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Quality improvement (QI) may be aimed at improving care for all patients, or it may be targeted at only certain patient groups. Health care providers have little guidance when determining when targeted QI may be preferred.The aim was to develop a method for quantifying performance inconsistency and guidelines for when inconsistency indicates targeted QI, which we apply to the performance of health plans for different patient groups.Retrospective analysis of 7 Health Care Effectiveness Data and Information Set (HEDIS) measures of clinical care quality.All Medicare Advantage (MA) beneficiaries eligible for any of 7 HEDIS measures 2015-2018.MA plans with higher overall performance tended to be less inconsistent in their performance (r=-0.2) across groups defined by race-and-ethnicity and low-income status (ie, dual eligibility for Medicaid or receipt of Low-Income Subsidy). Plan characteristics were usually associated with only small differences in inconsistency. The characteristics associated with differences in consistency [eg, size, Health Maintenance Organization (HMO) status] were also associated with differences in overall performance. We identified 9 (of 363) plans that had large inconsistency in performance across groups (0.8 SD) and investigated the reasons for inconsistency for 2 example plans.This newly developed inconsistency metric may help those designing and evaluating QI efforts to appropriately determine when targeted QI is preferred. It can be used in settings where performance varies across groups, which can be defined by patient characteristics, geographic areas, hospital wards, etc. Effectively targeting QI efforts is essential in today's resource-constrained health care environment.

OBJECTIVE: To investigate (a) the magnitude of the independent associations of neighborhood‐level and person‐level social risk factors (SRFs) with quality, (b) whether neighborhood‐level SRF associations may be proxies for person‐level SRF associations, and (c) how the association of person‐level SRFs and quality varies by neighborhood‐level SRFs. DATA SOURCES: 2015–2016 Medicare Advantage HEDIS data, Medicare beneficiary administrative data, and 2016 American Community Survey (ACS). STUDY DESIGN: Mixed effects linear regression models (1) estimated overall inequities by neighborhood‐level and person‐level SRFs, (2) compared neighborhood‐level associations to person‐level associations, and (3) tested the interactions of person‐level SRFs with corresponding neighborhood‐level SRFs. DATA COLLECTION/EXTRACTION METHODS: Beneficiary‐level SES and disability administrative data and five‐year ACS neighborhood‐level SRF information were each linked to HEDIS data. PRINCIPAL FINDINGS: For all or nearly all HEDIS measures, quality was worse in neighborhoods lower in SES and in neighborhoods with higher proportions of residents with a disability. Quality by neighborhood racial and ethnic composition was mixed. Accounting for corresponding person‐level SRFs reduced neighborhood SRF associations by 25% for disability, 43% for SES, and 74%–102% for racial and ethnic groups. Person‐level SRF coefficients were not consistently reduced in models that added neighborhood‐level SRFs. In 19 of 35 instances, there were significant (p

BACKGROUND Each year, about 10% of Medicare Advantage (MA) enrollees voluntarily switch to another MA contract, while another 2% voluntarily switch from MA to fee-for-service Medicare. Voluntary disenrollment from MA plans is related to beneficiaries' negative experiences with their plan, disrupts the continuity of care, and conflicts with goals to reduce Medicare costs. Little is known about racial/ethnic disparities in voluntary disenrollment from MA plans. OBJECTIVE The objective of this study was to investigate differences in rates of voluntary disenrollment from MA plans by race/ethnicity. SUBJECTS A total of 116,770,319 beneficiaries enrolled in 736 MA plans in 2015. METHODS Differences in rates of disenrollment across racial/ethnic groups [Asian or Pacific Islander (API), Black, Hispanic, and White] were summarized using 4 types of logistic regression models: adjusted and unadjusted models estimating overall differences and adjusted and unadjusted models estimating within-plan differences. Unadjusted overall models included only racial/ethnic group probabilities as predictors. Adjusted overall models added age, sex, dual eligibility, disability, and state of residence as control variables. Between-plan differences were estimated by subtracting within-plan differences from overall differences. RESULTS Adjusted rates of disenrollment were significantly (P

Algorithms are currently used to assist in a wide array of health care decisions. Despite the general utility of these health care algorithms, there is growing recognition that they may lead to unintended racially discriminatory practices, raising concerns about the potential for algorithmic bias. An intuitive precaution against such bias is to remove race and ethnicity information as an input to health care algorithms, mimicking the idea of "race-blind" decisions. However, we argue that this approach is misguided. Knowledge, not ignorance, of race and ethnicity is necessary to combat algorithmic bias. When race and ethnicity are observed, many methodological approaches can be used to enforce equitable algorithmic performance. When race and ethnicity information is unavailable, which is often the case, imputing them can expand opportunities to not only identify and assess algorithmic bias but also combat it in both clinical and nonclinical settings. A valid imputation method, such as Bayesian Improved Surname Geocoding, can be applied to standard data collected by public and private payers and provider entities. We describe two applications in which imputation of race and ethnicity can help mitigate potential algorithmic biases: equitable disease screening algorithms using machine learning and equitable pay-for-performance incentives.

OBJECTIVES: To evaluate whether sleep disturbances vary along a continuum of functional limitations in a large nationally representative sample of US adults. METHODS: Using 2014–2015 National Health Interview Survey data (n=33,424), we considered associations between each of five sleep disturbance measures (duration, trouble falling asleep, trouble staying asleep, use of sleep medications, waking rested) and Functional Limitations Index (FLI) score, which distinguishes among adults with little-or-no (least-limited), moderate (somewhat-limited), and high functional limitations (most-limited). RESULTS: Somewhat-limited and most-limited respondents reported significantly worse sleep health for all sleep disturbance measures than people with little-or-no limitations, even controlling for body mass index, psychological distress, and 14 health indicators. CONCLUSIONS: People with significant self-reported limitations in physical functioning, independent of specific disabilities or disabling condition, report more sleep disturbances. Clinicians may want to evaluate the sleep health of patients with functional limitations.

BACKGROUND: Social risk factors (SRFs) such as minority race-and-ethnicity or low income are associated with quality-of-care, health, and healthcare outcomes. Organizations might prioritize improving care for easier-to-treat groups over those with SRFs, but measuring, reporting, and further incentivizing quality-of-care for SRF groups may improve their care. OBJECTIVE: To develop, as a proof-of-concept, a Health Equity Summary Score (HESS): a succinct, easy-to-understand score that could be used to promote high-quality care to those with SRFs in Medicare Advantage (MA) health plans, which provide care for almost twenty million older and disabled Americans and collect extensive quality measure and SRF data. DESIGN: We estimated, standardized, and combined performance scores for two sets of quality measures for enrollees in 2013–2016 MA health plans, considering both current levels of care, within-plan improvement, and nationally benchmarked improvement for those with SRFs (specifically, racial-and-ethnic minority status and dual-eligibility for Medicare and Medicaid). PARTICIPANTS: All MA plans with publicly reported quality scores and 500 or more 2016 enrollees. MAIN MEASURES: Publicly reported clinical quality and patient experience measures. KEY RESULTS: Almost 90% of plans measured for MA Star Ratings received a HESS; plans serving few patients with SRFs were excluded. The summary score was moderately positively correlated with publicly reported overall Star Ratings (r = 0.66–0.67). High-scoring plans typically had sizable enrollment of both racial-and-ethnic minorities (38–42%) and dually eligible beneficiaries (29–38%). CONCLUSIONS: We demonstrated the feasibility of developing and estimating a HESS that is intended to promote and incentivize excellent care for racial-and-ethnic minorities and dually eligible MA enrollees. The HESS measures SRF-specific performance and does not simply duplicate overall plan Star Ratings. It also identifies plans that provide excellent care to large numbers of those with SRFs. Our methodology could be extended to other SRFs, quality measures, and settings.

