Measuring quality of health care from the user’s perspective in 41 countries: psychometric properties of WHO’s questions on health systems responsiveness
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To evaluate, for different populations, psychometric properties of questions on “health systems responsiveness”, a concept developed by World Health Organization (WHO) to describe non-clinical and non-financial aspects of quality of health care.
Data sources/study setting/data collection
The 2000–2002 WHO Multi-Country Study comprised 70 general population surveys. Forty-one surveys were interviewer-administered, from which we extracted respondent records indicating ambulatory and inpatient health services use (excluding long-term institutions) in the previous 12 months (50,876 ambulatory and 7,964 hospital interviews).
We evaluated feasibility, reliability, and construct validity using 33 items with polytomous response options, comparing responses from populations identified by countries, sex, age, education, health and income.
Average item missing rates ranged from 0 to 16%. Domain-specific alpha coefficients exceeded 0.7 in 7 (of 9) cases. Average intertemporal reliability was acceptable in 6 (of 10) sites, where Kappas ranged from 0.54 to 0.79, but low in 4 sites (K < 0.5). Kappa statistics were higher for male, educated and healthier populations than for female, less educated and less healthy populations. Factor solutions confirmed the domain structure of 7 domains (only 7 were operationalized for ambulatory settings). As in other studies, higher incomes and age was associated with more positive responsiveness reports and ratings.
Quality issues addressed by WHO’s questions are understood and reported adequately across diverse populations. More research is needed to interpret user-assessed quality of care comparisons across population groups within and between countries.
KeywordsQuality of health care Health care surveys Quality indicators Patient-centred care Physician-patient relations Psychometrics
List of Abbreviations
United States Agency for Healthcare Research and Quality
Consumer Assessment of Health Plans Survey
- MCS Study
Multi-Country Survey Study on Health and Health Systems Responsiveness
Maximum Likelihood (factor analysis)
Quality of care through patients’ eyes
Correlation Coefficient (Pearson or Spearman, as specified)
United Nations Development Programme
United Nations Educational, Scientific and Cultural Organization
World Health Organization
- 1.Kelley, E., & Hurst, J. (2006). Health care quality indicators project conceptual framework paper. OECD Health Working Papers No. 23. Retrieved 30 May at: http://www.oecd.or..Google Scholar
- 2.Donabedian, A. (1980). Explorations in quality assessment and monitoring: the definition of quality and approaches to assessment. Ann Arbor, Michigan: Health Administration PressGoogle Scholar
- 3.Murray, C. J. L., & Frenk, J. (2000). A framework for assessing the performance of health systems. Bulletin of the World Health Organisation, 78(6), 717–731Google Scholar
- 4.Thompson, A. G. H., & Sunol, R. (1995). Expectations as determinants of patient satisfaction. Health Expectation, 2, 93–104.Google Scholar
- 6.Wensing, M., Jung, H. P., Mainz J., Olesen, F., & Grol, R. (1998). A systematic review of the literature on patient priorities for general practice care. Part 1: Description of the research domain. Social Science and Medicine, 47(10), 1573–1588.Google Scholar
- 9.De Silva A. A framework for measuring responsiveness. (Discussion Paper 32) 2000. Retrieved December 1, 2005, from http://www.who.int/responsiveness/papers/e.Google Scholar
- 13.Ustun, B. S. et al. WHO multi-country survey study on health and responsiveness 2000–2001 (Discussion Paper 37) 2003. Retrieved December 1, 2005, from http://www.who.int/responsiveness/papers/e..Google Scholar
- 14.Schafer, J. L. (2001). NORM: multiple imputation of incomplete multivariate data under a normal model [statistical software]. University Park: Penn. State University. Department of StatisticsGoogle Scholar
- 16.DeVellis, R. F. (1991). Scale Development. Theory and applications. (Applied Social Research Methods Series Volume 26.) London: Sage PublicationsGoogle Scholar
- 17.UNDP (2001). Human development report. New York: UNDP.Google Scholar
- 19.Cramer, D., & Howitt, D. (2004). The SAGE dictionary of statistics. London: Sage PublicationsGoogle Scholar
- 20.Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. (3rd ed.). New York: McGraw-HillGoogle Scholar
- 21.Kim, J., & Mueller, C. W. (1978). Factor analysis statistical methods and practical issues. In E. M. Uslaner (Ed.), Quantitative Applications in the Social Sciences. London: SageGoogle Scholar
- 23.UNESCO. Educational Statistic, 2002. Retrieved May 30, 2006, from http://www.uis.unesco.org..Google Scholar
- 27.Ware, J. (1976). Scales for measuring general health perceptions. Health Services Research, (Winter), 396–415.Google Scholar
- 28.Hudson, S., Weisman, C., Anderson, R., & Camacho, F. (2004). The development and validation of the primary care satisfaction survey for women. Women Health Issues, 14, 35–50Google Scholar
- 30.Grogan, S., Conner, M., Norman, P., & Willits, D. (2000) Porter Validation of a questionnaire measuring patient satisfaction with general practitioner services. Quality and Safety in Health, Care 9, 210–215Google Scholar
- 32.Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life; perceptions evaluations and satisfactions. New York: Russell Sage FoundationGoogle Scholar