Using health information exchange to improve public health

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.

Enabling a Learning Public Health System:Enhanced Surveillance of HIV and Other Sexually Transmitted Infections

Sexually transmitted infections (STIs) continue to pose a substantial public health challenge in the United States (US). Surveillance, a cornerstone of disease control and prevention, can be strengthened to promote more timely, efficient, and equitable practices by incorporating health information exchange (HIE) and other large-scale health data sources into reporting. New York City patient-level electronic health record data between January 1, 2018 and June 30, 2023 were obtained from Healthix, the largest US public HIE. Healthix data were linked to neighborhood-level information from the American Community Survey. In this casecontrol study, chlamydia, gonorrhea, and HIV-positive cases were compared to controls to estimate the odds of receiving a specific laboratory test or positive result using generalized estimating equations with logit function and robust standard errors. Among 1,519,121 tests performed for chlamydia, 1,574,772 for gonorrhea, and 1,200,560 for HIV, 2%, 0.6% and 0.3% were positive for chlamydia, gonorrhea, and HIV, respectively. Chlamydia and gonorrhea co-occurred in 1,854 cases (7% of chlamydia and 21% of gonorrhea total cases). Testing behavior was often incongruent with geographic and sociodemographic patterns of positive cases. For example, people living in areas with the highest levels of poverty were less likely to test for gonorrhea but almost twice as likely to test positive compared to those in low poverty areas. Regional HIE enabled review of testing and cases using granular and complementary data not typically available given existing reporting practices. Enhanced surveillance spotlights potential incongruencies between testing patterns and STI risk in certain populations, signaling potential under- and over-testing. These and future insights derived from HIE data may be used to continuously inform public health practice and drive further improvements in provision and evaluation of services and programs.

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.

Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications

Electronic health record (EHR) systems collate patient data, and the integration and standardization of documents through Health Information Exchange (HIE) play a pivotal role in refining patient management. Although the clinical implications of AI in EHR systems have been extensively analyzed, its application in HIE as a crucial source of patient data is less explored. Addressing this gap, our systematic review delves into utilizing AI models in HIE, gauging their predictive prowess and potential limitations. Employing databases such as Scopus, CINAHL, Google Scholar, PubMed/Medline, and Web of Science and adhering to the PRISMA guidelines, we unearthed 1021 publications. Of these, 11 were shortlisted for the final analysis. A noticeable preference for machine learning models in prognosticating clinical results, notably in oncology and cardiac failures, was evident. The metrics displayed AUC values ranging between 61% and 99.91%. Sensitivity metrics spanned from 12% to 96.50%, specificity from 76.30% to 98.80%, positive predictive values varied from 83.70% to 94.10%, and negative predictive values between 94.10% and 99.10%. Despite variations in specific metrics, AI models drawing on HIE data unfailingly showcased commendable predictive proficiency in clinical verdicts, emphasizing the transformative potential of melding AI with HIE. However, variations in sensitivity highlight underlying challenges. As healthcare's path becomes more enmeshed with AI, a well-rounded, enlightened approach is pivotal to guarantee the delivery of trustworthy and effective AI-augmented healthcare solutions.

A State Health Department and Health Information Exchange Partnership: an Effective Collaboration for a Data-Driven Response for COVID-19 Contact Tracing in Maryland

BACKGROUND

Accurate, complete, timely data were essential to effective contact tracing for COVID-19. Maryland Department of Health partnered with Maryland's designated health information exchange, Chesapeake Regional Information System for Our Patients (CRISP), to establish data enhancement processes that provided the foundation for Maryland's successful contact tracing program.

METHODS

Hourly, electronic positive COVID-19 test results were routed through CRISP to the contact tracing data platform. CRISP matched reports against its master patient index to enhance the record with demographic, locating, fatality, vaccination, and hospitalization data. Records were de-duplicated and flagged if associated with a congregate setting, select state universities, or recent international travel. Chi-square tests were used to assess if CRISP-added phone numbers resulted in better contact tracing outcomes.

RESULTS

During June 15, 2020-September 1, 2021, CRISP pushed 531,094 records to the state's contact tracing data platform within an hour of receipt; of those eligible for investigation, 99% had a phone number. CRISP matched 521,731 (98%) records to their master patient index, allowing for deduplication and enrichment. CRISP flagged 15,615 cases in congregate settings and 3,304 cases as university students; these records were immediately routed for outbreak investigation. Records with an added phone number were significantly more likely to be successfully reached compared to cases with no added phone number (p = 0.01).

CONCLUSIONS

CRISP enhanced COVID-19 electronic laboratory reports with a near-instant impact on public health actions. The partnership and data processing workflows can serve as a blueprint for data modernization in public health agencies across the United States.

A qualitative assessment of nonclinical drivers of pediatric outpatient antibiotic prescribing: The importance of continuity

BACKGROUND AND OBJECTIVES

Antibiotic overuse is common in outpatient pediatrics and varies across clinical setting and clinician type. We sought to identify social, behavioral, and environmental drivers of outpatient antibiotic prescribing for pediatric patients.

METHODS

We conducted semistructured interviews with physicians and advanced practice providers (APPs) across diverse outpatient settings including pediatric primary, urgent, and retail care. We used the grounded theory constant comparative method and a thematic approach to analysis. We developed a conceptual model, building on domains of continuity to map common themes and their relationships within the healthcare system.

RESULTS

We interviewed 55 physicians and APPs. Clinicians across all settings prioritized provision of guideline-concordant care but implemented these guidelines with varying degrees of success. The provision of guideline-concordant care was influenced by the patient-clinician relationship and patient or parent expectations (relational continuity); the clinician's access to patient clinical history (informational continuity); and the consistency of care delivered (management continuity). No difference in described themes was determined by setting or clinician type; however, clinicians in primary care described having more reliable relational and informational continuity.

CONCLUSIONS

Clinicians described the absence of long-term relationships (relational continuity) and lack of availability of prior clinical history (informational continuity) as factors that may influence outpatient antibiotic prescribing. Guideline-concordant outpatient antibiotic prescribing was facilitated by consistent practice across settings (management continuity) and the presence of relational and informational continuity, which are common only in primary care. Management continuity may be more modifiable than informational and relational continuity and thus a focus for outpatient stewardship programs.

Establishment of epidemic early warning index system and optimization of infectious disease model: Analysis on monitoring data of public health emergencies

The ability to mitigate the damages caused by emergencies is an important symbol of the modernization of an emergency capability. When responding to emergencies, government agencies and decision makers need more information sources to estimate the possible evolution of the disaster in a more efficient manner. In this paper, an optimization model for predicting the dynamic evolution of COVID-19 is presented by combining the propagation algorithm of system dynamics with the warning indicators. By adding new parameters and taking the country as the research object, the epidemic situation in countries such as China, Japan, Korea, the United States and the United Kingdom was simulated and predicted, the impact of prevention and control measures such as effective contact coefficient on the epidemic situation was analyzed, and the effective contact coefficient of the country was analyzed. The paper strives to provide early warning of emergencies scientifically and effectively through the combination of these two technologies, and put forward feasible references for the implementation of various countermeasures. Judging from the conclusion, this study reaffirmed the importance of responding quickly to public health emergencies and formulating prevention and control policies to reduce population exposure and prevent the spread of the pandemic.

Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review

BACKGROUND

Modern artificial intelligence (AI) and machine learning (ML) methods are now capable of completing tasks with performance characteristics that are comparable to those of expert human operators. As a result, many areas throughout healthcare are incorporating these technologies, including in vitro diagnostics and, more broadly, laboratory medicine. However, there are limited literature reviews of the landscape, likely future, and challenges of the application of AI/ML in laboratory medicine.

CONTENT

In this review, we begin with a brief introduction to AI and its subfield of ML. The ensuing sections describe ML systems that are currently in clinical laboratory practice or are being proposed for such use in recent literature, ML systems that use laboratory data outside the clinical laboratory, challenges to the adoption of ML, and future opportunities for ML in laboratory medicine.

