An architecture for research computing in health to support clinical and translational investigators with electronic patient data

Nonadjuvanted Bivalent Respiratory Syncytial Virus Vaccination and Perinatal Outcomes

Importance

A nonadjuvanted bivalent respiratory syncytial virus (RSV) prefusion F (RSVpreF [Pfizer]) protein subunit vaccine was newly approved and recommended for pregnant individuals at 32 0/7 to 36 6/7 weeks' gestation during the 2023 to 2024 RSV season; however, clinical vaccine data are lacking.

Objective

To evaluate the association between prenatal RSV vaccination status and perinatal outcomes among patients who delivered during the vaccination season.

Design, Setting, and Participants

This retrospective observational cohort study was conducted at 2 New York City hospitals within 1 health care system among patients who gave birth to singleton gestations at 32 weeks' gestation or later from September 22, 2023, to January 31, 2024.

Exposure

Prenatal RSV vaccination with the RSVpreF vaccine captured from the health system's electronic health records.

Main Outcome and Measures

The primary outcome is preterm birth (PTB), defined as less than 37 weeks' gestation. Secondary outcomes included hypertensive disorders of pregnancy (HDP), stillbirth, small-for-gestational age birth weight, neonatal intensive care unit (NICU) admission, neonatal respiratory distress with NICU admission, neonatal jaundice or hyperbilirubinemia, neonatal hypoglycemia, and neonatal sepsis. Logistic regression models were used to estimate odds ratios (ORs), and multivariable logistic regression models and time-dependent covariate Cox regression models were performed.

Results

Of 2973 pregnant individuals (median [IQR] age, 34.9 [32.4-37.7] years), 1026 (34.5%) received prenatal RSVpreF vaccination. Fifteen patients inappropriately received the vaccine at 37 weeks' gestation or later and were included in the nonvaccinated group. During the study period, 60 patients who had evidence of prenatal vaccination (5.9%) experienced PTB vs 131 of those who did not (6.7%). Prenatal vaccination was not associated with an increased risk for PTB after adjusting for potential confounders (adjusted OR, 0.87; 95% CI, 0.62-1.20) and addressing immortal time bias (hazard ratio [HR], 0.93; 95% CI, 0.64-1.34). There were no significant differences in pregnancy and neonatal outcomes based on vaccination status in the logistic regression models, but an increased risk of HDP in the time-dependent model was seen (HR, 1.43; 95% CI, 1.16-1.77).

Conclusions and Relevance

In this cohort study of pregnant individuals who delivered at 32 weeks' gestation or later, the RSVpreF vaccine was not associated with an increased risk of PTB and perinatal outcomes. These data support the safety of prenatal RSVpreF vaccination, but further investigation into the risk of HDP is warranted.

Understanding enterprise data warehouses to support clinical and translational research: impact, sustainability, demand management, and accessibility

OBJECTIVES

Healthcare organizations, including Clinical and Translational Science Awards (CTSA) hubs funded by the National Institutes of Health, seek to enable secondary use of electronic health record (EHR) data through an enterprise data warehouse for research (EDW4R), but optimal approaches are unknown. In this qualitative study, our goal was to understand EDW4R impact, sustainability, demand management, and accessibility.

MATERIALS AND METHODS

We engaged a convenience sample of informatics leaders from CTSA hubs (n = 21) for semi-structured interviews and completed a directed content analysis of interview transcripts.

RESULTS

EDW4R have created institutional capacity for single- and multi-center studies, democratized access to EHR data for investigators from multiple disciplines, and enabled the learning health system. Bibliometrics have been challenging due to investigator non-compliance, but one hub's requirement to link all study protocols with funding records enabled quantifying an EDW4R's multi-million dollar impact. Sustainability of EDW4R has relied on multiple funding sources with a general shift away from the CTSA grant toward institutional and industry support. To address EDW4R demand, institutions have expanded staff, used different governance approaches, and provided investigator self-service tools. EDW4R accessibility can benefit from improved tools incorporating user-centered design, increased data literacy among scientists, expansion of informaticians in the workforce, and growth of team science.

DISCUSSION

As investigator demand for EDW4R has increased, approaches to tracking impact, ensuring sustainability, and improving accessibility of EDW4R resources have varied.

CONCLUSION

This study adds to understanding of how informatics leaders seek to support investigators using EDW4R across the CTSA consortium and potentially elsewhere.

Implementation of a commercial federated network of electronic health record data to enable sponsor-initiated clinical trials at an academic medical center

BACKGROUND

A commercial federated network called TriNetX has connected electronic health record (EHR) data from academic medical centers (AMCs) with biopharmaceutical sponsors in a privacy-preserving manner to promote sponsor-initiated clinical trials. Little is known about how AMCs have implemented TriNetX to support clinical trials.

FINDINGS

At our AMC over a six-year period, TriNetX integrated into existing institutional workflows enabled 402 requests for sponsor-initiated clinical trials, 14 % (n = 56) of which local investigators expressed interest in conducting. Although clinical trials administrators indicated TriNetX yielded unique study opportunities, measurement of impact of institutional participation in the network was challenging due to lack of a common trial identifier shared across TriNetX, sponsor, and our institution.

