Caroline E. Freiermuth

Electronic Interventions for Alcohol Misuse and Alcohol Use Disorders A Systematic Review

Alcohol misuse is a broad term that incorporates a spectrum of severity, ranging from hazardous use that exceeds guideline limits to misuse severe enough to meet criteria for an alcohol use disorder (AUD). Table 1 provides a glossary of terms along this spectrum. To address the impairment related to alcohol misuse (1) from a public health perspective, the U.S. Preventive Services Task Force recommends screening and brief intervention (2, 3), an approach that reduces alcohol consumption by 3 to 4 drinks per week for up to 12 months after the intervention (4). Screening and brief intervention sessions typically consist of brief assessment, followed by personalized normative feedback and advice to adhere to recommended drinking limits, which are typically defined for men as consuming 4 standard drinks or fewer (1 drink equals 14 g of alcohol) on any day and 14 drinks or fewer per week and for women as 3 drinks or fewer on any day and 7 drinks or fewer per week (5). Table 1. Glossary of Terms on the Spectrum of Alcohol Misuse* Alcohol misuse counseling, including screening and brief intervention, is constrained by barriers, such as inadequate funding, time, and trained personnel (68). In addition, the efficacy of screening and brief intervention in settings other than primary care is not established (9). Electronic interventions (e-interventions) may address some barriers and extend the reach of treatment by reducing demands for clinician time and clinic space while increasing the number of persons who can access treatment and their frequency of accessing treatment. With 87% of the U.S. population using the Internet (10), e-interventions can potentially reach persons with drinking problems who wish to remain anonymous, lack the time or resources for traditional therapy, need to access therapy during nonstandard business hours, or live in rural areas (11, 12). Previous systematic reviews that evaluated e-interventions for alcohol misuse have generally found short-term benefits (1317), but examination of maintenance of intervention effects is needed. Two recent systematic reviews have reported follow-up outcomes at 6 months or longer. However, they did not analyze college student and noncollege adult trials separately (13, 17), despite distinctions between these groups in patterns of alcohol consumption and associated impairment (18, 19). In addition, previous systematic reviews have generally not reported on the efficacy of e-interventions for AUDs (1317) or provided detailed descriptions of treatment intensity, including amount and type of human support (13, 14, 17). To characterize treatment intensity for alcohol misuse and evaluate evidence for their efficacy, we did a systematic review of randomized, controlled trials (RCTs). We compared e-interventions for alcohol misuse with inactive or minimal intervention controls for reducing alcohol consumption and alcohol-related impairment in adults and college students for 6 months or longer. Methods We followed a standard protocol in which key steps, such as eligibility assessment, data abstraction, and risk of bias, were piloted and discussed by team members. A technical report that fully details our methods and results is available (20). We addressed 3 research questions. First, for e-interventions that targeted adults who misused alcohol or had an AUD, what level, type, and method of user support were provided; by whom; and in what clinical context? Second, for adults who misused alcohol but did not meet diagnostic criteria for an AUD, what were the effects of e-interventions compared with inactive controls? Third, for adults who were at high risk for or who had an AUD, what were the effects of e-interventions compared with inactive controls? Appendix Table 1 provides individual trial characteristics. Appendix Table 1. Study Characteristics Data Sources and Searches We searched MEDLINE (via PubMed), the Cochrane Library, EMBASE, and PsycINFO from 1 January 2000 to 18 August 2014 for peer-reviewed, English-language RCTs. We used Medical Subject Heading terms and selected free-text terms for alcohol misuse, therapy types of interest, and electronic delivery. The MEDLINE search was updated on 25 March 2015. The search strategies are shown in Appendix Table 2. We reviewed bibliographies of included trials and applicable systematic reviews for missed publications (14, 15, 2125). To assess for publication bias, we searched ClinicalTrials.gov for trials that met our eligibility criteria (26) and found 2 trials that were completed at least 1 year before our literature search but were unpublished. Appendix Table 2. Search Strategies Trial Selection Two reviewers used prespecified eligibility criteria to assess all titles and abstracts. The full text of potentially eligible trials was retrieved for further evaluation. We included RCTs that compared e-interventions with inactive or active controls in patients with