Reliability of routinely collected hospital data for child maltreatment surveillance.

BACKGROUND: Internationally, research on child maltreatment-related injuries has been hampered by a lack of available routinely collected health data to identify cases, examine causes, identify risk factors and explore health outcomes. Routinely collected hospital separation data coded using the International Classification of Diseases and Related Health Problems (ICD) system provide an internationally standardised data source for classifying and aggregating diseases, injuries, causes of injuries and related health conditions for statistical purposes. However, there has been limited research to examine the reliability of these data for child maltreatment surveillance purposes. This study examined the reliability of coding of child maltreatment in Queensland, Australia. METHODS: A retrospective medical record review and recoding methodology was used to assess the reliability of coding of child maltreatment. A stratified sample of hospitals across Queensland was selected for this study, and a stratified random sample of cases was selected from within those hospitals. RESULTS: In 3.6% of cases the coders disagreed on whether any maltreatment code could be assigned (definite or possible) versus no maltreatment being assigned (unintentional injury), giving a sensitivity of 0.982 and specificity of 0.948. The review of these cases where discrepancies existed revealed that all cases had some indications of risk documented in the records. 15.5% of cases originally assigned a definite or possible maltreatment code, were recoded to a more or less definite strata. In terms of the number and type of maltreatment codes assigned, the auditor assigned a greater number of maltreatment types based on the medical documentation than the original coder assigned (22% of the auditor coded cases had more than one maltreatment type assigned compared to only 6% of the original coded data). The maltreatment types which were the most 'under-coded' by the original coder were psychological abuse and neglect. Cases coded with a sexual abuse code showed the highest level of reliability. CONCLUSION: Given the increasing international attention being given to improving the uniformity of reporting of child-maltreatment related injuries and the emphasis on the better utilisation of routinely collected health data, this study provides an estimate of the reliability of maltreatment-specific ICD-10-AM codes assigned in an inpatient setting.

Coding external causes of injuries: problems and solutions.

Complete and accurate information about hospitalised injuries is essential for injury risk and outcome research, though the accuracy and reliability of hospital data for injury surveillance are often questioned. To ascertain clinical coders' views of the reasons for a lack of specificity in external cause code usage and ways to improve external cause coding, a nationwide survey of coders was conducted in Australia in 2006. Four hundred and two coders participated in the questionnaire. The results of this study show that discharge summaries and doctors' notes were the poorest source of information regarding external causes, place of injury occurrence, and activity at the time of injury. Coders viewed missing external cause information and missing documentation as having the greatest impact on the quality of external cause coding. A large majority of coders suggested that improving clinical documentation in the emergency department and introducing a centralised structured form for external cause information would improve the quality of external cause coding. Clinical coders are a valuable source of information regarding problems with, and solutions to the collection of high quality data and this research has highlighted several areas where improvements can be made and further research is needed.

The quality of cause-of-injury data: where hospital records fall down.

OBJECTIVES: This research identifies the level of specificity of cause-of-injury morbidity data in Australia. The research explores reasons for poor-quality data across different causes-of-injury areas, including a lack of clinical documentation and insufficient detail in the classification system. METHODS: The 2002/03 hospital morbidity dataset of 593,079 injury-related hospital admissions was analysed to examine the specificity of coded external cause-of-injury data. RESULTS: While overall specificity appeared high, the cause of 47,660 injuries was not specifically defined according to the code assigned. Only 56% of cases for whom injury was the result of an accidental fall were assigned a specific code to identify the causal detail; 19% were assigned an 'Other Specified' fall code, suggesting a lack of specific code availability; and 25% were assigned an 'Unspecified Fall' code, suggesting a lack of clinical documentation to facilitate code selection. CONCLUSIONS: To improve the quality of injury-related hospital morbidity data, two main areas to focus resources are: 1) the development of more specific cause-of-injury codes; and 2) the provision of more detailed documentation from clinicians. IMPLICATIONS: Clinicians and clinical coders need to work together to improve the quality of injury-related coded data through the provision of specific codes and improved clinical documentation. Accurate and comprehensive data pertaining to the circumstances surrounding hospitalised injury events will benefit injury prevention and surveillance initiatives, provide justification for resources related to injury hospitalisation, and assist in external cause research in Australia.