Electronic Medical Records Research Articles

How Automation in Electronic Medical Records Can Lead to Errors in Dermatology

The integration of electronic health records has revolutionized healthcare by facilitating communication among providers, but it has also introduced significant challenges. In dermatology, a particular issue arises with the use of electronic medical record (EMR) systems that employ auto-populated fields on digital pathology requisition forms (RFs) for skin biopsies. These systems allow for the rapid selection of pre-set descriptions and differential diagnoses, which, while timesaving, frequently lead to diagnostic inaccuracies and potentially detrimental impacts on patient care. Dermatopathologists often receive biopsy specimens with RFs that list multiple provisional diagnoses based on generic, EMR-generated descriptions, which may not accurately represent the patient’s condition. This practice hampers the ability of dermatopathologists to perform effective clinicopathologic correlation, crucial for accurate diagnosis. We highlight that the convenience of EMR systems can discourage clinicians from recording detailed, accurate clinical observations. Consequently, this lack of detailed documentation prevents dermatopathologists from making informed diagnoses by correlating histologic features with clinical appearances. The current practice of using EMRs without consideration for their clinical relevance not only wastes healthcare resources but also poses a significant medico-legal risk. Therefore, refining EMR practices and integrating more comprehensive clinical data will ensure greater accuracy in dermatological diagnoses.

Using the PROMOTE Screener to Identify Psychosocial Risk Factors for Prenatal Substance Use

Introduction There is an urgent need to improve the identification of psychosocial vulnerabilities in clinical practice (eg, stress, unstable living conditions) and examine their contribution to prenatal substance use, especially for legal substances such as alcohol, tobacco, and recently, cannabis. Methods We conducted a retrospective chart review of 1842 patients who completed the PROMOTE screening instrument during their first prenatal visit to outpatient clinics of a New York State health system in 6/2019–11/2020. The PROMOTE includes 18 core items to assess psychosocial vulnerabilities including the NIDA Quick Screen assessing past year substance use. Outcomes were tobacco, cannabis, and alcohol use during pregnancy based on electronic medical record abstraction including clinical notes, self-report, or urine toxicology. Results A total of 188 (10.2%) patients used at least 1 substance prenatally, including 132 (7.2%) tobacco, 50 (2.7%) cannabis, and 45 (2.4%) alcohol. Two of the NIDA Quick Screen items (past year tobacco use and past year illegal drug use) were associated in the bivariate analysis with greater use risk of all 3 substances. Additional risk factors uniquely associated with specific prenatal substance use variables include low education predicting tobacco use (adjusted odds ratio [AOR] = 2.74, 95% confidence interval [CI] = 1.43–5.23), being unpartnered predicting cannabis use (AOR = 3.37, 95% CI = 1.21–9.39), and major life events predicting alcohol use (AOR = 3.25, 95% CI = 1.439–7.38). Conclusions Utilizing brief psychosocial self-screening instruments such as the PROMOTE can help identify and refer at-risk patients to appropriate care. Particular attention should be paid to life context including partner support, emotional health, stress, and past year substance use.

Predicting individual patient and hospital-level discharge using machine learning

Abstract Background Accurately predicting hospital discharge events could help improve patient flow and the efficiency of healthcare delivery. However, using machine learning and diverse electronic health record (EHR) data for this task remains incompletely explored. Methods We used EHR data from February-2017 to January-2020 from Oxfordshire, UK to predict hospital discharges in the next 24 h. We fitted separate extreme gradient boosting models for elective and emergency admissions, trained on the first two years of data and tested on the final year of data. We examined individual-level and hospital-level model performance and evaluated the impact of training data size and recency, prediction time, and performance in subgroups. Results Our models achieve AUROCs of 0.87 and 0.86, AUPRCs of 0.66 and 0.64, and F1 scores of 0.61 and 0.59 for elective and emergency admissions, respectively. These models outperform a logistic regression model using the same features and are substantially better than a baseline logistic regression model with more limited features. Notably, the relative performance increase from adding additional features is greater than the increase from using a sophisticated model. Aggregating individual probabilities, daily total discharge estimates are accurate with mean absolute errors of 8.9% (elective) and 4.9% (emergency). The most informative predictors include antibiotic prescriptions, medications, and hospital capacity factors. Performance remains robust across patient subgroups and different training strategies, but is lower in patients with longer admissions and those who died in hospital. Conclusions Our findings highlight the potential of machine learning in optimising hospital patient flow and facilitating patient care and recovery.