alcohol misuse or an AUD. We reported effects on alcohol consumption or another eligible outcome at 6 months or longer (Appendix Table 3). E-interventions could be delivered by CD-ROM, online, mobile applications, or interactive voice response (a technology that allows a computer to interact with humans using voice and signaling over analog telephone lines). Two investigators assessed for eligibility, and disagreements were resolved by team discussion or a third reviewer. Appendix Table 3. Inclusion and Exclusion Criteria Data Extraction and Quality Assessment Data abstractions were done by 1 reviewer and confirmed by a second. We assessed each trials risk of bias using criteria specific for RCTs and summarized overall risk of bias as low, moderate, or high using the approach described by the Agency for Healthcare Research and Quality (26). The Appendix shows questions and the rationale for quality ratings criteria, and detailed quality ratings for each included trial are displayed in Appendix Table 4. Appendix Table 4. Quality of Included Studies Data Synthesis and Analysis We evaluated the overall strength of evidence for selected outcomes as high, moderate, low, or insufficient using the domains of directness, risk of bias, consistency and precision of treatment effects, and risk of publication bias (27). Table 2 shows strength-of-evidence domain and overall ratings. Table 2. SOE, by Outcome Domains* While synthesizing abstracted data, we classified the e-interventions by the level of supplementary human support. Level 1 included e-interventions with no human support; level 2 included e-interventions supplemented by noncounseling interactions with study staff, such as technical support; and level 3 included e-interventions supplemented by counseling with trained staff. The key outcomes were alcohol consumption, meeting recommended alcohol consumption limits, rates of binge drinking, alcohol-related health, social or legal problems, health-related quality of life, and adverse effects. When at least 3 trials reported a given outcome, we did a meta-analysis. We combined continuous outcomes by using mean differences (MDs) or standardized MDs when instruments varied and combined dichotomous outcomes by using risk ratios in random-effects models. Alcohol consumption was converted to a common unit (grams per week) across trials. We used metafor package in R (R Foundation for Statistical Computing) (28) to calculate summary estimates of effect, stratified by condition and sample (college students vs. adults), at 6 and 12 months, with KnappHartung adjustment of SEs of the estimated coefficients (29, 30). When at least 3 trials were rated as low or moderate risk of bias, we excluded trials rated as high risk of bias and did sensitivity analyses to compute summary estimates. We evaluated statistical heterogeneity in treatment effects by using the Cochran Q and I 2 statistics. We planned subgroup analyses, specifying a priori, to explore the following potential sources of heterogeneity: follow-up rates, treatment dose, and level of human support given with the intervention. However, these analyses could not be done because subgroups did not meet the prespecified minimum of 4 trials per subgroup (31). When there were too few trials for quantitative synthesis, we analyzed data qualitatively, focusing on identifying novel aspects of the e-intervention and patterns of efficacy. Role of the Funding Source This review was funded by the U.S. Department of Veterans Affairs. The funding source had no role in the study design, data collection, analysis, preparation of the manuscript, or the decision to submit the manuscript for publication. Results We reviewed 100 full-text articles of the 856 citations that were screened and identified 28 trials that met eligibility criteria (Appendix Figure 1). The populations were divided between college students (n=14) and noncollege adults (n=14). Only 3 trials specifically recruited participants who were at high risk for or who had an AUD. The other 25 trials recruited participants who misused alcohol. A single trial used a mobile device as the delivery platform (32). Strength of evidence for each outcome is summarized in Table 2. Appendix Figure 1. Summary of evidence search and selection. AUD = alcohol use disorder; IVR = interactive voice response; RCT = randomized, controlled trial. * Manuscript reference list includes additional references cited for background and methods. All 28 trials and 3 trials of AUD were qualitatively described, and quantitative meta-analysis was done for 25 trials. E-Intervention Characteristics and Support Seventeen trials were minimal support (level 1) interventions that used no human support, 8 used low noncounseling support (level 2), and 3 included moderate or high (level 3) counseling support. Summary characteristics and support for e-interventions are listed in Table 3. Most trials examined a 1-time intervention (n=19), delivered online or at a desktop computer (n=24), that compared a persons alcohol consu

