Electronic Health Records Research Research Articles

Checklist and guidance on creating codelists for electronic health records research

Background Codelists are required to extract meaningful information on characteristics and events from electronic health records (EHRs). EHR research relies on codelists to define study populations and variables, thus, trustworthy codelists are important. Here, we provide a checklist, in the style of commonly used reporting guidelines, to help researchers adhere to best practice in codelist development and sharing. Methods Based on a literature search and a workshop with experienced EHR researchers we created a set of recommendations that are 1. broadly applicable to different datasets, research questions, and methods of codelist creation; 2. easy to follow, implement and document by an individual researcher, and 3. fit within a step-by-step process. We then formatted these recommendations into a checklist. Results We have created a 9-step checklist, comprising 26 items, with accompanying guidance on each step. The checklist advises on which metadata to provide, how to define a clinical concept, how to identify and evaluate existing codelists, how to create new codelists, and how to review, finalise, and publish a created codelist. Conclusions Use of the checklist can reassure researchers that best practice was followed during the development of their codelists, increasing trust in research that relies on these codelists and facilitating wider re-use and adaptation by other researchers.

The Impact of Prostate-Specific Antigen Screening on Prostate Cancer Incidence and Mortality in China: 13-Year Prospective Population-Based Cohort Study.

The status of prostate-specific antigen (PSA) screening is unclear in China. Evidence regarding the optimal frequency and interval of serial screening for prostate cancer (PCa) is disputable. This study aimed to depict the status of PSA screening and to explore the optimal screening frequency for PCa in China. A 13-year prospective cohort study was conducted using the Chinese Electronic Health Records Research in Yinzhou study's data set. A total of 420,941 male participants aged ≥45 years were included between January 2009 and June 2022. Diagnosis of PCa, cancer-specific death, and all-cause death were obtained from the electronic health records and vital statistic system. Hazard ratios (HRs) with 95% CIs were estimated using Cox regression analysis. The cumulative rate of ever PSA testing was 17.9% with an average annual percent change (AAPC) of 8.7% (95% CI 3.6%-14.0%) in the past decade in China. People with an older age, a higher BMI, higher waist circumference, tobacco smoking and alcohol drinking behaviors, higher level of physical activity, medication use, and comorbidities were more likely to receive PSA screening, whereas those with a lower education level and a widowed status were less likely to receive the test. People receiving serial screening ≥3 times were at a 67% higher risk of PCa detection (HR 1.67; 95% CI 1.48-1.88) but a 64% lower risk of PCa-specific mortality (HR 0.36; 95% CI 0.18-0.70) and a 28% lower risk of overall mortality (HR 0.72; 95% CI 0.67-0.77). People following a serial screening strategy at least once every 4 years were at a 25% higher risk of PCa detection (HR 1.25; 95% CI 1.13-1.36) but 70% (HR 0.30; 95% CI 0.16-0.57) and 23% (HR 0.77; 95% CI 0.73-0.82) lower risks of PCa-specific and all-cause mortality, respectively. This study reveals a low coverage of PSA screening in China and provides the first evidence of its benefits in the general Chinese population. The findings of this study indicate that receiving serial screening at least once every 4 years is beneficial for overall and PCa-specific survival. Further studies based on a nationwide population and with long-term follow-up are warranted to identify the optimal screening interval in China.

Electronic health records (EHRs) in clinical research and platform trials: Application of the innovative EHR-based methods developed by EU-PEARL

