Survey data were not available for the Private Payers Study, so the identification of potentially disabled people was based primarily on information available in the insurance claims databases contributed by the two participating large employers. Claims data contain a wealth of information on individual utilization of health care services, expenditures, diagnosis codes, and procedure codes that can be used as indicators of potential disability status. Although there is much literature focusing on the health care utilization and expenditures of Medicaid and Medicare beneficiaries, the use of claims data to study the health care utilization of people who may be disabled is much more limited.
Previous studies of the health care utilization of Medicaid and Medicare beneficiaries with disabilities have generally focused on program eligibility status (e.g., Medicare enrollees under age 65 or Supplemental Security Income (SSI) beneficiaries) as the indicator of disability. Recently, however, studies using Medicaid claims data have attempted to identify disabled people using criteria beyond program status alone (e.g., Crown et al., 1998a, 1998b; Kronick, et al., 1995). These studies focused on diagnosis codes and utilization criteria for identifying people with disabilities. Diagnosis code and utilization criteria are particularly appropriate for the Private Payers Study because these criteria can be used to identify people with potentially disabling chronic conditions from private health insurance claims, where program eligibility criteria, such as SSI or Social Security Disability Insurance (SSDI) status, are lacking.
The use of claims data for studying the health care utilization of potentially disabled people has several advantages. First, it enables researchers to study very large samples, and sometimes even entire populations, rather than relatively small samples of populations. This can be important when focusing upon certain types of disability which may be very rare. Second, health care claims data are not subject to self-reporting biases on the part of individuals (although they may be subject to other reliability problems). Third, and most importantly, claims data provide the opportunity of studying the total pattern of health services and expenditures of people who may be disabled.
The use of claims data for studying the health care utilization of disabled people does have limitations. For example, diagnosis codes may not always indicate the nature of a person's disability (e.g., an individual with severe mental retardation might have an office visit for an inner ear infection, with the former not noted as a diagnosis on the claim). In some situations, it is possible to address this problem by linking with other data sets. For example, by linking Medicaid data for SSI recipients with Social Security data on impairment codes, it is often possible to identify type of disability for many individuals even though it is not indicated in the claims. On the other hand, this linkage solution may not be feasible for employer health insurance data due to confidentiality restrictions and because very few enrollees are covered by SSI or SSDI. Even so, one would expect to see severe disabilities reflected in diagnosis codes over a longer period of time, such as a year.
A second limitation of claims data is that they generally contain very limited socioeconomic or demographic information on the individuals represented in the claims. This can place limits on the range of policy questions that can be addressed. For example, information on race is not available in the two employer data sets used for the Private Payers Study. Studies of race-related differences in access to care or treatment patterns among disabled people are therefore precluded.
A third limitation relates to reporting practices used by diagnosis coders. Like survey respondents, clinicians may hesitate to report the existence of sensitive conditions, such as mental or emotional problems.
Finally, as noted earlier, insurance claims which denote the existence of a chronic condition generally cannot be used to estimate the degree of disability associated with that condition. Thus, for the Private Payers Study, we refer to the samples included in the empirical analyses as those having potentially disabling chronic conditions, rather than using the more definitive-sounding term, disabled.