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The 130th Annual Meeting of APHA |
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The 130th Annual Meeting of APHA |
Bruce A. Lawrence, PhD, Pacific Institute for Research and Evaluation, 11710 Beltsville Drive, Suite 300, Calverton, MD 20705-3102, 301/755-2731, lawrence@pire.org, Harold B. Weiss, MPH, PhD, Center for Injury Research and Control, University of Pittsburgh, 200 Lothrop St., Suite B400, Pittsburgh, PA 15213, and Ted R. Miller, PhD, Public Services Research Institute, Pacific Institute for Research and Evaluation, Calverton Office Park, 11710 Beltsville Drive, Suite 300, Calverton, MD 20705-3102.
More than half of the states are now producing hospital discharge data with mandatory E-codes. To date, however, there has been no systematic evaluation of state hospital discharge data quality. The authors cleaned and pooled 1997 inpatient hospital discharge data from 19 states representing more than half the U.S. population. They selected all injury admissions, using detailed algorithms that examined both diagnoses and E-codes. The resulting dataset included 1.2 million injury discharges. Data quality varied. Most states E-coded more than 90% of injury records, but some E-coded less than 70%. Some states with the highest E-coding rates, however, frequently used "other," "undetermined," and "unspecified" E-codes. Some states thoroughly cleaned their data, yielding datasets with no invalid diagnoses or E-codes, while others proved very difficult to clean and correct. Most states used UB-92 formats for most variables, but nearly every state departed from the UB-92 standards in one way or another. The lack of standardized coding for payers was particularly problematic. State hospital discharge data, although a gold mine of useful information, can be improved significantly. Data from some states have many invalid codes for diagnoses, causes, and procedures. Many states fail to delete old records when correcting or updating, resulting in duplicate records for some admissions. Most states provide no straightforward way to distinguish between initial and follow-up visits. Documenting and coding of ethnicity/race and payer also needs improvement.
Learning Objectives:
Keywords: Data/Surveillance, Injury
Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.