ObjectiveElectronic Health Record (EHR) systems are digital platforms in clinical practice used to collect patients’ clinical information related to their health status and represents a useful storage of real-world data. EHRs have a potential role in research studies, in particular, in platform trials. Platform trials are innovative trial designs including multiple trial arms (conducted simultaneously and/or sequentially) on different treatments under a single master protocol. However, the use of EHRs in research comes with important challenges such as incompleteness of records and the need to translate trial eligibility criteria into interoperable queries. In this paper, we aim to review and to describe our proposed innovative methods to tackle some of the most important challenges identified. This work is part of the Innovative Medicines Initiative (IMI) EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project’s work package 3 (WP3), whose objective is to deliver tools and guidance for EHR-based protocol feasibility assessment, clinical site selection, and patient pre-screening in platform trials, investing in the building of a data-driven clinical network framework that can execute these complex innovative designs for which feasibility assessments are critically important. MethodsISO standards and relevant references informed a readiness survey, producing 354 criteria with corresponding questions selected and harmonised through a 7-round scoring process (0–1) in stakeholder meetings, with 85% of consensus being the threshold of acceptance for a criterium/question. ATLAS cohort definition and Cohort Diagnostics were mainly used to create the trial feasibility eligibility (I/E) criteria as executable interoperable queries. ResultsThe WP3/EU-PEARL group developed a readiness survey (eSurvey) for an efficient selection of clinical sites with suitable EHRs, consisting of yes-or-no questions, and a set-up of interoperable proxy queries using physicians’ defined trial criteria. Both actions facilitate recruiting trial participants and alignment between study costs/timelines and data-driven recruitment potential. ConclusionThe eSurvey will help create an archive of clinical sites with mature EHR systems suitable to participate in clinical trials/platform trials, and the interoperable proxy queries of trial eligibility criteria will help identify the number of potential participants. Ultimately, these tools will contribute to the production of EHR-based protocol design.

Interpreting pathology test result values with comparators () in Electronic Health Records research: an OpenSAFELY short data report.

Numeric results of pathology tests are sometimes returned as a range rather than a precise value, e.g. "<10". In health data research, test result values above or below clinical threshold values are often used to categorise patients into groups; however comparators (<, > etc) are typically stored separately to the numeric values and often ignored, but may influence interpretation. With the approval of NHS England we used routine clinical data from 24 million patients in OpenSAFELY to identify pathology tests with comparators commonly attached to result values. For each test we report: the proportion returned with comparators present, split by comparator type and geographic region; the specific numeric result values returned with comparators, and the associated reference limits. We identified 11 common test codes where at least one in four results had comparators. Three codes related to glomerular filtration rate (GFR) tests/calculations, with 31-45% of results returned with "≥" comparators. At least 90% of tests with numeric values 60 and 90 represented ranges (≥60 and ≥90 respectively) rather than exact values. The other tests - four blood tests (Nucleated red blood cell count, Plasma C reactive protein, Tissue transglutaminase immunoglobulin A, and Rheumatoid factor), two urine tests (albumin/microalbumin) and two faecal tests (calprotectin and quantitative faecal immunochemical test) - were returned with "≤" comparators (29-86%). Comparators appear commonly in certain pathology tests in electronic health records. For most common affected tests, we expect there to be minimal implications for researchers for most use-cases. However, care should be taken around whether results falling exactly on clinical threshold values should be considered "normal" or "abnormal". Results from GFR tests/calculations cannot reliably distinguish between mild kidney disease (60-<90) versus healthy kidney function (90+). More broadly, health data researchers using numeric test result values should consider the impact of comparators.

Optimization of the Electronic Health Record for Research.

Mini Abstract This surgical perspective highlights the current limitations of utilizing the electronic health record for research and discusses directions for future optimization.

MP44-19 EFFECTS OF PROSTATE-SPECIFIC ANTIGEN SCREENING ON PROSTATE CANCER INCIDENCE AND MORTALITY: A POPULATION-BASED COHORT STUDY IN CHINA

