Single Electronic Health Record Research Articles

Abstract TP43: Optimizing System-Wide Nursing Assessment Documentation in the Stroke Population

Background: Stroke centers following AHA guidelines for the treatment of acute ischemic stroke, are challenged by compliance with documentation of vital sign, neuro and neurovascular assessments post thrombolysis interventions. Standardizing documentation in the electronic health record (EHR) increases compliance and reduces patient harm. In a large healthcare system, multiple sites received corrective action findings from regulatory agencies for missed nursing assessments. The centers did not have a documentation workflow aligned with the EHR to capture assessments in the stroke population. Purpose: To create a system-wide documentation workflow that captures nursing assessments in the EHR. Methods: In 2019 a task force of stroke coordinators and clinical informaticists convened to define evidence-based nursing assessments in stroke patients post intervention, define within normal limits for each component, and identify barriers to documentation in the EHR. The EHR was evaluated for component location and other areas in need of optimization. Components were scattered across different EHR locations, leading to missing documentation and assessments were difficult to trend. The task force led the development and implementation of a single EHR location to document nursing assessments. The EHR revisions were implemented in July 2022 after being vetted by system EHR governance, nurse practice council, and stroke coordinator collaborative. Results: A single grouping was developed in the EHR including vitals, focused neurological and neurovascular assessments. This grouping was strategically placed within nursing’s existing workflow. Reference text addressing each element of the grouping and its “within defined limits’ definition were added to align with the organization's documentation standards. To increase visibility of documentation, trending, and the auditing process, a single results view was developed which included all documented assessment components. Conclusion: A system-wide documentation workflow aligned with the EHR optimized documentation workflow, improved visibility of assessments, reduced audit time and regulatory findings. Stroke centers should carefully consider the layout of nursing documentation in the EHR.

Standardizing default electronic health record tools to improve safety for hospitalized patients with Parkinson's disease.

Electronic Health Record (EHR) systems are often configured to address challenges and improve patient safety for persons with Parkinson's disease (PWP). For example, EHR systems can help identify Parkinson's disease (PD) patients across the hospital by flagging a patient's diagnosis in their chart, preventing errors in medication and dosing through the use of clinical decision support, and supplementing staff education through care plans that provide step-by-step road maps for disease-based care of a specific patient population. However, most EHR-based solutions are locally developed and, thus, difficult to scale widely or apply uniformly across hospital systems. In 2020, the Parkinson's Foundation, a national and international leader in PD research, education, and advocacy, and Epic, a leading EHR vendor with more than 35% market share in the United States, launched a partnership to reduce risks to hospitalized PWP using standardized EHR-based solutions. This article discusses that project which included leadership from physician informaticists, movement disorders specialists, hospital quality officers, the Parkinson's Foundation and members of the Parkinson's community. We describe the best practice solutions developed through this project. We highlight those that are currently available as standard defaults or options within the Epic EHR, discuss the successes and limitations of these solutions, and consider opportunities for scalability in environments beyond a single EHR vendor. The Parkinson's Foundation and Epic launched a partnership to develop best practice solutions in the Epic EHR system to improve safety for PWP in the hospital. The goal of the partnership was to create the EHR tools that will have the greatest impact on outcomes for hospitalized PWP.

Introduction of a Single Electronic Health Record for Maternity Units in Ireland: Outline of the Experiences of the Project Management Team.

Electronic health records (EHRs) are being introduced worldwide. The change from paper to electronic records has not always been a seamless or quick process; however, EHRs are viewed as central to updating modern health care, especially organization structures and delivery of sustainable care with the potential for joint decision-making with the patient. The objective of this viewpoint paper is to outline how an EHR is being developed in Ireland. The focus of the Maternal & Newborn Clinical Management System project is the design and implementation of an EHR for all women and babies in the maternity services in the Republic of Ireland. The paper also outlines the lessons learned from the planning to the optimization stage of the project. The paper was developed through discussions with the project management team and their completed reports that outline the lessons they acquired from each project stage. Key lessons learned from each stage of the project are highlighted. This viewpoint paper explains how the national project management team is implementing the EHR and outlines the experiences and lessons learned and the challenges ahead following the phase one introduction. The Maternal & Newborn Clinical Management System is an example of a clinician-led, patient-focused, change management project from its inception to implementation. The introduction of EHRs is essential in modernizing health care and optimizing patient outcomes through the accurate and appropriate use of data.

