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Abstract Background The Alpe-DPD study (NCT02324452) demonstrated that prospective genotyping and dose-individualization using four alleles in DPYD (DPYD*2A/rs3918290, c.1236G > A/rs75017182, c.2846A > T/rs67376798 and c.1679 T > G/rs56038477) can mitigate the risk of severe fluoropyrimidine toxicity. However, this could not prevent all toxicities. The goal of this study was to identify additional genetic variants, both inside and outside DPYD, that may contribute to fluoropyrimidine toxicity. Methods Biospecimens and data from the Alpe-DPD study were used. Exon sequencing was performed to identify risk variants inside DPYD. In silico and in vitro analyses were used to classify DPYD variants. A genome-wide association study (GWAS) with severe fluoropyrimidine-related toxicity was performed to identify variants outside DPYD. Association with severe toxicity was assessed using matched-pair analyses for the exon sequencing and logistic, Cox, and ordinal regression analyses for GWAS. Results Twenty-four non-synonymous, frameshift, and splice site DPYD variants were detected in ten of 986 patients. Seven of these variants (c.1670C > T, c.1913 T > C, c.1925 T > C, c.506delC, c.731A > C, c.1740 + 1G > T, c.763 − 2A > G) were predicted to be deleterious. The carriers of either of these variants showed a trend towards a 2.14-fold (95% CI, 0.41–11.3, P = 0.388) increased risk of severe toxicity compared to matched controls (N = 30). After GWAS of 942 patients, no individual single nucleotide polymorphisms achieved genome-wide significance (P ≤ 5 × 10−8), however, five variants were suggestive of association (P

Abstract Background An innovative, integrative care model for people with Parkinson (PRIME Parkinson) has gradually been implemented in a selected region of the Netherlands since 2021. A prospective evaluation of this model (PRIME-NL study) was initiated in parallel, spanning the year prior to implementation (baseline) and the implementation period. Following publication of the original study protocol, the COVID-19 crisis delayed implementation of the full PRIME Parkinson care model by two years and hampered the recruitment of study participants. Objective To describe which methodological adjustments were made to the study protocol because of these developments. Methods We compare various outcomes between a region where PRIME Parkinson care was implemented (innovation region) versus the rest of the Netherlands (usual care region). We use healthcare claims data of virtually all people with Parkinson in the Netherlands and annual questionnaires in a representative subsample of 984 people with Parkinson, 566 caregivers and 192 healthcare professionals. Four major methodological adjustments had to be made since publication of the original protocol. First, we extended the evaluation period by two years. Second, we incorporated annual process measures of the stage of implementation of the new care model. Third, we introduced a real-time iterative feedback loop of interim results to relevant stakeholders. Fourth, we updated the statistical analysis plan. Discussion This manuscript provides transparency in how the design and analyses of the evaluation study had to be adapted to control for external influences in a dynamic environment, including eruption of the COVID-19 crisis. Our solutions could serve as a template for evaluating other complex healthcare interventions in a dynamic environment.

Summary: The primary objective of the prospective, randomized, multicenter, phase 3 biomarker Microarray Analysis in breast cancer to Taylor Adjuvant Drugs Or Regimens trial (MATADOR: ISRCTN61893718) is to generate a gene expression profile that can predict benefit from either docetaxel, doxorubicin, and cyclophosphamide (TAC) or dose-dense scheduled doxorubicin and cyclophosphamide (ddAC). Patients with a pT1-3, pN0-3 tumor were randomized 1:1 between ddAC and TAC. The primary endpoint was a gene profile-treatment interaction for recurrence-free survival (RFS). We observed 117 RFS events in 664 patients with a median follow-up of 7 years. Hallmark gene set analyses showed significant association between enrichment in immune-related gene expression and favorable outcome after TAC in hormone receptor-negative, human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) (triple-negative breast cancer [TNBC]). We validated this association in TNBC patients treated with TAC on H&E slides; stromal tumor-infiltrating lymphocytes (sTILs) ≥20% was associated with longer RFS (hazard ratio 0.18, p = 0.01), while in patients treated with ddAC no difference in RFS was seen (hazard ratio 0.92, p = 0.86, pinteraction = 0.02).