You have accessJournal of UrologyCME1 Apr 2023MP44-19 EFFECTS OF PROSTATE-SPECIFIC ANTIGEN SCREENING ON PROSTATE CANCER INCIDENCE AND MORTALITY: A POPULATION-BASED COHORT STUDY IN CHINA Yongle Zhan, Xiaohao Ruan, Da Huang, Jingyi Huang, Jinlun Huang, Tsun Tsun Chun, Brian Ho, Ada Ng, James Tsu, and Rong Na Yongle ZhanYongle Zhan More articles by this author , Xiaohao RuanXiaohao Ruan More articles by this author , Da HuangDa Huang More articles by this author , Jingyi HuangJingyi Huang More articles by this author , Jinlun HuangJinlun Huang More articles by this author , Tsun Tsun ChunTsun Tsun Chun More articles by this author , Brian HoBrian Ho More articles by this author , Ada NgAda Ng More articles by this author , James TsuJames Tsu More articles by this author , and Rong NaRong Na More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003290.19AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Evidence regarding the benefit of prostate-specific antigen (PSA) testing for prostate cancer (PCa) is limited in China. Scarce research so far explores the optimal frequency and interval of repeated PSA testing. This study aims to evaluate the effects of serial screening in different frequencies and intervals against PCa incidence and mortality among Chinese population. METHODS: Data of this study came from the Chinese Electronic Health Records Research in Yinzhou (CHERRY) Study. Briefly, the CHERRY study is a population-based cohort study comprising more than one million adults enrolled from 1 January 2009 in Yinzhou, China. The population census, primary care, electronic medical records, health checks, surveillance, and death registry databases have been integrated into the CHERRY study. A total of 420,941 male participants aged over 45 at recruitment were included in the present study. Among them, a subgroup of 75,362 men who have undergone any PSA testing was selected for analysis. The number of receiving PSA screening, screening frequency and interval, PCa diagnosis and death were extracted from the electronic health records system. RESULTS: People receiving more than three times of PSA testing had 67% (95% confidence interval [CI]: 48-88%) higher risks of PCa detection, but 64% (95%CI: 30-82%) lower risks of PCa-specific mortality and 28% (95%CI: 23-33%) lower risks of overall mortality. Receiving at least one screening per four years could increase 25% (95%CI: 13-36%) risks of PCa detection, but decrease 70% (95%CI: 43-84%) and 23% (95%CI: 18-27%) risks of PCa-specific and overall mortality. For those repeated attenders, 2-yr to 3-yr intervals could decrease 50-85% risks of PCa-specific mortality and 9-57% risks of overall mortality (Figure 1). CONCLUSIONS: This study provides the first evidence for the benefits of PSA screening in Chinese general population, and supports that receiving serial screening at least once per four-year is beneficial for overall and prostate cancer-specific survival. Source of Funding: This work was in supported by grants from National Natural Science Foundation of China (Grant No. 81972645), Shanghai Youth Talent Support Program, intramural funding of The University of Hong Kong to Dr. Rong Na, and Shanghai Sailing Program (22YF1440500) to Dr. Da Huang © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e619 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yongle Zhan More articles by this author Xiaohao Ruan More articles by this author Da Huang More articles by this author Jingyi Huang More articles by this author Jinlun Huang More articles by this author Tsun Tsun Chun More articles by this author Brian Ho More articles by this author Ada Ng More articles by this author James Tsu More articles by this author Rong Na More articles by this author Expand All Advertisement PDF downloadLoading ...

Evaluating the Impact on Clinical Task Efficiency of a Natural Language Processing Algorithm for Searching Medical Documents: Prospective Crossover Study.

Information retrieval (IR) from the free text within electronic health records (EHRs) is time consuming and complex. We hypothesize that natural language processing (NLP)-enhanced search functionality for EHRs can make clinical workflows more efficient and reduce cognitive load for clinicians. This study aimed to evaluate the efficacy of 3 levels of search functionality (no search, string search, and NLP-enhanced search) in supporting IR for clinical users from the free text of EHR documents in a simulated clinical environment. A clinical environment was simulated by uploading 3 sets of patient notes into an EHR research software application and presenting these alongside 3 corresponding IR tasks. Tasks contained a mixture of multiple-choice and free-text questions. A prospective crossover study design was used, for which 3 groups of evaluators were recruited, which comprised doctors (n=19) and medical students (n=16). Evaluators performed the 3 tasks using each of the search functionalities in an order in accordance with their randomly assigned group. The speed and accuracy of task completion were measured and analyzed, and user perceptions of NLP-enhanced search were reviewed in a feedback survey. NLP-enhanced search facilitated more accurate task completion than both string search (5.14%; P=.02) and no search (5.13%; P=.08). NLP-enhanced search and string search facilitated similar task speeds, both showing an increase in speed compared to the no search function, by 11.5% (P=.008) and 16.0% (P=.007) respectively. Overall, 93% of evaluators agreed that NLP-enhanced search would make clinical workflows more efficient than string search, with qualitative feedback reporting that NLP-enhanced search reduced cognitive load. To the best of our knowledge, this study is the largest evaluation to date of different search functionalities for supporting target clinical users in realistic clinical workflows, with a 3-way prospective crossover study design. NLP-enhanced search improved both accuracy and speed of clinical EHR IR tasks compared to browsing clinical notes without search. NLP-enhanced search improved accuracy and reduced the number of searches required for clinical EHR IR tasks compared to direct search term matching.

Generation Scotland - Using Electronic Health Records for Research.

