| Title |
Is higher nursing home quality more costly?
|
|---|---|
| Published in |
HEPAC Health Economics in Prevention and Care, November 2015
|
| DOI | 10.1007/s10198-015-0743-4 |
| Pubmed ID | |
| Authors |
L. Di Giorgio, M. Filippini, G. Masiero |
| Abstract |
Widespread issues regarding quality in nursing homes call for an improved understanding of the relationship with costs. This relationship may differ in European countries, where care is mainly delivered by nonprofit providers. In accordance with the economic theory of production, we estimate a total cost function for nursing home services using data from 45 nursing homes in Switzerland between 2006 and 2010. Quality is measured by means of clinical indicators regarding process and outcome derived from the minimum data set. We consider both composite and single quality indicators. Contrary to most previous studies, we use panel data and control for omitted variables bias. This allows us to capture features specific to nursing homes that may explain differences in structural quality or cost levels. Additional analysis is provided to address simultaneity bias using an instrumental variable approach. We find evidence that poor levels of quality regarding outcome, as measured by the prevalence of severe pain and weight loss, lead to higher costs. This may have important implications for the design of payment schemes for nursing homes. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 56 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 18% |
| Student > Master | 10 | 18% |
| Student > Ph. D. Student | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Professor | 4 | 7% |
| Other | 9 | 16% |
| Unknown | 13 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 13 | 23% |
| Business, Management and Accounting | 7 | 13% |
| Economics, Econometrics and Finance | 6 | 11% |
| Social Sciences | 6 | 11% |
| Medicine and Dentistry | 5 | 9% |
| Other | 6 | 11% |
| Unknown | 13 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 May 2017.
All research outputs
#15,801,823
of 25,461,852 outputs
Outputs from HEPAC Health Economics in Prevention and Care
#838
of 1,308 outputs
Outputs of similar age
#209,215
of 394,127 outputs
Outputs of similar age from HEPAC Health Economics in Prevention and Care
#13
of 22 outputs
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