SUMMARY

AI and ML have and will continue to influence the practice and scope of laboratory medicine dramatically. This has been made possible by advancements in modern computing and the widespread digitization of health information. These technologies are being rapidly developed and described, but in comparison, their implementation thus far has been modest. To spur the implementation of reliable and sophisticated ML-based technologies, we need to establish best practices further and improve our information system and communication infrastructure. The participation of the clinical laboratory community is essential to ensure that laboratory data are sufficiently available and incorporated conscientiously into robust, safe, and clinically effective ML-supported clinical diagnostics.

A mixed-method service evaluation of health information exchange in England: technology acceptance and barriers and facilitators to adoption

Background

The need for information exchange and integrated care has stimulated the development of interoperability solutions that bring together patient data across the health and care system to enable effective information sharing. Health Information Exchange (HIE) solutions have been shown to be effective in supporting patient care, however, user adoption often varies among users and care settings. This service evaluation aimed to measure user acceptance of HIE and explore barriers and facilitators to its wider uptake.

Methods

A mixed-method study design was used. A questionnaire was developed using the Unified Theory of Acceptance and Use of Technology and administered to HIE users to assess technology acceptance. Pearson Chi² tests were used to examine differences in acceptance between user groups and care settings. Web-based, semi-structured interviews were conducted drawing on the Normalisation Process Theory to explore barriers and facilitators to adoption. Interview data were analysed thematically using the Framework Approach.

Results

A total of 105 HIE users completed the survey and another 12 participated in the interviews. Significant differences were found in HIE acceptance between users groups and care settings, with high adopters demonstrating higher acceptance and social care users showing lower acceptance. Participants identified several drivers to adoption, including increased information accessibility, better care coordination, informed decision-making, improved patient care, reduced duplication of procedures, and time and cost savings. However, they also highlighted a number of barriers, such as lack of awareness about the solution and its value, suboptimal communication strategies, inadequate training and lack of resources for knowledge dissemination, absence of champions to support the implementation, lack of end-user involvement in the implementation and evaluation of HIE, unclear accountability and responsibility for the overall success of the programme, and patient confidentiality concerns.

Conclusions

Working to better engage stakeholders, considering the needs of users from different care settings, providing users with training resources and support to increase their knowledge and confidence in using the system, developing implementation strategies to seek user feedback and monitor performance, and using communication strategies to increase awareness of the product and its value, can help improve uptake and adoption of HIE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06771-z.

Digital infrastructure evolution as generative entrenchment: The formation of a core–periphery structure

This article empirically investigates the process by which a digital infrastructure evolved and took the architectural form of a digital platform as a core–periphery structure over a 20-year period. Our study pays special attention to the developmental dependencies of the components of the infrastructure’s installed base and how the interdependencies between the platform core and periphery evolve over time. We use the notion of ‘generative entrenchment’ to provide an account of the formation and unfolding of a core–periphery structure from an evolving digital infrastructure that highlights three aspects of the process. First, the process of architectural evolution that our study depicts comprises three phases showing a gradual reversal of the entrenchment relationship of the platform core and periphery: (1) entrenchment of the periphery, (2) mutual entrenchment of the core and periphery, and (3) entrenchment of the core. Second, we show how the generatively entrenched infrastructure’s installed base shaped the decisions and choices regarding the initial platform core. Third, we identify three architectural practices (creating redundancy in the core, augmenting the core with novelty, and reducing the heterogeneity of an entrenched peripheral component and later integrating it into the core) that weakened the entrenchment of the peripheral components, amplified the role of the core, and consolidated the core–periphery structure.

Impact of Provider Prior Use of HIE on System Complexity, Performance, Patient Care, Quality and System Concerns

To date, most HIE studies have investigated user perceptions of value prior to use. Few studies have assessed factors associated with the value of HIE through its actual use. This study investigates provider perceptions on HIE comparing those who had prior experience vs those who had no experience with it. In so doing, we identify six constructs: prior use, system complexity, system concerns, public/population health, care delivery, and provider performance. This study uses a mixed methods approach to data collection. From 15 interviews of medical community leaders, a survey was constructed and administered to 263 clinicians. Descriptive statistics and analysis of variance was used, along with Tukey HSD tests for multiple comparisons. Results indicated providers whom previously used HIE had more positive perceptions about its benefits in terms of system complexity (p = .001), care delivery (p = .000), population health (p = .003), and provider performance (p = .005); women providers were more positive in terms of system concerns (p = .000); patient care (p = .031), and population health (p = .009); providers age 44-55 were more positive than older and younger groups in terms of patient care (p = .032), population health (p = .021), and provider performance (p = .014); while differences also existed across professional license groups (physician, nurse, other license, admin (no license)) for all five constructs (p < .05); and type of organization setting (hospital, ambulatory clinic, medical office, other) for three constructs including system concerns (p = .017), population health (p = .018), and provider performance (p = .018). There were no statistically significant differences found between groups based on a provider's role in an organization (patient care, administration, teaching/research, other). Different provider perspectives about the value derived from HIE use exist depending on prior experience with HIE, age, gender, license (physician, nurse, other license, admin (no license)), and type of organization setting (hospital, ambulatory clinic, medical office, other). This study draws from the theory of planned behavior to understand factors related to physicians' perceptions about HIE value, serving as a departure point for more detailed investigations of provider perceptions and behavior in regard to future HIE use and promoting interoperability.

Generalizable Layered Blockchain Architecture for Health Care Applications: Development, Case Studies, and Evaluation

Background

Data coordination across multiple health care facilities has become increasingly important for many emerging health care applications. Distrust has been recognized as a key barrier to the success of such applications. Leveraging blockchain technology could provide potential solutions tobuild trust between data providers and receivers by taking advantage of blockchain properties such as security, immutability, anonymity, decentralization, and smart contracts. Many health technologies have empirically proven that blockchain designs fit well with the needs of health care applications with certain degrees of success. However, there is a lack of robust architecture to provide a practical framework for developers to implement applications and test the performance of stability, efficiency, and scalability using standard blockchain designs. A generalized blockchain model is needed for the health care community to adopt blockchain technology and develop applications in a timely fashion.

Objective

This study aimed at building a generalized blockchain architecture that provides data coordination functions, including data requests, permission granting, data exchange, and usage tracking, for a wide spectrum of health care application developments.

Methods

An augmented, 3-layered blockchain architecture was built on a private blockchain network. The 3 layers, from bottom to top, are as follows: (1) incorporation of fundamental blockchain settings and smart contract design for data collection; (2) interactions between the blockchain and health care application development environment using Node.js and web3.js; and (3) a flexible development platform that supports web technologies such as HTML, https, and various programing languages. Two example applications, health information exchange (HIE) and clinical trial recruitment, were developed in our design to demonstrate the feasibility of the layered architecture. Case studies were conducted to test the performance in terms of stability, efficiency, and scalability of the blockchain system.

Results

A total of 331,142 simulated HIE requests from accounts of 40,000 patients were successfully validated through this layered blockchain architecture with an average exchange time of 11.271 (SD 2.208) seconds. We also simulated a clinical trial recruitment scenario with the same set of patients and various recruitment criteria to match potential subjects using the same architecture. Potential subjects successfully received the clinical trial recruitment information and granted permission to the trial sponsors to access their health records with an average time of 3.07 seconds.

Conclusions

This study proposes a generalized layered blockchain architecture that offers health technology community blockchain features for application development without requiring developers to have extensive experience with blockchain technology. The case studies tested the performance of our design and empirically proved the feasibility of the architecture in 2 relevant health application domains.

Leveraging Technology to Manage Chagas Disease by Tracking Domestic and Sylvatic Animal Hosts as Sentinels: A Systematic Review

Surveillance of Chagas in the United States show more is known about prevalence in animals and vectors than in humans. Leveraging health information technology (HIT) may augment surveillance efforts for Chagas disease (CD), given its ability to disseminate information through health information exchanges (HIE) and geographical information systems (GISs). This systematic review seeks to determine whether technological tracking of Trypanosoma cruzi–infected domestic and/or sylvatic animals as sentinels can serve as a potential surveillance resource to manage CD in the southern United States. A Boolean search string was used in PubMed and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). Relevance of results was established and analysis of articles was performed by multiple reviewers. The overall Cohen statistic was 0.73, demonstrating moderate agreement among the study team. Four major themes were derived for this systematic review (n = 41): animals act as reservoir hosts to perpetuate CD, transmission to humans could be dependent on cohabitation proximity, variations in T. cruzi genotypes could lead to different clinical manifestations, and leveraging technology to track T. cruzi in domestic animals could reveal prevalent areas or “danger zones.” Overall, our systematic review identified that HIT can serve as a surveillance tool to manage CD. Health information technology can serve as a surveillance tool to manage CD. This can be accomplished by tracking domestic and/or sylvatic animals as sentinels within a GIS. Information can be disseminated through HIE for use by clinicians and public health officials to reach at-risk populations.

Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation

Objective

We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.

Methods

Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions.

Results

LOINC's content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001).

Conclusion

LOINC's content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.

A Survey of LOINC Code Selection Practices Among Participants of the College of American Pathologists Coagulation (CGL) and Cardiac Markers (CRT) Proficiency Testing Programs

Context.—

Biomedical terminologies such as Logical Observation Identifiers, Names, and Codes (LOINC) were developed to enable interoperability of health care data between disparate health information systems to improve patient outcomes, public health, and research activities.

Objective.—

To ascertain the utilization rate and accuracy of LOINC terminology mapping to 10 commonly ordered tests by participants of the College of American Pathologists (CAP) Proficiency Testing program.

Design.—

Questionnaires were sent to 1916 US and Canadian laboratories participating in the 2018 CAP coagulation (CGL) and/or cardiac markers (CRT) surveys requesting information on practice setting, instrument(s) and test method(s), and LOINC code selection and usage in the laboratory and electronic health records.

Results.—

Ninety of 1916 CGL and/or CRT participants (4.7%) responded to the questionnaire. Of the 275 LOINC codes reported, 54 (19.6%) were incorrect: 2 codes (5934-2 and 12345-1) (0.7%) did not exist in the LOINC database and the highest error rates were observed in the property (27 of 275, 9.8%), system (27 of 275, 9.8%), and component (22 of 275, 8.0%) LOINC axes. Errors in LOINC code selection included selection of the incorrect component (eg, activated clotting time instead of activated partial thromboplastin time); selection of panels that can never be used to obtain an individual analyte (eg, prothrombin time panel instead of international normalized ratio); and selection of an incorrect specimen type.

Conclusions.—

These findings of real-world LOINC code implementation across a spectrum of laboratory settings should raise concern about the reliability and utility of using LOINC for clinical research or to aggregate data.

Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension

Background

Electronic health record (EHR) data, collected primarily for individual patient care and billing purposes, compiled in health information exchanges (HIEs) may have a secondary use for population health surveillance of noncommunicable diseases. However, data compilation across fragmented data sources into HIEs presents potential barriers and quality of data is unknown.

Methods

We compared 2015 patient data from a mid-size health system (Database A) to data from System A patients in the Utah HIE (Database B). We calculated concordance of structured data (sex and age) and unstructured data (blood pressure reading and A1C). We estimated adjusted hypertension and diabetes prevalence in each database and compared these across age groups.

Results

Matching resulted in 72,356 unique patients. Concordance between Database A and Database B exceeded 99% for sex and age, but was 89% for A1C results and 54% for blood pressure readings. Sensitivity, using Database A as the standard, was 57% for hypertension and 55% for diabetes. Age and sex adjusted prevalence of diabetes (8.4% vs 5.8%, Database A and B, respectively) and hypertension (14.5% vs 11.6%, respectively) differed, but this difference was consistent with parallel slopes in prevalence over age groups in both databases.

Conclusions

We identified several gaps in the use of HIE data for surveillance of diabetes and hypertension. High concordance of structured data demonstrate some promise in HIEs capacity to capture patient data. Improving HIE data quality through increased use of structured variables may help make HIE data useful for population health surveillance in places with fragmented EHR systems.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7367-z) contains supplementary material, which is available to authorized users.

Designing a communication protocol for acquired immunodeficiency syndrome information exchange

INTRODUCTION

Interoperability will provide similar understanding on the meaning of communicated messages to intelligent systems and their users. This feature is essential for controlling and managing contagious diseases which threaten public health, such as acquired immunodeficiency syndrome (AIDS). The aim of this study was also designing communication protocols for normalizing the content and structure of intelligent messages in order to optimize the interoperability.

MATERIALS AND METHODS

This study used a checklist to extract information content compatible with minimum data set (MDS) of AIDS. After coding information content through selected classification and nomenclature systems, the reliability and validity of codes were evaluated by external agreement method. The MindMaple software was used for mapping the information content to Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED-CT) integrated codes. Finally, the Clinical Document Architecture (CDA) format was used for standard structuring of information content.

RESULTS

The information content standard format, compatible selected classification, or nomenclature system and their codes were determined for all information contents. Their corresponding codes in SNOMED-CT were structured in the form of CDA body and title.

CONCLUSION

The complex and multidimensional nature of AIDS requires the participation of multidisciplinary teams from different organizations, complex analyzes, multidimensional and complex information modeling, and maximum interoperability. In this study, the use of CDA structure along with SNOMED-CT codes is completely compatible with optimal interoperability needs for AIDS control and management.

Hospitals' adoption of intra-system information exchange is negatively associated with inter-system information exchange

Introduction

U.S. policy on interoperable HIT has focused on increasing inter-system (ie, between different organizations) health information exchange. However, interoperable HIT also supports the movement of information within the same organization (ie, intra-system exchange).

Methods

We examined the relationship between hospitals' intra- and inter-system information exchange capabilities among health system hospitals included in the 2010-2014 American Hospital Association's Annual Health Information Technology Survey. We described the factors associated with hospitals that adopted more intra-system than inter-system exchange capability, and explored the extent of new capability adoption among hospitals that reported neither intra- or inter-system information capabilities at baseline.

Results

The prevalence of exchange increased over time, but the adoption of inter-system information exchange was slower; when hospitals adopt information exchange, adoption of intra-system exchange was more common. On average during our study period, hospitals could share 4.6 types of information by intra-system exchange, but only 2.7 types of information by inter-system exchange. Controlling for other factors, hospitals exchanged more types of information in an intra-system manner than inter-system when the number of different inpatient EHR vendors in use in health system is larger.

Conclusion

Consistent with the U.S. goals for more widely accessible patient information, hospitals' ability to share information has increased over time. However, hospitals are prioritizing within-organizational information exchange over exchange between different organizations. If increasing inter-system exchanges is a desired goal, current market incentives and government policies may be insufficient to overcome hospitals' motivations for pursuing an intra-system-information-exchange-first strategy.

Q fever: an under-reported reportable communicable disease

The objective of this study was to provide real-world clinical laboratory-based data to supplement Centers for Disease Control and Prevention (CDC) reporting of Q fever. We analysed titre results of specimens submitted to a large US clinical laboratory for Coxiella burnetii IgG antibody testing from 2010 through 2016. Presumptive Q fever was defined as acute (phase II IgG titre ⩾1:128, phase I titre <1:1024) or chronic (phase I IgG titre ⩾1:1024), based on the results from a single serum specimen. During 2010-2016, an average of 328 presumptive acute Q fever cases were identified at Quest each year, nearly three times the annual average reported to the CDC (122). During the same period, the number of chronic cases identified annually at Quest Diagnostics (34) was similar to that reported to the CDC (29). These findings suggest that CDC data may underestimate the incidence of acute Q fever.

Efficiency of Emergency Physicians: Insights from an Observational Study using EHR Log Files

OBJECTIVE

With federal mandates and incentives since the turn of this decade, electronic health records (EHR) have been widely adopted and used for clinical care. Over the last several years, we have seen both positive and negative perspectives on its use. Using an analysis of log files of EHR use, we investigated the nature of EHR use and their effect on an emergency department's (ED) throughput and efficiency.

METHODS

EHR logs of time spent by attending physicians on EHR-based activities over a 6-week period (n = 2,304 patients) were collected. For each patient encounter, physician activities in the EHR were categorized into four activities: documentation, review, orders, and navigation. Four ED-based performance metrics were also captured: door-to-provider time, door-to-doctor time, door-to-disposition time, and length of stay (LOS). Association between the four EHR-based activities and corresponding ED performance metrics were evaluated.

