While e-prescribing is a significant feature of meaningful use, it is also stands alone as a guide to tried and true adoption and sustained use. What eRx and the Surescripts National Progress report show is picture of how adoption takes place.
A model for success
The rise of e-prescribing over the past decade offers clues as to what’s missing in our present EHR valuation.
First, it’s having an appropriate amount of data. Antedating either incentive programs, the data for the annual report were and still are extensive:
One of the challenges is that we have so much data. What’s the right way to look at this?
Obviously, we said let’s look at prescribers who adopted previous to either the MIPPA or the EHR Incentive Programs kicking in and let’s understand what happens to those physicians from an adoption, utilization, and a behavioral standpoint (in terms of how they interact with their systems) over time.
Secondly, it’s having the right kind of data. For e-prescribing this means evaluating a prescriber’s use of an eRx system over a long period of time.
“Theoretically, we’ve postulated that when a physician adopts a standalone e-prescribing system or an EHR, it can take upwards of six months for that physician to get comfortable with the technology, for him or her to utilizing the system habitually,” continues Joseph, “What’s new about this analysis is not that we’ve seen their use levels off after six to nine months; utilization continues to increase on a pretty consistent and linear basis on a quarterly basis across all prescribers.”
Lastly, it’s having the right approach to data. In the digital age, data is a stream of information. Being able to capture this data requires systems that keep pace with the flow. “We have up-to-date, live real-time transactional data,” Joseph observes.
Conversely, fixed data — much of what constitutes these recent EHR reports — capture only a moment of time:
These studies of EHR use, clinical outcomes, and the costs associated with them, they’re so variable in terms of what the study outcomes are, what the findings are, how they are taken positively or negatively. By the way, all of that depends on the setting that the research looked at, the user base they looked at — it really is quite variable.
Akin to snapshot of a feature-length film, a small sample cannot account for all the factors preceding and following it. Its fullness is lost at the moment it’s removed from its context.
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