Use of Health Care Claims Data to Study Patients with Ophthalmologic Conditions

Abstract

Objective To describe what information is or is not included in health care claims data, provide an overview of the main advantages and limitations of performing analyses using health care claims data, and offer general guidance on how to report and interpret findings of ophthalmology-related claims data analyses. Design Systematic review. Participants Not applicable. Methods A literature review and synthesis of methods for claims-based data analyses. Main Outcome Measures Not applicable. Results Some advantages of using claims data for analyses include large, diverse sample sizes, longitudinal follow-up, lack of selection bias, and potential for complex, multivariable modeling. The disadvantages include (a) the inherent limitations of claims data, such as incomplete, inaccurate, or missing data, or the lack of specific billing codes for some conditions; and (b) the inability, in some circumstances, to adequately evaluate the appropriateness of care. In general, reports of claims data analyses should include clear descriptions of the following methodological elements: the data source, the inclusion and exclusion criteria, the specific billing codes used, and the potential confounding factors incorporated in the multivariable models. Conclusions The use of claims data for research is expected to increase with the enhanced availability of data from Medicare and other sources. The use of claims data to evaluate resource use and efficiency and to determine the basis for supplementary payment methods for physicians is anticipated. Thus, it will be increasingly important for eye care providers to use accurate and descriptive codes for billing. Adherence to general guidance on the reporting of claims data analyses, as outlined in this article, is important to enhance the credibility and applicability of findings. Guidance on optimal ways to conduct and report ophthalmology-related investigations using claims data will likely continue to evolve as health services researchers refine the metrics to analyze large administrative data sets.

The Association Between Sociodemographic Factors, Common Systemic Diseases, and Keratoconus

“…As such, the findings may have more generalizability relative to single center studies or those from academic centers that may be a biased sample of those with more severe disease. 44 In addition, claims data does not rely on patient self-report of medical conditions such as KCN. Others have demonstrated patient self-report is less reliable compared with diagnoses made by medical professionals.…”

“…First, without access to clinical records, we cannot confirm the presence of KCN among those identified as cases or absence of disease in controls. 44 That said, a study by Center for Medicare and Medicaid Services found the specialty of ophthalmology has one of the lowest rates of improper coding of ocular diagnoses. 46 Moreover, to help ensure that those who had been coded with KCN did indeed have the disease we required a confirmatory diagnosis on a separate visit.…”

Large Disparities in Receipt of Glaucoma Care between Enrollees in Medicaid and Those with Commercial Health Insurance

“…36 Claims data lack the detailed clinical information needed to determine the appropriateness of testing that was or was not performed. Likewise, we lacked information on eye care providers’ access to testing equipment to perform these tests or the cost of such equipment, which may have affected utilization.…”

Risk of venous thromboembolism occurrence among adults with selected autoimmune diseases: A study among a U.S. cohort of commercial insurance enrollees

“…However, studies using secondary data, including administrative databases such as MarketScan are not without merit. Administrative databases, including MarketScan data have been used for numerous research studies published in peer-reviewed journals [34,35]. Advantages of such databases include having multiple years of data for diverse populations that include demographic, health care related, and other information [34,35].…”

“…Administrative databases, including MarketScan data have been used for numerous research studies published in peer-reviewed journals [34,35]. Advantages of such databases include having multiple years of data for diverse populations that include demographic, health care related, and other information [34,35]. A number of reports on ICD-9-CM -coded information for VTE diagnoses in selected inpatient data sources have suggested positive predictive values of approximately 65%–95% for several of the codes used in our study to identify VTE diagnoses when present in inpatient hospital discharges [31,32].…”