EHR Vendors Research Articles

Unveiling the Adoption and Barriers of Telemedicine in US Hospitals: A Comprehensive Analysis (2017-2022).

Telemedicine has emerged as a vital healthcare delivery model, especially pronounced during the COVID-19 pandemic. Our study uniquely focuses on an institutional lens, examining US hospitals to offer targeted policy implications. To investigate the trend in telemedicine adoption across US hospitals from 2017 to 2022 and analyze the institutional challenges they encounter, particularly in the realm of electronic health information exchange. Cross-sectional study leveraging data from the American Hospital Association's (AHA) annual surveys for the years 2017 to 2021 and the 2022 AHA IT Supplement Survey. The study includes a national sample of US hospitals, covering a diverse range of hospital types including large, nonprofit, teaching, and system-affiliated institutions. US hospitals form the study's participants, with a substantial response rate to the surveys. Key metrics include the number of telemedicine patient encounters, percentage of hospitals offering telemedicine services, and institutional challenges to electronic health information exchange. Telemedicine encounters saw a 75% increase, growing from approximately 111.4 million in 2020 to nearly 194.4 million in 2021. The percentage of hospitals offering at least one form of telemedicine service went from 46% in 2017 to 72% in 2021. Larger, nonprofit, and teaching hospitals were more prone to telehealth adoption, without notable urban-rural disparities. While over 90% of hospitals allow patients to view and download medical records, only 41% permit online data submission. Importantly, 25% of hospitals identified Certified Health IT Developers such as EHR vendor as frequent culprits in information blocking, with cost being the primary obstacle. The findings underscore the rapid yet uneven adoption of telemedicine services in U.S. hospitals. The results point to the need for comprehensive policy interventions to address the challenges identified and realize telemedicine's full potential in healthcare delivery and resilience.

Electronic connectivity between hospital pairs: impact on emergency department-related utilization.

To use more precise measures of which hospitals are electronically connected to determine whether health information exchange (HIE) is associated with lower emergency department (ED)-related utilization. We combined 2018 Medicare fee-for-service claims to identify beneficiaries with 2 ED encounters within 30days, and Definitive Healthcare and AHA IT Supplement data to identify hospital participation in HIE networks (HIOs and EHR vendor networks). We determined whether the 2 encounters for the same beneficiary occurred at: the same organization, different organizations connected by HIE, or different organizations not connected by HIE. Outcomes were: (1) whether any repeat imaging occurred during the second ED visit; (2) for beneficiaries with a treat-and-release ED visit followed by a second ED visit, whether they were admitted to the hospital after the second visit; (3) for beneficiaries discharged from the hospital followed by an ED visit, whether they were admitted to the hospital. In adjusted mixed effects models, for all outcomes, beneficiaries returning to the same organization had significantly lower utilization compared to those going to different organizations. Comparing only those going to different organizations, HIE was not associated with lower levels of repeat imaging. HIE was associated with lower likelihood of hospital admission following a treat-and-release ED visit (1.83 percentage points [-3.44 to -0.21]) but higher likelihood of admission following hospital discharge (2.78 percentage points [0.48-5.08]). Lower utilization for beneficiaries returning to the same organization could reflect better access to information or other factors such as aligned incentives. HIE is not consistently associated with utilization outcomes reflecting more coordinated care in the ED setting.

Comparative effectiveness of generic commercial versus locally customized clinical decision support tools to reduce prescription of nonsteroidal anti-inflammatory drugs for patients with heart failure.