This study aims to impact the responsible management practices of factories in the Ready-Made Garment (RMG) sector in Bangladesh. Collaborative research with our main partner - the BGMEA University for Fashion and Technology (BUFT) - on responsible management has contributed to the embedding of ethical practices in the RMG sector. More specifically, in a first stage of this program, the collaborative knowledge development is ingrained in the degree and executive education programs of BUFT - impacting about a quarter of the professionals entering the RMG sector in Bangladesh - and has informed the practices and policies of professional bodies, such as BGMEA in Bangladesh, MODINT in the Netherlands and the International Apparel Federation (IAF). Furthermore, in a second stage of this program, research on sustainability hot spots in the RMG value chain has influenced decision-making of the European Committee in relation to their sustainability policies. It substantially advanced the understanding of how European non-development policies and regulations aimed at private and public market actors contribute to or undermine sustainable development policies. The project delivered practical tools and innovative regulatory reform proposals with substantial potential for greater policy-coherence for development, thereby contributing to an integral approach focusing on a shift towards responsibility.

Huntington's disease (HD) is a progressive neurodegenerative disease affecting motor and cognitive abilities. Multiple studies have found white matter anomalies in HD-affected humans and animal models of HD. The identification of sensitive white-matter-based biomarkers in HD animal models will be important in understanding disease mechanisms and testing the efficacy of therapeutic interventions. Here we investigated the progression of white matter deficits in the knock-in zQ175DN heterozygous (HET) mouse model of HD at 3, 6 and 11 months of age (M), reflecting different states of phenotypic progression. We compared findings from traditional diffusion tensor imaging (DTI) and advanced fixel-based analysis (FBA) diffusion metrics for their sensitivity in detecting white matter anomalies in the striatum, motor cortex, and segments of the corpus callosum. FBA metrics revealed progressive and widespread reductions of fiber cross-section and fiber density in myelinated bundles of HET mice. The corpus callosum genu was the most affected structure in HET mice at 6 and 11 M based on the DTI and FBA metrics, while the striatum showed the earliest progressive differences starting at 3 M based on the FBA metrics. Overall, FBA metrics detected earlier and more prominent alterations in myelinated fiber bundles compared to the DTI metrics. Luxol fast blue staining showed no loss in myelin density, indicating that diffusion anomalies could not be explained by myelin reduction but diffusion anomalies in HET mice were accompanied by increased levels of neurofilament light chain protein at 11 M. Altogether, our findings reveal progressive alterations in myelinated fiber bundles that can be measured using diffusion MRI, representing a candidate noninvasive imaging biomarker to study phenotype progression and the efficacy of therapeutic interventions in zQ175DN mice. Moreover, our study exposed higher sensitivity of FBA than DTI metrics, suggesting a potential benefit of adopting these advanced metrics in other contexts, including biomarker development in humans.

Background Hospital strategies aimed at increasing quality of care and simultaneously reducing costs show potential to improve healthcare, but knowledge on real-world effectiveness is limited. In 2014, two Dutch hospitals introduced such quality-driven strategies. Our aim was to evaluate contexts, mechanisms, and outcomes of both strategies using multiple perspectives.Methods We conducted a mixed methods evaluation. Four streams of data were collected and analysed: (1) semistructured interviewing of 62 stakeholders, such as medical doctors, nurses, managers, general practitioners (GPs), and consultants; (2) financial statements of both organisations and other hospitals in the Netherlands (counterfactual); (3) national database of quality indicators, and patient-reported experiences; and (4) existing material on strategy development and effects.Results Both strategies resulted in a relative decrease in volume of care within the hospital, while quality of care has not been affected negatively. One hospital failed to cut operating costs sufficiently, resulting in declining profit margins. We identified six main mechanisms that impacted these outcomes: (1) Quality-improvement projects spur change and commitment; (2) increased coordination between hospital and primary care leads to substitution of care; (3) insufficient use of data and support hinder quality improvement; (4) scaling down hospital facilities is required to convert volume reductions to cost savings; (5) shared savings through global budgets lead to shared efforts between payer and hospital; and (6) financial security for physicians facilitates shift towards quality-driven care.Conclusion This integrated analysis of mixed data sources demonstrated that the institution-wide nature of the strategies has induced a shift from a focus on production towards quality of care. Longer-term (financial) sustainability of hospital strategies aimed at decelerating production growth requires significant efforts in reducing fixed costs. This strategy poses financial risks for the hospital if operating costs are insufficiently reduced or if payer alignment is compromised.

