TY - JOUR
T1 - Statistical methods to enhance reporting of Aboriginal Australians in routine hospital records using data linkage affect estimates of health disparities
AU - Randall, Deborah A.
AU - Lujic, Sanja
AU - Leyland, Alastair H.
AU - Jorm, Louisa R.
PY - 2013
Y1 - 2013
N2 - Objective: To investigate under-recording of Aboriginal people in hospital data from New South Wales (NSW), Australia, define algorithms for enhanced reporting, and examine the impact of these algorithms on estimated disparities in cardiovascular and injury outcomes. Methods: NSW Admitted Patient Data were linked with NSW mortality data (2001-2007). Associations with recording of Aboriginal status were investigated using multilevel logistic regression. The number of admissions reported as Aboriginal according to six algorithms was compared with the original (unenhanced) Aboriginal status variable. Age-standardised admission, and 30- and 365-day mortality ratios were estimated for cardiovascular disease and injury. Results: Sixty per cent of the variation in recording of Aboriginal status was due to the hospital of admission, with poorer recording in private and major city hospitals. All enhancement algorithms increased the number of admissions reported as Aboriginal, from between 4.1% and 37.8%. Admission and mortality ratios varied markedly between algorithms, with less strict algorithms resulting in higher admission rate ratios, but generally lower mortality rate ratios, particularly for cardiovascular disease. Conclusions: The choice of enhancement algorithm has an impact on the number of people reported as Aboriginal and on estimated outcome ratios. The influence of the hospital on recording of Aboriginal status highlights the importance of continued efforts to improve data collection. Implications: Estimates of Aboriginal health disparity can change depending on how Aboriginal status is reported. Sensitivity analyses using a number of algorithms are recommended.
AB - Objective: To investigate under-recording of Aboriginal people in hospital data from New South Wales (NSW), Australia, define algorithms for enhanced reporting, and examine the impact of these algorithms on estimated disparities in cardiovascular and injury outcomes. Methods: NSW Admitted Patient Data were linked with NSW mortality data (2001-2007). Associations with recording of Aboriginal status were investigated using multilevel logistic regression. The number of admissions reported as Aboriginal according to six algorithms was compared with the original (unenhanced) Aboriginal status variable. Age-standardised admission, and 30- and 365-day mortality ratios were estimated for cardiovascular disease and injury. Results: Sixty per cent of the variation in recording of Aboriginal status was due to the hospital of admission, with poorer recording in private and major city hospitals. All enhancement algorithms increased the number of admissions reported as Aboriginal, from between 4.1% and 37.8%. Admission and mortality ratios varied markedly between algorithms, with less strict algorithms resulting in higher admission rate ratios, but generally lower mortality rate ratios, particularly for cardiovascular disease. Conclusions: The choice of enhancement algorithm has an impact on the number of people reported as Aboriginal and on estimated outcome ratios. The influence of the hospital on recording of Aboriginal status highlights the importance of continued efforts to improve data collection. Implications: Estimates of Aboriginal health disparity can change depending on how Aboriginal status is reported. Sensitivity analyses using a number of algorithms are recommended.
UR - http://handle.uws.edu.au:8081/1959.7/533636
U2 - 10.1111/1753-6405.12114
DO - 10.1111/1753-6405.12114
M3 - Article
SN - 1326-0200
VL - 37
SP - 442
EP - 449
JO - Australian and New Zealand Journal of Public Health
JF - Australian and New Zealand Journal of Public Health
IS - 5
ER -