ObjectivesGeneration Scotland (GS) is a family-based genetic epidemiology study of around 24,000 volunteers from 7000 families recruited across Scotland between 2006 and 2011 with follow-up through record linkage and re-contact. Broad consent was obtained for linkage to medical records for 98% of the cohort. Recruitment has recommenced in 2022.&#x0D; ApproachParticipants completed a demographic, health and lifestyle questionnaire, provided biological samples, and underwent detailed clinical assessment. The samples, phenotype and genotype data form a resource with broad consent for health-related research of current and projected public health importance.&#x0D; This has become a longitudinal dataset by linkage to routine NHS hospital, maternity, lab test, prescriptions, dentistry, mortality, cancer screening, GP data records, Covid-19 testing and vaccinations. Genome-wide association studies (GWAS) have been done on quantitative traits and biomarkers, with DNA methylation data and proteomics available for most of the cohort. Our “CovidLife” surveys collected data on the effects of the pandemic.&#x0D; ResultsResearchers can use the linked datasets to ascertain prevalent and incident disease cases and controls to test a wide range of research hypotheses. They can also recruit participants to new studies, including recall by genotype, utilising the NHS Scotland Community Health Index (CHI) Register for current contact details. We have established and validated electronic health record linkage, overcoming technical and governance issues in the process. Using consented data avoids some limitations of safe havens for analysis.&#x0D; GS is a contributor to major international consortia, with collaborators from many institutions worldwide, both academic and commercial. New recruits are now asked to give consent to linkage to other administrative data, and reuse of samples from routine NHS tests for medical research.&#x0D; ConclusionGS is now extending linkages to include radiology and health-relevant administrative data (e.g. education); and reopening recruitment to double the cohort size, including teenagers age 12+, collecting new data online and using remote sample collection.&#x0D; GS resources are available to academic and commercial researchers through a managed access process (www.generationscotland.org).

Applications of the NDR and DIAL models for risk prediction on cardiovascular disease in patients with type 2 diabetes in Ningbo

Objective: To validate the performance of cardiovascular risk prediction models based on the Sweden National Diabetes Register (NDR) and Diabetes Lifetime-perspective prediction (DIAL) model for assessing risks of 5-year and 10-year cardiovascular disease (CVD) among Chinese patients with type 2 diabetes. Methods: Based on the Chinese Electronic Health Records Research in Yinzhou study, 83 503 patients with type 2 diabetes aged 30-75 years without a history of CVD at baseline were included from January 1, 2010 to December 31, 2020. Recalibrated NDR model was used to estimate 5-year risk, while the recalibrated DIAL model was used to predict 5-year and 10-year risks. The competing events adjusted Kaplan-Meier analysis was used to obtain the observed cardiovascular events. Discrimination C statistics evaluated model accuracy, calibration χ2 value, and calibration plots. Results: Through a median follow-up of 7.0 years, 7 326 cardiovascular events, and 2 937 non-vascular deaths were identified among a total of 83 503 subjects. The recalibrated NDR model overestimated 5-year risk by 39.4% in men and 8.6% in women, whereas the overestimation for the recalibrated DIAL model was 14.6% in men and 50.1% in women. The DIAL model had a better discriminative ability (C-statistic=0.681, 95%CI: 0.672-0.690) than NDR model (C-statistic=0.667, 95%CI: 0.657-0.677) in 5-year risk prediction for men, and the models had a similar ability for women (C-statistic=0.699, 95%CI: 0.690-0.708 for NDR and C-statistic=0.698, 95%CI: 0.689-0.706 for DIAL). The prediction accuracy of the DIAL model was improved in the 10-year risk, with the underestimation being 1.6% for men and the overestimation being 12.8% for women. Conclusions: Both recalibrated NDR and DIAL models overestimated 5-year cardiovascular risk in Chinese patients with type 2 diabetes, while the higher overestimation was shown using the DIAL model. However, the improvement was found in predicting 10-year CVD risk using the DIAL model, which suggested the value of lifetime risk prediction and indicated the need for research on the lifetime risk prediction model for cardiovascular risk assessment in Chinese patients with type 2 diabetes.

Cohort design and natural language processing to reduce bias in electronic health records research

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95–0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012–0.030 in C3PO vs. 0.028–0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research.

Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research.

