Organizational decision‐making during COVID‐19: A qualitative analysis of the organizational decision‐making system in the United States during COVID‐19

This study sought to understand COVID‐19‐related organizational decisions were made across sectors. To gain this understanding, we conducted semi‐structured interviews with organizational decision‐makers in North Carolina about their experiences responding to COVID‐19. Conventional content analysis was used to analyse the context, inputs, and processes involved in decision‐making. Between October 2020 and February 2021, we interviewed 44 decision‐makers from the following sectors: business (n = 4), community non‐profit (n = 3), county government (n = 4), healthcare (n = 5), local public health (n = 5), public safety (n = 7), religious (n = 6), education (n = 7) and transportation (n = 3). We found that during the pandemic, organizations looked to scientific authorities, the decisions of peer organizations, data about COVID‐19, and their own experience with prior crises. Interpretation of inputs was informed by current political events, societal trends, and organization mission. Decision‐makers had to account for divergent internal opinions and community behaviour. To navigate inputs and contextual factors, organizations decentralized decision‐making authority, formed auxiliary decision‐making bodies, learned to resolve internal conflicts, learned in real time from their crisis response, and routinely communicated decisions with their communities. In conclusion, aligned with systems and contingency theories of decision‐making, decision‐making during COVID‐19 depended on an organization's 'fit' within the specifics of their existing system and their ability to orient the dynamics of that system to their own goals. [ FROM AUTHOR] Copyright of Journal of Contingencies & Crisis Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Barriers to COVID-19 vaccine uptake among resource-limited adults diagnosed with chronic illness.

Background: Despite the use of interventions (e.g., monetary incentives, educational campaigns, on-site workplace vaccination) to increase COVID-19 vaccination, differences in uptake persist by poverty level, insurance status, geography, race, and ethnicity, suggesting that these interventions may not be adequately addressing the barriers faced by these populations. Among a sample of resource-limited individuals with chronic illnesses, we (1) described the prevalence of different types of barriers to the COVID-19 vaccination and (2) identified associations between patients' sociodemographic characteristics and barriers to vaccination. Methods: We surveyed a national sample of patients with chronic illness and demonstrated healthcare affordability and/or access challenges about barriers to COVID-19 vaccination in July 2021. We categorized participant responses into cost, transportation, informational, and attitudinal barrier domains and assessed the prevalence of each domain, both overall and by self-reported vaccination status. Using logistic regression models, we examined unadjusted and adjusted associations between respondent characteristics (sociodemographic, geographic, and healthcare access) and self-reported barriers to vaccination. Results: Of 1,342 respondents in the analytic sample, 20% (264/1,342) reported informational barriers and 9% (126/1,342) reported attitudinal barriers to COVID-19 vaccination. Transportation and cost barriers were reported much less commonly, by only 1.1% (15/1,342) and 0.7% (10/1,342) of the sample, respectively. Controlling for all other characteristics, respondents with either a specialist as their usual source of care or no usual source of care had an 8.4 (95% CI: 1.7-15.1) and 18.1 (95% CI: 4.3-32.0) percentage point higher predicted probability, respectively, of reporting informational barriers to care. Compared to females, males had an 8.4% point (95% CI: 5.5-11.4) lower predicted probability of reporting attitudinal barriers. Only attitudinal barriers were associated with COVID-19 vaccine uptake. Conclusion: Among a sample of adults with chronic illnesses who had received financial assistance and case management services from a national non-profit, informational and attitudinal barriers were more commonly reported than logistical or structural access barriers (i.e., transportation and cost barriers). Interventions should target attitudinal barriers among patients with chronic illness, who may have particular concerns about the interaction of the vaccine with ongoing medical care. Additionally, interventions targeting informational barriers are particularly needed among individuals without a usual source of care.

Lessening the Impact of Financial Toxicity (LIFT): a protocol for a multi-site, single-arm trial examining the effect of financial navigation on financial toxicity in adult patients with cancer in rural and non-rural settings.

