LETTER
Utility and Limitations of Claims Data
Edwin D. Huff, PhD
15 June 1994 | Volume 120 Issue 12 | Pages 1049-1051
TO THE EDITOR:
Jollis and colleagues [1] draw conclusions regarding claims versus database discordance that extend beyond their data.
First, claims records and their corresponding comorbid diagnostic elements selected on the basis of associated coronary arteriography are not representative of all claims exclusive of coronary arteriography and their associated morbidities. One key reason is that approximately 75% of the indexed claims are accounted for by only three diagnostic-related groups (DRGs). Review of 2 fiscal years of Medicare claims representing 83 503 inpatient admissions in New Hampshire, of which 3173 included coronary arteriography, showed that the three main DRGs and their relative percentages of all medical and surgical cardiac patients (Medical Disease Category 5) were as follows: DRG 112, percutaneous procedures (25.6%); DRG 124, circulatory disorders other than acute myocardial infarction with cardiac catheterization and complex diagnosis (31.1%); and DRG 125, circulatory disorders other than acute myocardial infarction with cardiac catheterization without complex diagnosis (18.6%). Each different grouping has a distinct risk-related morbidity profile and expected outcome The relative mean hazard score representing the risk for mortality within 1 year of hospitalization for patients grouped in DRG 125 is significantly lower than that associated with DRG 124. Seventy-five percent of all principal diagnoses for DRG 125 are for chest pain, unspecified angina, or coronary atherosclerosis, whereas 70% of the principal diagnoses for DRG 124 are more evolved disease categories for the intermediate coronary syndrome and heart failure. Patients with lower hazard scores are younger and are more likely to be women. They also have fewer comorbid illnesses.
Second, Jollis and colleagues' record selection method puts them at risk for underestimating comorbid conditions [4], especially for patients hospitalized more than once in the same analysis period for later and more invasive surgical treatment that might include presurgical arteriography. For example, patients hospitalized for bypass grafting are much more likely to have had comorbid historical acute myocardial infarction and other comorbid cardiovascular diseases during these later hospitalizations.
Finally, the use of claims data from only one institution suggests that their undercoding of comorbid conditions is unique to their institution. The authors admit that their institution was placed on intensified review for 7 of 16 quarters by the local peer review organization (PRO). One wonders what problematic institutional practices may have occurred within their treating hospital to require intensified review and possibly differentiate this hospital from other hospitals.
Jollis and colleagues show nothing of enhanced analytical or clinical utility with the claimed riches of their data.
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Author and Article Information
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New Hampshire Foundation for Medical Care; Dover, NH 03820
Disclaimer: The conclusions and opinions expressed and the methods used herein are those of the author and are not necessarily Health Care Finance Administration policy. The author assumes full responsibility for the accuracy and completeness of the PRO data used, and no PRO funds were spent in the preparation of this effort.
1. Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB. Discordance of databases designed for claims payment versus clinical information systems: Implications for outcomes research. Ann Intern Med. 1993; 119:844-50.
2. Charlson ME, Pompei P, Ales KL, Mackenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987; 40:373-83.
3. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992; 45:613-9.
4. Huff ED. Discontinuity in the health care finance administration's published standardized mortality ratios due to underestimation bias across multiple admissions case selection methods. Clinical Performance and Quality Health Care. 1993; 1:194-8.
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