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ObjectiveTo explore trends in blood pressure (BP) control before and during the COVID-19 pandemic.Patients and methodsHealth systems participating in the National Patient-Centered Clinical Research Network (PCORnet) Blood Pressure Control Laboratory Surveillance System responded to data queries, producing 9 BP control metrics. Averages of the BP control metrics (weighted by numbers of observations in each health system) were calculated and compared between two 1-year measurement periods (January 1, 2019, through December 31, 2019, and January 1, 2020, through December 31, 2020).ResultsAmong 1,770,547 hypertensive persons in 2019, BP control to

Rural communities are among the most underserved and resource-scarce populations in the United States. However, there are limited data on COVID-19 outcomes in rural America. This study aims to compare hospitalization rates and inpatient mortality among SARS-CoV-2-infected persons stratified by residential rurality.This retrospective cohort study from the National COVID Cohort Collaborative (N3C) assesses 1,033,229 patients from 44 US hospital systems diagnosed with SARS-CoV-2 infection between January 2020 and June 2021. Primary outcomes were hospitalization and all-cause inpatient mortality. Secondary outcomes were utilization of supplemental oxygen, invasive mechanical ventilation, vasopressor support, extracorporeal membrane oxygenation, and incidence of major adverse cardiovascular events or hospital readmission. The analytic approach estimates 90-day survival in hospitalized patients and associations between rurality, hospitalization, and inpatient adverse events while controlling for major risk factors using Kaplan-Meier survival estimates and mixed-effects logistic regression.Of 1,033,229 diagnosed COVID-19 patients included, 186,882 required hospitalization. After adjusting for demographic differences and comorbidities, urban-adjacent and nonurban-adjacent rural dwellers with COVID-19 were more likely to be hospitalized (adjusted odds ratio [aOR] 1.18, 95% confidence interval [CI], 1.16-1.21 and aOR 1.29, CI 1.24-1.1.34) and to die or be transferred to hospice (aOR 1.36, CI 1.29-1.43 and 1.37, CI 1.26-1.50), respectively. All secondary outcomes were more likely among rural patients.Hospitalization, inpatient mortality, and other adverse outcomes are higher among rural persons with COVID-19, even after adjusting for demographic differences and comorbidities. Further research is needed to understand the factors that drive health disparities in rural populations.

Objective In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. Materials and Methods We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. Results Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. Discussion We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. Conclusion By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.

Comprehensive participatory planning and evaluation (CPPE), a model used in community engagement research, has not been applied to patient engagement in research. We describe our methodology and interim results using CPPE in a project focused on improving research engagement of rural and distant patients and stakeholders. Specifically, we describe our development of a causal map and the subsequent use of the map to guide patient and stakeholder-driven evaluation.

Background The HERO registry was established to support research on the impact of the COVID-19 pandemic on US healthcare workers. Objective Describe the COVID-19 pandemic experiences of and effects on individuals participating in the HERO registry. Design Cross-sectional, self-administered registry enrollment survey conducted from April 10 to July 31, 2020. Setting Participants worked in hospitals (74.4%), outpatient clinics (7.4%), and other settings (18.2%) located throughout the nation. Participants A total of 14,600 healthcare workers. Main Measures COVID-19 exposure, viral and antibody testing, diagnosis of COVID-19, job burnout, and physical and emotional distress. Key Results Mean age was 42.0 years, 76.4% were female, 78.9% were White, 33.2% were nurses, 18.4% were physicians, and 30.3% worked in settings at high risk for COVID-19 exposure (e.g., ICUs, EDs, COVID-19 units). Overall, 43.7% reported a COVID-19 exposure and 91.3% were exposed at work. Just 3.8% in both high- and low-risk settings experienced COVID-19 illness. In regression analyses controlling for demographics, professional role, and work setting, the risk of COVID-19 illness was higher for Black/African-Americans (aOR 2.32, 99% CI 1.45, 3.70, p < 0.01) and Hispanic/Latinos (aOR 2.19, 99% CI 1.55, 3.08, p < 0.01) compared with Whites. Overall, 41% responded that they were experiencing job burnout. Responding about the day before they completed the survey, 53% of participants reported feeling tired a lot of the day, 51% stress, 41% trouble sleeping, 38% worry, 21% sadness, 19% physical pain, and 15% anger. On average, healthcare workers reported experiencing 2.4 of these 7 distress feelings a lot of the day. Conclusions Healthcare workers are at high risk for COVID-19 exposure, but rates of COVID-19 illness were low. The greater risk of COVID-19 infection among race/ethnicity minorities reported in the general population is also seen in healthcare workers. The HERO registry will continue to monitor changes in healthcare worker well-being during the pandemic. Trial Registration ClinicalTrials.gov identifier NCT04342806 Supplementary Information The online version contains supplementary material available at 10.1007/s11606-020-06529-z.

