Scandinavian Working Papers in Economics
HERO Online Working Paper Series,
University of Oslo, Health Economics Research Programme
No 2001:12: Errors in Survey Based Quality Evaluation Variables in Efficiency Models of Primary Care Physicians
Sverre A.C. Kittelsen (), Guri Galtung Kjæserud and Odd Jarle Kvamme
Additional contact information
Sverre A.C. Kittelsen: Frisch Centre, Postal: Gaustadalléen 21, N-0349 Oslo, Norway
Guri Galtung Kjæserud: Frisch Centre, Postal: Norway
Odd Jarle Kvamme: Department of General Practice, Postal: University of Oslo, Norway
Abstract: Efficiency analyses in the health care sector are often criticised for not incorporating quality variables. The definition of quality of primary health care has many aspects, and it is inevitably also a question of the patients’ perception of the services received. This paper uses variables derived from patient evaluation surveys as measures of the quality of the production of health care services. It uses statistical tests to judge if such measures have a significant impact on the use of resources in various Data Envelopment Analysis (DEA) models. As the use of survey data implies that the quality variables are measured with error, the assumptions underlying a DEA model are not strictly fulfilled. This paper focuses on ways of correcting for biases that might result from the violation of selected assumptions. Firstly, any selection bias in the patient mix of each physician is controlled for by regressing the patient evaluation responses on the patient characteristics. The corrected quality evaluation variables are entered as outputs in the DEA model, and model specification tests indicate that out of 25 different quality variables, only waiting time has a systematic impact on the efficiency results. Secondly, the effect on the efficiency estimates of the remaining sampling error in the patient sample for each physician is accounted for by constructing confidence intervals based on resampling. Finally, as an alternative approach to including the quality variables in the DEA model, a regression model finds different variables significant, but not always with a trade-of between quality and quantity.
Keywords: DEA; Health economics; Quality; Patient evaluation; Efficiency; Errors in variables; Resampling; Bootstrap; Selection bias; Sampling error
25 pages, June 30, 2009
Full text files
HERO2001_12.pdf
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