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.

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.

Pricing through health apps generated data-Digital dividend as a game changer: Discrete choice experiment.

OBJECTIVES: The objective of this paper is to study under which circumstances wearable and health app users would accept a compensation payment, namely a digital dividend, to share their self-tracked health data. METHODS: We conducted a discrete choice experiment alternative, a separated adaptive dual response. We chose this approach to reduce extreme response behavior, considering the emotionally-charged topic of health data sales, and to measure willingness to accept. Previous experiments in lab settings led to demands for high monetary compensation. After a first online survey and two pre-studies, we validated four attributes for the final online study: monthly bonus payment, stakeholder handling the data (e.g., health insurer, pharmaceutical or medical device companies, universities), type of data, and data sales to third parties. We used a random utility framework to evaluate individual choice preferences. To test the expected prices of the main study for robustness, we assigned respondents randomly to one of two identical questionnaires with varying price ranges. RESULTS: Over a period of three weeks, 842 respondents participated in the main survey, and 272 respondents participated in the second survey. The participants considered transparency about data processing and no further data sales to third parties as very important to the decision to share data with different stakeholders, as well as adequate monetary compensation. Price expectations resulting from the experiment were high; pharmaceutical and medical device companies would have to pay an average digital dividend of 237.30€/month for patient generated health data of all types. We also observed an anchor effect, which means that people formed price expectations during the process and not ex ante. We found a bimodal distribution between relatively low price expectations and relatively high price expectations, which shows that personal data selling is a divisive societal issue. However, the results indicate that a digital dividend could be an accepted economic incentive system to gather large-scale, self-tracked data for research and development purposes. After the COVID-19 crisis, price expectations might change due to public sensitization to the need for big data research on patient generated health data. CONCLUSION: A continuing success of existing data donation models is highly unlikely. The health care sector needs to develop transparency and trust in data processing. An adequate digital dividend could be an effective long-term measure to convince a diverse and large group of people to share high-quality, continuous data for research purposes.