An overview of the Be Well Home Health Navigator Program to reduce contaminants in well water: Design and methods.

BACKGROUND: The Be Well Home Health Navigator Program is a prospective, randomized controlled trial (RCT) implemented to compare a community health navigator program to usual care program to reduce contaminants in drinking water. DESIGN AND SETTING: This 4-year two-armed RCT will involve well owners in Oregon that have private drinking water wells that contain arsenic, nitrate, or lead above maximum contaminant levels. INTERVENTION: The intervention leverages the trusted relationship between Cooperative Extension Service (CES) Community Educators and rural well owners to educate, assist and motivate to make decisions and set actionable steps to mitigate water contamination. In this study, CES will serve as home health navigators to deliver: 1) individualized feedback, 2) positive reinforcement, 3) teach-back moments, 4) decision-making skills, 5) navigation to resources, 6) self-management, and 7) repeated contact for shaping and maintenance of behaviors. Usual care includes information only with no access to individual meetings with CES. MEASURABLE OUTCOMES: Pre-specified primary outcomes include 1) adoption of treatment to reduce exposure to arsenic, nitrate, or lead in water which may include switching to bottled water and 2) engagement with well stewardship behaviors assessed at baseline, and post-6 and 12 months follow-up. Water quality will be measured at baseline and 12-month through household water tests. Secondary outcomes include increased health literacy scores and risk perception assessed at baseline and 6-month surveys. IMPLICATIONS: The results will demonstrate the efficacy of a domestic well water safety program to disseminate to other CES organizations. TRIAL REGISTRATION NUMBER: NCT05395663.

Sickening: who is protecting pharma consumers?

In 2022, John Abramson published Sickening: How Big Pharma Broke American Healthcare and How We Can Repair It. The book illustrates how large pharmaceutical companies have become misinformation machines that have corrupted peer-reviewed journals, systematic review authors, and guideline committees. Industry influence includes selective reporting of clinical trial results and selection of control groups likely to enhance benefits and disguise side effects. Other documented forms of influence include clear conflicts of interest for members of guideline committees and even direct intimidation. The book concludes with a series of implementable reforms, such as ensuring the accuracy and completeness of evidence, developing an independent National Health Board, designing clinical research to optimize health outcomes, requiring the posting of research data so that independent scholars can replicate analyses, and ensuring the accuracy of direct consumer advertising. Abramson's book is a must read for students of medicine, public health, and public policy.

Review of Evidence Supporting 2022 US Food and Drug Administration Drug Approvals.

This cross-sectional study examines the design and funding of studies, nd evidence available on ClinicalTrials.gov for drugs approved in 2022.

Explanations for variations in hospital expenditures among four large California counties.

OBJECTIVE: To investigate competing explanations for why Medicare Fee for Service (FFS) and private sector payments lead to hospital cost variations in Californian counties. DATA SOURCES: Ratios of private to Medicare hospital costs were obtained from state-based all-payer claims databases. Demographics were estimated from the U.S. Census Bureau and the California Health Interview Survey. Medicaid and Medicare spending was obtained from Kaiser Family Foundation. Medicare Advantage enrollment was obtained from the California Department of Health Care Services and market consolidation was estimated using the Herfindahl-Hirschman Index (HHI). STUDY DESIGN: Per capita costs, demographics, Medicaid and Medicare spending, Medicare Advantage enrollment, and HHI scores were compared for San Francisco (SF), Sacramento, Los Angeles (LA), and San Diego (SD). PRINCIPAL FINDINGS: LA hospitals had the lowest per capita private insurer costs, but the highest Medicare FFS costs. The findings might be explained by a lower HHI for LA, indicating a more competitive market, than SD, SF, and Sacramento. CONCLUSIONS: Medicare FFS hospital costs do not provide an accurate representation of health care spending in Californian counties. In more competitive markets, private insurance companies can negotiate lower prices, while oversupply may allow facilities to increase volume in Medicare FFS.

Depression trial results: A cross-sectional study of ClinicalTrials.gov.

