The Effects of Opt-out vs Opt-in Tobacco Treatment on Engagement, Cessation, and Costs: A Randomized Clinical Trial.

Importance: Tobacco use causes 7 million deaths per year; most national guidelines require people who use tobacco to opt in to care by affirming they are willing to quit. Use of medications and counseling is low even in advanced economy countries. Objective: To evaluate the efficacy of opt-out care vs opt-in care for people who use tobacco. Design, Setting, and Participants: In Changing the Default (CTD), a Bayesian adaptive population-based randomization trial, eligible patients were randomized into study groups, treated according to group assignment, and debriefed and consented for participation at 1-month follow-up. A total of 1000 adult patients were treated at a tertiary care hospital in Kansas City. Patients were randomized from September 2016 to September 2020; final follow-up was in March 2021. Interventions: At bedside, counselors screened for eligibility, conducted baseline assessment, randomized patients to study group, and provided opt-out care or opt-in care. Counselors and medical staff provided opt-out patients with inpatient nicotine replacement therapy, prescriptions for postdischarge medications, a 2-week medication starter kit, treatment planning, and 4 outpatient counseling calls. Patients could opt out of any or all elements of care. Opt-in patients willing to quit were offered each element of treatment described previously. Opt-in patients who were unwilling to quit received motivational counseling. Main Outcomes and Measures: The main outcomes were biochemically verified abstinence and treatment uptake at 1 month after randomization. Results: Of a total of 1000 eligible adult patients who were randomized, most consented and enrolled (270 [78%] of opt-in patients; 469 [73%] of opt-out patients). Adaptive randomization assigned 345 (64%) to the opt-out group and 645 (36%) to the opt-in group. The mean (SD) age at enrollment was 51.70 (14.56) for opt-out patients and 51.21 (14.80) for opt-out patients. Of 270 opt-in patients, 123 (45.56%) were female, and of 469 opt-out patients, 226 (48.19%) were female. Verified quit rates for the opt-out group vs the opt-in group were 22% vs 16% at month 1 and 19% vs 18% at 6 months. The Bayesian posterior probability that opt-out care was better than opt-in care was 0.97 at 1 month and 0.59 at 6 months. Treatment use for the opt-out group vs the opt-in group was 60% vs 34% for postdischarge cessation medication (bayesian posterior probability of 1.0), and 89% vs 37% for completing at least 1 postdischarge counseling call (bayesian posterior probability of 1.0). The incremental cost-effectiveness ratio was $678.60, representing the cost of each additional quit in the opt-out group. Conclusions and Relevance: In this randomized clinical trial, opt-out care doubled treatment engagement and increased quit attempts, while enhancing patients' sense of agency and alliance with practitioners. Stronger and longer treatment could increase cessation. Trial Registration: ClinicalTrials.gov Identifier: NCT02721082.

Assessment of DHA on reducing early preterm birth: the ADORE randomized controlled trial protocol.

BACKGROUND: Preterm birth contributes to 0.5 million deliveries in the United States (one of eight pregnancies) and poses a huge burden on public health with costs in the billions. Of particular concern is that the rate of earliest preterm birth (<34 weeks) (ePTB), which has decreased little since 1990 and has the greatest impact on the overall infant mortality, resulting in the greatest cost to society. Docosahexaenoic acid (DHA) supplementation provides a potential high yield, low risk strategy to reduce early preterm delivery in the US by up to 75%. We propose a Phase III Clinical Trial (randomized to low or high dose DHA, double-blinded) to examine the efficacy and safety of high dose DHA supplementation to reduce ePTB. We also plan for a secondary pregnancy efficacy analysis to determine if there is a subset of pregnancies most likely to benefit from DHA supplementation. METHODS: Between 900 and 1200 pregnant women who are ≥ 18 years old and between 12 and 20 weeks gestation will be recruited from three trial experienced academic medical institutions. Participants will be randomly assigned to two daily capsules of algal oil (totaling 800 mg DHA) or soybean and corn oil (0 mg DHA). Both groups will receive a commercially available prenatal supplement containing 200 mg DHA. Therefore, the experimental group will receive 1000 mg DHA/d and the control group 200 mg DHA/d. We will then employ a novel Bayesian response adaptive randomization design that assigns more subjects to the "winning" group and potentially allows for substantially smaller sample size while providing a stronger conclusion regarding the most effective group. The study has an overall Type I error rate of 5% and a power of 90%. Participants are followed throughout pregnancy and delivery for safety and delivery outcomes. DISCUSSION: We hypothesize that DHA will decrease the frequency of ePTB <34 weeks. Reducing ePTB is clinically important as these earliest preterm deliveries carry the highest risk of neonatal morbidity, as well as contribute significant stress for families and post a large societal burden. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (identifier: NCT02626299 ) on December 8, 2015. Additional summary details may be found in Table 1.

