For-profit Hospitals: A comparative and longitudinal study of the for-profit hospital sector in four Western countries

Many now argue that for-profit hospital ownership is on the rise because of the retrenchment of public entitlements and – often more importantly in health care – pro-market reforms in the delivery of these services1. Most theoretical notions assume that for-profit hospitals are more efficient than nonprofit and public hospitals2. It is thought that the inclusion of for-profits in the mainstream health care delivery system may increase efficiency or lower costs3. Issues and ideas around ownership are central in the public arena and for-profit hospital care has thus become the subject of fierce debate. Much of this discourse centers on the question whether health care differs fundamentally from other services, and should thus be sheltered from market forces4. Opponents of for-profit hospitals fear restricted access for those unable to pay, lower quality of care, cherry-picking of profitable services and patients, and excessive management interference in clinical autonomy. Proponents, on the other hand, believe that for-profits can bring about higher levels of efficiency and are more responsive to patient demands

COVID-19 vaccine challenges: what have we learned so far and what remains to be done?

Developing and distributing a safe and effective SARS-CoV-2 (COVID-19) vaccine has garnered immense global interest. Less than a year after COVID-19 was declared a pandemic, several vaccine candidates had received emergency use authorization across a range of countries. Despite this scientific breakthrough, the journey from vaccine discovery to global herd immunity against COVID-19 continues to present significant policy challenges that require a collaborative, global response. We offer a framework for understanding remaining and new policy challenges for successful global vaccine campaigns against COVID-19 as well as potential solutions to address them. Decision-makers must be aware of these challenges and strategize solutions that can be implemented at scale. These include challenges around maintaining R&D incentives, running clinical trials, authorizations, post-market surveillance, manufacturing and supply, global dissemination, allocation, uptake, and clinical system adaption. Alongside these challenges, financial and ethical concerns must also be addressed

New Provider Models for Sweden and Spain: Public, Private or Non-profit? Comment on “Governance, Government, and the Search for New Provider Models”

Sweden and Spain experiment with different provider models to reform healthcare provision. Both models have in common that they extend the role of the for-profit sector in healthcare. As the analysis of Saltman and Duran demonstrates, privatisation is an ambiguous and contested strategy that is used for quite different purposes. In our comment, we emphasize that their analysis leaves questions open on the consequences of privatisation for the performance of healthcare and the role of the public sector in healthcare provision. Furthermore, we briefly address the absence of the option of healthcare provision by not-for-profit providers in the privatisation strategy of Sweden and Spai

For-Profit Hospitals Out of Business? Financial Sustainability During the COVID-19 Epidemic Emergency Response

This perspective argues that for-profit hospitals will be heavily affected by epidemic crises, including the current coronavirus disease 2019 (COVID-19) outbreak. Policy-makers should be aware that for-profit hospitals in particular are likely to face financial distress. The suspension of all non-urgent elective surgery and the relegation of market-based mechanisms that determines the allocation and compensation of care puts the financial state of these hospitals at serious risk. We identify three organisational factors that determine which hospitals might be most affected (ie, care-portfolio, size and whether it is private equity [PE]-owned). In addition, we analyse contextual factors that could explain the impact of financial distress among for-profit hospitals on the wider healthcare system

For-profit hospitals have thrived because of generous public reimbursement schemes, not greater efficiency: a multi-country case study

For-profit hospitals’ market share has increased in many nations over recent decades. Previous studies suggest that their growth is not attributable to superior performance on access, quality of care, or efficiency. We analyzed other factors that we hypothesized may contribute to the increasing role of for-profit hospitals. We studied the historical development of the for-profit hospital sector across 4 nations with contrasting trends in for-profit hospital market share: the United States, the United Kingdom, Germany, and the Netherlands. We focused on 3 factors that we believed might help explain why the role of for-profits grew in some nations but not in others: (1) the treatment of for-profits by public reimbursement plans, (2) physicians’ financial interests, and (3) the effect of the political environment. We conclude that access to subsidies and reimbursement under favorable terms from public health care payors is an important factor in the rise of for-profit hospitals. Arrangements that aligned financial incentives of physicians with the interests of for-profit hospitals were important in stimulating for-profit growth in an earlier era, but they play little role at present. Remarkably, the environment for for-profit ownership seems to have been largely immune to political shifts

Track and Trace of Administrative Costs in the Dutch Long-Term Care System

Context: Practitioners and politicians alike emphasise the wish to reduce administrative costs (AC) in Dutch LTC, but a robust empirical body of evidence on the components, determinants and value of AC in LTC is absent. Neither has the expert consensus of ways to track and trace AC in LTC been sought. Objective(s): We investigated whether it is possible to reach consensus on operationalising AC in Dutch LTC. Successively we also explored whether the Dutch LTC reform in 2015 had the intended effect of reducing AC. Methods: We differentiated between AC for governing and financing LTC (macro), overhead costs of LTC delivery organisations (meso) and AC on the level of professional care delivery activities (micro). We identified possible data sources in grey literature and national accounts. The quality and completeness of identified data and potential determinants of AC were validated by experts via a survey and focus group discussions. Findings: We were able to reach agreement on how to track AC in Dutch LTC, but current research instruments and data systems are not robust and consistent enough to trace differences before and after the 2015 reform. Limitations: We did not investigate AC experienced by patients and self-selected participating experts. Implications: AC concern a considerable share of total LTC spending, but AC are hidden in regular health expenditure statistics. Our study highlights three approaches for a more sophisticated and fact-based policy debate on reducing low-value AC; defining AC on macro, meso and micro levels of the health care system, determining the underlying value/use of activities; and focusing on interactions of AC between system levels

