An Innovative Approach to Using Electronic Health Records Through Health Information Exchange to Build a Chronic Disease Registry in Michigan.

Michigan's CHRONICLE, the Chronic Disease Registry Linking Electronic Health Record Data, is a near-real-time disease monitoring system designed to harness electronic health record (EHR) data and existing health information exchange (HIE) infrastructure for transformative public health surveillance. Strong evidence indicates that using EHR data in chronic disease monitoring will provide rapid insight over time on health care use, outcomes, and public health interventions. We examined the potential of EHR data for chronic disease surveillance through close collaboration with our statewide HIE network and 2 participating health systems. We describe the development of CHRONICLE, the promising findings from its implementation, the identified challenges, and how those challenges will inform the next steps in testing, refining, and expanding the system. By detailing our approach to developing CHRONICLE and the considerations and early steps required to build an innovative, EHR-based chronic disease registry, we aim to inform public health leaders and professionals on the value of EHR data for chronic disease surveillance. With systematic testing, evaluation, and enhancement, our goal for CHRONICLE, as a fully realized and comprehensive surveillance system, is to model how collaborative health information exchange can support evidence-based strategies, resource allocation, and precision in disease monitoring.

Brochure: Diálogos de saberes

Los diálogos de saberes, también llamados diálogos interculturales, son procesos de comunicación e intercambio entre personas, grupos o comunidades que provienen de diferentes orígenes o culturas. En el caso del sector de la salud, los intercambios se realizan entre determinados grupos o personas y personal de salud capacitado. Su objetivo es, entre otros, mejorar el acceso a los servicios de salud y construir una salud intercultural, con énfasis en la resolución de problemas previamente planteados y sus causas, la comprensión mutua y la creación de vínculos sólidos. Este brochure describe de manera general el proceso que tienen los diálogos de saberes.

Redefining Health Care Data Interoperability: Empirical Exploration of Large Language Models in Information Exchange.

BACKGROUND: Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced language models, such as large language models (LLMs), may help overcome current challenges in information exchange. OBJECTIVE: This study aims to evaluate the capability of LLMs in transforming and transferring health care data to support interoperability. METHODS: Using data from the Medical Information Mart for Intensive Care III and UK Biobank, the study conducted 3 experiments. Experiment 1 assessed the accuracy of transforming structured laboratory results into unstructured format. Experiment 2 explored the conversion of diagnostic codes between the coding frameworks of the ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), and Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) using a traditional mapping table and a text-based approach facilitated by the LLM ChatGPT. Experiment 3 focused on extracting targeted information from unstructured records that included comprehensive clinical information (discharge notes). RESULTS: The text-based approach showed a high conversion accuracy in transforming laboratory results (experiment 1) and an enhanced consistency in diagnostic code conversion, particularly for frequently used diagnostic names, compared with the traditional mapping approach (experiment 2). In experiment 3, the LLM showed a positive predictive value of 87.2% in extracting generic drug names. CONCLUSIONS: This study highlighted the potential role of LLMs in significantly improving health care data interoperability, demonstrated by their high accuracy and efficiency in data transformation and exchange. The LLMs hold vast potential for enhancing medical data exchange without complex standardization for medical terms and data structure.

Is Electronic Information Exchange Associated With Lower 30-Day Readmission Charges Among Medicare Beneficiaries?

OBJECTIVE: Fragmented readmissions, when admission and readmission occur at different hospitals, are associated with increased charges compared with nonfragmented readmissions. We assessed if hospital participation in health information exchange (HIE) was associated with differences in total charges in fragmented readmissions. DATA SOURCE: Medicare Fee-for-Service Data, 2018. STUDY DESIGN: We used generalized linear models with hospital referral region and readmission month fixed effects to assess relationships between information sharing (same HIE, different HIEs, and no HIE available) and total charges of 30-day readmissions among fragmented readmissions; analyses were adjusted for patient-level clinical/demographic characteristics and hospital-level characteristics. DATA EXTRACTION METHODS: We included beneficiaries with a hospitalization for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, syncope, urinary tract infection, dehydration, or behavioral issues with a 30-day readmission for any reason. PRINCIPAL FINDINGS: In all, 279,729 admission-readmission pairs were included, 27% of which were fragmented (n=75,438); average charges of fragmented readmissions were $64,897-$71,606. Compared with fragmented readmissions where no HIE was available, the average marginal effects of same-HIE and different-HIE admission-readmission pairs were -$2329.55 (95% CI: -7333.73, 2674.62) and -$3905.20 (95% CI: -7592.85, -307.54), respectively. While the average marginal effects of different-HIE pairs were lower than those for no-HIE fragmented readmissions, the average marginal effects of same-HIE and different-HIE pairs were not significantly different from each other. CONCLUSIONS: There were no statistical differences in charges between fragmented readmissions to hospitals that share an HIE or that do not share an HIE compared with hospitals with no HIE available.