Assessment of mammography experiences and satisfaction among American Indian/Alaska Native women.

BACKGROUND: American Indian/Alaska Native (AI/AN) women have lower breast cancer (BCA) screening and 5-year survival rates than non-Hispanic Whites. Understanding reasons for low screening rates is important to combatting later stage diagnoses. The purpose of this study was to assess mammography experiences and satisfaction among AI/AN women. METHODS: Nine focus groups were held with rural (N = 15) and urban (N = 38) AI/AN women 40 years and older in Kansas and Kansas City, Missouri, living both near and far from Indian Health Service (IHS) and tribal facilities, to examine experiences and satisfaction with mammography. Transcripts were coded and themes identified using a community-based participatory research approach. FINDINGS: Themes were classified under knowledge, communication, and awareness of BCA; barriers to mammography; mammogram facility size; impressions of mammogram technologist; motivations for getting a mammogram; and how to improve the mammogram experience. Participants had knowledge of prevention, but described cultural reasons for not discussing it and described better experiences in smaller facilities. Participants indicated having a mammogram technologist who was friendly, knowledgeable, respectful, competent, and explained the test was a determining factor in satisfaction. Other factors included family history, physician recommendation, and financial incentives. Barriers included transportation, cost, perceptions of prejudice, and time constraints. Participants on reservations or near IHS facilities preferred IHS over mainstream providers. Suggestions for improvement included caring technologists, better machines with less discomfort, and education. CONCLUSIONS: Interventions to enhance the professionalism, empathy, and cultural awareness of mammogram technologists; reduce barriers; and provide positive expectations and incentives could improve satisfaction and compliance with screening mammography.

Capacity of US drug treatment facilities to provide evidence-based tobacco treatment.

Although people with drug problems consume a large proportion of cigarettes smoked in the United States, few drug treatment facilities offer tobacco treatment. Our analysis of 405 facilities showed that most had the skills but few had policies, leadership, or financial resources to provide evidence-based tobacco treatment. For-profits reported significantly fewer tobacco treatment resources than nonprofits. The Affordable Care and Mental Health Parity acts will improve treatment access for drug-dependent persons. To realize these acts' full promise, policymakers should ensure that clients have access to tobacco treatment.

End-of-life care in nursing homes: the high cost of staff turnover.

Nursing home staff turnover results in high cost--both economic and personal--and has a negative impact on the quality of care provided to residents at the end of life. Reducing staff turnover in nursing homes would benefit both the cost to the U.S. health care system, and, most importantly, the care residents receive in the vulnerable period leading to death. There is rising pressure on nursing homes to improve their palliative and end-of-life care practices and reduce transfers to hospital for situations and conditions that can be safely managed on site. Nursing care staff deserve an investment in the specific training necessary for them to give the highest quality care to dying residents. This training should be multifaceted and include the physiological, psychological, spiritual, interpersonal, and cultural (including ethnic) aspects of dying. Empowerment with these necessary knowledge, skills, and attitudes will not only result in better care for residents but likely also will reduce the burnout and frustration staff experience in caring for residents near death.

Input data quality control for NDNQI national comparative statistics and quarterly reports: a contrast of three robust scale estimators for multiple outlier detection.

