Explore the vast range of titles available.

The Patient-Reported Outcomes Measurement Information System (PROMIS) is a universally applicable set of instruments, including item banks, short forms and computer adaptive tests (CATs), measuring patient-reported health across different patient populations. PROMIS CATs are highly efficient and the use in practice is considered feasible with little administration time, offering standardized and routine patient monitoring. Before an item bank can be used as CAT, the psychometric properties of the item bank have to be examined. Therefore, the objective was to assess the psychometric properties of the Dutch-Flemish PROMIS Physical Function item bank (DF-PROMIS-PF) in Dutch patients receiving physical therapy. Cross-sectional study. 805 patients >18 years, who received any kind of physical therapy in primary care in the past year, completed the full DF-PROMIS-PF (121 items). Unidimensionality was examined by Confirmatory Factor Analysis and local dependence and monotonicity were evaluated. A Graded Response Model was fitted. Construct validity was examined with correlations between DF-PROMIS-PF T-scores and scores on two legacy instruments (SF-36 Health Survey Physical Functioning scale [SF36-PF10] and the Health Assessment Questionnaire Disability-Index [HAQ-DI]). Reliability (standard errors of theta) was assessed. The results for unidimensionality were mixed (scaled CFI = 0.924, TLI = 0.923, RMSEA = 0.045, 1th factor explained 61.5% of variance). Some local dependence was found (8.2% of item pairs). The item bank showed a broad coverage of the physical function construct (threshold-parameters range: -4.28-2.33) and good construct validity (correlation with SF36-PF10 = 0.84 and HAQ-DI = -0.85). Furthermore, the DF-PROMIS-PF showed greater reliability over a broader score-range than the SF36-PF10 and HAQ-DI. The psychometric properties of the DF-PROMIS-PF item bank are sufficient. The DF-PROMIS-PF can now be used as short forms or CAT to measure the level of physical function of physiotherapy patients.

The current coronavirus disease 2019 (COVID-19) pandemic is testing healthcare systems like never before and all efforts are now being put into controlling the COVID-19 crisis. We witness increasing morbidity, delivery systems that sometimes are on the brink of collapse, and some shameless rent seeking. However, besides all the challenges, there are also possibilities that are opening up. In this perspective, we focus on lessons from COVID-19 to increase the sustainability of health systems. If we catch the opportunities, the crisis might very well be a policy window for positive reforms. We describe the positive opportunities that the COVID-19 crisis has opened to reduce the sources of waste for our health systems: failures of care delivery, failures of care coordination, overtreatment or low-value care, administrative complexity, pricing failures and fraud and abuse. We argue that current events can canalize some very needy reforms to make our systems more sustainable. As always, political policy windows are temporarily open, and so swift action is needed, otherwise the opportunity will pass and the vested interests will come back to pursue their own agendas. Professionals can play a key role in this as well.

Besides improving the quality of care, quality improvement initiatives often also intend to produce cost savings. An example is prehabilitation, which can reduce complication rates and the length of stay in the hospital. However, the process from utilization reductions to actual societal cost savings remains uncertain in practice. Our aim was to identify barriers and facilitators throughout this process. We used the implementation of prehabilitation in a Dutch hospital as a test case. We held 20 semi-structured interviews between June and November 2023. Eighteen stakeholders were affiliated with the hospital and two with different health insurers. Nine interviews were held face-to-face and 11 via Microsoft Teams. The interviews were recorded and transcribed. The first transcripts were inductively coded by two authors, the subsequent transcripts by one and checked by another. Differences were resolved through discussion. We identified 20 barriers and 23 facilitators across four stages: reducing capacity, reducing departmental expenses, reducing hospital expenses and reducing insurer expenses. All participants expected that the excess capacity will be used for other priorities. This was perceived as highly valuable and as an efficiency gain. Other barriers to capture savings included the fear of losing resilience, flexibility, status and revenue. Misalignment between service contracts among hospitals and insurers can hinder the ability to financially incentivize cost reductions. Additionally, some contract types can hinder the transfer of hospital savings to insurers. Identified facilitators included shared savings agreements, an explicit strategy targeting all stages, and labor shortage, among others. This study systematically describes barriers and facilitators that prevent translating quality improvement initiatives into societal cost savings. Stakeholders expect that any saved capacity will be used for other priorities, including providing care due to the increasing demand. Capturing any cash savings does not occur automatically, emphasizing the need for a strategy targeting all stages.

A national clinical registry was established in the Netherlands containing data directly sampled from electronic health record systems of physical therapists (PTs). This registry aims to evaluate the potential of patient reported outcome measures (PROMs) to develop quality indicators (QIs) in physical therapy care. To test to what extent the collected PROM data are reliable, valid and discriminatory between practices in measuring outcomes of patients with non-specific low back pain (NSLBP). In this retrospective cohort study 865 PT practices with 6,560 PTs voluntarily collected PROM data of patients with NSLBP, using the Quebec Back Pain Disability Scale (QBPDS), the Numeric Pain Rating Scale (NPRS) and the Patient Specific Functioning Scale (PSFS). Reliability was determined by analysing the completeness of the dataset, the comparability by using national reference data, and through checking selection bias in the included patients. Validity was tested using the known-groups contrast between patients with (sub)acute vs. chronic NSLBP. To determine discriminative ability of outcomes between PT practices, case-mix corrected hierarchical multilevel analyses were performed. Reliability was sufficient by confirming fifteen of the sixteen hypotheses: 59% of all patients opted in for data analysis, 42% of these included patients showed repeated measurement, comparing with reference data and potential selection bias showed < 5% between group differences, while differences between (sub)acute and chronic NSLB-groups were significantly larger than 5% (less treatment sessions, lager differences in outcomes in (sub)acute NSLB patients). In addition, all nine adjusted hierarchical multilevel models confirm that the collected dataset on outcomes in PT care is able to discriminate between practices using PROM results of patients with NSLBP (ICC-scores range 0.11-0.21). PROMs of patients with NSLBP collected in the national clinical registry of KNGF are reliable, valid and able to discriminate between primary care PT practices.