Exploring the impact of primary care utilization and health information exchange upon treatment patterns and clinical outcomes of glioblastoma patients.

PURPOSE: There is limited literature describing care coordination for patients with glioblastoma (GBM). We aimed to investigate the impact of primary care and electronic health information exchange (HIE) between neurosurgeons, oncologists, and primary care providers (PCP) on GBM treatment patterns, postoperative outcomes, and survival. METHODS: We identified adult GBM patients undergoing primary resection at our institution (2007-2020). HIE was defined as shared electronic medical information between PCPs, oncologists, and neurosurgeons. Multivariate logistic regression analyses were used to determine the effect of PCPs and HIE upon initiation and completion of adjuvant therapy. Kaplan-Meier and multivariate Cox regression models were used to evaluate overall survival (OS). RESULTS: Among 374 patients (mean age ± SD: 57.7 ± 13.5, 39.0% female), 81.0% had a PCP and 62.4% had electronic HIE. In multivariate analyses, having a PCP was associated with initiation (OR: 7.9, P < 0.001) and completion (OR: 4.4, P < 0.001) of 6 weeks of concomitant chemoradiation, as well as initiation (OR: 4.0, P < 0.001) and completion (OR: 3.0, P = 0.007) of 6 cycles of maintenance temozolomide thereafter. Having a PCP (median OS [95%CI]: 14.6[13.1-16.1] vs. 10.8[8.2-13.3] months, P = 0.005) and HIE (15.40[12.82-17.98] vs. 13.80[12.51-15.09] months, P = 0.029) were associated with improved OS relative to counterparts in Kaplan-Meier analysis and in multivariate Cox regression analysis (hazard ratio [HR] = 0.7, [95% CI] 0.5-1.0, P = 0.048). In multivariate analyses, chemoradiation (HR = 0.34, [95% CI] 0.2-0.7, P = 0.002) and maintenance temozolomide (HR = 0.5, 95%CI 0.3-0.8, P = 0.002) were associated with improved OS relative to counterparts. CONCLUSION: Effective care coordination between neurosurgeons, oncologists, and PCPs may offer a modifiable avenue to improve GBM outcomes.

Social determinants of health predict readmission following COVID-19 hospitalization: a health information exchange-based retrospective cohort study.

Introduction: Since February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States. Methods: A retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022. Results and discussion: In this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90 days (n = 19,679), and 13% were readmitted within 30 days (n = 11,912). In logistic regression analyses, Hispanic and non-Hispanic Asian patients were less likely to be readmitted within 90 days (adjusted odds ratio [aOR]: 0.8, 95% confidence interval [CI]: 0.7-0.9, and aOR: 0.8, 95% CI: 0.8-0.8), while non-Hispanic Black patients were more likely to be readmitted (aOR: 1.1, 95% CI: 1.0-1.1, p = 0.002), compared to non-Hispanic White patients. Area deprivation index displayed a clear dose-response relationship to readmission: patients living in the most disadvantaged neighborhoods were more likely to be readmitted within 30 (aOR: 1.1, 95% CI: 1.0-1.2), 60 (aOR: 1.1, 95% CI: 1.2-1.2), and 90 days (aOR: 1.2, 95% CI: 1.1-1.2), compared to patients from the least disadvantaged neighborhoods. Our findings demonstrate the lasting impact of COVID-19, especially among members of marginalized communities, and the increasing burden of COVID-19 morbidity on the healthcare system.

Real world performance of the 21st Century Cures Act population-level application programming interface.

OBJECTIVE: To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule. MATERIALS AND METHODS: We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR. RESULTS: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12 000 resources/min. DISCUSSION: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. CONCLUSION: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Mapping Injection Order Messages to Health Level 7 Fast Healthcare Interoperability Resources to Collate Infusion Pump Data.