Testing the Feasibility of a Digital Point of Care Solution for the Trusted Near Real-Time Bidirectional Exchange of Novel and Informative Adverse Event Information

AbstractA digital point-of-care solution was implemented to test the feasibility of near-real-time bi-directional communication between pharmacovigilance experts (PVEs) and healthcare professionals (HCPs) for exchanging unique and informative adverse event (AE) information. The solution was implemented in a commercially available electronic health record (EHR) system/platform, no direct contact between PVEs and the HCPs was possible. The Clinical Affairs team of the EHR vendor was used as an intermediary to ensure appropriate information was exchanged while protecting HCP and patient privacy. The study yielded 9 drug-event pairs of interest (AEI), 2 of which were confirmed as AEs by the HCP. On average it took 20.6 h to receive initial AEI information and 58.8 h to receive follow-up information, which represents a 96% reduction in time compared to current methods. Both interactions provided unique data that would not have been collected otherwise leading to the PVE being able to appropriately determine a potential causal association. This study successfully demonstrated the feasibility of using a compliant, bi-directional, digitally enabled clinical communication channel at the point of care to complement existing pharmacovigilance activities.

Safety and Efficacy of Teclistamab in Patients With Relapsed or Refractory AL Amyloidosis

ABSTRACTIntroductionTeclistamab has demonstrated deep responses in patients with multiple myeloma in the MajesTEC‐1 study. However, the safety and efficacy of teclistamab in patients with AL amyloidosis are unknown.MethodsWe retrospectively analyzed patients with biopsy‐proven relapsed/refractory AL amyloidosis who were treated with teclistamab from December 2022 to February 2024 at the University of Pennsylvania. The data cutoff was 2/29/24. Adverse events (AE) were extracted from the electronic medical record. Patients were assessed for hematologic and organ response per consensus guidelines.ResultsEight patients were included in this case series: median age 63 (range 59–67), 75% female, 88% White. All eight patients achieved at least very good partial response (VGPR) and had normalization of free light chains (FLC), and six (75%) patients achieved undetectable FLC levels. Of the six patients with immunofixation completed, all six (100%) achieved hematologic complete response (hCR). The median time to hematologic VGPR and hCR was 13 days (range 12–18 days) and 88 days (range 32–150 days), respectively. The median duration of follow‐up was 8.5 months (range 1–14 months). Of the five patients with cardiac involvement, four (80%) achieved a cardiac response. Of the seven patients with renal involvement, two patients already achieved renal response prior to teclistamab, and of the remaining five, three (60%) achieved renal response. Six patients (75%) developed low‐grade cytokine release syndrome (CRS). No patients developed ICANS. Neutropenia and AKI both occurred in 25% of patients, respectively.ConclusionsIn this series of patients, teclistamab showed outstanding depth of response and was well‐tolerated. Teclistamab shows promise in treating patients with relapsed AL amyloidosis.

Living in the vicinity of pesticide-treated crop fields: Exploring associated perceptions and psychological aspects in relation to self-reported and registry-based health symptoms.

