Design and Development of a Community-Based, Interdisciplinary, Collaborative Dementia Care Program.

OBJECTIVE: To describe the design, development, and baseline characteristics of enrollees of a home-based, interdisciplinary, dyadic, pilot dementia care program. DESIGN: Single-arm, dementia care intervention in partnership with primary care providers delivered by Health Coaches to persons with dementia and caregiver "dyads" and supervised by an interdisciplinary team. SETTING: Home- and virtual-based dyad support. PARTICIPANTS: Persons with mild cognitive impairment or dementia diagnosis and/or who were prescribed antidementia medications; had an identified caregiver willing to participate; were under the care of a partner primary care provider; and had health insurance through the affiliated accountable care organization (Banner Health Network). INTERVENTION: Provision of personalized dementia education and support in the home or virtually by Health Coaches supported by an interdisciplinary team. MEASUREMENTS: Cognition, function, mood, and behavior of persons with dementia; caregiver stress and program satisfaction; primary care provider satisfaction. RESULTS: Served dyads from three primary care clinics with a total of 87 dyads enrolled between December 2018 and June 2020. CONCLUSION: A pilot Dementia Care Partners demonstrated feasibility and suggested acceptability, and high satisfaction among primary care providers and caregivers.

Overlooked Shortcomings of Observational Studies of Interventions in Coronavirus Disease 2019: An Illustrated Review for the Clinician.

The rapid spread of severe acute respiratory syndrome coronavirus 2 infection across the globe triggered an unprecedented increase in research activities that resulted in an astronomical publication output of observational studies. However, most studies failed to apply fully the necessary methodological techniques that systematically deal with different biases and confounding, which not only limits their scientific merit but may result in harm through misleading information. In this article, we address a few important biases that can seriously threaten the validity of observational studies of coronavirus disease 2019 (COVID-19). We focus on treatment selection bias due to patients' preference on goals of care, medical futility and disability bias, survivor bias, competing risks, and the misuse of propensity score analysis. We attempt to raise awareness and to help readers assess shortcomings of observational studies of interventions in COVID-19.

Defining, Estimating, and Communicating Overdiagnosis in Cancer Screening.

The toll of inadequate health care is well-substantiated, but recognition is mounting that "too much" is also possible. Overdiagnosis represents one harm of too much medicine, but the concept can be confusing: It is often conflated with related harms (such as overtreatment, misclassification, false-positive results, and overdetection) and is difficult to measure because it cannot be directly observed. Because the U.S. Preventive Services Task Force (USPSTF) issues screening recommendations aimed largely at healthy persons, it has a particular interest in understanding harms related to screening, especially but not limited to overdiagnosis. In support of the USPSTF, the authors summarize the knowledge and provide guidance on defining, estimating, and communicating overdiagnosis in cancer screening. To improve consistency, thinking, and reporting about overdiagnosis, they suggest a specific definition. The authors articulate how variation in estimates of overdiagnosis can arise, identify approaches to estimating overdiagnosis, and describe best practices for communicating the potential for harm due to overdiagnosis.

Collaborative Modeling: Experience of the U.S. Preventive Services Task Force.

Models can be valuable tools to address uncertainty, trade-offs, and preferences when trying to understand the effects of interventions. Availability of results from two or more independently developed models that examine the same question (comparative modeling) allows systematic exploration of differences between models and the effect of these differences on model findings. Guideline groups sometimes commission comparative modeling to support their recommendation process. In this commissioned collaborative modeling, modelers work with the people who are developing a recommendation or policy not only to define the questions to be addressed but ideally, work side-by-side with each other and with systematic reviewers to standardize selected inputs and incorporate selected common assumptions. This paper describes the use of commissioned collaborative modeling by the U.S. Preventive Services Task Force (USPSTF), highlighting the general challenges and opportunities encountered and specific challenges for some topics. It delineates other approaches to use modeling to support evidence-based recommendations and the many strengths of collaborative modeling compared with other approaches. Unlike systematic reviews prepared for the USPSTF, the commissioned collaborative modeling reports used by the USPSTF in making recommendations about screening have not been required to follow a common format, sometimes making it challenging to understand key model features. This paper presents a checklist developed to critically appraise commissioned collaborative modeling reports about cancer screening topics prepared for the USPSTF.

Multiple Trigger Points for Quantifying Heat-Health Impacts: New Evidence from a Hot Climate.

BACKGROUND: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events. OBJECTIVES: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season. METHODS: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature-health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different "trigger points" at which heat-health intervention measures might be activated. RESULTS: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22 °C) across multiple health events and diagnoses. CONCLUSION: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

A mobile cloud-based Parkinson's disease assessment system for home-based monitoring.

