Identifying In-Hospital Complications Using Lookback Periods In Australian Health Administrative Datasets

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Dharmenaan Palamuthusingam
Gishan Ratnayake
Carmel M Hawley
Elaine M Pascoe
David W Johnson
Magid Fahim


The condition onset flag (COF) variable was introduced into hospitalization coding practice in 2008 to distinguish ICD coded diagnoses as either preexisting, new or status unknown. For datasets with multiple hospitalizations per participant, the COF enables identification of diagnoses that may have arisen in between admissions thereby enriching datasets considerably. However, datasets preceding 2008 lack equivalent depth, potentially leading to data waste.

Objectives and Approach 
The aim of this study was to determine if a lookback period could accurately identify new onset conditions in datasets coded prior to 2008. Outcomes identified in an index admission and not present in the lookback period were classified as a new condition. Three different lookback periods entailing the preceding 3, 2, and immediately previous admission were investigated. Accuracy was determined by applying this procedure to datasets in which COF were assigned by coders and comparing agreement between the lookback procedure and the COF. Codes examined were myocardial infarction, pulmonary embolism and pneumonia. Sensitivity analyses excluded indexed admissions where a lookback period was not possible. True positives were those conditions correctly identified by the lookback periods when compared to that classified using the COF. The crude incidence rates were also determined.

248,042 hospital records from 12,355 patients on chronic kidney replacement therapy were analysed. Lookback Period 1 provided the highest true positive rates for all 3 complications, ranging from 83% to 92%. Sensitivity analyses excluding patients with no previous separations, demonstrated a true positive percentage from 98% to 100%. Lookback period 3 true positive rates were the lowest (77.2-78.3%). The crude incidence calculated for first-time myocardial infarction using Lookback Period 1 was 25 events per 1000 patient years, consistent with current literature. Rates calculated using the COF variable was more than 3-fold lower. This finding was similar when evaluating other clinical outcomes.

Conclusion / Implications
The Lookback Period 1 method accurately identifies in-hospital complications compared with the current method using the COF variable and is a means of identifying new hospital complications in health administrative datasets predating the availability of COF, thereby enriching existing datasets and minimising data waste.

Article Details

How to Cite
Palamuthusingam, D., Ratnayake, G., Hawley, C. M., Pascoe, E. M., Johnson, D. W. and Fahim, M. (2020) “Identifying In-Hospital Complications Using Lookback Periods In Australian Health Administrative Datasets”, International Journal of Population Data Science, 5(5). doi: 10.23889/ijpds.v5i5.1575.