In preparing a regulation database from published sources, we discovered that recognizes sources of information about insurance regulation (Institute for Health Policy Solutions, 1999; Health Policy Tracking Service, 1996-1998; and Blue Cross and Blue Shield Association, 1996-99) occasionally disagree. With funding from the Robert Wood Johnson Foundation and the National Association of Insurance Commissioners, we launched a 50-state survey to reconcile these differences.
The survey entailed calling each state department of insurance to obtain the name of the correct person to respond to questions about regulation, sending to each state department of insurance a customized 7-page survey instrument restating where available sources had agreed about their regulation in the small-group and individual health insurance markets. We asked each state to confirm, correct and complete the available information, especially clarifying dates of implementation versus enactment. We then followed up with each respondent in an hour-long telephone interview to review their responses.
The response rate to this effort was excellent (48 states and the District of Columbia responded and were interviewed). In a number of cases we discovered that, while all published sources agreed, they were wrong (for example, all published sources reflected the date of enactment of a specific provision, not implementation). In these cases, we obtained and reviewed the state’s insurance statute for confirmation. For two states, where we were unable to obtain either a survey response or, with reasonable effort, the state’s relevant insurance statute, we used published information to complete their regulatory profile.
From this information, we developed measures of regulation, using categorical variables where necessary (for example, for guaranteed issue or renewal), but developing continuous measures of regulation wherever possible (specifically, for age, health and composite rate bands; and for limits on preexisting condition exclusions). We measure rate regulation as the inverse of the ratio of the maximum allowable rate to the minimum allowable rate in regulation. Thus, we rate regulation values for each state in each year that varies between 1 (the rate factor is prohibited, in effect allowing only 1:1 rating on that factor) and, in the limiting case, zero (1/(∞:1). We measured limits on preexisting condition exclusions as the maximum number of months that insurers may exclude coverage for a preexisting condition.9
By developing continuous measures for these variables, we are able to avoid the problems of multicollinearity that have forced other researchers to bundle heterogenous reform measures and search for differences related to the presence or absence of regulation, without regard to differences the variety and restrictiveness of the states’ regulation. Instead, our analysis examines the impacts of specific regulatory measures (e.g., health rate bands separately from age rate bands), and also accounts for stricter limits on pricing and preexisting condition exclusions in some states compared to others. Descriptive statistics for all the market structure, regulation and control variables are provided in Tables 9 and 10.