BACKGROUND: Parkinson's disease (PD) is the most prevalent movement disorder of the central nervous system, and affects more than 6.3 million people in the world. The characteristic motor features include tremor, bradykinesia, rigidity, and impaired postural stability. Current therapy based on augmentation or replacement of dopamine is designed to improve patients' motor performance but often leads to levodopa-induced adverse effects, such as dyskinesia and motor fluctuation. Clinicians must regularly monitor patients in order to identify these effects and other declines in motor function as soon as possible. Current clinical assessment for Parkinson's is subjective and mostly conducted by brief observations made during patient visits. Changes in patients' motor function between visits are hard to track and clinicians are not able to make the most informed decisions about the course of therapy without frequent visits. Frequent clinic visits increase the physical and economic burden on patients and their families. OBJECTIVE: In this project, we sought to design, develop, and evaluate a prototype mobile cloud-based mHealth app, "PD Dr", which collects quantitative and objective information about PD and would enable home-based assessment and monitoring of major PD symptoms. METHODS: We designed and developed a mobile app on the Android platform to collect PD-related motion data using the smartphone 3D accelerometer and to send the data to a cloud service for storage, data processing, and PD symptoms severity estimation. To evaluate this system, data from the system were collected from 40 patients with PD and compared with experts' rating on standardized rating scales. RESULTS: The evaluation showed that PD Dr could effectively capture important motion features that differentiate PD severity and identify critical symptoms. For hand resting tremor detection, the sensitivity was .77 and accuracy was .82. For gait difficulty detection, the sensitivity was .89 and accuracy was .81. In PD severity estimation, the captured motion features also demonstrated strong correlation with PD severity stage, hand resting tremor severity, and gait difficulty. The system is simple to use, user friendly, and economically affordable. CONCLUSIONS: The key contribution of this study was building a mobile PD assessment and monitoring system to extend current PD assessment based in the clinic setting to the home-based environment. The results of this study proved feasibility and a promising future for utilizing mobile technology in PD management.

Heat-related deaths in hot cities: estimates of human tolerance to high temperature thresholds.

In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (ATmax) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥ 65 during the months May-October for years 2000-2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (ATmax = 90-97 °F; 32.2-36.1 °C) were below local median seasonal temperatures in the study period (ATmax = 99.5 °F; 37.5 °C). Heat threshold was defined as ATmax at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (ATmax = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (ATmax = 109 °F; 42.8 °C) and for all-cause mortality in females (ATmax = 107 °F; 41.7 °C) and males <65 years (ATmax = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.

Occupation and environmental heat-associated deaths in Maricopa county, Arizona: a case-control study.

BACKGROUND: Prior research shows that work in agriculture and construction/extraction occupations increases the risk of environmental heat-associated death. PURPOSE: To assess the risk of environmental heat-associated death by occupation. METHODS: This was a case-control study. Cases were heat-caused and heat-related deaths occurring from May-October during the period 2002-2009 in Maricopa County, Arizona. Controls were selected at random from non-heat-associated deaths during the same period in Maricopa County. Information on occupation, age, sex, and race-ethnicity was obtained from death certificates. Logistic regression analysis was used to estimate odds ratios for heat-associated death. RESULTS: There were 444 cases of heat-associated deaths in adults (18+ years) and 925 adult controls. Of heat-associated deaths, 332 (75%) occurred in men; a construction/extraction or agriculture occupation was described on the death certificate in 115 (35%) of these men. In men, the age-adjusted odds ratios for heat-associated death were 2.32 (95% confidence interval 1.55, 3.48) in association with construction/extraction and 3.50 (95% confidence interval 1.94, 6.32) in association with agriculture occupations. The odds ratio for heat-associated death was 10.17 (95% confidence interval 5.38, 19.23) in men with unknown occupation. In women, the age-adjusted odds ratio for heat-associated death was 6.32 (95% confidence interval 1.48, 27.08) in association with unknown occupation. Men age 65 years and older in agriculture occupations were at especially high risk of heat-associated death. CONCLUSION: The occurrence of environmental heat-associated death in men in agriculture and construction/extraction occupations in a setting with predictable periods of high summer temperatures presents opportunities for prevention.

Neighborhood effects on heat deaths: social and environmental predictors of vulnerability in Maricopa County, Arizona.

BACKGROUND: Most heat-related deaths occur in cities, and future trends in global climate change and urbanization may amplify this trend. Understanding how neighborhoods affect heat mortality fills an important gap between studies of individual susceptibility to heat and broadly comparative studies of temperature-mortality relationships in cities. OBJECTIVES: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000-2008). METHODS: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods. RESULTS: Neighborhood scores on three factors-socioeconomic vulnerability, elderly/isolation, and unvegetated area-varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor. CONCLUSIONS: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.

Cancer screening: the journey from epidemiology to policy.