BACKGROUND: When administering an infusion to a patient, it is necessary to verify that the infusion pump settings are in accordance with the injection orders provided by the physician. However, the infusion rate entered into the infusion pump by the health care provider cannot be automatically reconciled with the injection order information entered into the electronic medical records (EMRs). This is because of the difficulty in linking the infusion rate entered into the infusion pump by the health care provider with the injection order information entered into the EMRs. OBJECTIVES: This study investigated a data linkage method for reconciling infusion pump settings with injection orders in the EMRs. METHODS: We devised and implemented a mechanism to convert injection order information into the Health Level 7 Fast Healthcare Interoperability Resources (FHIR), a new health information exchange standard, and match it with an infusion pump management system in a standard and simple manner using a REpresentational State Transfer (REST) application programming interface (API). The injection order information was extracted from Standardized Structured Medical Record Information Exchange version 2 International Organization for Standardization/technical specification 24289:2021 and was converted to the FHIR format using a commercially supplied FHIR conversion module and our own mapping definition. Data were also sent to the infusion pump management system using the REST Web API. RESULTS: Information necessary for injection implementation in hospital wards can be transferred to FHIR and linked. The infusion pump management system application screen allowed the confirmation that the two pieces of information matched, and it displayed an error message if they did not. CONCLUSION: Using FHIR, the data linkage between EMRs and infusion pump management systems can be smoothly implemented. We plan to develop a new mechanism that contributes to medical safety through the actual implementation and verification of this matching system.

Interoperability in the Wild: Comparison of Real-World Electronic C-CDA Documents from Two Sources.

Although health information exchange (HIE) networks exist in multiple nations, providers still require access multiple sources to obtain medical records. We sought to measure and compare differences in data presence and concordance across regional HIE and EHR vendor-based networks. Using 1,054 randomly selected patients from a large health system in the US, we generated consolidated clinical document architecture (C-CDA) documents from each network. 778 (74%) patients had at least one C-CDA document present from either source. Among these patients, two-thirds had information in only one source. All documents contained demographics, but less than half of patients had data in clinical data domains. Moreover, data across HIE networks were not concordant. Results suggest that HIE networks have different, likely complementary, data available for the same patient, suggesting the need for better integration and deduplication for national HIE efforts.

Citizens Access to Health Information in National Portals in the Nordic Countries.

National eHealth portals for citizens are available in the five Nordic countries. This study describes and compares the Nordic citizen portals and identifies variations in content access and functionality. The findings suggest that availability of information and services depend on the organisation of the health system, the connection to national health information exchange platforms and incentives for providing data and services.

Data-Exchange Between Electronic Medical Record and Viral-Load Laboratory Database Towards Improving HIV Care in Ethiopia.

Electronic viral load (VL) Test Ordering and Result Reporting System (ETORRS) was introduced to create data exchange between the existing VL database and the electronic medical record (EMR) system, with the aim of reducing laboratory test results turnaround time (TAT), improving data quality, and supporting timely clinical response for patients with high VL. This use case is an illustrative example of initiating and adopting the principles of health information exchange for a priority health program.

Implementation of an HIV Case Based Surveillance Using Standards-Based Health Information Exchange in Rwanda.

As Rwanda approaches the UNAIDS Fast Track goals which recommend that 95% of HIV-infected individuals know their status, of whom 95% should receive treatment and 95% of those on treatment achieve viral suppression, the country currently relies on an inefficient paper, and disjointed electronic, systems for case-based surveillance (CBS). Rwanda has established an ecosystem of interoperable systems based on open standards to support HIV CBS. Data were successfully exchanged between an EMR, a client registry, laboratory information system and DHIS-2 Tracker, and subsequently, a complete analytic dataset was ingested into MS-Power Business Intelligence (MS-PowerBI) for analytics and visualization of the CBS data. Existing challenges included inadequate workforce capacity to support mapping of data elements to HL7 FHIR resources. Interoperability optimization to support CBS is work in progress and rigorous evaluations on the effect on health information exchange on monitoring patient outcomes are needed.

Preparing community pharmacy teams for health information exchange (HIE).

