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Learn how AI can help HCOs to accelerate patient access to approved treatment and reduce administrative strain. Discover how AI can help to automatically determine if PA is required, identify plan-specific requirements, surface necessary patient data, and identify and approve requests that are highly likely to be accepted.

Automatically ingest data from dozens of health data sources including...

Electronic Health Records

EHR data with comprehensive patient histories of vital signs and symptoms, problem lists and chief complaints, tests results, diagnoses and procedures, and prescriptions.

e-Prescribing Data

Data from electronic prescriptions detailing key information about medications, dosage, patient instructions for frequency and timing, and available refills.

Medical Claims

Data extracted from health insurance medical claims with details about dates and place of service, diagnosis codes, key procedures, use of medical equipment, and provider specialties.

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ClosedLoop generates explainable predictions using

thousands of auto-generated, clinically relevant contributing factors

Andrea Anderson
77-Year-Old Female
Likelihood of prior authorization approval for alkylating agent prescription
Risk Score Percentile
Impact on Risk  |  Contributing Factor
+27% | Diagnosis of Follicular Non-Hodgkin Lymphoma (12M)
Aug 2020
+23% | e-Rx for R-CHOP
Jun 2018
+17% | Procedure for Radiation Therapy (2)
Mar 2018
+11% | Procedure for Lymph Node Biopsy (12M)
Aug 2020

What Is Prior Authorization?

What exactly is prior authorization? Is it a useful process for ensuring appropriate healthcare or a morass of red tape that impedes care and undermines health? The answer depends on who you ask.

30% of physicians surveyed by the American Medical Association reported that prior authorization (PA) has led to a serious adverse event for a patient in their care.¹ 94% state it delays access to necessary care, and an overwhelming majority perceive the process to have a negative impact on patient health outcomes. PA requests are also extremely time-consuming; physicians and their staff report spending an average of two business days each week completing requests.¹

Payers contend that PA is extremely beneficial despite provider complaints. In a recent survey conducted by America’s Health Insurance Plans, 98% of plans surveyed reported that PA improves the quality of care and provides support for evidence-based treatment.² 91% also reported using PA to ensure patient safety, and 79% report that it lowers healthcare spending. However, payers also grapple with the associated administrative burdens. 

Why It Matters

PA was designed to act as a patient-safety and cost-saving measure for payers to ensure appropriate provider utilization management, but the massive administrative burden is taxing for both parties. Administrative PA processes have been estimated to contribute as much as $25 billion annually to total healthcare costs and can significantly delay care for patients.³ 

The PA request process is complex, laborious, and not standardized. Payer requirements are varied, change frequently, and may even differ across health plans offered by the same payer. Because clinical workflows and billing systems are rarely integrated, providers must manually retrieve pertinent information from a variety of data sources and transfer it into authorization requests. This process is prone to human error, lacks coding consistency, requires clinical staff to manually review individual plan specifications, and frequently takes place over multiple phone calls and faxes that strip away the structure of a patient’s medical record. 

AI Presents an Opportunity

Fortunately, Healthcare organizations (HCOs) can leverage AI to streamline PA. With predictive analytics, providers can easily determine if PA is required and quickly surface the necessary information. Payers can exploit AI-based models to identify and automatically approve requests that are highly likely to be approved—substantially decreasing the need for manual reviews. Ultimately, HCOs can leverage AI to dramatically reduce administrative burden, curb costs, and accelerate patient access to approved treatment options.

Did You Know...

  • 21% of physicians report that PA delays have led to an avoidable hospitalization¹
  • 12% of 182 million prior authorizations were fully electronic in 2018³
  • Roughly 50% of requests in 2018 were conducted entirely via faxes and phone calls³
  • $25 billion in costs has been attributed to administrative PA processes³
Citations & Footnotes

1. “2020 AMA prior authorization (PA) physician survey.” American Medical Association, https://www.ama-assn.org/system/files/2021-04/prior-authorization-survey.pdf. Accessed 6 May 2021.

2. “Key Results of Industry Survey on Prior Authorization.” America’s Health Insurance Plans, https://www.ahip.org/wp-content/uploads/Prior-Authorization-Survey-Results.pdf. Accessed 6 May 2021.

3. “Moving Forward: Building Momentum for End-to-End Automation of the Prior Authorization Process.” CAQH Core, https://www.caqh.org/sites/default/files/core/white-paper/CAQH-CORE-Automating-Prior-Authorization.pdf. Accessed 6 May 2021.

ClosedLoop is an exciting and important partner in our strategy to develop timely predictive insights through operationalized AI solutions that will drive member engagement and better health outcomes.

Pat Wang
President & CEO, Healthfirst

Our partnership with ClosedLoop adds the depth of AI to more accurately identify those patients who are most likely to benefit from our primary care interventions as well to evaluate these interventions and make more relevant and timely modifications to improve their effectiveness.

David Klebonis
Chief Operating Officer, PBACO

We are extremely impressed with the predictive modeling capabilities the ClosedLoop platform has delivered. The ClosedLoop team has exceeded all defined goals and benchmarks set to date and we anticipate a substantial return on our investment as these predictions are operationally deployed.

Cheryl Lulias
President & Executive Director, MHN

We’re able to store and operationalize analytics directly from ClosedLoop. That’s driving real value—it’s accelerated the implementation of key insights into clinical workflows and it allows us to more easily account for all of the different factors that influence intervention decisions.

Christer Johnson
Chief Analytics Officer, Healthfirst

At SWHR, our patient-centered network is committed to innovative care models that are value-based, high-quality, and data-driven. Because of our partnership with ClosedLoop, we’re better able to identify and act on the most impactful opportunities for our physician partners to improve patient results and reduce unnecessary costs.

Dr. Jason Fish
Chief Medical Officer & SVP, Southwestern Health Resources

We compared the ClosedLoop predicted spend to the spend predicted by a leading rules-based risk prediction engine and found that 75% of the time ClosedLoop was closer, and in most cases significantly closer, to the actual spend.

Phillip Bruns
Chief Technology Officer, CareATC

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