Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited.

Background: The increasing use of teleradiology has been accompanied by concerns relating to risk management and patient safety. Purpose: To compare characteristics of teleradiology and nonteleradiology radiology malpractice cases and identify contributing underlying these cases. Materials and Methods: In this retrospective analysis, a national database of medical malpractice cases was queried to identify cases involving telemedicine that closed between January 2010 and March 2022. Teleradiology malpractice cases were identified based on manual review of cases in which telemedicine was coded as one of the contributing factors. These cases were compared with nonteleradiology cases that closed during the same time period in which radiology had been determined to be the primary responsible clinical service. Claimant, clinical, and financial characteristics of the cases were recorded, and continuous or categorical data were compared using the Wilcoxon rank -sum test or Fisher exact test, respectively. Results: This study included 135 teleradiology and 3474 radiology malpractices cases. The death of a patient occurred more frequently in teleradiology cases (48 of 135 [35.6%]) than in radiology cases (685 of 3474 [19.7%]; P < .001). Cerebrovascular disease was more common final diagnosis in the teleradiology cases (13 of 135 [9.6%]) compared with the radiology cases (124 of 3474 [3.6%]; P = .002). Problems with communication among providers was a more frequent contributing factor in the teleradiology cases (35 of 135 [25.9%]) than in the radiology cases (439 of 3474 [12.6%]; P < .001). Teleradiology cases were more likely to close with indemnity payment (79 of 135 [58.5%]) than the radiology cases (1416 of 3474 [40.8%]; P < .001) and had a higher median indemnity payment than the radiology cases ($339 230 [IQR, $120 790-$731 615] vs $214 063 [IQR, $66 620-$585 424]; P = Conclusion: Compared with radiology cases, teleradiology cases had higher clinical and financial severity and were more likely to involve issues with communication.

BACKGROUND:Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited. OBJECTIVE:To measure AEs in the outpatient setting. DESIGN:Retrospective review of the electronic health record (EHR). SETTING:11 outpatient sites in Massachusetts in 2018. PATIENTS:3103 patients who received outpatient care. MEASUREMENTS:Using a trigger method, nurse reviewers identified possible AEs and physicians adjudicated them, ranked severity, and assessed preventability. Generalized estimating equations were used to assess the association of having at least 1 AE with age, sex, race, and primary insurance. Variation in AE rates was analyzed across sites. RESULTS:The 3103 patients (mean age, 52 years) were more often female (59.8%), White (75.1%), English speakers (90.8%), and privately insured (70.4%) and had a mean of 4 outpatient encounters in 2018. Overall, 7.0% (95% CI, 4.6% to 9.3%) of patients had at least 1 AE (8.6 events per 100 patients annually). Adverse drug events were the most common AE (63.8%), followed by health care-associated infections (14.8%) and surgical or procedural events (14.2%). Severity was serious in 17.4% of AEs, life-threatening in 2.1%, and never fatal. Overall, 23.2% of AEs were preventable. Having at least 1 AE was less often associated with ages 18 to 44 years than with ages 65 to 84 years (standardized risk difference, -0.05 [CI, -0.09 to -0.02]) and more often associated with Black race than with Asian race (standardized risk difference, 0.09 [CI, 0.01 to 0.17]). Across study sites, 1.8% to 23.6% of patients had at least 1 AE and clinical category of AEs varied substantially. LIMITATION:Retrospective EHR review may miss AEs. CONCLUSION:Outpatient harm was relatively common and often serious. Adverse drug events were most frequent. Rates were higher among older adults. Interventions to curtail outpatient harm are urgently needed. PRIMARY FUNDING SOURCE:Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.