Coronavirus Disease 2019 (COVID-19) has affected every country globally, with hundreds of millions of people infected with the SARS-CoV-2 virus and over 6 million deaths to date. It is unknown how alcohol use disorder (AUD) affects the severity and mortality of COVID-19. AUD is known to increase the severity and mortality of bacterial pneumonia and the risk of developing acute respiratory distress syndrome. Our objective is to determine whether individuals with AUD have increased severity and mortality from COVID-19.We utilized a retrospective cohort study of inpatients and outpatients from 44 centers participating in the National COVID Cohort Collaborative. All were adult COVID-19 patients with and without documented AUDs.We identified 25,583 COVID-19 patients with an AUD and 1,309,445 without. In unadjusted comparisons, those with AUD had higher odds of hospitalization (odds ratio [OR] 2.00, 95% confidence interval [CI] 1.94 to 2.06, p 0.001). After adjustment for age, sex, race/ethnicity, smoking, body mass index, and comorbidities, individuals with an AUD still had higher odds of requiring hospitalization (adjusted OR [aOR] 1.51, CI 1.46 to 1.56, p 0.001). In unadjusted comparisons, individuals with AUD had higher odds of all-cause mortality (OR 2.18, CI 2.05 to 2.31, p 0.001). After adjustment as above, individuals with an AUD still had higher odds of all-cause mortality (aOR 1.55, CI 1.46 to 1.65, p 0.001).This work suggests that AUD can increase the severity and mortality of COVID-19 infection. This reinforces the need for clinicians to obtain an accurate alcohol history from patients hospitalized with COVID-19. For this study, our results are limited by an inability to quantify the daily drinking habits of the participants. Studies are needed to determine the mechanisms by which AUD increases the severity and mortality of COVID-19.

To examine whether depression status before metabolic and bariatric surgery (MBS) influenced 5-year weight loss, diabetes, and safety/utilization outcomes in the PCORnet Bariatric Study.Research on the impact of depression on MBS outcomes is inconsistent with few large, long-term studies.Data were extracted from 23 health systems on 36,871 patients who underwent sleeve gastrectomy (SG; n=16,158) or gastric bypass (RYGB; n=20,713) from 2005-2015. Patients with and without a depression diagnosis in the year prior to MBS were evaluated for % total weight loss (%TWL), diabetes outcomes, and postsurgical safety/utilization (reoperations, revisions, endoscopy, hospitalizations, mortality) at 1, 3 and 5 years after MBS.27.1% of SG and 33.0% of RYGB patients had preoperative depression, and they had more medical and psychiatric comorbidities than those without depression. At 5 years of follow-up, those with depression, versus those without depression, had slightly less %TWL after RYGB, but not after SG (between group difference = 0.42%TWL, p=0.04). However, patients with depression had slightly larger HbA1c improvements after RYGB but not after SG (between group difference = -0.19, p=0.04). Baseline depression did not moderate diabetes remission or relapse, reoperations, revision, or mortality across operations; however, baseline depression did moderate the risk of endoscopy and repeat hospitalization across RYGB versus SG.Patients with depression undergoing RYGB and SG had similar weight loss, diabetes, and safety/utilization outcomes to those without depression. The effects of depression were clinically small compared to the choice of operation.

Background The National Patient‐Centered Clinical Research Network Blood Pressure Control Laboratory Surveillance System was established to identify opportunities for blood pressure (BP) control improvement and to provide a mechanism for tracking improvement longitudinally. Methods and Results We conducted a serial cross‐sectional study with queries against standardized electronic health record data in the National Patient‐Centered Clinical Research Network (PCORnet) common data model returned by 25 participating US health systems. Queries produced BP control metrics for adults with well‐documented hypertension and a recent encounter at the health system for a series of 1‐year measurement periods for each quarter of available data from January 2017 to March 2020. Aggregate weighted results are presented overall and by race and ethnicity. The most recent measurement period includes data from 1 737 995 patients, and 11 956 509 patient‐years were included in the trend analysis. Overall, 15% were Black, 52% women, and 28% had diabetes. BP control ( Conclusions Major opportunities exist for improving BP control and reducing disparities, especially through consistent medication intensification when BP is uncontrolled. These data demonstrate substantial room for improvement and opportunities to close health equity gaps.