BACKGROUND: To evaluate institutional nursing care performance in the context of national comparative statistics (benchmarks), approximately one in every three major healthcare institutions (over 1,800 hospitals) across the United States, have joined the National Database for Nursing Quality Indicators (NDNQI). With over 18,000 hospital units contributing data for nearly 200 quantitative measures at present, a reliable and efficient input data screening for all quantitative measures for data quality control is critical to the integrity, validity, and on-time delivery of NDNQI reports. METHODS: With Monte Carlo simulation and quantitative NDNQI indicator examples, we compared two ad-hoc methods using robust scale estimators, Inter Quartile Range (IQR) and Median Absolute Deviation from the Median (MAD), to the classic, theoretically-based Minimum Covariance Determinant (FAST-MCD) approach, for initial univariate outlier detection. RESULTS: While the theoretically based FAST-MCD used in one dimension can be sensitive and is better suited for identifying groups of outliers because of its high breakdown point, the ad-hoc IQR and MAD approaches are fast, easy to implement, and could be more robust and efficient, depending on the distributional property of the underlying measure of interest. CONCLUSION: With highly skewed distributions for most NDNQI indicators within a short data screen window, the FAST-MCD approach, when used in one dimensional raw data setting, could overestimate the false alarm rates for potential outliers than the IQR and MAD with the same pre-set of critical value, thus, overburden data quality control at both the data entry and administrative ends in our setting.

Outcome and assessment information set data that predict pressure ulcer development in older adult home health patients.

OBJECTIVES: To identify risk factors for pressure ulcer (PrU) development in older adult home health patients from admission Outcome and Assessment Information Set (OASIS) data. DESIGN: Retrospective cohort study. SETTING: A convenience sample of 5 home healthcare agencies from across the United States. PARTICIPANTS: The cohort sample included 5395 nonhospice patients 60 years or older who were admitted for intermittent skilled home healthcare between September 30, 2007, and January 30, 2009. MAIN MEASURES: OASIS data on age, sex, race/ethnicity, diagnoses, caregiving, mental health status, clinical status, and functional status relevant to PrU risk were extracted from the electronic medical record of eligible patients in participating agencies. Patient OASIS data were followed forward chronologically from admission to new PrU development or discharge. MAIN RESULTS: The 3323 females (61.6%) and 2072 males (38.4%) ranged from age 60 to 103 years (mean, 78.2 [SD, 8.6] years). The cumulative incidence of PrUs was 1.3% (n = 71 patients). Multiple logistic regression analyses revealed that bowel incontinence, needing assistance with grooming, dependence in ability to dress the upper body, dependence in ability to dress the lower body, dependence in toileting, inability to transfer, being chairfast or bedfast, and the presence of a PrU on admission were positively associated with new PrU development. Among patients who were PrU-free on admission, bowel incontinence and inability to transfer best predicted PrU development. CONCLUSION: Results suggest that OASIS data can be used to identify patients who are at risk for PrUs with potential for use nationwide.

The Box-Cox power transformation on nursing sensitive indicators: does it matter if structural effects are omitted during the estimation of the transformation parameter?

BACKGROUND: Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. METHODS: Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI® for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. RESULTS: Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. CONCLUSIONS: The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects.

An assessment of American Indian women's mammography experiences.

BACKGROUND: Mortality from breast cancer has increased among American Indian/Alaskan Native (AI/AN) women. Despite this alarming reality, AI/AN women have some of the lowest breast cancer screening rates. Only 37% of eligible AI/AN women report a mammogram within the last year and 52% report a mammogram within the last two years compared to 57% and 72% for White women. The experiences and satisfaction surrounding mammography for AI/AN women likely are different from that of women of other racial/ethnic groups, due to cultural differences and limited access to Indian Health Service sponsored mammography units. The overall goals of this study are to identify and understand the mammography experiences and experiential elements that relate to satisfaction or dissatisfaction with mammography services in an AI/AN population and to develop a culturally-tailored AI/AN mammography satisfaction survey. METHODS AND DESIGN: The three project aims that will be used to guide this work are: 1) To compare the mammography experiences and satisfaction with mammography services of Native American/Alaska Native women with that of Non-Hispanic White, Hispanic, and Black women, 2) To develop and validate the psychometric properties of an American Indian Mammography Survey, and 3) To assess variation among AI/AN women's assessments of their mammography experiences and mammography service satisfaction. Evaluations of racial/ethnic differences in mammography patient satisfaction have received little study, particularly among AI/AN women. As such, qualitative study is uniquely suited for an initial examination of their experiences because it will allow for a rich and in-depth identification and exploration of satisfaction elements. DISCUSSION: This formative research is an essential step in the development of a validated and culturally tailored AI/AN mammography satisfaction assessment. Results from this project will provide a springboard from which a maximally effective breast cancer screening program to benefit AI/AN population will be developed and tested in an effort to alter the current breast cancer-related morbidity and mortality trajectory among AI/AN women.