BACKGROUNDAdverse events during hospitalization are a major cause of patient harm, as documented in the 1991 Harvard Medical Practice Study. Patient safety has changed substantially in the decades since that study was conducted, and a more current assessment of harm during hospitalization is warranted.METHODSWe conducted a retrospective cohort study to assess the frequency, preventability, and severity of patient harm in a random sample of admissions from 11 Massachusetts hospitals during the 2018 calendar year. The occurrence of adverse events was assessed with the use of a trigger method (identification of information in a medical record that was previously shown to be associated with adverse events) and from review of medical records. Trained nurses reviewed records and identified admissions with possible adverse events that were then adjudicated by physicians, who confirmed the presence and characteristics of the adverse events.RESULTSIn a random sample of 2809 admissions, we identified at least one adverse event in 23.6%. Among 978 adverse events, 222 (22.7%) were judged to be preventable and 316 (32.3%) had a severity level of serious (i.e., caused harm that resulted in substantial intervention or prolonged recovery) or higher. A preventable adverse event occurred in 191 (6.8%) of all admissions, and a preventable adverse event with a severity level of serious or higher occurred in 29 (1.0%). There were seven deaths, one of which was deemed to be preventable. Adverse drug events were the most common adverse events (accounting for 39.0% of all events), followed by surgical or other procedural events (30.4%), patient-care events (which were defined as events associated with nursing care, including falls and pressure ulcers) (15.0%), and health care-associated infections (11.9%).CONCLUSIONSAdverse events were identified in nearly one in four admissions, and approximately one fourth of the events were preventable. These findings underscore the importance of patient safety and the need for continuing improvement. (Funded by the Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.).

Objectives The relationship between medical malpractice risk and one of the fundamental characteristics of physician practice, clinical volume, remains undefined. This study examined how the annual and per-patient encounter medical malpractice claims risk varies with clinical volume. Methods Clinical volume was determined using health insurance charges and was linked at the physician level to malpractice claims data from a malpractice insurer. The annual medical malpractice claims risk was expressed as the percent of physicians with a malpractice claim, and the per-encounter medical malpractice claims risk was expressed as malpractice claims per 1000 patient encounters. Both of these malpractice claims risk metrics were analyzed as a function of clinical volume, using linear and spline regression. Results As clinical volume increased, the percent of physicians with a malpractice claim increased linearly. Among all physicians studied, for each decile increase in clinical volume, there was a 0.373% increase in physicians with a malpractice claim (95% confidence interval, 0.301%–0.446%; P < 0.0001). As clinical volume increased, the rate of malpractice claims per 1000 patient encounters decreased. This relationship between clinical volume and per-encounter claims risk was nonlinear. There was a clinical volume threshold, below which decreasing clinical volume was associated with increasing per-encounter claims risk, and above which claims risk no longer significantly varied with increases in clinical volume. Conclusions Clinical volume is a crucial determinant of physician malpractice risk, with higher-volume physicians having higher annual risk but lower per-encounter risk. Clinical volume data should be incorporated into analyses of malpractice risk.

BACKGROUND:Hospitalists practice in high-stakes and litigious settings. However, little data exist about the malpractice claims risk faced by hospitalists.OBJECTIVE:To characterize the rates and characteristics of malpractice claims against hospitalists.DESIGN, SETTING, AND PARTICIPANTS:An analysis was performed of malpractice claims against hospitalists, as well as against select other specialties, using data from a malpractice claims database that includes approximately 31% of US malpractice claims.MAIN OUTCOMES AND MEASURES:For malpractice claims against hospitalists (n = 1,216) and comparator specialties (n = 18,644): claims rates (using a data subset), percentage of claims paid, median indemnity payment amounts, allegation types, and injury severity.RESULTS:Hospitalists had an annual malpractice claims rate of 1.95 claims per 100 physician-years, similar to that of nonhospitalist general internal medicine physicians (1.92 claims per 100 physician-years), and significantly greater than that of internal medicine subspecialists (1.30 claims per 100 physician-years) (P < .001). Claims rates for hospitalists nonsignificantly increased during the study period (2009-2018), whereas claims rates for four of the five other specialties examined significantly decreased over this period. The median indemnity payment for hospitalist claims was $231,454 (interquartile range, $100,000-$503,015), significantly higher than the amounts for all the other specialties except neurosurgery. The greatest predictor of a hospitalist case closing with payment (compared with no payment) was an error in clinical judgment as a contributing factor, with an adjusted odds ratio of 5.01 (95% CI, 3.37-7.45).CONCLUSION:During the study period, hospitalist claims rates did not drop, whereas they fell for other specialties. Hospitalists' claims had relatively high injury severity and median indemnity payment amounts. The malpractice environment for hospitalists is becoming less favorable.