To compare the effectiveness of 2 clinical decision support (CDS) tools to avoid prescription of nonsteroidal anti-inflammatory drugs (NSAIDs) in patients with heart failure (HF): a "commercial" and a locally "customized" alert. We conducted a retrospective cohort study of 2 CDS tools implemented within a large integrated health system. The commercial CDS tool was designed according to third-party drug content and EHR vendor specifications. The customized CDS tool underwent a user-centered design process informed by implementation science principles, with input from a cross disciplinary team. The customized CDS tool replaced the commercial CDS tool. Data were collected from the electronic health record via analytic reports and manual chart review. The primary outcome was effectiveness, defined as whether the clinician changed their behavior and did not prescribe an NSAID. A random sample of 366 alerts (183 per CDS tool) was evaluated that represented 355 unique patients. The commercial CDS tool was effective for 7 of 172 (4%) patients, while the customized CDS tool was effective for 81 of 183 (44%) patients. After adjusting for age, chronic kidney disease, ejection fraction, NYHA class, concurrent prescription of an opioid or acetaminophen, visit type (inpatient or outpatient), and clinician specialty, the customized alerts were at 24.3 times greater odds of effectiveness compared to the commercial alerts (OR: 24.3 CI: 10.20-58.06). Investing additional resources to customize a CDS tool resulted in a CDS tool that was more effective at reducing the total number of NSAID orders placed for patients with HF compared to a commercially available CDS tool.

Measuring integrated team-based oncology care: Developing a novel chart abstraction tool.

316 Background: In December 2018, the Livestrong Cancer Institutes (LCI) launched the CaLM Model of Whole-Person Cancer Care. Compared to traditional models of oncology care, CaLM offers integrated interdisciplinary supportive care. As team-based care delivery models like CaLM begin to become more predominant, health IT infrastructure and systems are failing to adequately capture and measure simple clinical data on team-based encounters. Athena, our EHR, lacked discrete fields to capture necessary data from shared appointments in order to evaluate patient utilization of team-based longitudinal care; requiring us to develop a manual chart abstraction to evaluate the clinical model. Methods: We performed a literature review and environmental scan on chart abstraction for team-based care. When limited results were found, we sought to develop a novel tool in REDCap. We developed a list of variables and domains that required measurement and worked with IT to determine which, if any, could be generated automatically in reports in the Athena EHR. Remaining domains (12 domains and 151 unique data points) were strategically embedded in a methodological abstraction tool that mapped closely to the logic and flow of the EHR. We tested the tool and iterated over three months in 2019. Before abstraction began, we developed and executed a two module, four hour training for data collectors to ensure quality data collection. Over a one year period, four abstractors pulled data from over 400 individual patient charts in the EHR. Results: We developed a unique two-phase quality assurance (QA) algorithm. Phase 1- We randomly selected 10% of patient records; two abstractors completed dual data entry (same chart). Dual data entry controls for discrepant values that can be common in large datasets. A third-party team reviewed both charts, recording discrepancies by category, harmonizing charts, and data was used to retrain data collectors during weekly meetings. Highest discrepancies occurred when documenting treatment history (95%). For 89% of records, there were differences in psychosocial utilization. As a result of these discrepancies, we opted to extend QA- the remaining 90% of records were reviewed by third party scanning half of domains for accuracy. The chart abstraction was successfully completed on over 400 patient charts; the process took over 18 months to complete. Conclusions: Analyzing patters of team-based care is likely a manual process, regardless of EHR vendor. Our tool is well-structured with the ability to be open source, so that other clinics can utilize our tool in lieu of replicating the same painstaking process.

Electronic case reporting (eCR) of COVID-19 to public health: implementation perspectives from the Minnesota Department of Health.

Electronic case reporting (eCR) is the automated generation and transmission of case reports from electronic health records to public health for review and action. These reports (electronic initial case reports: eICRs) adhere to recommended exchange and terminology standards. eCR is a partnership of the Centers for Disease Control and Prevention (CDC), Association of Public Health Laboratories (APHL) and Council of State and Territorial Epidemiologists (CSTE). The Minnesota Department of Health (MDH) received eICRs for COVID-19 from April 2020 (3 sites, manual process), automated eCR implementation in August 2020 (7 sites), and on-boarded ∼1780 clinical units in 460 sites across 6 integrated healthcare systems (through March 2022). Approximately 20 000 eICRs/month were reported to MDH during high-volume timeframes. With increasing provider/health system implementation, the proportion of COVID-19 cases with an eICR increased to 30% (March 2022). Evaluation of data quality for select demographic variables (gender, race, ethnicity, email, phone, language) across the 6 reporting health systems revealed a high proportion of completeness (>80%) for half of variables and less complete data for rest (ethnicity, email, language) along with low ethnicity data (<50%) for one health system. Presently eCR implementation at MDH includes only one EHR vendor. Next steps will focus on onboarding other EHRs, additional eICR data extraction/utilization, detailed analysis, outreach to address data quality issues, and expanding to other reportable conditions.

