Exploring the implications of the new ICD-10-CM classification system for injury surveillance: analysis of dually coded data from two medical centres.

INTRODUCTION: External cause of injury matrices is used to classify mechanisms/causes of injuries for surveillance and research. Little is known about the performance of the Centers for Disease Control and Prevention's new external cause of injury matrix for Clinical Modification of the 10th Revision of the International Classification of Diseases (ICD-10-CM), compared with the ICD-9-CM version. METHODS: Dually coded (ICD-9-CM and ICD-10-CM) administrative data were obtained from two major academic trauma centres. Injury-related cases were identified and categorised by mechanism/cause and manner/intent. Comparability ratios (CR) were used to estimate the net impact of changing from ICD-9-CM to ICD-10-CM on the number of cases classified to each mechanism/cause category. Chamberlain's percent positive agreements (PPA) were calculated and McNemar's test was used to assess the significance of observed classification differences. RESULTS: Of 4832 and 5211 dual-coded records from the two centres, 632 and 520 with injury-related principal diagnoses and external cause codes in both ICD-9-CM and ICD-10-CM were identified. CRs for the mechanisms/causes with at least 20 records ranged from 0.85 to 1.9 at one centre and from 0.97 to 1.07 at the other. Among these mechanisms/causes, PPAs ranged from 33% for 'other transport' to 94% for poisoning at one centre, and from 75% for 'other transport' to 100% for fires/burns at the other centre. Case assignment differed significantly for falls, motor vehicle traffic, other transport, and 'struck by/against' injuries at one centre, and for 'other pedal cyclist' at the other centre. CONCLUSION: Switching to ICD-10-CM and the new external cause of injury matrix may affect injury surveillance and research, especially for certain mechanisms/causes.

Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric.

This study aimed to evaluate a quality metric that identifies pediatric potentially avoidable transfers from diagnosis and procedure codes. Using physician medical record review as the gold standard, the following steps were used: (1) develop the initial metric definition, (2) estimate initial metric definition operating characteristics, (3) refine this definition to optimize the c-statistic, and (4) validate this optimized metric definition using a separate sample. The initial metric using Sample A patient transfers had a c-statistic of 0.63 (95% confidence interval = 0.53-0.73). Following 22 revisions, the optimized metric definition was a transfer discharged within 24 hours that did not receive any of a select list of 60 268 specialized diagnoses or procedures. The optimized metric on Sample B demonstrated a sensitivity of 80.6%, specificity of 85.7%, and c-statistic of 0.83 (95% confidence interval = 0.75-0.91). The quality metric developed and validated in this study demonstrated satisfactory operating characteristics, providing a feasible means to measure this important outcome.

Conversion of the Agency for Healthcare Research and Quality's Quality Indicators from ICD-9-CM to ICD-10-CM/PCS: The Process, Results, and Implications for Users.

OBJECTIVE: To convert the Agency for Healthcare Research and Quality's (AHRQ) Quality Indicators (QIs) from International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) specifications to ICD, 10th Revision, Clinical Modification and Procedure Classification System (ICD-10-CM/PCS) specifications. DATA SOURCES: ICD-9-CM and ICD-10-CM/PCS classifications, General Equivalence Maps (GEMs). STUDY DESIGN: We convened 77 clinicians and coders to evaluate ICD-10-CM/PCS codes mapped from ICD-9-CM using automated GEMs. We reviewed codes to develop "legacy" specifications resembling those in ICD-9-CM and "enhanced" specifications addressing enhanced capabilities of ICD-10-CM/PCS. DATA COLLECTION/EXTRACTION METHODS: We tabulated the numbers of mapped codes, added nonmapped codes, and deleted mapped codes to achieve the specifications. PRINCIPAL FINDINGS: Of 212 clinical concepts (sets of codes) that comprise the QI specifications, we either added nonmapped codes to or deleted mapped codes from 115 (54 percent). The legacy and enhanced specifications differed for 46 sets (22 percent), affecting 67 of the 101 QIs (66 percent). Occasionally, concepts that defied conversion required reformulation of indicators. CONCLUSIONS: Converting the AHRQ QIs to ICD-10-CM/PCS required a detailed, thorough process beyond automated mapping of codes. Differences between the legacy and enhanced versions of the QIs are frequently minor but sometimes substantive.