about better outcomes registry & network (BORN) data
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- For each data source, information about data collection and analytical methods, limitations, the citation and additional resources can be found on the Data Sources and Methods page.
The Better Outcomes Registry & Network (BORN) is a longitudinal administrative data source. BORN collects information related to maternal, perinatal and newborn health for the Ontario population.
Original Source: Better Outcomes Registry & Network (BORN) Ontario
- For data from BORN Standard Reports
[Standard report name] (Standard Report), BORN Information System (BIS), BORN Ontario. Information accessed on [date].
- For data from BORN Data Cube
Public Health Analytic Reporting Tool (Cube), BORN Information System (BIS), BORN Ontario. Information accessed on [date].
Data Collection Methods
- In 2009, the former Ontario Perinatal Surveillance System was granted registry status and was renamed the Better Outcomes Registry & Network (BORN). The five founding members of BORN (Ontario Maternal Multiple Marker Screening, Fetal Alert Network, Ontario Midwifery Program, Niday Perinatal Database and Ontario Newborn Screening) subsequently integrated their data into one maternal-child registry. On April 1, 2012, the BORN Information System (BIS) went live. As a registry, BORN is permitted to automatically capture personal health information without prior consent.
- The objective of BORN is to capture every birth in Ontario (to Ontario residents), including home births.
- Birthing hospitals and midwifery practice groups as well as fertility clinics, prenatal screening labs, newborn screening laboratories, prenatal and newborn screening follow-up clinics in Ontario contribute data to BORN.
- Hospitals and midwifery practice groups enter their own data into the BORN database either through direct data entry by health care staff (including nurses and clerks), HL7 feeds or through a manual electronic batch upload from the hospital database.
- BORN data are reviewed and cleaned by BORN Ontario staff and infant geographic information (e.g., infant Public Health Unit (PHU)) are added in the record based on postal code and city or town of residence, regardless of the location of birth (For example, if a Peel resident was born in another location in Ontario (e.g., Ottawa), they would be included in Peel’s data).
- For cases where the postal code is either missing or invalid, the city/town of residence and/or first three digits of postal code (Forward Sortation Area (FSA)) are used to assign PHU
- If the postal code provided is not valid, the FSA will be missing within the dataset (although the PHU will be assigned based on the city/town and/or FSA)
- To assess whether BORN data are releasable, small cell counts and missing data are considered:
- Counts and rates arising from fewer than six records are considered not releasable. In this scenario, the acronym ‘NR’ is presented in the data table, with a footnote stating ‘Not releasable due to small numbers.’
- Data with 0% to <10% missing are releasable, between ≥10% to <30% missing are released with caution, and ≥30 are not releasable.
- When releasable, the proportion of missing data is presented in the table. Missing responses are included in the denominator with a footnote stating ‘Missing responses were included in the calculation of the percentages for the categories in this table.’
- BORN is a dynamic data set, such that data are updated daily. Data for the same period extracted at two different time points may differ. To inform the user, the data extraction date is included in the data source line.
- The web-based system provides three standard summary reports: birth, newborn, and pregnancy. These aggregate reports include tables and graphs for various pre-defined indicators by health unit, peer group (not applicable for Peel) and Ontario.
- Health units also have access to analytic cubes, which provide the ability to create customized reports (pivot tables) of real-time aggregate BORN data for a subset of the variables collected.
- There are several measures available for the denominator, depending on the purpose of the analysis. For example, the denominator may be all live births, singleton live births, or all women who gave birth.
- Missing data are included in the calculation of the percentages in the tables and may appear as a possible response category, as described in the Release Guidelines section above.
- Outside of a special request, only Peel data are available for analysis in the analytic cube. However, Ontario comparator data are available for select variables from standard reports.
- For some variables, the number of missing or unknown responses can be quite high, although data completeness and quality has improved over time.
- There is a six-month delay after the period of interest before the data are considered complete.
- For some variables (e.g., smoking during pregnancy, alcohol use during pregnancy) some women may provide a socially desirable response to avoid perceived negative consequences or feelings of being judged by their health care provider.
- There are only a limited number of demographic variables available within the Public Health BORN data. For example, information related to maternal ethnicity, income or education is not included. Therefore, only ecological analyses of demographic data from other data sources (e.g., census information) are possible.
- Because of the changes in availability as well as definition of some variables over time, it is not always possible to observe trends over time.
REFERENCES AND RESOURCES
- Ontario Agency for Health Protection and Promotion (Public Health Ontario). BORN Information System: a data quality assessment for public health monitoring. Toronto (ON): Queen’s Printer for Ontario; 2016 Mar.
- Better Outcomes Registry & Network (BORN). BORN data quality report 2012-2014. 2016 Apr.
- BORN Public Health Working Group. Using BORN Ontario Data for Public Health Surveillance: User Guide for Epidemiologists & Data Analysts-BORN Public Health Analytics Cube. [Ontario]: Association of Public Health Epidemiologists in Ontario; 2017 Feb.
Last updated: February 12, 2019