Decision support systems evolving to better serve docs and patients

Clinical decision support systems represent a growing market that eventually will be more than a simple capability tacked onto electronic health records systems.

Clinical decision support systems represent a growing market that eventually will be more than a simple capability tacked onto electronic health records systems.

These systems are evolving beyond a selection of point solutions to a platform on which other health IT functions can be integrated, according to a new report from Frost & Sullivan. This gives the opportunity to accelerate the progress of value-based reimbursements, connected health and population health management, it contends.

Clinical decision support is a broad concept with many definitions depending on the perspective and role of the user. The market includes clinical, financial and workflow tools that provide data to physicians at the point of care. The data also includes information that can help a doctor understand prescription and patient adherence.

Insurers use clinical decision support as a source of content and an instrument to cut costs by ensuring patient care conforms to regulatory, treatment and administrative guidelines.

However, Frost & Sullivan notes, healthcare providers must be cautious in the application of clinical decision support solutions to the clinical workflow as the technology, implemented or interpreted incorrectly, can contribute to physician burnout and inefficient processes.

That said, clinical decision support is seen as a necessary facilitator of compliance activities because regulatory environments are complex and impossible to administer without automated assistance.

Mike Jude, research manager for digital health at Frost & Sullivan, sees potential for clinical decision support systems to move further in aiding providers because of the opportunity to present health data at the point of care, and he is bullish that this part of the market will expand.

Jude believes clinical decision support can address a multiple of healthcare needs and over time will incorporate a wider range of capabilities, such as intersecting various data sets to be able to show doctors the pharmaceutical background of patients. He also sees the opportunity for the systems to incorporate most of the data coming out of electronic health records because decision support systems have better interfaces than EHRs.

In the Frost & Sullivan report, Jude and other authors give five reasons why healthcare providers need to seriously consider the use of these systems.
  • Clinical workflow is a production process that ideally takes in ill patients as an input and discharges well patients as an output. In the process it consumers resources in the form of clinician and physician time and expertise, as well as use of diagnostic equipment and pharmaceuticals.
  • Digital health technology that increases the throughput of this process adds to its efficiency and efficacy while technology that simply adds cost or slows the process detracts from its efficiency and efficacy.
  • The challenge is to determine whether decision support solutions can measurably impact the clinical workflow in a positive way. These systems can be quantitatively evaluated in terms of process efficiency improvements.
  • However, clinical decision support should not be evaluated simply on process efficiency. Critical to such analysis is the impact that these solutions have on clinical personnel.
  • Such an analysis, then, depends on both quantitative as well as qualitative measures, which implies the use of decision analysis to address the decision support approach.

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