Background General population surveys are increasingly offering broader response options for questions on sexual orientation-for example, not only gay or lesbian, but also "something else" (SE) and "don't know" (DK). However, these additional response options are potentially confusing for those who may not know what the terms mean. Researchers studying sexual orientation-based disparities face difficult methodological trade-offs regarding how best to classify respondents identifying with the SE and DK categories. Objectives Develop respondent-level probabilities of sexual minority orientation without excluding or misclassifying the potentially ambiguous SE and DK responses. Compare 3 increasingly inclusive analytic approaches for estimating health disparities using a single item: (a) omitting SE and DK respondents; (b) classifying SE as sexual minority and omitting DK; and (c) a new approach classifying only SE and DK respondents with >50% predicted probabilities of being sexual minorities as sexual minority. Materials and methods We used the sociodemographic information and follow-up questions for SE and DK respondents in the 2013-2014 National Health Interview Survey to generate predicted probabilities of identifying as a sexual minority adult. Results About 94% of the 144 SE respondents and 20% of the 310 DK respondents were predicted to identify as a sexual minority adult, with higher probabilities for younger, wealthier, non-Hispanic white, and urban-dwelling respondents. Using a more specific definition of sexual minority orientation improved the precision of health and health care disparity estimates. Conclusions Predicted probabilities of sexual minority orientation may be used in this and other surveys to improve representation and categorization of those who identify as a sexual minority adult.

The US health care system is experiencing a sharp increase in opioid-related adverse events and spending, and opioid overprescription may be a key factor in this crisis. Ambient opioid exposure within households is one of the known major dangers of overprescription.To quantify the association between the postsurgical initiation of prescription opioid use in opioid-naive patients and the subsequent prescription opioid misuse and chronic opioid use among opioid-naive family members.This cohort study was conducted using administrative data from the database of a US commercial insurance provider with more than 35 million covered individuals. Participants included pairs of patients who underwent surgery from January 1, 2008, to December 31, 2016, and their family members within the same household. Data were analyzed from January 1 to November 30, 2018.Duration of opioid exposure and refills of opioid prescriptions received by patients after surgery.Risk of opioid misuse and chronic opioid use in family members were calculated using inverse probability weighted Cox proportional hazards regression models.The final cohort included 843 531 pairs of patients and family members. Most pairs included female patients (445 456 [52.8%]) and male family members (442 992 [52.5%]), and a plurality of pairs included patients in the 45 to 54 years age group (249 369 [29.6%]) and family members in the 15 to 24 years age group (313 707 [37.2%]). A total of 3894 opioid misuse events (0.5%) and 7485 chronic opioid use events (0.9%) occurred in family members. In adjusted models, each additional opioid prescription refill for the patient was associated with a 19.2% (95% CI, 14.5%-24.0%) increase in hazard of opioid misuse in family members. The risk of opioid misuse appeared to increase only in households in which the patient obtained refills. Family members in households with any refill had a 32.9% (95% CI, 22.7%-43.8%) increased adjusted hazard of opioid misuse. When patients became chronic opioid users, the hazard ratio for opioid misuse among family members was 2.52 (95% CI, 1.68-3.80), and similar patterns were found for chronic opioid use.This cohort study found that opioid exposure was a household risk. Family members of a patient who received opioid prescription refills after surgery had an increased risk of opioid misuse and chronic opioid use.

Objective: Examine care integration—efforts to unify disparate parts of health care organizations to generate synergy across activities occurring within and between them—to understand whether and at which organizational level health systems impact care quality and staff experience. Data Sources: Surveys administered to one practice manager (56/59) and up to 26 staff (828/1360) in 59 practice sites within 24 physician organizations within 17 health systems in four states (2017-2019). Study Design: We developed manager and staff surveys to collect data on organizational, social, and clinical process integration, at four organizational levels: practice site, physician organization, health system, and outside health systems. We analyzed data using descriptive statistics and regression. Principal Findings: Managers and staff perceived opportunity for improvement across most types of care integration and organizational levels. Managers/staff perceived little variation in care integration across health systems. They perceived better care integration within practice sites than within physician organizations, health systems, and outside health systems—up to 38 percentage points (pp) lower (P

We developed and pilot-tested an eight-session community-based cognitive behavior therapy group intervention to improve coping with intersectional stigma, address medical mistrust, and improve antiretroviral treatment adherence. Seventy-six HIV-positive Latinx sexual minority men (SMM; 38 intervention, 38 wait-list control) completed surveys at baseline, and 4- and 7-months post-baseline. Adherence was electronically monitored. Intention-to-treat, repeated-measures regressions showed improved adherence in the intervention vs. control group from baseline to follow-up [electronically monitored: b (95% CI) 9.24 (- 0.55, 19.03), p = 0.06; self-reported: b (95% CI) 4.50 (0.70, 8.30), p = .02]. Intervention participants showed marginally decreased negative religious coping beliefs in response to stigma [b (95% CI) = - 0.18 (- 0.37, 0.01), p = .06], and significantly lower medical mistrust [b (95% CI) = - 0.47 (- 0.84, - 0.09), p = .02]. Our intervention holds promise for improving HIV outcomes by empowering Latinx SMM to leverage innate resilience resources when faced with stigma.ClinicalTrials.gov ID (TRN): NCT03432819, 01/31/2018.Hemos desarrollado un estudio piloto para poner a prueba un programa de ocho-sesiones de terapia cognitivo-conductual basado en un grupo de comunidad para abordar el estigma interseccional, la desconfianza médica y mejorar la adherencia al tratamiento antirretroviral. Setenta y seis hombres Latinos de minorías sexuales VIH positivos (38 en el grupo de intervención, 38 en el grupo de control de lista de espera) completaron encuestas al inicio, y cuatro y siete meses después de la línea de base. La adherencia fue medida electrónicamente. Los resultados del análisis mostraron una mejor adherencia en el grupo de intervención en comparación al grupo de control desde el inicio hasta el seguimiento [monitoreado electrónicamente: b (95% IC) 9.24 (− 0.55, 19.03), p = .06; y autoreporte: b (95% IC) 4.50 (0.70, 8.30), p = .02]. Los participantes del grupo de intervención mostraron una disminución marginal en las creencias negativas de afrontamiento religioso al estigma [b (95% IC) − 0.18 (− 0.37, 0.01), p = .06], y significativamente menor desconfianza médica [b (95% IC) − 0.47 (− 0.84, − 0.09), p = .02]. Nuestra intervención es prometedora para mejorar los resultados del VIH al empoderar a hombres Latinos de minorías sexuales para tomar ventaja de los recursos de resiliencia innatos cuando se enfrentan al estigma.