BACKGROUND: Health information exchanges (HIEs) facilitate health care professionals' electronic sharing of patient information across different organizations. When community pharmacists have access to HIE, they can further contribute to improved patient outcomes. However, several implementation challenges are noted, which impede sustained pharmacist access to HIE. To our knowledge, no bidirectional HIE interface design and pharmacy team-informed implementation process has been documented. In response, our research team designed and developed an HIE interface prototype for use specifically by community pharmacy teams to access local HIE data through their pharmacy dispensing software. OBJECTIVES: To 1) identify barriers, facilitators, and recommendations for using HIE data in community pharmacies and 2) create a curated list of resources addressing identified implementation needs to aid future implementation of a fully functional, bidirectional HIE interface by community pharmacy teams. METHODS: Pharmacists, pharmacy technicians, and patients from three pharmacy sites within the Community Pharmacy Enhanced Services Network of Indiana participated in individual semi-structured interviews. Interview questions were mapped to select constructs across all domains of the Consolidated Framework for Implementation Research. Interview transcripts were deductively coded. A subset of participants participated in Evidence-Based Quality Improvement sessions to iteratively update planned resource items needed to support future HIE implementation. RESULTS: We interviewed 23 total participants: 8 pharmacists, 8 pharmacy technicians, and 7 patients. Five facilitators, four barriers, and two recommendations were identified. These were further characterized into four key implementation needs: instruction on how to use HIE; guidance on workflow and team roles; resources that are patient-facing; and resources that are provider-facing, resulting in 16 planned implementation resources. CONCLUSION: Our study provides the first-of-its-kind list of pharmacy team-informed resources to facilitate sustainability and scalability of HIE implementation in community pharmacies.

Collaborating for COVID-19: Hospital Health Information Exchange and Public Health Partnership.

Background: The coronavirus disease (COVID-19) pandemic highlighted the need for effective communication and information sharing among health care organizations and public health systems (PHSs). Health information exchange (HIE) plays a vital role in improving quality control and efficiency in hospital settings, particularly in underserved areas. Objective: This study aimed to investigate the variation of HIE availability among hospitals based on their collaboration with the PHS and affiliation with Accountable Care Organizations (ACOs) in 2020, as well as variation by community social determinants of health. Methods: The primary data set used for this study comprised the linked data set of the 2020 American Hospital Association (AHA) Annual Survey and the AHA Information Technology Supplement. The measures used included the hospital's participation in HIE networks, availability of data exchange, and HIE measures during the COVID-19 pandemic, including whether hospitals effectively received electronically transmitted information from outside providers for COVID-19 treatment. Results: The sample size of hospitals ranged from 1,316 to 1,436, depending on different outcomes related to HIE questions. Of the hospitals surveyed, ∼67% reported public health collaboration and ACO affiliation, while 7% reported neither. Hospitals without public health collaboration or ACO affiliation were more likely to be located in underserved areas. Compared with hospitals without public health collaboration or ACO affiliation, hospitals with both were 9% more likely to report the availability of electronically transmitted clinical information from outside providers and to participate in local and national HIE networks. Furthermore, these hospitals were 30% (marginal effect [ME] = 0.30, p < 0.001) more likely to report effective receipt of information from outside providers for COVID-19 treatment and 12% (ME = 0.12, p = 0.02) more likely to always/often receive clinical information for COVID-19 treatment electronically. Conclusions: Hospital collaboration with the PHS and ACO affiliation are associated with greater availability of electronic health data, particularly during the COVID-19 pandemic.

Findings from the 2023 Yearbook Section on Health Information Exchange.

OBJECTIVES: To summarize the recent literature and research and present a selection of the best papers published in 2022 related to Health Information Exchange (HIE). METHODS: A systematic review of the literature was performed by the two section editors with the help of a medical librarian. We searched bibliographic databases for HIE-related papers using both MeSH headings and keywords in titles and abstracts. A shortlist of ten candidate best papers was first selected by section editors before being peer-reviewed by Yearbook editors and independent external reviewers. RESULTS: Major themes of the set of ten articles included factors influencing the organizational adoption of HIE and clinicians' use of the information, use of HIE in non-traditional settings, patients' perspectives on HIE, and outcomes of using HIE. CONCLUSIONS: These studies provide suggestions for the research questions, theories, settings, methods, and outcomes that can be fruitfully used for further research on HIE.