RESULTS

We found positive correlations between physician review of patient charts, and door-to-disposition time (r = 0.43, p < 0.05), and with LOS (r = 0.48, p < 0.05). There were no statistically significant associations between any of the other performance metrics and EHR activities.

CONCLUSION

The results highlight that longer time spent on reviewing information on the EHR is potentially associated with decreased ED throughput efficiency. Balancing these competing goals is often a challenge of physicians, and its implications for patient safety is discussed.

Quantifying benefits of using health information exchange to support public health STI reporting and treatment in Western New York

OBJECTIVE:

To calculate average savings of using health information exchange (HIE) for demographic and treatment requests for chlamydia and gonorrhoea in Western New York, specifically the Erie County Department of Health and its catchment area.

METHOD:

We conducted a mixed-method case study. Qualitative methods included interviews, document review, and workflow mapping, which were used as the inputs to identify time savings. Case rates, time savings, and salary averages were used to calculate average savings.

RESULTS:

The avoided demographic information requests resulted in time and money savings (range of USD$2312-USD$4624 for chlamydia and USD$809-USD$1512 for gonorrhoea) as did avoided treatment requests (range of USD$671-USD$2803 for chlamydia and USD$981-USD$1635 for gonorrhoea).

DISCUSSION:

HIE supported sexually transmitted infection (STI) treatment by making it easier for public health staff to identify and act upon STI diagnoses. Availability of information online resulted in less reliance on provider offices for demographic and treatment information.

CONCLUSION:

Results indicated that using HIE to support treatment and management of STIs can save public health staff time spent on obtaining demographic and treatment information. Other public health departments could use HIE for this and other types of disease surveillance activities. Considering public health needs in HIE development and use can improve efficiency of public health services and enhance effectiveness of activities.

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting

BACKGROUND

Infectious diseases can appear and spread rapidly. Timely information about disease patterns and trends allows public health agencies to quickly investigate and efficiently contain those diseases. But disease case reporting to public health has traditionally been paper-based, resulting in somewhat slow, burdensome processes. Fortunately, the expanding use of electronic health records and health information exchanges has created opportunities for more rapid, complete, and easily managed case reporting and investigation. To assess how this new service might impact the efficiency and quality of a public health agency's case investigations, we compared the timeliness of usual case investigation to that of case investigations based on case report forms that were partially pre-populated with electronic data.

INTERVENTION

Between September 2013-March 2014, chlamydia disease report forms for certain clinics in Indianapolis were electronically pre-populated with clinical, lab and patient data available through the Indiana Health Information Exchange, then provided to the patient’s doctor. Doctors could then sign the form and deliver it to public health for investigation and population-level disease tracking. Methods: We utilized a novel matched case analysis of timeliness changes in receipt and processing of communicable disease report forms. Each Chlamydia cases reported with the pre-populated form were matched to cases reported in usual ways. We assessed the time from receipt of the case at the public health agency: 1) inclusion of the case into the public health surveillance system and 2) to close to case. A hierarchical random effects model was used to compare mean difference in each outcome between the target cases and the matched cases, with random intercepts for case.

RESULTS

Twenty-one Chlamydia cases were reported to the public health agency using the pre-populated form. Sixteen of these pre-populated form cases were matched to at least one other case, with a mean of 23 matches per case. The mean Reporting Lag for the pre-populated form cases was 2.5 days, which was 2.7 days shorter than the mean Reporting Lag for the matched controls (p = <0.001). The mean time to close a pre-populated form case was 4.7 days, which was 0.2 days shorter than time to close for the matched controls (p = 0.792).

CONCLUSIONS

Use of pre-populated forms significantly decreased the time it took for the local public health agency to begin documenting and closing chlamydia case investigations. Thoughtful use of electronic health data for case reporting may decrease the per-case workload of public health agencies, and improve the timeliness of information about the pattern and spread of disease.

Notifiable condition reporting practices: implications for public health agency participation in a health information exchange

Background

The future of notifiable condition reporting in the United States is undergoing a transformation with the increasing development of Health Information Exchanges which support electronic data-sharing and -transfer networks and the wider adoption of electronic laboratory reporting. Communicable disease report forms originating in clinics are an important source of surveillance data for public health agencies. However, problems of poor data quality and delayed submission of reports to public health agencies are common. In addition, studies of barriers and facilitators to reporting have assumed that the primary reporter is the treating physician, although the extent to which a provider is involved in the reporting workflow is unclear. We sought to better understand the barriers to and burden of notifiable condition reporting from the perspectives of the three primary groups involved in reporting workflow: providers, clinic staff who bear the principal responsibility for reporting, and the public health workers who receive and process reports from clinics. In addition, we sought to situate these findings within the context of the future of notifiable disease reporting and the potential impacts of electronic lab and medical records on the surveillance system.

Methods

Seven ambulatory care clinics and 3 public health agencies that are part of a Health Information Exchange in the state of Indiana, USA, participated in the study. Data were obtained from a survey of clinic physicians (N = 29), interviews with clinic reporters (N = 11), and interviews with public health workers (N = 9). Survey data were summarized descriptively and interview transcripts underwent qualitative analysis.

Results

In both clinics and public health agencies, the laboratory report initiates reporting workflow. Provider involvement with reporting primarily revolves around ordering medications to treat a condition confirmed by the lab result. In clinics, reporting is typically the responsibility of clinic reporters who vary in frequency of reporting. We found an association between frequency of reporting, reporting knowledge and perceptions of reporting burden. In both clinics and public health agencies, interruptions and delays in reporting workflow are encountered due to inaccurate or missing information and impact reporting timeliness, data quality and report completeness. Both providers and clinic reporters lack clarity regarding how data submitted by their reports are used by public health agencies. It is possible that the value of reporting may be diminished when those responsible do not perceive receiving benefit in return. This may account for the low awareness of or recollection of public health communications with clinics that we observed. Despite the high likelihood that public health advisories and guidance are based, in part, on data submitted by clinics, a direct concordance may not be recognized.

Conclusions

Unlike most studies of notifiable condition reporting, this study included the clinic reporters who bear primary responsibility for completing and submitting reports to public health agencies. A primary barrier to this reporting is timely and easy access to data. It is possible that expanded adoption of electronic health record and laboratory reporting systems will improve access to this data and reduce reporting the burden. However, a complete reliance on automatic electronic extraction of data requires caution and necessitates continued interfacing with clinic reporters for the foreseeable future—particularly for notifiable conditions that are high-impact, uncommon, prone to false positive readings by labs, or are hard to verify. An important finding of this study is the association between frequency of reporting, reporting knowledge and perceptions of reporting burden. Increased automation could result in even lower reporting knowledge and familiarity with reporting requirements which could actually increase reporters’ perception of notifiable condition reporting as burdensome. Another finding was of uncertainty regarding how data sent to public health agencies is used or provides clinical benefit. A strong recommendation generated by these findings is that, given their central role in reporting, clinic reporters are a significant target audience for public health outreach and education that aims to alleviate perceived reporting burden and improve reporting knowledge. In particular, communicating the benefits of public health’s use of the data may reduce a perceived lack of information reciprocity between clinical and public health organizations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-017-4156-4) contains supplementary material, which is available to authorized users.

Views of patient, healthcare professionals and administrative staff on flow of information and collaboration in a regional health information exchange: a qualitative study

BACKGROUND

Nowadays, patients can be more involved in developing healthcare services with their healthcare professionals. Patient-centred information is a key part of improving regional health information exchange (HIE), giving patients an active role in care management.

AIM

The aim was to get a deeper understanding of the flow of information and collaboration in one hospital district area from the viewpoint of patients, healthcare professionals and administrative staff.

METHODS

The data were collected by themed interviews and analysed using both deductive and inductive content analyses. The interview themes were the flow of information and collaboration after 5 years of HIE usage in one hospital district area in Finland.

FINDINGS

Health information exchange usage had changed the regional flow of information after the 5-year period. The patients were satisfied that their primary care physician was able to access their special care information. The experiences of healthcare professionals and administrative staff also showed that information availability and information exchange had improved regionally. HIE usage was also found to have improved regional collaboration between different organisations in patient health care.