PURPOSE: Cancer screening procedures have brought great benefit to the public's health. However, the science of cancer screening and the evidence arising from research in this field as it is applied to policy is complex and has been difficult to communicate, especially on the national stage. We explore how epidemiologists have contributed to this evidence base and to its translation into policy. METHODS: Our essay focuses on breast and lung cancer screening to identify commonalities of experience by epidemiologists across two different cancer sites and describe how epidemiologists interact with evolving scientific and policy environments. RESULTS: We describe the roles and challenges that epidemiologists encounter according to the maturity of the data, stakeholders, and the related political context. We also explore the unique position of cancer screening as influenced by the legislative landscape where, due to recent healthcare reform, cancer screening research plays directly into national policy. CONCLUSIONS: In the complex landscape for cancer screening policy, epidemiologists can increase their impact by learning from past experiences, being well prepared and communicating effectively.

The development and validation of a simulation tool for health policy decision making.

Computer simulations have been used to model infectious diseases to examine the outcomes of alternative strategies for managing their spread. Methicillin resistant Staphylococcus aureus (MRSA) skin and soft tissue infections have become prominent in many communities and efforts are underway to reduce the spread of this organism both in hospitals and communities. Currently, there are few tools for policy makers to use to examine the outcome of various choices when making decisions about MRSA. Using the example of MRSA, we describe, in this paper, a rigorous approach for development and validation of a tool that simulates the spread of MRSA infections. We used sensitivity analyses in a novel way and validated the simulation results against local data over time. Our approach for simulation development and validation is generalizeable to simulations of other diseases.

Glycemic control in youth with diabetes: the SEARCH for diabetes in Youth Study.

OBJECTIVE: To assess correlates of glycemic control in a diverse population of children and youth with diabetes. STUDY DESIGN: This was a cross-sectional analysis of data from a 6-center US study of diabetes in youth, including 3947 individuals with type 1 diabetes (T1D) and 552 with type 2 diabetes (T2D), using hemoglobin A(1c) (HbA(1c)) levels to assess glycemic control. RESULTS: HbA(1c) levels reflecting poor glycemic control (HbA(1c) >or= 9.5%) were found in 17% of youth with T1D and in 27% of those with T2D. African-American, American Indian, Hispanic, and Asian/Pacific Islander youth with T1D were significantly more likely to have higher HbA(1c) levels compared with non-Hispanic white youth (with respective rates for poor glycemic control of 36%, 52%, 27%, and 26% vs 12%). Similarly poor control in these 4 racial/ethnic groups was found in youth with T2D. Longer duration of diabetes was significantly associated with poorer glycemic control in youth with T1D and T2D. CONCLUSIONS: The high percentage of US youth with HbA(1c) levels above the target value and with poor glycemic control indicates an urgent need for effective treatment strategies to improve metabolic status in youth with diabetes.

Update on the methods of the U.S. Preventive Services Task Force: insufficient evidence.

The U.S. Preventive Services Task Force (USPSTF) seeks to provide reliable and accurate evidence-based recommendations to primary care clinicians. However, clinicians indicate frustration with the lack of guidance provided by the USPSTF when the evidence is insufficient to make a recommendation. This article describes a new USPSTF plan to commission its Evidence-based Practice Centers to collect information in 4 domains pertinent to clinical decisions about prevention and to report this information routinely. The 4 domains are potential preventable burden, potential harm of the intervention, costs (both monetary and opportunity), and current practice. The process and rationale used to select these domains are presented, along with examples of how clinicians might use the information to guide clinical decision making when evidence is insufficient.

Mortality, dementia, and apolipoprotein E genotype in elderly white women in the United States.

OBJECTIVES: To assess the risk of death in relation to apolipoprotein E (APOE) genotype and to evaluate how APOE genotype interacts with dementia and with other major medical conditions to affect survival. DESIGN: A 6-year prospective cohort study of dementia, APOE genotype and survival. SETTING: Health maintenance organization in southern California. PARTICIPANTS: One thousand eight hundred forty-two white women aged 75 and older. MEASUREMENTS: Dementia was determined using a multistage assessment procedure, medical record, and death certificate review. RESULTS: With women with the APOE 3/3 genotype as the referent, age-adjusted hazard ratios (HRs) for death according to genotype were 1.25 (95% confidence interval (CI)=1.00-1.56) for APOE 2/4, 3/4, or 4/4 and 0.83 (95% CI=0.62-1.13) for APOE 2/3 or 2/2. Survival was associated with APOE genotype (log rank test P=.02). Women with the APOE 2/4, 3/4, or 4/4 genotype died at an earlier age, and those with APOE 2/2 or 2/3 died later than those with the APOE 3/3 genotype. After adjustment for age, education, and hormone use, HRs for death were significantly higher in women with the APOE 2/4, 3/4, or 4/4 genotype who developed dementia (HR=3.74; 95% CI=2.81-4.99) and the APOE 2/3 genotype (HR=3.23; 95%=CI=1.97-5.28) than in women without dementia and the APOE 3/3 genotype. The HRs for death were greater with other medical conditions, but no interaction with any APOE genotype was found. CONCLUSION: In this population of elderly women, although having at least one epsilon4 allele increased the chances of an earlier death, having dementia increased the risk of death regardless of APOE genotype.