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Data preparation techniques for a perinatal psychiatric study based on linked data
Fenglian Xu1, Lisa Hilder, Marie-Paule Austin
1Perinatal and Reproductive Epidemiology Research Unit, School of Women and Children's Health, University of New South Wales, Randwick NSW 2031, Australia. f.xu@unsw.edu.au
Insights
This study details methods for preparing linked population data for perinatal psychiatric research. Creating a master dataset and calculating a statistical variable improve data quality and function.
Area of Science:
- Public Health
- Biostatistics
- Epidemiology
Background:
- Increasing use of population-based linked data in research.
- Limited literature on linked data preparation methodologies.
- Need for standardized methods in perinatal psychiatric studies.
Purpose of the Study:
- To describe a method for preparing linked population-based data.
- To detail the creation of a master dataset for perinatal psychiatric research.
- To explain the calculation of key statistical variables and recoding of diagnoses.
Main Methods:
- Utilized linked birth data from NSW collections: MDC, RCC, APDC, and PHDAS.
- Developed methods for merging data, creating a master dataset, and calculating a statistical variable for time intervals (SVTI).
- Included procedures for recoding psychiatric diagnoses and summarizing hospital admissions.
Main Results:
- A master dataset was created, integrating multiple data collections for improved quality and analysis.
- The statistical variable for time intervals (SVTI) was calculated to identify hospital admissions.
- Methods for recoding diagnoses and summarizing admissions were established.
Conclusions:
- Linked data preparation, including master dataset creation and SV calculation, enhances data quality.
- The described methods improve the functionality of linked data for research purposes.
- Standardized data preparation is crucial for robust perinatal psychiatric research.
Background:
In recent years there has been an increase in the use of population-based linked data. However, there is little literature that describes the method of linked data preparation. This paper describes the method for merging data, calculating the statistical variable (SV), recoding psychiatric diagnoses and summarizing hospital admissions for a perinatal psychiatric study.
Methods:
The data preparation techniques described in this paper are based on linked birth data from the New South Wales (NSW) Midwives Data Collection (MDC), the Register of Congenital Conditions (RCC), the Admitted Patient Data Collection (APDC) and the Pharmaceutical Drugs of Addiction System (PHDAS).
Results:
The master dataset is the meaningfully linked data which include all or major study data collections. The master dataset can be used to improve the data quality, calculate the SV and can be tailored for different analyses. To identify hospital admissions in the periods before pregnancy, during pregnancy and after birth, a statistical variable of time interval (SVTI) needs to be calculated. The methods and SPSS syntax for building a master dataset, calculating the SVTI, recoding the principal diagnoses of mental illness and summarizing hospital admissions are described.
Conclusion:
Linked data preparation, including building the master dataset and calculating the SV, can improve data quality and enhance data function.
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