Information extraction (IE), the distillation of specific information from unstructured data, is a core task in natural language processing. For rare entities (<1% prevalence), collection of positive examples required to train a model may require an infeasibly large sample of mostly negative ones. We combined unsupervised- with biased positive-unlabeled (PU) learning methods to: 1) facilitate positive example collection while maintaining the assumptions needed to 2) learn a binary classifier from the biased positive-unlabeled data alone. We tested the methods on a real-life use case of rare (<0.42%) entity extraction from medical malpractice documents. When tested on a manually reviewed random sample of documents, the PU model achieved an area under the precision-recall curve of0.283 and Fj of 0.410, outperforming fully supervised learning (0.022 and 0.096, respectively). The results demonstrate our method's potential to reduce the manual effort required for extracting rare entities from narrative texts.

OBJECTIVE:To compare malpractice claim rates before and after participation in simulation training, which focused on team training during a high-acuity clinical case. METHODS:We performed a retrospective analysis comparing the claim rates before and after simulation training among 292 obstetrician-gynecologists, all of whom were insured by the same malpractice insurer, who attended one or more simulation training sessions from 2002 to 2019. The insurer provided malpractice claims data involving study physicians, along with durations of coverage, which we used to calculate claim rates, expressed as claims per 100 physician coverage years. We used three different time periods in our presimulation and postsimulation training claim rates comparisons: the entire study period, 2 years presimulation and postsimulation training, and 1 year presimulation and postsimulation training. Secondary outcomes included indemnity payment amounts, percent of claims paid, and injury severity. RESULTS:Compared with presimulation training, malpractice claim rates were significantly lower postsimulation training for the full study period (11.2 vs 5.7 claims per 100 physician coverage years; P<.001) and the 2 years presimulation and postsimulation training (9.2 vs 5.4 claims per 100 physician coverage years; P=.043). For the 1 year presimulation and postsimulation training comparison, the decrease in claim rates was nonsignificant (8.8 vs 5.3 claims per 100 physician coverage years; P=.162). Attending more than one simulation session was associated with a greater reduction in claim rates. Postsimulation claim rates for physicians who attended one, two, or three or more simulation sessions were 6.3, 2.1, and 1.3 claims per 100 physician coverage years, respectively (P<.001). Compared with presimulation training, there was no significant difference in the median or mean indemnity paid, percent of claims on which an indemnity payment was made, or median severity of injury after simulation training. CONCLUSION:We observed a significant reduction in malpractice claim rates after simulation training. Wider use of simulation training within obstetrics and gynecology should be considered.

BACKGROUND:Identifying characteristics of malpractice claims involving emergency medicine (EM) physicians allows leaders to develop patient safety initiatives to prevent future harm events.METHODS:A retrospective study was performed of paid/unpaid claims closed 2007 to 2016 from Comparative Benchmarking System. Claims were identified by physician specialty involved (EM, internal medicine, general surgery). Various characteristics were compared by physician specialty. Multivariable regression was performed to identify factors associated with claim payment, in which (1) physician specialty was included as a predictor and (2) only the subset involving EM physicians was analyzed.RESULTS:Of 54,772 claims, 2760 involved EM physicians, 5886 involved internists, and 3207 involved surgeons. Death was the most common severity among EM claims (34%). Diagnosis-related allegations accounted for 58%, higher than 42% and 11% of claims involving internists and surgeons, respectively (P < 0.0001). Thirty-one percent was paid. The median indemnity paid on behalf of any defendant was $206,261 (interquartile range $55,065-527,651). The most common final diagnoses were myocardial infarction (2%), pulmonary embolus (2%), and cardiac arrest (2%). Procedure-related claims were associated with increased payment likelihood (odds ratio 1.21, 95% confidence interval 1.10-1.34).CONCLUSION:Malpractice claims in EM are often diagnosis- or procedure related. Our findings suggest that diagnostic accuracy and procedural competency should shape future quality improvement work.