Objectives To develop an easy-to-interpret, patient-reported Functional Limitations Index (FLI) that can be used to assess and monitor the full spectrum of functioning in a community-dwelling population. Study design Observational design using nationally representative survey data. Methods We used self-rated health as a criterion for empirically assigning weights to 5 National Health Interview Survey items assessing difficulty with seeing, hearing, walking, cognition, and self-care. In addition to succinctly summarizing cumulative limitations, we addressed 2 main questions: (1) Which limitations have stronger associations with self-rated health? and (2) How does severity (from 0, no difficulty, to 3, unable to do) relate to self-rated health? We generated a respondent-level summary score based on a model predicting self-rated health from the 5 linearly scored (0-3) items and used splines to account for nonlinear severity-self-rated health associations. Results The strongest association of specific functional limitations with self-rated health involved mobility; the weakest associations involved sensory limitations. The association of severity with self-rated health was nonlinear and largest moving from no difficulty to somewhat difficult. Nationally, 5% of noninstitutionalized adults were considered most limited, 8% somewhat limited, and 87% least limited. Great mobility limitations (defined as a lot of difficulty or unable to do) most distinguished limitation groups (present in 0% of least limited, 25% of somewhat limited, and 70% of most limited). Conclusions The FLI is an easy-to-administer, easy-to-interpret, and valid summary measure of disability that health plans and health care organizations can use for quality-of-care monitoring across a variety of settings to improve care for patients with disabilities.

Objective To describe differences in patient experiences of hospital care by preferred language within racial/ethnic groups. Data source 2014-2015 HCAHPS survey data. Study design We compared six composite measures for seven languages (English, Spanish, Russian, Portuguese, Chinese, Vietnamese, and Other) within applicable subsets of five racial/ethnic groups (Hispanics, Asian/Pacific Islanders, American Indian/Alaska Natives, Blacks, and Whites). We measured patient-mix adjusted overall, between- and within-hospital differences in patient experience by language, using linear regression. Data collection methods Surveys from 5 480 308 patients discharged from 4517 hospitals 2014-2015. Principal findings Within each racial/ethnic group, mean reported experiences for non-English-preferring patients were almost always worse than their English-preferring counterparts. Language differences were largest and most consistent for Care Coordination. Within-hospital differences by language were often larger than between-hospital differences and were largest for Care Coordination. Where between-hospital differences existed, non-English-preferring patients usually attended hospitals whose average patient experience scores for all patients were lower than the average scores for the hospitals of their English-preferring counterparts. Conclusions Efforts should be made to increase access to better hospitals for language minorities and improve care coordination and other facets of patient experience in hospitals with high proportions of non-English-preferring patients, focusing on cultural competence and language-appropriate services.

OBJECTIVES To investigate whether health care experiences of adult Medicaid beneficiaries differ by race/ethnicity and rural/urban status. DATA SOURCES A total of 270 243 respondents to the 2014-2015 Nationwide Adult Medicaid Consumer Assessment of Healthcare Providers and Systems Survey. STUDY DESIGN Linear regression was used to estimate case mix adjusted differences in patient experience between racial/ethnic minority and non-Hispanic white Medicaid beneficiaries, and between beneficiaries residing in small urban areas, small towns, and rural areas vs large urban areas. Dependent measures included getting needed care, getting care quickly, doctor communication, and customer service. PRINCIPAL FINDINGS Compared with white beneficiaries, American Indian/Alaska Native (AIAN) and Asian/Pacific Islander (API) beneficiaries reported worse experiences, while black beneficiaries reported better experiences. Deficits for AIAN beneficiaries were 6-8 points on a 0-100 scale; deficits for API beneficiaries were 13-22 points (P's

Objectives. To describe the types of social services provided at community health centers (CHCs), characteristics of CHCs providing these services, and the association between on-site provision and health care quality.Methods. We surveyed CHCs in 12 US states and the District of Columbia during summer 2017 (n = 208) to identify referral to and provision of services to address 8 social needs. Regression models estimated factors associated with the provision of social services by CHCs and the association between providing services and health care quality (an 8-item composite).Results. CHCs most often offered on-site assistance for needs related to food or nutrition (43%), interpersonal violence (32%), and housing (30%). Participation in projects with community-based organizations was associated with providing services on-site (odds ratio = 2.48; P = .018). On-site provision was associated with better performance on measures of health care quality (e.g., each additional social service was associated with a 4.3 percentage point increase in colorectal cancer screenings).Conclusions. Some CHCs provide social services on-site, and this was associated with better performance on measures of health care quality.Public Health Implications. Health care providers are increasingly seeking to identify and address patients’ unmet social needs, and on-site provision of services is 1 strategy to consider.

IMPORTANCE: Following reductions in US ambulatory care early in the pandemic, it remains unclear whether care consistently returned to expected rates across insurance types and services. OBJECTIVE: To assess whether patients with Medicaid or Medicare-Medicaid dual eligibility had significantly lower than expected return to use of ambulatory care rates than patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance. DESIGN, SETTING, AND PARTICIPANTS: In this retrospective cohort study examining ambulatory care service patterns from January 1, 2019, through February 28, 2021, claims data from multiple US payers were combined using the Milliman MedInsight research database. Using a difference-in-differences design, the extent to which utilization during the pandemic differed from expected rates had the pandemic not occurred was estimated. Changes in utilization rates between January and February 2020 and each subsequent 2-month time frame during the pandemic were compared with the changes in the corresponding months from the year prior. Age- and sex-adjusted Poisson regression models of monthly utilization counts were used, offsetting for total patient-months and stratifying by service and insurance type. EXPOSURES: Patients with Medicaid or Medicare-Medicaid dual eligibility compared with patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance, respectively. MAIN OUTCOMES AND MEASURES: Utilization rates per 100 people for 6 services: emergency department, office and urgent care, behavioral health, screening colonoscopies, screening mammograms, and contraception counseling or HIV screening. RESULTS: More than 14.5 million US adults were included (mean age, 52.7 years; 54.9% women). In the March-April 2020 time frame, the combined use of 6 ambulatory services declined to 67.0% (95% CI, 66.9%-67.1%) of expected rates, but returned to 96.7% (95% CI, 96.6%-96.8%) of expected rates by the November-December 2020 time frame. During the second COVID-19 wave in the January-February 2021 time frame, overall utilization again declined to 86.2% (95% CI, 86.1%-86.3%) of expected rates, with colonoscopy remaining at 65.0% (95% CI, 64.1%-65.9%) and mammography at 79.2% (95% CI, 78.5%-79.8%) of expected rates. By the January-February 2021 time frame, overall utilization returned to expected rates as follows: patients with Medicaid at 78.4% (95% CI, 78.2%-78.7%), Medicare-Medicaid dual eligibility at 73.3% (95% CI, 72.8%-73.8%), commercial at 90.7% (95% CI, 90.5%-90.9%), Medicare Advantage at 83.2% (95% CI, 81.7%-82.2%), and Medicare fee-for-service at 82.0% (95% CI, 81.7%-82.2%; P

Background Over 1.6 million adolescents in the United States meet criteria for substance use disorders (SUDs). While there are promising treatments for SUDs, adolescents respond to these treatments differentially in part based on the setting in which treatments are delivered. One way to address such individualized response to treatment is through the development of adaptive interventions (AIs): sequences of decision rules for altering treatment based on an individual’s needs. This protocol describes a project with the overarching goal of beginning the development of AIs that provide recommendations for altering the setting of an adolescent’s substance use treatment. This project has three discrete aims: (1) explore the views of various stakeholders (parents, providers, policymakers, and researchers) on deciding the setting of substance use treatment for an adolescent based on individualized need, (2) generate hypotheses concerning candidate AIs, and (3) compare the relative effectiveness among candidate AIs and non-adaptive interventions commonly used in everyday practice. Methods This project uses a mixed-methods approach. First, we will conduct an iterative stakeholder engagement process, using RAND’s ExpertLens online system, to assess the importance of considering specific individual needs and clinical outcomes when deciding the setting for an adolescent’s substance use treatment. Second, we will use results from the stakeholder engagement process to analyze an observational longitudinal data set of 15,656 adolescents in substance use treatment, supported by the Substance Abuse and Mental Health Services Administration, using the Global Appraisal of Individual Needs questionnaire. We will utilize methods based on Q-learning regression to generate hypotheses about candidate AIs. Third, we will use robust statistical methods that aim to appropriately handle casemix adjustment on a large number of covariates (marginal structural modeling and inverse probability of treatment weights) to compare the relative effectiveness among candidate AIs and non-adaptive decision rules that are commonly used in everyday practice. Discussion This project begins filling a major gap in clinical and research efforts for adolescents in substance use treatment. Findings could be used to inform the further development and revision of influential multi-dimensional assessment and treatment planning tools, or lay the foundation for subsequent experiments to further develop or test AIs for treatment planning. Electronic supplementary material The online version of this article (10.1186/s13722-017-0099-4) contains supplementary material, which is available to authorized users.

