Development and psychometrics of a short-form pharmaceutical care-specific measure for quality of life
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Background The validated patient-reported outcomes measure of pharmaceutical therapy for quality of life (PROMPT-QoL) contains 43-items, and can be too lengthy for some applications. Objectives To develop a brief version called the PROMPT, and test its psychometric properties. Setting Four public hospitals in Bangkok, Thailand. Method Secondary analysis of three databases used to develop and evaluate the original PROMPT-QoL. Items for the short-form PROMPT were selected based on expert and patient evaluations of content and importance, and lack of redundancy. All domains of the original version are represented in the PROMPT. Main outcome measures Psychometric properties (internal consistency and test–retest reliability, criterion, convergent and discriminant validity, and responsiveness), and indicators of practicality (e.g., administration time, missing data). Results Analyses of the PROMPT and its domain subscales demonstrated good internal consistency and fair-to-excellent test–retest reliability. Correlations between the original and short-form, overall and by domain, were high. Expectations for convergent and discriminant validity were met as correlations between the PROMPT and generic health-related quality of life measures (WHOQoL-BREF domains and summary scores of the SF-12v2) were modest (< 0.40). Based on data from a trial of pharmaceutical care, the PROMPT short-form was very responsive to reductions in medication related problems. Administration time for the PROMPT is estimated to be about 5 min, and across all datasets used, no missing data were found amongst the 16 items of the PROMPT. Conclusion The 16-item PROMPT appears to be a practical, reliable, valid, and responsive instrument to identify patient’s drug-related needs and to assess the humanistic impact of patient-centered pharmaceutical care.
KeywordsPatient-reported outcomes Pharmaceutical care PROMPT-QOL Psychometrics Quality of life Thailand
This study was funded by Thailand Research Fund, Chulalongkorn University and Faculty of Pharmaceutical Sciences, Chulalongkorn University (Grant Number: RSA 5580035). Part of this study was presented as a poster at 24th Annual Conference of International Society of Quality of Life Research in Philadelphia, U.S.A., during October 18–21, 2017. The authors would like to thank all patients for their participation in the study and the hospital staff for assistance with the data collection. The authors also thank Professor Cynthia R. Gross for her advice and helping edit the manuscript.
This study was funded by Thailand Research Fund, Chulalongkorn University and Faculty of Pharmaceutical Sciences, Chulalongkorn University (Grant No. RSA 5580035).
Conflicts of interest
None of the authors has any conflict of interest to declare.
- 1.Ernst FR, Grizzel AJ. Drug-related morbidity and mortality updating the cost-of-illness model. J Am Pharm Assoc. 2001;41:192–9.Google Scholar
- 2.Tarapan S. Causes and expenses for drug-related problems management in inpatients at Crown Prince Leungnokta Hospital. In: Masters thesis. Bangkok: Chulalongkorn University; 2010.Google Scholar
- 4.Cipolle RJ, Strand LM, Morley PC. Pharmaceutical care practice: the clinician’s guide. 2nd ed. New York: McGraw-Hill; 2004.Google Scholar
- 14.Cape P. Questionnaire length, fatigue effects and response quality revisited 2010. http://www.surveysampling.com/ssi-media/Corporate/white_papers/SSI_QuestionLength_WP.image. Accessed 17 April 2015.
- 15.US Department of Health and Human Services, Food and Drug Administration. Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims 2009. Available http://www.fda.gov/downloads/Drugs/Guidances/UCM193282.pdf. Accessed 24 March 2014.
- 17.Nunnally JC Jr. Psychometric theory. 2nd ed. New York: McGraw-Hill; 1978.Google Scholar
- 18.Rosner B. Fundamental of biostatistics. 5th ed. Pacific Grove, California: Duxbury Thomson Learning; 2000.Google Scholar
- 19.Cohen P. Statistical power analysis for the behavioral sciences. 2nd ed. New Jersey: Lawrence Erlbaum Associates Hillsdale; 1988.Google Scholar
- 24.Mohammed MA, Moles RJ, Hilmer SN, O’Donnel LK, Chen TF. Development and validation of an instrument for measuring the burden of medicine on functioning and well-being the medication-related burden quality of life (MRB-QoL) tool. BMJ Open. 2018;8:e018880. https://doi.org/10.1136/bmjopen-2017-018880.CrossRefPubMedPubMedCentralGoogle Scholar