Published clinical trials represent a subsample of the objective information needed to appraise treatments for depression. We characterize the extent of selective and delayed reporting in a systematic review (PROSPERO #CRD42020173606) of depression trial results registered on ClinicalTrials.gov. Inclusion criteria were studies registered on ClinicalTrials.gov with depression as the condition, had enrolled ages 18 and over, were completed between January 1, 2008 and May 1, 2019, and had posted results by February 1, 2022. Cox regression analyses of time to result posting from registration and from study completion included enrollment as a covariate. Among 442 protocols, median result posting occurred over two years after study completion and five years after registration. Among protocols with incomplete results, effect sizes (d or W) were calculated for 134 protocols. Median effect sizes for protocols with incomplete results were small (0.16, 95% CI 0.08, 0.21). For 28% of protocols, observed effects were contrary to the expected direction. Between-group effect size calculations were based on post-treatment data as pre-treatment data were inconsistently provided. Although drug and device trials in the U.S. are required to register on ClinicalTrials.gov, compliance is imperfect, and submissions are not peer reviewed. For depression treatment trials, long intervals between study completion and posting of results are common. Further, investigators often fail to report the results of statistical tests. Failure to post trial results in a timely manner and omission of statistical test reporting may lead to overestimates of treatment effects in systematic literature reviews.

Caring for People With Depression: Costs Among 43 Million Commercially Insured Patients With or Without Comorbid Illnesses.

BACKGROUND: Depression is a common comorbidity for patients with chronic medical conditions. Although the costs of treating chronic medical illness in combination with depression are believed to be significantly higher than the costs of treating each condition independently, few studies have formally modeled the cost consequences of mental health comorbidity. PURPOSE: To estimate the relative magnitude of the independent and synergistic contributions to health care costs from depression diagnosis and other chronic physical health conditions. METHODS: Cross-sectional, observational study using all individuals >18 years of age in the national Blue Cross Blue Shield (BCBS) Axis claims database (N = 43,872,144) from calendar year 2018. General linear models with and without interaction terms were used to assess the relative magnitude of independent and synergistic contributions to total annual health care costs of depression alone and in combination with coronary heart disease, chronic kidney disease, chronic obstructive pulmonary disease, diabetes (both types 1 and 2), hypertension, and arthritis. RESULTS: The incremental annual cost associated with having a diagnosis of depression was $2,951 compared to $1,986-$6,251 for the other chronic physical conditions. The interaction between depression and chronic conditions accounted for less than one-hundredth of the amount of variation in costs explained by the main effects of depression and each chronic physical condition. CONCLUSIONS: The independent increase in total annual health care costs associated with a depression diagnosis was comparable to that of many common physical chronic conditions. This finding underscores the importance of health care service and payment models that acknowledge depression as an equal contributor to overall health care costs. The combination of depression and another chronic condition did not synergistically increase total annual health care costs beyond the increases in costs associated with each condition independently. This finding has implications for simplifying risk adjustment models.

It is widely believed that depression, when combined with other chronic physical conditions, systematically inflates health care costs. For example, it is assumed that the costs of caring for a patient with both depression and heart disease are higher than the costs of caring for each condition independently. Using a database that included 43 million commercially insured people in the United States, we found that the costs of care for patients with depression were comparable to the costs for patients with other chronic medical conditions. This result supports the need for mental health parity and for trained mental health care providers in medical settings. We then considered the costs of caring for people with depression with or with or without one of seven common chronic physical condition. Contrary to expectation, the combination of depression and any of the diagnoses appeared to have largely independent relationships with health care costs. The results contradict the suggestion that depression and chronic condition diagnoses act synergistically to inflate health care expenditures.

Incidence of Ankylosing Spondylitis Among Male and Female United States Army Personnel.

