David T Eton1,2, Kathleen J Yost3,4, Jin-Shei Lai5, Jennifer L Ridgeway6,3, Jason S Egginton6,3, Jordan K Rosedahl3,7, Mark Linzer8, Deborah H Boehm9, Azra Thakur10, Sara Poplau9, Laura Odell11, Victor M Montori6,12, Carl R May12,13, Roger T Anderson14. 1. Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. eton.david@mayo.edu. 2. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. eton.david@mayo.edu. 3. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 4. Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 5. Department of Medical Social Sciences, Northwestern University School of Medicine, 633 St. Clair, 19th Floor, Chicago, IL, USA. 6. Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 7. Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 8. Hennepin County Medical Center, 701 Park Avenue, Minneapolis, MN, USA. 9. Minneapolis Medical Research Foundation, 701 Park Avenue, Minneapolis, MN, USA. 10. Amherst H. Wilder Foundation, 451 Lexington Parkway N, Saint Paul, MN, 55104, USA. 11. Pharmacy Services, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 12. Knowledge Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 13. Faculty of Health Sciences, University of Southampton, Southampton, UK. 14. Department of Public Health Sciences, University of Virginia School of Medicine, 6203E, West Complex, Charlottesville, VA, USA.
Abstract
PURPOSE: The purpose of this study was to develop and validate a new comprehensive patient-reported measure of treatment burden-the Patient Experience with Treatment and Self-management (PETS). METHODS: A conceptual framework was used to derive the PETS with items reviewed and cognitively tested with patients. A survey battery, including a pilot version of the PETS, was mailed to 838 multi-morbid patients from two healthcare institutions for validation. RESULTS: A total of 332 multi-morbid patients returned completed surveys. Diagnostics supported deletion and consolidation of some items and domains. Confirmatory factor analysis supported a domain model for scaling comprised of 9 factors: medical information, medications, medical appointments, monitoring health, interpersonal challenges, medical/healthcare expenses, difficulty with healthcare services, role/social activity limitations, and physical/mental exhaustion. Scales showed good internal consistency (α range 0.79-0.95). Higher PETS scores, indicative of greater treatment burden, were correlated with more distress, less satisfaction with medications, lower self-efficacy, worse physical and mental health, and lower convenience of healthcare (Ps < 0.001). Patients with lower health literacy, less adherence to medications, and more financial difficulties reported higher PETS scores (Ps < 0.01). CONCLUSION: A comprehensive patient-reported measure of treatment burden can help to better characterize the impact of treatment and self-management burden on patient well-being and guide care toward minimally disruptive medicine.
PURPOSE: The purpose of this study was to develop and validate a new comprehensive patient-reported measure of treatment burden-the Patient Experience with Treatment and Self-management (PETS). METHODS: A conceptual framework was used to derive the PETS with items reviewed and cognitively tested with patients. A survey battery, including a pilot version of the PETS, was mailed to 838 multi-morbid patients from two healthcare institutions for validation. RESULTS: A total of 332 multi-morbid patients returned completed surveys. Diagnostics supported deletion and consolidation of some items and domains. Confirmatory factor analysis supported a domain model for scaling comprised of 9 factors: medical information, medications, medical appointments, monitoring health, interpersonal challenges, medical/healthcare expenses, difficulty with healthcare services, role/social activity limitations, and physical/mental exhaustion. Scales showed good internal consistency (α range 0.79-0.95). Higher PETS scores, indicative of greater treatment burden, were correlated with more distress, less satisfaction with medications, lower self-efficacy, worse physical and mental health, and lower convenience of healthcare (Ps < 0.001). Patients with lower health literacy, less adherence to medications, and more financial difficulties reported higher PETS scores (Ps < 0.01). CONCLUSION: A comprehensive patient-reported measure of treatment burden can help to better characterize the impact of treatment and self-management burden on patient well-being and guide care toward minimally disruptive medicine.
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