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Administrative Data Sources (administrative + data_source)
Selected AbstractsLack of Agreement in Pediatric Emergency Department Discharge Diagnoses from Clinical and Administrative Data SourcesACADEMIC EMERGENCY MEDICINE, Issue 7 2007MSCE, Marc H. Gorelick MD Background:Diagnosis information from existing data sources is used commonly for epidemiologic, administrative, and research purposes. The quality of such data for emergency department (ED) visits is unknown. Objectives:To determine the agreement on final diagnoses between two sources, electronic administrative sources and manually abstracted medical records, for pediatric ED visits, in a multicenter network. Methods:This was a cross sectional study at 19 EDs nationwide. The authors obtained data from two sources at each ED during a three-month period in 2003: administrative sources for all visits and abstracted records for randomly selected visits during ten days over the study period. Records were matched using unique identifiers and probabilistic linkage. The authors recorded up to three diagnoses from each abstracted medical record and up to ten for the administrative data source. Diagnoses were grouped into 104 groups using a modification of the Clinical Classification System. Results:A total of 8,860 abstracted records had at least one valid diagnosis code (with a total of 12,895 diagnoses) and were successfully matched to records in the administrative source. Overall, 67% (95% confidence interval = 66% to 68%) of diagnoses from the administrative and abstracted sources were within the same diagnosis group. Agreement varied by site, ranging from 54% to 77%. Agreement varied substantially by diagnosis group; there was no difference by method of linkage. Clustering clinically similar diagnosis groups improved agreement between administrative and abstracted data sources. Conclusions:ED diagnoses retrieved from electronic administrative sources and manual chart review frequently disagree, even if similar diagnosis codes are grouped. Agreement varies by institution and by diagnosis. Further work is needed to improve the accuracy of diagnosis coding; development of a grouping system specific to pediatric emergency care may be beneficial. [source] Validity of the indicator ,death in low-mortality diagnosis-related groups' for measuring patient safety and healthcare quality in hospitalsINTERNAL MEDICINE JOURNAL, Issue 4 2010S. Mihrshahi Abstract The indicator ,death in low-mortality diagnosis-related groups (DRG)' is a patient safety indicator (PSI) that can be derived from routinely collected administrative data sources. It is included in a group of PSI that have been proposed to compare and monitor standards of hospital care in Australia. To summarize the attributes of this indicator as a measure of quality and safety in healthcare and examine issues regarding the development process, definitions and use of the indicator in practice. A structured literature search was conducted using the Ovid Medline database to identify peer-reviewed published literature which used ,death in low-mortality DRG' as a quality/safety indicator. Key quality websites were also searched. The studies were critically appraised using a standardized method. A total of 12 articles was identified which met our search criteria. Most were of low methodological quality because of their retrospective study designs. Only three studies provided evidence that the quality of care gap is higher in ,deaths in low-mortality DRG' than in other cases. Most of the studies reviewed show that there are several limitations of the indicator for assessing patient safety and quality of care. The few studies that have assessed associations with other measures of hospital quality have shown only weak and inconsistent associations. Higher quality, prospective, analytic studies are required before ,death in low-mortality DRG' is used as an indicator of quality and safety in healthcare. Based on current evidence, the most appropriate use is as a screening tool for institutions to quickly and easily identify a manageable number of medical records to investigate in more detail. [source] Active labour market policy in East GermanyTHE ECONOMICS OF TRANSITION, Issue 4 2009Waiting for the economy to take off Matching estimation; causal effects; programme evaluation; panel data Abstract We investigate the effects of the most important East German active labour market programmes on the labour market outcomes of their participants. The analysis is based on a large and informative individual database derived from administrative data sources. Using matching methods, we find that over a horizon of 2.5 years after the start of the programmes, they fail to increase the employment chances of their participants in the regular labour market. However, the programmes may have other effects for their participants that may be considered important in the especially difficult situation experienced in the East German labour market. [source] Identification of alcohol involvement in injury-related hospitalisations using routine data compared to medical record reviewAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 2 2010Kirsten McKenzie Abstract Objective: To quantify the extent that alcohol related injuries are adequately identified in hospitalisation data using ICD-10-AM codes indicative of alcohol involvement. Method: A random sample of 4,373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across four states in Australia. From this sample, cases were identified as involving alcohol if they contained an ICD-10-AM diagnosis or external cause code referring to alcohol, or if the text description extracted from the medical records mentioned alcohol involvement. Results: Overall, identification of alcohol involvement using ICD codes detected 38% of the alcohol-related sample, while almost 94% of alcohol-related cases were identified through a search of the text extracted from the medical records. The resultant estimate of alcohol involvement in injury-related hospitalisations in this sample was 10%. Emergency department records were the most likely to identify whether the injury was alcohol-related with almost three-quarters of alcohol-related cases mentioning alcohol in the text abstracted from these records. Conclusions and Implications: The current best estimates of the frequency of hospital admissions where alcohol is involved prior to the injury underestimate the burden by around 62%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine administrative data sources for identification of alcohol-related injuries. [source] The reliability of information on work-related injuries available from hospitalisation data in AustraliaAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 4 2009Kirsten McKenzie Abstract Objective: To examine the reliability of work-related activity coding for injury-related hospitalisations in Australia. Method: A random sample of 4,373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across four states in Australia. From this sample, cases were identified as work-related if they contained an ICD-10-AM work-related activity code (U73) allocated by either: (i) the original coder; (ii) an independent auditor, blinded to the original code; or (iii) a research assistant, blinded to both the original and auditor codes, who reviewed narrative text extracted from the medical record. The concordance of activity coding and number of cases identified as work-related using each method were compared. Results: Of the 4,373 cases sampled, 318 cases were identified as being work-related using any of the three methods for identification. The original coder identified 217 and the auditor identified 266 work-related cases (68.2% and 83.6% of the total cases identified, respectively). Around 10% of cases were only identified through the text description review. The original coder and auditor agreed on the assignment of work-relatedness for 68.9% of cases. Conclusions and implications: The best estimates of the frequency of hospital admissions for occupational injury underestimate the burden by around 32%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine, administrative data sources for a more complete identification of work-related injuries. [source] | ||||||||||