IMPORTANCERural communities are among the most underserved and resource-scarce populations in the United States (US), yet there are limited data on COVID-19 mortality in rural America. Furthermore, rural data are rarely centralized, precluding comparability across urban and rural regions.OBJECTIVEThe purpose of this study is to assess hospitalization rates and all-cause inpatient mortality among persons with definitive COVID-19 diagnoses residing in rural and urban areas.DESIGN, SETTINGS, AND PARTICIPANTSThis retrospective cohort study from the National COVID Cohort Collaborative (N3C) examines a cohort of 573,018 patients from 27 US hospital systems presenting with SARS-CoV-2 infection between January 2020 and March 2021, of whom 117,897 were hospitalized. A sample of 450,725 hospitalized persons without COVID-19 diagnoses was identified for comparison.EXPOSURESZIP Codes provided by source hospital systems were classified by urban-rural gradient through a crosswalk to the US Department of Agriculture Rural-Urban Commuting Area Codes.MAIN OUTCOMES AND MEASURESPrimary outcomes were hospitalization and all-cause mortality among hospitalized patients. Kaplan-Meier analysis and mixed effects logistic regression were used to estimate 30-day survival in hospitalized patients and associations between rurality, hospitalization, and inpatient mortality while controlling for major risk factors.RESULTSRural patients were more likely to be older, white, have higher body mass index, and diagnosed with SARS-CoV-2 later in the pandemic compared with their urban counterparts. Rural compared with urban inhabitants had higher rates of hospitalization (23% vs. 19%) and all-cause mortality among hospitalized patients (16% vs. 11%). After adjustment for demographic and baseline differences, rural residents (both urban adjacent and non-adjacent) with COVID-19 were more likely to be hospitalized (Adjusted Odds Ratio (AOR) 1.41, 95% Confidence Interval (CI), 1.37-1.45 and AOR 1.42, CI 1.35-1.50) and to die or be transferred to hospice (AOR 1.62, CI 1.30-1.49 and 1.38, CI 1.30-1.49), respectively. Similar differences in mortality were noted for hospitalized patients without SARS-CoV-2 infection.CONCLUSIONSHospitalization and inpatient mortality are higher among rural compared with urban persons with COVID-19, even after adjusting for several factors, including age and comorbidities. Further research is needed to understand the factors that drive health disparities in rural populations.KEY POINTSQUESTIONDo mortality and hospitalization rates among rural SARS-CoV-2 infected patients in the United States differ from that of their urban counterparts?FINDINGSHospitalization and mortality rates were significantly greater among rural compared with urban patients, even after adjusting for rural-urban differences including age and comorbidities. Similarly, in persons without SARS-CoV-2 infection, mortality rates were also higher among rural patients.MEANINGThese findings demonstrate a pervasive rural-urban discrepancy in all-cause inpatient mortality among rural individuals in the U.S. infected with SARS-COV-2 as well as among those who were uninfected. Further research is needed to understand factors driving health disparities among rural populations.

ObjectiveNumerous attempts have been made to create a standardized ‘presenting problem’ or ‘chief complaint’ list to characterize the nature of an Emergency Department visit. Previous attempts have failed to gain widespread adoption as none were freely sharable and contained the right level of specificity, structure, and clinical relevance to gain acceptance by the larger emergency medicine community. Using real-world data, we constructed a presenting problem list that addresses these challenges.Materials and MethodsWe prospectively captured the presenting problems for 180,424 consecutive emergency department patient visits at an urban, academic, Level I trauma center in the Boston metro area. No patients were excluded. We used a consensus process to iteratively derive our system using real-world data. We used the first 70% of consecutive visits to derive our ontology; followed by a 6 month washout period, and the remaining 30% for validation. All concepts were mapped to SNOMED-CT.ResultsOur system consists of a polyhierarchical ontology containing 692 unique concepts, 2,118 synonyms, and 30,613 non-visible descriptions to correct misspellings and non-standard terminology. Our ontology successfully captured structured data for 95.9% of visits in our validation dataset.Discussion and ConclusionWe present the HierArchical Presenting Problem ontologY (HaPPy). This ontology was empirically derived then iteratively validated by an expert consensus panel. HaPPy contains 692 presenting problem concepts, each concept being mapped to SNOMED-CT. This freely sharable ontology can help to facilitate presenting problem based quality metrics, research, and patient care.

Objective Clinical research data warehouses are largely populated from information extracted from electronic health records (EHRs). While these data provide information about a patient’s medications, laboratory results, diagnoses, and history, her social, economic, and environmental determinants of health are also major contributing factors in readmission, morbidity, and mortality and are often absent or unstructured in the EHR. Details about a patient’s socioeconomic status may be found in the U.S. census. To facilitate researching the impacts of socioeconomic status on health outcomes, clinical and socioeconomic data must be linked in a repository in a fashion that supports seamless interrogation of these diverse data elements. This study demonstrates a method for linking clinical and location-based data and querying these data in a de-identified data warehouse using Informatics for Integrating Biology and the Bedside. Materials and Methods Patient data were extracted from the EHR at Nebraska Medicine. Socioeconomic variables originated from the 2011-2015 five-year block group estimates from the American Community Survey. Data querying was performed using Informatics for Integrating Biology and the Bedside. All location-based data were truncated to prevent identification of a location with a population Results We successfully linked location-based and clinical data in a de-identified data warehouse and demonstrated its utility with a sample use case. Discussion With location-based data available for querying, research investigating the impact of socioeconomic context on health outcomes is possible. Efforts to improve geocoding can readily be incorporated into this model. Conclusion This study demonstrates a means for incorporating and querying census data in a de-identified clinical data warehouse.