Developing a Pediatric EHR Testing & Certification Program in the USA: Initial Phase.

In 2016, the 21st Century Cures Act included ONC's 10 functionality recommendations for voluntary testing and certification of pediatric EHRs. Since 2019, Drummond has been developing a new pediatric EHR testing and certification program with pediatric and industry experts. The testing criteria are based upon AAP's 47 requirements that include ONC's 10 recommendations. It is anticipated the program will be operationalized and ready for EHR vendors in 1Q2022.

How Do Dental Clinicians Obtain Up-To-Date Patient Medical Histories? Modeling Strengths, Drawbacks, and Proposals for Improvements.

BackgroundAccess to up-to-date patient medical history is essential for dental clinicians (DCs) to avoid potential harm to patients and to improve dental treatment outcomes. The predominant approach for dental clinicians (DCs) to gather patients' medical history is through patient-reported medical histories and medical consults. However, studies reported varied concordance and reliability of patient-reported medical conditions and medication histories compared to the patient medical records and this process also places a significant burden on patients. Information technology tools/platforms such as an integrated electronic health record containing an electronic dental record module may address these issues. However, these integrated systems are expensive and technically complex and may not be easily adopted by DCs in solo and small group practice who provide the most dental care. The recent expansion of regional healthcare information exchange (HIE) provides another approach, but to date, studies on connecting DCs with HIE are very limited. Our study objectives were to model different aspects of the current approaches to identify the strengths and weaknesses, and then model the HIE approach that addresses the weaknesses and retain the strengths of current approaches. The models of current approaches identified the people, resources, organizational aspects, workflow, and areas for improvement; while models of the HIE approach identified system requirements, functions, and processes that may be shared with software developers and other stakeholders for future development.MethodsThere are three phases in this study. In Phase 1, we retrieved peer-reviewed PubMed indexed manuscripts published between January 2013 and November 2020 and extracted modeling related data from selected manuscripts. In Phase 2, we built models for the current approaches by using the Integrated DEFinition Method 0 function modeling method (IDEF0), the Unified Modeling Language (UML) Use Case Diagram, and Business Process Model and Notation (BPMN) methods. In Phase 3, we created three conceptual models for the HIE approach.ResultsFrom the 47 manuscripts identified, three themes emerged: 1) medical consult process following patient-reported medical history, 2) integrated electronic dental record-electronic health record (EDR-EHR), and 3) HIE. Three models were built for each of the three themes. The use case diagrams described the actions of the dental patients, DCs, medical providers and the use of information systems (EDR-EHR/HIE). The IDEF0 models presented the major functions involved. The BPMN models depicted the detailed steps of the process and showed how the patient's medical history information flowed through different steps. The strengths and weaknesses revealed by the models of the three approaches were also compared.ConclusionsWe successfully modeled the DCs' current approaches of accessing patient medical history and designed an HIE approach that addressed the current approaches' weaknesses as well as leveraged their strengths. Organizational management and end-users can use this information to decide the optimum approach to integrate dental and medical care. The illustrated models are comprehensive and can also be adopted by EHR and EDR vendors to develop a connection between dental systems and HIEs.

How can we Develop a Standard Interface that easily Integrates with Hl7, boosting EHR Interoperability?

