Of course, it's not perfect. Even if we have the data, there's still a resource gap. For instance, physicians can't prescribe transportation assistance. We need a system that collects this data and incentivizes addressing these social factors. Thankfully, the healthcare industry is focusing on innovation and equity. By using AI technology to capture and analyze SDOH data on a granular level, physicians and health plans can tailor interventions to a patient's needs. However, challenges persist, including prior authorization delays, the lack of reimbursement for non-medical services, and the strain on physicians' time.
Harnessing AI for health equity
Prior authorization, a process requiring approval before certain medical services are delivered, can be a double-edged sword. While it helps control costs, it can also create administrative burdens for physicians and delays for patients. Despite challenges, innovation in healthcare offers hope. I fully support solutions used to solidify health equity, including using intelligent prior authorization as a catalyst for building a more equitable healthcare system. When used extensively, AI and machine learning technologies have the potential to analyze SDOH data and create personalized care pathways. These pathways consider clinical and social factors, ensuring patients receive tailored interventions regardless of background.
Intelligent prior authorization has the potential to be a powerful tool for promoting health equity by empowering physicians, streamlining processes, and personalizing care. Here's a closer look at three ways the healthcare system can achieve this.
1. Episodic authorizations for streamlined care:
Prior authorization often requires separate approvals for each step in a treatment plan, creating a bureaucratic maze, especially for complex conditions. AI and machine learning can analyze the entire treatment plan and recommend an "episodic authorization" that covers all the necessary services in a single step. This streamlined process is particularly helpful for underserved communities who may already face challenges accessing healthcare. Additionally, reduced administrative burden allows physicians to focus more on patient care, and patients experience fewer delays in receiving essential treatments.
2. Empowering physicians with real-time clinical guidance:
When a prior authorization is submitted, AI and machine learning technology can instantly analyze the patient's medical history, condition, and evidence-based guidelines. Instead of a simple approval or denial, the doctor receives a real-time clinical "nudge" that suggests alternative treatment options, highlights additional information needed to complete the request, or even recommends collaboration with specialists for complex cases. This two-way communication assists physicians to make informed decisions, ensures patients receive optimal care tailored to their needs, and reduces denials due to incomplete or missing information.