BACKGROUND: The appropriate dose of aspirin to lower the risk of death, myocardial infarction, and stroke and to minimize major bleeding in patients with established atherosclerotic cardiovascular disease is a subject of controversy. METHODS: Using an open-label, pragmatic design, we randomly assigned patients with established atherosclerotic cardiovascular disease to a strategy of 81 mg or 325 mg of aspirin per day. The primary effectiveness outcome was a composite of death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke, assessed in a time-to-event analysis. The primary safety outcome was hospitalization for major bleeding, also assessed in a time-to-event analysis. RESULTS: A total of 15,076 patients were followed for a median of 26.2 months (interquartile range [IQR], 19.0 to 34.9). Before randomization, 13,537 (96.0% of those with available information on previous aspirin use) were already taking aspirin, and 85.3% of these patients were previously taking 81 mg of daily aspirin. Death, hospitalization for myocardial infarction, or hospitalization for stroke occurred in 590 patients (estimated percentage, 7.28%) in the 81-mg group and 569 patients (estimated percentage, 7.51%) in the 325-mg group (hazard ratio, 1.02; 95% confidence interval [CI], 0.91 to 1.14). Hospitalization for major bleeding occurred in 53 patients (estimated percentage, 0.63%) in the 81-mg group and 44 patients (estimated percentage, 0.60%) in the 325-mg group (hazard ratio, 1.18; 95% CI, 0.79 to 1.77). Patients assigned to 325 mg had a higher incidence of dose switching than those assigned to 81 mg (41.6% vs. 7.1%) and fewer median days of exposure to the assigned dose (434 days [IQR, 139 to 737] vs. 650 days [IQR, 415 to 922]). CONCLUSIONS: In this pragmatic trial involving patients with established cardiovascular disease, there was substantial dose switching to 81 mg of daily aspirin and no significant differences in cardiovascular events or major bleeding between patients assigned to 81 mg and those assigned to 325 mg of aspirin daily. (Funded by the Patient-Centered Outcomes Research Institute; ADAPTABLE ClinicalTrials.gov number, NCT02697916.).

Introduction Computable biomedical knowledge artifacts (CBKs) are digital objects conveying biomedical knowledge in machine‐interpretable structures. As more CBKs are produced and their complexity increases, the value obtained from sharing CBKs grows. Mobilizing CBKs and sharing them widely can only be achieved if the CBKs are findable, accessible, interoperable, reusable, and trustable (FAIR+T). To help mobilize CBKs, we describe our efforts to outline metadata categories to make CBKs FAIR+T. Methods We examined the literature regarding metadata with the potential to make digital artifacts FAIR+T. We also examined metadata available online today for actual CBKs of 12 different types. With iterative refinement, we came to a consensus on key categories of metadata that, when taken together, can make CBKs FAIR+T. We use subject‐predicate‐object triples to more clearly differentiate metadata categories. Results We defined 13 categories of CBK metadata most relevant to making CBKs FAIR+T. Eleven of these categories (type, domain, purpose, identification, location, CBK‐to‐CBK relationships, technical, authorization and rights management, provenance, evidential basis, and evidence from use metadata) are evident today where CBKs are stored online. Two additional categories (preservation and integrity metadata) were not evident in our examples. We provide a research agenda to guide further study and development of these and other metadata categories. Conclusion A wide variety of metadata elements in various categories is needed to make CBKs FAIR+T. More work is needed to develop a common framework for CBK metadata that can make CBKs FAIR+T for all stakeholders.

The University of Nebraska Medical Center’s Rural Patient and Stakeholder Engagement in Research project used a novel approach to patient engagement in research: just-in-time engagement. In this approach, patients were identified and matched with researchers with shared research interests without preemptive patient and stakeholder education and training. Ten research teams initiated engaged research design between August and October of 2019. In this presentation, we will share process and outcomes measures of the just-in-time approach: measures of ongoing engagement at 6 and 9 months; evidence of research productivity, and patient and stakeholder satisfaction with their research involvement. We will also address ethical challenges, including challenges to engaging a diverse population. Part of a symposium sponsored by the Patient/Person Engagement in Research Interest Group.

Objectives To determine adherence to Choosing Wisely recommendations for using serum lipase to diagnose acute pancreatitis rather than amylase, avoiding concurrent amylase/lipase testing and avoiding serial measurements after the first elevated test as both are ineffective for tracking disease course. Methods Deidentified laboratory data from four large health systems were analyzed to determine concurrent testing rates, serial testing rates, and provider-ordering patterns. Results While most providers adhered to recommendations with 58,693 lipase-only tests ordered and performed, 86% of amylase tests were performed concurrently with lipase. Ambulatory, inpatient, and emergency department settings revealed concurrent rates of 51%, 41%, and 8%, respectively. Services with order sets containing both amylase and lipase were associated with higher rates of concurrent testing. Conclusions Concurrent amylase/lipase testing is an area of opportunity to improve compliance, especially in ambulatory settings. Revision of order sets and provider education could be interventions to reduce unnecessary testing and save costs.

