Accurate and efficient identification of complex chronic conditions in the electronic health record (EHR) is an important but challenging task that has historically relied on tedious clinician review and oversimplification of the disease. Here we adapt methods that allow for automated "noisy labeling" of positive and negative controls to create a "silver standard" for machine learning to automate identification of systemic lupus erythematosus (SLE). Our final model, which includes both structured data as well as text processing of clinical notes, outperformed all existing algorithms for SLE (AUC 0.97). In addition, we demonstrate how the probabilistic outputs of this model can be adapted to various clinical needs, selecting high thresholds when specificity is the priority and lower thresholds when a more inclusive patient population is desired. Deploying a similar methodology to other complex diseases has the potential to dramatically simplify the landscape of population identification in the EHR.

Mesh terms

Electronic Health Records, Machine Learning, Lupus Erythematosus, Phenotype, Algorithms.

BACKGROUND: Procedural training is a required competency in internal medicine (IM) residency, yet limited data exist on residents experience of procedural training. OBJECTIVES: We sought to understand how gender impacts access to procedural training among IM residents. METHODS: A mixed-methods, explanatory sequential study was performed. Procedure volume for IM residents between 2016 and 2020 was assessed at two large academic residencies (Program A and Program B: 399 residents and 4,020 procedures). Procedural rates and actual versus expected procedure volume by gender were compared, with separate analyses by clinical environment (intensive care unit [ICU] or structured procedural service). Semistructured gender-congruent focus groups were conducted. Topics included identity formation as a proceduralist and the resident procedural learning experience, including perceived gender bias in procedure allocation. RESULTS: Compared with men, women residents performed disproportionately fewer ICU procedures per month at Program A (1.4 vs. 2.7; P < 0.05) but not at Program B (0.36 vs. 0.54; P = 0.23). At Program A, women performed only 47% of ICU procedures, significantly fewer than the 54% they were expected to perform on the basis of their time on ICU rotations (P < 0.001). For equal gender distribution of procedural volume at Program A, 11% of the procedures performed by men would have needed to have been performed by women instead. Gender was not associated with differences in the Program A structured procedural service (53% observed vs. 52% expected; P = 0.935), Program B structured procedural service (40% observed vs. 43% expected; P = 0.174), or in Program B ICUs (33% observed vs. 34% expected; P = 0.656). Focus group analysis identified that women from both residencies perceived that assertiveness was required for procedural training in unstructured learning environments. Residents felt that gender influenced access to procedural opportunities, ability to self-advocate for procedural experience, identity formation as a proceduralist, and confidence in acquiring procedural skills. CONCLUSION: Gender disparities in access to procedural training during ICU rotations were seen at one institution but not another. There were ubiquitous perceptions that assertiveness was important to access procedural opportunities. We hypothesize that structured allocation of procedures would mitigate disparities by allowing all residents to access procedural training regardless of self-advocacy. Residency programs should adopt structured procedural training programs to counteract inequities.

Objective

Little data exist regarding mortality in ankylosing spondylitis (AS). We assessed diagnoses associated with in-hospital mortality in AS using a population-based inpatient data set.

Methods

Data were abstracted from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample between 2007 and 2011. We identified AS admissions using International Classification of Diseases, Ninth Revision, Clinical Modification code 720.0. In-hospital mortality was the primary outcome. Logistic regression was used to evaluate the association between top diagnoses and in-hospital mortality. We performed a secondary analysis from the same years in all patients (with and without AS) with cervical spine (C-spine) fracture to determine whether AS was an independent risk factor for mortality.

Results

Between 2007 and 2011, we identified 12,484 admissions and 267 deaths in AS patients. C-spine fracture with spinal cord injury and sepsis had the highest odds of death, with odds ratios (ORs) of 13.43 (95% confidence interval [95% CI] 8.00-22.55, P < 0.0001) and 7.63 (95% CI 5.62-10.36, P < 0.0001), respectively. In the same time period, there were 53,606 C-spine fracture admissions, of which 408 were coded with AS. Among all C-spine fracture hospitalizations, an AS diagnosis was associated with inpatient death (OR 1.61 [95% CI 1.16-2.22], P = 0.004).

Conclusion

In AS patients admitted to the hospital, C-spine fracture is a leading cause of in-hospital mortality. Other diagnoses associated with mortality include sepsis, pneumonia, cardiovascular disease, and comorbid illnesses. Among all hospitalizations with C-spine fracture, AS was associated with increased odds of death. C-spine fracture-associated mortality warrants further study to elucidate risk factors in order to prevent such devastating fractures in AS patients.

