“It’s good to feel like you’re doing something”: a qualitative study examining state health department employees’ views on why ineffective programs continue to be implemented in the USA

Background Mis-implementation, the inappropriate continuation of programs or policies that are not evidence-based or the inappropriate termination of evidence-based programs and policies, can lead to the inefficient use of scarce resources in public health agencies and decrease the ability of these agencies to deliver effective programs and improve population health. Little is known about why mis-implementation occurs, which is needed to understand how to address it. This study sought to understand the state health department practitioners’ perspectives about what makes programs ineffective and the reasons why ineffective programs continue. Methods Eight state health departments (SHDs) were selected to participate in telephone-administered qualitative interviews about decision-making around ending or continuing programs. States were selected based on geographic representation and on their level of mis-implementation (low and high) categorized from our previous national survey. Forty-four SHD chronic disease staff participated in interviews, which were audio-recorded and transcribed verbatim. Transcripts were consensus coded, and themes were identified and summarized. This paper presents two sets of themes, related to (1) what makes a program ineffective and (2) why ineffective programs continue to be implemented according to SHD staff. Results Participants considered programs ineffective if they were not evidence-based or if they did not fit well within the population; could not be implemented well due to program restraints or a lack of staff time and resources; did not reach those who could most benefit from the program; or did not show the expected program outcomes through evaluation. Practitioners described several reasons why ineffective programs continued to be implemented, including concerns about damaging the relationships with partner organizations, the presence of program champions, agency capacity, and funding restrictions. Conclusions The continued implementation of ineffective programs occurs due to a number of interrelated organizational, relational, human resources, and economic factors. Efforts should focus on preventing mis-implementation since it limits public health agencies’ ability to conduct evidence-based public health, implement evidence-based programs effectively, and reduce the high burden of chronic diseases. The use of evidence-based decision-making in public health agencies and supporting adaptation of programs to improve their fit may prevent mis-implementation. Future work should identify effective strategies to reduce mis-implementation, which can optimize public health practice and improve population health.

Containment of a multi-index B.1.1.7 outbreak on a university campus through a genomically-informed public health response

The first cluster of SARS-CoV-2 cases with lineage B.1.1.7 in the state of Michigan was identified through intensive university-led surveillance sampling and targeted sequencing. A collaborative investigation and response was conducted by the local and state health departments, and the campus and athletic medicine COVID-19 response teams, using S-gene target failure screening and rapid genomic sequencing to inform containment strategies. A total of 50 cases of B.1.1.7-lineage SARS-CoV-2 were identified in this outbreak, which was due to three coincident introductions of B.1.1.7-lineage SARS-CoV-2, all of which were genetically distinct from lineages which later circulated in the broader community. This investigation demonstrates the successful implementation of a genomically-informed outbreak response which can be extended to university campuses and other settings at high risk for rapid emergence of new variants.

Features of health insurance: an analysis of the German experience

The article examines the models of health insurance in Western countries. A comparative analysis of forms of social insurance and sources of financing payments for four models of medical insurance is carried out. The practical aspects of the functioning of compulsory health insurance in Germany are investigated, its positive features are revealed. Attention is paid to medical insurance, which provides insurance in case of loss of health for any reason. It provides greater accessibility, quality and completeness to meet the diverse needs of the population in the provision of medical services, and is more effective than government funding of the health care system. In addition, the social and economic efficiency of health insurance related to reimbursement of citizens' expenses related to receiving medical care, as well as other expenses aimed at maintaining health, depends on how comprehensively the concept of developing insurance medicine in the country has been worked out. The positive and negative aspects of health insurance are analyzed. The forms of health insurance are considered: compulsory health insurance and voluntary health insurance. It was found that one of the first countries where health insurance was introduced was Germany. There are two types of health insurance in Germany: public and private. Germany's state health insurance is compulsory. That is, every employee, as well as persons trained in production (Auszubildende), are subject to compulsory state health insurance and must be members of one of their freely chosen state health insurance funds. At the same time, if a person wishes to receive medical services that are not included in the list of compulsory health insurance, he can conclude a supplementary health insurance contract with the insurance company. Voluntary health insurance allows you to choose an inpatient medical institution and the conditions of stay in it, special services of a personal physician.

