Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-11T03:59:38.389Z Has data issue: false hasContentIssue false

An application of PCA-DEA with the double-bootstrap approach to estimate the technical efficiency of New Zealand District Health Boards

Published online by Cambridge University Press:  26 January 2021

Antony Andrews*
Affiliation:
School of Economics, Auckland University of Technology, 120 Mayoral Drive, Auckland1010, New Zealand
*
Corresponding author. Email: antony.andrews@aut.ac.nz

Abstract

Using yearly panel data from 2011 to 2017 on New Zealand District Health Boards (DHBs), this study combines principal component analysis and data envelopment intertemporal analysis with the double-bootstrap approach to estimate the technical efficiency of health care providers along with the trend of efficiency performances. The results show that although most large DHBs have improved their level of technical efficiency between 2011 and 2017, the majority of medium- and small-sized DHBs have not seen any noticeable improvement in their level of technical efficiency. The results also show that large and tertiary DHBs operate at a high level of technical efficiency. In contrast, most of the medium- and small-sized DHBs posted some of the lowest technical efficiency scores. Furthermore, the results show that medium- and small-sized DHBs have a higher average length of hospital stays which is found to be associated with decreasing levels of technical efficiency scores.

Type
Article
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adler, N and Golany, B (2001) Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe. European Journal of Operational Research 132, 260273.CrossRefGoogle Scholar
Adler, N and Yazhemsky, E (2010) Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction. European Journal of Operational Research 202, 273284.CrossRefGoogle Scholar
Aigner, D, Knox Lovell, CA and Schmidt, P (1977) Formulation and estimation of stochastic frontier production function models. Journal of Econometrics 6, 2137.CrossRefGoogle Scholar
Ali, AI and Seiford, LM (1990) Translation invariance in data envelopment analysis. Operations Research Letters 9, 403405.Google Scholar
Allsopp, L (2006) Investigating Health Technology Diffusion in New Zealand – How Does it Spread and Who Stands to Gain?. https://treasury.govt.nz/publications/wp/investigating-health-technology-diffusion-new-zealand-how-does-it-spread-and-who-stands-gain-wp-06.Google Scholar
ASMS (2017 a) Shortage of senior doctors at Nelson Marlborough DHB part of wider pattern. https://www.asms.org.nz/news/asms-news/2017/09/18/shortage-senior-doctors-nelson-marlborough-dhb-part-wider-pattern/.Google Scholar
ASMS (2017 b) Survey of clinical leaders on Senior Medical Officer staffing needs: Nelson Marlborough District Health Board.Google Scholar
Banker, RD, Charnes, A and Cooper, WW (1984) Some Models for Estimating Technical and Scale Efficiency in Data Envelopment Analysis. Vol. 30.Google Scholar
Charnes, A, Cooper, WW and Rhodes, EL (1978) Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429444.CrossRefGoogle Scholar
Charnes, A, Clark, CT, Cooper, WW and Golany, B (1984) A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces. Annals of Operations Research 2, 95112.CrossRefGoogle Scholar
Charnes, A, Cooper, WW, Lewin, AY and Seiford, LM (1994) Extensions to DEA models. In Data Envelopment Analysis: Theory, Methodology, and Applications. Dordrecht: Springer Netherlands, pp. 4961.CrossRefGoogle Scholar
Chattopadhyay, S and Ray, SC (1996) Technical, scale, and size efficiency in nursing home care: a non-parametric analysis of Connecticut homes. Health Economics 5, 363373.3.0.CO;2-1>CrossRefGoogle Scholar
Coelli, TJ, Rao, DS, O'Donnell, C and Battese, GE (2005) An Introduction to Efficiency and Productivity Analysis. New York: Springer Science+Business Media, Inc.Google Scholar
Controller and Auditor-General (2013) Regional services planning in the health sector. https://www.oag.govt.nz/2013/regional-services-planning/part2.htm.Google Scholar
Controller and Auditor-General (2017) Main matters arising from the 2016/17 audits of district health boards. https://www.oag.govt.nz/2018/dhbs-audits.Google Scholar
Cullinane, K and Wang, T (2010) The efficiency analysis of container port production using DEA panel data approaches. OR Spectrum 32, 717738.CrossRefGoogle Scholar