Retrospective cohort study. Leveraging electronic health records (EHRs) for spine surgery research is impeded by concerns regarding patient privacy and data ownership. Synthetic data derivatives may help overcome these limitations. This study's objective was to validate the use of synthetic data for spine surgery research. Data came from the EHR from 15 hospitals. Patients that underwent anterior cervical or posterior lumbar fusion (2010-2020) were included. Real data were obtained from the EHR. Synthetic data was generated to simulate the properties of the real data, without maintaining a one-to-one correspondence with real patients. Within each cohort, ability to predict 30-day readmissions and 30-day complications was evaluated using logistic regression and extreme gradient boosting machines (XGBoost). We identified 9,072 real and 9,088 synthetic cervical fusion patients. Descriptive characteristics were nearly identical between the 2 datasets. When predicting readmission, models built using real and synthetic data both had c-statistics of .69-.71 using logistic regression and XGBoost. Among 12,111 real and 12,126 synthetic lumbar fusion patients, descriptive characteristics were nearly the same for most variables. Using logistic regression and XGBoost to predict readmission, discrimination was similar with models built using real and synthetic data (c-statistics .66-.69). When predicting complications, models derived using real and synthetic data showed similar discrimination in both cohorts. Despite some differences, the most influential predictors were similar in the real and synthetic datasets. Synthetic data replicate most descriptive and predictive properties of real data, and therefore may expand EHR research in spine surgery.

Clinical Outcome and Medical Cost of Originator and Generic Antihypertensive Drugs: A Population-Based Study in Yinzhou, China.

Background: The substitution of generic drugs can effectively alleviate the rapid growth of drug costs; however, the clinical effectiveness and medical costs of originator products and generics were barely studied in China. Objectives: To compare the effectiveness of antihypertensive drugs and hypertension-related medical costs between originator and generic initiators in Yinzhou, China. Methods: We conducted a population-based retrospective cohort study using the Chinese Electronic Health Records Research in Yinzhou (CHERRY), from July 1, 2011, to December 31, 2018. Hypertension patients initiating with originator products were compared with patients initiating with generic counterparts. We used 1:1 propensity score matching to pair the two groups based on sociodemographic, clinical, and health service utilization variables. Cox proportional regression was adopted to compare the rate of hospitalization for hypertension-related cardiovascular disease between matched originator and generic initiators. Wilcoxon matched-pairs signed-rank test was used to compare annual hypertension-related medical costs. Results: Matched pairs (10,535) of patients were included in the comparative study of originator products and generics, corresponding to seven antihypertensive drugs including amlodipine, felodipine, nifedipine, irbesartan, losartan, valsartan, and metoprolol. The average age of patients included in the analysis was around 60 years (originator vs. generics initiators: from 59.0 vs. 59.1 years in losartan to 62.9 vs. 63.6 years in nifedipine). Higher hospitalization rates among originator initiators were observed for three calcium channel blockers (hazard ratio[95% CI]: amlodipine, 3.18[1.43, 7.11]; felodipine, 3.60[1.63, 7.98]; and nifedipine, 3.86[1.26, 11.81]; respectively). The remaining four out of seven drugs of the clinical endpoint estimates showed comparable outcomes between originator products and generics (hazard ratio[95% CI]: irbesartan, 1.19[0.50, 2.84]; losartan, 1.84[0.84, 4.07]; valsartan, 2.04[0.72, 5.78]; and metoprolol, 1.25[0.56, 2.80]; respectively). Higher median annual hypertension-related medical costs were observed in originator initiators (all p < 0.001), except for metoprolol (p = 0.646). Conclusion: We observed comparable or even better clinical outcomes and less medical cost associated with the use of antihypertensive generics compared to originator counterparts. This could help increase patient and provider confidence in the efficacy of generic medicines to manage hypertension diseases.

A Landscape Study Highlights the Urgent Need for Evidence Based Strategies to Enable Electronic Health Records Integration in the National Healthcare Systems of Low- and Middle-Income Countries