Identifying future high healthcare utilization in patients with multimorbidity – development and internal validation of machine learning prediction models using electronic health record data

Purpose: To develop and internally validate prediction models with machine learning for future potentially preventable healthcare utilization in patients with multiple long term conditions (MLTC). This study is the first step in investigating whether prediction models can help identify patients with MLTC that are most in need of integrated care. Methods: A retrospective cohort study was performed with electronic health record data from adults with MLTC from an academic medical center in the Netherlands. Based on demographic and healthcare utilization characteristics in 2017, we predicted ≥ 12 outpatient visits, ≥ 1 emergency department (ED) visits, and ≥ 1 acute hospitalizations in 2018. Four machine learning models (elastic net regression, extreme gradient boosting (XGB), logistic regression, and random forest) were developed, optimized, and evaluated in a hold-out dataset for each outcome. Results: A total of 14,486 patients with MLTC were included. Based on the area under the curve (AUC) and calibration curves, the XGB model was selected as final model for all three outcomes. The AUC was 0.82 for ≥ 12 outpatient visits, 0.76 for ≥ 1 ED visits and 0.73 for ≥ 1 acute hospitalizations. Despite adequate AUC and calibration, precision-recall curves showed suboptimal performance. Conclusions: The final selected models per outcome can identify patients with future potentially preventable high healthcare utilization. However, identifying high-risk patients with MLTC and substantiating if they are most in need of integrated care remains challenging. Further research is warranted investigating whether patients with high healthcare utilization are indeed the most in need of integrated care and whether quantitively identified patients match the identification based on clinicians’ experience and judgment.</p

Measuring Experienced Utility in the Context of Health Economic Evaluation:A Narrative Overview

Background and Aims: Expected utility is deeply ingrained in the field of health economic evaluation, but critics highlight its theoretical flaws, including assumptions of complete information, bounded rationality, and stable preferences. They propose incorporating experienced utility for greater accuracy and suggest certain measurement methods. However, the applicability of these measurement methods in health economic evaluation remains uncertain. Therefore, this article examines the advantages, disadvantages and potential use of these measurement methods in the context of health economic evaluation. Methods: The measurement methods suggested in the literature include assessing physiological indicators, peak-end perceptions, approach-avoidance tendencies, and retrospective impact. The advantages, disadvantages, and potential use of these measurement methods in the context of health economic evaluation are analyzed using the discourse dialectic method. Results: Evaluation of physiological indicators is minimally intrusive and relatively objective, but it relies on laboratory data collection, limits comparability across scales, and emphasizes direct experiences. Assessment of peak-end perceptions enhances memory accuracy, yet elicits exaggerated recollections, neglects experience duration, promotes faded peak or overvalued end experiences, and disregards experiences without end. Measurement of approach-avoidance tendencies detects implicit experiences but similarly depends on laboratory conditions, fixates on immediate automatic emotional associations, overlooks unavoidable events or states, and remains indifferent to approach-avoidance conflicts. Evaluation of retrospective impact fosters holistic reflection and highlights temporally extended experiences, yet it fails to account for external information contamination, disregards individual rationalization processes, and overlooks constraints on reflective capabilities. Conclusion: Each proposed measurement method had drawbacks affecting its suitability for health economic evaluation. However, retrospective impact assessment emerged as the most promising one, although further scholarly inquiry is warranted to examine the theoretical and practical complexities of this approach within health economic evaluation.</p

Care trajectories of chronically ill older adult patients discharged from hospital:a quantitative cross-sectional study using health insurance claims data

Background For older adults, a good transition from hospital to the primary or long-term care setting can decrease readmissions. This paper presents the 6-month post-discharge healthcare utilization of older adults and describes the numbers of readmissions and deaths for the most frequently occurring aftercare arrangements as a starting point in optimizing the post-discharge healthcare organization. Methods This cross-sectional study included older adults insured with the largest Dutch insurance company. We described the utilization of healthcare within 180 days after discharge from their first hospital admission of 2015 and the most frequently occurring combinations of aftercare in the form of geriatric rehabilitation, community nursing, long-term care, and short stay during the first 90 days after discharge. We calculated the proportion of older adults that was readmitted or had died in the 90-180 days after discharge for the six most frequent combinations. We performed all analyses in the total group of older adults and in a sub-group of older adults who had been hospitalized due to a hip fracture. Results A total of 31.7% of all older adults and 11.4% of the older adults with a hip fracture did not receive aftercare. Almost half of all older adults received care of a community nurse, whereas less than 5% received long-term home care. Up to 18% received care in a nursing home during the 6 months after discharge. Readmissions were lowest for older adults with a short stay and highest in the group geriatric rehabilitation + community nursing. Mortality was lowest in the total group of older aldults and subgroup with hip fracture without aftercare. Conclusions The organization of post-discharge healthcare for older adults may not be organized sufficiently to guarantee appropriate care to restore functional activity. Although receiving aftercare is not a clear predictor of readmissions in our study, the results do seem to indicate that older adults receiving community nursing in the first 90 days less often die compared to older adults with other types of aftercare or no aftercare. Future research is necessary to examine predictors of readmissions and mortality in both older adult patients discharged from hospital.</p