Kirsten Vallmuur1, Cate M Cameron2, Angela Watson3, Jacelle Warren4. 1. Centre for Healthcare Transformation, Australian Centre for Health Services Innovation (AusHSI), Queensland University of Technology, Brisbane, Queensland, Australia; Jamieson Trauma Institute, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Service, Herston, Queensland, Australia. Electronic address: k.vallmuur@qut.edu.au. 2. Jamieson Trauma Institute, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Service, Herston, Queensland, Australia; Centre for Healthcare Transformation, Australian Centre for Health Services Innovation (AusHSI), Queensland University of Technology, Brisbane, Queensland, Australia. 3. Centre for Accident Research and Road Safety Queensland, Queensland University of Technology (QUT), Brisbane, Queensland, Australia. 4. Centre for Healthcare Transformation, Australian Centre for Health Services Innovation (AusHSI), Queensland University of Technology, Brisbane, Queensland, Australia; Jamieson Trauma Institute, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Service, Herston, Queensland, Australia.
Abstract
INTRODUCTION: Trauma registries have been used internationally for several decades to measure the quality of trauma care between hospitals. Given the significant costs involved in establishing and maintaining trauma registries, and increasing availability of routinely collected, linked health data describing a patient's journey (and inherent cost savings in data re-use), there is significant interest in development of integrated, comprehensive trauma data repositories. However, approaches to estimating injury severity using routinely collected data would need to be developed if routinely collected hospital data were to be used as an alternative/supplement to registries. OBJECTIVES: This study aimed to compare the accuracy of registry-based injury severity estimates with ICD-based injury severity estimates in predicting mortality outcomes in a cohort of minor and major trauma patients in Queensland, using retrospectively linked trauma registry and hospital admissions data. METHODS: Queensland Trauma Registry (QTR) data with an admission date between 1 January 2005 and 31 December 2011 was linked with all acute care patients included in the Queensland Hospital Admitted Patient Data Collection (QHAPDC) with a Principal Diagnosis coded with an ICD-10-AM code within Chapter 19 (S00-T98). Abbreviated Injury Scale coding was undertaken manually by QTR trauma data nurses for the registry data. ICD-based injury severity scores (ICISS) were calculated automatically using all injury-related diagnoses captured in the QHAPDC data using the ICISS multiplicative and worst injury method. RESULTS: There were 92,140 QTR patients admitted between January 2005 and December 2011 with a valid ISS with a matching QHAPDC record (98.4% survived, 1.6% died). ICISS (multiplicative and worst injury approach) showed marginally better predictive accuracy than ISS when predicting mortality across minor and major injury and ICISS showed marginally better predictive accuracy to ISS when restricted to major trauma/high threat to life cases. Both ICISS and ISS restricted to major trauma/high threat to life showed poorer accuracy compared to the predictive performance when both minor and major cases were included. CONCLUSION: ICD-based predictions were as accurate as ISS-based predictions for this cohort and this study provides evidence to support the potential for using routinely coded hospital data for risk adjustment within State-based trauma data repositories.
INTRODUCTION:Trauma registries have been used internationally for several decades to measure the quality of trauma care between hospitals. Given the significant costs involved in establishing and maintaining trauma registries, and increasing availability of routinely collected, linked health data describing a patient's journey (and inherent cost savings in data re-use), there is significant interest in development of integrated, comprehensive trauma data repositories. However, approaches to estimating injury severity using routinely collected data would need to be developed if routinely collected hospital data were to be used as an alternative/supplement to registries. OBJECTIVES: This study aimed to compare the accuracy of registry-based injury severity estimates with ICD-based injury severity estimates in predicting mortality outcomes in a cohort of minor and major traumapatients in Queensland, using retrospectively linked trauma registry and hospital admissions data. METHODS: Queensland Trauma Registry (QTR) data with an admission date between 1 January 2005 and 31 December 2011 was linked with all acute care patients included in the Queensland Hospital Admitted Patient Data Collection (QHAPDC) with a Principal Diagnosis coded with an ICD-10-AM code within Chapter 19 (S00-T98). Abbreviated Injury Scale coding was undertaken manually by QTR trauma data nurses for the registry data. ICD-based injury severity scores (ICISS) were calculated automatically using all injury-related diagnoses captured in the QHAPDC data using the ICISS multiplicative and worst injury method. RESULTS: There were 92,140 QTR patients admitted between January 2005 and December 2011 with a valid ISS with a matching QHAPDC record (98.4% survived, 1.6% died). ICISS (multiplicative and worst injury approach) showed marginally better predictive accuracy than ISS when predicting mortality across minor and major injury and ICISS showed marginally better predictive accuracy to ISS when restricted to major trauma/high threat to life cases. Both ICISS and ISS restricted to major trauma/high threat to life showed poorer accuracy compared to the predictive performance when both minor and major cases were included. CONCLUSION: ICD-based predictions were as accurate as ISS-based predictions for this cohort and this study provides evidence to support the potential for using routinely coded hospital data for risk adjustment within State-based trauma data repositories.