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    Whole-patient measure of safety: using administrative data to assess the probability of highly undesirable events during hospitalization

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    Authors
    Perla, Rocco J.
    Hohmann, Samuel F.
    Annis, Karen
    UMass Chan Affiliations
    Department of Quantitative Health Sciences
    Document Type
    Journal Article
    Publication Date
    2013-09-01
    Keywords
    Clinical Coding
    *Hospitalization
    Humans
    Medical Errors
    *Patient Safety
    Probability
    Safety Management
    United States
    Health and Medical Administration
    Health Services Administration
    
    Metadata
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    Link to Full Text
    http://dx.doi.org/10.1111/jhq.12027
    Abstract
    Hospitals often have limited ability to obtain primary clinical data from electronic health records to use in assessing quality and safety. We outline a new model that uses administrative data to gauge the safety of care at the hospital level. The model is based on a set of highly undesirable events (HUEs) defined using administrative data and can be customized to address the priorities and needs of different users. Patients with HUEs were identified using discharge abstracts from July 1, 2008 through June 30, 2010. Diagnoses were classified as HUEs based on the associated present-on-admission status. The 2-year study population comprised more than 6.5 million discharges from 161 hospitals. The proportion of hospitalizations including at least one HUE during the 24-month study period varied greatly among hospitals, with a mean of 7.74% (SD 2.3%) and a range of 13.32% (max, 15.31%; min, 1.99%). The whole-patient measure of safety provides a global measure to use in assessing hospitals with the patient's entire care experience in mind. As administrative and clinical datasets become more consistent, it becomes possible to use administrative data to compare the rates of HUEs across organizations and to identify opportunities for improvement.
    Source
    J Healthc Qual. 2013 Sep-Oct;35(5):20-31. doi: 10.1111/jhq.12027. Link to article on publisher's site
    DOI
    10.1111/jhq.12027
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/30326
    PubMed ID
    24004036
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1111/jhq.12027
    Scopus Count
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    UMass Chan Faculty and Researcher Publications

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