IMPACT: The described framework will enable other sites with a well-defined apparatus for enabling the secondary analysis of EHR data for research through education, team science, and resource consolidation. OBJECTIVES/GOALS: EHR’s potential to improve healthcare outcomes extends far beyond the clinic. This vast repository of clinical insights has dramatic potential for biomedical research. To enhance accessibility for busy clinicians and underserved populations, we describe a framework for interfacing with EHR locally and through national network participation. METHODS/STUDY POPULATION: The Institutional Development Award (IDeA) program, which began in 1993, broadens NIH funding’s geographic distribution for biomedical research. Included in this is the IDeA Networks for Clinical and Translational Research, which focuses on enhancing clinical and translational science across a network of IDeA-states with traditionally underserved communities and rural providers. A prior survey of the needs and capabilities of IDeA-CTR centers identified the need for improved research support. Based on our annual member survey we developed a process for supporting distributed research projects across the GP-CTR. NIH also recently made a funding announcement for the IDeA-CTR community identifying EHR research as a major priority in responding to the COVID-19 pandemic. RESULTS/ANTICIPATED RESULTS: Results from site interviews and member surveys show a clear need for dedicated resources to navigate the process of EHR-derived research. Most described a different set of requirements for increasing accessibility to EHR for research and a strong desire to participate in research networks. Local investigators cited a lack of tools, educational materials, and accessibility. Initial efforts demonstrate strong research questions but limited technical, statistical, and terminological capabilities to succeed. In response, a pipeline for team science and promotion of projects from local phenotypes to national studies. We created a facilitator training program to expand the number of facilitators (n=22), quarterly training for investigators (n=104), and ongoing efforts to advance COVID-19 research. DISCUSSION/SIGNIFICANCE OF FINDINGS: As evidenced in the expanding number of EHR-based research networks there is a need for a system to promote project development and best practices. The proposed model promotes education, resource sharing, and team formation to advance clinical questions from the idea stage toward national research network participation.

Background: Unreliable compliance with infection prevention procedures necessitates an analysis of contributing factors. Methods: A retrospective study explored utility of 3236 nursing hygiene notes in the electronic healthcare record system (EHR). This 2012–2013 study identified defects in the chlorhexidine (CHG) bathing practice for a hospital unit. Results: The overall compliance with CHG bathing was 22.99%. Patients with length of stay less than 3 days, in most cases, did not have documentation for CHG bathing. Patient refusal to bathe was the most prevalent documented reason (66%) of the unsuccessful initial and repeated offers to bathe. The regular staff were statistically less successful in convincing patients to bathe. The 1455 notes produced by the regular staff (n = 10) demonstrated a significantly higher failure rate (56.08%) to execute this procedure in comparison with 1770 notes documented by the 246 temporary staff (31.19% failure rate) ( P value Discussion: This analysis yielded three main insights: lack of the CHG documentation in a large number of short admissions; inconsistent use of CHG baths; and presence of workarounds due to patient refusals to bathe. The study concluded that EHR structured and unstructured data can unlock the opportunity for identifying hidden defects and inform decision-makers about the need for change.

Importance Bariatric surgery can lead to substantial improvements in type 2 diabetes (T2DM), but outcomes vary across procedures and populations. It is unclear which bariatric procedure has the most benefits for patients with T2DM. Objective To evaluate associations of bariatric surgery with T2DM outcomes. Design, Setting, and Participants This cohort study was conducted in 34 US health system sites in the National Patient-Centered Clinical Research Network Bariatric Study. Adult patients with T2DM who had bariatric surgery between January 1, 2005, and September 30, 2015, were included. Data analysis was conducted from April 2017 to August 2019. Interventions Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG). Main Outcome and Measures Type 2 diabetes remission, T2DM relapse, percentage of total weight lost, and change in glycosylated hemoglobin (hemoglobin A1c). Results A total of 9710 patients were included (median [interquartile range] follow-up time, 2.7 [2.9] years; 7051 female patients [72.6%]; mean [SD] age, 49.8 [10.5] years; mean [SD] BMI, 49.0 [8.4]; 6040 white patients [72.2%]). Weight loss was significantly greater with RYGB than SG at 1 year (mean difference, 6.3 [95% CI, 5.8-6.7] percentage points) and 5 years (mean difference, 8.1 [95% CI, 6.6-9.6] percentage points). The T2DM remission rate was approximately 10% higher in patients who had RYGB (hazard ratio, 1.10 [95% CI, 1.04-1.16]) than those who had SG. Estimated adjusted cumulative T2DM remission rates for patients who had RYGB and SG were 59.2% (95% CI, 57.7%-60.7%) and 55.9% (95% CI, 53.9%-57.9%), respectively, at 1 year and 86.1% (95% CI, 84.7%-87.3%) and 83.5% (95% CI, 81.6%-85.1%) at 5 years postsurgery. Among 6141 patients who experienced T2DM remission, the subsequent T2DM relapse rate was lower for those who had RYGB than those who had SG (hazard ratio, 0.75 [95% CI, 0.67-0.84]). Estimated relapse rates for those who had RYGB and SG were 8.4% (95% CI, 7.4%-9.3%) and 11.0% (95% CI, 9.6%-12.4%) at 1 year and 33.1% (95% CI, 29.6%-36.5%) and 41.6% (95% CI, 36.8%-46.1%) at 5 years after surgery. At 5 years, compared with baseline, hemoglobin A1cwas reduced 0.45 (95% CI, 0.27-0.63) percentage points more for patients who had RYGB vs patients who had SG. Conclusions and Relevance In this large multicenter study, patients who had RYGB had greater weight loss, a slightly higher T2DM remission rate, less T2DM relapse, and better long-term glycemic control compared with those who had SG. These findings can help inform patient-centered surgical decision-making.