Association Between Electronic Health Record Time and Quality of Care Metrics in Primary Care

Physicians across the US spend substantial time working in the electronic health record (EHR), with primary care physicians (PCPs) spending the most time. The association between EHR time and ambulatory care quality outcomes is unclear. To characterize measures of EHR use and ambulatory care quality performance among PCPs. A cross-sectional study of PCPs with longitudinal patient panels using a single EHR vendor was conducted at Brigham and Women's Hospital and Massachusetts General Hospital during calendar year 2021. Independent variables included PCPs demographic and practice characteristics and EHR time measures (PCP-level mean of daily total EHR time, after-hours time, time from 5:30 pm to 7:00 am and time on weekends, and daily EHR time on notes, sending and receiving patient, staff, results, prescription, or system messages [in-basket], and clinical review). Outcome variables were ambulatory quality measures (year-end, PCP panel-level achievement of targets for hemoglobin A1c level control, lipid management, hypertension control, diabetes screening, and breast cancer screening). The sample included 291 physicians (174 [59.8%] women). Median panel size was 829 (IQR, 476-1157) patients and mean (SD) clinical full-time equivalent was 0.54 (0.27). The PCPs spent a mean (SD) of 145.9 (64.6) daily minutes on the EHR. There were significant associations between EHR time and panel-level achievement of hemoglobin A1c control, hypertension control, and breast cancer screening targets. In adjusted analyses, each additional 15 minutes of total daily EHR time was associated with 0.58 (95% CI, 0.32-0.84) percentage point greater panel-level hemoglobin A1c control, 0.52 (95% CI, 0.33-0.71) percentage point greater hypertension control, and 0.28 (95% CI, 0.05-0.52) higher breast cancer screening rates. Each daily additional 15 minutes of in-basket time was associated with 2.26 (95% CI, 1.05-3.48) greater panel-wide hemoglobin A1c control, 1.65 (95% CI, 0.83-2.47) percentage point greater hypertension control, and 1.26 (95% CI, 0.51-2.02) percentage point higher breast cancer screening rates. Associations were largely concentrated among PCPs with 0.5 clinical full-time equivalent or less. There were no associations between EHR use metrics and diabetes screening or lipid management in patients with cardiovascular disease. This cross-sectional study found an association between EHR time and some measures of ambulatory care quality. Although increased EHR time is associated with burnout, it may represent a level of thoroughness or communication that enhances certain outcomes. It may be useful for future studies to characterize payment models, workflows, and technologies that enable high-quality ambulatory care delivery while minimizing EHR burden.

Hospital's adoption of multiple methods of obtaining outside information and use of that information.

Hospitals have multiple methods available to engage in health information exchange (HIE); however, it is not well understood whether these methods are complements or substitutes. We sought to characterize patterns of adoption of HIE methods and examine the association between these methods and increased availability and use of patient information. Cross-sectional analysis of 3208 nonfederal acute care hospitals in the 2019 American Hospital Association Information Technology Supplement. The median hospital obtained outside information through 4 methods. Hospitals that obtained data through a regional HIE organization were 2.2 times more likely to also obtain data via Direct using a health information service provider (HISP) than hospitals that did not (P < .001). Hospitals in a single electronic health record (EHR) vendor network were no more or less likely to participate in a HISP or HIE. Six of 7 methods were associated with greater information availability. Only 4 of 7 methods (portals, interfaces, single vendor networks and multi-vendor networks but not access to outside EHR, regional exchange or Direct using a HISP) were associated with more frequent use of information, and single vendor networks were most strongly associated with more frequent use (odds ratio = 4.7, P < .001). Adoption of some methods was correlated, indicating complementary use. Few methods were negatively correlated, indicating limited competition. Although information availability was common, low correlation with use indicated that challenges related to integration may be slowing use of information. Complementarities between methods, and the role of integration in supporting information use, indicate the potential value of efforts aimed at ensuring exchange methods work well together, such as the Trusted Exchange Framework and Common Agreement.

