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Published in: BMC Health Services Research 1/2021

Open Access 01-12-2021 | Research article

Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

Authors: Joanne Martin, Edwin Amalraj Raja, Steve Turner

Published in: BMC Health Services Research | Issue 1/2021

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Abstract

Background

Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services?

Methods

There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions.

Results

Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital.

Conclusions

There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.
Literature
1.
go back to reference Gill PJ, Goldacre MJ, Mant D, Heneghan C, Thomson A, Seagroatt V, et al. Increase in emergency admissions to hospital for children aged under 15 in England, 1999–2010: national database analysis. Arch Dis Child. 2013;98:328–34.CrossRef Gill PJ, Goldacre MJ, Mant D, Heneghan C, Thomson A, Seagroatt V, et al. Increase in emergency admissions to hospital for children aged under 15 in England, 1999–2010: national database analysis. Arch Dis Child. 2013;98:328–34.CrossRef
2.
go back to reference Al-Mahtot M, Barwise-Munro R, Wilson P, Turner S. Changing characteristics of hospital admissions but not the children admitted-a whole population study between 2000 and 2013. Eur J Pediatr. 2017;177:381–8.CrossRef Al-Mahtot M, Barwise-Munro R, Wilson P, Turner S. Changing characteristics of hospital admissions but not the children admitted-a whole population study between 2000 and 2013. Eur J Pediatr. 2017;177:381–8.CrossRef
3.
go back to reference Walker KO, Clarke R, Ryan G, Brown AF. Effect of closure of a local safety-net hospital on primary care physicians’ perceptions of their role in patient care. Ann Fam Med. 2011;9:496–503.CrossRef Walker KO, Clarke R, Ryan G, Brown AF. Effect of closure of a local safety-net hospital on primary care physicians’ perceptions of their role in patient care. Ann Fam Med. 2011;9:496–503.CrossRef
4.
go back to reference Imison C. The reconfiguration of hospital services: is there evidence to guide us? Future Hosp J. 2015;2:137–41.CrossRef Imison C. The reconfiguration of hospital services: is there evidence to guide us? Future Hosp J. 2015;2:137–41.CrossRef
5.
go back to reference Fulop N, Walters R, Perri, Spurgeon P. Implementing changes to hospital services: factors influencing the process and ‘results’ of reconfiguration. Health Policy. 2012;104:128–35.CrossRef Fulop N, Walters R, Perri, Spurgeon P. Implementing changes to hospital services: factors influencing the process and ‘results’ of reconfiguration. Health Policy. 2012;104:128–35.CrossRef
6.
go back to reference Crandall M, Sharp D, Wei X, Nathens A, Hsia RY. Effects of closure of an urban level I trauma centre on adjacent hospitals and local injury mortality: a retrospective, observational study. Brit Med J Open. 2016;6:e011700. Crandall M, Sharp D, Wei X, Nathens A, Hsia RY. Effects of closure of an urban level I trauma centre on adjacent hospitals and local injury mortality: a retrospective, observational study. Brit Med J Open. 2016;6:e011700.
7.
go back to reference Lagarde M. How to do (or not to do) … Assessing the impact of a policy change with routine longitudinal data. Health Policy Planning. 2012;27:76–83.CrossRef Lagarde M. How to do (or not to do) … Assessing the impact of a policy change with routine longitudinal data. Health Policy Planning. 2012;27:76–83.CrossRef
8.
go back to reference Baum C, Schaffer M. ACTEST: Stata module to perform Cumby-Huizinga general test for autocorrelation in time series. Statistical Software Components: Boston College Department of Economics; 2015. Baum C, Schaffer M. ACTEST: Stata module to perform Cumby-Huizinga general test for autocorrelation in time series. Statistical Software Components: Boston College Department of Economics; 2015.
9.
go back to reference Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 2017;46:348–55.PubMed Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 2017;46:348–55.PubMed
10.
go back to reference Bhaskaran K, Gasparrini A, Hajat S, Smeeth L, Armstrong B. Time series regression studies in environmental epidemiology. Int J Epidemiol. 2013;42:1187–95.CrossRef Bhaskaran K, Gasparrini A, Hajat S, Smeeth L, Armstrong B. Time series regression studies in environmental epidemiology. Int J Epidemiol. 2013;42:1187–95.CrossRef
11.
go back to reference Amiel C, Williams B, Ramzan F, Islam S, Ladbrooke T, Majeed A, et al. Reasons for attending an urban urgent care centre with minor illness: a questionnaire study. Emerg Med J. 2014;31:e71-5.CrossRef Amiel C, Williams B, Ramzan F, Islam S, Ladbrooke T, Majeed A, et al. Reasons for attending an urban urgent care centre with minor illness: a questionnaire study. Emerg Med J. 2014;31:e71-5.CrossRef
Metadata
Title
Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres
Authors
Joanne Martin
Edwin Amalraj Raja
Steve Turner
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2021
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-021-06070-7

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