Background: It appears that a systematic strategy that includes the basic underpinnings of health care, from systems and technologies to clinical understanding and workflow processes, is required to achieve the next great leap in improving quality and safety. To make meaningful progress, health-care systems integration is essential. However, to provide interoperability in EHR, systems must support all versions of HL7.Software companies and healthcare organisations are still having trouble integrating HL7 with multiple interfaces. Thus, a standard interface or platform is required that easily integrates with HL7 boosting EHR interoperability. Methods: Basic Modelling Interface (BMI) interoperability standards will be the focus of this research. The research plan proposes a qualitative research approach that includes clinicians’ interview and a panel discussion to characterise the information flow models. Qualitative research using a thematic analysis of semi structured interviews will be conducted in the proposed research plan. Results: Gaining the HL7 standard is insufficient for integrating EHR with diverse apps or software in use, thus clinicians' willingness to adopt a common interface is critical. Medical practitioners and software vendors agreement required to develop an API that tackles HL7 integration issues and EHR interoperability. Planning techniques for dealing with HL7 issues and doing coordinated testing can help identify and install HL7 standard interfaces successfully. Conclusions: The proposed research plan will help us to create a standard interface for HL7 integration which will benefit clinicians, healthcare professionals, and groups such as patients, healthcare authorities, and EHR vendors. Lastly, reducing or eliminating healthcare concerns will help the economy, ecosystem, and society in both concrete and qualitative ways.

Quantitating and assessing interoperability between electronic health records.

Electronic health records (EHRs) contain a large quantity of machine-readable data. However, institutions choose different EHR vendors, and the same product may be implemented differently at different sites. Our goal was to quantify the interoperability of real-world EHR implementations with respect to clinically relevant structured data. We analyzed de-identified and aggregated data from 68 oncology sites that implemented 1 of 5 EHR vendor products. Using 6 medications and 6 laboratory tests for which well-accepted standards exist, we calculated inter- and intra-EHR vendor interoperability scores. The mean intra-EHR vendor interoperability score was 0.68 as compared to a mean of 0.22 for inter-system interoperability, when weighted by number of systems of each type, and 0.57 and 0.20 when not weighting by number of systems of each type. In contrast to data elements required for successful billing, clinically relevant data elements are rarely standardized, even though applicable standards exist. We chose a representative sample of laboratory tests and medications for oncology practices, but our set of data elements should be seen as an example, rather than a definitive list. We defined and demonstrated a quantitative measure of interoperability between site EHR systems and within/between implemented vendor systems. Two sites that share the same vendor are, on average, more interoperable. However, even for implementation of the same EHR product, interoperability is not guaranteed. Our results can inform institutional EHR selection, analysis, and optimization for interoperability.

Measuring time clinicians spend using EHRs in the inpatient setting: a national, mixed-methods study.

To understand hospitals' use of EHR audit-log-based measures to address burden associated with inpatient EHR use. Using mixed methods, we analyzed 2018 American Hospital Association Information Technology Supplement Survey data (n = 2864 hospitals; 64% response rate) to characterize measures used and provided by EHR vendors to track clinician time spent documenting. We interviewed staff from the top 3 EHR vendors that provided these measures. Multivariable analyses identified variation in use of the measures among hospitals with these 3 vendors. 53% of hospitals reported using EHR data to track clinician time documenting, compared to 68% of the hospitals using the EHR from the top 3 vendors. Among hospitals with EHRs from these vendors, usage was significantly lower among rural hospitals and independent hospitals (P < .05). Two of these vendors provided measures of time spent doing specific tasks while the third measured an aggregate of auditable activities. Vendors varied in the underlying data used to create measures, measure specification, and data displays. Tools to track clinicians' documentation time are becoming more available. The measures provided differ across vendors and disparities in use exist across hospitals. Increasing the specificity of standards underlying the data would support a common set of core measures making these measures more widely available. Although half of US hospitals use measures of time spent in the EHR derived from EHR generated data, work remains to make such measures and analyses more broadly available to all hospitals and to increase its utility for national burden measurement.

Association of Electronic Health Record Vendors With Hospital Financial and Quality Performance: Retrospective Data Analysis.