Cumming, J, McDonald, J, Barr, C, Martin, G, Gerring, Z and Daube, J (2014) New Zealand health system review. Health Systems in Transition 4, 224.Google Scholar
Dong, F, Mitchell, PD and Colquhoun, J (2015) Measuring farm sustainability using data envelope analysis with principal components: the case of Wisconsin cranberry. Journal of Environmental Management 147, 175183.CrossRefGoogle ScholarPubMed
Farrell, MJ (1957) The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General) 120, 253290.CrossRefGoogle Scholar
Gauld, R (2016) Could lessons have been drawn from New Zealand for England's NHS reforms? Commonwealth & Comparative Politics 54, 518535.CrossRefGoogle Scholar
Grosskopf, S and Valdmanis, V (1993) Evaluating hospital performance with case-mix-adjusted outputs. Medical Care 31, 525532.CrossRefGoogle ScholarPubMed
Hollingsworth, B and Peacock, SJ (2008) Efficiency Measurement in Health and Health Care. New York, NY: Routledge.CrossRefGoogle Scholar
Hussey, PS, De Vries, H, Romley, J, Wang, MC, Chen, SS, Shekelle, PG and McGlynn, EA (2009) A systematic review of health care efficiency measures. Health Services Research 44, 784805.CrossRefGoogle ScholarPubMed
Jacobs, R, Smith, PC and Street, A (2006) Measuring Efficiency in Health Care: Analytic Techniques and Health Policy. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Kumbhakar, SC, Wang, H-J and Horncastle, AP (2015) A Practitioner's Guide to Stochastic Frontier Analysis Using Stata. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Meeusen, W and Van den Broeck, J (1977) Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review 18, 435444.CrossRefGoogle Scholar
Mitropoulos, P, Talias, ΜA and Mitropoulos, I (2015) Combining stochastic DEA with Bayesian analysis to obtain statistical properties of the efficiency scores: an application to Greek public hospitals. European Journal of Operational Research 243, 302311.CrossRefGoogle Scholar
Nataraja, NR and Johnson, AL (2011) Guidelines for using variable selection techniques in data envelopment analysis. European Journal of Operational Research 215, 662669.CrossRefGoogle Scholar
Pastor, JT (1996) Translation invariance in data envelopment analysis: a generalisation. Annals of Operations Research 66, 91102.CrossRefGoogle Scholar
Robson, B, Purdie, G, Simmonds, S, Waa, A, Faulkner, R and Rameka, R (2015) Tairāwhiti District Health Board Māori Health Profile 2015. https://www.otago.ac.nz/wellington/otago152495.pdf.Google Scholar
Simar, L and Wilson, PW (1998) Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Management Science 44, 4961.CrossRefGoogle Scholar
Simar, L and Wilson, PW (2007) Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics 136, 3164.CrossRefGoogle Scholar
Skinner, J (1994) What do stochastic frontier cost functions tell us about inefficiency? Journal of Health Economics 13, 323328.CrossRefGoogle ScholarPubMed
The Treasury (2005) Treasury Report: Value for Money in Health – The DHB Sector. https://treasury.govt.nz/sites/default/files/2007-11/tr05-344.pdf.Google Scholar
The Treasury (2014) Briefing to the Incoming Minister: Health. http://www.treasury.govt.nz/publications/briefings/2014-health/bim-14-health.pdf.Google Scholar
The Treasury (2016) Analysis of District Health Board Performance to June 30 2015. http://www.treasury.govt.nz/publications/informationreleases/health/dhb-performance/dhb-performance-jun16.pdf.Google Scholar
The Treasury (2017) Financial Statements of the Government of New Zealand for the Year Ended June 30 2017. https://treasury.govt.nz/publications/year-end/financial-statements-30-june-2017-html.Google Scholar
Ueda, T and Hoshiai, Y (1997) Application of principal component analysis for parsimonious summarisation of DEA inputs and/or outputs. Journal of the Operations Research Society of Japan 40, 466478.CrossRefGoogle Scholar
West Coast District Health Board (2017) West Coast Physio Shortages Result in Changes. https://www.wcdhb.health.nz/media-release/west-coast-physio-shortages-result/.Google Scholar
West Coast District Health Board (2018) Quality Accounts 2018. https://www.wcdhb.health.nz/wp-content/uploads/Focus-on-People-2018-E-Version.pdf.Google Scholar
Worthington, AC (2004) Frontier efficiency measurement in health care: a review of empirical techniques and selected applications. Medical Care Research and Review 61, 135170.CrossRefGoogle ScholarPubMed