CONCLUSIONS

It was recognised that patients had taken on more responsibility for transferring their follow-up treatment information. Healthcare information exchange between professionals not only improves patient care or patient involvement in their own care, but it also requires that patient self-care or self-care management is integrated into HIE systems to share information not only among professionals, but also between patients and professionals. This information will be used in the development of healthcare systems to meet more the developing of the continuity of care the patient's point of view.

Crossing Borders: An Online Interdisciplinary Course in Health Informatics for Students From Two Countries

A cross-countries and interprofessional novel approach for delivering an international interdisciplinary graduate health informatics course online is presented. Included in this discussion are the challenges, lessons learned, and pedagogical recommendations from the experiences of teaching the course. Four professors from three different fields and from three universities collaborated in offering an international health informatics course for an interdisciplinary group of 18 US and seven Norwegian students. Highly motivated students and professors, an online technology infrastructure that supported asynchronously communication and course delivery, the ability to adapt the curriculum to meet the pedagogy requirements at all universities, and the support of higher administration for international collaboration were enablers for success. This project demonstrated the feasibility and advantages of an interdisciplinary, interprofessional, and cross-countries approach in teaching health informatics online. Students were able to establish relationships and conduct professional conversations across disciplines and international boundaries using content management software. This graduate course can be used as a part of informatics, computer science, and/or health science programs.

Assessing Skills and Capacity for Informatics: Activities Most Commonly Performed by or for Local Health Departments

OBJECTIVE

To describe the informatics activities performed by and for local health departments.

DESIGN

Analysis of data from the 2015 Informatics Capacity and Needs Assessment Survey of local health departments conducted by the Jiann-Ping Hsu College of Public Health at Georgia Southern University in collaboration with the National Association of County & City Health Officials.

PARTICIPANTS

324 local health departments.

MAIN OUTCOME MEASURE(S)

Informatics activities performed at or for local health departments in use and analysis of data, system design, and routine use of information systems.

RESULTS

A majority of local health departments extract data from information systems (69.5%) and use and interpret quantitative (66.4%) and qualitative (55.1%) data. Almost half use geographic information systems (45.0%) or statistical or other analytical software (39.7%). Local health departments were less likely to perform project management (35.8%), business process analysis and redesign (24.0%), and developing requirements for informatics system development (19.7%). Local health departments were most likely to maintain or modify content of a Web site (72.1%). A third of local health departments (35.8%) reported acting as "super users" for their information systems. A significantly higher proportion of local health departments serving larger jurisdictions (500 000+) and those with shared governance reported conducting informatics activities.

CONCLUSION

Most local health department informatics activities are completed by local health department staff within each department or a central department, but many state health departments also contribute to informatics at the local level. Larger local health departments and those with shared governance were more likely to perform informatics activities. Local health departments need effective leadership, a skilled workforce, strong partnerships, and policies that foster implementation of health information systems to successfully engage in informatics. Local health departments also face important training needs, including data analytics, project management, and geographical information systems, so they can adapt to the increasing availability of electronic data and changes in technology.

Clinical Data Systems to Support Public Health Practice: A National Survey of Software and Storage Systems Among Local Health Departments

CONTEXT

Numerous software and data storage systems are employed by local health departments (LHDs) to manage clinical and nonclinical data needs. Leveraging electronic systems may yield improvements in public health practice. However, information is lacking regarding current usage patterns among LHDs.

OBJECTIVE

To analyze clinical and nonclinical data storage and software types by LHDs.

DESIGN

Data came from the 2015 Informatics Capacity and Needs Assessment Survey, conducted by Georgia Southern University in collaboration with the National Association of County and City Health Officials.

PARTICIPANTS

A total of 324 LHDs from all 50 states completed the survey (response rate: 50%).

MAIN OUTCOME MEASURES

Outcome measures included LHD's primary clinical service data system, nonclinical data system(s) used, and plans to adopt electronic clinical data system (if not already in use). Predictors of interest included jurisdiction size and governance type, and other informatics capacities within the LHD. Bivariate analyses were performed using χ and t tests.

RESULTS

Up to 38.4% of LHDs reported using an electronic health record (EHR). Usage was common especially among LHDs that provide primary care and/or dental services. LHDs serving smaller populations and those with state-level governance were both less likely to use an EHR. Paper records were a common data storage approach for both clinical data (28.9%) and nonclinical data (59.4%). Among LHDs without an EHR, 84.7% reported implementation plans.

CONCLUSIONS

Our findings suggest that LHDs are increasingly using EHRs as a clinical data storage solution and that more LHDs are likely to adopt EHRs in the foreseeable future. Yet use of paper records remains common. Correlates of electronic system usage emerged across a range of factors. Program- or system-specific needs may be barriers or facilitators to EHR adoption. Policy makers can tailor resources to address barriers specific to LHD size, governance, service portfolio, existing informatics capabilities, and other pertinent characteristics.

Differing Strategies to Meet Information-Sharing Needs: Publicly Supported Community Health Information Exchanges Versus Health Systems' Enterprise Health Information Exchanges

POLICY POINTS

Community health information exchanges have the characteristics of a public good, and they support population health initiatives at the state and national levels. However, current policy equally incentivizes health systems to create their own information exchanges covering more narrowly defined populations. Noninteroperable electronic health records and vendors' expensive custom interfaces are hindering health information exchanges. Moreover, vendors are imposing the costs of interoperability on health systems and community health information exchanges. Health systems are creating networks of targeted physicians and facilities by funding connections to their own enterprise health information exchanges. These private networks may change referral patterns and foster more integration with outpatient providers.

CONTEXT

The United States has invested billions of dollars to encourage the adoption of and implement the information technologies necessary for health information exchange (HIE), enabling providers to efficiently and effectively share patient information with other providers. Health care providers now have multiple options for obtaining and sharing patient information. Community HIEs facilitate information sharing for a broad group of providers within a region. Enterprise HIEs are operated by health systems and share information among affiliated hospitals and providers. We sought to identify why hospitals and health systems choose either to participate in community HIEs or to establish enterprise HIEs.

METHODS

We conducted semistructured interviews with 40 policymakers, community and enterprise HIE leaders, and health care executives from 19 different organizations. Our qualitative analysis used a general inductive and comparative approach to identify factors influencing participation in, and the success of, each approach to HIE.

FINDINGS

Enterprise HIEs support health systems' strategic goals through the control of an information technology network consisting of desired trading partners. Community HIEs support obtaining patient information from the broadest set of providers, but with more dispersed benefits to all participants, the community, and patients. Although not an either/or decision, community and enterprise HIEs compete for finite organizational resources like time, skilled staff, and money. Both approaches face challenges due to vendor costs and less-than-interoperable technology.

CONCLUSIONS

Both community and enterprise HIEs support aggregating clinical data and following patients across settings. Although they can be complementary, community and enterprise HIEs nonetheless compete for providers' attention and organizational resources. Health policymakers might try to encourage the type of widespread information exchange pursued by community HIEs, but the business case for enterprise HIEs clearly is stronger. The sustainability of a community HIE, potentially a public good, may necessitate ongoing public funding and supportive regulation.

Increased Identification of Emergency Department 72-hour Returns Using Multihospital Health Information Exchange

OBJECTIVES

Emergency departments (EDs) commonly analyze cases of patients returning within 72 hours of initial ED discharge as potential opportunities for quality improvement. In this study, we tested the use of a health information exchange (HIE) to improve identification of 72-hour return visits compared to individual hospitals' site-specific data.

METHODS

We collected deidentified patient data over a 5-year study period from Healthix, an HIE in the New York metropolitan area. We measured site-specific 72-hour ED returns and compared these data to those obtained from a regional 31-site HIE (Healthix) and to those from a smaller, antecedent 11-site HIE. Although only ED visits were counted as index visits, either ED or inpatient revisits within 72 hours of the index visit were considered as early returns.