BackgroundElectronic health records (EHRs) are a central feature of care delivery in acute care hospitals; however, the financial and quality outcomes associated with system performance remain unclear.ObjectiveIn this study, we aimed to evaluate the association between the top 3 EHR vendors and measures of hospital financial and quality performance.MethodsThis study evaluated 2667 hospitals with Cerner, Epic, or Meditech as their primary EHR and considered their performance with regard to net income, Hospital Value–Based Purchasing Total Performance Score (TPS), and the unweighted subdomains of efficiency and cost reduction; clinical care; patient- and caregiver-centered experience; and patient safety. We hypothesized that there would be a difference among the 3 vendors for each measure.ResultsNone of the EHR systems were associated with a statistically significant financial relationship in our study. Epic was positively associated with TPS outcomes (R2=23.6%; β=.0159, SE 0.0079; P=.04) and higher patient perceptions of quality (R2=29.3%; β=.0292, SE 0.0099; P=.003) but was negatively associated with patient safety quality scores (R2=24.3%; β=−.0221, SE 0.0102; P=.03). Cerner and Epic were positively associated with improved efficiency (R2=31.9%; Cerner: β=.0330, SE 0.0135, P=.01; Epic: β=.0465, SE 0.0133, P<.001). Finally, all 3 vendors were associated with positive performance in the clinical care domain (Epic: β=.0388, SE 0.0122, P=.002; Cerner: β=.0283, SE 0.0124, P=.02; Meditech: β=.0273, SE 0.0123, P=.03) but with low explanatory power (R2=4.2%).ConclusionsThe results of this study provide evidence of a difference in clinical outcome performance among the top 3 EHR vendors and may serve as supportive evidence for health care leaders to target future capital investments to improve health care delivery.

Provider participation in the Florida Medicaid Promoting Interoperability program: Practice characteristics, meaning use attestations, and incentive payments

ObjectiveThe objective of this study was to quantify the rate of provider participation beyond year 1 incentive in the Florida Medicaid Promoting Interoperability (PI) program, formerly the Electronic Health Record Incentive program, and identify the provider and practice characteristics associated with Meaningful Use attestations. Methods and materialsWe conducted a retrospective cohort study using the 2011–2018 records from the PI program, Provider Participation Database. Bivariate associations between Meaningful Use and categorical and ordinal variables were tested using Chi-square and Mantel-Haenszel Chi-square, respectively, with results informing logistic regressions. Adjusted odds ratios and 95 % confidence intervals are reported. ResultsWe found that 42.56 % of Florida Medicaid providers achieved Meaningful Use after receiving first-year incentives. Logistic regression showed that pediatricians represented the largest percentage of providers who achieved Meaningful Use (65.06 %) while dentists had the lowest Meaningful Use (7.78 %). We also found that certain geographic areas and various EHR vendors were associated with higher rates of providers Meaningful Use attestation. DiscussionAlthough the PI program successfully influenced the adoption of a basic EHR system, low Meaningful Use attestations have inadvertently created a digital “advanced use” divide among providers who serve large numbers of Medicaid patients. This is concerning because advanced EHR functions are necessary precursors to address unmet socioeconomic needs to reduce health disparities. ConclusionFlorida has distributed over $100 million to Medicaid providers who ultimately did not achieve Meaningful Use after collecting their first-year incentive. Policy interventions that can promote advanced EHR use functions are necessary to optimize technology in low-resourced practice settings where the potential benefits are greater.

Structured Data Capture for Oncology.

Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC’s primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data’s lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic—SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document.

Moving toward a sociotechnical systems approach to continuous health information technology design: the path forward for improving electronic health record usability and reducing clinician burnout.

Based on our analysis of descriptions provided by four EHR vendors on their EHR usability efforts, we provide three recommendations aimed at improving the usability of health information technology and reducing clinician burnout. First, EHR vendors need to dedicate increased attention to the design of the entire sociotechnical (work) system, including the EHR technology and its usability as well as the interactions of the technology with other system elements. Second, EHR vendors need to deepen and broaden their understanding of the work of clinicians and care teams by using diverse and mixed method. Third, in collaboration with health care organizations, EHR vendors should engage in cycles of continuous design and learning in order to improve the usability of health IT.

Information blocking remains prevalent at the start of 21st Century Cures Act: results from a survey of health information exchange organizations.

