Advancing value-based goals with intelligent clinical decision support

Joe Guerriero, Senior Vice President of MDGuidelines, Reed Group

(Editor’s Note: This article is part one of a three part series. Part two is published here. Part three is published here.)

How do you deliver on the promise of improved outcomes while still tightly managing costs? That’s a question that more than 700 ACOs face every day.[1] It’s also the same dilemma payers and employers have wrestled with for years, which is why it’s critical to learn from their approach. By leveraging both evidence-based guidelines and physiological duration tables, many employers have successfully returned individuals to health quickly and safely, all without wasting resources.

One key challenge, however, is that many physicians don’t have tools at the point of care to help them determine the safest, quickest path or the length of time it may take for a patient to heal and return to their normal lifestyle. As a result, there are tremendous variations in how providers manage specific conditions, injuries and illnesses. And these variations can have a negative impact on both patient outcomes and the bottom line. 

To address this challenge, ACOs can provide intelligent clinical decision support tools to providers at the point of care. With a combination of evidence-based clinical guidelines and physiological duration tables, physicians can better coordinate care around the final goal of returning patients to health, all while taking into account patients’ unique attributes and circumstances. Treatment planning can include personalization through predictive modeling based on factors like age, gender, geographic location, and underlying co-morbid conditions, such as diabetes or heart disease.

Having the ability to combine personalized recovery timeframes at the point of care facilitates an informed dialogue between doctor and patient. Patients benefit tremendously from understanding their expected path and timeframe for returning to their normal lifestyle and activity levels. From there, care and resources can be coordinated appropriately toward the goal of returning patients to active living as soon as possible, while managing setbacks if they arise.

From an organizational standpoint, the use of evidence-based treatment provides information needed to drive improvements across the organization that can enhance care and make processes more efficient. With the implementation of physiological duration guidelines, organizations have enormous opportunity to use data and advanced analytics to tackle inefficiency and waste, while fine-tuning best practices, for example:

  • Compare estimated and actual treatment durations to measure performance and identify areas for improvement;
  • Reveal and eliminate variations and inconsistencies in care and utilization;
  • Implement and assess best practices for diagnostic and treatment planning and management;
  • Identify cohorts of patients and conditions for proactive intervention and management; and
  • Offer education and training to help providers understand and adhere to evidence-based protocols and actively engage patients in their care.

When providers look at the patient’s needs holistically and provide personalized, coordinated care, they improve total patient health and well-being. What’s more, with intelligent clinical decision support at the point of care, ACOs can achieve the Triple Aim: Quality outcomes as clinicians manage the entire episode of care according to expected recovery timeframes, more cost-effective use of resources and better patient experiences as they return to health in a safe and timely manner.

In addition, organizations that demonstrate their ability to consistently deliver high quality outcomes using proven, evidence-based treatment and physiological duration guidelines will have a strong differentiator in their market that will help them attract new business and improve their bottom line.

In parts two and three of this article series, we will explore financial performance improvements in more detail and consider the benefits of using point-of-care tools as a means to engage patients more fully in their own care.

[1] Projected Growth of Accountable Care Organizations. Leavitt Partners. December 2015.

accountable care organizations, ACOs, analytics, clinical decision support, predictive modeling, Reed Group


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