1090-P: Prevalence of Diabetic Cardiomyopathy in an Electronic Health Record–Based Cohort

Introduction: Diabetic cardiomyopathy (DbCM) is characterized by abnormal cardiac structure/function, associated with incident HF, and has a 67% prevalence in the community. However, the prevalence of DbCM in a real-world, electronic health record (EHR) system is not known. Methods: Adult patients with DM in a single center EHR free of CVD with available data on HF risk factors were included. The presence of DbCM was defined using different definitions (Figure) . DbCM prevalence was compared across subgroups with differences assessed using the chi-squared test. Adjusted logistic regression models were constructed to evaluate significant predictors of DbCM. Results: Among 1,921 individuals with DM, prevalence of DbCM in the overall cohort was 8.7% and 64.4% in the most and least restrictive definitions, respectively. Across all definitions, increasing age and Hispanic ethnicity was associated with higher proportion of DbCM (Figure A,D) . No consistent differences in DbCM prevalence were observed across sex and race-based subgroups across definitions (Figure B-C) . In multivariable-adjusted logistic regression, higher creatinine and longer QRS duration were associated with higher risk of DbCM across all definitions. Conclusions: In a single-center, EHR cohort, the prevalence of DbCM was up to 64.4%. Increasing age and Hispanic ethnicity had a higher prevalence of DbCM. Disclosure M.W.Segar: None. K.Patel: None. M.Vaduganathan: Advisory Panel; American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Cytokinetics, Lexicon Pharmaceuticals, Pharmacosmos, Relypsa, Roche Diagnostics, and Sanofi, Other Relationship; Novartis and Galmed , Research Support; Amgen, AstraZeneca, Boehringer Ingelheim, Novartis, Roche Diagnostics, and Sanofi, Speaker's Bureau; Novartis and Roche Diagnostics. A.Chandra: None. D.L.Willett: None. A.Pandey: Advisory Panel; Lilly, Consultant; Tricog, Research Support; Applied Therapeutics, Gilead Sciences, Inc.

Use of electronic health record systems in accountable care organizations.

To assess the ability of accountable care organizations (ACOs) to use electronic health record (EHR) data for quality. Cross-sectional study of ACOs participating in the Medicare Shared Savings Program(MSSP). A national survey of MSSP ACOs included questions on the number of EHR systems used across all providers in the ACO and barriers to reporting EHR-based quality measures. Just 9% of ACOs use a single EHR system, whereas 77% use 6 or more EHR systems. The more EHR systems an ACO uses, the less likely it is to report having the infrastructure to aggregate EHR data and the more concerned it is about the short-term viability and accuracy of EHR-based quality measures. ACOs have diverse structures that often result in the usage of multiple EHR systems. This has the potential to cause serious delays when CMS begins requiring ACOs to report their quality measures through their EHRs in2022.

Lessons Learned from Creating Alert Governance during an Electronic Health Record Transition

Abstract Background Our multihospital transition to a single electronic health record (EHR) provided an opportunity to transform alert governance. Our case provides insights into the unique challenges and opportunities of creating governance during a transition to meet both implementation and future alert management needs. ObjectivesThis case report describes the efforts of UW Medicine Information Technology Services to advance alert governance during EHR transition and highlights the opportunities to improve care quality and provider experience within a changing environment. Methods We used a multidisciplinary approach and external evidence to define governance for provider-facing interruptive alerts. We established the context for our governance efforts with a systemic environmental scan. We used literature review and expert consultation to determine alert design and performance best practices, sought to design postimplementation evaluation tools, and engaged clinical stakeholders to help with decision-making. Results We created alert design and implementation tools and an alert approval process, eliminating 21 unnecessary alerts prior to implementation. We developed prototype evaluation metrics and enlisted clinical owners for postimplementation optimization of 221 alerts. Conclusion We leveraged the fluid environment of our EHR implementation to rapidly build a provider-led governance infrastructure to meet immediate transitional needs and to facilitate future alert maintenance and improvement.

