Transforming the Quality Maternal Newborn Care Framework into an index (QMNCFi) to measure the quality of maternity care

BACKGROUND: The Quality Maternal and Newborn Care (QMNC) Framework describes the care that childbearing women and newborn infants need in all settings. It comprises five components and was designed for use in planning, workforce development, and resource allocation, aimed at improving the quality and cost effectiveness of maternal and newborn care globally. The purpose of this paper is to describe the first phase of a project designed to transform the Framework into a quantitative tool for service user assessment of the quality of maternity care. METHODS: Each component of the original Framework content was developed into a draft service user questionnaire and distributed to an expert panel, drawn from a range of low-, middle-, and high-resource countries. The panel consisted of five Framework authors, nine midwife researchers, six midwives, and five service user (consumer) advocates. Two rounds of discussion and revision were undertaken with the expert panel who commented on the importance, relevance and clarity of questions, and then on their necessity, wording, and order. A third round involved two experts in survey design. RESULTS: Following 24 responses in the first round, the questions were refined and returned to the panel. After incorporating the second-round comments from 16 experts, the survey was then sent to two experts in questionnaire design and construction. Face validity was affirmed through this consultative process. CONCLUSIONS: Despite Covid-19 pandemic-related restrictions, this robust iterative consultative process with an international expert panel has resulted in the prototype QMNC Framework index (QMNCFi)-a questionnaire designed for use in diverse settings to assess the quality of maternity care. The QMNCFi's psychometric properties are now being tested in an international online survey

Exploring the qualities of midwifery-led continuity of care in Australia (MiLCCA) using the quality maternal and newborn care framework

© 2019 Problem: Midwifery-led continuity of care has well documented evidence of benefits for mothers and babies, however uptake of these models by Australian maternity services has been slow. Background: It is estimated that only 10% of women have access to midwifery-led continuity of care in Australia. The Quality Maternal Newborn Care (QMNC) Framework has been developed as a way to implement and upscale health systems that meet the needs of childbearing women and their infants. The Framework can be used to explore the qualities of existing maternity services. Aim: We aimed to use the QMNC Framework to explore the qualities of midwifery-led continuity of care in two distinct settings in Australia with recommendations for replication of the model in similar settings. Methods: Data were collected from services users and service providers via focus groups. Thematic analysis was used to develop initial findings that were then mapped back to the QMNC Framework. Findings: Good quality care was facilitated by Fostering connection, Providing flexibility for women and midwives and Having a sense of choice and control. Barriers to the provision of quality care were: Contested care and Needing more preparation for unexpected outcomes. Discussion: Midwifery-led continuity of carer models shift the power dynamic from a hierarchical one, to one of equality between women and midwives facilitating informed decision making. There are ongoing issues with collaboration between general practice, obstetrics and midwifery. Organisations have a responsibility to address the challenges of contested care and to prepare women for all possible outcomes to ensure women experience the best quality care as described in the framework. Conclusion: The QMNC Framework is a useful tool for exploring the facilitators and barriers to the widespread provision of midwifery-led continuity of care

Adapting the Quality Maternal and Newborn Care (QMNC) Framework to evaluate models of antenatal care:A pilot study

<div><p>Background</p><p>Recent evidence indicates that continuity models of maternity care result in improved clinical and psychosocial outcomes, but their causal mechanisms are poorly understood. The recent Lancet Series on Midwifery’s Quality Maternal and Newborn Care Framework describes five components of quality care and their associated characteristics. As an initial step in developing this Framework into an evaluation toolkit, we transformed its components and characteristics into a topic guide to assess stakeholder perceptions and experiences of care provided and received. The main purpose of this study was to assess the feasibility of this process.</p><p>Methods</p><p>We conducted twelve focus groups in two Scottish health board areas with 13 pregnant women, 18 new mothers, 26 midwives and 12 obstetricians who had experience of a range of different models of maternity care. Transcripts were analysed using a six-phase approach of thematic analysis. We mapped the identified themes and sub-themes back to the Framework.</p><p>Results</p><p>The emerging themes and sub-themes demonstrated the feasibility of using the QMNC framework as a data collection tool, and as a lens for analysing the data. Of the four emerging themes, only Organisation Culture / Work Structure’ mapped directly to a single Framework component. The others—‘Relationships’; ‘Information and support’; and ‘Uncertainty’–mapped to between two and five components, illustrating the interconnectedness of the Framework’s components. Some negative sub-themes mirrored positive Framework characteristics of care. Some re-phrasing and re-ordering of the topic guides in later focus groups ensured we could cover all aspects of the Framework adequately.</p><p>Conclusion</p><p>Adapting the Quality Maternal and Newborn Care Framework enabled us to focus on aspects of care which worked well and which didn’t work well for these key stakeholders. Identifying ‘what works for whom and why’ in different models of care is a necessary step in reinforcing and replicating the most effective models of care.</p></div