Sub-Saharan Africans infected with HIV-1C make up the largest AIDS patient population in the world and exhibit large heterogeneity in disease progression before initiating antiretroviral therapy. To identify host variants associated with HIV disease progression, we performed genome-wide association studies on a total of 556 treatment-naive HIV-infected individuals in Botswana. We characterized the pattern of HIV disease progression using a novel functional principal component analysis, which can better capture longitudinal CD4 and viral load (VL) trajectories. Two single-nucleotide polymorphisms (SNPs) near HCG22 (chr6, peak variant rs2535307, combined p = 3.72 × 10−7, minor allele as risky allele) and CCNG1 (chr5, peak variant kgp22385164, combined p = 1.88 × 10−6, minor allele as risky allele) were significantly associated with CD4 and VL dynamics. Inspection of SNPs in these gene regions in a third Botswana cohort (using GWATCH) also revealed a strong association of HCG22 with HIV-1C acquisition, suggesting that this region is associated with infection as well as disease progression. Our study uncovered two genetic regions that are significant and have specific effects on HIV-1C acquisition or progression in sub-Saharan Africans, and the result suggested new potential targets for AIDS prevention and treatment. In addition, our results also indicate the possibility of using genetic markers as HIV disease progression indicators in sub-Saharan Africans to prioritize fast progressors for antiretroviral treatment.

The growth in healthcare spending is an important topic in the United States, and preterm and low-birthweight infants have some of the highest healthcare expenditures of any patient population. We performed a retrospective cohort study of spending in this population using a large, national claims database of commercially insured individuals. A total of 763,566 infants with insurance coverage through Aetna, Inc. for the first 6 months of post-natal life were included, and received approximately $8.4 billion (2016 USD) in healthcare services. Infants with billing codes indicating preterm status (n = 50,511) incurred medical expenditures of $76,153 on average, while low-birthweight status (n = 418) had the highest per infant average expenditures of $603,778. Understanding the drivers of variation in costs within gestational age and birthweight bands is an important target for future studies.

Background Adolescents respond differentially to substance use treatment based on their individual needs and goals. Providers may benefit from guidance (via decision rules) for personalizing aspects of treatment, such as level-of-care (LOC) placements, like choosing between outpatient or inpatient care. The field lacks an empirically-supported foundation to inform the development of an adaptive LOC-placement protocol. This work begins to build the evidence base for adaptive protocols by estimating them from a large observational dataset. Methods We estimated two-stage LOC-placement protocols adapted to individual adolescent characteristics collected from the Global Appraisal of Individual Needs assessment tool (n = 10,131 adolescents). We used a modified version of Q-learning, a regression-based method for estimating personalized treatment rules over time, to estimate four protocols, each targeting a potentially distinct treatment goal: one primary outcome (a composite of ten positive treatment outcomes) and three secondary (substance frequency, substance problems, and emotional problems). We compared the adaptive protocols to non-adaptive protocols using an independent dataset. Results Intensive outpatient was recommended for all adolescents at intake for the primary outcome, while low-risk adolescents were recommended for no further treatment at followup while higher-risk patients were recommended to inpatient. Our adaptive protocols outperformed static protocols by an average of 0.4 standard deviations (95 % confidence interval 0.2−0.6) of the primary outcome. Conclusions Adaptive protocols provide a simple one-to-one guide between adolescents’ needs and recommended treatment which can be used as decision support for clinicians making LOC-placement decisions.

To date, few programs that integrate traditional practices with evidence-based practices have been developed, implemented, and evaluated with urban American Indians/Alaska Natives (AI/ANs) using a strong research design. The current study recruited urban AI/AN teens across northern, central, and southern California during 2014-2017 to participate in a randomized controlled trial testing two cultural interventions that addressed alcohol and other drug (AOD) use. Adolescents were 14-18years old (inclusive), and either verbally self-identified as AI/AN or were identified as AI/AN by a parent or community member. We tested the added benefit of MICUNAY (Motivational Interviewing and Culture for Urban Native American Youth) to a CWG (Community Wellness Gathering). MICUNAY was a group intervention with three workshops that integrated traditional practices with motivational interviewing. CWGs were cultural events held monthly in each city. AI/AN urban adolescents (N=185) completed a baseline survey, were randomized to MICUNAY + CWG or CWG only, and then completed a three- and six-month follow-up. We compared outcomes on AOD use, spirituality, and cultural identification. Overall, AOD use remained stable over the course of the study, and we did not find significant differences between these two groups over time. It may be that connecting urban AI/AN adolescents to culturally centered activities and resources is protective, which has been shown in other work with this population. Given that little work has been conducted in this area, longer term studies of AOD interventions with urban AI/AN youth throughout the U.S. are suggested to test the potential benefits of culturally centered interventions.

Key Points Question Is the adoption of more advanced electronic health record (EHR) capabilities associated with better ambulatory clinical quality of care? Findings In cross-sectional analyses of 3 states from 2014 to 2017, ambulatory clinics (769-972 per year) with more advanced EHR capabilities had higher scores on a composite measure of ambulatory clinical quality than did other clinics, which translated into an approximately 9% difference in rank order of quality. Across the much smaller number of clinics that gained advanced EHR capabilities between 2014 and 2017 (n = 72), the composite of ambulatory clinical quality improved more than for other clinics, but the difference was not statistically significant. Meaning This study suggests that ambulatory clinics with advanced EHR capabilities were associated with a better performance on a composite measure of ambulatory clinical quality than clinics with less-advanced EHR capabilities; clinics that adopted advanced EHR capabilities during a 3-year period were not associated with significant increases in ambulatory clinical quality performance., Importance Electronic health records (EHRs) are widely promoted to improve the quality of health care, but information about the association of multifunctional EHRs with broad measures of quality in ambulatory settings is scarce. Objective To assess the association between EHRs with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care. Design, Setting, and Participants This cross-sectional and longitudinal study was conducted using survey responses from 1141 ambulatory clinics in Minnesota, Washington, and Wisconsin affiliated with a health system that responded to the Healthcare Information and Management Systems Society Annual Survey and reported performance measures in 2014 to 2017. Statistical analysis was performed from July 10, 2019, through February 26, 2021. Main Outcomes and Measures A composite measure of EHR capability that considered 50 EHR capabilities in 7 functional domains, grouped into the following ordered categories: no functional EHR, EHR underuser, EHR, neither underuser or superuser, EHR superuser; as well as a standardized composite of ambulatory clinical performance measures that included 3 to 25 individual measures (median, 13 individual measures). Results In 2014, 381 of 746 clinics (51%) were EHR superusers; this proportion increased in each subsequent year (457 of 846 clinics [54%] in 2015, 510 of 881 clinics [58%] in 2016, and 566 of 932 clinics [61%] in 2017). In each cross-sectional analysis year, EHR superusers had better clinical quality performance than other clinics (adjusted difference in score: 0.39 [95% CI, 0.12-0.65] in 2014; 0.29 [95% CI, −0.01 to 0.59] in 2015; 0.26 [95% CI, –0.05 to 0.56] in 2016; and 0.20 [95% CI, –0.04 to 0.45] in 2017). This difference in scores translates into an approximately 9% difference in a clinic’s rank order in clinical quality. In longitudinal analyses, clinics that progressed to EHR superuser status had only slightly better gains in clinical quality between 2014 and 2017 compared with the gains in clinical quality of clinics that were static in terms of their EHR status (0.10 [95% CI, −0.13 to 0.32]). In an exploratory analysis, different types of EHR capability progressions had different degrees of associated improvements in ambulatory clinical quality (eg, progression from no functional EHR to a status short of superuser, 0.06 [95% CI, −0.40 to 0.52]; progression from EHR underuser to EHR superuser, 0.18 [95% CI, −0.14 to 0.50]). Conclusions and Relevance Between 2014 and 2017, ambulatory clinics in Minnesota, Washington, and Wisconsin with EHRs having greater capabilities had better composite measures of clinical quality than other clinics, but clinics that gained EHR capabilities during this time had smaller increases in clinical quality that were not statistically significant., This cross-sectional study assesses the association between electronic health records with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care.