CONCLUSION

To the best of our knowledge, this study is among the first to describe integration of a federated network of EHR data into institutional workflows for sponsor-initiated clinical trials. This case report may inform efforts at other institutions.

Linking Patient Encounters across Primary and Ancillary Electronic Health Record Systems: A Comparison of Two Approaches

Background

To achieve scientific goals, researchers often require integration of data from a primary electronic health record (EHR) system and one or more ancillary EHR systems used during the same patient care encounter. Although studies have demonstrated approaches for linking patient identity records across different EHR systems, little is known about linking patient encounter records across primary and ancillary EHR systems.

Objectives

We compared a patients-first approach versus an encounters-first approach for linking patient encounter records across multiple EHR systems.

Methods

We conducted a retrospective observational study of 348,904 patients with 533,283 encounters from 2010 to 2020 across our institution's primary EHR system and an ancillary EHR system used in perioperative settings. For the patients-first approach and the encounters-first approach, we measured the number of patient and encounter links created as well as runtime.

Results

While the patients-first approach linked 43% of patients and 49% of encounters, the encounters-first approach linked 98% of patients and 100% of encounters. The encounters-first approach was 20 times faster than the patients-first approach for linking patients and 33% slower for linking encounters.

Conclusion

Findings suggest that common patient and encounter identifiers shared among EHR systems via automated interfaces may be clinically useful but not "research-ready" and thus require an encounters-first linkage approach to enable secondary use for scientific purposes. Based on our search, this study is among the first to demonstrate approaches for linking patient encounters across multiple EHR systems. Enterprise data warehouse for research efforts elsewhere may benefit from an encounters-first approach.

A method to automate the discharge summary hospital course for neurology patients

OBJECTIVE

Generation of automated clinical notes has been posited as a strategy to mitigate physician burnout. In particular, an automated narrative summary of a patient's hospital stay could supplement the hospital course section of the discharge summary that inpatient physicians document in electronic health record (EHR) systems. In the current study, we developed and evaluated an automated method for summarizing the hospital course section using encoder-decoder sequence-to-sequence transformer models.

MATERIALS AND METHODS

We fine-tuned BERT and BART models and optimized for factuality through constraining beam search, which we trained and tested using EHR data from patients admitted to the neurology unit of an academic medical center.

RESULTS

The approach demonstrated good ROUGE scores with an R-2 of 13.76. In a blind evaluation, 2 board-certified physicians rated 62% of the automated summaries as meeting the standard of care, which suggests the method may be useful clinically.

DISCUSSION AND CONCLUSION

To our knowledge, this study is among the first to demonstrate an automated method for generating a discharge summary hospital course that approaches a quality level of what a physician would write.

Beyond the Spreadsheet: Data Management for Physicians in the Era of Big Data

Big Data is transforming health care. Characteristics of Big Data require data management strategies to effectively use, analyze, and apply the data. Clinicians are not typically learned in the fundamentals of these strategies which may cause a divide between collected data and data used. This article introduces the fundamentals of Big Data management and encourages clinicians to work with their information technology partners to further understand these processes and to identify opportunities for collaboration.

The International Classification of Diseases, 10 th Edition, Clinical Modification (ICD-10-CM) Code I16.0 Accurately Identifies Patients with Hypertensive Urgency

Objective

Hypertensive urgency, defined as acutely elevated BP without target organ damage, is associated with an increased risk of adverse cardiovascular events and accounts for a substantial proportion of national emergency department (ED) visits. To advance research in this space, we sought to validate the new ICD-10-CM diagnostic code for hypertensive urgency within a single healthcare system.

Methods

We performed a retrospective chart-review study of ED encounters at Weill Cornell Medicine from 2016 â€" 2021. We randomly selected 25 encounters with the ICD-10-CM code I16.0 as the primary discharge diagnosis and 25 encounters with primary ICD-10-CM discharge diagnosis codes for benign headache disorders. A single board-certified vascular neurologist reviewed all 50 encounters while blinded to the assigned ICD-10-CM codes to identify cases of hypertensive urgency. We calculated the sensitivity, specificity, and positive predictive values of the ICD-10-CM code I16.0 with 95% confidence intervals (CI).

Results

Out of 50 randomly selected ED encounters, 24 were adjudicated as hypertensive urgency. All encounters adjudicated as hypertensive urgency had been assigned the ICD-10-CM discharge diagnosis code of I16.0. All 25 of the encounters adjudicated as headache were assigned an ICD-10-CM discharge diagnosis code for a benign headache disorder. The ICD-10-CM code for hypertensive urgency, I16.0, was thus found to have a sensitivity of 100% (95% CI: 86-100%), specificity of 96% (95% CI: 80-100%), and positive predictive value of 96% (95% CI: 78-99%).

Conclusion

We found that the new ICD-10-CM code for hypertensive urgency, I16.0, can reliably identify patients with this condition.