The Effects of Ownership, Operating Environment, and Strategic Choices on Nursing Home Efficiency

Rosko, Michael D.; Chilingerian, Jon A.; Zinn, Jacqueline S.; Aaronson, William E.

doi:10.1097/00005650-199510000-00003

Cited by 103 publications

(83 citation statements)

References 33 publications

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“…Nyman and Bricker's findings indicate that for-profit nursing homes employ 4.5% fewer inputs per patient day than otherwise comparable not-for-profit homes. The general conclusions of this study have been corroborated by a host of studies including Nyman, Bricker, and Link (1990), Fizel and Nunnikhoven (1992), Chattopadhyay and Heffley (1994), and Rosko et al (1995).…”

Section: Property Rights and Principal-agent Problemssupporting

confidence: 81%

Ownership Form and Consumer Welfare: Evidence from the Nursing Home Industry

Santerre

Vernon²

2007

INQUIRY

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This paper compares the likely consumer benefits of higher quality with the potentially greater production costs that result from increased not-for-profit activity in a nursing home services market area. The comparison of consumer benefits and costs is made possible by observing empirically how an increased market penetration of not-for-profit facilities affects the use of private-pay nursing home care. Increased (decreased) use of nursing home care suggests that the consumer benefits associated with additional notfor-profit nursing homes are greater (less) than consumer costs. The empirical results indicate that, from a consumer's perspective, too few not-for-profit nursing homes may exist in the typical market area of the United States. The policy implication is that more quality of care per dollar might be obtained by attracting a greater percentage of notfor-profit nursing homes into many market areas.As is the case with many other health care industries, organizations with different ownership forms characterize the nursing home industry in the United States. National estimates indicate that 66% of all nursing homes are organized on a for-profit basis; private not-for-profits make up another 27% of all nursing homes, and public nursing homes account for the remaining 7% (CMS 2003).

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Section: Property Rights and Principal-agent Problemssupporting

confidence: 81%

Ownership Form and Consumer Welfare: Evidence from the Nursing Home Industry

Santerre

Vernon²

2007

INQUIRY

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“…Due to greater competition for medical and non-medical staff relative to other regions in Ireland, labour costs are higher in Dublin. Consequently, as wage rates increase, nursing home managers react by using their labour inputs more efficiently (Zinn, 1993;Rosko et al, 1995). 8 Furthermore, as Dublin represents a special case compared to other regions and cities in Ireland, it is important to account for this -almost 40 % of all nursing homes in our sample are located in the Dublin area (see Table 5 below).…”

Section: Locationmentioning

confidence: 99%

“…Rosko et al, 1995), and to deficiencies or inspection scores (e.g. Nyman and Bricker, 1989;and Fizel and Nunnikhoven, 1993).…”

Section: Qualitymentioning

confidence: 99%

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Technical and scale efficiency in public and private Irish nursing homes – a bootstrap DEA approach

Luasa

Dineen

Zieba

2016

Health Care Manag Sci

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This article provides methodological and empirical insights into the estimation of technical efficiency in the nursing home sector. Focusing on long-stay care and using primary data, we examine technical and scale efficiency in 39 public and 73 private Irish nursing homes by applying an input-oriented data envelopment analysis (DEA). We employ robust bootstrap methods to validate our nonparametric DEA scores and to integrate the effects of potential determinants in estimating the efficiencies. Both the homogenous and two-stage double bootstrap procedures are used to obtain confidence intervals for the bias-corrected DEA scores. Importantly, the application of the double bootstrap approach affords true DEA technical efficiency scores after adjusting for the effects of ownership, size, case-mix, and other determinants such as location, and quality. Based on our DEA results for variable returns to scale technology, the average technical efficiency score is 62%, and the mean scale efficiency is 88%, with nearly all units operating on the increasing returns to scale part of the production frontier. Moreover, based on the double bootstrap results, Irish nursing homes are less technically efficient, and more scale efficient than the conventional DEA estimates suggest. Regarding the efficiency determinants, in terms of ownership, we find that private facilities are less efficient than the public units. Furthermore, the size of the nursing home has a positive effect, and this reinforces our finding that Irish homes produce at increasing returns to scale. Also, notably, we find that a tendency towards quality improvements can lead to poorer technical efficiency performance.

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“…And also internationally the focus has been only on institutions, like nursing homes (see e.g. Chattopadhyay and Ray (1996), Dusansky and Wilson (1994), Kooreman (1994), Nyman and Bricker (1989), Rosko et al, 1995). This study will include both institutionalised-and home care.…”

Section: Introductionmentioning

confidence: 99%

Efficiency in the Provision of Municipal Nursing- and Home-Care Services: The Norwegian Experience

Erlandsen

Førsund

2002

Efficiency in the Public Sector

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in ABSTRACTThe municipalities in Norway are responsible for providing care for their inhabitants in need. The care takes two main forms: institutionalised care in nursing homes and home-based care. Based on cross-section data for 1995 for 471 municipalities the efficiency of the care activity is investigated using the non-parametric DEA approach. Quality is regarded as very important for the amount of resources spent, but measures that capture quality are very hard to come by. The available data source allows only single-bed rooms as a quality indicator for nursing homes and only number of clients in various age groups as basis for output variables in general. For the three basic activities nursing homes, home based care and home based medical treatment nine output variables are defined based on three age groups; 0-17, 18-79, and 80+. The forming of age groups are designed to reflect the severity of need for care in order to take care of the "patient-mix"-effect. In addition, net throughput of clients as a variable catching short-term clients in nursing homes is used as an output. Labour in manyears and other current expenses are the inputs. There are no data for capital inputs, like buildings and equipment. Significant differences in efficiency between municipalities are revealed and efficient peers identified that can be studied by municipalities wanting to improve performance.

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The Effects of Ownership, Operating Environment, and Strategic Choices on Nursing Home Efficiency

Cited by 103 publications

References 33 publications

Ownership Form and Consumer Welfare: Evidence from the Nursing Home Industry

Ownership Form and Consumer Welfare: Evidence from the Nursing Home Industry

Technical and scale efficiency in public and private Irish nursing homes – a bootstrap DEA approach

Efficiency in the Provision of Municipal Nursing- and Home-Care Services: The Norwegian Experience

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