One of the most studied effects of the Affordable Care Act has been the growth of narrow provider networks in marketplace plans. Limiting network size has proven to be an efficient cost-cutting method for insurers but compromises the accessibility of care for millions of Americans. Medicaid beneficiaries, who represent the poorest populations and face particularly high health risks, have notoriously suffered from insufficient access to care due to provider shortages and low provider reimbursement rates.
The government ensures access to care by measuring network adequacy, the ability of a health plan to provide timely access to in-network physicians, hospitals, and specialists. Despite a regulatory push at the federal level to apply more rigorous network adequacy standards to Medicaid managed care and marketplace plans, state governments are ultimately responsible for setting their own standards and ensuring compliance to them. This has led to a broad range of standards with varying levels of oversight and complexity across state governments and among payer groups.
In California, the DMHC is responsible for monitoring the compliance of health plans serving over 25 million people in California, including Medicaid managed care plans. California has one of the most complex and rigorous standards established for ensuring network adequacy as dictated by the Knox-Keene Act. Many of these standards, such as ensuring geographic access, require computation at a large scale and expertise in geographic information systems (GIS). One particularly complex component is measuring a plan’s compliance with the state’s time and distance standards, which mandate that all residents of a particular service area must have access to an in-network primary care physician (PCP) within 15 miles or 30 minutes of their home or work. The challenge is identifying the number and location of all potential enrollees to adequately represent population distribution and density without incurring an unworkable computing cost, while also maintaining transparency for both insurance plans and the public.
We worked with the DMHC to develop an improved statewide population model as well as an easy-to-use web application to visualize and export necessary data elements for subsequent analysis. This application used a statistical model based on postal delivery route data to provide highly granular population distribution information by ZIP code. Access to a more accurate data model helps DMHC ensure that people in remote regions are not ignored and that health plans operating in the state are providing their members with sufficient coverage. In addition to providing an enhanced population model, we evaluated alternative GIS software options for improving the accuracy of their drive-time and drive-distance analysis at scale.
DMHC now has improved high-resolution representative population data for their calculations, along with a path forward for a redesign of the technical aspects of their network adequacy regulation process.