Barriers to the adoption of clinical decision support tools
What follows is excerpted from “The convergence of quality and efficiency,” by Helen Blumen and Lynn Nemiccolo. Today’s discussion continues where yesterday left off, explaining resistance to the convergence concept.
One of the major barriers identified in the NEJM study was physician resistance. In the hospitals surveyed, 36% of those who did not have an EHR stated that physician resistance was a barrier.34 Physicians resist the use of CDS tools for a variety of reasons, but the main reason is the belief that the use of an EHR and CDS tools will decrease clinical productivity and affect financial reimbursement. Other reasons range from not wanting a computer system to infringe on their decision making to something known as alert fatigue. Alert fatigue is when physicians have been exposed to poorly implemented EHRs that warn them continuously of possible problems as they access the system. Moreover, many of the CDS tools used today have been developed without clinician input, increasing resistance to their use. But if guidelines can be used to fine-tune EHR, and EHR can inform the creation of more user-efficient guidelines, what can emerge is a usability feedback loop that results in a self-improving system that avoids the dynamic of alert fatigue.
Cost is another significant barrier to EHR adoption. The initial cost of purchasing an EHR system is compounded by the implementation costs. Once the system is implemented, hospitals incur ongoing costs related to maintaining the system as well as keeping current the evidence-based clinical knowledge that is accessed by the CDS tools. All of the people using the EHR system require extensive training, further affecting the productivity of the provider.
The expenses related to EHR have made it seem to many a losing proposition. Indeed, there has been a clear lack of proven return on investment (ROI) for the implementation of organization-wide EHRs. Anecdotal estimates range from $1 million to more than $80 million for the purchase and multi-year implementation of an EHR. The wide range of these figures and the history of failed attempts at implementing tools such as CPOE have discouraged hospitals with limited funds from implementing EHRs. Another anticipated barrier to the adoption of EHRs is the tight time frame recently stipulated for implementation by the federal government in the HITECH Act section of the stimulus bill. The bill states that physicians and hospitals must demonstrate meaningful use of a certified EHR in order to receive financial incentives, starting in 2011. These two terms, meaningful use and certified, have yet to be defined. The determination of these definitions will require that the two committees responsible for defining them, the Health Information Policy Committee and the Health Information Standards Committee, be established. Once the terms are defined, vendors will be required to implement any changes required to meet the standards, including interoperability between systems. It is questionable whether any organization without some kind of an EHR system already in place will meet the initial timeline.
Given the difficulty of meeting the EHR implementation deadlines specified in the HITECH Act, it seems even less likely that providers will have the time and resources needed to bring evidence-based guidelines to bear in their EHR strategy. Thus we are presented with a catch-22: EHRs may be necessary to bring about the systemic movement toward evidence-based medicine, yet the pace at which EHRs have been mandated may not allow for the inclusion of evidence-based medicine in their implementation. Will a new wave of alert fatigue undermine the good intentions of the HITECH Act?
The barriers are high, but the payoff could be significant. EHRs are not merely a delivery mechanism for guidelines—they are also potentially a valuable source of data that can provide new information about quality outcomes and practice styles, and even result in new and improved guidelines. EHRs can help identify inconsistencies in utilization of care that compromise quality and they can help standardize care and minimize quality disparities. In this manner, EHRs can empower a research feedback loop that helps turn American healthcare into a self-improving system.
Of course, there is a catch. The research potential posed by EHRs is countered by concerns over patient privacy. Despite the presence of HIPAA, there remain questions over how new entrants like Google and Microsoft will be regulated. And as people gravitate toward digital health records, the potential volume and severity of medical identity theft increases.
A practical concern also exists: How do we make all these systems interoperable? How do we avoid creating a kind of technical Tower of Babel that reinforces the existing information silos?
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