Statistical models of outcome in malpractice lawsuits involving death or neurologically impaired infants

Bors-Koefoed, Roy; Zylstra, Samuel; Resseguie, Laurence J.; Ricci, Barbara; Kelly, Emer; Mondor, Maureen C.

doi:10.3109/14767059809020427

Cited by 3 publications

(3 citation statements)

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“…More recently, blood-brain barrier crossover issues, as measured in prairie voles, have been raised by Carter, Boone, Pournajafi-Nazarloo, and Bales (2009), whereby Pitocin exposure may trigger differential exposure to fetal hypoxia via alternations in maternal uterine contraction intensity. Pitocin induction and fetal distress (Akoury, 1991;Bidgood & Steer, 1987;Satin, 1992) has been implicated in fetal neurological impairment (Bors-Koefoed et al, 1998;Fein et al, 1997) and considered in autism (Fein et al, 1997, Waterhouse, Fein, & Modahl, 1996), yet overlooked with respect to ADHD sequelae. Prenatal stress can injure the immature fetal brain, causing significant neurological impairment (Hirst, Walker, Yawno, & Palliser, 2009).…”

Section: Neurodevelopmental Implicationsmentioning

confidence: 99%

Perinatal Pitocin as an Early ADHD Biomarker: Neurodevelopmental Risk?

Kurth

Haußmann

2011

J Atten Disord

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Section: Neurodevelopmental Implicationsmentioning

confidence: 99%

Perinatal Pitocin as an Early ADHD Biomarker: Neurodevelopmental Risk?

Kurth

Haußmann

2011

J Atten Disord

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“…Considering that the use of oxytocin during labor and delivery can lead to uterine tachysystole (previously hyperstimulation) [24] , that it has been found to have a negative impact on the probability of successfully defending a professional [9] , and its use, especially its misuse, has been alleged to be responsible for many, if not most of, adverse outcomes and professional liability suits involving abnormal labor [3,5,14] , it is surprising that so many variations continue to be in use despite our knowledge that standardized patterns are safer than many variations.…”

Section: Discussionmentioning

confidence: 99%

Reduction of cesarean delivery rates after implementation of a comprehensive patient safety program

Grünebaum

Dudenhausen

Chervenak

et al. 2012

Journal of Perinatal Medicine

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Aims: The objective of this paper was to review our institution ' s cesarean delivery rates starting in 2004 prior to the full implementation of a patient safety program including a uniform oxytocin policy until 2012 when the oxytocin policy and the safety program had been fully implemented. Results: Cesarean delivery rates at our institution decreased incrementally from 41.6 % in 2004 to 32.7 % in 2012. The decrease in cesarean delivery rates was observed for each of the fi ve age groups. Conclusion: Concerns about an increase in cesarean delivery rates after implementation of a comprehensive patient safety program including a standardized oxytocin protocol may be unfounded. Despite the increase of US national cesarean delivery rates, our study shows that it is possible to safely lower cesarean delivery rates without concomitant concerns of litigations.

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“…Therefore, a reliable prediction model for litigation outcomes in medical litigation research is critical for improving hospital management, which can effectively reduce plaintiff victory (medical doctor loss) [12]. However, such studies using conventional logistic regression models [13] or machine learning [14,15] to predict litigation outcomes involving medical doctors at the individual and system levels are limited. Systematic reviews have reported that prediction validity using machine learning is similar or slightly better than that of logistic regression models [16,17].…”

Section: Introductionmentioning

confidence: 99%

Impact of System and Diagnostic Errors on Medical Litigation Outcomes: Machine Learning-Based Prediction Models

2022

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No prediction models using use conventional logistic models and machine learning exist for medical litigation outcomes involving medical doctors. Using a logistic model and three machine learning models, such as decision tree, random forest, and light-gradient boosting machine (LightGBM), we evaluated the prediction ability for litigation outcomes among medical litigation in Japan. The prediction model with LightGBM had a good predictive ability, with an area under the curve of 0.894 (95% CI; 0.893–0.895) in all patients’ data. When evaluating the feature importance using the SHApley Additive exPlanation (SHAP) value, the system error was the most significant predictive factor in all clinical settings for medical doctors’ loss in lawsuits. The other predictive factors were diagnostic error in outpatient settings, facility size in inpatients, and procedures or surgery settings. Our prediction model is useful for estimating medical litigation outcomes.

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Statistical models of outcome in malpractice lawsuits involving death or neurologically impaired infants

Cited by 3 publications

References 0 publications

Perinatal Pitocin as an Early ADHD Biomarker: Neurodevelopmental Risk?

Perinatal Pitocin as an Early ADHD Biomarker: Neurodevelopmental Risk?

Reduction of cesarean delivery rates after implementation of a comprehensive patient safety program

Impact of System and Diagnostic Errors on Medical Litigation Outcomes: Machine Learning-Based Prediction Models

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