Practitioners Assess Achievements and Challenges of Nonfatal Injury Surveillance.

OBJECTIVE

Injury surveillance relies on data coded for administrative rather than epidemiological accuracy. The Centers for Disease Control and Prevention (CDC) established the 5-year Surveillance Quality Improvement (SQI) initiative to advance consensus and methodology for injury epidemiology reporting and analysis. Evaluation of the positive predictive value of the CDC's injury surveillance definitions based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding in designated injury categories comprised much of the SQI initiative's work. The goal of the current study is to identify achievements and challenges in SQI as articulated by experienced injury epidemiology practitioners who participated in the CDC-funded SQI initiative.

DESIGN, SETTING, AND PARTICIPANTS: We conducted semistructured interviews with 12 representatives of state and federal public health agencies who had participated extensively in the SQI initiative. The interviews were transcribed and coded using NVivo qualitative analysis software. Initial coding of the data involved both in vivo coding (using the words of participants) and coding of a priori themes.

MAIN OUTCOME MEASURES

Qualitative analysis identified 2 overarching themes, variability among states and observations on the science of injury surveillance.

RESULTS

Within the 2 broad themes, the respondents provided valuable insights regarding access to medical records, case definition validation, unique contributions of medical record abstracting, variations in the practice of medical coding, and the potential for use of data from medical record reviews in other injury-related areas.

CONCLUSIONS

The contributions of the SQI initiative have provided valuable insights into ICD-10-CM case definitions for national injury surveillance. Challenges remain with regard to data access and quality with ongoing reliance on administrative datasets for injury surveillance.