Exposure to pesticides in the living environment can be associated with the prevalence of health symptoms. This study investigates associations between health symptoms among residents in areas with fruit crop fields where pesticides are applied, and psychological perceptions and attitudes about environmental aspects and exposures. A cross-sectional survey combined with routine primary care electronic health records (EHR) data was conducted in 2017 in rural areas of the Netherlands with high concentration of fruit crops (n = 3,321, aged ≥ 16 years). Individual exposure to pesticides was estimated using geocoded data on fruit crops around the home. Validated instruments were used to assess symptom report and psychological perceptions and attitudes. Annual prevalence of various health symptoms was derived from EHRs. Multilevel regression models were used to analyze associations between health symptoms (outcome), fruit crops, and multiple psychological perceptions and attitudes (confounders). Living in the vicinity of fruit crop fields was generally not associated with self-reported symptom duration and general practitioner (GP) registered symptoms. For self-reported symptoms, symptom prevalence decreased when crop density within 250m and 500m from the home increased. No associations were found at other distances. Furthermore, higher levels of environmental worries, perceived exposure, and perceived sensitivity to pesticides and attribution of symptoms to environmental exposures were generally associated with a higher number of self-reported symptoms, and longer symptom duration. Symptoms reported to GPs were not associated with psychological perceptions and attitudes, except for perceived sensitivity to pesticides. Psychological perceptions and attitudes appear to be related to self-reported symptoms, but not to GP-registered symptoms, independent of the actual levels of exposure as measured by the size of the area of crop fields. Perceptions about environmental factors should be taken into account in environmental health risk assessment research when studying health symptoms.

Assessing the interdependency among effectiveness, satisfaction and efficient use of the Lightwave Health Information Management System (LHIMS) by health professionals in Ghana.

The success of an electronic health records (EHR) system is dependent on the effectiveness, satisfaction, and efficient use of these systems by health professionals. This paper explores the interdependency among effectiveness, satisfaction, and efficient use of Lightwave Health Information Management Systems (LHIMS) which is an EHR by health professionals. A non-interventional descriptive cross-sectional study design was employed for this research. The study used stratified random sampling for the selection of participants. The population for the study was all the health professionals in the Central Region of Ghana. The number of health professionals who responded to the questions was 1126. The findings suggest that understanding the interdependency of efficiency, effectiveness and satisfaction is crucial for the successful implementation and adoption of LHIMS in healthcare organisations. The study investigated the interdependence among effectiveness, satisfaction, and efficient use of the LHIMS by health professionals, and found a positive but weak significant relationship between these factors. Inconclusion, this study aimed to assess the interdependency among effectiveness, satisfaction, and efficient use of LHIMS by health professionals. The. results support a positive but weak significant relationship between satisfaction, effectiveness, and efficient use of the LHIMS. These findings have implications for policymakers and hospital management in their efforts to improve the use of LHIMS. Policymakers can focus on any one of the three usability areas to enhance LHIMS use, with visible effects across the other two domains.

Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores.

Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized. To characterize the individual-level agreement of CHD PRSs that perform similarly at the population level. Cross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data. Polygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples. PRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ. A total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement. CHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians.

Examining the Information Security Awareness Levels of Healthcare Workers and Their Attitudes Towards the Privacy of Electronic Health Records

Examining the Information Security Awareness Levels of Healthcare Workers and Their Attitudes Towards the Privacy of Electronic Health Records

High blood pressure in the emergency department as an opportunistic screening tool for detection of hypertension.

Hypertension is the most preventable cause of morbidity and mortality, but many individuals are underdiagnosed and lack treatment control. High blood pressure (BP) in the emergency department (ED) is commonly observed, but mostly used for short-term evaluation. We aimed to study the usefulness of high BP in the ED as a screening tool for undiagnosed hypertension. We used the electronic medical record system to identify all patients that had attended the ED at a university hospital from 2018-01-01 to 2018-03-31 and from 2018-07-01 to 2018-09-30 with an obtained systolic BP ≥ 160 and/or diastolic BP ≥ 100 mmHg measured at the ED. We excluded patients with previously diagnosed hypertension and patients on BP-lowering medication. All patients identified where contacted two years after attending the ED, with a letter of consent and a questionnaire regarding diagnosis of hypertension and current medication. 5424 patients attended the ED during the 6-months-period. 271 patients met the inclusion criteria and were asked to participate. 167 individuals (62%) agreed to participate and responded to the questionnaire. Mean age of participants were 63.1 years and 51% were women. 134 patients (80%) had measured their BP after the ED-visit, and 48 (36%) of those had been diagnosed with hypertension. 96% of patients diagnosed with hypertension were on BP-lowering medication. To follow-up BP ≥ 160/100 mmHg after an ED visit can reveal undiagnosed hypertension in one third of the patients. Given the amount of undiagnosed hypertension, an ED-measured BP might provide an important tool to detect and start treatment of hypertension.

