A team of researchers from Johns Hopkins, the Ohio State University, and the National Cancer Institute discuss that, deployed on projections from NCI survey data, 75% of US adults will utilize personal health records (PHRs) by the year 2020, even without extra interventions.
In a paper issued in the Journal of Medical Internet Research, academics extrapolated from the Health Information National Trends Survey (HINTS) from the years of 2008, 2011, and 2013 and implemented a product adoption prediction technique known as Bass modeling to secure PHR uptake into the future.
The writers depict 3 different models, relying on whether they believed the innovation start date for PHR technology to be 2001 (the development date for the oldest systems) or 2007 (the 1st year, in accordance to initial research, that clinically-based systems were widely present). The 3rd model was a compromise, putting the start date in the year 2004.
The best of these models put adoption at 75% in the year 2020, but all of them outperformed the adoption aims of the Meaningful Use Stage 2 and 3 instructions.
“Consumers’ PHR utilization is increasing in both the numbers of people involved and the degree of technological functionality they can handle,” researchers wrote. “As agencies recognize ways to make these devices more widely present, sophisticated PHR technologies would shift from the domain of initial adopters to the widespread utilization among a majority of customers in the market. As this happens, the key factor restricting PHR functionalities’ diffusion may well be health care vendors’ and contributors’ reticence to deploy these devices in a manner that resonates with the sufferer. It is not the customer who is unwilling to utilize these tools, but the deployment and hurdles they face that restricts their adoption.”
Deployed on their analysis, writers argued that Meaningful Use targets could really slow down PHR adoption from the amounts it would naturally tend towards.
“MU targets on this problem may have the similar issues in PHR adoption that they experienced in EHR adoption: the standards of engagement are low enough to permit for incremental accesses to adoption as opposed to incentivizing transformative goals,” they wrote. “Policy discussions in a ‘post-meaningful use’ world would take advantage from insights offered through these kinds of data-based diffusion analyses, particularly as the emphasis moves away from applying incentives for the proposed adoption, to driving innovation to curry the interest of engaged customers.”
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