How Good is New South Wales Admitted Patient Data Collection in Recording Births?

Abstract

This record linkage study aims to examine the coding concordance of delivery outcome and discharge status between the New South Wales (NSW) Midwives Data Collection (MDC) and Admitted Patients Data Collection (APDC) as well as factors that contribute to hospital births not being recorded in the APDC. Births recorded in the APDC and MDC datasets for the calendar year 2005 were used for analysis. Births registered in the NSW Registry of Births Deaths and Marriages for the same period were used as validation. Descriptive analysis was used to examine coding concordance between the APDC and MDC datasets for matched records, and logistic regression analyses were used to identify factors associated with hospital births not being included in the APDC. A total of 90,585 unique births were recorded in the MDC for the calendar year 2005. A total of 79,173 confirmed hospital births were matched to corresponding records in the APDC; 2,249 (3%) confirmed hospital births were not found in the APDC. For unmatched records, logistic regression analyses showed that the level of obstetric hospital in which babies were born was a significant factor associated with information not being recorded in the APDC. As compared with local, small isolated, and small metropolitan hospitals (Levels 1 to 3 hospitals), larger tertiary hospitals (Levels 4 to 6) and private hospitals had decreased odds of hospital births not being recorded in the APDC. For matched records, 95% and 99% of records were found to be coded consistently between the APDC and MDC datasets for outcome of delivery and discharge status respectively. With a high level of coding concordance between the APDC and MDC datasets and only a small percentage of hospital births not being recorded in the APDC, the obstetrics subset of the APDC dataset was found to be of good quality.

Keywords

Data Linkage Data Quality Birth Records Medical Records Clinical Coding International Classification of Diseases Hospital Information Systems Informatics Health Information Management

Get full access to this article

View all access options for this article.

References

Australian Bureau of Statistics (2008). NSW Health Department Admitted Patient Data Collection, February 2008 .Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/Explanatory%20Notes1452007?opendocument&tabname=Notes&prodno=1368.1&issue=2007&num=&view (accessed 8 December 2010).

Australian Bureau of Statistics (2006). Birth Australia 2005, October 2006. Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3301.02005?OpenDocument (accessed 5 January 2011).

Bell

J. C.

Ford

J. B.

Cameron

C. A.

Roberts

C. L.

(2008). The accuracy of population health data for monitoring trends and outcomes among women with diabetes in pregnancy. Diabetes Research and Clinical Practices 81(1): 105–109.

Centre for Health Record Linage (n.d.). Guide to health record linkage services, version 1.3. Available at: http://www.cherel.org.au/GuidetoCHeReLservices.pdf (Accessed 1 November 2010).

Chen

J. S.

Roberts

C. L.

Ford

J. B.

Taylor

L. K.

Simpson

J. M.

(2010). Cross-sectional reporting of previous Cesarean birth was validated using longitudinal linked data. Journal of Clinical Epidemiology 63(6): 672–678.

Comino

E. J.

Titmuss

Harris

Craig

Pulver

L. J.

(2007). Identification of Aboriginal infants at an urban hospital. Journal of Paediatrics and Child Health 43(9): 623–626.

Ford

J. B.

Roberts

Taylor

L. K.

(2006). Characteristics of unmatched maternal and baby records in linked birth records and hospital discharge data. Paediatric and Perinatal Epidemiology 20(4): 329–337.

Ford

J. B.

Roberts

C. L.

Algert

Bowen

J. R.

Bajuk

Henderson-Smart

D. R.

(2007). The validity of hospital discharge data for determining neonatal morbidity and mortality. BMC Health Services Research 7: 188.

Hadfield

R. M.

Lain

S, J.

Cameron

C. A.

Bell

J. C.

Morris

J. M.

Roberts

C. L.

(2008). The prevalence of maternal medical conditions during pregnancy and a validation of their reporting in the hospital discharge data. Australian and New Zealand Obstetrics and Gynaecology 48(1): 79–82.

10.

Kelman

C. W.

Bass

A. J.

Holman

C. D. J.

(2002). Research use of linked health data – a best practice protocol. Australian and New Zealand Journal of Public Health 26(3): 251–255.

11.

Lain

S. J.

Roberts

C. L.

Hadfield

R. M.

Bell

J. C.

Morris

J. M.

(2008). How accurate is the reporting of obstetric haemorrhage in hospital discharge data? A validation study. Australian and New Zealand Journal of Obstetrics and Gynaecology 48(5): 481–484.

12.

Lam

M. K.

Innes

Saad

Rust

Dimitropoulos

Cumerlato

(2008). An evaluation of the quality of obstetric morbidity coding using an objective assessment tool, the Performance Indicators For Coding Quality (PICQ). The Health Information Management Journal 37(2): 19–29.

13.

McKenzie

Harding

L. F.

Walker

S. M.

Harrison

J. E.

Enraght-Moony

E. L.

Waller

G. S.

(2006). The quality of national data on injuries requiring hospitalisation. Medical journal of Australia 185(9): 185.

14.

National Centre for Classification in Health (2004). International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification, 4th edition. Sydney, National Centre for Classification in Health, University of Sydney.

15.

NSW Department of Health [DoHA] (2005). NSW Public Health Bulletin Supplement: NSW Mothers and Babies 2005, 18(S1). Sydney, NSW Department of Health.

16.

NSW Department of Health [DoHA] (2007). Client Registration Guideline. Available at: http://www.health.nsw.gov.au/policies/gl/2007/pdf/GL2007_024.pdf (accessed 10 December 2010).

17.

NSW Department of Health [DoHA] (2009). NSW Health Services Comparison Data Book 2007/2008 Volume 1, Sydney, NSW Department of Health.

18.

NSW Government (2010). NSW Government Legislation: Private Health Facilities Regulation 2010. Available at: http://www.legislation.nsw.gov.au/maintop/view/inforce/subordleg+64+2010+cd+0+N (accessed 6 December 2010).

19.

NSW Consolidated Acts (n.d.). Births, Deaths and Marriages Acts 1995 - Births Registration. Available at: http://www.austlii.edu.au/au/legis/nsw/consol_act/bdamra1995383/s13.html (accessed 1 December 2010).

20.

Andersen

A. M. Nybo

Wohlfahrt

Christens

Olsen

Melbye

(2000). Maternal age and fetal loss: Population based register linkage study. BMJ 320(7251): 1708–1712.

21.

Roberts

C. L.

Bell

J. C.

Ford

J. B.

Hadfield

R. M.

Algert

C. S.

Morris

(2008). The accuracy of reporting of the hypertensive disorders of pregnancy in population health data. Hypertension in Pregnancy 27(3): 285–297.

22.

Roberts

C. L.

Bell

J. C.

Ford

J. B.

Morris

(2009). Monitoring the quality of maternity care: How well are labour and delivery events reported in population health data? Paediatric and Perinatal Epidemiology 23(2): 144–152.

23.

Roberts

C. L.

Ford

J. B.

Lain

Algert

C. S.

Sparks

D. J.

(2008). The accuracy of reporting of general anaesthesia for childbirth: A validation study. Anaesthesia and Intensive Care 36(3): 418–424.

24.

SPSS Inc (2008). SPSS Base V.17.0 for Windows. Chicago, IL, SPSS Inc.

25.

Taylor

L. K.

Travis

Pym

Olive

Henderson-Smart

D. J.

(2005). How useful are hospital morbidity data for monitoring conditions occurring in the perinatal period. Australian and New Zealand Journal of Obstetrics and Gynaecology 45(1): 36–41.