What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality.

Accurate recording of diagnosis (DX) data in electronic health records (EHRs) is important for clinical practice and learning health care. Previous studies show statistically stable patterns of data entry in EHRs that contribute to inaccurate DX, likely because of a lack of data entry support. We conducted qualitative research to characterize the preferences of oncological care providers on cancer DX data entry in EHRs during clinical practice. We conducted semistructured interviews and focus groups to uncover common themes on DX data entry preferences and barriers to accurate DX recording. Then, we developed a survey questionnaire sent to a cohort of oncologists to verify the generalizability of our initial findings. We constrained our participants to a single specialty and institution to ensure similar clinical backgrounds and clinical experience with a single EHR system. A total of 12 neuro-oncologists and thoracic oncologists were involved in the interviews and focus groups. The survey developed from these two initial thrusts was distributed to 19 participants yielding a 94.7% survey response rate. Clinicians reported similar user interface experiences, barriers, and dissatisfaction with current DX entry systems including repetitive entry operations, difficulty in finding specific DX options, time-consuming interactions, and the need for workarounds to maintain efficiency. The survey revealed inefficient DX search interfaces and challenging entry processes as core barriers. Oncologists seem to be divided between specific DX data entry and time efficiency because of current interfaces and feel hindered by the burdensome and repetitive nature of EHR data entry. Oncologists' top concern for adopting data entry support interventions is ensuring that it provides significant time-saving benefits and increasing workflow efficiency. Future interventions should account for time efficiency, beyond ensuring data entry effectiveness.

Hospital Adoption of Electronic Decision Support Tools for Preeclampsia Management.

Background:Electronic health record (EHR)–based clinical decision support tools can improve the use of evidence-based clinical guidelines for preeclampsia management that can reduce maternal mortality and morbidity. No study has investigated the organizational capabilities that enable hospitals to use EHR-based decision support tools to manage preeclampsia.Objective:To examine the association of organizational capabilities and hospital adoption of EHR-based decision support tools for preeclampsia management.Methods:Cross-sectional analyses of hospitals providing obstetric care in 2017. In total, 739 hospitals responded to the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS) and were linked to the 2017 American Hospital Association (AHA) Annual Survey Database and the Area Health Resources File (AHRF). A total of 425 hospitals providing obstetric care across 49 states were included in the analysis. The main outcome was whether a hospital adopted EHR-based clinical decision support tools for preeclampsia management. Hospital organizational capabilities assessed as predictors include EHR functions, adoption of evidence-based clinical treatments, use of quality improvement methods, and dissemination processes to share best patient care practices. Logistic regression estimated the association of hospital organizational capabilities and hospital adoption of EHR-based decision support tools to manage preeclampsia, controlling for hospital structural and patient sociodemographic characteristics.Results:Two-thirds of the hospitals (68%) adopted EHR-based decision support tools for preeclampsia, and slightly more than half (56%) of hospitals had a single EHR system. Multivariable regression results indicate that hospitals with a single EHR system were more likely to adopt EHR-based decision support tools for preeclampsia (17.4 percentage points; 95% CI, 1.9 to 33.0; P < .05) than hospitals with a mixture of EHR and paper-based systems. Compared with hospitals having multiple EHRs, on average, hospitals having a single EHR were also more likely to adopt the tools by 9.3 percentage points, but the difference was not statistically significant (95% CI, −1.3 to 19.9). Hospitals with more processes to aid dissemination of best patient care practices were also more likely to adopt EHR-based decision-support tools for preeclampsia (0.4 percentage points; 95% CI, 0.1 to 0.6, for every 1-unit increase in dissemination processes; P < .01).Conclusion:Standardized EHRs and policies to disseminate evidence are foundational hospital capabilities that can help advance the use of EHR-based decision support tools for preeclampsia management in the approximately one-third of US hospitals that still do not use them.

Sexual Orientation Demographic Data in a Clinical Cohort of Transgender Patients.

