Women's Preferences for Birthing Hospital in Denmark: A Discrete Choice Experiment

Getting midwives back to hospitals: A discrete choice experiment

BACKGROUND

There is a severe global shortage of midwives, and the situation worsens when qualified professionals leave their jobs because of inadequate working conditions. Hospitals have increasing difficulties in filling vacancies for midwives. In the case of Germany, midwives tend to give up birth assistance after an average of seven years working in delivery rooms, which are usually led by physicians.

OBJECTIVE

We aim to provide concrete recommendations on encouraging qualified professionals to work in maternity wards by examining the job preferences of midwives who currently do not provide such services. These insights shall help policy makers and hospital managers to fill vacancies more quickly and provide adequate care to more women.

DESIGN

Discrete choice experiment.

SETTING(S)

Online survey promoted through email and social media to midwives in Germany.

PARTICIPANTS

415 midwives participated; we examine the subgroup of 241 midwives who do not offer birth assistance.

METHODS

We obtain individual parameter estimates through a multinominal logit analysis with hierarchical Bayes estimation techniques, calculate importance weights, and simulate uptake probabilities of different hypothetical job offers that include birth assistance.

RESULTS

Participants want to provide birth assistance but fiercely reject doing so under physicians' supervision. With a 15 % increase in income, however, 16 % would accept this least preferred setting. Forty-four percent, however, would choose to offer birth assistance if they could work in a midwife-led unit. An additional increase in income of 5 % (15 %) could even lead to uptake probabilities of 67 % (77 %).

CONCLUSIONS

There is a common understanding that midwife-led care is a safe and effective option for healthy women. Policy makers are advised to further extend their initial support for such units to fill vacancies quicker and enable comprehensive healthcare for more childbearing women.

TWEETABLE ABSTRACT

Midwife-led units help counter shortages: Midwives want to provide birth assistance but reject doing so under physicians' supervision.

Bypassing of nearest labor & delivery unit is contingent on rurality, wealth, and race

Patient decisions to bypass the closest labor & delivery (L&D) facility in favor of other birthing locations can have consequences for the provision of health care in rural and micropolitan areas as patient volumes decline and payer mixes change. Among 220 589 uncomplicated births in Iowa, we document characteristics of birth parents who bypass their closest birthing facility, show how this bypassing behavior results in changed travel times to delivery facilities across the rural/urban divide, and indicate the parts of the state where bypassing behavior is most prevalent. From 2013 to 2019, 55.2% of deliveries occurred in facilities that were further from birthing parents' residences than the closest L&D facility. Bypassing is associated with White, non-Hispanic race/ethnicity, and private insurance status. Although bypassing is least common among micropolitan birth parents, this group has the greatest travel burden to birthing facilities and exhibits increasing rates of bypassing over time. Perinatal quality improvement programs can target locations and populations where low-risk birthing parents can be encouraged to deliver close to home if medically appropriate, particularly in small towns and rural areas. This can potentially alleviate the risk of obstetric deserts by ensuring L&D units maintain patient volumes necessary to continue operations.

Current Practices for Accounting for Preference Heterogeneity in Health-Related Discrete Choice Experiments: A Systematic Review

BACKGROUND

Accounting for preference heterogeneity is a growing analytical practice in health-related discrete choice experiments (DCEs). As heterogeneity may be examined from different stakeholder perspectives with different methods, identifying the breadth of these methodological approaches and understanding the differences are major steps to provide guidance on good research practices.

OBJECTIVES

Our objective was to systematically summarize current practices that account for preference heterogeneity based on the published DCEs related to healthcare.

METHODS

This systematic review is part of the project led by the Professional Society for Health Economics and Outcomes Research (ISPOR) health preference research special interest group. The systematic review conducted systematic searches on the PubMed, OVID, and Web of Science databases, as well as on two recently published reviews, to identify articles. The review included health-related DCE articles published between 1 January 2000 and 30 March 2020. All the included articles also presented evidence on preference heterogeneity analysis based on either explained or unexplained factors or both.

RESULTS

Overall, 342 of the 2202 (16%) articles met the inclusion/exclusion criteria for extraction. The trend showed that analyses of preference heterogeneity increased substantially after 2010 and that such analyses mainly examined heterogeneity due to observable or unobservable factors in individual characteristics. Heterogeneity through observable differences (i.e., explained heterogeneity) is identified among 131 (40%) of the 342 articles and included one or more interactions between an attribute variable and an observable characteristic of the respondent. To capture unobserved heterogeneity (i.e., unexplained heterogeneity), the studies largely estimated either a mixed logit (n = 205, 60%) or a latent-class logit (n = 112, 32.7%) model. Few studies (n = 38, 11%) explored scale heterogeneity or heteroskedasticity.

CONCLUSIONS

Providing preference heterogeneity evidence in health-related DCEs has been found as an increasingly used practice among researchers. In recent studies, controlling for unexplained preference heterogeneity has been seen as a common practice rather than explained ones (e.g., interactions), yet a lack of providing methodological details has been observed in many studies that might impact the quality of analysis. As heterogeneity can be assessed from different stakeholder perspectives with different methods, researchers should become more technically pronounced to increase confidence in the results and improve the ability of decision makers to act on the preference evidence.

Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly used to elicit preferences for health and healthcare. Although many applications assume preferences are homogenous, there is a growing portfolio of methods to understand both explained (because of observed factors) and unexplained (latent) heterogeneity. Nevertheless, the selection of analytical methods can be challenging and little guidance is available. This study aimed to determine the state of practice in accounting for preference heterogeneity in the analysis of health-related DCEs, including the views and experiences of health preference researchers and an overview of the tools that are commonly used to elicit preferences.

METHODS

An online survey was developed and distributed among health preference researchers and nonhealth method experts, and a systematic review of the DCE literature in health was undertaken to explore the analytical methods used and summarize trends.

RESULTS

Most respondents (n = 59 of 70, 84%) agreed that accounting for preference heterogeneity provides a richer understanding of the data. Nevertheless, there was disagreement on how to account for heterogeneity; most (n = 60, 85%) stated that more guidance was needed. Notably, the majority (n = 41, 58%) raised concern about the increasing complexity of analytical methods. Of the 342 studies included in the review, half (n = 175, 51%) used a mixed logit with continuous distributions for the parameters, and a third (n = 110, 32%) used a latent class model.

CONCLUSIONS

Although there is agreement about the importance of accounting for preference heterogeneity, there are noticeable disagreements and concerns about best practices, resulting in a clear need for further analytical guidance.

Call (and pay) the midwife: A discrete choice experiment on mothers' preferences and their willingness to pay for midwifery care

BACKGROUND

Mothers in Germany are entitled to midwifery care; however, they face a lack of skilled professionals. While the reliability of the access to midwifery is of great public interest, we know little about clients' preferences.

OBJECTIVES

We conduct a discrete choice experiment to study preferences and willingness to accept copayment for the entire scope of midwifery care (pregnancy, delivery, and postnatal). Thereby, we aim to provide policy recommendations for priority settings in times of scarcity. Furthermore, we evaluate to what extent midwives' education matters to parents and assess the degree of support for the latest Midwifery Reform Act that transfers education from vocational schools to universities.

DESIGN

Discrete choice experiment with separated adaptive dual response.

SETTINGS

Online Survey promoted through Facebook to parents in Germany.

RESPONDENTS

2080 respondents completed the experiment. They all have or are expecting at least one natural child, mainly born between 2018 and 2020 (87%). The average respondent is female (99%), 33 years old, with a university degree (50%).

METHODS

We use a d-optimal fractional factorial design and obtain individual parameter estimates through a Multinomial Logit analysis with Hierarchical Bayes estimation techniques. We calculate willingness to pay and importance weights and simulate uptake probabilities for different packages of care. To avoid extreme choice behavior, we apply separated adaptive dual response.

RESULTS

Home visits during the postnatal phase are most important (importance weight 50%); online support is demanded when no personal support is available. We find that 1:1 care during delivery is highly preferred, but one midwife supporting two women intrapartum is still acceptable. The midwife´s education plays a minor role with an importance weight of 3%; however, we find a preference for midwives trained at vocational schools rather than at universities.

CONCLUSIONS

In times of scarcity, postnatal care in the form of home visits should be prioritized over pregnancy counseling, and online services should be promoted as an add-on but not as a substitute for personal support. There is a high level of willingness to accept co-financing to ensure the availability of services usually covered by health insurance.

Exploring women's preferences for birth settings in England: A discrete choice experiment

Objective

To explore pregnant women’s preferences for birth setting in England.

Design

Labelled discrete choice experiment (DCE).

Setting

Online survey.

Sample

Pregnant women recruited through social media and an online panel.

Methods

We developed a DCE to assess women’s preferences for four hypothetical birth settings based on seven attributes: reputation, continuity of care, distance from home, time to see a doctor, partner able to stay overnight, chance of straightforward birth and safety for baby. We used a mixed logit model, with setting modelled as an alternative-specific constant, and conducted a scenario analysis to evaluate the impact of changes in attribute levels on uptake of birth settings.

Main outcome measures

Women’s preferences for birth setting.

Results

257 pregnant women completed the DCE. All birth setting attributes, except ‘time to see doctor’, were significant in women’s choice (p<0.05). There was significant heterogeneity in preferences for some attributes. Changes to levels for ‘safety for the baby’ and ‘partner able to stay overnight’ were associated with larger changes from baseline uptake of birth setting. If the preferences identified were translated into the real-world context up to a third of those who reported planning birth in an obstetric unit might choose a midwifery unit assuming universal access to all settings, and knowledge of the differences between settings.

Conclusions

We found that ‘safety for the baby’, ‘chance of a straightforward birth’ and ‘can the woman’s partner stay overnight following birth’ were particularly important in women’s preferences for hypothetical birth setting. If all birth settings were available to women and they were aware of the differences between them, it is likely that more low risk women who currently plan birth in OUs might choose a midwifery unit.