Using the Quality Maternal and Newborn Care Framework to evaluate women's experiences of different models of care:A qualitative study

© 2019 Elsevier Ltd Objective: There is evidence that continuity of care - increasingly a focus of maternity care policy in the UK - contributes to improved outcomes. However, uncertainty remains about which models of care are most effective in which circumstances, and why this is. A plausible explanation is grounded in the idea that the continuity elements of care contribute to and reinforce best quality care. The Quality Maternal and Newborn Care Framework describes the components and characteristics of quality care. As a first step in developing a maternity care evaluation toolkit, we adapted this Framework to see if it could be used to evaluate perceptions and experiences of different models of care. Design: A qualitative comparative enquiry using focus groups. From a six-phase thematic analysis, we first derived then compared the principal sub-themes from the focus groups and mapped these to the original Framework. Setting: Two health boards in Scotland. Participants: Pregnant women, new mothers, midwives and obstetricians who had experience of various models of maternity care. This paper reports findings from the pregnant women and new mothers. Results: These are presented in two parts: the seven focus groups with pregnant women and new mothers are reported in this paper; the five focus groups with midwives and obstetricians in our accompanying paper. Those using the maternity services had experience of caseloading midwifery, ‘modified universal provision’ and ‘high risk’ models of maternity care. While women from all groups shared certain perspectives, those with experience of caseloading midwifery were consistently positive, reporting positive relationships, tailored care and effective communication. Women experiencing other models of care, especially the modified universal provision model, tended to report more negative relational experiences: lack of information, lack of tailored care, and anxiety and confusion. Timing of the focus group (i.e. during pregnancy or after the birth) appeared to make little difference to responses. Mapping responses to the Framework's characteristics of care was straightforward; mapping also showed how the Framework's components of care are interlinked. Key conclusions: Our adaptation of the Quality Maternal and Newborn Care Framework as a data collection tool allowed us to compare women with experience of different models of care, and relational factors were identifiable in many responses. Positive responses were found in all models but were most emphasised in the caseloading midwifery model, suggesting that the experience of caseloading continuity and its relational elements is highly valued. While further work is required to identify if this can be linked to improved clinical outcomes, we have established that the Quality Maternal and Newborn Care Framework can be adapted as an exploratory tool for assessing perceptions and experiences of maternity care

Using a quality care framework to evaluate user and provider experiences of maternity care:A comparative study

© 2019 Objective: The Quality Maternal and Newborn Care Framework describes the components and characteristics of quality care and emphasises relational and continuity elements. Continuity of care is increasingly a focus of maternity care policy in the United Kingdom. While some outcomes have been shown to be improved, there is uncertainty about why certain models of care are more effective. Our overall objective is to develop a maternity care evaluation toolkit which incorporates this Framework along with other outcome evaluations. An initial step in developing this toolkit was to use the adapted Framework to evaluate perceptions and experiences of maternity care. Our specific objective in this study was to test this adapted Framework in a series of focus groups with key stakeholders, and to compare findings between different groups. Findings related to service users (pregnant women and new mothers) are reported in our accompanying paper; this paper presents findings from focus groups with service providers (midwives and obstetricians), and then compares user and provider perspectives. Design: A qualitative comparative enquiry involving three focus groups with 26 midwives (eight newly qualified; eight working in a community midwifery unit; and ten senior tertiary-based) and two focus groups with twelve obstetricians of all grades. We used a six-phase thematic analysis to derive then compare the focus groups’ principal sub-themes; we then mapped these to the original Quality Maternal and Newborn Care Framework and compared these service providers’ responses with those from the pregnant women and new mothers. Setting: Two health boards in Scotland. Participants: Midwives and obstetricians who had experience of various models of maternity care. Findings: There were significant areas of overlap in their perceptions of providing maternity care. All groups reported ‘limited resources and time’; the community midwifery unit and senior midwives and one group of obstetricians provided a critique of the system. Achieving tailored care was acknowledged as a problem by the senior midwives and one group of obstetricians. Only obstetricians discussed strategies for improvement. The newly qualified midwives were most positive in their responses. There was both overlap and contrast when comparing the views of service users and providers. We found most agreement when participants discussed some of the Framework's characteristics of care in negative terms, such as (in) accessible care, (lack of) adequate resources, and (absence of) tailored care. Key Conclusions: Being able firstly to map the participants’ responses to the Quality Maternal and Newborn Care Framework, and then to identify strengths and gaps in the provision of quality maternity care, suggests to us that the Framework, derived as it is from a comprehensive analysis of the global evidence on quality care, can indeed be used to inform an evaluation toolkit. While aware that we cannot generalise from this limited qualitative study, we are currently undertaking similar work in other countries by which we hope to confirm our findings and further develop the toolkit

Randomised pragmatic waitlist trial with process evaluation investigating the effectiveness of peer support after brain injury: protocol.

