Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling. Min, A., Park, C., G., & Scott, L., D. Western journal of nursing research, 5, 2016.
abstract   bibtex   
Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states.
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 title = {Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling},
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 year = {2016},
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 keywords = {data envelopment analysis,multilevel modeling,nursing home,technical efficiency},
 month = {5},
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 city = {University of Illinois at Chicago, USA amin21@uic.edu.; University of Illinois at Chicago, USA.; University of Illinois at Chicago, USA.},
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 notes = {LR: 20160525; CI: (c) The Author(s) 2016; JID: 7905435; OTO: NOTNLM; aheadofprint},
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 abstract = {Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states.},
 bibtype = {article},
 author = {Min, A and Park, C G and Scott, L D},
 journal = {Western journal of nursing research}
}
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