RESULTS

A total of 12,669,657 patient encounters were analyzed across the 31 HIE EDs, including 6,352,829 encounters from the antecedent 11-site HIE. Site-specific 72-hour return visit rates ranged from 1.1% to 15.2% (median = 5.8%) among the individual 31 sites. When the larger HIE was used to identify return visits to any site, individual EDs had a 72-hour return frequency of 1.8% to 15.5% (median = 6.8%). HIE increased the identification ability of 72-hour ED return analyses by a mean of 11.16% (95% confidence interval = 11.10% to 11.22%) compared with site-specific (no HIE) analyses.

CONCLUSION

This analysis demonstrates incremental improvements in our ability to identify early ED returns using increasing levels of HIE data aggregation. Although intuitive, this has not been previously described using HIE. ED quality measurement and patient safety efforts may be aided by using HIE in 72-hour return analyses.

Organizational Uses of Health Information Exchange to Change Cost and Utilization Outcomes: A Typology from a Multi-Site Qualitative Analysis

Health information exchange (HIE) systems facilitate access to patient information for a variety of health care organizations, end users, and clinical and organizational goals. While a complex intervention, organizations' usage of HIE is often conceptualized and measured narrowly. We sought to provide greater specificity to the concept of HIE as an intervention by formulating a typology of organizational HIE usage. We interviewed representatives of a regional health information organization and health care organizations actively using HIE information to change patient utilization and costs. The resultant typology includes three dimensions: user role, usage initiation, and patient set. This approach to categorizing how health care organizations are actually applying HIE information to clinical and business tasks provides greater clarity about HIE as an intervention and helps elucidate the conceptual linkage between HIE an organizational and patient outcomes.

The US National Tuberculosis Surveillance System: A Descriptive Assessment of the Completeness and Consistency of Data Reported from 2008 to 2012

BACKGROUND

In 2009, the Tuberculosis (TB) Information Management System transitioned into the National TB Surveillance System to allow use of 4 different types of electronic reporting schemes: state-built, commercial, and 2 schemes developed by the Centers for Disease Control and Prevention. Simultaneously, the reporting form was revised to include additional data fields.

OBJECTIVE

Describe data completeness for the years 2008-2012 and determine the impact of surveillance changes.

METHODS

Data were categorized into subgroups and assessed for completeness (eg, the percentage of patients dead at diagnosis who had a date of death reported) and consistency (eg, the percentage of patients alive at diagnosis who erroneously had a date of death reported). Reporting jurisdictions were grouped to examine differences by reporting scheme.

RESULTS

Each year less than 1% of reported cases had missing information for country of origin, race, or ethnicity. Patients reported as dead at diagnosis had death date (a new data field) missing for 3.6% in 2009 and 4.4% in 2012. From 2010 to 2012, 313 cases (1%) reported as alive at diagnosis had a death date and all of these were reported through state-built or commercial systems. The completeness of reporting for guardian country of birth for pediatric patients (a new data field) ranged from 84% in 2009 to 88.2% in 2011.

CONCLUSIONS

Despite major changes, completeness has remained high for most data elements in TB surveillance. However, some data fields introduced in 2009 remain incomplete; continued training is needed to improve national TB surveillance data.

Current National Approach to Healthcare ICT Standardization: Focus on Progress in New Zealand

Objectives

Many countries try to efficiently deliver high quality healthcare services at lower and manageable costs where healthcare information and communication technologies (ICT) standardisation may play an important role. New Zealand provides a good model of healthcare ICT standardisation. The purpose of this study was to review the current healthcare ICT standardisation and progress in New Zealand.

Methods

This study reviewed the reports regarding the healthcare ICT standardisation in New Zealand. We also investigated relevant websites related with the healthcare ICT standards, most of which were run by the government. Then, we summarised the governance structure, standardisation processes, and their output regarding the current healthcare ICT standards status of New Zealand.

Results

New Zealand government bodies have established a set of healthcare ICT standards and clear guidelines and procedures for healthcare ICT standardisation. Government has actively participated in various enactments of healthcare ICT standards from the inception of ideas to their eventual retirement. Great achievements in eHealth have already been realized, and various standards are currently utilised at all levels of healthcare regionally and nationally. Standard clinical terminologies, such as International Classification of Diseases (ICD) and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) have been adopted and Health Level Seven (HL7) standards are actively used in health information exchanges.

Conclusions

The government to New Zealand has well organised ICT institutions, guidelines, and regulations, as well as various programs, such as e-Medications and integrated care services. Local district health boards directly running hospitals have effectively adopted various new ICT standards. They might already be benefiting from improved efficiency resulting from healthcare ICT standardisation.

Health Information Exchange in Emergency Medicine

Emergency physicians often must make critical, time-sensitive decisions with a paucity of information with the realization that additional unavailable health information may exist. Health information exchange enables clinician access to patient health information from multiple sources across the spectrum of care. This can provide a more complete longitudinal record, which more accurately reflects the way most patients obtain care: across multiple providers and provider organizations. This information article explores various aspects of health information exchange that are relevant to emergency medicine and offers guidance to emergency physicians and to organized medicine for the use and promotion of this emerging technology. This article makes 5 primary emergency medicine-focused recommendations, as well as 7 additional secondary generalized recommendations, to health information exchanges, policymakers, and professional groups, which are crafted to facilitate health information exchange's purpose and demonstrate its value.

Developing a common health information exchange platform to implement a nationwide health information network in South Korea

Objectives

We aimed to develop a common health information exchange (HIE) platform that can provide integrated services for implementing the HIE infrastructure in addition to guidelines for participating in an HIE network in South Korea.

Methods

By exploiting the Health Level 7 (HL7) Clinical Document Architecture (CDA) and Integrating the Healthcare Enterprise (IHE) Cross-enterprise Document Sharing-b (XDS.b) profile, we defined the architectural model, exchanging data items and their standardization, messaging standards, and privacy and security guidelines, for a secure, nationwide, interoperable HIE. We then developed a service-oriented common HIE platform to minimize the effort and difficulty of fulfilling the standard requirements for participating in the HIE network. The common platform supports open application program interfaces (APIs) for implementing a document registry, a document repository, a document consumer, and a master patient index. It could also be used for testing environments for the implementation of standard requirements.

Results

As the initial phase of implementing a nationwide HIE network in South Korea, we built a regional network for workers' compensation (WC) hospitals and their collaborating clinics to share referral and care record summaries to ensure the continuity of care for industrially injured workers, using the common HIE platform and verifying the feasibility of our technologies.

Conclusions

We expect to expand the HIE network on a national scale with rapid support for implementing HL7 and IHE standards in South Korea.

Patterns and correlates of public health informatics capacity among local health departments: an empirical typology

OBJECTIVE

Little is known about the nationwide patterns in the use of public health informatics systems by local health departments (LHDs) and whether LHDs tend to possess informatics capacity across a broad range of information functionalities or for a narrower range. This study examined patterns and correlates of the presence of public health informatics functionalities within LHDs through the creation of a typology of LHD informatics capacities.

METHODS

Data were available for 459 LHDs from the 2013 National Association of County and City Health Officials Profile survey. An empirical typology was created through cluster analysis of six public health informatics functionalities: immunization registry, electronic disease registry, electronic lab reporting, electronic health records, health information exchange, and electronic syndromic surveillance system. Three-categories of usage emerged (Low, Mid, High). LHD financial, workforce, organization, governance, and leadership characteristics, and types of services provided were explored across categories.

RESULTS

Low-informatics capacity LHDs had lower levels of use of each informatics functionality than high-informatics capacity LHDs. Mid-informatics capacity LHDs had usage levels equivalent to high-capacity LHDs for the three most common functionalities and equivalent to low-capacity LHDs for the three least common functionalities. Informatics capacity was positively associated with service provision, especially for population-focused services.

CONCLUSION

Informatics capacity is clustered within LHDs. Increasing LHD informatics capacity may require LHDs with low levels of informatics capacity to expand capacity across a range of functionalities, taking into account their narrower service portfolio. LHDs with mid-level informatics capacity may need specialized support in enhancing capacity for less common technologies.