Background People with dementia are increasingly living at home, relying on primary care providers for most healthcare needs. Suboptimal collaboration and communication between providers could cause inefficiencies and worse patient outcomes. Innovative strategies are needed to address this growing disease burden and rising healthcare costs. The DementiaNet programme, a community care network approach targeted at patients with dementia in the Netherlands, has been shown to improve patient’s quality of care. However, very little is known about the impact of DementiaNet on admission risks and healthcare costs. This study addresses this knowledge gap.Methods A longitudinal cohort analysis was performed, using medical and long-term care claims data from 38 525 patients between 2015-2019. The primary outcomes were risk of hospital admission and annual total healthcare costs. Mixed-model regression analyses were used to identify changes in outcomes.Results Patients who received care from a DementiaNet community care network showed a general trend in lower risk of admission for all types of admissions studied (ie, hospital, emergency ward, intensive care, crisis, and nursing home). Also, the intervention group showed a significant reduction of 12% in nursing days (relative risk [RR] 0.88; 95% CI: 0.77–0.96). No significant differences were found for total healthcare costs. However, we found effects in two sub-elements of total healthcare costs, being a decrease of 19.7% (95% CI: 7.7%–30.2%) in annual hospital costs and an increase of 10.2% (95% CI: 2.3%–18.6%) in annual primary care costs.Conclusion Our study indicates that DementiaNet’s community care network approach may reduce admission risks for patients with dementia over a long-term period of five years. This is accompanied by a decrease in nursing days and savings in hospital care that exceed increased primary care costs. This improvement in integrated dementia care supports wider scale implementation and evaluation of these networks.

Background Purchasing systems aim to improve resource allocation in healthcare markets. The Netherlands is characterized by four different purchasing systems: managed competition in the hospital market, a non-competitive single payer system for long-term care (LTC), municipal procurement for home care and social services, and selfprocurement via personal budgets. We hypothesize that managed competition and competitive payer reforms boost reallocations of provider market share by means of active purchasing, ie, redistributing funds from high-quality providers to low-quality providers.Methods We define a Market Activity Index (MAI) as the sum of funds reallocated between providers annually. Provider expenditures are extracted from provider financial statements between 2006 and 2019. We compare MAI in six healthcare sectors under four different purchasing systems, adjusting for reforms, and market entry/exit. Next, we perform in-depth analyses on the hospital market. Using multivariate linear regressions, we relate reallocations to selective contracting, provider quality, and market characteristics.Results No difference was found between reallocations in the hospital care market under managed competition and the non-competitive single payer LTC (MAI between 2% and 3%), while MAI was markedly higher under procurement by municipalities and personal budget holders (between 5% and 15%). While competitive reforms temporarily increased MAI, no structural effects were found. Relatively low hospital MAI could not be explained by market characteristics. Furthermore, the extent of selective contracting or hospital quality differences had no significant effects on reallocations of funds.Conclusion Dutch managed competition and competitive purchaser reforms had no discernible effect on reallocations of funds between providers. This casts doubt on the mechanisms advocated by managed competition and active purchasing to improve allocative efficiency.

Introduction: This study aimed to assess the effect of integrated palliative care (IPC) on potentially inappropriate end- of-life care and healthcare-costs in the last 30 days of life in the Netherlands. Methods: Nationwide health-insurance claims data were used to assess potentially inappropriate end-of-life care (≥2 emergency room visits; ≥2 hospital admissions; >14 days hospitalization; chemotherapy; ICU admission; hospital death) and healthcare-costs in all deceased adults in IPC regions pre- and post- implementation and in those receiving IPC compared to a 1:2 matched control group. Results: In regions providing IPC deceased adults (n = 37,468) received significantly less potentially inappropriate end-of-life care post-implementation compared to pre-implementation (26.5% vs 27.9%; p < 0.05). Deceased adults who received IPC (n = 210) also received significantly less potentially inappropriate end-of-life care compared to a matched control group (14.8% vs 28.3%; p < 0.05). Mean hospital costs significantly decreased for deceased adults who received IPC (€2,817), while mean costs increased for general practitioner services (€311) and home care (€1,632). Discussion: These results highlight the importance of implementation of integrated palliative care and suitable payment. Further research in a larger sample is needed. Conclusion: This study shows less potentially inappropriate end-of-life care and a shift in healthcare costs from hospital to general practitioner and home care with IPC. Academic Disciplines: Medicine; Nursing; Health economics Research Sample: Deceased adults

