Jeroen Nathan Struijs

Maternal postpartum health problems can persist well beyond the conventional six-week postpartum care period. No nationwide studies have combined large-scale electronic health records (EHRs) from perinatal and general practice (GP) care linking long-term health problems to birth mode. We aim to examine how birth mode (spontaneous vaginal, instrumental vaginal, and caesarean section) influences the frequency and hazard of maternal physical and psychological health problems in GP care from six weeks to three years postpartum. In this observational population-based cohort study we linked Dutch perinatal EHRs (2014–2020) to GP EHRs (2015–2023), including women who gave birth to a term singleton. Health problems were retrieved from GP EHR’s using International Classification of Primary Care codes and GP notes, the latter analysed with natural language processing. Women were stratified by parity. Frequencies of the most common health problems were calculated. Cox proportional hazard models estimated crude and adjusted associations between birth mode and postpartum health problems, using spontaneous vaginal birth as the reference.In total, 10 628 primiparous and 11 719 multiparous women were included. Frequencies of common health problems (e.g., urinary tract infection, abdominal pains or cramps, tiredness or weakness, and psychological or -social issues) did not differ substantially between birth modes. Adjusted for confounders, caesarean section and instrumental vaginal birth were linked to significantly increased hazards of dyspareunia. Caesarean section was additionally associated with an elevated anaemia hazard but reduced hazards of urinary incontinence and ureterovaginal prolapse compared to spontaneous vaginal birth. We showed maternal health problems persisting up to three years postpartum and vary by birth mode. These findings may raise awareness among mothers and care providers of key long-term maternal health problems, underscoring the need for a new paradigm of prolonged postpartum care.

Recognizing and addressing vulnerability during the first thousand days of life can prevent health inequities. It is necessary to determine the best data for predicting multidimensional vulnerability (i.e. risk factors to vulnerability across different domains and a lack of protective factors) at population level to understand national prevalence and trends. This study aimed to (1) assess the feasibility of predicting multidimensional vulnerability during pregnancy using routinely collected data, (2) explore potential improvement of these predictions by adding self-reported data on health, well-being, and lifestyle, and (3) identify the most relevant predictors. The study was conducted using Dutch nationwide routinely collected data and self-reported Public Health Monitor data. First, to predict multidimensional vulnerability using routinely collected data, we used random forest (RF) and considered the area under the curve (AUC) and F1 measure to assess RF model performance. To validate results, sensitivity analyses (XGBoost and Lasso) were done. Second, we gradually added self-reported data to predictions. Third, we explored the RF model’s variable importance. The initial RF model could distinguish between those with and without multidimensional vulnerability (AUC = 0.98). The model was able to correctly predict multidimensional vulnerability in most cases, but there was also misclassification (F1 measure = 0.70). Adding self-reported data improved RF model performance (e.g. F1 measure = 0.80 after adding perceived health). The strongest predictors concerned self-reported health, socioeconomic characteristics, and healthcare expenditures and utilization. It seems possible to predict multidimensional vulnerability using routinely collected data that is readily available. However, adding self-reported data can improve predictions.

Objective: Population health management (PHM) is a promising data-driven approach to address the challenges faced by health care systems worldwide. Although Business Intelligence (BI) systems are known to be relevant for a data-driven approach, the usage for PHM is limited in its elaboration. To explore available scientific publications, a systematic review guided by PRISMA was conducted of mature BI initiatives to investigate their decision contexts and BI capabilities. Materials and Methods: PubMed, Embase, and Web of Science were searched for articles published from January 2012 through November 2023. Articles were included if they described a (potential) BI system for PHM goals. Additional relevant publications were identified through snowballing. Technological Readiness Levels were evaluated to select mature initiatives from the 29 initiatives found. From the 11 most mature systems the decision context (eg, patient identification, risk stratification) and BI capabilities (eg, data warehouse, linked biobank) were extracted. Results: The initiatives found are highly fragmented in decision context and BI capabilities. Varied terminology is used and much information is missing. Impact on population’s health is currently limited for most initiatives. Care Link, CommunityRx, and Gesundes Kinzigtal currently stand out in aligning BI capabilities with their decision contexts. Discussion and Conclusion: PHM is a data-driven approach that requires a coherent data strategy and understanding of decision contexts and user needs. Effective BI capabilities depend on this understanding. Designing public-private partnerships to protect intellectual property while enabling rapid knowledge development is crucial. Development of a framework is proposed for systematic knowledge building.

