Evolving swabbing practices for COVID-19 in a New Zealand emergency department during the early stages of an emerging pandemic.

OBJECTIVE: To review if tests for suspected COVID-19 were performed according to the Ministry of Health (MoH) case definitions, identify patterns associated with testing outside of the case definition, and discuss the potential impacts on hospital services. METHODS: This was a retrospective audit of patients presenting to the Wellington Hospital ED between 24 March 2020 and 27 April 2020 who were swabbed for COVID-19 in ED. Swabs were audited against the March 15th and April 8th MoH COVID-19 case definitions. RESULTS: Five hundred and thirty-six COVID-19 swabs for 518 patients were taken during the study period. There was poor alignment of testing with the March 15th case definition, with only 11.6% of the 164 swabs taken during this period meeting the case definition. Of the 145 swabs that did not meet the case definition, the majority (n = 119, 82.1%) met symptom criteria only. Alignment of testing with the wider April 8th case definition was much higher with 88.2% meeting criteria. Factors associated with being swabbed despite not meeting the case definitions included fever >38°, a diagnosis of cancer, subsequent hospital admission, and for the March case definition only 'contact with a traveller'. CONCLUSION: There were associations found between testing outside of criteria and specific variables potentially perceived as high-risk. Poor alignment of testing with case definitions can impact hospital services through the (mis)use of limited laboratory testing capacity and implications for resource management. Improved communication and feedback between clinicians and policymakers may improve case definition implementation in a clinical setting.

We still don't count: the under-counting and under-representation of Maori in health and disability sector data.

AIM: To examine ethnicity data quality; in particular, the representation and potential under-counting of Maori in health and disability sector data, as well as implications for inequities. METHODS: Maori and non-Maori ethnicity data are analysed at: 1) a population aggregate level across multiple 2018 datasets (Estimated Resident Population, Census Usually Resident Population, Health Service User (HSU) population and Primary Health Organisation (PHO) enrolments); and 2) an individual level for those linked in PHO and 2018 Census datasets. Ethnicity is drawn from the National Health Index (NHI) in health datasets and variations by age and gender are explored. RESULTS: Aggregate analyses show that Maori are considerably under-represented in HSU and PHO data. In linked analysis Maori were under-counted on the NHI by 16%. Under-representation in data and under-counting occur across both genders but are more pronounced for Maori men with variations by age. CONCLUSION: High quality ethnicity data are fundamental for understanding and monitoring Maori health and health inequities as well as in the provision of targeted services and interventions that are responsive to Maori aspirations and needs. The continued under-counting of Maori in health and disability sector data is a breach of Te Tiriti o Waitangi and must be addressed with urgency.

Ethnicity data audit in a secondary care gastroenterology service.

AIM: To audit the quality of ethnicity data stored under National Health Index (NHI) in the Hutt Hospital database against a fresh collection of self-identified ethnicity to identify the level of (mis)match present between the datasets. METHOD: Self-identified ethnicity data was collected from 200 consecutive patients presenting to outpatient gastroenterology services and compared to National Health Index (NHI) in the Hutt Hospital database, using the process outlined in the Primary Care Ethnicity Data Audit Toolkit. RESULTS: The overall level of match between the individual's self-identified ethnicity and that recorded in the hospital database was 89% (95% CI [83.8-93.0]). Eighteen patients (9%) self-identified as Maori, 16.7% (95% CI [3.6-41.4]) of whom were not recorded as Maori in the hospital database. Three patients were recorded as Maori in the hospital database but did not self-identify as Maori. CONCLUSION: Ethnicity data are fundamental to the monitoring and provision of equitable health and healthcare, with a range of applications in the health sector. Our findings of poor-quality ethnicity data for Maori in a hospital NHI database are consistent with previous studies. The assessment of ethnicity data quality must be done in multiple ways to reflect its multiple uses.