Community-based psychiatry services in Sri Lanka: A new model in the making

Sri Lanka is a lower middle-income small island nation in the Indian Ocean with a multi-ethnic population of 22 million. The healthcare system of the country is well-established and fairly advanced, the delivery of which is free to the consumer. The health indicators of the country are impressive compared to regional figures. Psychiatric care in Sri Lanka saw a rapid development over the last four decades as the care model transformed from an asylum-based one, established during the British colonial times, to a district-wise hospital-based care delivery model. Gradually, the teams that provided inpatient and outpatient services at the hospitals started to also provide community-based care. The newly added community based services include outreach clinics, residential intermediate rehabilitation centres, home based care, community resource/support centres and telephone help lines. There is no or little separate funding for community-based care services. The teams that deliver community services are funded, mostly indirectly, by the state health authorities. This is so as these community teams are essentially the same psychiatry teams that are based at the hospitals, which are funded and run by the state health authorities. This lack of separation of the community and hospital teams without separate and dedicated funding is an impediment to service development, which needs to be addressed. Paradoxically, it conforms an advantage by making care delivery from the hospital to the community continuous, as it is the same team that provides both hospital- and community-based care. In addition to the essential mental health care provision in the community with this basic infrastructure, each community service has improvised and adapted utilization of other resources available to them, formally as well as informally, to compensate their financial and human resource limitations. These other resources are the community officials and the community services of the non-health sectors of the government, mainly of the civil administration. Though sustainability maybe questionable when services involve informal resources from the non-health sectors, it has so far proven useful and effective, in a resource-poor environment, as it brings the community and various sectors together to facilitate services to support their own community.

Efforts by the National Academy for State Health Policy

The National Academy for State Health Policy hosts both the RAISE Act Family Caregiving Resource and Dissemination Center and the Hub for State Strategies to Build and Support Palliative Care, with generous funding from The John A. Hartford Foundation. The value of supporting individuals with serious illness and complex conditions as well as their family caregivers through telehealth, care management, advance care planning, and other added family caregiver supports has been especially evident during the COVID-19 pandemic. Policymakers are now grappling with how to restructure hard-hit health care and long-term services and supports systems to better support these individuals and their family caregivers. The State Hub provides concrete resources for states working to implement and expand high-quality palliative care, and the RAISE Center is assisting the Family Caregiving Advisory Council with creating the country’s first national Family Caregiver Strategy.

Activities Under the RAISE Family Caregiving Act: Developing a National Strategy to Support Family Caregivers

This presentation describes the unique collaboration between The John A. Hartford Foundation, the Administration or Community Living (ACL), and the National Academy for State Health Policy (NASHP) in supporting the RAISE Act Family Caregiver Resource and Dissemination Center, and the goals and activities of the RAISE Act Family Caregiving Advisory Council. Most importantly, she will present the the development of recommendations for a national strategy to support family caregivers involving all levels of government as well as private-sector actors. These recommendations fall into five primary areas, which Fox-Grage will discuss in detail. She will also discuss the Center’s development of family caregiving resources for state and federal policymakers and other stakeholders as well as next steps in turning the Council’s recommendations into concrete action.

Non-Hodgkin Lymphoma Mortality in the Elderly Population By Race, Gender, and Region in the United States

Background: Over the past decades, non-Hodgkin lymphoma (NHL) patients have significant improvement in the 5-year relative survival rate. In elderly NHL patients, comorbidities play a major role in mortality. Studies have shown that lower survival rates are multifactorial and strongly associated with certain races, gender, socioeconomic status, and availability of rituximab. Therefore, we aim to assess the differences in causes of mortality among races and genders. To better understand environmental contributions to one-year survival rate in NHL patients state-wise in the US, we examined the mortality-to-incidence rate (MIR) in senior NHL patients characterized by race, gender, and American health ranking (AHR) index. Methods: This is a retrospective study using the Centers for Disease Control and Prevention database from 2008 to 2017. Patients ≥65 years with non-Hodgkin lymphoma were included. AHR assesses the nation's health on a state-by-state basis to determine state health rankings with a composite index of health measures. AHR consists of five weighted core measures (four groups of health determinants and one health outcome): (1). Behaviors including excessive drinking, obesity, smoking, (2). Community and environment including air pollution, poverty, infectious disease, violent crime, (3). Policy including immunization, public health funding, uninsured rate, (4). Clinical care including primary care physicians, mental health providers, preventable hospitalizations, and (5). Outcomes including cancer deaths, cardiovascular deaths, diabetes, disparity in mental status. A ten-year (2008-2017) average of all-determinants value from AHR were reported and MIR, a parameter that can serve as a proxy for survival, was compared between US states. We analyzed the association between NHL mortality and state health disparities using linear regression. Multiple-cause-of-death data is based on death certificates for US residents. Each death certificate contains a single underlying cause of death, up to twenty additional multiple causes, and demographic data. We analyzed the multiple cause age-adjusted mortality rate in White males and females versus African American males and females. All data were analyzed using R version 4.0.5, with p-values <0.05 in two-sided t-tests to indicate statistical significance. Results: In this 10-year analysis, the mean age-adjusted mortality rate (AAMR) in Whites, African Americans, and all populations were 38.2, 21.4, and 36.7 per 1,000,000 population, respectively. Among all 50 states, Idaho had the highest AAMR for all populations (42.7/1,000,000) and Whites (43.1/1,000,000); Minnesota had the highest AAMR for African Americans (29/1,000,000). District of Columbia had the lowest AAMR for all populations (26.4/1,000,000); New Mexico had the lowest AAMR for Whites (30.6/1,000,000) and New York had the lowest AAMR for African Americans (Table 1). Our results demonstrated that elderly NHL patients in states with better health all-determinants index had significantly lower MIR in all populations (R 2=0.2654, p <0.001, Figure 1). The three lowest MIR states in the US were Florida (0.319), Connecticut (0.348), and New York (0.348) (Figure 2). Whites were more likely to have underlying comorbidities than African Americans, especially ischemic heart disease (Male: OR 87.16, 95% CI 74.23-102.34; Female: 26.10, 95% CI 22.01-30.94), congestive heart failure (Male: OR 53.31, 95% CI 45.35-62.66; Female: OR 25.98, 95% CI 22.25-30.34), and chronic obstructive pulmonary disease (Male: OR 54.55, 95% CI 45.27-65.73; Female: OR 45.98, 95% CI 36.48-57.95) (Table 2,3). Conclusions: States of better health index in terms of all determinants had lower MIR for elderly NHL patients in the US. Factors contributing to the difference in MIR possibly include variations in socioeconomic status, insurance coverage, and healthcare access. Our results highlight the need to focus on secondary prevention to decrease morbidities and health disparities in NHL patients. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Association between the Leukemia Mortality-to-Incidence Ratio and State Geographic Healthcare Disparities in the United States

