Skip to main content
Top
Published in: BMC Health Services Research 1/2019

Open Access 01-12-2019 | Care | Research article

Rapid evaluation for health and social care innovations: challenges for “quick wins” using interrupted time series

Authors: Andrew McCarthy, Peter McMeekin, Shona Haining, Lesley Bainbridge, Claire Laing, Joanne Gray

Published in: BMC Health Services Research | Issue 1/2019

Login to get access

Abstract

Background

Rapid evaluation was at the heart of National Health Service England’s evaluation strategy of the new models of care vanguard programme. This was to facilitate the scale and spread of successful models of care throughout the health & social care system. The aim of this paper is to compare the findings of the two evaluations of the Enhanced health in Care Homes (EHCH) vanguard in Gateshead, one using a smaller data set for rapidity and one using a larger longitudinal data set and to investigate the implications of the use of rapid evaluations using interrupted time series (ITS) methods.

Methods

A quasi-experimental design study in the form of an ITS was used to evaluate the impact of the vanguard on secondary care use. Two different models are presented differing by timeframes only. The short-term model consisted of data for 11 months data pre and 20 months post vanguard. The long-term model consisted of data for 23 months pre and 34 months post vanguard.

Results

The cost consequences, including the cost of running the EHCH vanguard, were estimated using both a single tariff non-elective admissions methodology and a tariff per bed day methodology. The short-term model estimated a monthly cost increase of £73,408 using a single tariff methodology. When using a tariff per bed day, there was an estimated monthly cost increase of £14,315.
The long-term model had, using a single tariff for non-elective admissions, an overall cost increase of £7576 per month. However, when using a tariff per bed-days, there was an estimated monthly cost reduction of £57,168.