Interoperability between emergency department (ED) information systems requires a shared data specification. In 2013 Health Level Seven International, an international standards body, approved a specification for Data Elements for Emergency Department Systems (DEEDS) for use in the United States. A similar specification was created in Germany for national employment, defining data elements and forms. This study presents the first step in the efforts to harmonize the two data definitions for International approval by comparing the meaning of the German Emergency Department Medical Record (GEDMR) data element definitions with the US DEEDS using a methodology for terminology mapping from ISO/TR 12300. The comparison between GEDMR and DEEDS did show significant differences in certain domains. The results support development of an international standard for ED data elements.

Display Omitted A graph database approach employing SNOMED CT as the semantic core of a patient data warehouse.SNOMED CT data queries demonstrating negation and disjunction using a graph database approach.Using multiple controlled medical terminologies without external terminology services. ObjectiveSNOMED CT is the international lingua franca of terminologies for human health. Based in Description Logics (DL), the terminology enables data queries that incorporate inferences between data elements, as well as, those relationships that are explicitly stated. However, the ontologic and polyhierarchical nature of the SNOMED CT concept model make it difficult to implement in its entirety within electronic health record systems that largely employ object oriented or relational database architectures. The result is a reduction of data richness, limitations of query capability and increased systems overhead. The hypothesis of this research was that a graph database (graph DB) architecture using SNOMED CT as the basis for the data model and subsequently modeling patient data upon the semantic core of SNOMED CT could exploit the full value of the terminology to enrich and support advanced data querying capability of patient data sets. MethodsThe hypothesis was tested by instantiating a graph DB with the fully classified SNOMED CT concept model. The graph DB instance was tested for integrity by calculating the transitive closure table for the SNOMED CT hierarchy and comparing the results with transitive closure tables created using current, validated methods. The graph DB was then populated with 461,171 anonymized patient record fragments and over 2.1 million associated SNOMED CT clinical findings. Queries, including concept negation and disjunction, were then run against the graph database and an enterprise Oracle relational database (RDBMS) of the same patient data sets. The graph DB was then populated with laboratory data encoded using LOINC, as well as, medication data encoded with RxNorm and complex queries performed using LOINC, RxNorm and SNOMED CT to identify uniquely described patient populations. ResultsA graph database instance was successfully created for two international releases of SNOMED CT and two US SNOMED CT editions. Transitive closure tables and descriptive statistics generated using the graph database were identical to those using validated methods. Patient queries produced identical patient count results to the Oracle RDBMS with comparable times. Database queries involving defining attributes of SNOMED CT concepts were possible with the graph DB. The same queries could not be directly performed with the Oracle RDBMS representation of the patient data and required the creation and use of external terminology services. Further, queries of undefined depth were successful in identifying unknown relationships between patient cohorts. ConclusionThe results of this study supported the hypothesis that a patient database built upon and around the semantic model of SNOMED CT was possible. The model supported queries that leveraged all aspects of the SNOMED CT logical model to produce clinically relevant query results. Logical disjunction and negation queries were possible using the data model, as well as, queries that extended beyond the structural IS_A hierarchy of SNOMED CT to include queries that employed defining attribute-values of SNOMED CT concepts as search parameters. As medical terminologies, such as SNOMED CT, continue to expand, they will become more complex and model consistency will be more difficult to assure. Simultaneously, consumers of data will increasingly demand improvements to query functionality to accommodate additional granularity of clinical concepts without sacrificing speed. This new line of research provides an alternative approach to instantiating and querying patient data represented using advanced computable clinical terminologies.

Electronic Health Records (EHRs) can improve the quality, safety, and efficiency of patient care. Migration to EHRs is progressing, but has been slowed by concerns related to interoperability, security, cost, patient safety, and usability. This paper focuses on EHR usability, specifically heuristic evaluation, or utilizing accepted guidelines for assessing EHR interface design. Health-care researchers initially applied industry-standard heuristics to EHRs, but subsequently health-care-specific groups have adapted and expanded these standard heuristics, calling for development and use of heuristics specific to EHRs. This paper first summarizes the evolution of heuristic evaluation of EHRs, then discusses the similarities and differences between these various approaches. This is an important step in developing community consensus on integrated heuristics, the basis of successful heuristic evaluation of EHRs. We then discuss the ‘Theory of Fit’ as a means of explaining the existence of these somewhat different heuristics, and close with suggestions for further research.

Background Emergency departments in the United States service over 130 million visits per year. The demands for information from these visits require interoperable data exchange standards. While multiple data exchange specifications are in use, none have undergone rigorous standards review. This paper describes the creation and balloting of the Health Level Seven (HL7) Data Elements for Emergency Department Systems (DEEDS). Methods Existing data exchange specifications were collected and organized into categories reflecting the workflow of emergency care. The concepts were then mapped to existing standards for vocabulary, data types, and the HL7 information model. The HL7 community then processed the specification through the normal balloting process addressing all comments and concerns. The resulting specification was then submitted for publication as an HL7 informational standard. Results The resulting specification contains 525 concepts related to emergency care required for operations and reporting to external agencies. An additional 200 of the most commonly ordered laboratory tests were included. Each concept was given a unique identifier and mapped to Logical Observation Identifiers, Names, and Codes (LOINC). HL7 standard data types were applied. Discussion The HL7 DEEDS specification represents the first set of common ED related data elements to undergo rigorous standards development. The availability of this standard will contribute to improved interoperability of emergency care data.