IMPORTANCE: Case reports that externalize expert diagnostic reasoning are utilized for clinical reasoning instruction but are difficult to search based on symptoms, final diagnosis, or differential diagnosis construction. Computational approaches that uncover how experienced diagnosticians analyze the medical information in a case as they formulate a differential diagnosis can guide educational uses of case reports. OBJECTIVE: To develop a reasoning-encoded case database for advanced clinical reasoning instruction by applying natural language processing (NLP), a sub-field of artificial intelligence, to a large case report library. DESIGN: We collected 2525 cases from the New England Journal of Medicine (NEJM) Clinical Pathological Conference (CPC) from 1965 to 2020 and used NLP to analyze the medical terminology in each case to derive unbiased (not prespecified) categories of analysis used by the clinical discussant. We then analyzed and mapped the degree of category overlap between cases. RESULTS: Our NLP algorithms identified clinically relevant categories that reflected the relationships between medical terms (which included symptoms, signs, test results, pathophysiology, and diagnoses). NLP extracted 43,291 symptoms across 2525 cases and physician-annotated 6532 diagnoses (both primary and related diagnoses). Our unsupervised learning computational approach identified 12 categories of medical terms that characterized the differential diagnosis discussions within individual cases. We used these categories to derive a measure of differential diagnosis similarity between cases and developed a website ( universeofcpc.com ) to allow visualization and exploration of 55 years of NEJM CPC case series. CONCLUSIONS: Applying NLP to curated instances of diagnostic reasoning can provide insight into how expert clinicians correlate and coordinate disease categories and processes when creating a differential diagnosis. Our reasoning-encoded CPC case database can be used by clinician-educators to design a case-based curriculum and by physicians to direct their lifelong learning efforts.

Objective

To evaluate hypogammaglobulinaemia and risk of serious infectious adverse events in active lupus nephritis.

Methods

The Abatacept and Cyclophosphamide Combination Efficacy and Safety Study (ACCESS) compared abatacept with placebo in participants with lupus nephritis undergoing treatment with Euro-Lupus Nephritis low-dose cyclophosphamide. Serum IgG levels were assessed prior to initiation of treatment and throughout the trial. Hypogammaglobulinaemia was defined as IgG <450 mg/dL.

Results

Hypogammaglobulinaemia was observed in 16/102 (15.7%) participants prior to initiation of induction therapy for active lupus nephritis. Participants with nephrotic range proteinuria were more likely to have hypogammaglobulinaemia, and serum IgG levels were inversely correlated with urine protein to creatinine ratio (r=-0.42, p<0.0001). Following initiation of treatment for active lupus nephritis, additional participants developed hypogammaglobulinaemia by weeks 2-4. Serum IgG levels then increased, and all but one participant had serum IgG ≥450 mg/dL at 24 weeks. Hypogammaglobulinaemia was not associated with an increased risk of serious infectious adverse events.

Conclusions

In active lupus nephritis in ACCESS, hypogammaglobulinaemia was common and inversely correlated with proteinuria. Serum IgG levels were lowest in the weeks immediately following initiation of induction therapy, and subsequently improved by 24 weeks. Hypogammaglobulinaemia was not associated with serious infectious adverse events.

Trial registration

Objective Infection is a leading cause of morbidity and mortality in systemic lupus erythematosus (SLE). Therapeutic practices have evolved over the past 15 years, but effects on infectious complications of SLE are unknown. We evaluated trends in hospitalizations for severe and opportunistic infections in a population-based SLE study. Methods Data derive from the 2000 to 2011 United States National Inpatient Sample, including individuals who met a validated administrative definition of SLE. Primary outcomes were diagnoses of bacteremia, pneumonia, opportunistic fungal infection, herpes zoster, cytomegalovirus, or pneumocystis pneumonia (PCP). We used Poisson regression to determine whether infection rates were changing in SLE hospitalizations and used predictive marginals to generate annual adjusted rates of specific infections. Results We identified 361,337 SLE hospitalizations from 2000 to 2011 meeting study inclusion criteria. Compared to non-SLE hospitalizations, SLE patients were younger (51 vs. 62 years), predominantly female (89% vs. 54%), and more likely to be racial/ethnic minorities. SLE diagnosis was significantly associated with all measured severe and opportunistic infections. From 2000 to 2011, adjusted SLE hospitalization rates for herpes zoster increased more than non-SLE rates: 54 to 79 per 10,000 SLE hospitalizations compared with 24 to 29 per 10,000 non-SLE hospitalizations. Conversely, SLE hospitalizations for PCP disproportionately decreased: 5.1 to 2.5 per 10,000 SLE hospitalizations compared with 0.9 to 1.3 per 10,000 non-SLE hospitalizations. Conclusions Among patients with SLE, herpes zoster hospitalizations are rising while PCP hospitalizations are declining. These trends likely reflect evolving SLE treatment strategies. Further research is needed to identify patients at greatest risk for infectious complications. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Objective

Cognitive dysfunction and cardiovascular disease are common and debilitating manifestations of systemic lupus erythematosus (SLE). In this study, we evaluated the relationship between cardiovascular events, traditional cardiovascular risk factors, and SLE-specific risk factors as predictors of cognitive dysfunction in a large cohort of participants with SLE.