Arterial spin labeling (ASL) is a promising, non-invasive perfusion magnetic resonance imaging technique for quantifying cerebral blood flow (CBF). Unfortunately, ASL suffers from an inherently low signal-to-noise ratio (SNR) and spatial resolution, undermining its potential. Increasing spatial resolution without significantly sacrificing SNR or scan time represents a critical challenge towards routine clinical use. In this work, we propose a model-based super-resolution reconstruction (SRR) method with joint motion estimation that breaks the traditional SNR/resolution/scan-time trade-off. From a set of differently oriented 2D multi-slice pseudo-continuous ASL images with a low through-plane resolution, 3D-isotropic, high resolution, quantitative CBF maps are estimated using a Bayesian approach. Experiments on both synthetic whole brain phantom data, and on in vivo brain data, show that the proposed SRR Bayesian estimation framework outperforms state-of-the-art ASL quantification.

Academic Medical Centres (AMCs) are large organisations with a complex structure due to various intertwined missions and (public) roles that can be conflicting. This complexity makes it difficult to adapt to changing circumstances. The literature points to the use of business models to address such challenges. A business model describes the resources, processes, and cost assumptions that an organisation makes in order to the delivery of a unique value proposition to a customer/patient. Do AMC business operations managers actually use business models to address challenges and operate in a way that enables AMCs to adapt to changing circumstances? This study explored whether the use of a business model is a starting point for bringing about change in AMC operations. A case study design was considered appropriate to explore the knowledge and experience of business models among business operations managers of Dutch AMCs. Through purposive sampling, participants were invited to participate in a questionnaire to provide in-depth and detailed information about the use of business models in AMCs. Our research showed that a business model can support the complex organisation of an AMC, but the design and use of business models varies. In general, respondents attribute more potential to the use of a business model than they experience in daily practice. The majority consider a business model to be suitable for bringing about change, but see it only sparingly used in their own AMC. This is the first study to provide some initial insights into the use of business models in Dutch AMCs. We can assume that improvements are possible in order to optimise the change potential of business models in AMCs worldwide. In order to successfully implement an innovative business model, the interpretation of the concept of a business model and the creation of a framework of preconditions should be taken into account. Healthcare providers, policy makers or researchers should explicitly identify the environment in which the model will operate. In particular, by identifying the level of readiness for change readiness at all levels of the organisation.

IntroductionAcademic medical centres (AMCs) are designed to perform multiple tasks within a single organisation. This institutional complexity gives rise to intricate governance challenges and promotes incrementalism and muddling.MethodIn this study, we hypothesised that radical change could provide a solution to the current incrementalism and we explored the conditions under which such changes could or could not be achieved.ResultsWe conducted unstructured interviews with various high-level stakeholders and identified issues that negatively affected the governance of Dutch AMCs, which include: 1) negative undercurrents and unspoken issues due to conflicts of interests, 2) organisational complexity due to relationships with a university and academic medical specialists, 3) lack of sufficient government direction, 4) competition between AMCs due to perverse systemic incentives, 5) different interests, focus, and organisational culture, 6) concentration of care, which does not always lead to enhanced quality and efficiency as the provision of less complex care is of utmost importance for education and research, 7) the infeasibility of public and regional functions of an AMC, 8) the inefficiency of managing three core tasks within the same organisation and, 9) healthcare market regulation.DiscussionOur hypothesis that radical change offers a solution to the current incrementalism in AMCs could not be adequately explored. Indeed, our exploration of the conditions under which radical change could potentially take place revealed that there are factors currently at play that make a substantive conversation between stakeholders about radical change difficult, if not impossible. The results also show that the government is in a position to take the lead and create conditions that foster mutual trust and common interests among AMCs, as well as between AMCs and other hospitals.