PURPOSE:To identify patient-, provider-, and claim-related factors of medical malpractice claims in which physician trainees were directly involved in the harm events.METHOD:The authors performed a case-control study using medical malpractice claims closed between 2012-2016 and contributed to the Comparative Benchmarking System database by teaching hospitals. Using the service extender flag, they classified claims as cases if physician trainees were directly involved in the harm events. They classified claims as controls if they were from the same facilities, but trainees were not directly involved in the harm events. They performed multivariable regression with predictor variables being patient and provider characteristics. The outcome was physician trainee involvement in harm events.RESULTS:From the original pool of 30,973 claims, there were 581 cases and 2,610 controls. The majority of cases involved residents (471, 81%). Cases had a statistically significant higher rate of having a trainee named as defendants than controls (184, 32% vs 233, 9%; P < .001). The most common final diagnosis for cases was puncture or laceration during surgery (62, 11%). Inadequate supervision was a contributing factor in 140 (24%) cases overall, with the majority (104, 74%) of these claims being procedure related. Multivariable regression analysis revealed that trainees were most likely to be involved in harm events in specialties such as oral surgery/dentistry and obstetrics-gynecology (OR = 7.99, 95% CI 2.93, 21.83 and OR = 1.85, 95% CI 1.24, 2.66, respectively), when performing procedures (OR = 1.58, 95% CI 1.27, 1.96), or when delivering care in the emergency room (OR = 1.65, 95% CI 1.43, 1.91).CONCLUSIONS:Among claims involving physician trainees, procedures were common and often associated with inadequate supervision. Training directors of surgical specialties can use this information to improve resident supervision policies. The goal is to reduce the likelihood of future harm events.

BACKGROUND:In the ambulatory setting, missed cancer diagnoses are leading contributors to patient harm and malpractice risk; however, there are limited data on the malpractice case characteristics for these cases.OBJECTIVE:The aim of this study was to examine key features and factors identified in missed cancer diagnosis malpractice claims filed related to primary care and evaluate predictors of clinical and claim outcomes.METHODS:We analyzed 2155 diagnostic error closed malpractice claims in outpatient general medicine. We created multivariate models to determine factors that predicted case outcomes.RESULTS:Missed cancer diagnoses represented 980 (46%) cases of primary care diagnostic errors, most commonly from lung, colorectal, prostate, or breast cancer. The majority (76%) involved errors in clinical judgment, such as a failure or delay in ordering a diagnostic test (51%) or failure or delay in obtaining a consult or referral (37%). These factors were independently associated with higher-severity patient harm. The majority of these errors were of high severity (85%).CONCLUSIONS:Malpractice claims involving missed diagnoses of cancer in primary care most often involve routine screening examinations or delays in testing or referral. Our findings suggest that more reliable closed-loop systems for diagnostic testing and referrals are crucial for preventing diagnostic errors in the ambulatory setting.

Background: As adoption and use of electronic health records (EHRs) grows in the United States, there is a growing need in the field of applied clinical informatics to evaluate physician perceptions and beliefs about the impact of EHRs. The meaningful use of EHR incentive program provides a suitable context to examine physician beliefs about the impact of EHRs.Objective: Contribute to the sparse literature on physician beliefs about the impact of EHRs in areas such as quality of care, effectiveness of care, and delivery of care.Methods: A cross-sectional online survey of physicians at two academic medical centers (AMCs) in the northeast who were preparing to qualify for the meaningful use of EHR incentive program.Results: Of the 1,797 physicians at both AMCs who were preparing to qualify for the incentive program, 967 completed the survey for an overall response rate of 54%. Only 23% and 27% of physicians agreed or strongly agreed that meaningful use of the EHR will help them improve the care they personally deliver and improve quality of care respectively. Physician specialty was significantly associated with beliefs; e. g., 35% of primary care physicians agreed or strongly agreed that meaningful use will improve quality of care compared to 26% of medical specialists and 21% of surgical specialists (p=0.009). Satisfaction with outpatient EHR was also significantly related to all belief items.Conclusions: Only about a quarter of physicians in our study responded positively that meaningful use of the EHR will improve quality of care and the care they personally provide. These findings are similar to and extend findings from qualitative studies about negative perceptions that physicians hold about the impact of EHRs. Factors outside of the regulatory context, such as physician beliefs, need to be considered in the implementation of the meaningful use of the EHR incentive program.