The digital health landscape at children’s hospitals in Canada

ABSTRACT Objectives Canadian hospitals have historically lagged behind peer nations in terms of adoption of digital health tools. The aim of this study was to assess the current state of adoption of digital health tools at children’s hospitals in Canada. Methods We conducted an online survey of Canadian pediatric tertiary-care hospitals between January and July 2023. The 35-item questionnaire was administered in English and French. Hospital characteristics, informatics infrastructure data and electronic health record (EHR) functionality data were summarized using descriptive statistics. Results The survey was completed by 15 of the 17 (88.2%) pediatric hospitals in Canada. All institutions had an EHR with 10 (66.6%) being fully digitized and five (33.3%) being partially digitized. Funding and availability of clinicians with expertise in clinical informatics were cited as barriers to implementing digital health tools. The availability of core EHR functionalities ranged from 53.3% for medication to 100% for the presence of a laboratory and radiology information system. Only five (33.3%) institutions reported that they had a patient portal. Discussion While all hospitals in this study had an EHR, functionalities varied greatly between centers. Canada lags behind the United States in terms of adoption of digital health tools such as patient portals likely due to governmental mandates and incentives, and a focus on cultivating a physician informatics workforce. Conclusion Canadian pediatric hospitals lag behind peer institutions in digital maturity. This study highlights the perceived need from hospitals for policies, funding, and resources from the Canadian government to help increase the uptake of comprehensive EHRs.

A Qualitative Study of School Mental Health Providers’ Experiences with Chart Notes: Perceived Utility, Burden, and Areas for Growth

ABSTRACT Background Despite the ubiquity of chart notes and their well-known impact on medical providers’ job stress and satisfaction, little is known about how mental health providers interact with and are impacted by documentation requirements, particularly in school environments. Objective This qualitative study sought to investigate school mental health providers’ perspectives on and experiences with documentation. Method Four focus groups with eight school mental health providers were conducted. Providers were asked about their current documentation practices and desired changes to their electronic health record system. Recordings of focus groups were transcribed and analyzed for themes using a rapid qualitative analytic approach. Results Key themes revolved around the purpose, features, time demands, training needs, and writing processes surrounding chart notes. Providers reported spending substantial time and energy on documentation and viewed chart notes primarily as a billing requirement, but also valued their utility for treatment planning, outcome monitoring, and clinical accountability. Providers expressed frustration with redundant data entry, lack of protected time for documentation, insufficient training for and communication around updates to documentation requirements, and strained interactions with supervisors during editing. Providers highlighted scheduling protected work time for documentation, enhancing documentation training with a focus on habit formation, standardizing supervisory expectations and providing documentation specific training for supervisors, and redesigning electronic health record interfaces with automation and checklists as strategies that could improve their experiences with chart notes. Conclusions Providers highlighted the ways current training and supervision practices, time constraints, and electronic health record functionality contribute to job stress and burnout while also noting the value of documentation for treatment planning and processing difficult emotions. Roadmaps outlining further research that is needed to understand these suggestions from providers in the larger context of clinical documentation, as well their potential benefits and tradeoffs for providers and other stakeholders, are discussed.

Estimated clinical utility of multi-gene pharmacogenetic testing in a retrospective cohort of gynecology patients.

