“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.

Religion and Death in the United States: A Meta-Regression Comparative Assessment of Between-County Mortality Heterogeneity in the United States

Religion can have a favorable impact on individual-level health. The influence of religion on population health, however, remains less clear. This study investigated the association between religion and mortality at the population-level. Using county data, a meta-regression was performed to examine between-county mortality heterogeneity. The percent heterogeneity associated with religion variables were compared to demographics (i.e., place, race, language, age, and gender) and health factors (i.e., individual behaviors, clinical care, social and economic, and physical environment) as predictors of mortality. Religion was measured in terms of adherence (i.e., prevalence attending/belonging to a congregation), congregation density, and the diversity of adherents and congregation by denominations. Results showed counties with lower mortality were associated with higher proportions of religion adherents and a greater diversity of adherents and congregations. Counties with higher mortality were associated with higher religion congregation density. Religion, as a parsimonious multivariate model with all demographic and health factor predictors, had less added value when controlled for individual variables or constructs. The direction of association between religion and mortality was consistent, even when controlling for demographics and health factors, and thus merits further consideration as a population health determinant, as it may play a critical role in understanding other population health outcomes.

URMC Universal Depression Screening Initiative: Patient Reported Outcome Assessments to Promote a Person-Centered Biopsychosocial Population Health Management Strategy

Background: Patient-reported outcomes (PROs) can promote person-centered biopsychosocial health care by measuring outcomes that matter to patients, including functioning and well-being. Data support feasibility and acceptability of PRO administration as part of routine clinical care, but less is known about its effects on population health, including detection of unmet healthcare needs. Our objectives were to examine differences in rates of clinically significant depression across sociodemographic groups and clinical settings from universal depression screens in a large health system, estimate the number of patients with untreated depression detected by screenings, and examine associations between biopsychosocial PROs—physical, psychological, and social health.Methods: We analyzed data from over 200,000 adult patients who completed depression screens—either PROMIS (Patient Reported Outcomes Measurement Information System) or PHQ-2/9—as part of routine outpatient care.Results: Depression screens were positive in 14.2% of the sample, with more positive screens among younger vs. older adults, women vs. men, non-White vs. White, and Hispanics vs. non-Hispanics. These same sociodemographic indicators, as well as completing screening in primary care (vs. specialty care) were also associated with greater likelihood of detected depression in the medical record.Discussion: Universal screening for depression symptoms throughout a large health system appears acceptable and has the potential to detect depression in diverse patient populations outside of behavioral health. Expanded delivery of PROs to include physical and social health as well as depression should be explored to develop a clinically-relevant model for addressing patients' biopsychosocial needs in an integrated fashion across the health system.

Surveillance, Self-Governance, and Mortality: The Impact of Prescription Drug Monitoring Programs on U.S. Overdose Mortality, 2000–2016

Policy mechanisms shaping population health take numerous forms, from behavioral prohibitions to mandates for action to surveillance. Rising drug overdoses undermined the state’s ability to promote population-level health. Using the case of prescription drug monitoring programs (PDMPs), we contend that PDMP implementation highlights state biopower operating via mechanisms of surveillance, whereby prescribers, pharmacists, and patients perceive agency despite choices being constrained. We consider whether such surveillance mechanisms are sufficient or if prescriber/dispenser access or requirements for use are necessary for population health impact. We test whether PDMPs reduced overdose mortality while considering that surveillance may require time to reach effectiveness. PDMPs reduced opioid overdose mortality 2 years postimplementation and sustained effects, with similar effects for prescription opioids, benzodiazepines, and psychostimulants. Access or mandates for action do not reduce mortality beyond surveillance. Overall, PDMP effects on overdose mortality are likely due to self-regulation under surveillance rather than mandated action.

Effects of Varying Approaches to Lifting COVID-19 Pandemic Restrictions in the United States

Background Policy approaches to lifting COVID-19 restrictions have varied significantly across the United States. An evaluation of the effects of state reopening policies on population health outcomes can inform ongoing and future pandemic responses. This study evaluates the approaches to lifting social distancing restrictions based on adherence to the Centers for Disease Control and Prevention (CDC) guidance established during the first wave of the COVID-19 pandemic. Methods We performed a retrospective study using difference-in-differences analyses to examine the effects of reopening policies on COVID-19 outcomes with risk-adjustment for population density, temporal changes, and concurrent mask policy implementation. We examined the effects of reopening policies on per capita case rates and rates of severe COVID-19 outcomes, including hospitalizations and deaths. Results Adherence to CDC reopening gating metrics and phased social distancing guidelines resulted in fewer COVID-19 cases, hospitalizations, and deaths. Phase one adherent states exhibited a 50-fold reduction in daily new cases and a 3-fold reduction in daily new deaths after reopening. Phase two adherent states experienced improvements in COVID-19 outcomes after reopening, while non-adherent states had a resurgence of worsening outcomes after lifting restrictions. Conclusions Our study findings indicate that adherence to CDC reopening guidance after implementing social distancing restrictions during the COVID-19 pandemic substantially prevents new cases, hospitalizations, and deaths. Following a stepwise reopening strategy and ensuring a sustained decline in case rates and test positivity rates before lifting restrictions can mitigate on a large scale the negative effects of a pandemic on population health outcomes.

Health data collection methods and procedures across EU member states: findings from the InfAct Joint Action on health information

Background Health-related data are collected from a variety of sources for different purposes, including secondary use for population health monitoring (HM) and health system performance assessment (HSPA). Most of these data sources are not included in databases of international organizations (e.g., WHO, OECD, Eurostat), limiting their use for research activities and policy making. This study aims at identifying and describing collection methods, quality assessment procedures, availability and accessibility of health data across EU Member States (MS) for HM and HSPA. Methods A structured questionnaire was developed and administered through an online platform to partners of the InfAct consortium form EU MS to investigate data collections applied in HM and HSPA projects, as well as their methods and procedures. A descriptive analysis of the questionnaire results was performed. Results Information on 91 projects from 18 EU MS was collected. In these projects, data were mainly collected through administrative sources, population health interview or health examination surveys and from electronic medical records. Tools and methods used for data collection were mostly mandatory reports, self-administered questionnaires, or record linkage of various data sources. One-third of the projects shared data with EU research networks and less than one-third performed quality assessment of their data collection procedures using international standardized criteria. Macrodata were accessible via open access and reusable in 22 projects. Microdata were accessible upon specific request and reusable in 15 projects based on data usage licenses. Metadata was available for the majority of the projects, but followed reporting standards only in 29 projects. Overall, compliance to FAIR Data principles (Findable, Accessible, Interoperable, and Reusable) was not optimal across the EU projects. Conclusions Data collection and exchange procedures differ across EU MS and research data are not always available, accessible, comparable or reusable for further research and evidence-based policy making. There is a need for an EU-level health information infrastructure and governance to promote and facilitate sharing and dissemination of standardized and comparable health data, following FAIR Data principles, across the EU.