BACKGROUND Clinical decision support (CDS) is associated with improvement in quality and efficiency in healthcare delivery. The appropriate way to evaluate its effectiveness remains uncertain. METHODS We analyzed data from our electronic health record (EHR) measuring the display frequency of eight reminders for Coronary Artery disease and Type 2 Diabetes and their associated performance according to a predefined methodology. We propose two key performance indicators to measure their impact on a target population: the reminder performance (RP), and the number needed to remind (NNR), to evaluate the impact that Clinical decision support reminders have on the adherence to guideline derived CDS interventions on the entire patient population, and individual providers receiving the interventions. RESULTS Data were available for 116,027 patients and a total of 1,982,735 reminders were displayed to a subset of 65,516 patients during the study period from January 1 to December 31, 2010. The evaluation framework assessed provider acknowledgement of the CDS intervention, and the presence of the expected performance event while accounting for patients' exposure to the CDS reminders. The total RP was 2.7% while the average NNR was 3.1 for all the reminders under study. CONCLUSIONS The proposed framework to asses of CDS performance provides a novel approach to improve the design and evaluation of CDS interventions. The application of this methodology represents an indicator to understand the impact of CDS interventions and subsequent patient outcomes. Further research is required to evaluate the impact of these systems on the quality of care.

Objectives: To evaluate the impact on smoking status documentation of a payer-sponsored pay-for-performance (P4P) incentive that targeted a minority of an integrated healthcare delivery system's patients.Study Design: Three commercial insurers simultaneously adopted P4P incentives to document smoking status of their members with 3 chronic diseases. The healthcare system responded by adding a smoking status reminder to all patients' electronic health records (EHRs). We measured change in smoking status documentation before (2008-2009) and after (2010-2011) P4P implementation by patient P4P eligibility.Methods: The P4P-eligible patients were compared primarily with a subset of non P4P-eligible patients who resembled P4P-eligible patients and also with all non-P4P-eligible patients. Multivariate models adjusted for patient and provider characteristics and accounted for provider-level clustering and preimplementation trends.Results: Documentation increased from 48% of 207,471 patients before P4P to 71% of 227,574 patients after P4P. Improvement from 56% to 83% occurred among P4P-eligible patients (adjusted odds ratio [AOR], 3.6; 95% confidence interval [CI], 2.9-4.5) and from 56% to 80% among the comparable subset of non P4P-eligible patients (AOR, 3.0; 95% CI, 2.3-3.9). The difference in improvement between groups was significant (AOR, 1.3; 95% CI, 1.1-1.4; P = .009).Conclusions: A P4P incentive targeting a minority of a healthcare system's patients stimulated adoption of a systemwide EHR reminder and improved smoking status documentation overall. Combining a P4P incentive with an EHR reminder might help healthcare systems improve treatment delivery for smokers and meet "meaningful use" standards for EHRs.

It is not known whether narrative medical text directly reflects clinical reality. We have tested the hypothesis that the pattern of distribution of lexical concept of medication intensification in narrative provider notes correlates with clinical practice as reflected in electronic medication records. Over 29,000 medication intensifications identified in narrative provider notes and 444,000 electronic medication records for 82 anti-hypertensive, anti-hyperlipidemic and anti-hyperglycemic medications were analyzed. Pearson correlation coefficient between the fraction of dose increases among all medication intensifications and therapeutic range calculated from EMR medication records was 0.39 (p = 0.0003). Correlations with therapeutic ranges obtained from two medication dictionaries, used as a negative control, were not significant. These findings provide evidence that narrative medical documents directly reflect clinical practice and constitute a valid source of medical data.

Electronic medical records (EMRs) can improve many aspects of patient care(1). Utilization of electronic medical records is increasing and is particularly encouraged by recent federal legislation(2). However EMRs are not always used optimally. Concerns have been raised about inappropriate copying and pasting of information between provider notes(3, 4). Up to 50% of the content of progress notes may be copied from older documents(5, 6) and copying frequently leads to errors in documentation(6). However, whether copied text generally reflects the care delivered is not known. Lifestyle counseling improves outcomes in patients with diabetes and is recommended by treatment guidelines(7). Narrative provider notes are the primary source of information on whether lifestyle counseling was provided. However, if copying and pasting of note fragments does not reflect treatment, the information contained in narrative electronic documents may not be reliable. We therefore performed a retrospective study of over 5,000 patients with diabetes to determine the relationship between copied lifestyle counseling and glucose control.