Data preparation techniques for a perinatal psychiatric study based on linked data

• Main Authors: Xu Fenglian, Hilder Lisa, Austin Marie-Paule, Sullivan Elizabeth A
• Format: Article
• Language: English
• Published: BMC 2012-06-01
• Series: BMC Medical Research Methodology
• Subjects: Data preparation; Method; Psychiatric study; Australia
• Online Access: http://www.biomedcentral.com/1471-2288/12/71

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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).</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>Linked data preparation, including building the master dataset and calculating the SV, can improve data quality and enhance data function.</p>