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CDS and Population Health

The role of rules-based clinical decision support in population health management.

An estimated 40 percent of all deaths result from diseases and behaviors that can be prevented and at a significantly lower cost. The incremental growth in the senior population complicates things further.

The Congressional Budget Office estimates that approximately 10,000 people are now enrolling for Medicare every day. Unfortunately, our medical workforce cannot keep up with this workload.

In a recent study, the American Association of Medical Colleges estimated that by 2025, the market demand for physicians will fall short by 46,100 to 90,400, including a 12,500 to 31,100 shortage in primary care specialists. Thus, improving outcomes and patient engagement, the two critical elements of the triple aim that rest on physician' shoulders, are becoming increasingly difficult to achieve.

Meanwhile, the healthcare industry is in a state of constant flux. Although, federal mandates for meaningful use have improved EHR adoption, there remains a significant gap in the effective utilization of all this available health data and it is costing us dearly.

Organizations are starting to explore ways to leverage electronic patient data for improving quality and adapting to the environmental shift from procedure-centric to patient-centric care. Population Health Management (PHM) is being increasingly utilized as a key strategy towards a multi-faceted approach for identifying problems early, matching patients to appropriate care teams, managing transitions and follow-up of care. However, the critical first step is the identification of patient populations that would most likely benefit from planned health and behavioral interventions.

Advanced clinical decision support (CDS) can play a pivotal role in achieving this goal. Rule based CDS can screen patients using evidence based criteria and reliably deliver the appropriate medical advice to the point of care, all integrated with the clinician workflow for optimal efficiency.

SEE ALSO: CDS and CDI Come of Age

Patient Data and Rules-Based Decision Support

Post incentivized meaningful use, physician access to updated evidence and information has significantly increased. The digital age has helped to speed the discovery rate of clinical information, adding to an already-vast volume that doubles every 3.5 years.

Improving population health outcomes begins with the actionable, patient-specific use of this up-to-date knowledge; however, few facilities have the ability to provide physicians with the non-disruptive support necessary for such an initiative. The solution lies within the patient data found in current clinical systems. CDS rules, consisting of several smart algorithms, can efficiently harness and convert vast medical knowledge into smaller, usable bits of information and run on live patient data in real time.

By running patient data against a series of evidence-based rules customized for a patient population and based on appropriate clinical scenarios, advanced CDS can generate real-time alerts and treatment advice. This information can be relayed within an electronic health record or directed via mobile apps to clinicians at the point of care. This rules-based CDS can be adjusted for patient specific factors, such as age, weight, vitals, medical conditions, and ongoing medications, to support the decision making process, thereby improving the quality of care while helping clinicians manage larger patient populations.

To ensure that the advice is accurate and received in a timely manner, the decision support systems must be able to readily access the patient data in real-time. Much like the volume of medical knowledge, the amount of patient data available to clinicians has grown rapidly in recent years. However, the expansion of this data throughout disparate clinical systems, such as EHRs, labs and pharmacy, presents perhaps the largest barrier to CDS innovation.

Bridging the Divide

Most EHRs today are not designed for population health management. Differences in terminologies within health IT platforms restrict the free exchange of information and hinder the availability of data for smart population health management. This lack of interoperability can reduce the accuracy of real-time alerting and point-of-care advice. Central repositories for health information, also known as Health Information Exchanges (HIEs), have been created to serve, store and share population-wide information for more accurate and representative clinical statistics, billing and clinical management.

Several third party tools have also made significant headway in bridging the digital divide. Through parsing data, harmonizing information, and normalizing non-discrete bits of information that stem from disparate sources, rules-based CDS can disrupt the status quo by giving health care organizations the ability to create their own clinical registries and contribute to inter and intra organizational HIEs to monitor quality.

Through contributing to population registries containing actionable and sharable information, rules-based CDS can help facilitate innovations and improvements in healthcare. However, the rules governing the delivery of medical evidence and advice must be customized based on provider-specific, patient-specific and clinical-scenario specific information, such as common comorbidities and medications. Furthermore, to sustain outcomes after the initial integration and build on success, decision support technology must be able to evolve with patient populations and new medical discoveries-a necessary feature unavailable in out-of-the-box tools built into EHRs.

Several innovations in health IT are underway and being designed to help healthcare providers adapt to the changing industry environment and pull clinical value from previous meaningful-use investments. The integration of tools, like rule-based CDS, fosters sustainable patient outcomes while supporting health goals in the digital age of medicine.

Sharad Manaktala, MD, PhD, is the Senior Scientist of Clinical Informatics for Wolters Kluwer's Innovation Lab. He can be reached at

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