A Planning Checklist for Interprofessional Consultations for Women in Midwifery Care

Phillippi, Julia C.; Holley, Sharon L.; Thompson, Jennifer L.; Virostko, Kate; Bennett, Kelly

doi:10.1111/jmwh.12900

Cited by 5 publications

(3 citation statements)

References 16 publications

(12 reference statements)

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“…Collectively, these findings demonstrate the challenges of implementation science in maternity care within nations that are less than affluent. To manage sociocultural barriers, it can be helpful to adapt an intervention to a given context [113,140,159,161]-this might Mixed-methods 27 Case study 12 [139][140][141][142][143][144][145][146][147][148][149][150] Pre-post study 8 [151][152][153][154][155][156][157][158] Ethnography 6 [159][160][161][162][163][164] Cohort study 4 [165][166][167][168] Pilot-test 8 [169][170][171][172][173][174][175][176] Longitudinal survey 2 [177,178] Quasi-experimental 1 [179] Randomised controlled trial 2 [180,…”

Section: Theories Models and Framework: Absentmentioning

confidence: 99%

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Implementation science in maternity care: a scoping review

Piper

Coates

2021

Implementation Sci

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Background Despite wide recognition that clinical care should be informed by the best available evidence, this does not always occur. Despite a myriad of theories, models and frameworks to promote evidence-based population health, there is still a long way to go, particularly in maternity care. The aim of this study is to appraise the scientific study of methods to promote the systematic uptake of evidence-based interventions in maternity care. This is achieved by clarifying if and how implementation science theories, models, and frameworks are used. Methods To map relevant literature, a scoping review was conducted of articles published between January 2005 and December 2019, guided by Peters and colleagues’ (2015) approach. Specifically, the following academic databases were systematically searched to identify publications that presented findings on implementation science or the implementation process (rather than just the intervention effect): Business Source Complete; CINAHL Plus with Full Text; Health Business Elite; Health Source: Nursing/Academic Edition; Medline; PsycARTICLES; PsycINFO; and PubMed. Information about each study was extracted using a purposely designed data extraction form. Results Of the 1181 publications identified, 158 were included in this review. Most of these reported on factors that enabled implementation, including knowledge, training, service provider motivation, effective multilevel coordination, leadership and effective communication—yet there was limited expressed use of a theory, model or framework to guide implementation. Of the 158 publications, 144 solely reported on factors that helped and/or hindered implementation, while only 14 reported the use of a theory, model and/or framework. When a theory, model or framework was used, it typically guided data analysis or, to a lesser extent, the development of data collection tools—rather than for instance, the design of the study. Conclusion Given that models and frameworks can help to describe phenomenon, and theories can help to both describe and explain it, evidence-based maternity care might be promoted via the greater expressed use of these to ultimately inform implementation science. Specifically, advancing evidence-based maternity care, worldwide, will require the academic community to make greater explicit and judicious use of theories, models, and frameworks. Registration Registered with the Joanna Briggs Institute (registration number not provided).

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Section: Theories Models and Framework: Absentmentioning

confidence: 99%

“…This often involved identifying factors that might help or hinder implementation via stakeholder interviews or focus groups [126,127,171,178,182]. Many of these efforts informed policies, guidelines and/or implementation plans [116,124,125,172,182].…”

Section: Theories Models and Framework: Absentmentioning

confidence: 99%

Implementation science in maternity care: a scoping review

Piper

Coates

2021

Implementation Sci

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“…As a subjective process, authors acknowledge risk selection's complexity, determined by health care organisation, care providers and women [98]. Organisation characteristics include the number of care providers involved in care provision, location, communication, collaboration, and geography [30,58,69,93,[99][100][101][102][103][104][105][106][107][108][109][110][111][112][113]. Health care providers' perceived risk, knowledge, expertise, confidence, personal views, awareness and attitude, financial considerations and women's characteristics and preference, amongst others, are described as decisive factors [17][18][19]26,46,[86][87][88]95,99,100,105,107,109,[114][115][116][117][118].…”

Section: Risk Selection As a Practice: Detecting And Assessing Risk mentioning

confidence: 99%

Towards a better understanding of risk selection in maternal and newborn care: A systematic scoping review

et al. 2020

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Globally, millions of women and their children suffer due to preventable morbidity and mortality, associated with both underuse and overuse of maternal and newborn care. An effective system of risk selection that differentiates between what care should be provided and who should provide it is a global necessity to ensure women and children receive appropriate care, at the right place and the right time. Poor conceptualization of risk selection impedes evaluation and comparison of models of risk selection across various settings, which is necessary to improve maternal and newborn care. We conducted a scoping review to enhance the understanding of risk selection in maternal and newborn care. We included 210 papers, published over the past four decades, originating from 24 countries. Using inductive thematic analysis, we identified three main dimensions of risk selection: (1) risk selection as an organisational measure to optimally align women's and children's needs and resources, (2) risk selection as a practice to detect and assess risk and to make decisions about the delivery of care, and (3) risk selection as a tool to ensure safe care. We found that these three dimensions have three themes in common: risk selection (1) is viewed as both requiring and providing regulation, (2) has a provider centred focus and (3) aims to avoid underuse of care. Due to the methodological challenges of contextual diversity, the concept of risk selection needs clear indicators that capture the complexity of care to make crosssetting evaluation and comparison of risk selection possible. Moreover, a comprehensive understanding of risk selection needs to consider access disparity, women's needs, and unnecessary medicalization.

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