Maximizing financial performance with intelligent clinical decision support

Joe Guerriero, Senior Vice President of MDGuidelines, Reed Group

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

Wasteful spending attributed to overtreatment amounts to a staggering $158-to-$226 billion annually.[1] With numbers like these, it’s not surprising that minimizing clinical care variation and controlling avoidable utilization are among the top five concerns for hospital and health system executives.[2] 

When a patient’s health is not well managed or it takes longer to heal from an illness or injury, not only does the patient suffer, but the costs shared by the patient, providers, employers and payers increase as well. In a value-based care environment, the more responsibility providers assume for the quality and cost of care, the more critical it becomes to be able to manage financial risk while improving health outcomes.

Following practice guidelines supported by medical evidence is widely proven as an effective way to achieve these goals – and could reduce U.S. healthcare costs by $90-to-$110 billion annually.[3] By leveraging intelligent clinical decision support tools at the point of care, providers can consistently employ the most effective treatments to return patients to health safely and efficiently. Once implemented, healthcare organizations can gain substantial benefits from more effective resource utilization coupled with better clinical outcomes.

Yet, many providers lack reliable, evidence-based tools at the point of care to support consistent and effective treatment. When providers don’t have access to the information and tools they need during the patient encounter, waste such as redundant or unnecessary tests and treatments, extra visits or overprescribing of medications, is often the result. By some estimates, 30 percent of all Medicare clinical care spending is actually unnecessary or even harmful and could be avoided altogether.[4]

Seeking to change such statistics, the Centers for Medicare and Medicaid Services’ (CMS) bundled payment program incentivizes provid­ers to better coordinate care, avoid unnecessary services and improve pa­tient outcomes. For example, under its comprehensive care for joint replacement (CCJR) model, participating hospitals will receive a bundled payment for the inpatient stay and ninety days of post-acute care.[5]

With a focus on delivering quality outcomes at a fixed cost, risk-bearing organizations can support providers with tools at the point of care that combine clinical content, treatment guidelines, predictive modeling and duration tables. When guidelines and supporting information are integrated into electronic health record (EHR) systems and made part of the clinical workflow, providers can access valuable decision support in a way that is efficient yet does not disrupt the patient encounter.

Among these tools are evidence-based treatment guidelines that map out the most effective and efficient course of treatment and use of resources. The addition of physiological duration tables helps providers and patients discuss reliable estimates for how long it may take to return to health and normal activity levels. Further, predictive data modeling helps show how demographic variables such age, gender, geographic location and underlying co-morbid conditions (e.g., diabetes or heart disease) can affect the expected timeframe within which a patient may return to productivity. This powerful combination of guidelines, duration tables and data modeling enables providers to better coordinate care around the final goal of returning patients to health, all while taking into account each patient’s unique attributes and circumstances.

When providers across organizations consistently follow treatment guidelines, it results in better outcomes as well as decreased resource utilization, which translates directly into savings in medical costs. By supporting physicians with evidence-based tools at the point-of-care, risk-bearing organizations can eliminate costly variations in care and achieve the Triple Aim with better outcomes, lower costs and a more positive patient experiences.

In part three of this article series, we will consider the benefits of using intelligent clinical decision support as a means to engage patients more fully in their own care.

[1] “Health Policy Brief: Reducing Waste in Health Care,” Health Affairs, December 13, 2012.

[2]Health System Executives’ Primary Concerns Shift to Focus on Consumers,” Beckers Hospital Review, April 4, 2016.

[3]The Big Data Revolution in Health Care: Accelerating Value and Innovation,” January 2013.

[4] “Health Policy Brief: Reducing Waste in Health Care,” Health Affairs, December 13, 2012.

[5]Bundled Payments for Care Improvement Initiative,” Health Affairs Health Policy Brief. Robert Wood Johnson Foundation, November 23, 2015.

accountable care organizations, ACOs, clinical decision support, duration tables, predictive modeling, Reed Group, Triple Aim


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