A Review of: Kumar, M., &amp; Mostafa, J. (2020). Electronic health records for better health in lower- and middle-income countries: A landscape study. Library Hi Tech, 38(4), 751–767. https://doi.org/10.1108/LHT-09-2019-0179 Abstract Objective – To identify how low- and middle-income countries (LMICs) approached the development of national and subnational electronic health records (EHRs) and to understand the challenges related to EHR research priorities and sustainability. Design – Landscape study consisting of a review of the scientific literature, country-focused grey literature, and consultation with international experts. Setting – Hospitals and healthcare systems within LMICs. Subjects – The 402 publications retrieved through a systematic search of four scientific electronic databases along with 49 publications found through a country-focused analysis of grey literature and 14 additional publications found through consultation with two international experts. Methods – On 15 May 2019, the authors comprehensively searched four major scientific databases: Global Health, PubMed, Scopus, and Web of Science. They also searched the grey literature and repositories in consultation with country-based international digital health experts. The authors subsequently used Mendeley reference management software to organize and remove duplicate publications. Peer-reviewed publications that focused on developing national EHRs within LMIC healthcare systems were included for the title and abstract screening. Data analysis was mainly qualitative, and the results were organized to highlight stakeholders, health information architecture (HIA), and sustainability. Main Results – The results were presented in three subsections. The first two described critical stakeholders for developing national and subnational EHRs and HIA, including country eHealth foundations, EHRs, and subsystems. The third section presented and discussed pressing challenges related to EHR sustainability. The findings of the three subsections were further explored through the presentation of three LMIC case studies that described stakeholders, HIA, and sustainability challenges. Conclusion – The results of this landscape study highlighted the scant evidence available to develop and sustain national and subnational EHRs within LMICs. The authors noted that there appears to be a gap in understanding how EHRs impact patient-level and population outcomes within the LMICs. The study revealed that EHRs were primarily designed to support monitoring and evaluating health programs focused on a particular disease or group of diseases rather than common health problems. While national governments and international donors focused on the role of EHRs to improve patient care, the authors highlighted the urgent need for further research on the development of EHRs, with a focus on efficiency, evaluation, monitoring, and quality within the national healthcare enterprise.

Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment.

We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.

Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment

We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.

Electronic Health Records in Danish Home Care and Nursing Homes: Inadequate Documentation of Care, Medication, and Consent.

Electronic health records (EHRs) are used in long-term care to document the patients' condition, medication, and care, thereby supporting communication among caregivers and counteracting adverse drug events. However, the use of EHRs in long-term care has lagged behind EHR use in hospitals. In addition, most EHR research focuses on hospitals. This study gives a countrywide status of the documentation-related risks to patient safety in Danish home care and nursing homes, which are the two main providers of long-term care. Such a status provides a basis for national improvement efforts and international comparisons. The study is based on the reports from 893 inspections of home care and nursing homes by the Danish Patient Safety Authority (Styrelsen for Patientsikkerhed [STPS]). As much as 69% of the inspected institutions document inadequately to an extent that has led to demands (i.e., issues the institution is legally obliged to rectify) or requests (i.e., issues the institution is merely asked to rectify) from STPS. Documentation issues about the patients' condition and care are present in nearly all institutions that receive demands (97%) and in the majority of those that receive requests (68%). Documentation issues about medication and consent to care are also common, but less so. The predominant risk to patient safety is incomplete documentation. It covers 72% of the documentation issues identified in the institutions that received demands; the remaining risks concern inconsistent (11%), nonexistent (7%), inaccessible (5%), and noncompliant (5%) documentation. The documentation inadequacies are similar for home care and nursing homes. Inadequate EHR documentation is a widespread problem in Danish long-term care. While previous research mainly focuses on how EHR documentation affects patient medication, this study finds that documentation issues about the patients' condition and care are more prevalent and that issues about their consent are also common.

Assessing an Electronic Health Record research platform for identification of clinical trial participants

Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Patient counts were compared with results obtained in a conventional manual search performed for a reference study that investigated the associations of atrial fibrillation (AF) and cerebrovascular incidents. The Clinical Data Warehouse (CDW) of Turku University Hospital was used to verify the capabilities of the EHR Research Platform.The EHR query resulted in a larger patient count than the manual query (EHR Research Platform 5859 patients, manual selection 2166 patients). This was due to the different search logic and some exclusion criteria that were not addressable in structured digital format. The EHR Research Platform (5859 patients) and the CDW search (5840 patients) employed the same search logic. The temporal relationship between the two diagnoses could be identified when they were available in structured format and the time difference was longer than a single hospital visit.Searching for patients with the EHR Research Platform can help to identify potential trial participants from a hospital's EHR system by limiting the number of records to be manually reviewed. EHR query tools can best be utilized in trials where the selection criteria are expressed in structured digital format.

GP coding behaviour for non-specific clinical presentations: a pilot study.

