Exploring the differences in ICD and hospital morbidity data collection features across countries: an international survey

Background The International Classification of Diseases (ICD) is the reference standard for reporting diseases and health conditions globally. Variations in ICD use and data collection across countries can hinder meaningful comparisons of morbidity data. Thus, we aimed to characterize ICD and hospital morbidity data collection features worldwide. Methods An online questionnaire was created to poll the World Health Organization (WHO) member countries that were using ICD. The survey included questions focused on ICD meta-features and hospital data collection systems, and was distributed via SurveyMonkey using purposive and snowball sampling. Accordingly, senior representatives from organizations specialized in the topic, such as WHO Collaborating Centers, and other experts in ICD coding were invited to fill out the survey and forward the questionnaire to their peers. Answers were collated by country, analyzed, and presented in a narrative form with descriptive analysis. Results Responses from 47 participants were collected, representing 26 different countries using ICD. Results indicated worldwide disparities in the ICD meta-features regarding the maximum allowable coding fields for diagnosis, the definition of main condition, and the mandatory type of data fields in the hospital morbidity database. Accordingly, the most frequently reported answers were “reason for admission” as main condition definition (n = 14), having 31 or more diagnostic fields available (n = 12), and “Diagnoses” (n = 26) and “Patient demographics” (n = 25) for mandatory data fields. Discrepancies in data collection systems occurred between but also within countries, thereby revealing a lack of standardization both at the international and national level. Additionally, some countries reported specific data collection features, including the use or misuse of ICD coding, the national standards for coding or lack thereof, and the electronic abstracting systems utilized in hospitals. Conclusions Harmonizing ICD coding standards/guidelines should be a common goal to enhance international comparisons of health data. The current international status of ICD data collection highlights the need for the promotion of ICD and the adoption of the newest version, ICD-11. Furthermore, it will encourage further research on how to improve and standardize ICD coding.

Linking midwives and hospital morbidity data to investigate the effect of interpregnancy interval on gestational diabetes: a 35-year cohort study in Western Australia

IntroductionInterpregnancy interval (IPI) is a potentially modifiable risk factor for preganncy outcomes, and short and long IPI may be associated with increased rik of pregnancy complications. Record linkage provides the only practiacble means to investigate IPI effects, which requires large generalisable sample sizes and long follow-up time. Objectives and ApproachThis study examines the effect of IPI on gestational diabetes in Western Australia, with the aim to inform the evidence-base for IPI recommendations in high-income countries. A longitudinal population-based retrospective cohort study was conducted using de-identified, probabilistically-linked records for all births in Western Australia from 1980 to 2015 (inclusive) from the state’s Midwives Notification System and the WA Hospital Morbidity Data Collection. Logistic regression model was used to estimate the odds of gestational diabetes by IPI category. Analyses included all women with at least two consecutive singleton live births at 20-44 weeks of gestation. ResultsA cohort of 320,616 women were included in the study. Of these, 13,680 (4\%) had an IPI > 120 months (AOR:1.53, 95\% CI 1.38-1.70) as compared to 18-23 months. Conclusion/ImplicationsOur findings show that both short and long IPIs may be associated with increased risk of gestational diabetes in a high-income setting. In this study, data linkage improved ascertainment of the outcome measure. Results suggest 18-23 months following a previous livebirth may be optimal for avoiding complications in future pregnancies.

Validation of intellectual disability coding through hospital morbidity records using an intellectual disability population-based database in Western Australia

ObjectivesTo investigate how well intellectual disability (ID) can be ascertained using hospital morbidity data compared with a population-based data source.Design, setting and participantsAll children born in 1983–2010 with a hospital admission in the Western Australian Hospital Morbidity Data System (HMDS) were linked with the Western Australian Intellectual Disability Exploring Answers (IDEA) database. The International Classification of Diseases hospital codes consistent with ID were also identified.Main outcome measuresThe characteristics of those children identified with ID through either or both sources were investigated.ResultsOf the 488 905 individuals in the study, 10 218 (2.1%) were identified with ID in either IDEA or HMDS with 1435 (14.0%) individuals identified in both databases, 8305 (81.3%) unique to the IDEA database and 478 (4.7%) unique to the HMDS dataset only. Of those unique to the HMDS dataset, about a quarter (n=124) had died before 1 year of age and most of these (75%) before 1 month. Children with ID who were also coded as such in the HMDS data were more likely to be aged under 1 year, female, non-Aboriginal and have a severe level of ID, compared with those not coded in the HMDS data. The sensitivity of using HMDS to identify ID was 14.7%, whereas the specificity was much higher at 99.9%.ConclusionHospital morbidity data are not a reliable source for identifying ID within a population, and epidemiological researchers need to take these findings into account in their study design.