Decisions on antibiotic-resistant infection (ARI) prevention in dynamic health care settings should be agile and target the right process at the right time. Health information technologies can aid the recognition of high-risk situations for ARI transmission and timely facilitate operators' situational awareness (SA) in various military and civilian health care locations or transport platforms. High SA is one of the significant predictors of better performance. The objective of this study was to evaluate the impact of the developed health information visualization (VIZ) on the users' SA regarding situations when risks of ARI transmission and exposure are high. The enrolled 19 subjects assessed the proposed VIZ artifacts representing 1 scenario, compared the VIZ effectiveness against the currently employed local methods, and reported their SA (perception and comprehension) with the use of a pre- and post-self-rating questionnaire. The results showed that the VIZ significantly increased SA in the study subjects and revealed the importance of communicating the risk of exposure to ARIs. The VIZ enabled the participants to quickly acknowledge the high-risk individuals (super-spreaders), locations (hot spots), and biosafety (deficient infection prevention). The study concluded that SA-oriented technologies may be promising for promoting better infection prevention practices.

Objective This research investigated the use of SNOMED CT to represent diagnostic tissue morphologies and notable tissue architectures typically found within a pathologist's microscopic examination report to identify gaps in expressivity of SNOMED CT for use in anatomic pathology. Methods 24 breast biopsy cases were reviewed by two board certified surgical pathologists who independently described the diagnostically important tissue architectures and diagnostic morphologies observed by microscopic examination. In addition, diagnostic comments and details were extracted from the original diagnostic pathology report. 95 unique clinical statements were extracted from 13 malignant and 11 benign breast needle biopsy cases. Results 75% of the inventoried diagnostic terms and statements could be represented by valid SNOMED CT expressions. The expressions included one pre-coordinated expression and 73 post-coordinated expressions. No valid SNOMED CT expressions could be identified or developed to unambiguously assert the meaning of 21 statements (ie, 25% of inventoried clinical statements). Evaluation of the findings indicated that SNOMED CT lacked sufficient definitional expressions or the SNOMED CT concept model prohibited use of certain defined concepts needed to describe the numerous, diagnostically important tissue architectures and morphologic changes found within a surgical pathology microscopic examination. Conclusions Because information gathered during microscopic histopathology examination provides the basis of pathology diagnoses, additional concept definitions for tissue morphometries and modifications to the SNOMED CT concept model are needed and suggested to represent detailed histopathologic findings in computable fashion for purposes of patient information exchange and research. Trial registration number UNMC Institutional Review Board ID# 342-11-EP.

Background: Although bariatric procedures are commonly performed in clinical practice, long-term data on the comparative effectiveness and safety of different procedures on sustained weight loss, comorbidities, and adverse effects are limited, especially in important patient subgroups (eg, individuals with diabetes, older patients, adolescents, and minority patients). Objective: The objective of this study was to create a population-based cohort of patients who underwent 3 commonly performed bariatric procedures—adjustable gastric band (AGB), Roux-en-Y gastric bypass (RYGB), and sleeve gastrectomy (SG)—to examine the long-term comparative effectiveness and safety of these procedures in both adults and adolescents. Methods: We identified adults (20 to 79 years old) and adolescents (12 to 19 years old) who underwent a primary (first observed) AGB, RYGB, or SG procedure between January 1, 2005 and September 30, 2015 from 42 health systems participating in the Clinical Data Research Networks within the National Patient-Centered Clinical Research Network (PCORnet). We extracted information on patient demographics, encounters with healthcare providers, diagnoses recorded and procedures performed during these encounters, vital signs, and laboratory test results from patients’ electronic health records (EHRs). The outcomes of interest included weight change, incidence of major surgery-related adverse events, and diabetes remission and relapse, collected for up to 10 years after the initial bariatric procedure. Results: A total of 65,093 adults and 777 adolescents met the eligibility criteria of the study. The adult subcohort had a mean age of 45 years and was predominantly female (79.30%, 51,619/65,093). Among adult patients with non-missing race or ethnicity information, 72.08% (41,248/57,227) were White, 21.13% (12,094/57,227) were Black, and 20.58% (13,094/63,637) were Hispanic. The average highest body mass index (BMI) recorded in the year prior to surgery was 49 kg/m2. RYGB was the most common bariatric procedure among adults (49.48%, 32,208/65,093), followed by SG (45.62%, 29,693/65,093) and AGB (4.90%, 3192/65,093). The mean age of the adolescent subcohort was 17 years and 77.5% (602/777) were female. Among adolescent patients with known race or ethnicity information, 67.3% (473/703) were White, 22.6% (159/703) were Black, and 18.0% (124/689) were Hispanic. The average highest recorded BMI in the year preceding surgery was 53 kg/m2. The majority of the adolescent patients received SG (60.4%, 469/777), followed by RYGB (30.8%, 239/777) and AGB (8.9%, 69/777). A BMI measurement (proxy for follow-up) was available in 84.31% (44,978/53,351), 68.09% (20,783/30,521), and 68.56% (7159/10,442) of the eligible adult patients at 1, 3, and 5 years of follow-up, respectively. The corresponding proportion was 82.0% (524/639), 49.9% (174/349), and 38.8% (47/121) in the adolescent subcohort. Conclusions: Our study cohort is one of the largest cohorts of patients with bariatric procedures in the United States. Patients are geographically and demographically diverse, which improves the generalizability of the research findings and allows examination of treatment effect heterogeneity. Ongoing and planned investigations will provide real-world evidence on the long-term benefits and risks of these most commonly used bariatric procedures in current clinical practice.

