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.

Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness.

Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical evidence, which can be obtained from various sources, poses a challenge in collecting, appraising, and synthesizing the evidential information. Recent advancements in generative AI, exemplified by large language models, hold promise in facilitating the arduous task. However, developing accountable, fair, and inclusive models remains a complicated undertaking. In this perspective, we discuss the trustworthiness of generative AI in the context of automated summarization of medical evidence.

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.

Assessing the safety of new germicidal far-UVC technologies.

The COVID-19 pandemic underscored the crucial importance of enhanced indoor air quality control measures to mitigate the spread of respiratory pathogens. Far-UVC is a type of germicidal ultraviolet technology, with wavelengths between 200 and 235 nm, that has emerged as a highly promising approach for indoor air disinfection. Due to its enhanced safety compared to conventional 254 nm upper-room germicidal systems, far-UVC allows for whole-room direct exposure of occupied spaces, potentially offering greater efficacy, since the total room air is constantly treated. While current evidence supports using far-UVC systems within existing guidelines, understanding the upper safety limit is critical to maximizing its effectiveness, particularly for the acute phase of a pandemic or epidemic when greater protection may be needed. This review article summarizes the substantial present knowledge on far-UVC safety regarding skin and eye exposure and highlights research priorities to discern the maximum exposure levels that avoid adverse effects. We advocate for comprehensive safety studies that explore potential mechanisms of harm, generate action spectra for crucial biological effects and conduct high-dose, long-term exposure trials. Such rigorous scientific investigation will be key to determining safe and effective levels for far-UVC deployment in indoor environments, contributing significantly to future pandemic preparedness and response.

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

OBJECTIVE: Obtaining electronic patient data, especially from electronic health record (EHR) systems, for clinical and translational research is difficult. Multiple research informatics systems exist but navigating the numerous applications can be challenging for scientists. This article describes Architecture for Research Computing in Health (ARCH), our institution's approach for matching investigators with tools and services for obtaining electronic patient data. MATERIALS AND METHODS: Supporting the spectrum of studies from populations to individuals, ARCH delivers a breadth of scientific functions-including but not limited to cohort discovery, electronic data capture, and multi-institutional data sharing-that manifest in specific systems-such as i2b2, REDCap, and PCORnet. Through a consultative process, ARCH staff align investigators with tools with respect to study design, data sources, and cost. Although most ARCH services are available free of charge, advanced engagements require fee for service. RESULTS: Since 2016 at Weill Cornell Medicine, ARCH has supported over 1200 unique investigators through more than 4177 consultations. Notably, ARCH infrastructure enabled critical coronavirus disease 2019 response activities for research and patient care. DISCUSSION: ARCH has provided a technical, regulatory, financial, and educational framework to support the biomedical research enterprise with electronic patient data. Collaboration among informaticians, biostatisticians, and clinicians has been critical to rapid generation and analysis of EHR data. CONCLUSION: A suite of tools and services, ARCH helps match investigators with informatics systems to reduce time to science. ARCH has facilitated research at Weill Cornell Medicine and may provide a model for informatics and research leaders to support scientists elsewhere.

Comparing automated vs. manual data collection for COVID-specific medications from electronic health records.

INTRODUCTION: Data extraction from electronic health record (EHR) systems occurs through manual abstraction, automated extraction, or a combination of both. While each method has its strengths and weaknesses, both are necessary for retrospective observational research as well as sudden clinical events, like the COVID-19 pandemic. Assessing the strengths, weaknesses, and potentials of these methods is important to continue to understand optimal approaches to extracting clinical data. We set out to assess automated and manual techniques for collecting medication use data in patients with COVID-19 to inform future observational studies that extract data from the electronic health record (EHR). MATERIALS AND METHODS: For 4,123 COVID-positive patients hospitalized and/or seen in the emergency department at an academic medical center between 03/03/2020 and 05/15/2020, we compared medication use data of 25 medications or drug classes collected through manual abstraction and automated extraction from the EHR. Quantitatively, we assessed concordance using Cohen's kappa to measure interrater reliability, and qualitatively, we audited observed discrepancies to determine causes of inconsistencies. RESULTS: For the 16 inpatient medications, 11 (69%) demonstrated moderate or better agreement; 7 of those demonstrated strong or almost perfect agreement. For 9 outpatient medications, 3 (33%) demonstrated moderate agreement, but none achieved strong or almost perfect agreement. We audited 12% of all discrepancies (716/5,790) and, in those audited, observed three principal categories of error: human error in manual abstraction (26%), errors in the extract-transform-load (ETL) or mapping of the automated extraction (41%), and abstraction-query mismatch (33%). CONCLUSION: Our findings suggest many inpatient medications can be collected reliably through automated extraction, especially when abstraction instructions are designed with data architecture in mind. We discuss quality issues, concerns, and improvements for institutions to consider when crafting an approach. During crises, institutions must decide how to allocate limited resources. We show that automated extraction of medications is feasible and make recommendations on how to improve future iterations.