BackgroundClinical coding is an integral part of primary care. Disease incidence studies based on primary care electronic health records (EHRs) rely on the accuracy of these codes. Current code validation methods are not appropriate for non-specific conditions and provide limited information about GPs' decision-making behaviour around coding. Qualitative methods could offer insight into decision-making behaviour around coding of patients with non-specific conditions.AimTo investigate the decision-making behaviour of GPs when applying Read codes to non-specific clinical presentations, using Lyme disease as a case example.Design & settingA pilot study was undertaken, involving masked semi-structured interviews of eight GPs in the North West of England.MethodSemi-structured interviews were carried out based on 11 clinical cases representative of Lyme disease presentations. Discrete answers were described descriptively. Interview transcripts were analysed using a thematic approach.ResultsThemes underpinning GPs’ coding behaviour included: GP personal and professional experience; clinical evidence; diagnostic uncertainty; professional integrity and defensive practice; and patient-sourced health information and beliefs. GPs placed Lyme disease on their differential diagnosis list for five cases; in only two cases would GPs select a Lyme disease related Read code.ConclusionGPs were reluctant to code with specific diagnostic Read codes when they were presented with patients with vague or unfamiliar symptomology. This masked questionnaire methodology offers a new approach to validate incidence figures, based on Read codes of non-specific conditions. The reluctance to code poses many problems for primary care EHRs research. Further research is needed to understand what drives GPs’ coding behaviour.

Ethical, Legal, and Social Issues Related to the Inclusion of Individuals With Intellectual Disabilities in Electronic Health Record Research: Scoping Review.

BackgroundData from electronic health records (EHRs) are increasingly used in the field of genetic research to further precision medicine initiatives. However, many of these efforts exclude individuals with intellectual disabilities, which often stem from genetic conditions. To include this important subpopulation in EHR research, important ethical, legal, and social issues should be considered.ObjectiveThe goal of this study was to review prior research to better understand what ethical, legal, and social issues may need further investigation when considering the research use of EHRs for individuals with genetic conditions that may result in intellectual disability. This information will be valuable in developing methods and best practices for involving this group in research given they are considered a vulnerable population that may need special research protections.MethodsWe conducted a scoping review to examine issues related to the use of EHRs for research purposes and those more broadly associated with genetic research. The initial search yielded a total of 460 unique citations. We used an evaluative coding process to determine relevancy for inclusion.ResultsThis approach resulted in 59 articles in the following areas: informed consent, privacy and security, return of results, and vulnerable populations. The review included several models of garnering informed consent in EHR or genetic research, including tiered or categorical, blanket or general, open, and opt-out models. Second, studies reported on patients’ concerns regarding the privacy and security of EHR or genetic data, such as who has access, type of data use in research, identifiability, and risks associated with privacy breach. The literature on return of research results using biospecimens examined the dissension in the field, particularly when sharing individualized genetic results. Finally, work involving vulnerable populations highlighted special considerations when conducting EHR or genetic research.ConclusionsThe results frame important questions for researchers to consider when designing EHR studies, which include individuals with intellectual disabilities, including appropriate safeguards and protections.

Research Use of Electronic Health Records: Patients’ Views on Alternative Approaches to Permission

Background: The increased use of electronic health records (EHRs) has resulted in new opportunities for research, but also raises concerns regarding privacy, confidentiality, and patient awareness. Because public trust is essential to the success of the research enterprise, patient perspectives are essential to the development and implementation of ethical approaches to the research use of EHRs. Yet, little is known about patients’ views and expectations regarding various approaches to seeking permission for research use of their EHR data. Methods: We conducted semi-structured interviews with 120 patients in four counties in diverse regions of the southeastern United States: Appalachia, the Mississippi Delta, and the Piedmont area of North Carolina. We asked participants to consider, from multiple stakeholder perspectives, the advantages and disadvantages of three approaches to notifying patients of, or obtaining permission for, research use of their EHR data; whether they believed it would be acceptable if their healthcare organization used each approach; and which approach would be most appropriate. Results: Nearly all participants said General Notification, Broad Permission, and Categorical Permission would each be acceptable approaches to notification of, or permission for, EHR research. Over half identified Broad Permission as the most appropriate approach. Across all of these discussions, major themes included the importance of clarity, simplicity, and usability of patient-facing materials, as well as the level of transparency, trustworthiness, and respect for patients the approach conveys. Conclusions: Our findings help to inform the development and implementation of ethical approaches to the research use of EHRs by identifying key patient considerations regarding various approaches to permission and suggesting potential actions for healthcare organizations and researchers.