Abstract Background Affordability and accessibility of hospital care are under pressure. Research on hospital care financing focuses primarily on incentives in the financial system outside the hospital. It is notable that little is known about (incentives in) internal funding in hospitals. Therefore, our study focuses on the budget allocation in hospitals: the distribution model. Based on our hypothesis that the reimbursement and distribution models in hospitals might interact, we gain knowledge about-, and insight into, the interaction of different reimbursement and distribution models used in Dutch hospitals, and how they affect the financial output of hospital care. Methods An online survey with 22 questions was conducted among financial senior management as an expert group in 49 Dutch hospitals. Results Ultimately, 38 of 49 approached experts fully completed the survey, which amounts to 78% of the hospitals we approached and 60% of all Dutch hospitals. The results on the reimbursement model indicate price * volume with adjusted prices above a maximum cap as the most common dominant contract type. On the internal distribution model, 75–80% of the experts reported incremental budgeting as the dominant budgeting method. Results on the interaction between the reimbursement and the distribution model show that both general and specific changes in contract agreements are only partially incorporated in hospital budgets. In 28 out of 31 hospitals with self-employed medical specialists, a relation is reported between the reimbursement model and the contracts with the Medical Consultant Group(s) in which the medical specialists are united. Conclusions Our results in Dutch setting indicate a limited interaction between the reimbursement model and the distribution model. This lack of congruence between both models might limit the desired effects of incentives in contractual agreements aimed at the financial output. This applies to different reimbursement and distribution models. Further research into the various interactions and incentives, as visualized in our conceptual framework, could result in evidence-based advice for achieving affordable and accessible hospital care.

Abstract Background Hospital care organization, structured around medical specialties and focused on the separate treatment of individual organ systems, is challenged by the increasing prevalence of multimorbidity. To support the hospitals’ realization of multidisciplinary care, we hypothesized that using machine learning on clinical data helps to identify groups of medical specialties who are simultaneously involved in hospital care for patients with multimorbidity. Methods We conducted a cross-sectional study of patients in a Dutch general hospital and used a fuzzy c-means clustering algorithm for the analysis. We explored the patients’ membership degrees in each cluster to identify subgroups of medical specialties that provide care to the same patients with multimorbidity. We used retrospectively collected electronic health record data from 2017. We extracted data from 22,133 patients aged ≥18 years who had received outpatient clinical care for two or more chronic and/ or oncological diagnoses. Results We found six clusters of medical specialties and identified 22 subgroups. The clusters were labeled based on the specialties that most characterized them: 1. dermatology/ plastic surgery, 2. six specialties (gynecology/ rheumatology/ orthopedic surgery/ urology/ gastroenterology/ otorhinolaryngology), 3. pulmonology, 4. internal medicine/ cardiology/ geriatrics, 5. neurology/ physiatry (rehabilitation)/ anesthesiology, and 6. internal medicine. Most patients had a full or dominant membership to one of these clusters of medical specialties (11 subgroups), whereas fewer patients had a membership to two clusters. The prevalence of specific diagnosis groups, patient characteristics, and healthcare utilization differed between subgroups. Conclusion Our study shows that clusters and subgroups of medical specialties simultaneously involved in hospital care for patients with multimorbidity can be identified with fuzzy c-means cluster analysis using clinical data. Clusters and subgroups differed regarding the involved medical specialties, diagnoses, patient characteristics, and healthcare utilization. With this strategy, hospitals and medical specialists can further analyze which subgroups are target populations that might benefit from improved multidisciplinary collaboration.

