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Assessing the impact of health system organizational structure on hospital electronic data sharing.

ABSTRACT: Objective:Horizontal consolidation in the hospital industry has gained momentum in the United States despite concerns over rising costs and lower quality. Hospital systems frequently point to potential gains in interoperability and electronic exchange of patient information as consolidation benefits. We sought to assess whether hospitals in different health system structures varied in their interoperable data sharing. Materials and methods:We created a cross-sectional national hospital sample from the 2014 AHA Annual Survey and 2015 IT Supplement. We combined the existing taxonomy of health system organizational forms and the ONC's functionality-based, technology-agnostic definition of interoperability. We used logistic regression models to assess the relationship between health systems' organizational forms and interoperability engagement, controlling for hospital characteristics. Results:We found that interoperability engagement varied greatly across hospitals in different health system structures, with facilities in more centralized health systems more likely to be interoperable. Hospitals in one system type, featuring centralized insurance product development but diverse service offerings across member organizations, had significantly higher odds of being engaged in interoperable data sharing in our multivariate regression results. Discussion:The heterogeneity in health system interoperability engagement indicates that incentives to share data vary greatly across organizational strategies and structures. Our results suggest that horizontal consolidation in the hospital industry may not bring significant gains in interoperability progress unless that consolidation takes a specific business alignment form. Conclusion:Policymakers should be wary of claims that horizontal consolidation will lead to interoperability gains. Future research should explore the specific mechanisms that lead to greater interoperability in certain health system organizational structures.

SUBMITTER: Holmgren AJ

PROVIDER: S-EPMC7646916 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Assessing the impact of health system organizational structure on hospital electronic data sharing.

Holmgren A Jay AJ Ford Eric W EW

Journal of the American Medical Informatics Association : JAMIA 20180901 9

<h4>Objective</h4>Horizontal consolidation in the hospital industry has gained momentum in the United States despite concerns over rising costs and lower quality. Hospital systems frequently point to potential gains in interoperability and electronic exchange of patient information as consolidation benefits. We sought to assess whether hospitals in different health system structures varied in their interoperable data sharing.<h4>Materials and methods</h4>We created a cross-sectional national hos ...[more]

PMID: 29982687

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Project description:ImportanceBig data studies may allow for the aggregation of patients with rare diseases such as uveitis to answer important clinical questions. Standardization of uveitis-related variables will be necessary, including the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes used to identify patients of interest. There are currently limited data on the uniformity of diagnosis mapping to ICD-10 codes for uveitis diagnoses among different health systems.ObjectiveTo assess the degree of uniformity in mapping of uveitis clinical concepts to ICD-10 codes across health care systems using the same electronic health record (EHR) system.Design, setting, and participantsThis multicenter survey study was conducted between September 14 and October 9, 2020, at 5 academic health care systems that use the Epic EHR. Researchers from the University of Washington, Harvard University, Stanford University, Yale University, and the University of California, San Francisco queried 54 uveitis-related diagnostic terms and recorded the associated ICD-10 codes.Main outcomes and measuresThe degree of uniformity for uveitis clinical concepts and associated ICD-10 codes.ResultsFifty-four uveitis-related diagnostic terms were queried within the Epic EHR at 5 different health care systems. There was perfect agreement among all 5 centers for 52 of the 54 diagnostic terms. Two diagnostic terms had differences in ICD-10 coding: juvenile idiopathic arthritis associated chronic uveitis and intermediate uveitis. Intermediate uveitis was associated with codes H20.1x (ICD-10 description: chronic iridocyclitis) or H20.9 (ICD-10 description: unspecified iridocyclitis) in 3 centers while being associated with code H30.2x (ICD-10 description: posterior cyclitis) at the 2 remaining centers. The discrepancies appear to be related to a recent update in diagnostic mapping in the Epic EHR.Conclusions and relevanceThis study suggests that ICD-10 code mapping to uveitis diagnostic terminology appears to be highly uniform at different centers with the Epic EHR. However, temporal changes in diagnosis mapping to ICD-10 codes and a lack of 1-to-1 mapping of diagnosis to ICD-10 code add additional sources of complexity to the interpretation of big data studies in uveitis.

