Decision Conflicts in Clinical Care during COVID-19: A Multi-Perspective Inquiry.

Background: The early COVID-19-pandemic was characterized by changes in decision making, decision-relevant value systems and the related perception of decisional uncertainties and conflicts resulting in decisional burden and stress. The vulnerability of clinical care professionals to these decisional dilemmas has not been characterized yet. Methods: A cross-sectional questionnaire study (540 patients, 322 physicians and 369 nurses in 11 institutions throughout Germany) was carried out. The inclusion criterion was active involvement in clinical treatment or decision making in oncology or psychiatry during the first year of COVID-19. The questionnaires covered five decision dimensions (conflicts and uncertainty, resources, risk perception, perception of consequences for clinical processes, and the perception of consequences for patients). Data analysis was performed using ANOVA, Pearson rank correlations, and the Chi²-test, and for inferential analysis, nominal logistic regression and tree classification were conducted. Results: Professionals reported changes in clinical management (27.5%) and a higher workload (29.2%), resulting in decisional uncertainty (19.2%) and decisional conflicts (22.7%), with significant differences between professional groups (p < 0.005), including anxiety, depression, loneliness and stress in professional subgroups (p < 0.001). Nominal regression analysis targeting "Decisional Uncertainty" provided a highly significant prediction model (LQ p < 0.001) containing eight variables, and the analysis for "Decisional Conflicts" included six items. The classification rates were 64.4% and 92.7%, respectively. Tree analysis confirmed three levels of determinants. Conclusions: Decisional uncertainty and conflicts during the COVID-19 pandemic were independent of the actual pandemic load. Vulnerable professional groups for the perception of a high number of decisional dilemmas were characterized by individual perception and the psychological framework. Coping and management strategies should target vulnerability, enable the handling of the individual perception of decisional dilemmas and ensure information availability and specific support for younger professionals.

Differences in Stakeholders' Perception of the Impact of COVID-19 on Clinical Care and Decision-Making.

Background: Pandemics are related to changes in clinical management. Factors that are associated with individual perceptions of related risks and decision-making processes focused on prevention and vaccination, but perceptions of other healthcare consequences are less investigated. Different perceptions of patients, nurses, and physicians on consequences regarding clinical management, decisional criteria, and burden were compared. Study Design: Cross-sectional OnCoVID questionnaire studies. Methods: Data that involved 1231 patients, physicians, and nurses from 11 German institutions that were actively involved in clinical treatment or decision-making in oncology or psychiatry were collected. Multivariate statistical approaches were used to analyze the stakeholder comparisons. Results: A total of 29.2% of professionals reported extensive changes in workload. Professionals in psychiatry returned severe impact of pandemic on all major aspects of their clinical care, but less changes were reported in oncology (p < 0.001). Both patient groups reported much lower recognition of treatment modifications and consequences for their own care. Decisional and pandemic burden was intensively attributed from professionals towards patients, but less in the opposite direction. Conclusions: All of the groups share concerns about the impact of the COVID-19 pandemic on healthcare management and clinical processes, but to very different extent. The perception of changes is dissociated in projection towards other stakeholders. Specific awareness should avoid the dissociated impact perception between patients and professionals potentially resulting in impaired shared decision-making.

A pyramid model to describe changing decision making under high uncertainty during the COVID-19 pandemic.

The COVID-19 pandemic put healthcare systems, hospitals and medical personal under great pressure. Based on observations in Germany, we theorise a general model of rapid decision-making that makes sense of the growing complexity, risks and impact of missing evidence. While adapting decision-making algorithms, management, physicians, nurses and other healthcare professionals had to move into uncharted territory while addressing practical challenges and resolving normative (legal and ethical) conflicts. During the pandemic, this resulted in decisional uncertainties for healthcare professionals. We propose an idealised risk-based model that anticipates these shifts in decision-making procedures and underlying value frameworks. The double pyramid model visualises foreseeable procedural adaptations. This does not only help practitioners to secure operational continuity in a crisis but also contributes to improving the conceptual underpinnings of the resilience of healthcare during the next pandemic or similar future crises situations.

Economic Perspective of Cancer Care and Its Consequences for Vulnerable Groups.

Within healthcare systems in all countries, vulnerable groups of patients can be identified and are characterized by the reduced utilization of available healthcare. Many different reasons can be attributed to this observation, summarized as implementation barriers involving acceptance, accessibility, affordability, acceptability and quality of care. For many patients, cancer care is specifically associated with the occurrence of vulnerability due to the complex disease, very different target groups and delivery situations (from prevention to palliative care) as well as cost-intensive care. Sociodemographic factors, such as educational level, rural/remote location and income, are known determinants for these vulnerable groups. However, different forms of financial burdens likely influence this vulnerability in cancer care delivery in a distinct manner. In a narrative review, these socioeconomic challenges are summarized regarding their occurrence and consequences to current cancer care. Overall, besides direct costs such as for treatment, many facets of indirect costs including survivorship costs for the cancer patients and their social environment need to be considered regarding the impact on vulnerability, treatment compliance and abundance. In addition, individual cancer-related financial burden might also affect the society due to the loss of productivity and workforce availability. Healthcare providers are requested to address this vulnerability during the treatment of cancer patients.