Abstract Background Many countries are looking for ways to increase nurse practitioner (NP) and physician assistant/associate (PA) deployment. Countries are seeking to tackle the pressing issues of increasing healthcare demand, healthcare costs, and medical doctor shortages. This article provides insights into the potential impact of various policy measures on NP/PA workforce development in the Netherlands. Methods We applied a multimethod approach study using three methods: 1) a review of government policies, 2) surveys on NP/PA workforce characteristics, and 3) surveys on intake in NP/PA training programs. Results Until 2012, the annual intake into NP and PA training programs was comparable to the number of subsidized training places. In 2012, a 131% increase in intake coincided with extending the legal scope of practice of NPs and PAs and substantially increasing subsidized NP/PA training places. However, in 2013, the intake of NP and PA trainees decreased by 23% and 24%, respectively. The intake decreased in hospitals, (nursing) home care, and mental healthcare, coinciding with fiscal austerity in these sectors. We found that other policies, such as legal acknowledgment, reimbursement, and funding platforms and research, do not consistently coincide with NP/PA training and employment trends. The ratios of NPs and PAs to medical doctors increased substantially in all healthcare sectors from 3.5 and 1.0 per 100 full-time equivalents in medical doctors in 2012 to 11.0 and 3.9 in 2022, respectively. For NPs, the ratios vary between 2.5 per 100 full-time equivalents in medical doctors in primary care and 41.9 in mental healthcare. PA-medical doctor ratios range from 1.6 per 100 full-time equivalents in medical doctors in primary care to 5.8 in hospital care. Conclusions This study reveals that specific policies coincided with NP and PA workforce growth. Sudden and severe fiscal austerity coincided with declining NP/PA training intake. Furthermore, governmental training subsidies coincided and were likely associated with NP/PA workforce growth. Other policy measures did not consistently coincide with trends in intake in NP/PA training or employment. The role of extending the scope of practice remains to be determined. The skill mix is shifting toward an increasing share of medical care provided by NPs and PAs in all healthcare sectors.

Image warping is a popular tool for modeling deformation and motion in digital images. Inversion of such models requires two related operators: adjoint and differentiated image warping. Many applications rely on these operators, often through ad hoc and approximate implementations, which leads to a suboptimal quality and convergence speed, and hinders development of and comparison across different applications.In this work, we present an open-source image warping toolbox called ImWIP (Image Warping for Inverse Problems) that overcomes these issues. It implements differentiable image warping operators, together with their exact adjoints and derivatives (up to floating point errors). ImWIP is demonstrated on examples from X-ray computed tomography and magnetic resonance imaging, and is shown to improve both reconstruction quality and convergence speed compared to state-of-the-art warping methods.

BackgroundChronic heart failure (HF) is a chronic disease affecting more than 64 million people worldwide, with an increasing prevalence and a high burden on individual patients and society. Telemonitoring may be able to mitigate some of this burden by increasing self-management and preventing use of the health care system. However, it is unknown to what degree telemonitoring has been adopted by hospitals and if the use of telemonitoring is associated with certain patient characteristics. Insight into the dissemination of this technology among hospitals and patients may inform strategies for further adoption. ObjectiveWe aimed to explore the use of telemonitoring among hospitals in the Netherlands and to identify patient characteristics associated with the use of telemonitoring for HF. MethodsWe performed a retrospective cohort study based on routinely collected health care claim data in the Netherlands. Descriptive analyses were used to gain insight in the adoption of telemonitoring for HF among hospitals in 2019. We used logistic multiple regression analyses to explore the associations between patient characteristics and telemonitoring use. ResultsLess than half (31/84, 37%) of all included hospitals had claims for telemonitoring, and 20% (17/84) of hospitals had more than 10 patients with telemonitoring claims. Within these 17 hospitals, a total of 7040 patients were treated for HF in 2019, of whom 5.8% (409/7040) incurred a telemonitoring claim. Odds ratios (ORs) for using telemonitoring were higher for male patients (adjusted OR 1.90, 95% CI 1.50-2.41) and patients with previous hospital treatment for HF (adjusted OR 1.76, 95% CI 1.39-2.24). ORs were lower for higher age categories and were lowest for the highest age category, that is, patients older than 80 years (OR 0.30, 95% CI 0.21-0.44) compared to the reference age category (18-59 years). Socioeconomic status, degree of multimorbidity, and excessive polypharmacy were not associated with the use of telemonitoring. ConclusionsThe use of reimbursed telemonitoring for HF was limited up to 2019, and our results suggest that large variation exists among hospitals. A lack of adoption is therefore not only due to a lack of diffusion among hospitals but also due to a lack of scaling up within hospitals that already deploy telemonitoring. Future studies should therefore focus on both kinds of adoption and how to facilitate these processes. Older patients, female patients, and patients with no previous hospital treatment for HF were less likely to use telemonitoring for HF. This shows that some patient groups are not served as much by telemonitoring as other patient groups. The underlying mechanism of the reported associations should be identified in order to gain a deeper understanding of telemonitoring use among different patient groups.

