Person:

Regan, Susan

Background: Routine screening for HIV infection leads to early detection and treatment. We examined patient characteristics associated with repeated screening in a high prevalence country. Methods: We analyzed data from a cohort of 5,229 adults presenting for rapid HIV testing in the outpatient departments of 2 South African hospitals from November 2006 to August 2010. Patients were eligible if they were ≥18 years, reported no previous diagnosis with HIV infection, and not pregnant. Before testing, participants completed a questionnaire including gender, age, HIV testing history, health status, and knowledge about HIV and acquaintances with HIV. Enrollment HIV test results and CD4 counts were abstracted from the medical record. We present prevalence of HIV infection and median CD4 counts by HIV testing history (first-time vs. repeat). We estimated adjusted relative risks (ARR’s) for repeat testing by demographics, health status, and knowledge of HIV and others with HIV in a generalized linear model. Results: Of 4,877 participants with HIV test results available, 26% (N = 1258) were repeat testers. Repeat testers were less likely than first-time testers to be HIV-infected (34% vs. 54%, p<0.001). Median CD4 count was higher among repeat than first-time testers (201/uL vs. 147/uL, p<0.001). Among those HIV negative at enrollment (N = 2,499), repeat testing was more common among those with family or friends living with HIV (ARR 1.50, 95% CI: 1.33–1.68), women (ARR: 1.24, 95% CI: 1.11–1.40), and those self-reporting very good health (ARR: 1.28, 95% CI: 1.12–1.45). Conclusions: In this high prevalence setting, repeat testing was common among those undergoing HIV screening, and was associated with female sex, lower prevalence of HIV infection, and higher CD4 counts at diagnosis.

Background: A hospital admission offers smokers an opportunity to quit. Smoking cessation counseling provided in the hospital is effective, but only if it continues for more than one month after discharge. Providing smoking cessation medication at discharge may add benefit to counseling. A major barrier to translating this research into clinical practice is sustaining treatment during the transition to outpatient care. An evidence-based, practical, cost-effective model that facilitates the continuation of tobacco treatment after discharge is needed. This paper describes the design of a comparative effectiveness trial testing a hospital-initiated intervention against standard care. Methods/design: A two-arm randomized controlled trial compares the effectiveness of standard post-discharge care with a multi-component smoking cessation intervention provided for three months after discharge. Current smokers admitted to Massachusetts General Hospital who receive bedside smoking cessation counseling, intend to quit after discharge and are willing to consider smoking cessation medication are eligible. Study participants are recruited following the hospital counseling visit and randomly assigned to receive Standard Care or Extended Care after hospital discharge. Standard Care includes a recommendation for a smoking cessation medication and information about community resources. Extended Care includes up to three months of free FDA-approved smoking cessation medication and five proactive computerized telephone calls that use interactive voice response technology to provide tailored motivational messages, offer additional live telephone counseling calls from a smoking cessation counselor, and facilitate medication refills. Outcomes are assessed at one, three, and six months after hospital discharge. The primary outcomes are self-reported and validated seven-day point prevalence tobacco abstinence at six months. Other outcomes include short-term and sustained smoking cessation, post-discharge utilization of smoking cessation treatment, hospital readmissions and emergency room visits, and program cost per quit. Discussion: This study tests a disseminable smoking intervention model for hospitalized smokers. If effective and widely adopted, it could help to reduce population smoking rates and thereby reduce tobacco-related mortality, morbidity, and health care costs.