This cross-sectional study examines changes in low-value care use and spending from 2014 to 2018 among the fee-for-service Medicare population., Key Points Question Have low-value care use and spending decreased over time with increasing focus on reducing waste in the US health care system? Findings In this cross-sectional study of more than 21 million individuals with fee-for-service Medicare, the percentage receiving any of 32 measured low-value services decreased marginally from 2014 to 2018. Claim line–level spending on low-value care per 1000 individuals did not decrease substantially over this period. Meaning This study found that among individuals with fee-for-service Medicare receiving any of 32 measured services, low-value care use and spending decreased marginally from 2014 to 2018, despite a national education campaign to address low-value care and increased attention on reducing health care waste., Importance Low-value care, defined as care offering no net benefit in specific clinical scenarios, is associated with harmful outcomes in patients and wasteful spending. Despite a national education campaign and increasing attention on reducing health care waste, recent trends in low-value care delivery remain unknown. Objective To assess national trends in low-value care use and spending. Design, Setting, and Participants In this cross-sectional study, analyses of low-value care use and spending from 2014 to 2018 were conducted using 100% Medicare fee-for-service enrollment and claims data. Included individuals were aged 65 years or older and continuously enrolled in Medicare parts A, B, and D during each measurement year and the previous year. Data were analyzed from September 2019 through December 2020. Exposure Being enrolled in fee-for-service Medicare for a period of time, in years. Main Outcomes and Measures The Milliman MedInsight Health Waste Calculator was used to assess 32 claims-based measures of low-value care associated with Choosing Wisely recommendations and other professional guidelines. The calculator designates services as wasteful, likely wasteful, or not wasteful based on an absence of indication of appropriate use in the claims history; calculator-designated wasteful services were defined as low-value care. Spending was calculated as claim-line level (ie, spending on the low-value service) and claim level (ie, spending on the low-value service plus associated services), adjusting for inflation. Results Among 21 045 759 individuals with fee-for-service Medicare (mean [SD] age, 77.4 [7.9] years; 12 515 915 [59.5%] women), the percentage receiving any of 32 low-value services decreased from 36.3% (95% CI, 36.3%-36.4%) to 33.6% (95% CI, 33.6%-33.6%) from 2014 to 2018. Uses of low-value services per 1000 individuals decreased from 677.8 (95% CI, 676.2-679.5) to 632.7 (95% CI, 632.6-632.8) from 2014 to 2018. Three services comprised approximately two-thirds of uses among 32 low-value services per 1000 individuals: preoperative laboratory testing decreased from 213.8 (95% CI, 213.4-214.2) to 166.2 (95% CI, 166.2-166.2), while opioids for back pain increased from 154.4 (95% CI, 153.6-155.2) to 182.1 (95% CI, 182.1-182.1) and antibiotics for upper respiratory infections increased from 75.0 (95% CI, 75.0-75.1) to 82 (95% CI, 82.0-82.0). Spending per 1000 individuals on low-value care also decreased, from $52 765.5 (95% CI, $51 952.3-$53 578.6) to $46 921.7 (95% CI, $46 593.7-$47 249.7) at the claim-line level and from $160 070.4 (95% CI, $158 999.8-$161 141.0) to $144 741.1 (95% CI, $144 287.5-$145 194.7) at the claim level. Conclusions and Relevance This cross-sectional study found that among individuals with fee-for-service Medicare receiving any of 32 measured services, low-value care use and spending decreased marginally from 2014 to 2018, despite a national education campaign in collaboration with clinician specialty societies and increased attention on low-value care. While most use of low-value care came from 3 services, 1 of these was opioid prescriptions, which increased over time despite the harms associated with their use. These findings may represent several opportunities to prevent patient harm and lower spending.

The extent to which disparities affect all sexual minority women (SMW) versus specific subgroups of lesbian, bisexual, or other women remains unclear, in part due to inconsistent analysis of available data. We propose an integrated approach that aggregates subgroups to maximize power to detect broadly applicable disparities, then tests for subgroup heterogeneity, exercising caution with disaggregation when there is no direct evidence of heterogeneity.Multivariate analyses of 2014-2015 National Health Interview Survey data examined six barriers to care. We compared heterosexual women (n = 36,474) with SMW (n = 1048) overall and tested for heterogeneous outcomes among subgroups of SMW compared with heterosexual women and with each other.Controlling for sociodemographics and health status, aggregated analyses showed that SMW were more likely than heterosexual peers to have trouble finding a provider (adjusted percentages 5.1% vs. 3.2%, p 0.01) and no optimal usual place of care (14.5% vs. 11.2%, p 0.01). There was no evidence of subgroup heterogeneity for either barrier, suggesting uniform disparities for SMW. In contrast, only lesbian/gay women were more likely than heterosexual women to be told their health insurance was not accepted (p = 0.03); this was the only outcome for which the adjusted difference between bisexual and lesbian/gay women was significant (2.8% vs. 6.3%, p = 0.02).Analyses that only disaggregated data would have understated overall sexual minority disparities and perhaps overstated subgroup differences; an integrated approach can more accurately characterize disparities experienced by all SMW versus those specific to certain subgroups. Large national surveys should include sexual orientation questions to support adequately powered comparisons.

