The high cost of EHRs is said to curtail use of predictive analytics
As more and more healthcare providers use electronic health records (EHR), opportunities for leveraging predictive analytics to improve population health and lower costs to providers should increase.
“The ever increasing volume, variety, and velocity of clinical and non-clinical data have compelled healthcare organizations to implement statistical tools, data science, and mining technology,” according to a new report published by Research and Markets.
But the high price tag of EHRs will “act as a significant barrier” to predictive analytics adoption among healthcare providers, the report said.
“The cost of implementing healthcare information system is expensive as it requires installation of software, hardware, networking infrastructure, IT support, and training fees,” Research and Markets wrote. “In addition, the integration of EHR systems with pharmacy information and laboratory information systems for information exchange requires additional hardware and software installation costs that may not be affordable for hospitals in developing countries.”
In a 2014 survey of U.S. physicians by marketing and research firm MPI Group and Medical Economics, 45 percent of respondents said their practices spent more than $100,000 on an EHR, while 77 percent of larger practices said the cost of their EHRs was near $200,000. The investment by hospital systems is even higher.
Despite the warning, Research and Markets forecasts a compound annual growth rate of 5.53 percent for the EHR market from this year through 2020, citing the transition to ICD-10 from ICD-9 as a “driver” of the market.
“EHR adoption is picking up among clinics and hospitals as it is user-friendly and easy to manage,” the report said. “EHR stores patient health-related data such as past medications, radiology reports, and progress reports. It helps automate and streamline a healthcare service provider’s workflow.”
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