Rural Docs Pull Ahead in Electronic Records
A greater percentage of rural medical practitioners have adopted electronic medical records, which are touted as a way to hold down costs and improve health-care results. A new study looks at the numbers and why rural may be outpacing urban practices in using this new technology.
The findings counter broadly held assumptions that rural areas always lag urban ones in the adoption of new technology.
The reasons for rural practitioners’ quicker acceptance of computer-based medical record keeping could be the unique characteristics of rural practices (such as more Medicare and Medicaid patients) or changes in the data products available to rural practices. Or it might be the result of an innovative government program that helps practices learn to use electronic records.
What are EMRs?
Electronic medical records (or EMRs, for short) are computer-based patient records that allow the sharing of information between medical sites (such as a doctor’s office and a hospital, or a pharmacist and a specialist). EMRs became a hot topic in the healthcare industry in the 1990s, with the idea that they could help reduce medical costs (due to a reduction in unnecessary tests) and improve health outcomes (due to better coordination of care and fewer medical errors).
Initially, however, EMRs were slow to catch on in many practices because of high start-up costs, technology requirements, and reluctance from many physicians. As part of the American Recovery and Reinvestment Act of 2009, the HITECH Act specifically focused on increasing the adoption of EMRs by offering Medicare and Medicaid incentive payments to physicians who “meaningfully used” EMRs.
The funding behind this effort was significant – over $30 billion in incentive payments, translating to between $44,000 and $64,000 per eligible practitioner. These payments were to be made over a period of four to six years as the practitioners continued to demonstrate “meaningful use.” In most cases, these payments would be enough to cover the up-front costs associated with purchasing an electronic medical records system. In addition to these payments, the act set up a federally funded Regional Extension Center (REC) program with personnel dedicated to assisting primary care providers to adopt and use EMRs. The REC program placed a particular emphasis on clinicians who care for uninsured and underinsured populations – including those in rural areas.
Rural Practices Move Ahead
The impact of these programs on practices – particularly those in rural locations – has been dramatic. As of 2012, and for the first time, practice-level EMR adoption rates in rural areas outpaced those in urban areas (56% to 49%), according to the study. This represents an impressive shift from earlier studies that showed rural doctors significantly lagging their urban counterparts (this 2007 study documents physician EMR adoption rates of 18% rural vs. 24% urban).
Figure 1 shows that 27 states have overall EMR adoption rates that are statistically higher in rural practices than those found in urban practices. Of those, 10 states have EMR adoption rates that are more than 9 percentage points higher in rural areas of the state (the dark blue). Only 2 states (Connecticut and Vermont) have higher rates in urban locations. Three states do not have any nonmetropolitan counties (DE, NJ, RI), and 18 states did not have adoption rates that were statistically different between metro and non-metro areas.
Another explanation might be that EMR companies have now successfully catered to the rural market, creating smaller, less robust systems than were initially available. Early adopters of EMRs had only a few choices of systems, and these were typically developed for large urban practices. As EMRs became more common, the market evolved and several vendors explicitly targeted rural practices.
Overall, the results show that rural physicians have enthusiastically embraced EMRs and that rural areas can actually lead the way in the adoption of an important technology.
Brian Whitacre is an Extension faculty member in the Department of Agricultural Economics at Oklahoma State University.
The study on which this article is based will be published in a forthcoming edition of the Journal of the American Medical Informatics Association.