OBJECTIVES: There are limited public health data on urban American Indian/Alaska Native (AI/AN) populations, particularly adolescents. The current study attempted to address gaps by providing descriptive information on experiences of urban AI/AN adolescents across northern, central, and southern California. DESIGN: We describe demographics and several behavioral health and cultural domains, including: alcohol and other drug (AOD) use, risky sexual behavior, mental and physical health, discrimination experiences, involvement in traditional practices, and cultural pride and belonging. We recruited 185 urban AI/AN adolescents across northern, central, and southern California from 2014 to 2017 who completed a baseline survey as part of a randomized controlled intervention trial. RESULTS: Average age was 15.6 years; 51% female; 59% of adolescents that indicated AI/AN descent also endorsed another race or ethnicity. Rates of AOD use in this urban AI/AN sample were similar to rates for Monitoring the Future. About one-third of adolescents reported ever having sexual intercourse, with 15% reporting using alcohol or drugs before sex. Most reported good mental and physical health. Most urban AI/AN adolescents participated in traditional practices, such as attending Pow Wows and learning their tribal history. Adolescents also reported discrimination experiences, including being a victim of racial slurs and discrimination by law enforcement. CONCLUSIONS: This study describes a select sample of California urban AI/AN adolescents across several behavioral health and cultural domains. Although these adolescents reported numerous discrimination experiences and other stressors, findings suggest that this sample of urban AI/AN teens may be particularly resilient with regard to behavioral health.

ObjectiveWe investigated the presence of non-neuromuscular phenotypes in patients affected by Spinal Muscular Atrophy (SMA), a disorder caused by a mutation in the Survival of Motor Neuron (SMN) gene, and whether these phenotypes may be clinically detectable prior to clinical signs of neuromuscular degeneration and therefore independent of muscle weakness.MethodsWe utilized a de-identified database of insurance claims to explore the health of 1,038 SMA patients compared to controls. Two analyses were performed: (1) claims from the entire insurance coverage window; and (2) for SMA patients, claims prior to diagnosis of any neuromuscular disease or evidence of major neuromuscular degeneration to increase the chance that phenotypes could be attributed directly to reduced SMN levels. Logistic regression was used to determine whether phenotypes were diagnosed at significantly different rates between SMA patients and controls and to obtain covariate-adjusted odds ratios.ResultsResults from the entire coverage window revealed a broad spectrum of phenotypes that are differentially diagnosed in SMA subjects compared to controls. Moreover, data from SMA patients prior to their first clinical signs of neuromuscular degeneration revealed numerous non-neuromuscular phenotypes including defects within the cardiovascular, gastrointestinal, metabolic, reproductive, and skeletal systems. Furthermore, our data provide evidence of a potential ordering of disease progression beginning with these non-neuromuscular phenotypes.ConclusionsOur data point to a direct relationship between early, detectable non-neuromuscular symptoms and SMN deficiency. Our findings are particularly important for evaluating the efficacy of SMN-increasing therapies for SMA, comparing the effectiveness of local versus systemically delivered therapeutics, and determining the optimal therapeutic treatment window prior to irreversible neuromuscular damage.

Urban American Indian/Alaska Native (AI/AN) adolescents are an understudied population in the USA who are at risk for a variety of health problems. Perceived discrimination (PD), including both overt PD and racial microaggressions (RMA), is known to adversely affect health. However, studies analyzing associations between overt PD and RMA and various health behaviors are limited. This study measured past-year alcohol use, heavy drinking, marijuana use, commercialized tobacco use, consequences experienced from alcohol and marijuana use in the past 3 months, mental and physical health status, AI/AN traditional activity participation, and overt PD and RMA among 182 urban AI/AN adolescents in California. To assess the association between overt PD and RMAs and health outcomes, we conducted either logistic regression (for dichotomous outcomes: past-year alcohol use, past-year heavy drinking, past-year marijuana use, consequences of alcohol and marijuana use, commercialized tobacco use) or linear regression (for continuous outcomes: mental and physical health, AI/AN traditional practices). In contrast to our hypotheses, overt PD and RMA were not significantly associated with substance use or mental or physical health among this sample of urban AI/AN adolescents. After adjusting for age and gender, overt PD and RMA were only correlated with past-year cigarette use and alcohol-related consequences experienced in the past 3 months. Potential factors that may play a role in decreasing effects of overt PD and RMA among urban AI/AN adolescents are discussed, including participation in AI/AN traditional practices and community engagement.

Objective To evaluate on a large scale, across 272 common types of laboratory tests, the impact of healthcare processes on the predictive value of electronic health record (EHR) data. Design Retrospective observational study. Setting Two large hospitals in Boston, Massachusetts, with inpatient, emergency, and ambulatory care. Participants All 669 452 patients treated at the two hospitals over one year between 2005 and 2006. Main outcome measures The relative predictive accuracy of each laboratory test for three year survival, using the time of the day, day of the week, and ordering frequency of the test, compared to the value of the test result. Results The presence of a laboratory test order, regardless of any other information about the test result, has a significant association (P

Since 1990 the World Health Organization has recommended HIV surveillance among pregnant women as an essential surveillance activity for countries with generalized HIV epidemics. Despite the widespread availability and potential usefulness of antenatal HIV surveillance analyses of such data present important challenges. Within an individual clinic the HIV status of its attendees may be correlated because of similarities in HIV risk among women close in age. Between-clinic correlation may also arise as women often seek antenatal care at clinics located close to their home and individuals living in nearby communities may share important characteristics or behaviours related to susceptibility. A general estimating equation-based approach for spatially-correlated binary data such as that antenatal HIV surveillance based on a pairwise composite likelihood has been described. We present an extended version of this model that can accommodate penalized spline estimators and apply it to antenatal HIV surveillance data collected in 2011 in Botswana to estimate the effects of proximity to the hotspot of the countrys HIV epidemic and age on HIV prevalence. Finally we compare the results with a logistic regression analysis which ignores potential correlation of responses. Copyright (c) 2015 John Wiley & Sons Ltd.

Objective To quantify the effects of varying opioid prescribing patterns after surgery on dependence, overdose, or abuse in an opioid naive population. Design Retrospective cohort study. Setting Surgical claims from a linked medical and pharmacy administrative database of 37 651 619 commercially insured patients between 2008 and 2016. Participants 1 015 116 opioid naive patients undergoing surgery. Main outcome measures Use of oral opioids after discharge as defined by refills and total dosage and duration of use. The primary outcome was a composite of misuse identified by a diagnostic code for opioid dependence, abuse, or overdose. Results 568 612 (56.0%) patients received postoperative opioids, and a code for abuse was identified for 5906 patients (0.6%, 183 per 100 000 person years). Total duration of opioid use was the strongest predictor of misuse, with each refill and additional week of opioid use associated with an adjusted increase in the rate of misuse of 44.0% (95% confidence interval 40.8% to 47.2%, P

Importance Autism spectrum disorder (ASD) is known to be more prevalent among males than females in the general population. Although overall risk of recurrence of ASD among siblings has been estimated to be between 6.1% and 24.7%, information on sex-specific recurrence patterns is lacking. Objective To estimate high-confidence sex-specific recurrence rates of ASD among siblings. Design, Setting, and Participants This observational study used an administrative database to measure the incidence of ASD among children in 1 583 271 families (37 507 with at least 1 diagnosis of ASD) enrolled in commercial health care insurance plans at a large US managed health care company from January 1, 2008, through February 29, 2016. Families in the study had 2 children who were observed for at least 12 months between 4 and 18 years of age. Main Outcomes and Measures The primary measure of ASD recurrence was defined as the diagnosis of ASD in a younger sibling of an older sibling with an ASD diagnosis. Results Among the 3 166 542 children (1 547 266 females and 1 619 174 males; mean [SD] age, 11.2 [4.7] years) in the study, the prevalence of ASD was 1.96% (95% CI, 1.94%-1.98%) among males and 0.50% (95% CI, 0.49%-0.51%) among females. When a male was associated with risk in the family, ASD was diagnosed in 4.2% (95% CI, 3.8%-4.7%) of female siblings and 12.9% (95% CI, 12.2%-13.6%) of male siblings. When a female was associated with risk in the family, ASD was diagnosed in 7.6% (95% CI, 6.5%-8.9%) of female siblings and 16.7% (95% CI, 15.2%-18.4%) of male siblings. Conclusions and Relevance These findings are in agreement with the higher rates of ASD observed among males than among females in the general population. Our study provides more specific guidance for the screening and counseling of families and may help inform future investigations into the environmental and genetic factors that confer risk of ASD.

