Loading…

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Met...

Full description

Saved in:
Bibliographic Details
Published in:BMC health services research 2021-11, Vol.21 (1), p.1-1281, Article 1281
Main Authors: Piubello Orsini, Luca, Leardini, Chiara, Vernizzi, Silvia, Campedelli, Bettina
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53
cites cdi_FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53
container_end_page 1281
container_issue 1
container_start_page 1
container_title BMC health services research
container_volume 21
creator Piubello Orsini, Luca
Leardini, Chiara
Vernizzi, Silvia
Campedelli, Bettina
description Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach--that is, multistage data envelopment analysis (DEA)--was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels. Keywords: Data envelopment analysis, Efficiency, Quality, Public hospitals, Tobit, Malmquist productivity index
doi_str_mv 10.1186/s12913-021-07276-5
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_59655f497c854687b93065461dc1a2ab</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A686383426</galeid><doaj_id>oai_doaj_org_article_59655f497c854687b93065461dc1a2ab</doaj_id><sourcerecordid>A686383426</sourcerecordid><originalsourceid>FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53</originalsourceid><addsrcrecordid>eNptkktr3DAQx01padK0X6AnQS-9ONHbUg-FEPpYCPTSHouQZcnRYktbyQ7st-9sNrTZUnSYYfSf3zCPpnlL8CUhSl5VQjVhLaakxR3tZCueNeeEd7SVWrLnT_yz5lWtW4xJp2j3sjljXDGFsTxvfm6SDyG66JPboxzQbu2n6NBdrru42Kl-QBbN67TEutjRo8EuFvl076e8m31akE122tdYUUzgow3kRLDFjzGn182LAAz_5tFeND8-f_p-87W9_fZlc3N92zrB8dISHbDrfY974kJgetBMYqooxVwKLDXlahDKOj04pnnw1Pak7zilUhMlvGAXzebIHbLdml2Jsy17k200D4FcRmPLEt3kjdBSiMB155TgUnW9ZliCRwZHLICB9fHIgknMfnDQZLHTCfT0J8U7M-Z7oyTsgDEAvH8ElPxr9XUxc6zOT5NNPq_VUIk5F1BdgfTdP9JtXgtM9KAisF6mOP6rGi00EFPIUNcdoOZaKskU41SC6vI_KniDn6PLsOYI8ZMEekxwJddafPjTI8HmcGDmeGAGDsw8HJgR7DeoXL-r</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2611293840</pqid></control><display><type>article</type><title>Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region</title><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><source>ABI/INFORM Global</source><source>PubMed Central</source><creator>Piubello Orsini, Luca ; Leardini, Chiara ; Vernizzi, Silvia ; Campedelli, Bettina</creator><creatorcontrib>Piubello Orsini, Luca ; Leardini, Chiara ; Vernizzi, Silvia ; Campedelli, Bettina</creatorcontrib><description>Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach--that is, multistage data envelopment analysis (DEA)--was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels. Keywords: Data envelopment analysis, Efficiency, Quality, Public hospitals, Tobit, Malmquist productivity index</description><identifier>ISSN: 1472-6963</identifier><identifier>EISSN: 1472-6963</identifier><identifier>DOI: 10.1186/s12913-021-07276-5</identifier><identifier>PMID: 34838006</identifier><language>eng</language><publisher>London: BioMed Central Ltd</publisher><subject>Analysis ; Costs ; Data envelopment analysis ; Economic aspects ; Efficiency ; Financial analysis ; First aid ; Health services ; Hospitals ; Hospitals, Public ; Industrial efficiency ; Italy ; Length of stay ; Linear programming ; Malmquist productivity index ; Medical care ; Methods ; Mortality ; Older people ; Prevention ; Public hospitals ; Quality ; Quality management ; Regional government ; Social aspects ; Tobit</subject><ispartof>BMC health services research, 2021-11, Vol.21 (1), p.1-1281, Article 1281</ispartof><rights>COPYRIGHT 2021 BioMed Central Ltd.</rights><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53</citedby><cites>FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627633/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2611293840?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,11688,25753,27924,27925,36060,36061,37012,37013,44363,44590,53791,53793</link.rule.ids></links><search><creatorcontrib>Piubello Orsini, Luca</creatorcontrib><creatorcontrib>Leardini, Chiara</creatorcontrib><creatorcontrib>Vernizzi, Silvia</creatorcontrib><creatorcontrib>Campedelli, Bettina</creatorcontrib><title>Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region</title><title>BMC health services research</title><description>Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach--that is, multistage data envelopment analysis (DEA)--was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels. Keywords: Data envelopment analysis, Efficiency, Quality, Public hospitals, Tobit, Malmquist productivity index</description><subject>Analysis</subject><subject>Costs</subject><subject>Data envelopment analysis</subject><subject>Economic aspects</subject><subject>Efficiency</subject><subject>Financial analysis</subject><subject>First aid</subject><subject>Health services</subject><subject>Hospitals</subject><subject>Hospitals, Public</subject><subject>Industrial efficiency</subject><subject>Italy</subject><subject>Length of stay</subject><subject>Linear programming</subject><subject>Malmquist productivity index</subject><subject>Medical care</subject><subject>Methods</subject><subject>Mortality</subject><subject>Older