This study aimed to estimate the clinical utility of performing multi-gene pharmacogenetic testing on patients undergoing gynecologic surgery/procedure by evaluating the prescribing rate of Clinical Pharmacogenetics Implementation Consortium (CPIC) level A medications and frequency of drug-gene interactions (DGIs). The electronic health record was queried for 76 current procedural terminology codes to identify gynecologic surgeries/procedures that occurred between 1 January 2015 to 31 December 2020 in patients with at least one of 152 international classification of disease codes. Prescription data for CPIC level A medications was extracted. Those enrolled in the Penn Medicine Biobank were assessed for DGIs. The cohort consisted of 7798 female patients and 682 were in the biobank. Up to 6 years following their surgery or procedure, 80% were ordered ≥1 CPIC level A medication. Over half (54%) of these medications were ordered within 3 days after their surgery or procedure. The most common CPIC level A medications ordered were ibuprofen (57%) and ondansetron (42%). Overall, 7% of the cohort had ≥1 known or predicted DGI with medications they were prescribed. Multi-gene pharmacogenetic testing may be beneficial to gynecologic surgery/procedure patients by assisting clinicians with prescribing postoperative analgesics and future medications.

Critical Data for Critical Care: A Primer on Leveraging Electronic Health Record Data for Research From Society of Critical Care Medicine’s Panel on Data Sharing and Harmonization

A growing body of critical care research draws on real-world data from electronic health records (EHRs). The bedside clinician has myriad data sources to aid in clinical decision-making, but the lack of data sharing and harmonization standards leaves much of this data out of reach for multi-institution critical care research. The Society of Critical Care Medicine (SCCM) Discovery Data Science Campaign convened a panel of critical care and data science experts to explore and document unique advantages and opportunities for leveraging EHR data in critical care research. This article reviews and illustrates six organizing topics (data domains and common data elements; data harmonization; data quality; data interoperability and digital infrastructure; data access, sharing, and governance; and ethics and equity) as a data science primer for critical care researchers, laying a foundation for future publications from the SCCM Discovery Data Harmonization and Sharing Guiding Principles Panel.

Facilitating phenotyping from clinical texts: the medkit library.

Phenotyping consists in applying algorithms to identify individuals associated with a specific, potentially complex, trait or condition, typically out of a collection of Electronic Health Records (EHRs). Because a lot of the clinical information of EHRs are lying in texts, phenotyping from text takes an important role in studies that rely on the secondary use of EHRs. However, the heterogeneity and highly specialized aspect of both the content and form of clinical texts makes this task particularly tedious, and is the source of time and cost constraints in observational studies. To facilitate the development, evaluation and reproducibility of phenotyping pipelines, we developed an open-source Python library named medkit. It enables composing data processing pipelines made of easy-to-reuse software bricks, named medkit operations. In addition to the core of the library, we share the operations and pipelines we already developed and invite the phenotyping community for their reuse and enrichment. medkit is available at https://github.com/medkit-lib/medkit. Documentation, examples and tutorials are available at https://medkit-lib.org/.

Observed Glycemic and Psychosocial Benefits in the Prospective Bigfoot Unity Real World Study: A Six-Month Analysis.

The Bigfoot Unity Diabetes Management System integrates Abbott FreeStyle Libre 2 continuous glucose monitoring (CGM) data into a smart pen cap and mobile app enabling clinician-directed insulin dose recommendations and real-time alerts. The objective was to analyze real world 6-month glycemic control in a prospective study for individuals using the System for multiple daily insulin injections (MDI). We conducted a 6-month analysis from the BURST study (NCT05088265) of individuals with type 1 or type 2 diabetes (T2D). Participants reported baseline demographics, adverse event and other surveys electronically. Either at-home kit or electronic medical record glycated hemoglobin A1c (HbA1c) data were collected. Of 102 participants in the per-protocol cohort, median age was 59 years, 87% had T2D, 42% used CGM previously, 62% were White non-Hispanic and 59% female. Mean HbA1c decreased from 9.1 ± 1.7% at baseline to 8.0 ± 1.2% at 6 months (mean difference -1.1%, 95% confidence interval -1.4 to -0.8, P < 0.001). At 6 months, time in range 70-180 mg/dL, time <70 mg/dL and <54 mg/dL were 56 ± 23%, 1.0 ± 1.4% and 0.04 ± 0.14%, respectively. Six severe hypoglycemia events occurred in 4 participants (none system related) and no diabetic ketoacidosis events occurred in the per-protocol cohort. In this study primarily of older adults with T2D using MDI, durable glycemic improvement occurred using the System at 6 months, with the frequency of hypoglycemia being substantially below established targets of <4% and <1% for time below 70 and 54 mg/dL, respectively.