Project description:BackgroundOrganizational readiness for change is a key factor in success or failure of electronic health record (EHR) system implementations. Readiness is a multifaceted and multilevel abstract construct encompassing individual and organizational aspects, which makes it difficult to assess. Available tools for assessing readiness need to be tested in different contexts.ObjectiveTo identify and assess relevant variables that determine readiness to implement an EHR in oncology in a low-and-middle income setting.MethodsAt the Uganda Cancer Institute (UCI), a 100-bed tertiary oncology center in Uganda,we conducted a cross-sectional survey using the Paré model. This model has 39 indicator variables (Likert-scale items) for measuring 9 latent variables that contribute to readiness. We analyzed data using partial least squares structural equation modeling (PLS-SEM). In addition, we collected comments that we analyzed by qualitative content analysis and sentiment analysis as a way of triangulating the Likert-scale survey responses.ResultsOne hundred and forty-six clinical and non-clinical staff completed the survey, and 116 responses were included in the model. The measurement model showed good indicator reliability, discriminant validity, and internal consistency. Path coefficients for 6 of the 9 latent variables (i.e. vision clarity, change appropriateness, change efficacy, presence of an effective champion, organizational flexibility, and collective self-efficacy) were statistically significant at p < 0.05. The R2 for the outcome variable (organizational readiness) was 0.67. The sentiments were generally positive and correlated well with the survey scores (Pearson's r = 0.73). Perceived benefits of an EHR included improved quality, security and accessibility of clinical data, improved care coordination, reduction of errors, and time and cost saving. Recommended considerations for successful implementation include sensitization, training, resolution of organizational conflicts and computer infrastructure.ConclusionChange management during EHR implementation in oncology in low- and middle- income setting should focus on attributes of the change and the change targets, including vision clarity, change appropriateness, change efficacy, presence of an effective champion, organizational flexibility, and collective self-efficacy. Particularly, issues of training, computer skills of staff, computer infrastructure, sensitization and strategic implementation need consideration.

Project description:ObjectiveTo model the impacts of the bicycle sharing system in London on the health of its users.DesignHealth impact modelling and evaluation, using a stochastic simulation model.SettingCentral and inner London, England.Data sourcesTotal population operational registration and usage data for the London cycle hire scheme (collected April 2011-March 2012), surveys of cycle hire users (collected 2011), and London data on travel, physical activity, road traffic collisions, and particulate air pollution (PM2.5, (collected 2005-12).Participants578,607 users of the London cycle hire scheme, aged 14 years and over, with an estimated 78% of travel time accounted for by users younger than 45 years.Main outcome measuresChange in lifelong disability adjusted life years (DALYs) based on one year impacts on incidence of disease and injury, modelled through medium term changes in physical activity, road traffic injuries, and exposure to air pollution.ResultsOver the year examined the users made 7.4 million cycle hire trips (estimated 71% of cycling time by men). These trips would mostly otherwise have been made on foot (31%) or by public transport (47%). To date there has been a trend towards fewer fatalities and injuries than expected on cycle hire bicycles. Using these observed injury rates, the population benefits from the cycle hire scheme substantially outweighed harms (net change -72 DALYs (95% credible interval -110 to -43) among men using cycle hire per accounting year; -15 (-42 to -6) among women; note that negative DALYs represent a health benefit). When we modelled cycle hire injury rates as being equal to background rates for all cycling in central London, these benefits were smaller and there was no evidence of a benefit among women (change -49 DALYs (-88 to -17) among men; -1 DALY (-27 to 12) among women). This sex difference largely reflected higher road collision fatality rates for female cyclists. At older ages the modelled benefits of cycling were much larger than the harms. Using background injury rates in the youngest age group (15 to 29 years), the medium term benefits and harms were both comparatively small and potentially negative.ConclusionLondon's bicycle sharing system has positive health impacts overall, but these benefits are clearer for men than for women and for older users than for younger users. The potential benefits of cycling may not currently apply to all groups in all settings.