Antibiotic resistant infections are a serious threat for public health. Hospitals are accountable for preventing the infection transmission among patients. Situation awareness interface may improve healthcare workers’ awareness about daily aberrations in infection burden and risks associated with infection transmission and underuse of preventive interventions. This study attempted to apply the rules for image contraction to furnish large amount of the electronic health record epidemiological data into a single image that would reduce informational overload and increase infection prevention situational awareness in a distributed group of healthcare workers. This research postulated that contextualization of the infection prevention data may provide critical cues for decision-making and detecting situations when prevalence and variety of antibiotic-resistant carriers reach dangerous thresholds.

The Health Information Technology for Economic and Clinical Health Act of 2009 and the Centers for Medicare & Medicaid Services "meaningful use" incentive programs, in tandem with the boundless additional requirements for detailed reporting of quality metrics, have galvanized hospital efforts to implement hospital-based electronic health records. As such, emergency department information systems (EDISs) are an important and unique component of most hospitals' electronic health records. System functionality varies greatly and affects physician decisionmaking, clinician workflow, communication, and, ultimately, the overall quality of care and patient safety. This article is a joint effort by members of the Quality Improvement and Patient Safety Section and the Informatics Section of the American College of Emergency Physicians. The aim of this effort is to examine the benefits and potential threats to quality and patient safety that could result from the choice of a particular EDIS, its implementation and optimization, and the hospital's or physician group's approach to continuous improvement of the EDIS. Specifically, we explored the following areas of potential EDIS safety concerns: communication failure, wrong order-wrong patient errors, poor data display, and alert fatigue. Case studies are presented that illustrate the potential harm that could befall patients from an inferior EDIS product or suboptimal execution of such a product in the clinical environment. The authors have developed 7 recommendations to improve patient safety with respect to the deployment of EDISs. These include ensuring that emergency providers actively participate in selection of the EDIS product, in the design of processes related to EDIS implementation and optimization, and in the monitoring of the system's ongoing success or failure. Our recommendations apply to emergency departments using any type of EDIS: custom-developed systems, best-of-breed vendor systems, or enterprise systems.

Summary Objective: The objective of this case report is to evaluate the importance of specialized domain knowledge when designing and using structured templated notes in a clinical environment. Methods: To analyze the impact of specialization on structured note generation we compared notes generated for three scenarios: 1) We compared the templated history of present illness (HPI) for patients presenting with a dermatology concern to the dermatologist versus the emergency department. 2) We compared the evaluation of chest pain by ED physicians versus cardiologists. 3) Finally, we compared the data elements asked for in the evaluation of the gastrointestinal system between cardiologists and the liver transplant service (LTS). We used the SNOMED CT representation via BioPortal to evaluate specificity and grouping between data elements and specialized physician groups. Results: We found few similarities in structured data elements designed by and for the specific physician groups. The distinctness represented both differences in granularity as well as fundamental differences in data elements requested. When compared to ED physicians, dermatologists had different and more granular elements while cardiologists requested much more granular data. Comparing cardiologists and LTS, there were differences in the data elements requested. Conclusion: This case study supports the importance of domain knowledge in EHR design and implementation. That different specialities should want and use different information is well supported by cognitive science literature. Despite this, it is rare for domain knowledge to be considered in EHR implementation. Physicians with correct domain knowledge should be involved in the design process of templated notes.

SummaryObjective: Less than 20% of hospitals in the US have an electronic health record (EHR). In this qualitative study, we examine the perspectives of both academic and private physicians and administrators as stakeholders, and their alignment, to explore their perspectives on the use of technology in the clinical environment.Methods: Focus groups were conducted with 74 participants who were asked a series of open-ended questions. Grounded theory was used to analyze the transcribed data and build convergent themes. The relevance and importance of themes was constructed by examining frequency, convergence, and intensity. A model was proposed that represents the interactions between themes. Results: Six major themes emerged, which include the impact of EHR systems on workflow, patient care, communication, research/outcomes/billing, education/learning, and institutional culture. Academic and private physicians were confident of the future benefits of EHR systems, yet cautious about the current implementations of EHR, and its impact on interactions with other members of the healthcare team and with patients, and the amount of time necessary to use EHR’s. Private physicians differed on education and were uneasy about the steep learning curve necessary for use of new systems. In contrast to physicians, university and hospital administrators are optimistic, and value the availability of data for use in reporting.Conclusion: The results of our study indicate that both private and academic physicians concur on the need for features that maintain and enhance the relationship with the patient and the healthcare team. Resistance to adoption is related to insufficient functionality and its potential negative impact on patient care. Integration of data collection into clinical workflows must consider the unexpected costs of data acquisition.