Objective: The Surviving Sepsis Campaign (SSC or “the Campaign”) developed guidelines for management of severe sepsis and septic shock. A performance improvement initiative targeted changing clinical behavior (process improvement) via bundles based on key SSC guideline recommendations on process improvement and patient outcomes. Design and setting: A multifaceted intervention to facilitate compliance with selected guideline recommendations in the ICU, ED, and wards of individual hospitals and regional hospital networks was implemented voluntarily in the US, Europe, and South America. Elements of the guidelines were “bundled” into two sets of targets to be completed within 6 h and within 24 h. An analysis was conducted on data submitted from January 2005 through March 2008. Main results: Data from 15,022 subjects at 165 sites were analyzed to determine the compliance with bundle targets and association with hospital mortality. Compliance with the entire resuscitation bundle increased linearly from 10.9% in the first site quarter to 31.3% by the end of 2 years (P < 0.0001). Compliance with the entire management bundle started at 18.4% in the first quarter and increased to 36.1% by the end of 2 years (P = 0.008). Compliance with all bundle elements increased significantly, except for inspiratory plateau pressure, which was high at baseline. Unadjusted hospital mortality decreased from 37 to 30.8% over 2 years (P = 0.001). The adjusted odds ratio for mortality improved the longer a site was in the Campaign, resulting in an adjusted absolute drop of 0.8% per quarter and 5.4% over 2 years (95% CI, 2.5–8.4%). Conclusions: The Campaign was associated with sustained, continuous quality improvement in sepsis care. Although not necessarily cause and effect, a reduction in reported hospital mortality rates was associated with participation. The implications of this study may serve as an impetus for similar improvement efforts.Electronic supplementary material The online version of this article (doi:10.1007/s00134-009-1738-3) contains supplementary material, which is available to authorized users.

Objective: We assessed racial and ethnic differences in depression diagnosis and treatment in a primary care population. Methods: A sample of primary care outpatients in 2007 was generated using the electronic medical record (EMR). Patients were considered depressed if their providers billed for depression-related codes; they were considered prescribed antidepressants if any antidepressants were on their medication list. Rates of diagnosis and medication prescription were estimated using a generalized linear model with a Poisson distribution, adjusting for covariates. Results: In the resulting sample (n=85,790), all minority groups were less likely to be diagnosed with depression as compared to Whites (p<0.05); 11.36% of Whites had a depression diagnosis, as compared to 6.44% of Asian Americans, 7.55% of African Americans, and 10.18% of Latino Americans. Among those with a depression diagnosis (n=11,096), 54.07% of African Americans were prescribed antidepressant medications, as compared to 63.19% Whites (p<0.05); Asian Americans and Latino Americans showed a trend of being less likely to be prescribed antidepressant medications. Conclusions: Our study illustrates differences in diagnosis and treatment for minority primary care patients, and is innovative in using the EMR to probe these differences. Further research is needed to understand the underlying reasons for these observed differences.

Importance The Human Immunodeficiency Virus (HIV) epidemic has evolved, with an increasing non-communicable disease (NCD) burden emerging and need for long-term management, yet there are limited data to help delineate the optimal care model to screen for NCDs for this patient population. Objective: The primary aim was to compare rates of NCD preventive screening in persons living with HIV/AIDS (PLWHA) by type of HIV care model, focusing on metabolic/cardiovascular disease (CVD) and cancer screening. We hypothesized that primary care models that included generalists would have higher preventive screening rates. Design: Prospective observational cohort study. Setting: Partners HealthCare System (PHS) encompassing Brigham & Women’s Hospital, Massachusetts General Hospital, and affiliated community health centers. Participants: PLWHA age >18 engaged in active primary care at PHS. Exposure HIV care model categorized as infectious disease (ID) providers only, generalist providers only, or ID plus generalist providers. Main Outcome(s) and Measures(s) Odds of screening for metabolic/CVD outcomes including hypertension (HTN), obesity, hyperlipidemia (HL), and diabetes (DM) and cancer including colorectal cancer (CRC), cervical cancer, and breast cancer. Results: In a cohort of 1565 PLWHA, distribution by HIV care model was 875 ID (56%), 90 generalists (6%), and 600 ID plus generalists (38%). Patients in the generalist group had lower odds of viral suppression but similar CD4 counts and ART exposure as compared with ID and ID plus generalist groups. In analyses adjusting for sociodemographic and clinical covariates and clustering within provider, there were no significant differences in metabolic/CVD or cancer screening rates among the three HIV care models. Conclusions: There were no notable differences in metabolic/CVD or cancer screening rates by HIV care model after adjusting for sociodemographic and clinical factors. These findings suggest that HIV patients receive similar preventive health care for NCDs independent of HIV care model.