The visit-data warehouse: enabling novel secondary use of health information exchange data

INTRODUCTION/OBJECTIVES

Health Information Exchange (HIE) efforts face challenges with data quality and performance, and this becomes especially problematic when data is leveraged for uses beyond primary clinical use. We describe a secondary data infrastructure focusing on patient-encounter, nonclinical data that was built on top of a functioning HIE platform to support novel secondary data uses and prevent potentially negative impacts these uses might have otherwise had on HIE system performance.

BACKGROUND

HIE efforts have generally formed for the primary clinical use of individual clinical providers searching for data on individual patients under their care, but many secondary uses have been proposed and are being piloted to support care management, quality improvement, and public health.

DESCRIPTION OF THE HIE AND BASE INFRASTRUCTURE

This infrastructure review describes a module built into the Healthix HIE. Healthix, based in the New York metropolitan region, comprises 107 participating organizations with 29,946 acute-care beds in 383 facilities, and includes more than 9.2 million unique patients. The primary infrastructure is based on the InterSystems proprietary Caché data model distributed across servers in multiple locations, and uses a master patient index to link individual patients' records across multiple sites. We built a parallel platform, the "visit data warehouse," of patient encounter data (demographics, date, time, and type of visit) using a relational database model to allow accessibility using standard database tools and flexibility for developing secondary data use cases. These four secondary use cases include the following: (1) tracking encounter-based metrics in a newly established geriatric emergency department (ED), (2) creating a dashboard to provide a visual display as well as a tabular output of near-real-time de-identified encounter data from the data warehouse, (3) tracking frequent ED users as part of a regional-approach to case management intervention, and (4) improving an existing quality improvement program that analyzes patients with return visits to EDs within 72 hours of discharge.

RESULTS/LESSONS LEARNED

Setting up a separate, near-real-time, encounters-based relational database to complement an HIE built on a hierarchical database is feasible, and may be necessary to support many secondary uses of HIE data. As of November 2014, the visit-data warehouse (VDW) built by Healthix is undergoing technical validation testing and updates on an hourly basis. We had to address data integrity issues with both nonstandard and missing HL7 messages because of varied HL7 implementation across the HIE. Also, given our HIEs federated structure, some sites expressed concerns regarding data centralization for the VDW. An established and stable HIE governance structure was critical in overcoming this initial reluctance.

CONCLUSIONS

As secondary use of HIE data becomes more prevalent, it may be increasingly necessary to build separate infrastructure to support secondary use without compromising performance. More research is needed to determine optimal ways of building such infrastructure and validating its use for secondary purposes.

Applications of health information exchange information to public health practice

Increased information availability, timeliness, and comprehensiveness through health information exchange (HIE) can support public health practice. The potential benefits to disease monitoring, disaster response, and other public health activities served as an important justification for the US' investments in HIE. After several years of HIE implementation and funding, we sought to determine if any of the anticipated benefits of exchange participation were accruing to state and local public health practitioners participating in five different exchanges. Using qualitative interviews and template analyses, we identified public health efforts and activities that were improved by participation in HIE. HIE supported public health activities consistent with expectations in the literature. However, no single department realized all the potential benefits of HIE identified. These findings suggest ways to improve HIE usage in public health.

Validating Health Information Exchange (HIE) Data For Quality Measurement Across Four Hospitals

Health information exchange (HIE) provides an essential enhancement to electronic health records (EHR), allowing information to follow patients across provider organizations. There is also an opportunity to improve public health surveillance, quality measurement, and research through secondary use of HIE data, but data quality presents potential barriers. Our objective was to validate the secondary use of HIE data for two emergency department (ED) quality measures: identification of frequent ED users and early (72-hour) ED returns. We compared concordance of various demographic and encounter data from an HIE for four hospitals to data provided by the hospitals from their EHRs over a two year period, and then compared measurement of our two quality measures using both HIE and EHR data. We found that, following data cleaning, there was no significant difference in the total counts for frequent ED users or early ED returns for any of the four hospitals (p<0.001).

Creating a connected community: lessons learned from the Western new york beacon community

INTRODUCTION

Secure exchange of clinical data among providers has the potential to improve quality, safety, efficiency, and reduce duplication. Many communities are experiencing challenges in building effective health information exchanges (HIEs). Previous studies have focused on financial and technical issues regarding HIE development. This paper describes the Western New York (WNY) HIE growth and lessons learned about accelerating progress to become a highly connected community.

METHODS

HEALTHeLINK, with funding from the Office of the National Coordinator for Health Information Technology (ONC) under the Beacon Community Program, expanded HIE usage in eight counties. The communitywide transformation process used three main drivers: (1) a communitywide Electronic Health Record (EHR) adoption program; (2) clinical transformation partners; and (3) HIE outreach and infrastructure development.

RESULTS

ONC Beacon Community funding allowed WNY to achieve a new level in the use of interoperable HIE. Electronic delivery of results into the EHR expanded from 23 practices in 2010 to 222 practices in 2013, a tenfold increase. There were more than 12.5 million results delivered electronically (HL7 messages) to 222 practices' EHRs via the HIE in 2013. Use of a secure portal and Virtual Health Record (VHR) to access reports (those not delivered directly to the EHR) also increased significantly, from 13,344 report views in 2010 to over 600,000 in 2013.

DISCUSSION AND CONCLUSION

The WNY Beacon successfully expanded the sharing of clinical information among different sources of data and providers, creating a highly connected community to improve the quality and continuity of care. Technical, organizational, and community lessons described in this paper should prove beneficial to others as they pursue efforts to create connected communities.

Leveraging health information exchange to improve population health reporting processes: lessons in using a collaborative-participatory design process

Introduction:

Surveillance, or the systematic monitoring of disease within a population, is a cornerstone function of public health. Despite significant investment in information technologies (IT) to improve the public’s health, health care providers continue to rely on manual, spontaneous reporting processes that can result in incomplete and delayed surveillance activities.

Background:

Participatory design principles advocate including real users and stakeholders when designing an information system to ensure high ecological validity of the product, incorporate relevance and context into the design, reduce misconceptions designers can make due to insufficient domain expertise, and ultimately reduce barriers to adoption of the system. This paper focuses on the collaborative and informal participatory design process used to develop enhanced, IT-enabled reporting processes that leverage available electronic health records in a health information exchange to prepopulate notifiable-conditions report forms used by public health authorities.

Methods:

Over nine months, public health stakeholders, technical staff, and informatics researchers were engaged in a multiphase participatory design process that included public health stakeholder focus groups, investigator-engineering team meetings, public health survey and census regarding high-priority data elements, and codesign of exploratory prototypes and final form mock-ups.

Findings:

A number of state-mandated report fields that are not highly used or desirable for disease investigation were eliminated, which allowed engineers to repurpose form space for desired and high-priority data elements and improve the usability of the forms. Our participatory design process ensured that IT development was driven by end user expertise and needs, resulting in significant improvements to the layout and functionality of the reporting forms.

Discussion:

In addition to informing report form development, engaging with public health end users and stakeholders through the participatory design process provided new insights into public health workflow and allowed the team to quickly triage user requests while managing user expectations within the realm of engineering possibilities.

Conclusion:

Engaging public health, engineering staff, and investigators in a shared codesigning process ensured that the new forms will not only meet real-life needs but will also support development of a product that will be adopted and, ultimately, improve communicable and infectious disease reporting by clinicians to public health.

Electronic health information exchange in underserved settings: examining initiatives in small physician practices & community health centers

BACKGROUND

Health information exchange (HIE) is an important tool for improving efficiency and quality and is required for providers to meet Meaningful Use certification from the United States Centers for Medicare and Medicaid Services. However widespread adoption and use of HIE has been difficult to achieve, especially in settings such as smaller-sized physician practices and federally qualified health centers (FQHCs). We assess electronic data exchange activities and identify barriers and benefits to HIE participation in two underserved settings.

METHODS

We conducted key-informant interviews with stakeholders at physician practices and health centers. Interviews were recorded, transcribed, and then coded in two waves: first using an open-coding approach and second using selective coding to identify themes that emerged across interviews, including barriers and facilitators to HIE adoption and use.