people</subject><subject>Prevention</subject><subject>Public hospitals</subject><subject>Quality</subject><subject>Quality management</subject><subject>Regional government</subject><subject>Social aspects</subject><subject>Tobit</subject><issn>1472-6963</issn><issn>1472-6963</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkktr3DAQx01padK0X6AnQS-9ONHbUg-FEPpYCPTSHouQZcnRYktbyQ7st-9sNrTZUnSYYfSf3zCPpnlL8CUhSl5VQjVhLaakxR3tZCueNeeEd7SVWrLnT_yz5lWtW4xJp2j3sjljXDGFsTxvfm6SDyG66JPboxzQbu2n6NBdrru42Kl-QBbN67TEutjRo8EuFvl076e8m31akE122tdYUUzgow3kRLDFjzGn182LAAz_5tFeND8-f_p-87W9_fZlc3N92zrB8dISHbDrfY974kJgetBMYqooxVwKLDXlahDKOj04pnnw1Pak7zilUhMlvGAXzebIHbLdml2Jsy17k200D4FcRmPLEt3kjdBSiMB155TgUnW9ZliCRwZHLICB9fHIgknMfnDQZLHTCfT0J8U7M-Z7oyTsgDEAvH8ElPxr9XUxc6zOT5NNPq_VUIk5F1BdgfTdP9JtXgtM9KAisF6mOP6rGi00EFPIUNcdoOZaKskU41SC6vI_KniDn6PLsOYI8ZMEekxwJddafPjTI8HmcGDmeGAGDsw8HJgR7DeoXL-r</recordid><startdate>20211127</startdate><enddate>20211127</enddate><creator>Piubello Orsini, Luca</creator><creator>Leardini, Chiara</creator><creator>Vernizzi, Silvia</creator><creator>Campedelli, Bettina</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>KB0</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20211127</creationdate><title>Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region</title><author>Piubello Orsini, Luca ; Leardini, Chiara ; Vernizzi, Silvia ; Campedelli, Bettina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analysis</topic><topic>Costs</topic><topic>Data envelopment analysis</topic><topic>Economic aspects</topic><topic>Efficiency</topic><topic>Financial analysis</topic><topic>First aid</topic><topic>Health services</topic><topic>Hospitals</topic><topic>Hospitals, Public</topic><topic>Industrial efficiency</topic><topic>Italy</topic><topic>Length of stay</topic><topic>Linear programming</topic><topic>Malmquist productivity index</topic><topic>Medical care</topic><topic>Methods</topic><topic>Mortality</topic><topic>Older people</topic><topic>Prevention</topic><topic>Public hospitals</topic><topic>Quality</topic><topic>Quality management</topic><topic>Regional government</topic><topic>Social aspects</topic><topic>Tobit</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Piubello Orsini, Luca</creatorcontrib><creatorcontrib>Leardini, Chiara</creatorcontrib><creatorcontrib>Vernizzi, Silvia</creatorcontrib><creatorcontrib>Campedelli, Bettina</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing &amp; Allied Health Source</collection><collection>ABI/INFORM Collection (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Health Management Database (Proquest)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>BMC health services research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Piubello Orsini, Luca</au><au>Leardini, Chiara</au><au>Vernizzi, Silvia</au><au>Campedelli, Bettina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region</atitle><jtitle>BMC health services research</jtitle><date>2021-11-27</date><risdate>2021</risdate><volume>21</volume><issue>1</issue><spage>1</spage><epage>1281</epage><pages>1-1281</pages><artnum>1281</artnum><issn>1472-6963</issn><eissn>1472-6963</eissn><abstract>Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach--that is, multistage data envelopment analysis (DEA)--was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels. Keywords: Data envelopment analysis, Efficiency, Quality, Public hospitals, Tobit, Malmquist productivity index</abstract><cop>London</cop><pub>BioMed Central Ltd</pub><pmid>34838006</pmid><doi>10.1186/s12913-021-07276-5</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1472-6963
ispartof BMC health services research, 2021-11, Vol.21 (1), p.1-1281, Article 1281
issn 1472-6963
1472-6963
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_59655f497c854687b93065461dc1a2ab
source Publicly Available Content Database (Proquest) (PQ_SDU_P3); ABI/INFORM Global; PubMed Central
subjects Analysis
Costs
Data envelopment analysis
Economic aspects
Efficiency
Financial analysis
First aid
Health services
Hospitals
Hospitals, Public
Industrial efficiency
Italy
Length of stay
Linear programming
Malmquist productivity index
Medical care
Methods
Mortality
Older people
Prevention
Public hospitals
Quality
Quality management
Regional government
Social aspects
Tobit
title Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-21T08%3A45%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Inefficiency%20of%20public%20hospitals:%20a%20multistage%20data%20envelopment%20analysis%20in%20an%20Italian%20region&rft.jtitle=BMC%20health%20services%20research&rft.au=Piubello%20Orsini,%20Luca&rft.date=2021-11-27&rft.volume=21&rft.issue=1&rft.spage=1&rft.epage=1281&rft.pages=1-1281&rft.artnum=1281&rft.issn=1472-6963&rft.eissn=1472-6963&rft_id=info:doi/10.1186/s12913-021-07276-5&rft_dat=%3Cgale_doaj_%3EA686383426%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c540t-19f0cbeb0b1cff39d936028220465069248d58ac9dc394fe2ab1b742269185e53%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2611293840&rft_id=info:pmid/34838006&rft_galeid=A686383426&rfr_iscdi=true