Introduction: Population Health Management (PHM) focusses on keeping the whole population as healthy as possible. As such, it could be a promising approach for long-term health improvement in type 2 diabetes. This scoping review aimed to examine the extent to which and how PHM is used in the care for people with type 2 diabetes. Methods: PubMed, Web of Science, and Embase were searched between January 2000 and September 2021 for papers on self-reported PHM initiatives for type 2 diabetes. Eligible initiatives were described using the analytical framework for PHM. Results: In total, 25 studies regarding 18 PHM initiatives for type 2 diabetes populations were included. There is considerable variation in whether and how the PHM steps are operationalized in existing PHM initiatives. Population identification, impact evaluation, and quality improvement processes were generally part of the PHM initiatives. Triple Aim assessment and risk stratification actions were scarce or explained in little detail. Moreover, cross-sector integration is key in PHM but scarce in practice. Conclusion: Operationalization of PHM in practice is limited compared to the PHM steps described in the analytical framework. Extended risk stratification and integration efforts would contribute to whole-person care and further health improvements within the population.

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.

Background: In 2018, the Dutch government initiated the Solid Start program to provide each child the best start in life. The program focuses on the crucial first thousand days of life, which span from preconception to a child’s second birthday, and has a specific focus towards (future) parents and young children in vulnerable situations. A key program element is improving collaboration between the medical and social sector by creating Solid Start coalitions. This study aimed to describe the implementation of the Dutch Solid Start program, in order to learn for future practice and policy. Specifically, this paper describes to what extent Solid Start is implemented within municipalities and outlines stakeholders’ experiences with the implementation of Solid Start and the associated cross-sectoral collaboration. Methods: Quantitative and qualitative data were collected from 2019 until 2021. Questionnaires were sent to all 352 Dutch municipalities and analyzed using descriptive statistics. Qualitative data were obtained through focus group discussions(n = 6) and semi-structured interviews(n = 19) with representatives of care and support organizations, knowledge institutes and professional associations, Solid Start project leaders, advisors, municipal officials, researchers, clients and experts-by-experience. Qualitative data were analyzed using the Rainbow Model of Integrated Care. Results: Findings indicated progress in the development of Solid Start coalitions(n = 40 in 2019, n = 140 in 2021), and an increase in cross-sectoral collaboration. According to the stakeholders, initiating Solid Start increased the sense of urgency concerning the importance of the first thousand days and stimulated professionals from various backgrounds to get to know each other, resulting in more collaborative agreements on cross-sectoral care provision. Important elements mentioned for effective collaboration within coalitions were an active coordinator as driving force, and a shared societal goal. However, stakeholders experienced that Solid Start is not yet fully incorporated into all professionals’ everyday practice. Most common barriers for collaboration related to systemic integration at macro-level, including limited resources and collaboration-inhibiting regulations. Stakeholders emphasized the importance of ensuring Solid Start and mentioned various needs, including sustainable funding, supportive regulations, responsiveness to stakeholders’ needs, ongoing knowledge development, and client involvement. Conclusion: Solid Start, as a national program with strong local focus, has led to various incremental changes that supported cross-sectoral collaboration to improve care during the first thousand days, without major transformations of systemic structures. However, to ensure the program’s sustainability, needs such as sustainable funding should be addressed.

Objective: To evaluate the effectiveness and cost-effectiveness of offering the combined lifestyle programme “Healthy Heart”, addressing overweight, diet, physical activity, smoking and alcohol, to improve lifestyle behaviour and reduce cardiovascular risk. Design: A practice-based non-randomised stepped-wedge cluster trial with two-year follow-up. Outcomes were obtained via questionnaires and routine care data. A cost–utility analysis was performed. During the intervention period, “Healthy Heart” was offered during regular cardiovascular risk management consultations in primary care in The Hague, The Netherlands. The period prior to the intervention period served as the control period. Results: In total, 511 participants (control) and 276 (intervention) with a high cardiovascular risk were included (overall mean ± SD age 65.0 ± 9.6; women: 56%). During the intervention period, 40 persons (15%) participated in the Healthy Heart programme. Adjusted outcomes did not differ between the control and intervention period after 3–6 months and 12–24 months. Intervention versus control (95% CI) 3–6 months: weight: β −0.5 (−1.08–0.05); SBP β 0.15 (−2.70–2.99); LDL-cholesterol β 0.07 (−0.22–0.35); HDL-cholesterol β −0.03 (−0.10–0.05); physical activity β 38 (−97–171); diet β 0.95 (−0.93–2.83); alcohol OR 0.81 (0.44–1.49); quit smoking OR 2.54 (0.45–14.24). Results were similar for 12–24 months. Mean QALYs and mean costs of cardiovascular care were comparable over the full study period (mean difference (95% CI) QALYs: −0.10 (−0.20; 0.002); costs: EUR 106 (−80; 293)). Conclusions: For both the shorter (3–6 months) and longer term (12–24 months), offering the Healthy Heart programme to high-cardiovascular-risk patients did not improve their lifestyle behaviour nor cardiovascular risk and was not cost-effective on a population level.

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.