Population-based study on coverage and healthcare processes for cancer during implementation of national healthcare insurance in Indonesia.

Background: A national healthcare insurance has been implemented in Indonesia since 2014. Although cancer care currently represents a smaller part of the healthcare support, the demographic development will lead to a rapid growth of the population within age groups at cancer risk. This requires strategic and developmental planning of cancer care resources. Based on data of the national healthcare insurance, current cancer care processes and their determinants were evaluated. Methods: Nationwide reimbursement data as well as demographic, economic and healthcare infrastructure data were used for the study. Poor and underserved population was stratified according to the national classification system. Availability of healthcare resources was evaluated at provincial level. Cancer care usage was analysed applying descriptive and multivariate statistical approaches (regression, cluster analysis, tree classification). Findings: Cancer care was provided in primary care (PHC) for 2.6/1000 and advanced care (AHC) for 4.8/1000 participants within the family-based membership structure. Regression analysis revealed human resource availability in rural/remote areas a determinant for cancer PHC. Cancer care in AHC was determined by PHC provided by general practitioners (GP), availability of AHC infrastructure (Class A & B hospital beds) and treatment migration between provinces. Tree classification confirmed predominant roles of GP, AHC infrastructure and referral between cancer care provider levels. Interpretation: Cancer care will gain much higher importance for the Indonesian healthcare system within the next decade. Infrastructure, human resources, and process development should avoid rising overload of cancer care delivery by targeting reduction of treatment migration (availability of GPs in rural/remote provinces), improvement of referral systems (effective clinical selection processes and back-referral) and AHC cancer care structures (regional distribution of Class A & B hospitals). Funding: This project was supported by grants from Centre for Research, Publication, and Community Development Muhammadiyah University of Yogyakarta (SW, ID), and data provision by BPJS Indonesia.

Availability and Accessibility of Primary Care for the Remote, Rural, and Poor Population of Indonesia.

Background: Adopting Universal Health Coverage for implementation of a national health insurance system [Jaminan Kesehatan Nasional (JKN)/Badan Penyelenggara Jaminan Sosial or the Indonesian National Social Health Insurance Scheme (BPJS)] targets the 255 million population of Indonesia. The availability, accessibility, and acceptance of healthcare services are the most important challenges during implementation. Referral behavior and the utilization of primary care structures for underserved (rural/remote regions) populations are key guiding elements. In this study, we provided the first assessment of BPJS implementation and its resulting implications for healthcare delivery based on the entire insurance dataset for the initial period of implementation, specifically focusing on poor and remote populations. Methods: Demographic, economic, and healthcare infrastructure information was obtained from public resources. Data about the JKN membership structure, performance information, and reimbursement were provided by the BPJS national head office. For analysis, an ANOVA was used to compare reimbursement indexes for primary healthcare (PHC) and advanced healthcare (AHC). The usage of primary care resources was analyzed by comparing clustered provinces and utilization indices differentiating poor [Penerima Bantuan Iur (PBI) membership] and non-poor populations (non-PBI). Factorial and canonical discrimination analyses were applied to identify the determinants of PHC structures. Results: Remote regions cover 27.8% of districts/municipalities. The distribution of the poor population and PBI members were highly correlated (r2 > 0.8; p < 0.001). Three clusters of provinces [remote high-poor (N = 13), remote low-poor (N = 15), non-remote (N = 5)] were identified. A discrimination analysis enabled the >82% correct cluster classification of infrastructure and human resources of health (HRH)-related factors. Standardized HRH (nurses and general practitioners [GP]) availability showed significant differences between clusters (p < 0.01), whereas the availability of hospital beds was weakly correlated. The usage of PHC was ~2-fold of AHC, while non-PBI members utilized AHC 4- to 5-fold more frequently than PBI members. Referral indices (r2 = 0.94; p < 0.001) for PBI, non-PBI, and AHC utilization rates (r2 = 0.53; p < 0.001) were highly correlated. Conclusion: Human resources of health availability were intensively related to the extent of the remote population but not the numbers of the poor population. The access points of PHC were mainly used by the poor population and in remote regions, whereas other population groups (non-PBI and non-Remote) preferred direct access to AHC. Guiding referral and the utilization of primary care will be key success factors for the effective and efficient usage of available healthcare infrastructures and the achievement of universal health coverage in Indonesia. The short-term development of JKN was recommended, with a focus on guiding referral behavior, especially in remote regions and for non-PBI members.