INTRODUCTION : Leukemia is the seventh leading cause of cancer death in the United States (US) in 2021. The Mortality Incidence Rate Ratio, also known as Mortality-to-Incidence Ratio (MIR), is calculated by dividing the mortality rate by the incidence rate for selected cancers and population. The MIR provides a population-based indicator of cancer survival which has previously been used to assess healthcare disparities among different countries. Here weevaluated the potential association between leukemia MIR and state-based health disparities in the US. METHODS: Leukemia (AML, CML, ALL, CLL and other leukemias) MIRs for 2008-2017 were obtained from United States Cancer Statistics (USCS) database provided by the Centers for Disease Control and Prevention (CDC). America's Health Rankings (AHR), a partnership of the United Health Foundation and the American Public Health Association, evaluates the nation's health on a state-by-state basis by using weighted measures in 5 different categories (25% for Behaviors, 22.5% for Community & Environment, 12.5% for Policy, 15% for Clinical Care, and 25% for Outcomes). AHR then determines state health rankings and reflects state health disparities based on these specific factors. Here we analyzed the potential association between leukemia MIRs and state health rankings by linear regression. RESULTS: From 2008 to 2017, a total of 489,037 people were diagnosed with leukemia and 231,069 people died from leukemia in the US. The 10-year average of age-adjusted incidence rate and mortality rate were 14.2 and 6.7 per 100,000 population respectively. The average MIR between all states was calculated to be 0.470. As seen in Table 1, the lowest MIR (best survival) was found in Florida (0.374), New York (0.391), and New Jersey (0.412) with AHR 34, 19 and 11 respectively. The highest MIR (worst survival) was found in Mississippi (0.579), Wyoming (0.570), and Ohio (0.569) with AHR 50, 24 and 37 respectively. According to AHR, over the last decade, the states with the highest health rankings were reported in Vermont (No. 1), Hawaii (No. 2), and Massachusetts (No. 3) with MIR 0.508, 0.439 and 0.502 respectively. The states with the lowest health rankings were reported in Arkansas (No. 48), Louisiana (No. 49), and Mississippi (No. 50) with MIR 0.559, 0.503 and 0.579 respectively. In our analysis, states with better health rankings were significantly associated with lower MIRs (R 2=0.232, P<0.001), as seen in Figure 1. CONCLUSIONS: There is a remarkable geographic difference in leukemia MIRs in the US between 2008-2017. Leukemia MIR was significantly associated with state health rankings reported by the AHR. Although the quality of clinical care for leukemia patients remains to be an important predictor of mortality, our findings suggest that other aggregate determinants of health, including social, economic, and community and physical environment may also play a vital role in influencing leukemia survival. More in-depth analysis of these data focusing on specific leukemia subtypes as well as other factors (race, gender, age) may be helpful in identifying and addressing other non-medical issues negativity impacting on leukemia outcomes in different geographical regions in the United States. Figure 1 Figure 1. Disclosures Wang: Kura Oncology: Consultancy, Honoraria, Other: Advisory board, steering committee, Speakers Bureau; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Stemline Therapeutics: Consultancy, Honoraria, Other: Advisory board, Speakers Bureau; Kite Pharmaceuticals: Consultancy, Honoraria, Other: Advisory Board; Takeda: Consultancy, Honoraria, Other: Advisory board; Pfizer: Consultancy, Honoraria, Other: Advisory Board, Speakers Bureau; Novartis: Consultancy, Honoraria, Other: Advisory Board; Mana Therapeutics: Consultancy, Honoraria; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Other: Advisory Board; Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Advisory Board; DAVA Oncology: Consultancy, Speakers Bureau; Rafael Pharmaceuticals: Other: Data safety monitoring committee; Gilead: Consultancy, Honoraria, Other: Advisory board; Daiichi Sankyo: Consultancy, Honoraria, Other: Advisory board; PTC Therapeutics: Consultancy, Honoraria, Other: Advisory board; Genentech: Consultancy; MacroGenics: Consultancy.