BACKGROUND: Almost half of the patients with cancer report cancer-related financial hardship, termed "financial toxicity" (FT), which affects health-related quality of life, care retention, and, in extreme cases, mortality. This increasingly prevalent hardship warrants urgent intervention. Financial navigation (FN) targets FT by systematically identifying patients at high risk, assessing eligibility for existing resources, clarifying treatment cost expectations, and working with patients and caregivers to develop a plan to cope with cancer costs. This trial seeks to (1) identify FN implementation determinants and implementation outcomes, and (2) evaluate the effectiveness of FN in improving patient outcomes. METHODS: The Lessening the Impact of Financial Toxicity (LIFT) study is a multi-site Phase 2 clinical trial. We use a pre-/post- single-arm intervention to examine the effect of FN on FT in adults with cancer. The LIFT trial is being conducted at nine oncology care settings across North Carolina in the United States. Sites vary in geography (five rural, four non-rural), size (21-974 inpatient beds), and ownership structure (governmental, non-profit). The study will enroll 780 patients total over approximately 2 years. Eligible patients must be 18 years or older, have a confirmed cancer diagnosis (any type) within the past 5 years or be living with advanced disease, and screen positive for cancer-related financial distress. LIFT will be delivered by full- or part-time financial navigators and consists of 3 components: (1) systematic FT screening identification and comprehensive intake assessment; (2) connecting patients experiencing FT to financial support resources via trained oncology financial navigators; and (3) ongoing check-ins and electronic tracking of patients' progress and outcomes by financial navigators. We will measure intervention effectiveness by evaluating change in FT (via the validated Comprehensive Score of Financial Toxicity, or COST instrument) (primary outcome), as well as health-related quality of life (PROMIS Global Health Questionnaire), and patient-reported delayed or forgone care due to cost. We also assess patient- and stakeholder-reported implementation and service outcomes post-intervention, including uptake, fidelity, acceptability, cost, patient-centeredness, and timeliness. DISCUSSION: This study adds to the growing evidence on FN by evaluating its implementation and effectiveness across diverse oncology care settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04931251. Registered on June 18, 2021.

Organizational decision‐making during COVID‐19: A qualitative analysis of the organizational decision‐making system in the United States during COVID‐19

This study sought to understand COVID‐19‐related organizational decisions were made across sectors. To gain this understanding, we conducted semi‐structured interviews with organizational decision‐makers in North Carolina about their experiences responding to COVID‐19. Conventional content analysis was used to analyse the context, inputs, and processes involved in decision‐making. Between October 2020 and February 2021, we interviewed 44 decision‐makers from the following sectors: business (n = 4), community non‐profit (n = 3), county government (n = 4), healthcare (n = 5), local public health (n = 5), public safety (n = 7), religious (n = 6), education (n = 7) and transportation (n = 3). We found that during the pandemic, organizations looked to scientific authorities, the decisions of peer organizations, data about COVID‐19, and their own experience with prior crises. Interpretation of inputs was informed by current political events, societal trends, and organization mission. Decision‐makers had to account for divergent internal opinions and community behaviour. To navigate inputs and contextual factors, organizations decentralized decision‐making authority, formed auxiliary decision‐making bodies, learned to resolve internal conflicts, learned in real time from their crisis response, and routinely communicated decisions with their communities. In conclusion, aligned with systems and contingency theories of decision‐making, decision‐making during COVID‐19 depended on an organization's ‘fit’ within the specifics of their existing system and their ability to orient the dynamics of that system to their own goals. [ FROM AUTHOR]

Cross-sector decision landscape in response to COVID-19: A qualitative network mapping analysis of North Carolina decision-makers.

Introduction: The COVID-19 pandemic response has demonstrated the interconnectedness of individuals, organizations, and other entities jointly contributing to the production of community health. This response has involved stakeholders from numerous sectors who have been faced with new decisions, objectives, and constraints. We examined the cross-sector organizational decision landscape that formed in response to the COVID-19 pandemic in North Carolina. Methods: We conducted virtual semi-structured interviews with 44 organizational decision-makers representing nine sectors in North Carolina between October 2020 and January 2021 to understand the decision-making landscape within the first year of the COVID-19 pandemic. In line with a complexity/systems thinking lens, we defined the decision landscape as including decision-maker roles, key decisions, and interrelationships involved in producing community health. We used network mapping and conventional content analysis to analyze transcribed interviews, identifying relationships between stakeholders and synthesizing key themes. Results: Decision-maker roles were characterized by underlying tensions between balancing organizational mission with employee/community health and navigating organizational vs. individual responsibility for reducing transmission. Decision-makers' roles informed their perspectives and goals, which influenced decision outcomes. Key decisions fell into several broad categories, including how to translate public health guidance into practice; when to institute, and subsequently loosen, public health restrictions; and how to address downstream social and economic impacts of public health restrictions. Lastly, given limited and changing information, as well as limited resources and expertise, the COVID-19 response required cross-sector collaboration, which was commonly coordinated by local health departments who had the most connections of all organization types in the resulting network map. Conclusions: By documenting the local, cross-sector decision landscape that formed in response to COVID-19, we illuminate the impacts different organizations may have on information/misinformation, prevention behaviors, and, ultimately, health. Public health researchers and practitioners must understand, and work within, this complex decision landscape when responding to COVID-19 and future community health challenges.

Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study.

Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers. Highlights: Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.