Traumatic brain injury (TBI) is an important global health problem. Formal service provision fails to address the ongoing needs of people with TBI and their family in the context of a social and relational process of learning to live with and adapt to life after TBI. Our feasibility study reported peer support after TBI is acceptable to both mentors and mentees with reported benefits indicating a high potential for effectiveness and likelihood of improving outcomes for both mentees and their mentors. To (a) test the effectiveness of a peer support intervention for improving participation, health and well-being outcomes after TBI and (b) determine key process variables relating to intervention, context and implementation to underpin an evidence-based framework for ongoing service provision. A randomised pragmatic waitlist trial with process evaluation. Mentee participants (n=46) will be included if they have moderate or severe TBI and are no more than 18 months post-injury. Mentor participants (n=18) will be people with TBI up to 6 years after injury, who were discharged from inpatient rehabilitation at least 1 year prior. The primary outcome will be mentee participation, measured using the Impact on Participation and Autonomy questionnaire after 22 weeks. Primary analysis of the continuous variables will be analysis of covariance with baseline measurement as a covariate and randomised treatment as the main explanatory predictor variable at 22 weeks. Process evaluation will include analysis of intervention-related data and qualitative data collected from mentors and service coordinators. Data synthesis will inform the development of a service framework for future implementation. Ethics approval has been obtained from the New Zealand Health and Disability Ethics Committee (19/NTB/82) and Auckland University of Technology Ethics Committee (19/345). Dissemination of findings will be via traditional academic routes including publication in internationally recognised peer-reviewed journals. ACTRN12619001002178. [Abstract copyright: © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

The Impact of the Financial Crisis and Natural Catastrophes on CAT Bonds

CAT bonds are important instruments for the insurance of catastrophe risk. Due to a low degree of deal standardization, there is uncertainty about the determination of the CAT bond premium. In addition, it is not apparent how CAT bonds react after the financial crisis or a natural catastrophe. We empirically verify which factors determine the CAT bond premium and what effects arise if a catastrophe occurs. On a broad data set using secondary market premiums we find strong evidence that the recent financial crisis has a significant impact on CAT bond premiums. Furthermore, we find that after hurricane Katrina an increased risk perception for hurricanes can be observed

Making sense of recovery after traumatic brain injury through a peer mentoring intervention:a qualitative exploration

Objective To explore the acceptability of peer mentoring for people with a traumatic brain injury (TBI) in New Zealand. Design This is a qualitative descriptive study exploring the experiences reported by mentees and mentors taking part in a feasibility study of peer mentoring. Interviews with five mentees and six mentors were carried out. Data were analysed using conventional content analysis. Setting The first mentoring session took place predischarge from the rehabilitation unit. The remaining five sessions took place in mentees' homes or community as preferred. Participants Twelve people with TBI took part: Six mentees (with moderate to severe TBI; aged 18-46) paired with six mentors (moderate to severe TBI >12 months previously; aged 21-59). Pairing occurred before mentee discharge from postacute inpatient brain injury rehabilitation. Mentors had been discharged from rehabilitation following a TBI between 1 and 5 years previously. Intervention The peer mentoring programme consisted of up to six face-to-face sessions between a mentee and a mentor over a 6-month period. The sessions focused on building rapport, exploring hopes for and supporting participation after discharge through further meetings and supported community activities. Results Data were synthesised into one overarching theme: Making sense of recovery. This occurred through the sharing of experiences and stories; was pivotal to the mentoring relationship; and appeared to benefit both mentees and mentors. Mentors were perceived as valued experts because of their personal experience of injury and recovery, and could provide support in ways that were different from that provided by clinicians or family members. Mentors required support to manage the uncertainties inherent in the role. Conclusions The insight mentors developed through their own lived experience established them as a trusted and credible source of hope and support for people re-engaging in the community post-TBI. These findings indicate the potential for mentoring to result in positive outcomes

Unobtrusive monitoring of behavior and movement patterns to detect clinical depression severity level via smartphone

The number of individuals with mental disorders is increasing and they are commonly found among individuals who avoid social interaction and like to live alone. Amongst such mental health disorders is depression which is both common and serious. The present paper introduces a method to assess the depression level of an individual using a smartphone by monitoring their daily activities. The time domain characteristics from a smartphone acceleration sensor were used alongside a vector machine algorithm to classify physical activities. Additionally, the geographical location information was clustered using a smartphone GPS sensor to simplify movement patterns. A total of 12 features were extracted from individuals’ physical activity and movement patterns and were analyzed alongside their weekly depression scores using the nine-item Patient Health Questionnaire. Using a wrapper feature selection method, a subset of features was selected and applied to a linear regression model to estimate the depression score. The support vector machine algorithm was then used to classify the depression severity level among individuals (absence, moderate, severe) and had an accuracy of 87.2% in severe depression cases which outperformed other classification models including the k-nearest neighbor and artificial neural network. This method of identifying depression is a cost-effective solution for long-term use and can monitor individuals for depression without invading their personal space or creating other day-to-day disturbances