Assessment of Natural Sunlight Protection Provided by 10 High-SPF Broad-Spectrum Sunscreens and Sun-Protective Fabrics.

In 1978, the FDA Advisory Panel proposed both indoor and natural sunlight SPF testing methods but reverted to indoor testing only in 1993. Today's sunscreen sun protection and broad-spectrum claims are based on mandated clinical tests using solar simulators and in vitro spectrophotometers. This research evaluated the protection of 10 high-SPF (30-110), broad-spectrum sunscreen products, as well as 6 sun-protective fabrics against natural sunlight in Arequipa, Peru. Each of the 17 subjects was exposed to natural sunlight for 1 h and 59 min under clear skies, with temperatures and humidity similar to those in an indoor clinical laboratory. Test sites were photographed 16-24 h later. Four dermatologists evaluated the photographs for erythema and persistent pigment darkening (PPD). Perceptible sun-induced skin injury (sunburn and/or pigmentation) was detected at 97% of the sunscreen-protected scores. The most sun-sensitive subjects obtained the least erythema protection. The higher the SPF was, the higher the erythema protection, but the intensity of PPD was also higher. The 2 sunscreens using only FDA-approved sunscreen filters rated 30 SPF and 45+ SPF performed poorly: Eighty-one percent of the 136 scores were graded 1 minimal erythema dose or higher erythema, achieving, at a maximum, SPF of 5-7 in natural sunlight. Sun-protective fabrics tested provided excellent sun protection. The erythema and PPD observed through the sunscreens in less than 2 h are incongruous with the broad-spectrum, high-SPF sunscreen claims. Reapplying these sunscreens and staying in the sun longer, as stated on the product labels, would have subjected the subjects to even more UV exposure. High-SPF, broad-spectrum sunscreen claims based on indoor solar simulator testing do not agree with the natural sunlight protection test results.

Multi-laboratory study of hybrid diffuse reflectance spectroscopy to assess sunscreen SPF and UVA-PFs.

BACKGROUND: Proof-of-principle studies have established the use of Hybrid Diffuse Reflectance Spectroscopy (HDRS) methods to assess both Ultraviolet-A Protection Factor (UVA-PF) and Sun Protection Factor (SPF) indices in individual laboratories. METHODS: Multiple laboratories evaluated 23 emulsions and two spray sunscreen products to evaluate repeatability and accuracy of assessment of SPF and UVA-PF values, using HDRS test systems from various manufacturers using different designs. RESULTS: All of the laboratories reported similar SPF and UVA-PF values within a narrow range of values to establish the reliability of the HDRS methodology across laboratories, independent of equipment manufacturer or operator. CONCLUSION: HDRS test methodology provides a reliable objective instrumental estimation of sunscreen SPF and UVA-PF. These data were provided to ISO-TC217 WG7 to substantiate the ongoing development of an ISO Standard HDRS Method.

ReCiter: An open source, identity-driven, authorship prediction algorithm optimized for academic institutions.