Abstract Background Cancer rates and expenditures are increasing, resulting in debates on the exact value of this care. Perspectives on what exactly constitutes worthwhile values differ. This study aims to explore all values–elements regarding new oncological treatments for patients with cancer and all stakeholders involved and to assess their implications in different decision‐making procedures. Method Thirty‐one individual in‐depth interviews were conducted with different stakeholders to identify values within oncology. A focus group with seven experts was performed to explore its possible implications in decision‐making procedures. Results The overarching themes of values identified were impact on daily life and future, costs for patients and loved ones, quality of life, impact on loved ones, societal impact and quality of treatments. The expert panel revealed that the extended exploration of values that matter to patients is deemed useful in patient‐level decision‐making, information provision, patient empowerment and support during and after treatment. For national reimbursement decisions, implications for the broad range of values seems less clear. Conclusion Clinical values are not the only ones that matter to oncological patients and the stakeholders in the field. We found a much broader range of values. Proper recognition of values that count might add to patient‐level decision‐making, but implications for reimbursement decisions are less clear. The results could be useful to guide clinicians and policymakers when it comes to decision‐making in oncology. Making more explicit which values counts for whom guarantees a more systematic approach to decision‐making on all levels.

rs-fMRI is used to investigate human brain connectivity changes induced by prolonged microgravity in cosmonauts before and after spaceflight, with both persistent and reversible location specific changes in connectivity being observed.

Objective Noninvasive telemonitoring aims to improve healthcare for patients with chronic heart failure (HF) by reducing hospitalizations and improving patient experiences. Yet, sustainable adoption seems to be limited. Therefore, the goal of our study is to gain insight in the processes that support sustainable adoption of telemonitoring for patients with HF. Methods We conducted semi-structured interviews with 25 stakeholders that were involved with the adoption of telemonitoring, such as healthcare professionals, policymakers and healthcare insurers. We analyzed the interviews by using a combination of open-coding and the themes of the Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability framework. Results We found that telemonitoring projects have moved beyond initial pilot phases despite a high level of complexity on multiple topics. The patient selection, the business case, the evidence, the aims of telemonitoring, integration of telemonitoring in the care pathway, reimbursement, and future centralization were items that yielded different and sometimes contradictory opinions. Conclusions This study showed that the sustainable adoption of telemonitoring for HF is a complex endeavor. Different aims and perspectives play an important role in the patient selection, design, evaluations and envisioned futures of telemonitoring. High conviction among participants of the added value that telemonitoring may support further adoption of telemonitoring. Structural evaluations will be needed to guide cyclical improvement and adapt programs to employ telemonitoring in such a manner that it contributes to collectively supported aims.

Background A lack of knowledge exists on real world hospital strategies that seek to improve quality, while reducing or containing costs. The aim of this study is to identify hospitals that have implemented such strategies and determine factors influencing the implementation.Methods We searched PubMed, EMBASE, Web of Science, Cochrane Library and EconLit for case studies on hospitalwide strategies aiming to increase quality and reduce costs. Additionally, grey literature databases, Google and selected websites were searched. We used inductive coding to identify factors relating to implementation of the strategies.Results The literature search identified 4198 papers, of which our included 17 papers describe 19 case studies from five countries, mostly from the United States. To accomplish their goals, hospitals use different management strategies, such as continuous quality improvement (CQI), clinical pathways, Lean, Six Sigma and value-based healthcare (VBHC). Reported effects on both quality and costs are predominantly positive. Factors identified to be relevant for implementation were categorized in eleven themes: (1) strategy, (2) leadership, (3) engagement, (4) reorganization, (5) finances, (6) data and information technology (IT), (7) projects, (8) support, (9) skill development, (10) culture, and (11) communication. Recurring barriers for implementation are a lack of physician engagement, insufficient financial support, and poor data collection.Conclusion Hospital strategies that explicitly aim to provide high quality care at low costs may be a promising option to bend the cost curve while improving quality. We found a limited amount of studies, and varying contexts across case studies. This underlines the importance of integrated evaluation research. When implementing a quality enhancing, cost reducing strategy, we recommend considering eleven conditions for successful implementation that we were able to derive from the literature.