Background. Microbial translocation has been implicated in the pathogenesis of liver fibrosis and cirrhosis. We sought to determine whether markers of microbial translocation are associated with liver disease progression during coinfection with human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Methods. We measured serial plasma lipopolysaccharide (LPS), endotoxin core antibody, intestinal fatty acid– binding protein (I-FABP), soluble CD14 (sCD14), interleukin 6 (IL-6), interleukin 10, and tumor necrosis factor α (TNF-α) levels over a 5-year period in 44 HIV/HCV-coinfected women, 21 of whom experienced liver disease progression and 23 were nonprogressors. Results. While LPS levels did not differ significantly over time between progressors and nonprogressors (P= .60), progressors had significantly higher plasma levels of sCD14, a marker of monocyte activation by LPS, at the first time point measured (P= .03) and throughout the study period (P= .001); progressors also had higher IL-6 and I-FABP levels over the 5-year study period (P= .02 and .03, respectively). The associations between progression and sCD14, I-FABP, and IL-6 levels were unchanged in models controlling for HIV RNA and CD4 + T-cell count. Conclusions. Although LPS levels did not differ between liver disease progressors and nonprogressors, the association of sCD14, I-FABP, and IL-6 levels with liver disease progression suggests that impairment of gut epithelial integrityand consequent microbial translocation may play a role in the complex interaction of HIV and HCV pathogenesis.

As gene expression measurement technology is shifting from microarrays to sequencing, the statistical tools available for their analysis must be adapted since RNA-seq data are measured as counts. Recently, it has been proposed to tackle the count nature of these data by modeling log-count reads per million as continuous variables, using nonparametric regression to account for their inherent heteroscedasticity. Adopting such a framework, we propose tcgsaseq, a principled, model-free and efficient top-down method for detecting longitudinal changes in RNA-seq gene sets. Considering gene sets defined a priori, tcgsaseq identifies those whose expression vary over time, based on an original variance component score test accounting for both covariates and heteroscedasticity without assuming any specific parametric distribution for the transformed counts. We demonstrate that despite the presence of a nonparametric component, our test statistic has a simple form and limiting distribution, and both may be computed quickly. A permutation version of the test is additionally proposed for very small sample sizes. Applied to both simulated data and two real datasets, the proposed method is shown to exhibit very good statistical properties, with an increase in stability and power when compared to state of the art methods ROAST, edgeR and DESeq2, which can fail to control the type I error under certain realistic settings. We have made the method available for the community in the R package tcgsaseq., 23 pages, 6 figures, typo corrections & acceptance acknowledgement

Valid estimation of treatment effects from observational data requires proper control of confounding. If the number of covariates is large relative to the number of observations, then controlling for all available covariates is infeasible. In cases where a sparsity condition holds, variable selection or penalization can reduce the dimension of the covariate space in a manner that allows for valid estimation of treatment effects. In this article, we propose matching on both the estimated propensity score and the estimated prognostic scores when the number of covariates is large relative to the number of observations. We derive asymptotic results for the matching estimator and show that it is doubly robust, in the sense that only one of the two score models need be correct to obtain a consistent estimator. We show via simulation its effectiveness in controlling for confounding and highlight its potential to address nonlinear confounding. Finally, we apply the proposed procedure to analyze the effect of gender on prescription opioid use using insurance claims data.

To estimate the association between vitamin D deficiency and bacterial vaginosis (BV) among nonpregnant HIV-infected and uninfected women.In a substudy of the Women's Interagency HIV Study, including women from Chicago and New York, the association between BV and vitamin D deficiency, demographics, and disease characteristics was tested using generalized estimating equations. Deficiency was defined as20 ng/mL 25 (OH) vitamin D and insufficiency as20 and ≤30 ng/mL. BV was defined by the Amsel criteria.Among 602 observations of nonpregnant women (480 HIV infected and 122 uninfected), BV was found in 19%. Vitamin D deficiency was found in 59.4%, and insufficiency was found in 24.4%. In multivariable analysis, black race was the most significant predictor of BV (adjusted odds ratio [AOR] 5.90, (95% confidence interval [CI] 2.52-13.8). Vitamin D deficiency was independently associated with BV among HIV-infected women (AOR 3.12, 95% CI 1.16-8.38) but not among HIV-uninfected women. There was a negative linear correlation between vitamin D concentration and prevalence of BV in HIV-infected women (r=-0.15, p=0.001).Vitamin D deficiency was very common in this cohort and significantly associated with BV among HIV-infected women. These preliminary findings suggest that further epidemiologic and mechanistic exploration of the relationship between vitamin D and BV in HIV-infected women is warranted.

Objective. To explore the previously reported associations between cervical squamous lesions and psychologic measures of stress and depression. Methods. In a multicenter cohort study, women with HIV and HIV-seronegative women had Pap tests and completed self-report questionnaires including the Perceived Stress Scale-10 (PSS), which measures perceived stress, the Posttraumatic Stress Disorder (PTSD) Checklist-Civilian Version (PCL-C), which measures symptoms of PTSD, and the Center for Epidemiologic Studies Depression (CES-D) scale, which measures depressive symptoms. Results. Median scores were 13 (range = 0-38) for the PSS, 24 (range = 17-85) for the PCL-C, and 8 (range = 0-57) for the CES-D, indicating moderate stress and minimal depression. For PSS, compared with women in the lowest tertile of reported stress, the odds ratios (ORs) for squamous intraepithelial lesions (SIL) were 0.88 (95% confidence interval [CI] = 0.50-1.54) for women in the middle tertile and 0.96 (95% CI = 0.54-1.68) for women in the highest tertile. For PCL-C, compared with women in the lowest tertile of PTSD symptoms, ORs for SIL were 0.79 (95% CI = 0.43-1.41) for women in the middle tertile and 1.17 (95% CI = 0.68-2.01) for women in the highest tertile. Rates of SIL were similar for CES-D scores 16 or higher (compared with women with lower scores; OR = 1.41, 95% CI = 0.88-2.26) and 23 or higher (OR = 1.39, 95% CI = 0.81-2.40). In the multivariable analysis including the number of sexual partners, age, income, ethnicity, and serostatus, stress as measured by PSS and PCL-C and depressive symptoms as measured by CES-D remained unassociated with SIL. Conclusions. We found no evidence that stress and depression affect the prevalence of cervical squamous lesions.

CDAD led to significantly worse outcomes in these patients., Data are limited on the attributable outcomes of Clostridium difficile–associated disease (CDAD), particularly in CDAD-endemic settings. We conducted a retrospective cohort study of nonsurgical inpatients admitted for >48 hours in 2003 (N = 18,050). The adjusted hazard ratios for readmission (hazard ratio 2.19, 95% confidence interval [CI] 1.87–2.55) and deaths within 180 days (hazard ratio 1.23, 95% CI 1.03–1.46) were significantly different among CDAD case-patients and noncase patients. In a propensity score matched-pairs analysis that used a nested subset of the cohort (N = 706), attributable length of stay attributable to CDAD was 2.8 days, attributable readmission at 180 days was 19.3%, and attributable death at 180 days was 5.7%. CDAD patients were significantly more likely than controls to be discharged to a long-term-care facility or outside hospital. Even in a nonoutbreak setting, CDAD had a statistically significant negative impact on patient illness and death, and the impact of CDAD persisted beyond hospital discharge.