Academic institutions need to maintain publication lists for thousands of faculty and other scholars. Automated tools are essential to minimize the need for direct feedback from the scholars themselves who are practically unable to commit necessary effort to keep the data accurate. In relying exclusively on clustering techniques, author disambiguation applications fail to satisfy key use cases of academic institutions. Algorithms can perfectly group together a set of publications authored by a common individual, but, for them to be useful to an academic institution, they need to programmatically and recurrently map articles to thousands of scholars of interest en masse. Consistent with a savvy librarian's approach for generating a scholar's list of publications, identity-driven authorship prediction is the process of using information about a scholar to quantify the likelihood that person wrote certain articles. ReCiter is an application that attempts to do exactly that. ReCiter uses institutionally-maintained identity data such as name of department and year of terminal degree to predict which articles a given scholar has authored. To compute the overall score for a given candidate article from PubMed (and, optionally, Scopus), ReCiter uses: up to 12 types of commonly available, identity data; whether other members of a cluster have been accepted or rejected by a user; and the average score of a cluster. In addition, ReCiter provides scoring and qualitative evidence supporting why particular articles are suggested. This context and confidence scoring allows curators to more accurately provide feedback on behalf of scholars. To help users to more efficiently curate publication lists, we used a support vector machine analysis to optimize the scoring of the ReCiter algorithm. In our analysis of a diverse test group of 500 scholars at an academic private medical center, ReCiter correctly predicted 98% of their publications in PubMed.

Ten principles for data sharing and commercialization.

Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop guidelines themselves. Through discussions with multiple stakeholders at various institutions, we have generated a set of guidelines with 10 key principles to guide the responsible and appropriate use and sharing of clinical data for the purposes of care and discovery. Industry, universities, and healthcare institutions can build upon these guidelines toward creating a responsible, ethical, and practical response to data sharing.

Origins and Evolution of Photocarcinogenesis Action Spectra, Including Germicidal UVC†.

Germicidal ultraviolet radiation (GUV) provides a means of dramatically reducing airborne spread of microorganisms in residential and workspace environments. Regarding design and use of GUV, both efficacy and safety data have accumulated over several decades, with a substantial increase of attention during the current COVID-19 pandemic. Considerations for skin and eye safety previously resulted in guidance on exposures in institutional and workplace settings. This report details the evolution of limits for skin exposures, with particular attention to the risk of skin neoplasia.

A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System.

BACKGROUND: Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories in electronic health record (EHR) systems, many institutions have reported gaps in EHR race data that hinder secondary use for population-level research focused on underserved populations. When evaluating race data available for research purposes, we found our institution's enterprise EHR contained structured race data for only 51% (1.6 million) of patients. OBJECTIVES: We seek to improve the availability and quality of structured race data available to researchers by integrating values from multiple local sources. METHODS: To address the deficiency in race data availability, we implemented a method to supplement OMB race values from four local sources-inpatient EHR, inpatient billing, natural language processing, and coded clinical observations. We evaluated this method by measuring race data availability and data quality with respect to completeness, concordance, and plausibility. RESULTS: The supplementation method improved race data availability in the enterprise EHR up to 10% for some minority groups and 4% overall. We identified structured OMB race values for more than 142,000 patients, nearly a third of whom were from racial minority groups. Our data quality evaluation indicated that the supplemented race values improved completeness in the enterprise EHR, originated from sources in agreement with the enterprise EHR, and were unbiased to the enterprise EHR. CONCLUSION: Implementation of this method can successfully increase OMB race data availability, potentially enhancing accrual of patients from underserved populations to research studies.

Role of Technology in Self-Assessment and Feedback Among Hospitalist Physicians: Semistructured Interviews and Thematic Analysis.