There are specific issues regarding sexual orientation (SO) collection and analysis among transgender and nonbinary patients. A limitation to meaningful SO and gender identity (GI) data collection is their consideration as a fixed trait or demographic data point. A de-identified patient database from a single electronic health record (EHR) that allows for searching any discrete data point in the EHR was used to query demographic data (sex assigned at birth and current GI) for transgender individuals from January 2011 to March 2020 at a large urban tertiary care academic health center. A cohort of transgender individuals were identified by using EHR data from a two-step demographic question. Almost half of male identified (46.70%, n = 85) and female identified (47.51%, n = 86) individuals had "heterosexual/straight" input for SO. Overall, male and female identified (i.e., binary) GI aggregate categories had similar SO responses. Assigned male at birth (AMAB) nonbinary individuals (n = 6) had "homosexual/gay" SO data input. Assigned female at birth (AFAB) nonbinary individuals (n = 56) had almost half "something else" SO data input (41.67%, n = 15). Individuals with "choose not to disclose" for GI (n = 249) almost all had "choose not to disclose" SO data (96.27%, n = 232). Current SO categories do not fully capture transgender individuals' identities and experiences, and limit the clinical and epidemiological utility of collecting this data in the current form. Anatomical assumptions based on SO should be seen as a potential shortcoming in over-reliance on SO as an indicator of screening needs and risk factors.

Opioid Prescribing After Implementation of Single Click Access to a State Prescription Drug Monitoring Program Database in a Health System's Electronic Health Record.

To determine the effect of one-click integration of a state's prescription drug monitoring program (PDMP) on the number of PDMP searches and opioid prescriptions, stratified by specialty. Our large health system worked with the state department of public health to integrate the PDMP with the electronic health record (EHR), which enabled providers to query the data with a single click inside the EHR environment. We evaluated Schedule II or III opioid prescriptions reported to the Massachusetts PDMP 6 months before (November 15, 2017-May 15, 2018) and 6 months after (May 16, 2018, to November 16, 2018) integration. Search counts, prescriptions, patients, morphine milligram equivalents, as well as prescriber specialty were compared. There were 3,185 unique prescribers with a record of a Schedule II and/or III opioid prescription in both study periods that met inclusion criteria. After integration, the number of PDMP searches increased from 208,684 in the pre-integration phase to 298,478 searches in the post-integration phase (+43.0%). The number of opioid prescriptions dispensed decreased by 4.8%, the number of patients receiving a prescription decreased by 5.1%, and the mean morphine milligram equivalents (MMEs) per prescriber decreased by 5.4%. There were some notable specialty-specific differences in these measures. Integration of the PDMP into the EHR markedly increased the number of searches but was associated with modest decreases in opioids prescribed and patients receiving a prescription. Single click EHR integration of the PDMP, if implemented broadly, may be a way for states to significantly increase PDMP utilization.

The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform.

ObjectiveLearning healthcare systems use routinely collected data to generate new evidence that informs future practice. While implementing an electronic health record (EHR) system can facilitate this goal for individual institutions, meaningfully aggregating data from multiple institutions can be more empowering. Cosmos is a cross-institution, single EHR vendor-facilitated data aggregation tool. This work aims to describe the initiative and illustrate its potential utility through several use cases.MethodsCosmos is designed to scale rapidly by leveraging preexisting agreements, clinical health information exchange networks, and data standards. Data are stored centrally as a limited dataset, but the customer facing query tool limits results to prevent patient reidentification.ResultsIn 2 years, Cosmos grew to contain EHR data of more than 60 million patients. We present practical examples illustrating how Cosmos could further efforts in chronic disease surveillance (asthma and obesity), syndromic surveillance (seasonal influenza and the 2019 novel coronavirus), immunization adherence and adverse event reporting (human papilloma virus and measles, mumps, rubella, and varicella vaccination), and health services research (antibiotic usage for upper respiratory infection).DiscussionA low barrier of entry for Cosmos allows for the rapid accumulation of multi-institutional and mostly de-duplicated EHR data to power research and quality improvement queries characteristic of learning healthcare systems. Limitations are being vendor-specific, an “all or none” contribution model, and the lack of control over queries run on an institution’s healthcare data.ConclusionCosmos provides a model for within-vendor data standardization and aggregation and a steppingstone for broader intervendor interoperability.