Recent policy making aims to prevent health systems, lectronic health record (EHR) vendors, and others from blocking the electronic sharing of patient data necessary for clinical care. We sought to assess the prevalence of information blocking prior to enforcement of these rules. We conducted a national survey of health information exchange organizations (HIEs) to measure the prevalence of information blocking behaviors observed by these third-party entities. Eighty-nine of 106 HIEs (84%) meeting the inclusion criteria responded. The majority (55%) of HIEs reported that EHR vendors at least sometimes engage in information blocking, while 30% of HIEs reported the same for health systems. The most common type of information blocking behavior EHR vendors engaged in was setting unreasonably high prices, which 42% of HIEs reported routinely observing. The most common type of information blocking behavior health systems engaged in was refusing to share information, which 14% of HIEs reported routinely observing. Reported levels of vendor information blocking was correlated with regional competition among vendors and information blocking was concentrated in some geographic regions. Our findings are consistent with early reports, revealing persistently high levels of information blocking and important variation by actor, type of behavior, and geography. These trends reflect the observations and experiences of HIEs and their potential biases. Nevertheless, these data serve as a baseline against which to measure the impact of new regulations and to inform policy makers about the most common types of information blocking behaviors. Enforcement aimed at reducing information blocking should consider variation in prevalence and how to most effectively target efforts.

Measures of electronic health record use in outpatient settings across vendors.

Electronic health record (EHR) log data capture clinical workflows and are a rich source of information to understand variation in practice patterns. Variation in how EHRs are used to document and support care delivery is associated with clinical and operational outcomes, including measures of provider well-being and burnout. Standardized measures that describe EHR use would facilitate generalizability and cross-institution, cross-vendor research. Here, we describe the current state of outpatient EHR use measures offered by various EHR vendors, guided by our prior conceptual work that proposed seven core measures to describe EHR use. We evaluate these measures and other reporting options provided by vendors for maturity and similarity to previously proposed standardized measures. Working toward improved standardization of EHR use measures can enable and accelerate high-impact research on physician burnout and job satisfaction as well as organizational efficiency and patient health.

Quantifying the competitiveness of the electronic health record market and its implications for interoperability

ObjectiveThe objective of this study was to quantify both the competitiveness of the EHR vendor market in the United States of America (US) and the degree of fragmentation of individual Medicare beneficiaries’ medical records across the differing EHR vendors found in the US healthcare system. Methods and materialsWe determined the Part A and Part B Medicare-expenditure weighted market shares of EHR vendors and estimated the rate of attestation of meaningful use (MU) for EHRs among Medicare Part A & B providers from 2011 to 2016. Based on these data we calculated the annual Herfindahl-Hirschman Index to quantify the competitiveness of the EHR market as well as the number of vendors individual Medicare beneficiaries’ medical records were stored in for the period 2014–2016. ResultsWe find that as of 2016 the EHR vendor environment was competitive but trending towards becoming highly concentrated soon. We also found that patient medical records were highly fragmented as only 4.5 % of expenditure-weighted individual Medicare beneficiaries had their MU medical records associated with a single vendor, while 19.8 % of expenditure-weighted beneficiaries had their MU medical records stored in 8 or more vendors. DiscussionThese results indicate that there are tradeoffs between EHR market competition, and the challenges associated with achieving interoperability across numerous competing vendors. ConclusionUncertainty of interoperability among different EHR vendors may make transmission of medical records among different providers challenging, mitigating the benefit of vendor competition. This highlights the critical importance of current interoperability efforts moving forward.

The DREAM Initiative: study protocol for a randomized controlled trial testing an integrated electronic health record and community health worker intervention to promote weight loss among South Asian patients at risk for diabetes