BACKGROUND: Lifelong learning is embedded in the culture of medicine, but there are limited tools currently available for many clinicians, including hospitalists, to help improve their own practice. Although there are requirements for continuing medical education, resources for learning new clinical guidelines, and developing fields aimed at facilitating peer-to-peer feedback, there is a gap in the availability of tools that enable clinicians to learn based on their own patients and clinical decisions. OBJECTIVE: The aim of this study was to explore the technologies or modifications to existing systems that could be used to benefit hospitalist physicians in pursuing self-assessment and improvement by understanding physicians' current practices and their reactions to proposed possibilities. METHODS: Semistructured interviews were conducted in two separate stages with analysis performed after each stage. In the first stage, interviews (N=12) were conducted to understand the ways in which hospitalist physicians are currently gathering feedback and assessing their practice. A thematic analysis of these interviews informed the prototype used to elicit responses in the second stage. RESULTS: Clinicians actively look for feedback that they can apply to their practice, with the majority of the feedback obtained through self-assessment. The following three themes surrounding this aspect were identified in the first round of semistructured interviews: collaboration, self-reliance, and uncertainty, each with three related subthemes. Using a wireframe, the second round of interviews led to identifying the features that are currently challenging to use or could be made available with technology. CONCLUSIONS: Based on each theme and subtheme, we provide targeted recommendations for use by relevant stakeholders such as institutions, clinicians, and technologists. Most hospitalist self-assessments occur on a rolling basis, specifically using data in electronic medical records as their primary source. Specific objective data points or subjective patient relationships lead clinicians to review their patient cases and to assess their own performance. However, current systems are not built for these analyses or for clinicians to perform self-assessment, making this a burdensome and incomplete process. Building a platform that focuses on providing and curating the information used for self-assessment could help physicians make more accurately informed changes to their own clinical practice and decision-making.

Global data of unprotected skin minimal erythema dose relationship to Individual Typology Angle.

BACKGROUND: Determination of the Minimal Erythema Dose (MEDu ) of unprotected skin is perhaps the most critical aspect of the Sun Protection Factor (SPF) value and disproportionately influences the SPF. Individual Typology Angle (ITA°), a skin reflectance measure of the skin's pigmentation, has been used by many clinical laboratories to estimate the MEDu values for SPF testing. METHODS: Individual Typology Angle and unprotected MEDu data on 9931 individuals were received from 12 laboratories located on 5 continents to determine MEDu values in prospective sunscreen testing studies. RESULTS: These data were compiled and normalized by laboratory (to account for differences in number of subjects within each laboratory). A polynomial regression best fits the relationship between ITA° and their MEDu and may be used to accurately predict the MEDu of an unknown test subject. CONCLUSION: The regression data have been incorporated into the latest ISO24444 (Cosmetics - Protection test methods - in vivo determination of the sun protection factor (SPF), 2019) in vivo Sunscreen testing method that must be utilized to determine a subject's provisional MEDu for the testing procedure. Use of this common ITA°-MEDu relationship will help to minimize SPF variability between testing laboratories due to use of widely varying MEDu values.

Replacing Paper Informed Consent with Electronic Informed Consent for Research in Academic Medical Centers: A Scoping Review.

Although experts have identified benefits to replacing paper with electronic consent (eConsent) for research, a comprehensive understanding of strategies to overcome barriers to adoption is unknown. To address this gap, we performed a scoping review of the literature describing eConsent in academic medical centers. Of 69 studies that met inclusion criteria, 81% (n=56) addressed ethical, legal, and social issues; 67% (n=46) described user interface/user experience considerations; 39% (n=27) compared electronic versus paper approaches; 33% (n=23) discussed approaches to enterprise scalability; and 25% (n=17) described changes to consent elections. Findings indicate a lack of a leading commercial eConsent vendor, as articles described a myriad of homegrown systems and extensions of vendor EHR patient portals. Opportunities appear to exist for researchers and commercial software vendors to develop eConsent approaches that address the five critical areas identified in this review.

Evaluation of sunscreen efficacy over time and re-application using hybrid diffuse reflectance spectroscopy.

BACKGROUND: In 2007, the FDA added requirements for sunscreens to be labeled "re-apply at least every 2 hours" based on very limited data. This study used hybrid diffuse reflectance spectroscopy (HDRS) to evaluate the persistence of protection by 80 minutes water-resistant sunscreen formulation with and without re-application, and with and without sweat-inducing activity over 6 hours. METHODS: Sunscreens were applied to subject's foreheads and backs, and they remained at rest or exercised to induce sweating in a heated environment. Efficacy of a sun protection factor (SPF 50) very water-resistant sunscreen was measured with HDRS instrumentation and ultraviolet (UV) photography to determine the sunscreen protection over time. RESULTS: The sunscreen maintained SPF 50 efficacy over 6 hours for the non-active group with a single application, and for 2 hours for the active group, dropping slowly to SPF 30 level after 6 hours of sweating. Re-application of sunscreen gave additive SPF, with two applications resulting in SPF >100 and three applications approximately SPF 150. UV photography was insensitive to the differences in protection detected with HDRS instrumentation. CONCLUSIONS: Sunscreen efficacy is maintained over time in the absence of sweating or rub-off. After two hours of sweating, an 80 minutes water-resistant sunscreen does not need to be re-applied "at least every 2 hours."