OBJECTIVE: Incidence rates of ankylosing spondylitis (AS) among males versus females are poorly understood. Results of prior research have been mixed, including findings of a 3:1 incidence ratio for males versus females, but with increasing AS rates among females. The objective was to estimate the incidence of AS among members of the US military. METHODS: We estimated the incidence of AS in a retrospective cohort study of diverse, working-age US military service members during March 2014 to June 2017 (n = 728,556) who underwent clinical practice guideline-directed screening for chronic back pain. Incident AS cases were identified using diagnostic codes from electronic medical and administrative records. RESULTS: In contrast to some prior studies, AS incidence was similar among males and females (incidence rate ratio 1.16, P = 0.23; adjusted odds ratio [OR] 0.79 [95% confidence interval (95% CI) 0.61-1.02]; P = 0.072). AS rates increased approximately monotonically with age. Consistent with prior research, the AS incidence rate was greater in the White population than in the Black population (adjusted OR 1.39 [95% CI 1.01-1.66]; P = 0.04). CONCLUSION: In this study population, the incidence of AS was similar for the sexes. Previous observations of male predominance have typically been derived from clinic populations that are less representative of the US race/ethnicity distribution and based on disease ascertainment tools that may have identified subjects later in their disease course. Our study population also differed in being subject to organized screenings for musculoskeletal symptoms. Our findings suggest that sex may not predict AS incidence in the US population.

Continuous monitoring of eating and sleeping behaviors in the home environments of older adults: a case study demonstration.

Accurate observation of patient functioning is necessary for rigorous clinical research and for improving the quality of patient care. However, clinic or laboratory environments systematically differ from the contexts of everyday life. Further, assessments that are completed in a single institutional session may not be generalizable. Here, we describe a computer vision methodology that measures human functioning continuously in the environments where patients live, sleep, and eat.

An evaluation of a care coaching and provider referral intervention for behavioral health needs.

OBJECTIVES: To evaluate changes in health care spending and utilization associated with a telehealth-based care coach-supported and behavioral health (BH) provider referral intervention in the United States. STUDY DESIGN: Observational retrospective cohort study with propensity score matching of treated and control groups. METHODS: Difference-in-differences (DID) analysis was used to calculate per-member per-month (PMPM) savings and changes in utilization in a treated group relative to matched controls over 36 months. The study included 1800 adults with substance use disorder (SUD), anxiety, or depression who were eligible for the intervention. Treated members (n = 900) graduated from the program. Matched control members (n = 900) were eligible but never enrolled. Primary outcomes included all-cause and disease-attributable health care cost and utilization PMPM, categorized by place of service. RESULTS: There were statistically significant reductions in total all-cause medical costs of $485 PMPM (P < .001) and a 66% pre-post reduction in inpatient encounters, with $488 PMPM DID savings for inpatient admissions (P < .001) among the treated cohort compared with the control cohort over 36 months. Conversely, there were statistically significant cost increases ($110 PMPM; P < .001) for all-cause office visits in the treated cohort compared with the control cohort. Similar results were seen in SUD-attributable and BH-attributable costs. CONCLUSIONS: Although the results could be affected by unmeasured confounding, they suggest that care coaching interventions that offer BH provider referrals may produce long-term savings, reductions in avoidable utilization, and increases in targeted services to treat BH conditions. Rigorous evaluations are needed to confirm these findings.

Service discharges among US Army personnel with selected musculoskeletal and skin conditions: a retrospective cohort study.

OBJECTIVES: To determine the probability of discharge from military service among soldiers following an incident diagnosis of ankylosing spondylitis (AS), rheumatoid arthritis (RA), psoriasis or systemic lupus erythematous. METHODS: All soldiers on active duty in the US Army between January 2014 and June 2017 were included in a retrospective cohort analysis. Termination from service was ascertained using personnel records. Diagnostic codes were used to identify incident cases of the four musculoskeletal and skin diseases and, for comparison, diabetes mellitus (DM). Time to discharge was modelled using sex stratified multivariate survival analysis. RESULTS: The analysis included 657 417 individuals with a total of 1.2 million person-years of observation. An elevated risk of discharge was observed in association with each of the five chronic conditions studied. The increase in adjusted risk of discharge was highest among soldiers with AS (men, HR=2.5, 95% CI 2.1 to 3.0; women, HR=2.1, 95% CI 1.4 to 3.2) and with DM (men, HR=2.4, 95% CI 2.2 to 2.7; women, HR=2.2, 95% CI 1.8 to 2.5), followed by those with RA (men, HR=1.8, 95% CI 1.5 to 2.2; women, HR=1.8, 95% CI 1.4 to 2.4). CONCLUSIONS: Military discharges are consequential for the service and the service member. The doubling in risk of discharge for those with AS or RA was comparable to that for personnel with DM. Conditions that affect the spine and peripheral joints may often be incompatible with military readiness. Nevertheless, a substantial fraction of service members with these diagnoses continued in service.

Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults.

INTRODUCTION: In 2020, prior to COVID-19 vaccine rollout, the Brighton Collaboration created a priority list, endorsed by the World Health Organization, of potential adverse events relevant to COVID-19 vaccines. We adapted the Brighton Collaboration list to evaluate serious adverse events of special interest observed in mRNA COVID-19 vaccine trials. METHODS: Secondary analysis of serious adverse events reported in the placebo-controlled, phase III randomized clinical trials of Pfizer and Moderna mRNA COVID-19 vaccines in adults (NCT04368728 and NCT04470427), focusing analysis on Brighton Collaboration adverse events of special interest. RESULTS: Pfizer and Moderna mRNA COVID-19 vaccines were associated with an excess risk of serious adverse events of special interest of 10.1 and 15.1 per 10,000 vaccinated over placebo baselines of 17.6 and 42.2 (95 % CI -0.4 to 20.6 and -3.6 to 33.8), respectively. Combined, the mRNA vaccines were associated with an excess risk of serious adverse events of special interest of 12.5 per 10,000 vaccinated (95 % CI 2.1 to 22.9); risk ratio 1.43 (95 % CI 1.07 to 1.92). The Pfizer trial exhibited a 36 % higher risk of serious adverse events in the vaccine group; risk difference 18.0 per 10,000 vaccinated (95 % CI 1.2 to 34.9); risk ratio 1.36 (95 % CI 1.02 to 1.83). The Moderna trial exhibited a 6 % higher risk of serious adverse events in the vaccine group: risk difference 7.1 per 10,000 (95 % CI -23.2 to 37.4); risk ratio 1.06 (95 % CI 0.84 to 1.33). Combined, there was a 16 % higher risk of serious adverse events in mRNA vaccine recipients: risk difference 13.2 (95 % CI -3.2 to 29.6); risk ratio 1.16 (95 % CI 0.97 to 1.39). DISCUSSION: The excess risk of serious adverse events found in our study points to the need for formal harm-benefit analyses, particularly those that are stratified according to risk of serious COVID-19 outcomes. These analyses will require public release of participant level datasets.

A Novel Explainability Approach for Technology-Driven Translational Research on Brain Aging.

Brain aging leads to difficulties in functional independence. Mitigating these difficulties can benefit from technology that predicts, monitors, and modifies brain aging. Translational research prioritizes solutions that can be causally linked to specific pathophysiologies at the same time as demonstrating improvements in impactful real-world outcome measures. This poses a challenge for brain aging technology that needs to address the tension between mechanism-driven precision and clinical relevance. In the current opinion, by synthesizing emerging mechanistic, translational, and clinical research-related frameworks, and our own development of technology-driven brain aging research, we suggest incorporating the appreciation of four desiderata (causality, informativeness, transferability, and fairness) of explainability into early-stage research that designs and tests brain aging technology. We apply a series of work on electrocardiography-based "peripheral" neuroplasticity markers from our work as an illustration of our proposed approach. We believe this novel approach will promote the development and adoption of brain aging technology that links and addresses brain pathophysiology and functional independence in the field of translational research.

Transparency of results reporting for depression treatment studies in ClinicalTrials.gov: a cross-sectional study.