Conclusions

Although it is acknowledged that there is often a need for rapid evaluations in order to identify “quick wins” and to expedite learning within health and social care systems, we conclude that this may not be appropriate for quasi-experimental designs estimating effect using ITS for complex interventions. Our analyses suggests that care must be taken when conducting and interpreting the results of short-term evaluations using ITS methods, as they may produce misleading results and may lead to a misallocation of resources.
Appendix
Available only for authorised users
Literature
1.
go back to reference NHS England, Care Quality Commission, Health Education England, Monitor, Public Health England, Trust Development Authority. NHS five year forward view. London: NHS England; 2014. NHS England, Care Quality Commission, Health Education England, Monitor, Public Health England, Trust Development Authority. NHS five year forward view. London: NHS England; 2014.
2.
go back to reference NHS England. The framework for enhanced health in care homes. England N: NHS England; 2016. NHS England. The framework for enhanced health in care homes. England N: NHS England; 2016.
3.
go back to reference NHS England. Evaluation strategy for new care model vanguards. England N: NHS England; 2016. NHS England. Evaluation strategy for new care model vanguards. England N: NHS England; 2016.
4.
go back to reference Cook RD, Weisberg S. Diagnostics for heteroscedasticity in regression. Biometrika. 1983;70(1):1–10.CrossRef Cook RD, Weisberg S. Diagnostics for heteroscedasticity in regression. Biometrika. 1983;70(1):1–10.CrossRef
5.
go back to reference Breusch TS. Testing for autocorrelation in dynamic linear models*. Aust Econ Pap. 1978;17(31):334–55.CrossRef Breusch TS. Testing for autocorrelation in dynamic linear models*. Aust Econ Pap. 1978;17(31):334–55.CrossRef
6.
go back to reference Godfrey LG. Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica. 1978;46(6):1293–301.CrossRef Godfrey LG. Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica. 1978;46(6):1293–301.CrossRef
7.
go back to reference Newey WK, West KD. A simple, positive semi-definite, Heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica. 1987;55(3):703–8.CrossRef Newey WK, West KD. A simple, positive semi-definite, Heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica. 1987;55(3):703–8.CrossRef
8.
go back to reference NHS Employers. Agenda for change pay scales and points April 2016. London: NHS Employers; 2016. NHS Employers. Agenda for change pay scales and points April 2016. London: NHS Employers; 2016.
9.
go back to reference Curtis L, Burns A. Unit costs of health and social care 2016. Canterbury: Personal Social Services Research Unit; 2016. Curtis L, Burns A. Unit costs of health and social care 2016. Canterbury: Personal Social Services Research Unit; 2016.
10.
go back to reference Department of Health and Social Care. NHS reference costs 2015 to 2016. Canterbury: Personal Social Services Research Unit; 2016. Department of Health and Social Care. NHS reference costs 2015 to 2016. Canterbury: Personal Social Services Research Unit; 2016.
11.
go back to reference Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299–309.CrossRef Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299–309.CrossRef
12.
go back to reference Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr. 2013;13(6, Supplement):S38–44.CrossRef Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr. 2013;13(6, Supplement):S38–44.CrossRef
13.
go back to reference The Health Foundation. The impact of providing enhanced support for care home residents in Rushcliffe. 2017. The Health Foundation. The impact of providing enhanced support for care home residents in Rushcliffe. 2017.
14.
go back to reference The Health Foundation. The impact of providing enhanced support for Sutton Homes of Care residents. 2018. The Health Foundation. The impact of providing enhanced support for Sutton Homes of Care residents. 2018.
15.
go back to reference Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15(2):480–500.CrossRef Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15(2):480–500.CrossRef
16.
go back to reference Shadish WR, Cook TD, Campbell DT. Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin; 2002. Shadish WR, Cook TD, Campbell DT. Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin; 2002.
17.
go back to reference Hawley S, Ali MS, Berencsi K, Judge A, Prieto-Alhambra D. Sample size and power considerations for ordinary least squares interrupted time series analysis: a simulation study. Clin Epidemiol. 2019;11:197–205.CrossRef Hawley S, Ali MS, Berencsi K, Judge A, Prieto-Alhambra D. Sample size and power considerations for ordinary least squares interrupted time series analysis: a simulation study. Clin Epidemiol. 2019;11:197–205.CrossRef
18.
go back to reference Ramsay CR, Matowe L, Grilli R, Grimshaw JM, Thomas RE. Interrupted time series designs in health technology assessment: lessons from two systematic reviews of behavior change strategies. Int J Technol Assess Health Care. 2003;19(4):613–23.CrossRef Ramsay CR, Matowe L, Grilli R, Grimshaw JM, Thomas RE. Interrupted time series designs in health technology assessment: lessons from two systematic reviews of behavior change strategies. Int J Technol Assess Health Care. 2003;19(4):613–23.CrossRef
19.
go back to reference Cochrane Effective Practice and Organisation of Care (EPOC). Interrupted time series (ITS) analyses. London: Cochrane Collaberation; 2017. Cochrane Effective Practice and Organisation of Care (EPOC). Interrupted time series (ITS) analyses. London: Cochrane Collaberation; 2017.
20.
go back to reference Petch A. Delivering integrated care and support (insights no 24). Glasgow: Institute for Research and Innovation in Social Services; 2014. Petch A. Delivering integrated care and support (insights no 24). Glasgow: Institute for Research and Innovation in Social Services; 2014.
21.
go back to reference Hawe P, Shiell A, Riley T. Theorising interventions as events in systems. Am J Community Psychol. 2009;43(3–4):267–76.CrossRef Hawe P, Shiell A, Riley T. Theorising interventions as events in systems. Am J Community Psychol. 2009;43(3–4):267–76.CrossRef
22.
go back to reference Lopez Bernal J, Cummins S, Gasparrini A. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol. 2018;47(6):2082–93.CrossRef Lopez Bernal J, Cummins S, Gasparrini A. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol. 2018;47(6):2082–93.CrossRef
23.
go back to reference The Kings Fund. Enhanced health in care homes learning from experiences so far. 2017. The Kings Fund. Enhanced health in care homes learning from experiences so far. 2017.
Metadata
Title
Rapid evaluation for health and social care innovations: challenges for “quick wins” using interrupted time series
Authors
Andrew McCarthy
Peter McMeekin
Shona Haining
Lesley Bainbridge
Claire Laing
Joanne Gray
Publication date
01-12-2019
Publisher
BioMed Central
Keyword
Care
Published in
BMC Health Services Research / Issue 1/2019
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-019-4821-7

Other articles of this Issue 1/2019

BMC Health Services Research 1/2019 Go to the issue