Barriers to Health Information Exchange Among Ambulatory Physicians: Results From a Nationally Representative Sample.

PURPOSE: Health information exchange (HIE) improves healthcare quality, but is underutilized by providers. This study used a nationally representative survey of ambulatory physicians to examine barriers to HIE, and identify which barriers have the greatest impact on providers' use of HIE. METHODS: A pooled sample of 1,292 physicians from the 2018-2019 National Electronic Health Record Survey was used. Univariate statistics described rates and patterns of eight common barriers to HIE. Multivariate logistic regression examined the relationship between each barrier and the use of HIE. RESULTS: Barriers to HIE were common and diverse. Negative attitudes toward HIE's ability to improve clinical quality significantly decreased HIE use (OR = .44, p < .01). CONCLUSIONS: To increase adoption of HIE, efforts should focus on addressing providers' negative attitudes toward HIE. These findings can guide targeted implementation strategies to improve HIE adoption.

Social and Health Information Platform: Piloting a Standards-Based, Digital Platform Linking Social Determinants of Health Data into Clinical Workflows for Community-Wide Use.

BACKGROUND: Social determinants of health (SDoH)a are increasingly recognized as a main contributor to clinical health outcomes, but the technologies and workflows within clinics make it difficult for health care providers to address SDoH needs during routine clinical visits. OBJECTIVES: Our objectives were to pilot a digital platform that matches, links, and visualizes patient-level information and community-level deidentified data from across sectors; establish a technical infrastructure that is scalable, generalizable, and interoperable with new datasets or technologies; employ user-centered codesign principles to refine the platform's visualizations, dashboards, and alerts with community health workers, clinicians, and clinic administrators. METHODS: We used privacy-preserving record linkage (PPRL) tools to ensure that all identifiable patient data were encrypted, only matched and displayed with consent, and never accessed or stored by the data intermediary. We used limited data sets (LDS) to share nonidentifiable patient data with the data intermediary through a health information exchange (HIE) to take advantage of existing partner agreements, technical infrastructure, and community clinical data. RESULTS: The platform was successfully piloted in two Federally Qualified Health Clinics by 26 clinic staff. SDoH and demographic data from findhelp were successfully linked, matched, and displayed with clinical and demographic data from the HIE, Connxus. Pilot users tested the platform using real-patient data, guiding the refinement of the social and health information platform's visualizations and alerts. Users emphasized the importance of visuals and alerts that gave quick insights into individual patient SDoH needs, survey responses, and clinic-level trends in SDoH service referrals. CONCLUSION: This pilot shows the importance of PPRL, LDS, and HIE-based data intermediaries in sharing data across sectors and service providers for scalable patient-level care coordination and community-level insights. Clinic staff are integral in designing, developing, and adopting health technologies that will enhance their ability to address SDoH needs within existing workflows without adding undue burdens or additional stress.

Advancing health information during interhospital transfer: An interrupted time series.

INTRODUCTION: Although the transfer of patients between acute care hospitals (interhospital transfer, IHT) is common, health information exchange (HIE) during IHT remains inadequate, with fragmented communication and unreliable access to clinical information. This study aims to design, implement, and rigorously evaluate the implementation of a HIE platform to improve data access during IHT. METHODS AND ANALYSIS: Study subjects include patients aged >18 transferred to the medical, cardiology, oncology, or intensive care unit (ICU) services at an 800-bed quaternary care hospital; and healthcare workers involved in their care. The first aim of this study is to optimize clinician workflow, data visualization, and interoperability through user-centered design sessions for HIE platform development. The second aim is to evaluate the impact of the intervention on clinician-reported medical errors among 500 pre- and 500 postintervention IHT patients using interrupted time series methodology, adjusting for confounding variables and temporal trends. The third aim is to evaluate intervention fidelity, use and perceived usability of the platform, and barriers and facilitators of implementation from interprofessional stakeholder input, using mixed-methods evaluation. The fourth aim is to consolidate key findings to create a toolkit for spread and sustainability. ETHICS AND DISSEMINATION: We will track patient safety endpoints and clinician workflow burdens and ensure the protection of patient data throughout the study. We will disseminate our findings via the creation of a toolkit for spread and sustainability, partnering with our funder (AHRQ) for dissemination, and communicating our results via abstracts and publications.