Creation of a Longitudinal Legal Data Set to Support Legal Epidemiology Studies of Mental Health Insurance Legislation.

ABSTRACT

OBJECTIVE: This article describes policy surveillance methodology used to track changes in the comprehensiveness of state mental health insurance laws over 23 years, resulting in a data set that supports legal epidemiology studies measuring effects of these laws on mental health outcomes. METHODS: Structured policy surveillance methods, including a coding protocol, blind coding of laws in 10% of states, and consensus meetings, were used to track changes in state laws from 1997 through 2019-2020. The legal database Westlaw was used to identify relevant statutes. The legal coding instrument included six questions across four themes parity, mandated coverage, definitions of mental health conditions, and enforcement-compliance. Points (range 0-7) were assigned to reflect the laws' comprehensiveness and aid interpretation of changes over time. RESULTS: The search resulted in 147 coding time periods across 51 jurisdictions (50 states, District of Columbia). Intercoder consensus rates increased from 89% to 100% in the final round of blinded duplicate coding. Since 1997, average comprehensiveness scores increased from 1.31 to 3.82. In 1997, 41% of jurisdictions had a parity law, 28% mandated coverage, 31% defined mental health conditions, and 8% required state agency enforcement. In 2019-2020, 94% of jurisdictions had a parity law, 63% mandated coverage, 75% defined mental health conditions, and 29% required state enforcement efforts. CONCLUSIONS: Comprehensiveness of state mental health insurance laws increased from 1997 through 2019-2020. The State Mental Health Insurance Laws Dataset will enable evaluation research on effects of comprehensive legislation and cumulative impact.