Domino Determann1,2, Mattijs S Lambooij1, Dorte Gyrd-Hansen3,4, Esther W de Bekker-Grob2,5, Ewout W Steyerberg2, Marcel Heldoorn6, Line Bjørnskov Pedersen3,7, G Ardine de Wit1,8. 1. Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands. 2. Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. 3. COHERE - Centre of Health Economics Research, Department of Business and Economics, University of Southern Denmark, Odense, Denmark. 4. COHERE - Centre of Health Economics Research, Department of Public Health, University of Southern Denmark, Odense, Denmark. 5. Institute of Health Policy and Management, Erasmus University Rotterdam, the Netherlands. 6. Dutch Federation of Patients and Consumer Organizations (NPCF), Utrecht, the Netherlands. 7. Research Unit for General Practice, University of Southern Denmark, Odense, Denmark. 8. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
Abstract
OBJECTIVE: To identify groups of potential users based on their preferences for characteristics of personal health records (PHRs) and to estimate potential PHR uptake. METHODS: We performed a discrete choice experiment, which consisted of 12 choice scenarios, each comprising 2 hypothetical PHR alternatives and an opt-out. The alternatives differed based on 5 characteristics. The survey was administered to Internet panel members of the Dutch Federation of Patients and Consumer Organizations. We used latent class models to analyze the data. RESULTS: A total of 1,443 potential PHR users completed the discrete choice experiment. We identified 3 latent classes: "refusers" (class probability 43%), "eager adopters" (37%), and "reluctant adopters" (20%). The predicted uptake for the reluctant adopters ranged from 4% in the case of a PHR with the worst attribute levels to 68% in the best case. Those with 1 or more chronic diseases were significantly more likely to belong to the eager adopter class. The data storage provider was the most decisive aspect for the eager and reluctant adopters, while cost was most decisive for the refusers. Across all classes, health care providers and independent organizations were the most preferred data storage providers. CONCLUSION: We identified 3 groups, of which 1 group (more than one-third of potential PHR users) indicated great interest in a PHR irrespective of PHR characteristics. Policymakers who aim to expand the use of PHRs will be most successful when health care providers and health facilities or independent organizations store PHR data while refraining from including market parties.
OBJECTIVE: To identify groups of potential users based on their preferences for characteristics of personal health records (PHRs) and to estimate potential PHR uptake. METHODS: We performed a discrete choice experiment, which consisted of 12 choice scenarios, each comprising 2 hypothetical PHR alternatives and an opt-out. The alternatives differed based on 5 characteristics. The survey was administered to Internet panel members of the Dutch Federation of Patients and Consumer Organizations. We used latent class models to analyze the data. RESULTS: A total of 1,443 potential PHR users completed the discrete choice experiment. We identified 3 latent classes: "refusers" (class probability 43%), "eager adopters" (37%), and "reluctant adopters" (20%). The predicted uptake for the reluctant adopters ranged from 4% in the case of a PHR with the worst attribute levels to 68% in the best case. Those with 1 or more chronic diseases were significantly more likely to belong to the eager adopter class. The data storage provider was the most decisive aspect for the eager and reluctant adopters, while cost was most decisive for the refusers. Across all classes, health care providers and independent organizations were the most preferred data storage providers. CONCLUSION: We identified 3 groups, of which 1 group (more than one-third of potential PHR users) indicated great interest in a PHR irrespective of PHR characteristics. Policymakers who aim to expand the use of PHRs will be most successful when health care providers and health facilities or independent organizations store PHR data while refraining from including market parties.
Authors: John F P Bridges; A Brett Hauber; Deborah Marshall; Andrew Lloyd; Lisa A Prosser; Dean A Regier; F Reed Johnson; Josephine Mauskopf Journal: Value Health Date: 2011-04-22 Impact factor: 5.725
Authors: Caroline Lubick Goldzweig; Greg Orshansky; Neil M Paige; Ali Alexander Towfigh; David A Haggstrom; Isomi Miake-Lye; Jessica M Beroes; Paul G Shekelle Journal: Ann Intern Med Date: 2013-11-19 Impact factor: 25.391