OBJECTIVE: Pay-for-performance programs are used to promote improved health care quality, often through increased use of health information technology. However, little is known about whether pay-for-performance programs influence the adoption of health information technology, especially among child health providers. This study explored how various pay-for-performance compensation methods are related to health information technology use. METHODS: Survey data from 1014 child health providers practicing in Florida were analyzed by using univariate and multivariate techniques. Questions asked about the adoption of electronic health records and personal digital assistants, as well as types of activities that affected child health provider compensation or income. RESULTS: The most common reported method to affect respondents' compensation was traditional productivity or billing (78%). Of the pay-for-performance-related methods of compensation, child health providers indicated that measures of clinical care (41%), patient surveys and experience (34%), the use of health information technology (29%), and quality bonuses or incentives (27%) were a major or minor factor in their compensation. In multivariate logistic regression analyses, only pay-for-performance programs that compensated directly for health information technology use were associated with an increased likelihood of electronic health record system adoption. Pay-for-performance programs linking measures of clinical quality to compensation were positively associated with personal digital assistant use among child health providers. CONCLUSIONS: Pay-for-performance programs that do not directly emphasize health information technology use do not influence the adoption of electronic health records among Florida physicians treating children. Understanding how different pay-for-performance compensation methods incentivize health information technology adoption is important for improving quality.
OBJECTIVE: Pay-for-performance programs are used to promote improved health care quality, often through increased use of health information technology. However, little is known about whether pay-for-performance programs influence the adoption of health information technology, especially among child health providers. This study explored how various pay-for-performance compensation methods are related to health information technology use. METHODS: Survey data from 1014 child health providers practicing in Florida were analyzed by using univariate and multivariate techniques. Questions asked about the adoption of electronic health records and personal digital assistants, as well as types of activities that affected child health provider compensation or income. RESULTS: The most common reported method to affect respondents' compensation was traditional productivity or billing (78%). Of the pay-for-performance-related methods of compensation, child health providers indicated that measures of clinical care (41%), patient surveys and experience (34%), the use of health information technology (29%), and quality bonuses or incentives (27%) were a major or minor factor in their compensation. In multivariate logistic regression analyses, only pay-for-performance programs that compensated directly for health information technology use were associated with an increased likelihood of electronic health record system adoption. Pay-for-performance programs linking measures of clinical quality to compensation were positively associated with personal digital assistant use among child health providers. CONCLUSIONS: Pay-for-performance programs that do not directly emphasize health information technology use do not influence the adoption of electronic health records among Florida physicians treating children. Understanding how different pay-for-performance compensation methods incentivize health information technology adoption is important for improving quality.
Authors: L Keoki Williams; Edward L Peterson; Karen Wells; Janis Campbell; Mingqun Wang; Vimal K Chowdhry; Matthew Walsh; Robert Enberg; David E Lanfear; Manel Pladevall Journal: J Allergy Clin Immunol Date: 2010-05-31 Impact factor: 10.793