The Next Generation of Intelligent Decision Support


The Next Generation of Intelligent Decision Support

By Carm Huntress, Founder, Featured on HIStalk’s Readers Write

Research has repeatedly shown that Americans trust doctors more than any other professionals they interact with. But what happens when healthcare providers don’t have reliable data at their fingertips? They may prescribe medications that are not covered under the patient’s insurance. They may send the patient to a lab that is out of network. Or they may order care that is costly and requires authorization from the patient’s health plan. In the blink of an eye, trust in providers can be broken.

What’s needed to maintain trust in our healthcare providers is better data at the point of care. New intelligent systems are necessary that can deliver comprehensive, curated, actionable data to provider workflows so that they can select the most clinically relevant, affordable care options for their patients.

Prescription Data Intelligence

Real-time prescription benefit (RTPB)—one type of decision-support tool that brings pharmacy coverage data to EHR workflows—has been adopted by thousands of health systems, hospitals, and clinics across the country. However, some RTPB solutions leverage outdated or static files that are not exact. This has caused providers to lose trust in these tools and has slowed progress toward transparency.

We can no longer accept inferior data and inaccurate processes that prevent us from delivering cost-effective care. Patients and providers deserve better.

By working in lockstep, EHRs, payers, providers, and RTPB vendors can deliver prescription data that is normalized, actionable, and valuable. Some examples of how intelligence can be used to enhance this type of point-of-care decision support include:

  • Real-time delivery. Data displayed must be updated in real time, showing patient-specific cost and coverage information that matches what the claims system would display. This way, patients are not surprised when the find out the actual cost of their care.
  • Quantity translations. Providers often enter medication quantities in simple terms (i.e. inhalers, pills, bottles), but vendors must be able to translate these quantities into those that the payer/PBM can bill for (i.e. mL, grams). Otherwise, no prices will be returned.
  • Better data mapping. Providers are often unaware of the drug codes required to identify each medication prescribed, but in order to receive an accurate price, solutions must automatically swap inapplicable codes and convert codes to display relevant information.
  • Smart filtering. In many cases, solutions display any covered care option. Instead of creating more EHR noise, it is essential that vendors suppress irrelevant alternatives and ensure only meaningful options are shown.

It is the combination of these intelligent features that can create a truly exceptional prescribing experience and drive trust in decision support tools. By augmenting raw patient data with a next-gen intelligence layer, effective decision-making can become the norm.

What’s Next?

Delivering prescription data is just the beginning. Providers are often requesting—and the industry is quickly moving toward—the transmission of medical benefit data to allow for a more complete picture of patient coverage. With both pharmacy and medical benefit data available, providers can view real-time insights on patient health needs and deliver care in new, meaningful ways.

Technology vendors can no longer meet the minimum delivery requirements for patient coverage and cost data. If they do, providers will ignore data presented to them, and patients will lose trust in their caregivers. However, vendors are leveraging advanced logic to deliver real-time data that is individualized to the patient and intuitive technologies to enable better decisions at the point-of-care. Connecting intelligent systems into payer, PBM, and EHR ordering process allows for visibility into valuable information when it matters most, reducing costs, improving workflows, and getting patients the right care the first time.

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