Dissemination of child abuse clinical decision support: Moving beyond a single electronic health record

BackgroundChild maltreatment is a leading cause of pediatric morbidity and mortality. We previously reported on development and implementation of a child abuse clinical decision support system (CA-CDSS) in the Cerner electronic health record (EHR). Our objective was to develop a CA-CDSS in two different EHRs. MethodsUsing the CA-CDSS in Cerner as a template, CA-CDSSs were developed for use in four hospitals in the Northwell Health system who use Allscripts and two hospitals in the University of Wisconsin health system who use Epic. Each system had a combination of triggers, alerts and child abuse-specific order sets. Usability evaluation was done prior to launch of the CA-CDSS. ResultsOver an 18-month period, a CA-CDSS was embedded into Epic and Allscripts at two hospital systems. The CA-CDSSs vary significantly from each other in terms of the type of triggers which were able to be used, the type of alert, the ability of the alert to link directly to child abuse-specific order sets and the order sets themselves. ConclusionsDissemination of CA-CDSS from one EHR into the EHR in other health care systems is possible but time-consuming and needs to be adapted to the strengths and limitations of the specific EHR. Site-specific usability evaluation, buy-in of multiple stakeholder groups and significant information technology support are needed. These barriers limit scalability and widespread dissemination of CA-CDSS.

Comparing Electronic Health Record Domains' Utility to Identify Transgender Patients.

Earlier literature has reported on the utility of diagnostic codes and demographic information for identifying transgender patients. We aim to assess which method identifies the most transgender patients utilizing readily available tools from within the electronic health record (EHR). A de-identified patient database from a single EHR that allows for searching any discrete data point in the EHR was used to query International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) diagnostic codes and demographic data specific to transgender patients from January 2011 to April 2019. Demographic data and ICD-10 codes yielded 1494 individual EHRs with transgender-specific data domains. ICD-10 diagnostic codes alone identified 942 (63.05%) unique EHRs. Demographics alone identified 218 (14.59%) unique EHRs. A total of 334 (22.36%) unique EHRs had both ICD-10 and demographic identifiers. Of those identified by transgender-specific demographic data (552), 294 (53.26%) were trans masculine, 215 (38.95%) were trans feminine, and 43 (7.79%) were nonbinary. Of the 552 demographic-identified transgender patients, 141 (25.86%) were identified by a two-part gender identity demographic question. ICD-10 diagnostic codes, not demographic data, identified the most transgender patient records, but neither diagnostic codes alone nor demographic data captured the full population. Only 26.36% of the charts identified as transgender patients had both ICD-10 codes and demographic data. We recommend that when identifying transgender populations through EHR domains, a combination of diagnostic codes and demographic data be used. Furthermore, research is needed to optimize disclosure and collection of demographic information for gender minority populations.

Optimizing health IT to improve health system performance: A work in progress

BackgroundDespite significant investments in health information technology (IT), the technology has not yielded the intended performance effects or transformational change. We describe activities that health systems are pursuing to better leverage health IT to improve performance. MethodsWe conducted semi-structured telephone interviews with C-suite executives from 24 U.S. health systems in four states during 2017–2019 and analyzed the data using a qualitative thematic approach. ResultsHealth systems reported two broad categories of activities: laying the foundation to improve performance with IT and using IT to improve performance. Within these categories, health systems were engaged in similar activities but varied greatly in their progress. The most substantial effort was devoted to the first category, which enabled rather than directly improved performance, and included consolidating to a single electronic health record (EHR) platform and common data across the health system, standardizing data elements, and standardizing care processes before using the EHR to implement them. Only after accomplishing such foundational activities were health systems able to focus on using the technology to improve performance through activities such as using data and analytics to monitor and provide feedback, improving uptake of evidence-based medicine, addressing variation and overuse, improving system-wide prevention and population health management, and making care more convenient. Conclusions and implicationsLeveraging IT to improve performance requires significant and sustained effort by health systems, in addition to significant investments in hardware and software. To accelerate change, better mechanisms for creating and disseminating best practices and providing advanced technical assistance are needed.