Evaluation of a REDCap-based Workflow for Supporting Federal Guidance for Electronic Informed Consent.

Adoption of electronic informed consent (eConsent) for research remains low despite evidence of improved patient comprehension, usability, and workflow processes compared to paper. At our institution, we implemented an eConsent workflow using REDCap, a widely used electronic data capture system. The goal of this study was to evaluate the extent to which the REDCap eConsent solution adhered to federal guidance for eConsent. Of 29 requirements derived from sixteen recommendations from the United States Office for Human Research Protections (OHRP) and Food and Drug Administration (FDA), the REDCap eConsent solution supported 24 (86%). To the best of our knowledge, this is among the first studies to evaluate an eConsent approach's support for federal guidance. Findings suggest use of REDCap may help other institutions overcome barriers to eConsent adoption, and that OHRP and FDA expand guidance to recommend eConsent solutions integrate with enterprise clinical and research information systems.

Implementation of Informatics to Support the NIH All of Us Research Program in a Healthcare Provider Organization.

The NIH All of Us Research Program, a national effort to collect biospecimens and health data for over one million participants from across the United States, requires participating healthcare provider organizations (HPOs) to use informatics tools maintained by the NIH to manage participant consent, biospecimen processing, physical measurements, and other workflows. HPOs also maintain distinct workflows for handling overlapping tasks within their individual aegis, which do not necessarily achieve seamless interoperability with NIH-maintained cloud-based systems. At our HPO, we implemented informatics to address gaps in enrollment workflows and hardware, clinical workflow integration, patient engagement, laboratory support, and study team reporting. In this case report we detail our approach to inform efforts at other institutions for the NIH All of Us Research Program and other studies.

A Method for Integrating Healthcare Provider Organization and Research Sponsor Systems and Workflows to Support Large-Scale Studies.

Healthcare provider organizations (HPOs) increasingly participate in large-scale research efforts sponsored by external organizations that require use of consent management systems that may not integrate seamlessly with local workflows. The resulting inefficiency can hinder the ability of HPOs to participate in studies. To overcome this challenge, we developed a method using REDCap, a widely adopted electronic data capture system, and novel middleware that can potentially generalize to other settings. In this paper, we describe the method, illustrate its use to support the NIHAll of Us Research Program and PCORI ADAPTABLE studies at our HPO, and encourage other HPOs to test replicability of the method to facilitate similar research efforts. Code is available on GitHub at https://github.com/wcmc-research-informatics/.

Evaluating sunscreen ultraviolet protection using a polychromatic diffuse reflectance device.

BACKGROUND: Sun protection factor (SPF) and UVA protection factor (UVA-PF) are determined using in vivo tests, with high exposures of subjects to ultraviolet (UV) radiation. Hybrid diffuse reflectance spectroscopy (HDRS) enables estimation of both indices using only trace amounts UVB. However, the equipment requires two expensive monochromators that must synchronously scan the spectrum. METHODS: An alternate approach was developed using a polychromatic source that illuminates the skin via a custom light guide array, and the diffuse reflected light is measured with a photomultiplier. The ratio of the diffuse reflectance with and without the sunscreen on the skin determines the polychromatic diffuse reflectance UVA-PF (PDRS UVA-PF0 ). This factor was used to adjust in vitro UV spectroscopy scans of the sunscreen (with and without UV exposure to assess photostability), to calculate SPF and UVA protection factors. Ten sunscreens were evaluated and compared to in vivo SPF and UVA-PF values. RESULTS: The data show an excellent correlation with known in vivo determinations. CONCLUSION: This polychromatic HDRS approach uses simpler, faster, and less expensive equipment to determine both UVA-PF and SPFs without high doses of UV radiation to the test subjects.