| Literature DB >> 35321901 |
Rohan D'Souza1,2,3, Rebecca J Seymour4, Marian Knight5, Susie Dzakpasu6, K S Joseph7,8, Sara Thorne9, Maria B Ospina10, Jon Barrett4, Jocelynn Cook11,12, Deshayne B Fell13, Heather Scott14, Amy Metcalfe15, Thomas van den Akker16,17, Stephen Lapinsky18, Leslie Skeith19,20, Beth Murray-Davis21, Prakesh Shah22, Milena Forte23, Rizwana Ashraf4, Josie Chundamala3, Sarah A Hutchinson3, Kenneth K Chen24,25, Isabelle Malhamé26,27.
Abstract
INTRODUCTION: Severe maternal morbidity (SMM)-an unexpected pregnancy-associated maternal outcome resulting in severe illness, prolonged hospitalisation or long-term disability-is recognised by many, as the preferred indicator of the quality of maternity care, especially in high-income countries. Obtaining comprehensive details on events and circumstances leading to SMM, obtained through maternity units, could complement data from large epidemiological studies and enable targeted interventions to improve maternal health. The aim of this study is to assess the feasibility of gathering such data from maternity units across Canadian provinces and territories, with the goal of establishing a national obstetric survey system for SMM in Canada. METHODS AND ANALYSIS: We propose a sequential explanatory mixed-methods study. We will first distribute a cross-sectional survey to leads of all maternity units across Canada to gather information on (1) Whether the unit has a system for reviewing SMM and the nature and format of this system, (2) Willingness to share anonymised data on SMM by direct entry using a web-based platform and (3) Respondents' perception on the definition and leading causes of SMM at a local level. This will be followed by semistructured interviews with respondent groups defined a priori, to identify barriers and facilitators for data sharing. We will perform an integrated analysis to determine feasibility outcomes, a narrative description of barriers and facilitators for data-sharing and resource implications for data acquisition on an annual basis, and variations in top-5 causes of SMM. ETHICS AND DISSEMINATION: The study has been approved by the Mount Sinai and Hamilton Integrated Research Ethics Boards. The study findings will be presented at annual scientific meetings of the Society of Obstetricians and Gynaecologists of Canada, North American Society of Obstetric Medicine, and International Network of Obstetric Survey Systems and published in an open-access peer-reviewed Obstetrics and Gynaecology or General Internal Medicine journal. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Entities:
Keywords: adult intensive & critical care; audit; maternal medicine; obstetrics
Mesh:
Year: 2022 PMID: 35321901 PMCID: PMC8943762 DOI: 10.1136/bmjopen-2022-061093
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Figure 1Study schematic – Canadian Obstetric Survey System Feasibility Study. CAM, Canadian Association of Midwives; CNN, Canadian Neonatal Network; CPSS, Canadian Perinatal Surveillance System; SOGC, Society of Obstetricians and Gyanecologists of Canada; SMM, Severe maternal morbidity.
Canadian Obstetric Survey System (CanOSS) Feasibility Study—linking study objectives and research questions with study outcomes
| Objective | Research question | Outcome |
| 1. Feasibility outcomes | 1. Quantitative |
Existence of a system for reviewing SMM. Nature of the system and the variation between regions. Willingness to share data on SMM, regionally, provincially, or nationally, through direct data entry into a web-based platform. |
| 2. Barriers to data sharing | 2. Qualitative |
Barriers, challenges, perspectives, concerns and suggestions, obtained through thematic analysis. |
| 3. Leading causes of SMM | 3. Quantitative |
Top five causes of SMM. Variations in perceived causes of SMM between and within regions, provinces and territories. |
| 4. Resource utilisation | 4. Mixed-Methods |
Estimate of resources required for ongoing collection of granular data on SMM as part of the Canadian Obstetric Survey System (CanOSS). |
SMM, Severe maternal morbidity.