Project description:ObjectiveEfficient, effective health care requires rapid availability of patient information. We designed, implemented, and assessed the impact of a primary care electronic medical record (EMR) in three rural Kenyan health centers.MethodLocal clinicians identified data required for primary care and public health reporting. We designed paper encounter forms to capture these data in adult medicine, pediatric, and antenatal clinics. Encounter form data were hand-entered into a new primary care module in an existing EMR serving onsite clinics serving patients infected with the human immunodeficiency virus (HIV). Before subsequent visits, Summary Reports were printed containing selected patient data with reminders for needed HIV care. We assessed effects on patient flow and provider work with time-motion studies before implementation and two years later, and we surveyed providers' satisfaction with the EMR.ResultsBetween September 2008 and December 2011, 72 635 primary care patients were registered and 114 480 encounter forms were completed. During 2011, 32 193 unique patients visited primary care clinics, and encounter forms were completed for all visits. Of 1031 (3.2%) who were HIV-infected, 85% received HIV care. Patient clinic time increased from 37 to 81 min/visit after EMR implementation in one health center and 56 to 106 min/visit in the other. However, outpatient visits to both health centers increased by 85%. Three-quarters of increased time was spent waiting. Despite nearly doubling visits, there was no change in clinical officers' work patterns, but the nurses' and the clerks' patient care time decreased after EMR implementation. Providers were generally satisfied with the EMR but desired additional training.ConclusionsWe successfully implemented a primary care EMR in three rural Kenyan health centers. Patient waiting time was dramatically lengthened while the nurses' and the clerks' patient care time decreased. Long-term use of EMRs in such settings will require changes in culture and workflow.

Project description:ObjectiveTo demonstrate that electronic health record (EHR) data can be used in an automated approach to evaluate cataract surgery outcomes.DesignRetrospective analysis.SubjectsResident and faculty surgeons.MethodsElectronic health record data were collected from cataract surgeries performed at the Johns Hopkins Wilmer Eye Institute, and cases were categorized into resident or attending as primary surgeon. Preoperative and postoperative visual acuity (VA) and unplanned return to operating room were extracted from the EHR.Main outcome measuresPostoperative VA and reoperation rate within 90 days.ResultsThis study analyzed 14 537 cataract surgery cases over 32 months. Data were extracted from the EHR using an automated approach to assess surgical outcomes for resident and attending surgeons. Of 337 resident surgeries with both preoperative and postoperative VA data, 248 cases (74%) had better postoperative VA, and 170 cases (51%) had more than 2 lines improvement. There was no statistical difference in the proportion of cases with better postoperative VA or more than 2 lines improvement between resident and attending cases. Attending surgeons had a statistically greater proportion of cases with postoperative VA better than 20/40, but this finding has to be considered in the context that, on average, resident cases started out with poorer baseline VA.A multivariable regression model of VA outcomes vs. resident/attending status that controlled for preoperative VA, patient age, American Society of Anesthesiologists (ASA) score, and estimated income found that resident status, preoperative VA, patient age, ASA score, and estimated income were all significant predictors of VA. The rate of unplanned return to the operating room within 90 days of cataract surgery was not statistically different between resident (1.8%) and attending (1.2%) surgeons.ConclusionsThis study demonstrates that EHR data can be used to evaluate and monitor surgical outcomes in an ongoing way. Analysis of EHR-extracted cataract outcome data showed that preoperative VA, ASA classification, and attending/resident status were important in predicting postoperative VA outcomes. These findings suggest that the utilization of EHR data could enable continuous assessment of surgical outcomes and inform interventions to improve resident training. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

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Assessing the impact of health system organizational structure on hospital electronic data sharing.

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Assessing the impact of health system organizational structure on hospital electronic data sharing.

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