Eline Frouke de Vries

Background: Glioblastoma is an incurable form of brain cancer with a median overall survival of 1.5 years. Despite its progressive nature and high symptom burden, palliative care is not consistently integrated in routine glioblastoma care. Early integration of palliative care better addresses the needs of patients and caregivers, improves quality of life, and reduces inappropriate care in the end-of-life phase. This study aims to design an integrated care pathway to support the early integration of palliative care for patients with glioblastoma. Methods: We used a design thinking approach, engaging stakeholders from neuro-oncology, specialist palliative care, primary care, district nursing, healthcare administration, health insurance, health economics, and patient advocacy. The process consisted of thirteen informal interviews (with healthcare professionals, patients, and caregivers), six expert meetings, and two workshops. Results: First, we mapped existing routine glioblastoma care and identified perceived barriers to early palliative care integration, including variations in advance care planning (ACP) timing, clinicians’ hesitation, unclear referral criteria to specialist palliative care, suboptimal care coordination, and limited experience with glioblastoma in the primary care setting. Second, iterative prototyping led to the development of a care pathway with key components: initiation of ACP by the lead clinician within six weeks of diagnosis, integrated multidisciplinary team meetings for complex cases, ongoing coordination, clear referral triggers for specialist palliative care, and structured caregiver care. Conclusions: The co-designed pathway provides a feasible model for integrating early palliative care into routine care for patients with glioblastoma. Future steps include implementation and evaluation of the care pathway and development of a payment model.

Introduction: Observational data are increasingly seen as a valuable source for integrated care research. Especially since the growing availability of routinely collected data and quasi-experimental methods. The aim of this paper is to describe the potentials and challenges when using observational data for integrated maternity care research, based on our experience from developing and working with the Data-InfrAstructure for ParEnts and childRen (DIAPER). Methods and Results: We provide a description of DIAPER, which is a linked data-infrastructure on the individual level based on maternity care claims data, quality and utilization of maternity care and data from municipal registries, covering the life course from preconception to adulthood. We then discuss potentials and practical applications of DIAPER such as to evaluate alternative payment models for integrated maternity care, to set the policy agenda regarding postpartum care, to provide insights into value of care and into provider variation, and to evaluate (policy) interventions designed to promote and support integrated maternity care. This is relevant for several stakeholders: policy makers, payers, providers and clients/patients. Based on experiences with DIAPER, we identify remaining challenges: missing data sources (especially self-reported outcomes), suboptimal quality of data, privacy concerns and potential biases introduced during data linkage, and describe how these challenges were tackled within the applications of DIAPER. Conclusions: With DIAPER we demonstrated that using observational data can be of added value for integrated care research, but also that challenges remain. It is essential to keep exploring and developing the possibilities of observational data and continue the discussions in the scientific community. Learning from each other’s successes and failures will be critical.

Early detection of vulnerability during or before pregnancy can contribute to optimizing the first 1000 days, a crucial period for children’s development and health. We aimed to identify classes of vulnerability among pregnant women in the Netherlands using pre-pregnancy data on a wide range of social risk and protective factors, and validate these classes against the risk of adverse outcomes. We conducted a latent class analysis based on 42 variables derived from nationwide observational data sources and self-reported data. Variables included individual, socioeconomic, lifestyle, psychosocial and household characteristics, self-reported health, healthcare utilization, life-events and living conditions. We compared classes in relation to adverse outcomes using logistic regression analyses. In the study population of 4172 women, we identified five latent classes. The largest ‘healthy and socioeconomically stable’-class [n = 2040 (48.9%)] mostly shared protective factors, such as paid work and positively perceived health. The classes ‘high care utilization’ [n = 485 (11.6%)], ‘socioeconomic vulnerability’ [n = 395 (9.5%)] and ‘psychosocial vulnerability’ [n = 1005 (24.0%)] were characterized by risk factors limited to one specific domain and protective factors in others. Women classified into the ‘multidimensional vulnerability’-class [n = 250 (6.0%)] shared multiple risk factors in different domains (psychosocial, medical and socioeconomic risk factors). Multidimensional vulnerability was associated with adverse outcomes, such as premature birth and caesarean section. Co-existence of multiple risk factors in various domains is associated with adverse outcomes for mother and child. Early detection of vulnerability and strategies to improve parental health and well-being might benefit from focussing on different domains and combining medical and social care and support.