Mapping Implementation Strategies to Address Barriers to Pre-Exposure Prophylaxis Use Among Women Through POWER Up (Pre-Exposure Prophylaxis Optimization Among Women to Enhance Retention and Uptake): Content Analysis.

Black cisgender women (hereafter referred to as "women") experience one of the highest incidences of HIV among all populations in the United States. Pre-exposure prophylaxis (PrEP) is an effective biomedical HIV prevention option, but uptake among women is low. Despite tailored strategies for certain populations, including men who have sex with men and transgender women, Black women are frequently overlooked in HIV prevention efforts. Strategies to increase PrEP awareness and use among Black women are needed at multiple levels (ie, community, system or clinic, provider, and individual or patient). This study aimed to identify barriers and facilitators to PrEP uptake and persistence among Black cisgender women and to map implementation strategies to identified barriers using the CFIR (Consolidated Framework for Implementation Research)-ERIC (Expert Recommendations for Implementing Change) Implementation Strategy Matching Tool. We conducted a secondary analysis of previous qualitative studies completed by a multidisciplinary team of HIV physicians, implementation scientists, and epidemiologists. Studies involved focus groups and interviews with medical providers and women at a federally qualified health center in Chicago, Illinois. Implementation science frameworks such as the CFIR were used to investigate determinants of PrEP use among Black women. In this secondary analysis, data from 45 total transcripts were analyzed. We identified barriers and facilitators to PrEP uptake and persistence among cisgender women across each CFIR domain. The CFIR-ERIC Implementation Strategy Matching Tool was used to map appropriate implementation strategies to address barriers and increase PrEP uptake among Black women. Barriers to PrEP uptake were identified across the CFIR domains. Barriers included being unaware that PrEP was available (characteristics of individuals), worrying about side effects and impacts on fertility and pregnancy (intervention characteristics), and being unsure about how to pay for PrEP (outer setting). Providers identified lack of training (characteristics of individuals), need for additional clinical support for PrEP protocols (inner setting), and need for practicing discussions about PrEP with women (intervention characteristics). ERIC mapping resulted in 5 distinct implementation strategies to address barriers and improve PrEP uptake: patient education, provider training, PrEP navigation, clinical champions, and electronic medical record optimization. Evidence-based implementation strategies that address individual, provider, and clinic factors are needed to engage women in the PrEP care continuum. Tailoring implementation strategies to address identified barriers increases the probability of successfully improving PrEP uptake. Our results provide an overview of a comprehensive, multilevel implementation strategy (ie, "POWER Up") to improve PrEP uptake among women. RR2-10.1371/journal.pone.0285858.

Generalizability of Kidney Transplant Data in Electronic Health Records - The Epic Cosmos Database versus the Scientific Registry of Transplant Recipients.

