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Horrocks D, Kinzer D, Afzal S, Alpern J, Sharfstein JM. The Adequacy of Individual Hospital Data to Identify High Utilizers and Assess Community Health. JAMA Intern Med. 2016;176(6):856–858. doi:10.1001/jamainternmed.2016.1248
Many hospitals are analyzing data from their own information systems to develop new strategies to improve population health. Such analyses aim to identify high utilizers who may benefit from additional support and to elucidate community patterns of potentially preventable serious illness, but the extent to which individual hospital data are sufficient for these purposes is unclear.
The Chesapeake Regional Health Information System for Our Patients, Maryland’s Health Information Exchange, aggregates data for all 48 of the state’s acute care hospitals. The Health Information Exchange uses a Master Patient Index based on IBM’s Initiate technology to link admission, discharge, and transfer data, clinical records, and billing diagnoses for unique individuals. As part of a quality improvement initiative and ongoing efforts to support community health planning, using a complete set of admission, discharge, and transfer data, we examined the patterns of hospital use of all patients with more than 5 emergency department visits to Maryland hospitals in calendar year 2014. We also evaluated all hospital admissions for calendar year 2014 to Maryland hospitals to determine the percentage of volume received by the most utilized hospital in each zip code. All 434 zip codes statewide whose residents had more than 10 acute care admissions to a single Maryland hospital and who had more than 99 residents in the 2010 census were included.
Of 45 861 individuals with more than 5 emergency department visits to Maryland hospitals in 2014, 8438 (18.4%) visited more than 3 hospitals, 8905 (19.4%) visited 3 hospitals, 14 627 (31.9%) visited 2 hospitals, and 13 891 (30.3%) visited only 1 hospital. Only 27 251 (59.4%) of the 45 861 made more than 5 emergency department visits to 1 hospital, meaning that the rest would fail to be identified by individual hospital analyses.
The majority of Maryland residents (53.0%) live in zip codes where no single hospital received more than half of inpatient volume. In zip codes close to multiple hospitals, there is only modest concentration of inpatient utilization (Figure).
As a result of new payment incentives that favor reductions in avoidable illnesses, more hospitals are working to identify and assist high utilizers. For more than two-thirds of frequent visitors to emergency departments in Maryland, however, no single hospital had a full picture of their care. Moreover, hospital-specific analyses would have failed to identify approximately 2 in 5 high utilizers. These results do not account for the fact that some facilities within the same hospital system may be able to share data. Nonetheless, the findings, which are consistent with a previous analysis based on hospital claims for 1 city,1 support the importance of health information exchange for the identification and understanding of this vulnerable population.
Hospitals are also increasingly engaged in efforts to advance overall community health. A precondition for success is the effective measurement of health outcomes at the local level; hospital data can be more timely and local than usual public health information sources.2 For zip codes that cover most of Maryland’s population, however, no single hospital’s records captured even half of the inpatient utilization. This suggests that data sharing may be essential to tracking the trajectory of chronic illness at the population level. Further research at smaller geographic units than zip code is needed to confirm this finding.
Even though hospitals in competitive markets may have the most to gain from health information exchange, they are the least likely to participate.3 As financial incentives continue to evolve, perhaps this reluctance will fade. By shining a light on patterns of preventable use of hospital services, data sharing can illuminate a path to substantial improvements in community health.
Corresponding Author: Joshua M. Sharfstein, MD, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Room W1033D, Baltimore, MD 21205 (firstname.lastname@example.org).
Published Online: April 25, 2016. doi:10.1001/jamainternmed.2016.1248.
Author Contributions: Mr Afzal and Dr Sharfstein had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Kinzer, Sharfstein.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Alpern, Sharfstein.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Alpern.
Administrative, technical, or material support: Afzal.
Study supervision: Horrocks, Afzal.
Conflict of Interest Disclosures: Mr Afzal is a principal and Dr Sharfstein an adviser to Audacious Inquiry, a company that provides services to Maryland’s health information exchange. No other disclosures are reported.