A considerable number of gram-negative bacteraemias occur outside intensive care units (ICUs). Inadequate antibiotic therapy in ICUs has been associated with adverse outcomes; however, there are no prospective studies in non-ICU patients.A 6 month (1 August 2006-31 January 2007), prospective cohort study of non-ICU patients with gram-negative bacteraemia in a tertiary-care hospital was performed. Inadequate empirical antibiotic therapy was defined as no antibiotic or starting a non-susceptible antibiotic within 24 h after the initial positive blood culture.Two hundred and fifty non-ICU patients had gram-negative bacteraemia. The mean age was 56.4 (+/-16.1) years. The predominant bacteria in monomicrobial infections were Escherichia coli (24%), Klebsiella pneumoniae (18%) and Pseudomonas aeruginosa (8%). Sixty-one (24%) patients had polymicrobial bacteraemia. Seventy patients (28%) required ICU transfer and 35 (14%) died. Seventy-nine (31.6%) received inadequate empirical antibiotic therapy. These patients were more likely to have a hospital-acquired infection [odds ratio (OR) = 1.99, 95% confidence interval (CI) = 1.11-3.56, P = 0.02] and less likely to have E. coli monomicrobial bacteraemia [OR 0.40 (95% CI 0.19-0.86), P = 0.02]. There were no differences in occurrence of sepsis [72 (91.1%) patients with inadequate versus 159 (93.0%) with adequate therapy; P = 0.6], ICU transfer [20 (25.3%) versus 50 (29.2%); P = 0.5], post-bacteraemia length of stay (median = 6.8 versus 6.1 days; P = 0.09) or death [11 (13.9%) versus 24 (14.0%); P = 1.0].Nearly one-third of the non-ICU patients with gram-negative bacteraemia received inadequate empirical antibiotic therapy. There was no difference in adverse outcomes between patients receiving inadequate or adequate therapy in this study.

Studying multiple outcomes simultaneously allows researchers to begin to identify underlying factors that affect all of a set of diseases (i.e., shared etiology) and what may give rise to differences in disorders between patients (i.e., disease subtypes). In this work, our goal is to build risk scores that are predictive of multiple phenotypes simultaneously and identify subpopulations at high risk of multiple phenotypes. Such analyses could yield insight into etiology or point to treatment and prevention strategies. The standard canonical correlation analysis (CCA) can be used to relate multiple continuous outcomes to multiple predictors. However, in order to capture the full complexity of a disorder, phenotypes may include a diverse range of data types, including binary, continuous, ordinal, and censored variables. When phenotypes are diverse in this way, standard CCA is not possible and no methods currently exist to model them jointly. In the presence of such complications, we propose a semi-parametric CCA method to develop risk scores that are predictive of multiple phenotypes. To guard against potential model mis-specification, we also propose a nonparametric calibration method to identify subgroups that are at high risk of multiple disorders. A resampling procedure is also developed to account for the variability in these estimates. Our method opens the door to synthesizing a wide array of data sources for the purposes of joint prediction.

Considerable interest has recently been focused on studying multiple phenotypes simultaneously in both epidemiological and genomic studies, either to capture the multidimensionality of complex disorders or to understand shared etiology of related disorders. We seek to identify {\em multiple regulators} or predictors that are associated with multiple outcomes when these outcomes may be measured on very different scales or composed of a mixture of continuous, binary, and not-fully-observed elements. We first propose an estimation technique to put all effects on similar scales, and we induce sparsity on the estimated effects. We provide standard asymptotic results for this estimator and show that resampling can be used to quantify uncertainty in finite samples. We finally provide a multiple testing procedure which can be geared specifically to the types of multiple regulators of interest, and we establish that, under standard regularity conditions, the familywise error rate will approach 0 as sample size diverges. Simulation results indicate that our approach can improve over unregularized methods both in reducing bias in estimation and improving power for testing., Comment: 25 pages, 6 figures

Background Mortality attributable to bloodstream infection (BSI) is still controversial. We studied the impact of BSI on mortality after coronary artery bypass surgery, including the specific impact of different etiologic organisms. Methods Our cohort consisted of 4515 patients who underwent coronary artery bypass procedures at a university hospital from 1996 through 2004. We used Society of Thoracic Surgery data supplemented with laboratory and infection control data. Mortality dates were identified using Society of Thoracic Surgery data and the Social Security Death Index. BSI within 90 days after surgery was defined by a positive blood culture result. Cox proportional hazards and propensity score models were used to analyze the association between BSI and mortality. Results Patients with BSI had a 4.2-fold increased risk of death (95% confidence interval [CI], 3.0-5.9) 2-90 days after coronary artery bypass surgery, compared with uninfected patients. The risk of death was higher among patients with BSI due to gram-negative bacteria (hazard ratio [HR], 6.8; 95% CI, 3.9-12.0) and BSI due to Staphylococcus aureus (HR, 7.2; 95% CI, 3.3-15.7) and lowest among patients with BSI caused by gram-positive bacteria other than S. aureus (HR, 2.2; 95% CI, 1.1-4.6). The risk of death was highest among patients who developed BSI but had the lowest likelihood of infection (HR, 10.0; 95% CI, 3.5-28.8) and was lowest among patients who developed BSI but had the highest likelihood of infection (HR, 2.3; 95% CI, 1.2-4.6). Conclusions BSIs due to gram-negative bacteria and BSIs due to S. aureus contributed significantly to mortality. Mortality attributable to BSI was highest among patients predicted to be least likely to develop infection and was lowest among severely ill patients who were most likely to develop infection. BSI appears to be an important contributor to death after coronary artery bypass surgery, particularly among the healthiest patients.

Objective To determine if women with undocumented HIV status in late pregnancy or at labor and delivery who are rapidly tested and identified as HIV infected have high-risk behaviors and psychosocial obstacles hindering postpartum follow-up. Methods Consenting participants (women with undocumented HIV status and ≥24 weeks gestational age (GA) and imminent delivery or ≥34 weeks GA) in 6 cities were rapidly tested and interviewed. HIV-positive women were offered follow-up. Results From 2001–2005, 54 HIV-infected women were identified: median age 26 years; 91% African American; 11 (20%) lost custody of their infants; 30 (56%) knew they or their partner were HIV-infected, but had no antenatal HIV care; 25 met criteria for starting antiretroviral therapy. Comparison between 48 HIV-infected and 130 HIV-negative women, tested and interviewed at the same hospitals, showed HIV-infected women more likely to be African American (P < .01) and report no prenatal care (P < .001), use street drugs (P < .01), have unstable residency (P < .05), not live with the father of their infant (P < .001), and have children in foster care (P < .01). Sixteen women (30%) and 17 (31%) infants did not remain in follow-up study due to relocation, child protective custody, and psychosocial issues including frequent substance use. Conclusion Over half of HIV-infected women knew they or their partner were infected with HIV, but did not initially disclose their status. Increased support services and substance abuse treatment are critical to facilitate better continuity of care for these socially marginalized women.

Background Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. Methods and Results We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p, National Institutes of Health (U.S.). Informatics for Integrating Biology and the Bedside Project (U54LM008748)