Developing real-world evidence from electronic health records (EHR) is vital to advance kidney transplantation (KT). We assessed the feasibility of studying KT using the Epic Cosmos aggregated EHR dataset, which includes 274 million unique individuals cared for in 238 U.S. health systems, by comparing it with the Scientific Registry of Transplant Recipients (SRTR). We identified 69,418 KT recipients transplanted between January 2014 and December 2022 in Cosmos (39.4% of all US KT transplants during this period). Demographics and clinical characteristics of recipients captured in Cosmos were consistent with the overall SRTR cohort. Survival estimates were generally comparable, although there were some differences in long-term survival. At 7 years post-transplant, patient survival was 80.4% in Cosmos and 77.8% in SRTR. Multivariable Cox regression showed consistent associations between clinical factors and mortality in both cohorts, with minor discrepancies in the associations between death and both age and race. In summary, Cosmos provides a reliable platform for KT research, allowing EHR-level clinical granularity not available with either the transplant registry or healthcare claims. Consequently, Cosmos will enable novel analyses to improve our understanding of KT management on a national scale.

Appropriately matching transport care units to patients in an interhospital Transport Care: an implementation report.

In interfacility transport care, a critical challenge exists in accurately matching ambulance response levels to patients' needs, often hindered by limited access to essential patient data at the time of transport requests. Existing systems cannot integrate patient data from sending hospitals' electronic health records (EHR) into the transfer request process, primarily due to privacy concerns, interoperability challenges, and the sensitive nature of EHR data. We introduce a distributed digital health platform, Interfacility Transport Care (ITC)-InfoChain, designed to solve this problem without compromising EHR security or data privacy. This report details the implementation of Interfacility Transport Care (ITC)-InfoChain, a secure, blockchain-based platform designed to enhance real-time data sharing without compromising data privacy or EHR security. The ITC-InfoChain platform prototype was implemented on AWS cloud infrastructure, employing Hyperledger Fabric as a permissioned blockchain. Key elements included participant registration, identity management, and patient data collection isolated from the sending hospital's EHR system. The client program submits encrypted patient data to a distributed ledger, accessible to the receiving facility's critical care unit at the time of transport request and EMS teams during transport through the PatienTrack web application. Performance was evaluated through KPIs such as data transaction times and scalability across transaction loads. The ITC-InfoChain demonstrated strong performance and scalability. Data transaction times averaged 3.1 seconds for smaller volumes (1-20 transactions) and 6.4 seconds for 100 transactions. Optimized configurations improved processing times to 1.8-1.9 seconds for 400 transactions. These results confirm the platform's capacity to handle high transaction volumes, supporting timely, real-time data access for decision-making during transport requests and patient transfers. The ITC-InfoChain platform addresses the challenge of matching appropriate transport units to patient needs by ensuring data privacy, integrity, and real-time data sharing, enhancing coordination of patient care. The platform's success suggests potential for regional pilots and broader adoption in secure healthcare systems. Stakeholder resistance due to blockchain unfamiliarity and data privacy concerns remains. Funding has been sought to support a pilot program to address these challenges through targeted education and engagement.

Electronic Documentation of Findings in Visual Impairment Counselling Using FIDUS Software

The increasing use of electronic documentation extends to consultation for the visually impaired. The aim of this project was to develop a set of forms and electronic patient records specifically for low vision care, giving equal consideration to ophthalmological, orthoptic, and optometric specialities, as well as teaching aspects. FIDUS software (FIDUS Arztservice Wente GmbH, Darmstadt, Germany) is a well-established tool in ophthalmology practices and clinics. The software was used as a basis to develop digital entry forms with features such as auto-fill, selection recommendations, and inventory management for visual aids. The aim of the project was to maximise clarity and ease of use while also saving time during consultation with visually impaired patients. This article presents the implementation of these criteria using the electronic FIDUS record card with the corresponding electronic forms for electronic patient records taken during consultation with visually impaired patients. The index card visualises the patient's most important data and findings at a glance. Specifically designed for low vision consultation, the examination form documents visual aids prescribed to the patient in detail while also saving time. Other forms enable direct printing of prescription recommendations, test reports, and certificates. Entry forms can also be printed out for conventional handwritten records. We have achieved an electronic patient record system specifically geared to ophthalmological and optical care requirements including local inventory for visually impaired patients. Determining the level of acceptance on the part of examiners, patients, and students and optimising the software will require follow-up studies.