- Integrating digital solutions into big vendors' electronic medical records is challenging for smaller health tech companies, according to a new report from Health 2.0.
- The majority of EMR vendors included in the survey of more than 100 small health tech companies did not support any integrations. Allscripts and athenahealth were the only two exceptions.
- Most importantly, the surveyed companies that accomplished integration reported that the EMR vendors' application programming interfaces (APIs) were either "not great" or "poorly designed".
Since the federal government made a big push for EMR adoption, complaints have been flooding in about the systems' lack of usability and interoperability, as well as how time-consuming they can be. The largest burden for many has been financial. Having the ability of accessing patients' data may be nonetheless beneficial as it allows for a more comprehensive and accurate care plan even if it's missing some valuable information.
However, costs were not the largest deterrent for integration considerations among smaller tech companies since most of the big EMR vendors did not require an integration fee and half of the tech companies that responded to Health 2.0's survey had complicated APIs. Some reported the value their solutions would add would be insufficient for some EMR vendors to consider.
Survey responses suggest some EMR vendors are unhelpful. Epic, for example, told 70% of surveyed companies that a client's recommendation was required for their help.
Athenahealth, Allscripts, and McKesson had the best APIs, survey findings show. Allscripts didn't waste any time with advertising these results on Twitter.
Companies were very hesitant in responding to the survey because, according to Matthew Holt, co-chairman at Health 2.0 and founder of The Health Care Blog, they "view integration as a competitive advantage."
"Data quality and standardization is very poor, and for most of the client-server EMR vendors, each data model is different," Holt concluded. "So on a population level, data exchange may require much more work correcting data before it’s ready for analytics and treatment."