Abstract Background. There are limited data on human immunodeficiency virus (HIV) quality indicators according to model of HIV care delivery. Comparing HIV quality indicators by HIV care model could help inform best practices because patients achieving higher levels of quality indicators may have a mortality benefit. Methods. Using the Partners HIV Cohort, we categorized 1565 patients into 3 HIV care models: infectious disease provider only (ID), generalist only (generalist), or infectious disease provider and generalist (ID plus generalist). We examined 12 HIV quality indicators used by 5 major medical and quality associations and grouped them into 4 domains: process, screening, immunization, and HIV management. We used generalized estimating equations to account for most common provider and multivariable analyses adjusted for prespecified covariates to compare composite rates of HIV quality indicator completion. Results. We found significant differences between HIV care models, with the ID plus generalists group achieving significantly higher quality measures than the ID group in HIV management (94.4% vs 91.7%, P = .03) and higher quality measures than generalists in immunization (87.8% vs 80.6%, P = .03) in multivariable adjusted analyses. All models achieved rates that equaled or surpassed previously reported quality indicator rates. The absolute differences between groups were small and ranged from 2% to 7%. Conclusions. Our results suggest that multiple HIV care models are effective with respect to HIV quality metrics. Factors to consider when determining HIV care model include healthcare setting, feasibility, and physician and patient preference.

Background: Unplanned care interruption (UCI) challenges effective HIV treatment. We determined the frequency and risk factors for UCI in Nigeria. Methods: We conducted a retrospective-cohort study of adults initiating antiretroviral therapy (ART) between January 2009 and December 2011. At censor, patients were defined as in care, UCI, or inactive. Associations between baseline factors and UCI rates were quantified using Poisson regression. Results: Among 2,496 patients, 44 % remained in care, 35 % had ≥1 UCI, and 21 % became inactive. UCI rates were higher in the first year on ART (39/100PY), than the second (19/100PY), third (16/100PY), and fourth (14/100PY) years (p < 0.001). In multivariate analysis, baseline CD4 > 350/uL (IRR 3.21, p < 0.0001), being a student (IRR 1.95, p < 0.0001), and less education (IRR 1.58, p = 0.001) increased risk for UCI. Fifty-five percent of patients with UCI and viral load data had HIV viral load > 1,000 copies/ml upon return to care. Discussion UCI were observed in over one-third of patients treated, and were most common in the first year on ART. High baseline CD4 count at ART initiation was the greatest predictor of subsequent UCI. Conclusions: Interventions focused on the first year on ART are needed to improve continuity of HIV care.

Background: Cigarette smoking is widespread among HIV-infected patients, who confront increased risk of smoking-related co-morbidities. The effects of HIV infection and HIV-related variables on smoking and smoking cessation are incompletely understood. We investigated the correlates of smoking and quitting in an HIV-infected cohort using a validated natural language processor to determine smoking status. Method We developed and validated an algorithm using natural language processing (NLP) to ascertain smoking status from electronic health record data. The algorithm was applied to records for a cohort of 3487 HIV-infected from a large health care system in Boston, USA, and 9446 uninfected control patients matched 3:1 on age, gender, race and clinical encounters. NLP was used to identify and classify smoking-related portions of free-text notes. These classifications were combined into patient-year smoking status and used to classify patients as ever versus never smokers and current smokers versus non-smokers. Generalized linear models were used to assess associations of HIV with 3 outcomes, ever smoking, current smoking, and current smoking in analyses limited to ever smokers (persistent smoking), while adjusting for demographics, cardiovascular risk factors, and psychiatric illness. Analyses were repeated within the HIV cohort, with the addition of CD4 cell count and HIV viral load to assess associations of these HIV-related factors with the smoking outcomes. Results: Using the natural language processing algorithm to assign annual smoking status yielded sensitivity of 92.4, specificity of 86.2, and AUC of 0.89 (95% confidence interval [CI] 0.88–0.91). Ever and current smoking were more common in HIV-infected patients than controls (54% vs. 44% and 42% vs. 30%, respectively, both P<0.001). In multivariate models HIV was independently associated with ever smoking (adjusted rate ratio [ARR] 1.18, 95% CI 1.13–1.24, P <0.001), current smoking (ARR 1.33, 95% CI 1.25–1.40, P<0.001), and persistent smoking (ARR 1.11, 95% CI 1.07–1.15, P<0.001). Within the HIV cohort, having a detectable HIV RNA was significantly associated with all three smoking outcomes. Conclusions: HIV was independently associated with both smoking and not quitting smoking, using a novel algorithm to ascertain smoking status from electronic health record data and accounting for multiple confounding clinical factors. Further research is needed to identify HIV-related barriers to smoking cessation and develop aggressive interventions specific to HIV-infected patients.

