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Purpose: Native Americans and Latinos have higher COVID‐19 infection and mortality rates and may have limited access to diagnostic testing. Home‐based testing may improve access to care in rural and underserved populations. This study tests the effect of community health worker (CHW) support on accessibility, feasibility, and completion of COVID‐19 home testing among Native American and Latino adults living on the Flathead Reservation in Montana and in Yakima Valley, Washington. Methods: A two‐arm, multisite, pragmatic randomized controlled trial was conducted using block randomization stratified by site and participant age. Active arm participants received CHW assistance with online COVID‐19 test kit registration and virtual swabbing support. The passive arm participants received standard‐of‐care support from the kit vendor. Logistic regression modeled the association between study arm and test completion (primary outcome) and between study arm and test completion with return of valid test results (secondary outcome). Responses to posttest surveys and interviews were summarized using deductive thematic analysis. Findings: Overall, 63% of participants (n = 268) completed COVID‐19 tests, and 50% completed tests yielding a valid result. Active arm participants had higher odds of test completion (odds ratio: 1.66, 95% confidence interval [1.01, 2.75]). Differences were most pronounced among adults ≥60 years. Participants cited ease of use and not having to leave home as positive aspects, and transportation and mailing issues as negative aspects of home‐based testing. Conclusions: CHW support led to higher COVID‐19 test completion rates, particularly among older adults. Significant testing barriers included language, educational level, rurality, and test kit issues. [ABSTRACT FROM AUTHOR]

AbstractBackgroundBack pain is one of the most important causes of functional limitation, disability, and utilization of health care resources for adults of all ages, but especially among older adults. Despite the high prevalence of back pain in this population, important questions remain unanswered regarding the comparative effectiveness of commonly used diagnostic tests and treatments in the elderly. The overall goal of the Back pain Outcomes using Longitudinal Data (BOLD) project is to establish a rich, sustainable registry to describe the natural history and evaluate prospectively the effectiveness, safety, and cost-effectiveness of interventions for patients 65 and older with back pain.Methods/designBOLD is enrolling 5,000 patients ≥ 65 years old who present to a primary care physician with a new episode of back pain. We are recruiting study participants from three integrated health systems (Kaiser-Permanente Northern California, Henry Ford Health System in Detroit and Harvard Vanguard Medical Associates/ Harvard Pilgrim Health Care in Boston). Registry patients complete validated, standardized measures of pain, back pain-related disability, and health-related quality of life at enrollment and 3, 6 and 12 months later. We also have available for analysis the clinical and administrative data in the participating health systems’ electronic medical records. Using registry data, we will conduct an observational cohort study of early imaging compared to no early imaging among patients with new episodes of back pain. The aims are to: 1) identify predictors of early imaging and; 2) compare pain, functional outcomes, diagnostic testing and treatment utilization of patients who receive early imaging versus patients who do not receive early imaging. In terms of predictors, we will examine patient factors as well as physician factors.DiscussionBy establishing the BOLD registry, we are creating a resource that contains patient-reported outcome measures as well as electronic medical record data for elderly patients with back pain. The richness of our data will allow better matching for comparative effectiveness studies than is currently possible with existing datasets. BOLD will enrich the existing knowledge base regarding back pain in the elderly to help clinicians and patients make informed, evidence-based decisions regarding their care.

Previous studies demonstrate that self-reports of mammography screening for breast cancer and colonoscopy screening for colorectal cancer demonstrate concordance, based on adherence to screening guidelines, with electronic medical records (EMRs) in over 90% of those interviewed, as well as high sensitivity and specificity, and can be used for monitoring our Healthy People goals. However, for screening tests for cervical and lung cancers, and for various sub-populations, concordance between self-report and EMRs has been noticeably lower with poor sensitivity or specificity. This study aims to test the validity and reliability of lung, colorectal, cervical, and breast cancer screening questions from the 2021 and 2022 National Health Interview Survey (NHIS). We present the protocol for a study designed to measure the validity and reliability of the NHIS cancer screening questions compared to EMRs from four US-based healthcare systems. We planned a randomized trial of a phone- vs web-based survey with NHIS questions that were previously revised based on extensive cognitive interviewing. Our planned sample size will be 1576 validity interviews, and 1260 interviews randomly assigned at 1 or 3 months after the initial interview. We are enrolling people eligible for cancer screening based on age, sex, and smoking history per US Preventive Services Task Force recommendations. We will evaluate question validity using concordance, sensitivity, specificity, positive predictive value, negative predictive value, and report-to-records ratio. We further are randomizing participants to complete a second survey 1 vs 3 months later to assess question reliability. We suggest that typical measures of concordance may need to be reconsidered in evaluating cancer screening questions. [ABSTRACT FROM AUTHOR]