Application of a Proactive Risk Analysis to Emergency Department Sickle Cell Care

Introduction Patients with sickle cell disease (SCD) often seek care in emergency departments (EDs) for severe pain. However, there is evidence that they experience inaccurate assessment, suboptimal care, and inadequate follow-up referrals. The aim of this project was to 1) explore the feasibility of applying a failure modes, effects and criticality analysis (FMECA) in two EDs examining four processes of care (triage, analgesic management, high risk/high users, and referrals made) for patients with SCD, and 2) report the failures of these care processes in each ED. Methods A FMECA was conducted of ED SCD patient care at two hospitals. A multidisciplinary group examined each step of four processes. Providers identified failures in each step, and then characterized the frequency, impact, and safeguards, resulting in risk categorization. Results Many “high risk” failures existed in both institutions, including a lack of recognition of high-risk or high-user patients and a lack of emphasis on psychosocial referrals. Specific to SCD analgesic management, one setting inconsistently used existing analgesic policies, while the other setting did not have such policies. Conclusion FMECA facilitated the identification of failures of ED SCD care and has guided quality improvement activities. Interventions can focus on improvements in these specific areas targeting improvements in the delivery and organization of ED SCD care. Improvements should correspond with the forthcoming National Heart, Lung and Blood-sponsored guidelines for treatment of patients with sickle cell disease.

A Prospective Emergency Department Quality Improvement Project to Improve the Treatment of Vaso-Occlusive Crisis in Sickle Cell Disease: Lessons Learned

BACKGROUND Guidelines recommend rapid, aggressive management of vaso-occlusive crisis (VOC) for patients with sickle cell disease (SCD). A large prospective research and quality improvement (QI) project was conducted to measure changes in clinical outcomes in two EDs-academic medical centers with emergency medicine residency programs and Level 1 trauma centers-during a 2.5-year time period (October 2011-March 2014). METHODS A QI team used a Plan-Do-Study-Act approach to modify and implement changes to opioid analgesic protocols for the emergency department (ED) treatment of VOC. Data were collected quarterly; the team reviewed the results and made modifications to improve outcomes. A structured health record review was conducted to assess clinical outcomes (10 records/quarter/site). Patient interviews were conducted to measure satisfaction with pain management. Outcomes were compared before (T1) and after (T2) implementation of an electronic health record (EHR). RESULTS One hundred ninety-six ED health records (118 unique patients, mean age = 32 [standard deviation, 11], 51% male) were analyzed. Before implementation, trends in decreasing time to initial analgesic administration were noted. There was a statistically significant increase in arrival to administration of first analgesic time between T1 and T2 at Site 1 but not at Site 2. Neither site showed significant changes in time between the administration of the first and second opioid doses, total opioid dose administered, or patient satisfaction. CONCLUSION While QI efforts initially shortened door-to-analgesic times, these gains were not sustained. The lessons learned can help other EDs improve the timely delivery of analgesics to patients with SCD.

Shift in Emergency Department Provider Attitudes Toward Patients With Sickle Cell Disease.

Patients with sickle cell disease frequently seek care in the emergency department. They have reported experiencing negative attitudes from emergency providers. This study was undertaken to evaluate change in emergency provider attitudes toward patients with sickle cell disease over a 2.5-year time period when several educational efforts were ongoing. The General Perceptions about Sickle Cell Disease Patients Scale was used to measure emergency provider attitudes at 2 emergency departments at baseline, 6 months, and 30 months into the project. Analyses of covariance were used to test for effects of site, time, and provider type, as well as their interactions, on Negative attitudes, Uneasiness With Care, and Positive Attitudes subscale scores, after controlling for years of provider experience. The number of surveys returned at the 3 time points was 216, 182, and 113, respectively. The mean Negative Attitudes subscale scores decreased significantly over time, with significantly higher mean Negative Attitudes subscale scores reported by nurses than by physicians. The mean Uneasiness With Care subscale scores did not differ significantly over time, but the mean score was significantly higher for physicians than for nurses. The mean Positive Attitudes subscale scores significantly improved over time, with physicians tending to have a higher mean Positive Attitudes subscale scores than nurses. During the observation period, there was improvement in attitudes, with a decline in mean Negative Attitudes subscale scores and increase in mean Positive Attitudes subscale scores. Physicians reported better attitudes than nurses.

