to assess practitioner awareness of patient risk factors. Methods: Births between 1 April 2011 and 30 April 2016 at a university hospital maternity service in Melbourne, Australia were considered. Univariate binary logistic regression was performed to identify the variables contributing to complaints and claims. Backwards-stepwise logistic regression was applied to develop each screening tool. Clinicians completed a survey to assess awareness of identified risk factors. Results: In the study period, there were 41,443 births, 173 complaints and 19 claims. The complaints tool had only fair predictive capacity (receiver operating characteristic 0.72, p < 0.001) and the claims tool failed. Neither approach afforded sufficient discrimination to be useful in routine predictive modelling. One hundred and one practitioners completed the survey (response rate 15.7%). Practitioners were better at recognising risk factors for legal claims than for patient complaints. Conclusion: Whilst new risk factors for patient complaints and medicolegal claims were identified, we were unable to develop a screening tool that was sufficiently discriminatory to be useful in routine predictive triaging. However, increasing practitioner awareness of key risk factors may afford opportunities to improve care quality.

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Do Poor People Sue Doctors More Frequently? Confronting Unconscious Bias and the Role of Cultural Competency

Cited by 32 publications

References 10 publications

Defensive Medicine in Neurosurgery

Defensive Medicine in Neurosurgery

No Evidence for Race and Socioeconomic Status as Independent Predictors of 30-Day Readmission Rates Following Orthopedic Surgery

Using patient factors to predict obstetric complaints and litigation: A mixed methods approach to quality improvement

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