Methods

Subjects included 694 participants from the Lupus Outcomes Study (LOS), a longitudinal study of SLE outcomes based on an annual telephone survey querying demographic and clinical variables. The Hopkins Verbal Learning Test-Revised and the Controlled Oral Word Association Test were administered to assess cognitive function. Multiple logistic regression was used to identify cardiovascular events (myocardial infarction, stroke), traditional cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus, obesity, smoking), and SLE-specific risk factors (antiphospholipid antibodies [aPL], disease activity, disease duration) associated with cognitive impairment in year 7 of the LOS.

Results

The prevalence of cognitive impairment as measured by verbal memory and verbal fluency metrics was 15%. In adjusted multiple logistic regression analyses, aPL (odds ratio [OR] 2.10, 95% confidence interval [95% CI] 1.3-3.41), hypertension (OR 2.06, 95% CI 1.19-3.56), and a history of stroke (OR 2.27, 95% CI 1.16-4.43) were significantly associated with cognitive dysfunction. In additional analyses evaluating the association between these predictors and severity of cognitive impairment, stroke was significantly more prevalent in participants with severe impairment when compared to those with mild or moderate impairment (P = 0.036).

Conclusion

These results suggest that the presence of aPL, hypertension, and stroke are key variables associated with cognitive impairment, which may aid in identification of patients at greatest risk.

Objective

To explore the use of electronic health record (EHR) data to estimate surgery resident duty hours and monitor real time workload.

Design

Retrospective analysis of resident duty hours logged using a voluntary global positioning system (GPS)-based smartphone application compared to duty hour estimates by an EHR-based algorithm. The algorithm estimated duty hours using EHR activity data and operating room logs. A dashboard was developed through Plan-Do-Study-Act cycles for real-time monitoring of workload.

Setting

Single tertiary/quaternary medical center general surgery residency program with approximately 90 categorical, preliminary, and integrated residents at eight clinical sites.

Participants

Categorical, preliminary, and integrated surgery residents of all clinical years who volunteered to pilot a GPS application to track duty hours.

Results

Of 2,623 work periods by 59 residents were logged with both methods. EHR-estimated work periods started later than GPS logs (median 0.3 hours, interquartile range [IQR] -0.1 - 0.3); EHR-estimated work periods ended earlier than GPS logs (median 0.1 hours, IQR -0.7 - 0.3); and EHR-estimated duty hour totals were less than totals logged by GPS (median -0.3 hours, IQR -0.8 - +0.1). Overall correlation between weekly duty hours logged by EHR and GPS was 0.79. Correlations between the 2 systems stratified from PGY-1 through PGY-5 were 0.76, 0.64, 0.82, 0.87, and 0.83, respectively. The algorithm identified six 80-hour workweek violations (averaged over 4 weeks), while GPS logs identified 8. EHR-based duty hours and operational data were integrated into a dashboard to enable real time monitoring of resident workloads.

Conclusions

EHR-based estimation of surgical resident duty hours has good correlation with GPS-based assessment of duty hours and identifies most workweek duty hour violations. This approach allows for dynamic workload monitoring and may be combined with operational data to anticipate and prevent duty hour violations, thereby optimizing learning.

On June 24, 2022, the US Supreme Court ended constitutional protections for abortion, resulting in wide variability in access from severe restrictions in many states and fewer restrictions in others. Healthcare institutions capture information about patients pregnancy and abortion care and, due to interoperability, may share it in ways that expose their providers and patients to social stigma and potential legal jeopardy in states with severe restrictions. In this article, we describe sources of risk to patients and providers that arise from interoperability and specify actions that institutions can take to reduce that risk. Institutions have significant power to define their practices for how and where care is documented, how patients are identified, where data are sent or hosted, and how patients are counseled, and thus should protect patients privacy and ability to receive medical care that is safe and legal where it is performed.

Hepatitis B virus (HBV) reactivation in the setting of rituximab use is a potentially fatal but preventable safety event. The rate of HBV screening and proportion of patients at risk who receive antiviral prophylaxis in patients initiating rituximab is unknown.We analyzed electronic health record (EHR) data from 2 health systems, a university center and a safety net health system, including diagnosis grouper codes, problem lists, medications, laboratory results, procedures codes, clinical encounter notes, and scanned documents. We identified all patients who received rituximab between 6/1/2012 and 1/1/2016. We calculated the proportion of rituximab users with inadequate screening for HBV according to the Centers for Disease Control guidelines for detecting latent HBV infection before their first rituximab infusion during the study period. We also assessed the proportion of patients with positive hepatitis B screening tests who were prescribed antiviral prophylaxis. Finally, we characterized safety failures and adverse events.We included 926 patients from the university and 132 patients from the safety net health system. Sixty-one percent of patients from the university had adequate screening for HBV compared with 90% from the safety net. Among patients at risk for reactivation based on results of HBV testing, 66% and 92% received antiviral prophylaxis at the university and safety net, respectively.We found wide variations in hepatitis B screening practices among patients receiving rituximab, resulting in unnecessary risks to patients. Interventions should be developed to improve patient safety procedures in this high-risk patient population.