Precision Utilization Management: Meeting Patients Where They Are



September 22, 2020

Providers view prior authorization as a manual, burdensome, and laborious process, mostly because of process missteps such as lack of clinical data integration, inconsistency in data exchange standards, and differing policies among payers. According to a recent American Medical Association survey, handling the surging prior authorization requests translates into a “high” or “extremely high” burden for 75% of physician respondents. And 90% of surveyed physicians reported that the PA process delays patient access to necessary care. An important front-line negative impact of this time-consuming and often ineffective process is that patients feel the brunt of the delays and are disgruntled due to the endless appeals before receiving the needed care.

The rapid maturity in cognitive automation and predictive analytics supported by robust data sources presents an opportunity for payers to evolve traditional utilization management (UM) processes into an intelligent authorization process. What about taking a surgeon’s scalpel to the process, with a more targeted, precision UM? This more precise UM is a proactive data-driven program that uses the power of predictive analytics to provide a prospective view into the downstream needs of the patient, thereby reducing unnecessary repetition of authorization—every step of the way.

The precision UM method not only reduces burden on providers but leads to reduced provider abrasion, enhanced member satisfaction, and decreased administrative resources and costs in managing the authorization process.

Four critical elements of precision UM meet the patients where they are in their care journey:

  • Precision analytics: Member analytics looks at member behavior, historical data on compliance with preventive/recommended treatment, comorbidities, and lifestyle factors to accurately predict duration and level-of-care needs. These analytics help provide a prospective approval for the entire course of treatment. For example, a request for varicose vein ablation can be automated through predictive analytics if the historical claims and clinical data show a patient’s lack of improvement with conservative compression therapy and abnormal lab-based venous varicosity. Other lifestyle factors—such as comorbidities or a ground-floor versus an upstairs bedroom—also factor into what additional services (physical therapy or home health) need to be authorized.
  • Provider scorecard: The provider scorecard comprises analytics based on compliance to process fraud, waste, and abuse, as well as outcome measures such as accurate and timely information submission. This provides the ability to audit on the back end for continued gold-card status across UM needs and can help drive dynamic changes to the automated authorizations for stringent cost and quality outcomes.
  • Intelligent automation of authorizations against clinical guidelines: Using machine learning tools enabled by natural language processing functionality, this innovation can reduce review time by 30-40% and optimize the approval to denial ratio by 20%.
  • Care management and care coaching to holistically address the member for better lifecycle outcomes: Upon identification of key parameters driving utilization needs, a holistic care transition and care management program can help members seek only necessary and targeted care needs that will maximize outcomes. Addressing social determinants such as two-story housing when the member has a walker or lack of transport to attend outpatient therapy can reduce unnecessary utilization, optimize recovery timelines, and reduce readmission to hospitalization.

To provide the precision focus above, healthcare organizations are looking for BPO partners with end to-end-expertise and clinical resources to scale support with intelligent tools and workflows to reduce cost and improve the effectiveness of UM programs. These BPOs have the analytics to deliver superior insights with client data, including deep dives to determine root causes of inaccuracies and process inefficiencies. Adoption of precision UM, electronic requests, and interoperable data exchange can significantly improve the payer provider collaboration. Additionally, providers should also consider clinical data audit using NLP solutions, which would increase the accuracy of documentation required for the UM processes.

Rather than expending time and resources to hire or train internal personnel, a skilled BPO organization can bring knowledge and skills in these areas to an organization immediately, with limited lead time. Ultimately, the goal is to develop a partnership that brings precision-UM-focused talent, best practices, and resources to the table.