Background: Smoking cessation interventions for hospitalized smokers are effective in promoting smoking cessation, but only if the tobacco dependence treatment continues after the patient leaves the hospital. Sustaining tobacco dependence treatment after hospital discharge is a challenge for health care systems. Our previous single-site randomized controlled trial demonstrated the effectiveness of an intervention that facilitated the delivery of comprehensive tobacco cessation treatment, including both medication and counseling, after hospital discharge. We subsequently streamlined the intervention model to increase its potential for dissemination. This new model is being tested in a larger multi-site trial with broader eligibility criteria in order to enroll a more representative sample of hospitalized smokers. This paper describes the trial design and contrasts it with the earlier study. Methods/Design A 2-arm, 3-site randomized controlled trial is testing the hypothesis that a multi-component Sustained Care intervention is more effective than Standard Care in helping hospitalized cigarette smokers stop smoking after hospital discharge. The trial enrolls adult daily cigarette smokers who are admitted to 1 of 3 participating hospitals in Massachusetts or Pennsylvania. Participants receive the same smoking cessation intervention in the hospital. They are randomly assigned to receive either Standard Care or Sustained Care after hospital discharge. Participants in the Sustained Care arm receive a free 3-month supply of FDA-approved smoking cessation medication and 5 interactive voice response calls that provide tailored motivational messages, medication refills, and access to a live tobacco treatment counselor. Participants in the Standard Care arm receive a smoking cessation medication recommendation and information about community resources. Outcomes are assessed at 1, 3, and 6 months after discharge. The primary outcome is biochemically-validated tobacco abstinence for the past 7 days at 6-month follow-up. Other outcome measures include self-reported tobacco abstinence measures, use of medication and counseling after discharge, hospital readmissions, and program cost-effectiveness. Discussion We adapted a proven intervention for hospitalized smokers to enhance its potential for dissemination and are testing it in a multi-site trial. Study enrollment data suggests that the trial achieved the goal of recruiting a broader sample of hospitalized smokers. Trial registration Comparative Effectiveness of Post-Discharge Strategies for Hospitalized Smokers (Helping HAND2) NCT01714323. Registered October 22, 2012.

HIV clinics formerly supported by the President’s Emergency Plan for AIDS Relief are transferring patients to public-sector clinics. We evaluated adolescent linkage to care after a large-scale transfer from a President’s Emergency Plan for AIDS Relief-subsidized pediatric HIV clinic in Durban, South Africa. All adolescents (11–18 years) in care at a pediatric state-subsidized, hospital-based clinic (HBC) were transferred, from May to June 2012, to government sites [primary health care (PHC) clinic; community health center (CHC); and HBCs] or private clinics. Caregivers were surveyed 7–8 months after transfer to assess their adolescents’ linkage to care and their reports were validated by clinic record audits in a subset of randomly selected clinics. Of the 309 (91%) caregivers reached, only 5 (2%) reported that their adolescent did not link. Of the 304 adolescents who linked, 105 (35%) were referred to a PHC, 73 (24%) to a CHC and 106 (35%) to a HBC. A total of 146 (48%) linked adolescents attended a different clinic than that assigned. Thirty-five (20%) of the 178 who linked and were assigned to a PHC or CHC ultimately attended a HBC. Based on clinic validation, the estimated transfer success was 88% (95% confidence interval: 77%–97%). The large majority of adolescents successfully transferred to a new HIV clinic, although nearly half attended a clinic other than that assigned.