Recommendations for the Conduct and Reporting of Research Involving Flexible Electronic Health Record-Based Interventions.

In the past 2 decades, the United States has seen widespread adoption of electronic health records (EHRs) and a transition from mostly locally developed EHRs to commercial systems. However, most research on quality improvement and safety interventions in EHRs is still conducted at a single site, in a single EHR. Although single-site studies are important early in the innovation lifecycle, multisite studies of EHR interventions are critical for generalizability. Because EHR software, configuration, and local context differ considerably across health care organizations, it can be difficult to implement a single, standardized intervention across multiple sites in a study. This article outlines key strengths, weaknesses, challenges, and opportunities for standardization of EHR interventions in multisite studies and describes flexible trial designs suitable for studying complex interventions, including EHR interventions. It also outlines key considerations for reporting on flexible trials of EHR interventions, including sharing details of the process for designing interventions and their content, details of outcomes being studied and approaches for pooling, and the importance of sharing code and configuration whenever possible.

Associations between Psychiatric Disorders and Cannabis-Related Disorders Documented in Electronic Health Records

ABSTRACT Data from a large network of community health centers connected via a single electronic health record (EHR) system examined associations between psychiatric disorders and documentation of a cannabis-related disorder among patients with reported cannabis use. Participants were adults who had at least one ambulatory visit at a clinic in three states between 1/1/2012 and 12/31/2016 and had either 1) a documented cannabis-related disorder indicated by an ICD-9/10 code on the problem list or encounter list or 2) documentation of cannabis use in the EHR social history section. Clinics included 101,405 patients with either cannabis use recorded in the social history of the EHR (n = 71,660) or a cannabis-related disorder documented in the encounter or problem list (n = 29,745). GEE logistic regression modeling estimated adjusted odds ratios (aOR). Odds of patients having cannabis-related disorder recorded on the encounter or problem list were higher for individuals with depression (aOR = 1.08, 95% CI: 1.04–1.13), anxiety (aOR = 1.16, CI: 1.11–1.21) and bipolar disorder (aOR = 1.16, CI: 1.10–1.23). A diagnosis of schizophrenia increased the odds of a cannabis-related disorder by 62% (aOR = 1.62, CI: 1.48– 1.78). Primary care providers should routinely screen for and document cannabis-related disorders and psychiatric disorders.

Resident Inbox Task Completion Is Improved with a Single Electronic Health Record (EHR) System.

Resident Inbox Task Completion Is Improved with a Single Electronic Health Record (EHR) System.

Progress in using the electronic health record to improve primary care.

The seminal work in the 1970s by Geoffrey Rose on population-based strategies for prevention1 and Julian Tudor Hart on evidence-based anticipatory care2,3 had a profound influence on primary care and were actively supported by the Royal College of General Practitioners. In 1985 in the East London borough of Tower Hamlets, five GP practices collaborated as the Healthy Eastenders Project to support a basic electronic health record (EHR) system, employing nurses for preventive activities and providing comparative audits of their care. By 1992, with the first wave of general practice computerisation, a single EHR system, Egton Medical Information Systems (EMIS), was deployed across all practices in Tower Hamlets with the neighbouring boroughs of City and Hackney and Newham following closely. The Clinical Effectiveness Group (CEG) began to form a supportive network for implementing and evaluating work on preventive care across the locality.4 The early system required ‘floppy disks’ to extract data using Morbidity Information Query and Export Syntax (MIQUEST) with manual transport, usually by bicycle, to the CEG office to collate information from each practice. Although cumbersome, the results were transformative, and for the first time practices could see their own performance and share comparable information with their peers.4–6 In the early days, the theoretical framework used by the CEG team to translate evidence-based innovation into routine clinical practice was necessarily pragmatic. With increasing experience, two complementary strategies framed the process of change. The first included elements of change management described by Kotter.7 These included: building the case for change, forming a coalition that includes both clinicians and managers, empowering others to act on the programme by the provision of education, comparative performance data, and quality improvement tools, creating early wins for the programme, and consolidating the new approach into work-as-usual to …