RESULTS

We interviewed 24 providers, administrators and office staff from 16 locations in two states. They identified barriers to HIE use at three levels-regional (e.g., lack of area-level exchanges; partner organizations), inter-organizational (e.g., strong relationships with exchange partners; achieving a critical mass of users), and intra-organizational (e.g., type of electronic medical record used; integration into organization's workflow). A major perceived benefit of HIE use was the improved care-coordination clinicians could provide to patients as a direct result of the HIE information. Utilization and perceived benefit of the exchange systems differed based on several practice- and clinic-level factors.

CONCLUSIONS

The adoption and use of HIE in underserved settings appears to be impeded by regional, inter-organizational, and intra-organizational factors and facilitated by perceived benefits largely at the intra-organizational level. Stakeholders should consider factors both internal and external to their organization, focusing efforts in changing modifiable factors and tailoring HIE efforts based on all three categories of factors. Collective action between organizations may be needed to address inter-organizational and regional barriers. In the interest of facilitating HIE adoption and use, the impact of interventions at various levels on improving the use of electronic health data exchange should be tested.

Health information exchange implementation: lessons learned and critical success factors from a case study

BACKGROUND

Much attention has been given to the proposition that the exchange of health information as an act, and health information exchange (HIE), as an entity, are critical components of a framework for health care change, yet little has been studied to understand the value proposition of implementing HIE with a statewide HIE. Such an organization facilitates the exchange of health information across disparate systems, thus following patients as they move across different care settings and encounters, whether or not they share an organizational affiliation. A sociotechnical systems approach and an interorganizational systems framework were used to examine implementation of a health system electronic medical record (EMR) system onto a statewide HIE, under a cooperative agreement with the Office of the National Coordinator for Health Information Technology, and its collaborating organizations.

OBJECTIVE

The objective of the study was to focus on the implementation of a health system onto a statewide HIE; provide insight into the technical, organizational, and governance aspects of a large private health system and the Virginia statewide HIE (organizations with the shared goal of exchanging health information); and to understand the organizational motivations and value propositions apparent during HIE implementation.

METHODS

We used a formative evaluation methodology to investigate the first implementation of a health system onto the statewide HIE. Qualitative methods (direct observation, 36 hours), informal information gathering, semistructured interviews (N=12), and document analysis were used to gather data between August 12, 2012 and June 24, 2013. Derived from sociotechnical concepts, a Blended Value Collaboration Enactment Framework guided the data gathering and analysis to understand organizational stakeholders' perspectives across technical, organizational, and governance dimensions.

RESULTS

Several challenges, successes, and lessons learned during the implementation of a health system to the statewide HIE were found. The most significant perceived success was accomplishing the implementation, although many interviewees also underscored the value of a project champion with decision-making power. In terms of lessons learned, social reasons were found to be very significant motivators for early implementation, frequently outweighing economic motivations. It was clear that understanding the guides early in the project would have mitigated some of the challenges that emerged, and early communication with the electronic health record vendor so that they have a solid understanding of the undertaking was critical. An HIE implementations evaluation framework was found to be useful for assessing challenges, motivations, value propositions for participating, and success factors to consider for future implementations.

CONCLUSIONS

This case study illuminates five critical success factors for implementation of a health system onto a statewide HIE. This study also reveals that organizations have varied motivations and value proposition perceptions for engaging in the exchange of health information, few of which, at the early stages, are economically driven.

Does self-reporting facilitate history taking in food poisoning mass-casualty incidents?

INTRODUCTION

Medical history is an important contributor to diagnosis and patient management. In mass-casualty incidents (MCIs), health care providers are often overwhelmed by large numbers of casualties. An efficient, reliable, and affordable method of information collection is essential for effective health care response.

HYPOTHESIS/PROBLEM

In some MCIs, self-reporting of symptoms can decrease the time required for history taking, without sacrificing the completeness of triage information.

METHODS

Two resident doctors and a number of seventh graders who had previous experience of abdominal discomfort were invited to join this study. A questionnaire was developed to collect information on common symptoms in food poisoning. Each question was scored, and enrolled students were randomly divided into two groups. The experimental group students answered the questionnaire first and then were interviewed to complete the medical history. The control group students were interviewed in the traditional way to collect medical history. Time of all interviews was measured and recorded. The time needed to complete the history taking and completeness of obtained information were compared with students' t tests, or Mann-Whitney U tests, based on the normality of data. Comprehensibility of each question, scored by enrolled students, was reported by descriptive statistics.

RESULTS

There were 41 students enrolled: 22 in the experimental group and 19 in the control group. Time to complete history taking in the experimental group (163.0 seconds, SD=52.3) was shorter than that in the control group (198.7 seconds, SD=40.9) (P=.010). There was no difference in the completeness of history obtained between the experimental group and the control group (94.8%, SD=5.0 vs 94.2%, SD=6.1; P=.747). Between the two doctors, no significant difference was found in the time required for history taking (185.2 seconds, SD=42.2 vs 173.1 seconds, SD=58.6; P=.449), or the completeness of information (94.1%, SD=5.9 vs 95.0%, SD=5.0; P=.601). Most of the questions were scored "good" in comprehensibility.

CONCLUSION

Self-reporting of symptoms can shorten the time of history taking during a food poisoning mass-casualty event without sacrificing the completeness of information.

People with epilepsy who use multiple hospitals; prevalence and associated factors assessed via a health information exchange

OBJECTIVE

Hospital crossover occurs when people seek care at multiple hospitals, creating information gaps for physicians at the time of care. Health information exchange (HIE) is technology that fills these gaps, by allowing otherwise unaffiliated physicians to share electronic medical information. However, the potential value of HIE is understudied, particularly for chronic neurologic conditions like epilepsy. We describe the prevalence and associated factors of hospital crossover among people with epilepsy, in order to understand the epidemiology of who may benefit from HIE.

METHODS

We used a cross-sectional study design to examine the bivariate and multivariable association of demographics, comorbidity, and health service utilization variables with hospital crossover, among people with epilepsy. We identified 8,074 people with epilepsy from the International Classification of Diseases, Ninth Revision (ICD-9) codes, obtained from an HIE that linked seven hospitals in Manhattan, New York. We defined hospital crossover as care from more than one hospital in any setting (inpatient, outpatient, emergency, or radiology) over 2 years.

RESULTS

Of 8,074 people with epilepsy, 1,770 (22%) engaged in hospital crossover over 2 years. Crossover was associated with younger age (children compared with adults, adjusted odds ratio [OR] 1.4, 95% confidence interval [CI] 1.2-1.7), living near the hospitals (Manhattan vs. other boroughs of New York City, adjusted OR 1.6, 95% CI 1.4-1.8), more visits in the emergency, radiology, inpatient, and outpatient settings (p < 0.001 for each), and more head computerized tomography (CT) scans (p < 0.01). The diagnosis of "encephalopathy" was consistently associated with crossover in bivariate and multivariable analyses (adjusted OR 2.66, 95% CI 2.14-3.29), whereas the relationship between other comorbidities and crossover was less clear.

SIGNIFICANCE

Hospital crossover is common among people with epilepsy, particularly among children, frequent users of medical services, and people living near the study hospitals. HIE should focus on these populations. Further research should investigate why hospital crossover occurs, how it affects care, and how HIE can most effectively mitigate the resultant fragmentation of medical records.

Validating emergency department vital signs using a data quality engine for data warehouse

Background :

Vital signs in our emergency department information system were entered into free-text fields for heart rate, respiratory rate, blood pressure, temperature and oxygen saturation.

Objective :

We sought to convert these text entries into a more useful form, for research and QA purposes, upon entry into a data warehouse.

Methods :

We derived a series of rules and assigned quality scores to the transformed values, conforming to physiologic parameters for vital signs across the age range and spectrum of illness seen in the emergency department.

Results :

Validating these entries revealed that 98% of free-text data had perfect quality scores, conforming to established vital sign parameters. Average vital signs varied as expected by age. Degradations in quality scores were most commonly attributed logging temperature in Fahrenheit instead of Celsius; vital signs with this error could still be transformed for use. Errors occurred more frequently during periods of high triage, though error rates did not correlate with triage volume.

Conclusions :

In developing a method for importing free-text vital sign data from our emergency department information system, we now have a data warehouse with a broad array of quality-checked vital signs, permitting analysis and correlation with demographics and outcomes.