The goal of this study is to understand the design needs and preferences of patients and care partners for a needleless vascular connection device called the Ambulatory Kidney to Improve Vitality (AKTIV) Connection. One of the greatest barriers to patients' self-management of home-based hemodialysis treatments is connecting the dialysis device to their own blood supply. We gathered detailed data on patients' and care partners' design needs and preferences with the goal of mitigating this barrier to usage with the AKTIV Connection. In particular, we interviewed 16 hemodialysis patients and 7 care partners using a mixed-method approach of rating and semi-structured questions. Participants indicated they would prefer carrying the AKTIV Connection on or around the waist or in a belt bag. Inductive content analysis showed that the participants considered the ideal AKTIV Connection to connect to a patient's bloodstream in the chest area, be rectangularly shaped with rounded corners, and have upper size and weight limits in reference to a modern-day smartphone. We also identified 10 categories of ideal features of the AKTIV Connection and 12 categories of concerns related to connecting the AKTIV Connection to a patient's bloodstream. The findings from this study will help guide the design and development of the AKTIV Connection so that it meets patients' and care partners' needs and preferences, ultimately helping improve the quality of life of patients with end-stage renal disease. [ABSTRACT FROM AUTHOR]

Multicancer early detection (MCED) tests represent a potentially game‐changing early cancer detection technology. Modeling efforts, such as those of Hudnut et al. in this issue of Cancer, as well as systematic clinical studies and data collection, along with public health and primary care efforts, need to be undertaken to determine whether MCED tests become an opportunity to decrease the heavy burden of cancer for all. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer is the most common cause of cancer related death in the US, but survival is far better when people are diagnosed at an earlier stage. There are currently no clinical quality measures that are routinely used to measure the quality or timeliness of diagnosis of lung cancer in the US. We used Natural Language Processing (NLP) to extract information on the symptoms and signs that had been recorded in the electronic medical records of patients presenting in ambulatory care over the 2 years prior to their diagnosis with lung cancer. We found that the time from the first recorded symptoms/signs associated with lung cancer to diagnosis was 570 days. The time intervals from chest CT or chest X-ray imaging to diagnosis, and from specialist consultation to diagnosis were shorter—at 43 and 72 days, respectively. Advanced techniques such as NLP can be used to extract detailed information from electronic medical records, that could potentially be used to create clinical quality measures with the goal of improving the timeliness of diagnosis of this cancer. The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012–2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273–691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11–240), specialist consultation to diagnosis 72 days (IQR 13–456), and from diagnosis to treatment initiation 7 days (IQR 0–36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis. [ABSTRACT FROM AUTHOR]

Although mobile hemodialysis treatments have been found to be an effective alternative to current in-center and home-based hemodialysis treatments, many barriers to its successful implementation remain. These barriers include the lack of considering user-centered monitoring protocols. This study investigates 24 patients' and 12 care partners' expectations for monitoring procedures for a mobile hemodialysis device. Individual semi-structured interviews were conducted at three locations within the Veterans Affairs Health Care System: Seattle, WA; Nashville, TN; and Louisville, KY. All interviews were transcribed and analyzed using inductive or deductive content analysis approaches. We identified 10 categories of indicators suggesting patients' needs to receive dialysis treatment and 11 categories of indicators suggesting patients' successful dialysis treatment. Furthermore, we identified six categories of patients' and care partners' design expectations for monitoring procedures. The findings from this study have the potential to guide the development of a monitoring system to help ensure users' acceptance of future mobile hemodialysis devices. [ABSTRACT FROM AUTHOR]