Background Optimal care for Parkinson’s disease (PD) requires coordination and collaboration between providers within a complex care network. Individual patients have personalised networks of their own providers, creating a unique informal network of providers who treat (‘share’) the same patient. These ‘patient-sharing networks’ differ in density, ie, the number of identical patients they share. Denser patient-sharing networks might reflect better care provision, since providers who share many patients might have made efforts to improve their mutual care delivery. We evaluated whether the density of these patient-sharing networks affects patient outcomes and costs. Methods We analysed medical claims data from all PD patients in the Netherlands between 2012 and 2016. We focused on seven professional disciplines that are commonly involved in Parkinson care. We calculated for each patient the density score: the average number of patients that each patient’s providers shared. Density scores could range from 1.00 (which might reflect poor collaboration) to 83.00 (which might reflect better collaboration). This score was also calculated at the hospital level by averaging the scores for all patients belonging to a specific hospital. Using logistic and linear regression analyses we estimated the relationship between density scores and health outcomes, healthcare utilization, and healthcare costs. Results The average density score varied considerably (average 6.7, SD 8.2). Adjusted for confounders, higher density scores were associated with a lower risk of PD-related complications (odds ratio [OR]: 0.901; P < .001) and with lower healthcare costs (coefficients: -0.018, P = .005). Higher density scores were associated with more frequent involvement of neurologists (coefficient 0.068), physiotherapists (coefficient 0.052) and occupational therapists (coefficient 0.048) (P values all

The notion of utility gained a strong foothold in health economics over the last decades. However, the concept of health utility has not yet been decisively or irrefutably defined and the definitions that exist often do not take into account the current state of psychological literature. This perspective paper shows that the current definition of health utility emphasizes decision-making processes, deploys personal preferences, assumes psychological egoism, and attempts to objectively and cardinally measure utility. However, these foundational axioms that underly the current definition of health utility are not necessarily in concurrence with the current state of psychological literature. Due to these perceived shortcomings of the current health utility definition, it may be beneficial to redefine the concept of health utility in accordance with the current state of psychological literature. In order to develop such a revised definition of health utility the commonly deployed formula (Eidos = Genos + Diaphora) originating from Aristotle’s metaphysics is applied. The revised definition of health utility proposed in this perspective paper alludes to health utility as ‘the subjective value, expressed in terms of perceived pain or pleasure, that is attributed to the cognitive, affective and conative experience of one’s own physical, mental and social health state, which is determined through self-reflection and interaction with significant others’. Although this revised definition does neither replace nor supersede other conceptualizations of health utility, it may serve as a refreshing avenue for further discussion and could, eventually, support policymakers and health economists in operationalizing and measuring health utility in an even more accurate and veracious manner.

Diffusion weighted MRI is an indispensable tool for routine patient screening and diagnostics of pathology. Recently, several deep learning methods have been proposed to quantify diffusion parameters, but poor generalisation to new data prevents broader use of these methods, as they require retraining of the neural network for each new scan protocol. In this work, we present the dtiRIM, a new deep learning method for Diffusion Tensor Imaging (DTI) based on the Recurrent Inference Machines. Thanks to its ability to learn how to solve inverse problems and to use the diffusion tensor model to promote data consistency, the dtiRIM can generalise to variations in the acquisition settings. This enables a single trained network to produce high quality tensor estimates for a variety of cases. We performed extensive validation of our method using simulation and in vivo data, and compared it to the Iterated Weighted Linear Least Squares (IWLLS), the approach of the state-of-the-art MRTrix3 software, and to an implementation of the Maximum Likelihood Estimator (MLE). Our results show that dtiRIM predictions present low dependency on tissue properties, anatomy and scanning parameters, with results comparable to or better than both IWLLS and MLE. Further, we demonstrate that a single dtiRIM model can be used for a diversity of data sets without significant loss in quality, representing, to our knowledge, the first generalisable deep learning based solver for DTI.