BackgroundElectronic health record (EHR)-based interventions that use registries and alerts can improve chronic disease care in primary care settings. Community health worker (CHW) interventions also have been shown to improve chronic disease outcomes, especially in minority communities. Despite their potential, these two approaches have not been tested together, including in small primary care practice (PCP) settings. This paper presents the protocol of Diabetes Research, Education, and Action for Minorities (DREAM) Initiative, a 5-year randomized controlled trial integrating both EHR and CHW approaches into a network of PCPs in New York City (NYC) in order to support weight loss efforts among South Asian patients at risk for diabetes.Methods/designThe DREAM Initiative was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (National Institutes of Health). A total of 480 individuals at risk for type 2 diabetes will be enrolled into the intervention group, and an equal number will be included in a matched control group. The EHR intervention components include the provision of technical assistance to participating PCPs regarding prediabetes-related registry reports, alerts, and order sets. The CHW intervention components entail group education sessions on diabetes prevention, including weight loss and nutrition. A mixed-methods approach will be used to evaluate the feasibility, adoption, and impact (≥ 5% weight loss) of the integrated study components. Additionally, a cost effectiveness analysis will be conducted using outcomes, implementation costs, and healthcare claims data to determine the incremental cost per person achieving 5% weight loss.DiscussionThis study will be the first to test the efficacy of an integrated EHR–CHW intervention within an underserved, minority population and in a practical setting via a network of small PCPs in NYC. The study’s implementation is enhanced through cross-sector partnerships, including the local health department, a healthcare payer, and EHR vendors. Through use of a software platform, the study will also systematically track and monitor CHW referrals to social service organizations. Study findings, including those resulting from cost-effectiveness analyses, will have important implications for translating similar strategies to other minority communities in sustainable ways.Trial registrationThis study protocol has been approved and is made available on ClinicalTrials.gov by NCT 03188094 as of 15 June 2017.

Evaluation of First Electronic Case Reports received in Illinois

ObjectiveComparison of content in eCR and ELR cases reportingReview technical challenges and strategies for data managementIntroductionCommunicable disease reporting from providers can be a time-consuming process that results in delayed or incomplete reporting of infectious diseases, limiting public health's ability to respond quickly to prevent or control disease. The recent development of an HL7 standard for automated Electronic initial case reports (eICR) represents an important advancement for public health surveillance. The Illinois Department of Public Health (IDPH) participated in a pilot with the Public Health Informatics Institute and an Illinois-based provider group to accept eICR reports for Gonorrhea and Chlamydia.MethodsThe provider group working with their EHR vendor submitted a batch of CT and GC reports directly to IDPH in September 2017 according to the published eICR standard. A summary of the provider and PHII work has been presented previously in the STI eCR Learning Community. The eICR reports received from the provider were compared to case report data in the communicable disease surveillance system, I-NEDSS. Data was extracted from I-NEDSS that included race and ethnicity, timing of specimen collection, result, ELR submission surveillance action and treatment.ResultsIDPH received a batch of 89 files containing 77 unique persons, with 54 chlamydia (CT), 13 Gonorrhea (GC) and 10 co-infected case reports. The communicable disease surveillance system had captured 76 (98.7%) of the persons reported in the pilot. Among those, an Electronic Laboratory Report (ELR) was received for 72 (95%) cases, on average within 1 day of the lab report date. Data in I-NEDSS had a completion of 45% for race and ethnicity compared to 99% for race and 92% for ethnicity in the eICR files. Information on treatment in the surveillance system was reported for 18 (24%) cases compared to 67 (87%) cases.ConclusionsThis pilot was the first submission of real patient data submitted using the eICR standard to IDPH. Data was more complete from provider eICR reports for key demographic of race and ethnicity and treatment. A comparison with the current surveillance system showed near complete and timely case capture from ELR data. Integrated reporting of both ELR and eICR can produce a more complete case report through automated submissions and potentially reduce burden of data collection on health department communicable disease investigators. As public health reporting moves in this direction, public health agencies will have some substantial tasks to correctly ingest, map and interpret the increased amounts of information that are contained in the eICR. Further, the advantages of case reporting will be dependent on automated processes within the communicable disease system to merge data and apply business rules to automatically process completed case reports for high volume diseases, such as STIs. This work will continue as providers are ready to submit reports from different vendor products from a near real-time production environment.

Updates to the HL7 2.5.1 Implementation Guide for Syndromic Surveillance

Updates to the HL7 2.5.1 Implementation Guide for Syndromic Surveillance