OBJECTIVES: Depression affects an estimated 7% of the adult population at an estimated cost of over US$200 billion/year in the USA. Complete, transparent reporting of clinical trial data facilitates valid estimates of treatment efficacy. In the USA, ClinicalTrials.gov increases transparency through mandatory prospective trial registration and outcome reporting. We examined characteristics of the transparent reporting of depression treatment studies registered in ClinicalTrials.gov. DESIGN: Cross sectional. SETTING AND PARTICIPANTS: US-based studies identified in a search of ClinicalTrials.gov with depression as the condition, enrolling ages 18 and older, and completed between 1 January 2008 and 1 May 2019. INTERVENTIONS: All interventions were included. MAIN OUTCOMES AND MEASURES: The main outcome was whether any results were reported prior to 1 May 2020. Data were extracted regarding inclusion and exclusion criteria, publications related to the study and specification of hypotheses. RESULTS: 725 studies involving 156 634 patients met inclusion criteria. 416 (57.4%) of the studies posted some results. However, statistical test results were not included in 230 studies (55.3%). Most studies had data that could have been analysed and reported. Compared with studies without results, studies with any results were more likely to have hypotheses, include drug treatment conditions, and to have publications related to the study. CONCLUSIONS: Required study registration does not always result in transparent outcome reporting. Better compliance with mandated reporting and improved reporting standards would facilitate a more comprehensive representation of depression treatment research.

Health-Related Quality of Life Measurement in Public Health.

Patient-reported outcomes are recognized as essential for the evaluation of medical and public health interventions. Over the last 50 years, health-related quality of life (HRQoL) research has grown exponentially from 0 to more than 17,000 papers published annually. We provide an overview of generic HRQoL measures used widely in epidemiological studies, health services research, population studies, and randomized clinical trials [e.g., Medical Outcomes Study SF-36 and the Patient-Reported Outcomes Measurement Information System (PROMIS®)-29]. In addition, we review methods used for economic analysis and calculation of the quality-adjusted life year (QALY). These include the EQ-5D, the Health Utilities Index (HUI), the self-administered Quality of Well-being Scale (QWB-SA), and the Health and Activities Limitation Index (HALex). Furthermore, we consider hybrid measures such as the SF-6D and the PROMIS-Preference (PROPr). The plethora of HRQoL measures has impeded cumulative science because incomparable measures have been used in different studies. Linking among different measures and consensus on standard HRQoL measurement should now be prioritized. In addition, enabling widespread access to common measures is necessary to accelerate future progress.

Covid-19 pandemic lessons: uncritical communication of test results can induce more harm than benefit and raises questions on standardized quality criteria for communication and liability.

BACKGROUND: The COVID-19 pandemic is characterized by both health and economic risks. A 'safety loop' model postulates risk-related decisions are not based on objective and measurable risks but on the subjective perception of those risks. We here illustrate a quantification of the difference between objective and subjective risks. METHOD: The objective risks (or chances) can be obtained from traditional 2 × 2 tables by calculating the positive (+LR) and negative (-LR) likelihood ratios. The subjective perception of objective risks is calculated from the same 2 × 2 tables by exchanging the X- and Y-axes. The traditional 2 × 2 table starts with the hypothesis, uses a test and a gold standard to confirm or exclude the investigated condition. The 2 × 2 table with inverted axes starts with the communication of a test result and presumes that the communication of bad news (whether right or false) will induce 'Perceived Anxiety' while good news will induce 'Perceived Safety'. Two different functions (confirmation and exclusion) of both perceptions (Perceived Anxiety and Safety) can be quantified with those calculations. RESULTS: The analysis of six published tests and of one incompletely reported test on COVID-19 polymerase chain reactions (completed by four assumptions on high and low sensitivities and specificities) demonstrated that none of these tests induces 'Perceived Safety'. Eight of the ten tests confirmed the induction of 'Perceived Anxiety' with + LRs (range 3.1-5900). In two of these eight tests, a -LR (0.25 and 0.004) excluded the induction of 'Perceived Safety'. CONCLUSIONS: Communication of test results caused perceived anxiety but not perceived safety in 80% of the investigated tests. Medical tests - whether true or false - generate strong psychological messages. In the case of COVID-19 tests may induce more perceived anxiety than safety. Risk communication has to balance objective and subjective risks.