Background: Around the world, policies and interventions are used to encourage clinicians to reduce low-value care. In order to facilitate this, we need a better understanding of the factors that lead to low-value care. We aimed to identify the key factors affecting low-value care on a national level. In addition, we highlight differences and similarities in three countries. Methods: We performed 18 semi-structured interviews with experts on low-value care from three countries that are actively reducing low-value care: the United States, Canada, and the Netherlands. We interviewed 5 experts from Canada, 6 from the United States, and 7 from the Netherlands. Eight were organizational leaders or policy-makers, 6 as low-value care researchers or project leaders, and 4 were both. The transcribed interviews were analyzed using inductive thematic analysis. Results: The key factors that promote low-value care are the payment system, the pharmaceutical and medical device industry, fear of malpractice litigation, biased evidence and knowledge, medical education, and a ‘more is better’ culture. These factors are seen as the most important in the United States, Canada and the Netherlands, although there are several differences between these countries in their payment structure, and industry and malpractice policy. Conclusion: Policy-makers and researchers that aim to reduce low-value care have experienced that clinicians face a mix of interdependent factors regarding the healthcare system and culture that lead them to provide low-value care. Better awareness and understanding of these factors can help policy-makers to facilitate clinicians and medical centers to deliver high-value care.

Chronic 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. We 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. We 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. Less 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. The 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.

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) semi-structured 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.

Chronic heart failure accounts for approximately 1%-2% of health care expenditures in most developed countries. These costs are primarily driven by hospitalizations and comorbidities. Telemonitoring has been proposed to reduce the number of hospitalizations and decrease the cost of treatment for patients with heart failure. However, the effects of telemonitoring on health care utilization remain unclear. This systematic review aims to study the effect of telemonitoring programs on health care utilization and costs in patients with chronic heart failure. We assess the effect of telemonitoring on hospitalizations, emergency department visits, length of stay, hospital days, nonemergency department visits, and health care costs. We searched PubMed, Embase, and Web of Science for randomized controlled trials and nonrandomized studies on noninvasive telemonitoring and health care utilization. We included studies published between January 2010 and August 2020. For each study, we extracted the reported data on the effect of telemonitoring on health care utilization. We used P<.05 and CIs not including 1.00 to determine whether the effect was statistically significant. We included 16 randomized controlled trials and 13 nonrandomized studies. Inclusion criteria, population characteristics, and outcome measures differed among the included studies. Most studies showed no effect of telemonitoring on health care utilization. The number of hospitalizations was significantly reduced in 38% (9/24) of studies, whereas emergency department visits were reduced in 13% (1/8) of studies. An increase in nonemergency department visits (6/9, 67% of studies) was reported. Health care costs showed ambiguous results, with 3 studies reporting an increase in health care costs, 3 studies reporting a reduction, and 4 studies reporting no significant differences. Health care cost reductions were realized through a reduction in hospitalizations, whereas increases were caused by the high costs of the telemonitoring program or increased health care utilization. Most telemonitoring programs do not show clear effects on health care utilization measures, except for an increase in nonemergency outpatient department visits. This may be an unwarranted side effect rather than a prerequisite for effective telemonitoring. The consequences of telemonitoring on nonemergency outpatient visits should receive more attention from regulators, payers, and providers. This review further demonstrates the high clinical and methodological heterogeneity of telemonitoring programs. This should be taken into account in future meta-analyses aimed at identifying the effective components of telemonitoring programs.

Background The Netherlands has reformed its long-term care (LTC) system to improve its financial sustainability by reducing access to in-kind nursing-home care and stimulating care within the home setting. This reform led to the rise of small-scale homelike nursing homes (SHNH) that are publicly financed by home-care packages. Small-scale care may require additional financial resources and personnel. Our aim is to compare the total healthcare costs of institutional in-kind nursing homes and deinstitutionalized home-like care homes. Methods We conducted an instrumental variable (IV) analysis to adjust for selection effects between both groups, using nationwide data including all LTC users. We use distance to the nearest provider as an instrument. In addition, we conducted semi-structured interviews with managers and policymakers to provide context for the quantitative data and validate our findings. Results Baseline statistics demonstrate that while LTC costs are lower in deinstitutionalized settings, total healthcare costs are higher, mainly due to additional medical costs outside the LTC system. After adjustment for observable and unobservable user characteristics, no significant cost differences were found. Conclusions This study may suggest that deinstitutionalization of LTC provision through publicly funded SNHNs primarily resulted in selection effects and spillover effects to other healthcare sectors, while for the marginal client, no clear difference in healthcare costs was observed.