Emergency Department (ED), ED Observation, Day Hospital, and Hospital Admissions for Adults with Sickle Cell Disease

Introduction Use of alternative venues to manage uncomplicated vaso-occlusive crisis (VOC), such as a day hospital (DH) or ED observation unit, for patients with sickle cell anemia, may significantly reduce admission rates, which may subsequently reduce 30-day readmission rates. Methods In the context of a two-institution quality improvement project to implement best practices for management of patients with sickle cell disease (SCD) VOC, we prospectively compared acute care encounters for utilization of 1) emergency department (ED); 2) ED observation unit; 3) DH, and 4) hospital admission, of two different patient cohorts with SCD presenting to our two study sites. Using a representative sample of patients from each institution, we also tabulated SCD patient visits or admissions to outside hospitals within 20 miles of the patients’ home institutions. Results Over 30 months 427 patients (297 at Site 1 and 130 at Site 2) initiated 4,740 institutional visits, totaling 6,627 different acute care encounters, including combinations of encounters. The range of encounters varied from a low of 0 (203 of 500 patients [40.6%] at Site 1; 65 of 195 patients [33.3%] at Site 2), and a high of 152 (5/month) acute care encounters for one patient at Site 2. Patients at Site 2 were more likely to be admitted to the hospital during the study period (88.4% vs. 74.4%, p=0.0011) and have an ED visit (96.9% vs. 85.5%, p=0.0002). DH was used more frequently at Site 1 (1.207 encounters for 297 patients at Site 1, vs. 199 encounters for 130 patients at Site 2), and ED observation was used at Site 1 only. Thirty-five percent of patients visited hospitals outside their home academic center. Conclusion In this 30-month assessment of two sickle cell cohorts, healthcare utilization varied dramatically between individual patients. One cohort had more hospital admissions and ED encounters, while the other cohort had more day hospital encounters and used a sickle cell disease observation VOC protocol. One-third of patients sampled visited hospitals for acute care outside of their care providers’ institutions.

Social and Behavioral Factors in Sickle Cell Disease: Employment Predicts Decreased Health Care Utilization

Abstract:The purpose: to determine frequency of health care encounters among people with sickle cell disease (SCD) seeking treatment for a vaso-occlusive crisis (VOC). Health care encounters are categorized by visit type (day hospital, ED visit, hospitalization), prevalence of self-reported behavioral and social factors, and any associations between behavioral and social factors and health care encounters. Ninety-five people with SCD were enrolled in a prospective descriptive study in North Carolina. Patients were interviewed concerning behavioral-social factors, and a report of health care encounters was produced, generated by ICD codes associated with VOCs between October 2011 and March 2014. Among 95 patients, there were a total of 839 day hospital and 1,990 ED visits, and 1,101 hospital admissions. Prevalent behavioral and social factors were depression (29%), anxiety (34%), illicit drug use (6%); unstable home situation (17%); and unemployment (81%). Employment and stable home were significantly associated with decreased frequency of health care encounters.

Characteristics of patients that do not initially respond to intravenous antihypertensives in the emergency department: subanalysis of the CLUE trial.

Introduction Hypertensive emergency has a high mortality risk and the treatment goal is to quickly lower blood pressure with intravenous (IV) medications. Characteristics that are associated with non-response to IV antihypertensives have not been identified. The objective is to identify patient characteristics associated with resistance to IV antihypertensives. Methods This was a subanalysis of patients enrolled in the previously described comparative effectiveness trial of IV nicardipine vs. labetalol use in the emergency department (CLUE) study, a randomized trial of nicardipine vs. labetalol. Non-responders were defined as those patients who did not achieve target systolic blood pressure (SBP), as set by the treating physician, within thirty minutes of IV antihypertensive medication, +/− 20mmHg. Stepwise logistic regression was used to identify covariates associated with the measurement outcomes. Results CLUE enrolled 226 patients, 52.7% female, 76.4% black, mean age of 52.6±14.6 years, of whom 110 were treated with nicardipine and 116 with labetalol. The median (IQR) initial systolic blood pressure was 211mmHg (198, 226), 210 (200, 230), and 211mmHg (198, 226), for the total, non-responder, and responder cohorts, respectively (p-value=0.65, 95% CI [−5.8–11.3]). Twenty-nine were non-responders, 9 in the nicardipine and 20 in the labetalol group. In univariate analysis, several symptoms suggestive of end organ damage were associated with non-response. After multiple variable logistic regression (AUC = 0.72), treatment with labetalol (OR 2.7, 95% CI [1.1–6.7]), history of stroke (OR 5.4, 95% CI [1.6–18.5]), and being male (OR 3.3, 95% CI [1.4–8.1]) were associated with failure to achieve target blood pressure. Conclusion Male gender and history of previous stroke are associated with difficult to control blood pressure.