The following appeared a little while ago.
PHR adoption hinges primarily on ease of use, value to consumers
November 7, 2012 | By Susan D. Hall
Ease of use and the perceived advantage of logging on to personal health records were the leading factors to PHR adoption according to researchers from Brigham and Women's Hospital in Boston, who published their findings this week in the Journal of Medical Internet Research.
The study also looked at sociodemographic characteristics, access and use of technology, perceived innovativeness with technology, and perceptions of privacy and security.
In the study, 760 surveyed patients from the ambulatory care practices of Brigham and Women's Hospital and Massachusetts General Hospital were identified in three groups: PHR users; rejecters--those who never logged on; and non-adopters--those who initially logged on, but never used the PHR.
Non-adopters reported lower rates of computer use than PHR users and rejecters. Not too surprisingly, PHR users scored the ease of use and relative advantage of the PHR higher than rejecters and non-adopters.
The work contrasts to a recent study published by researchers from the University of Central Florida which found no link between age, income and education in willingness to adopt a PHR. That study focused only on intent to adopt a PHR, not whether patients actually adopted the technology.
More here:
Here is the abstract:
Patient Perceptions of a Personal Health Record: A Test of the Diffusion of Innovation Model
Srinivas Emani1*, PhD, MA; Cyrus K Yamin2*, MD; Ellen Peters3*, PhD; Andrew S Karson4*, MD, MPH; Stuart R Lipsitz1*, ScD; Jonathan S Wald5*, MD, MPH; Deborah H Williams1*, MHA; David W Bates1,6*, MD, MSc
ABSTRACT
Background: Personal health records (PHRs) have emerged as an important tool with which patients can electronically communicate with their doctors and doctor’s offices. However, there is a lack of theoretical and empirical research on how patients perceive the PHR and the differences in perceptions between users and non-users of the PHR.
Objective: To apply a theoretical model, the diffusion of innovation model, to the study of PHRs and conduct an exploratory empirical study on the applicability of the model to the study of perceptions of PHRs. A secondary objective was to assess whether perceptions of PHRs predict the perceived value of the PHR for communicating with the doctor’s office.
Methods: We first developed a survey capturing perceptions of PHR use and other factors such as sociodemographic characteristics, access and use of technology, perceived innovativeness in the domain of information technology, and perceptions of privacy and security. We then conducted a cross-sectional survey (N = 1500). Patients were grouped into five groups of 300: PHR users (innovators, other users, and laggards), rejecters, and non-adopters. We applied univariate statistical analysis (Pearson chi-square and one-way ANOVA) to assess differences among groups and used multivariate statistical techniques (factor analysis and multiple regression analysis) to assess the presence of factors identified by the diffusion of innovation model and the predictors of our dependent variable (value of PHR for communicating with the doctor’s office).
Results: Of the 1500 surveys, 760 surveys were returned for an overall response rate of 51%. Computer use among non-adopters (75%) was lower than that among PHR users (99%) and rejecters (92%) (P < .001). Non-adopters also reported a lower score on personal innovativeness in information technology (mean = 2.8) compared to 3.6 and 3.1, respectively, for users and rejecters (P < .001). Four factors identified by the diffusion of innovation model emerged in the factor analysis: ease of use, relative advantage, observability, and trialability. PHR users perceived greater ease of use and relative advantage of the PHR than rejecters and non-adopters (P<.001). Multiple regression analysis showed the following factors as significant positive predictors of the value of PHR for communicating with the doctor’s office: relative advantage, ease of use, trialability, perceptions of privacy and security, age, and computer use.
Conclusion: Our study found that the diffusion of innovation model fits the study of perceptions of the PHR and provides a suitable theoretical and empirical framework to identify the factors that distinguish PHR users from non-users. The ease of use and relative advantage offered by the PHR emerged as the most important domains among perceptions of PHR use and in predicting the value of the PHR. Efforts to improve uptake and use of PHRs should focus on strategies that enhance the ease of use of PHRs and that highlight the relative advantages of PHRs.
Objective: To apply a theoretical model, the diffusion of innovation model, to the study of PHRs and conduct an exploratory empirical study on the applicability of the model to the study of perceptions of PHRs. A secondary objective was to assess whether perceptions of PHRs predict the perceived value of the PHR for communicating with the doctor’s office.
Methods: We first developed a survey capturing perceptions of PHR use and other factors such as sociodemographic characteristics, access and use of technology, perceived innovativeness in the domain of information technology, and perceptions of privacy and security. We then conducted a cross-sectional survey (N = 1500). Patients were grouped into five groups of 300: PHR users (innovators, other users, and laggards), rejecters, and non-adopters. We applied univariate statistical analysis (Pearson chi-square and one-way ANOVA) to assess differences among groups and used multivariate statistical techniques (factor analysis and multiple regression analysis) to assess the presence of factors identified by the diffusion of innovation model and the predictors of our dependent variable (value of PHR for communicating with the doctor’s office).
Results: Of the 1500 surveys, 760 surveys were returned for an overall response rate of 51%. Computer use among non-adopters (75%) was lower than that among PHR users (99%) and rejecters (92%) (P < .001). Non-adopters also reported a lower score on personal innovativeness in information technology (mean = 2.8) compared to 3.6 and 3.1, respectively, for users and rejecters (P < .001). Four factors identified by the diffusion of innovation model emerged in the factor analysis: ease of use, relative advantage, observability, and trialability. PHR users perceived greater ease of use and relative advantage of the PHR than rejecters and non-adopters (P<.001). Multiple regression analysis showed the following factors as significant positive predictors of the value of PHR for communicating with the doctor’s office: relative advantage, ease of use, trialability, perceptions of privacy and security, age, and computer use.
Conclusion: Our study found that the diffusion of innovation model fits the study of perceptions of the PHR and provides a suitable theoretical and empirical framework to identify the factors that distinguish PHR users from non-users. The ease of use and relative advantage offered by the PHR emerged as the most important domains among perceptions of PHR use and in predicting the value of the PHR. Efforts to improve uptake and use of PHRs should focus on strategies that enhance the ease of use of PHRs and that highlight the relative advantages of PHRs.
(J Med Internet Res 2012;14(6):e150)
doi:10.2196/jmir.2278
doi:10.2196/jmir.2278
The full paper is found here:
This is another paper DoHA / NEHTA need to look at carefully. Note three things.
1. The digital divide seems to be pretty important.
2. Usage seems to need the capacity to communicate with the doctor’s office - which the NEHRS does not facilitate.
3. Ease of use matters!
4. Providing real and perceived value to consumers matters!
Well worth a close look.
David.
As my kids would say..."Epic Fail"....NEHRS
ReplyDeleteDavid, this report from the Brigham's group offers interesting findings that differ from those of Warner Slack (1976/2012) where age, gender and previous computer experience were not signficant factors in the use of mhealth. Also the Californian Care Foundation found the highest uptake of mHealth bu the lower socioeconomic Latino communities. In addition more Afro-Americans adopt health related Apps than other groups. http://clarityspecialists.wordpress.com/2011/02/23/some-interesting-mobile-health-mhealth-statistics-from-himss-11/
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