An effective system of risk selection is a global necessity to ensure women and children receive appropriate care at the right time and at the right place. To gain more insight into the existing models of risk selection (MRS), we explored the distribution of different MRS across regions in The Netherlands, and examined the relation between MRS and primary care midwives’ and obstetricians’ satisfaction with different MRS. We conducted a nationwide survey amongst all primary midwifery care practices and obstetrics departments. The questionnaire was completed by 312 (55%) primary midwifery care practices and 53 (72%) obstetrics departments. We identified three MRS, which were distributed differently across regions: (1) primary care midwives assess risk and initiate a consultation or transfer of care without discussing this first with the obstetrician, (2) primary care midwives assess risk and make decisions about consultation or transfer of care collaboratively with obstetricians, and (3) models with other characteristics. Across these MRS, variations exist in several aspects, including the routine involvement of the obstetrician in the care of healthy pregnant women. We found no significant difference between MRS and professionals’ level of satisfaction. An evidence- and value-based approach is recommended in the pursuit of the optimal organization of risk selection. This requires further research into associations between MRS and maternal and perinatal outcomes, professional payment methods, resource allocation, and the experiences of women and care professionals.

Background: Healthcare costs related to ESRD are well-described, but broader societal costs of ESRD are less known. This study aimed to estimate patient and family costs, including informal care costs and out-of-pocket costs, and costs due to productivity loss related to ESRD, for patients receiving dialysis and living with a kidney transplant, using a bottom-up approach. Methods: A total of 655 patients were asked to complete a digital questionnaire consisting of two standardised instruments (iMCQ and iPCQ) from November 2016 through January 2017. We applied a retrospective bottom-up cost estimation by combining data from the questionnaire with unit prices from the Dutch costing manual. Results: Our study sample consisted of 230 patients, of which 165 were kidney transplant recipients and 65 received dialysis. The total annual non-healthcare related costs were estimated at €8284 (SD: €14,266) for transplant recipients and €23,488 (SD: €39,434) for dialysis patients. Costs due to productivity loss contributed most to the total non-healthcare costs (66% for transplant recipients and 65% for dialysis patients), followed by informal care costs (26% resp. 29%) and out-of-pocket costs, such as medication and travel expenses (8% resp. 6%). Conclusion: By exposing patient, family and productivity costs, our study revealed that dialysis and transplantation are not only costly within the healthcare system, but also incur high non-healthcare costs (18–23% resp. 35% of the total societal costs). It is important to reveal these types of non-healthcare costs in order to understand the full burden of ESRD for society and the potential impact of new therapies.

Although effects of alternative payment models on health outcomes and health spending are unclear, they are increasingly implemented in maternity care. We aimed to provide an overview of alternative payment models implemented in maternity care, describing their key design elements among which the type of APM, the care providers that participate in the model, populations and care services that are included and the applied risk mitigation strategies. Next to that, we made an inventory of the empirical evidence on the effects of APMs on maternal and neonatal health outcomes and spending on maternity care. We searched PubMed, Embase and Scopus databases for articles published from January 2007 through October 2020. Search key words included ‘alternative payment model’, ‘value based payment model’, ‘obstetric’, ‘maternity’. English or Dutch language articles were included if they described or empirically evaluated initiatives implementing alternative payment models in maternity care in high-income countries. Additional relevant documents were identified through reference tracking. We systematically analyzed the initiatives found and examined the evidence regarding health outcomes and health spending. The process was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to ensure validity and reliability. We identified 17 initiatives that implemented alternative payment models in maternity care. Thirteen in the United States, two in the United Kingdom, one in New Zealand and one in the Netherlands. Within these initiatives three types of alternative payment models were implemented; pay-for-performance (n = 2), shared savings models (n = 7) and bundled payment models (n = 8). Alternative payment models that shifted more financial accountability towards providers seemed to include more strategies that mitigated those risks. Risk mitigation strategies were applied to the included population, included services or at the level of total expenditures. Of these seventeen initiatives, we found four empirical effect studies published in peer-reviewed journals. Three of them were of moderate quality and one weak. Two studies described an association of the alternative payment model with an improvement of specific health outcomes and two studies described a reduction in medical spending. This study shows that key design elements of alternative payment models including risk mitigation strategies vary highly. Risk mitigation strategies seem to be relevant tools to increase APM uptake and protect providers from (initially) bearing too much (perceived) financial risk. Empirical evidence on the effects of APMs on health outcomes and spending is still limited. A clear definition of key design elements and a further, in-depth, understanding of key design elements and how they operate into different health settings is required to shape payment reform that aligns with its goals.

Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases 18 th De Vries; Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases provides more detailed insight into the causes of regional variation in healthcare spending. Future policies on which interventions could be targeted can benefit on these insights.