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Gaps in health information exchange between hospitals that treat many shared patients.

ABSTRACT: Objective:Hospitals that routinely share patients are those that most critically need to engage in electronic health information exchange (HIE) with each other to ensure clinical information is available to inform treatment decisions. We surveyed pairs of hospitals in a nationwide sample to describe whether and how hospitals within each hospital referral region (HRR) that have the highest shared patient (HSP) volume engaged in HIE with each other. Methods:We used Medicare's Physician Shared Patient Patterns data to identify hospital pairs with the highest shared patient volume in each hospital referral region. We surveyed a purposeful sample of pairs and then calculated descriptive statistics to compare: (1) HIE with the HSP hospital vs HIE with other hospitals, and (2) HIE with the HSP hospital versus federal measures of HIE engagement that are not partner-specific. Results:We received responses from 25.5% of contacted hospitals and 33.5% of contacted pairs, allowing us to examine information sharing among 68 hospitals in 63 pairs. 23% of respondents reported worse information sharing with their HSP hospital than with other hospitals while 17% indicated better sharing with their HSP hospital and 48% indicated no difference. Our HSP-specific measures of HIE differed from federal measures of HIE engagement: while 97% of respondents are classified as routinely sending information electronically in federal measures, in our data only 63% did so with their HSP hospital. Conclusions:Despite increased HIE engagement, our descriptive results indicate that HIE is not developing in a way that facilitates information exchange where it might benefit the most patients. New policy efforts, particularly those emerging from the 21st Century Cures Act, need to explicitly pursue strategies that ensure that HSP providers engage in exchange with each other.

SUBMITTER: Everson J

PROVIDER: S-EPMC7646909 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Gaps in health information exchange between hospitals that treat many shared patients.

Everson Jordan J Adler-Milstein Julia J

Journal of the American Medical Informatics Association : JAMIA 20180901 9

<h4>Objective</h4>Hospitals that routinely share patients are those that most critically need to engage in electronic health information exchange (HIE) with each other to ensure clinical information is available to inform treatment decisions. We surveyed pairs of hospitals in a nationwide sample to describe whether and how hospitals within each hospital referral region (HRR) that have the highest shared patient (HSP) volume engaged in HIE with each other.<h4>Methods</h4>We used Medicare's Physic ...[more]

PMID: 30010887

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Project description:BACKGROUND:Laboratory testing occupies a prominent place in health care. Information technology systems have the potential to empower laboratory experts and to enhance the interpretation of test results in order to better support physicians in their quest for better and safer patient care. This study sought to develop a better understanding of which laboratory information exchange (LIE) systems and features specialist physicians are using in hospital settings to consult their patients' laboratory test results, and what benefit they derive from such use. METHODS:As part of a broader research program on the use of health information exchange systems for laboratory medicine in Quebec, Canada, this study was designed as on online survey. Our sample is composed of 566 specialist physicians working in hospital settings, out of the 1512 physicians who responded to the survey (response rate of 17%). Respondents are representative of the targeted population of specialist physicians in terms of gender, age and hospital location. RESULTS:We first observed that 80% of the surveyed physicians used the province-wide interoperable electronic health records (iEHR) system and 93% used a laboratory results viewer (LRV) to consult laboratory test results and most (72%) use both systems to retrieve lab results. Next, our findings reveal important differences in the capabilities available in each type of system and in the use of these capabilities. Third, there are differences in the nature of the perceived benefits obtained from the use of each of these two systems. Last, the extent of use of an LRV is strongly influenced by the IT artefact itself (i.e., the hospital's LRV available capabilities) while the use of the provincial iEHR system is influenced by its organizational context (i.e. the hospital's size and location). CONCLUSIONS:The main contribution of this study lies in its insights into the role played by context in shaping physicians' choices about which laboratory information exchange systems to adopt and which features to use, and the different perceptions they have about benefits arising from such use. One related implication for practice is that success of LIE initiatives should not be solely assessed with basic usage statistics.

Project description:ImportanceInstituting widespread measurement of outcomes for cancer hospitals using administrative data is difficult owing to lack of cancer-specific information such as disease stage.ObjectiveTo evaluate the performance of hospitals that treat patients with cancer using Medicare data for outcome ascertainment and risk adjustment and to assess whether hospital rankings based on these measures are altered by the addition of cancer-specific information.Design, setting, and participantsRisk-adjusted cumulative mortality rates of patients with cancer were captured in Medicare claims data from 2005 through 2009 nationally and assessed at the hospital level. Similar analyses were conducted using Surveillance, Epidemiology, and End Results (SEER)-Medicare data for the subset of the United States covered by the SEER program to determine whether the inclusion of cancer-specific information (only available in cancer registries) in risk adjustment altered measured hospital performance. Data were from 729 279 fee-for-service Medicare beneficiaries treated for cancer in 2006 at hospitals treating 10 or more patients with each of the following cancers, according to Medicare claims: lung, prostate, breast, colon, and other. An additional sample of 18 677 similar patients were included from the SEER-Medicare administrative data.Main outcomes and measuresRisk-adjusted mortality overall and by cancer category, stratified by type of hospital; measures of correlation and agreement between hospital-level outcomes risk adjusted using Medicare data alone and Medicare data with SEER data.ResultsThere were large survival differences between different types of hospitals that treat Medicare patients with cancer. At 1 year, mortality for patients treated by hospitals exempt from the Medicare prospective payment system was 10% lower than at community hospitals (18% vs 28%) across all cancers, and the pattern persisted through 5 years of follow-up and within specific cancer categories. Performance ranking of hospitals was consistent with or without SEER-Medicare disease stage information (weighted κ ≥ 0.81).Conclusions and relevancePotentially important outcome differences exist between different types of hospitals that treat patients with cancer after risk adjustment using information in Medicare administrative data. This type of risk adjustment may be adequate for evaluating hospital performance, since the additional adjustment for data available only in cancer registries does not seem to appreciably alter measures of performance.

Project description: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.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.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.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.

Project description:AbstractHealth information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = -0.086; 95% Confidence Interval, -0.162 to -0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial - perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.

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Gaps in health information exchange between hospitals that treat many shared patients.

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Gaps in health information exchange between hospitals that treat many shared patients.

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