BackgroundPatients with untreated substance use disorders (SUDs) are at risk for frequent emergency department visits and repeated hospitalizations. Project Engage, a US pilot program at Wilmington Hospital in Delaware, was conducted to facilitate entry of these patients to SUD treatment after discharge. Patients identified as having hazardous or harmful alcohol consumption based on results of the Alcohol Use Disorders Identification Test-Primary Care (AUDIT-PC), administered to all patients at admission, received bedside assessment with motivational interviewing and facilitated referral to treatment by a patient engagement specialist (PES). This program evaluation provides descriptive information on self-reported rates of SUD treatment initiation of all patients and health-care utilization and costs for a subset of patients.MethodsProgram-level data on treatment entry after discharge were examined retrospectively. Insurance claims data for two small cohorts who entered treatment after discharge (2009, n = 18, and 2010, n = 25) were reviewed over a six-month period in 2009 (three months pre- and post-Project Engage), or over a 12-month period in 2010 (six months pre- and post-Project Engage). These data provided descriptive information on health-care utilization and costs. (Data on those who participated in Project Engage but did not enter treatment were unavailable).ResultsBetween September 1, 2008, and December 30, 2010, 415 patients participated in Project Engage, and 180 (43%) were admitted for SUD treatment. For a small cohort who participated between June 1, 2009, and November 30, 2009 (n = 18), insurance claims demonstrated a 33% ($35,938) decrease in inpatient medical admissions, a 38% ($4,248) decrease in emergency department visits, a 42% ($1,579) increase in behavioral health/substance abuse (BH/SA) inpatient admissions, and a 33% ($847) increase in outpatient BH/SA admissions, for an overall decrease of $37,760. For a small cohort who participated between June 1, 2010, and November 30, 2010 (n = 25), claims demonstrated a 58% ($68,422) decrease in inpatient medical admissions; a 13% ($3,308) decrease in emergency department visits; a 32% ($18,119) decrease in BH/SA inpatient admissions, and a 32% ($963) increase in outpatient BH/SA admissions, for an overall decrease of $88,886.ConclusionsThese findings demonstrate that a large percentage of patients entered SUD treatment after participating in Project Engage, a novel intervention with facilitated referral to treatment. Although the findings are limited by the retrospective nature of the data and the small sample sizes, they do suggest a potentially cost-effective addition to existing hospital services if replicated in prospective studies with larger samples and controls.

The admission AUDIT-PC score is an excellent discriminator of AWS and could be an important component of future clinical prediction rules. Calibration and further validation on a large prospectivecohort is indicated.

BackgroundWarfarin is recommended for stroke prevention in high-risk patients with atrial fibrillation. However, it is often underutilized and inadequately managed in actual clinical practice.ObjectivesTo examine the patterns of warfarin use and their relationship with stroke and bleeding in atrial fibrillation patients in community-based primary care practices.DesignRetrospective longitudinal cohort study.ParticipantsA total of 1141 atrial fibrillation patients were selected from 17 primary care practices with a shared electronic medical record and characterized by stroke risk, potential barriers to anticoagulation, and comorbid conditions.Main measuresDuration and number of warfarin exposures, interruptions in warfarin exposure > 45 days, stroke, and bleeding events.ResultsAmong 1141 patients with a mean age of 70 years (standard deviation 13.3) and mean follow-up of 3.4 years (standard deviation 3.0), 764 (67%) were treated with warfarin. Warfarin was discontinued within 1 year in 194 (25.4%), and 349 (45.7%) remained on warfarin at the end of follow-up. Interruptions in warfarin use were common, occurring in 32.6% (249 of 764) of patients. Those with two or more interruptions were younger and at lower baseline stroke risk when compared to those with no interruptions. There were 76 first strokes and 73 first-bleeding events in the follow-up period. When adjusted for baseline stroke risk, time to warfarin start, and total exposure time, two or more interruptions in warfarin use was associated with an increased risk of stroke (relative risk, 2.29; 95% confidence interval: 1.29–4.07). There was no significant association between warfarin interruptions and bleeding events.ConclusionWarfarin was underutilized in a substantial portion of eligible atrial fibrillation patients in these community-based practices. In addition, prolonged interruptions in anticoagulation were common in this population, and multiple interruptions were associated with over twice the risk of stroke when compared to those treated continuously.

Clinical and demographic characteristics influence choice and duration of initial oral hypoglycemic treatment as well as regimen changes.

Use of electronic health record (EHR) content for comparative effectiveness research (CER) and population health management requires significant data configuration. A retrospective cohort study was conducted using patients with diabetes followed longitudinally (N=36,353) in the EHR deployed at outpatient practice networks of 2 health care systems. A data extraction and classification algorithm targeting identification of patients with a new diagnosis of type 2 diabetes mellitus (T2DM) was applied, with the main criterion being a minimum 30-day window between the first visit documented in the EHR and the entry of T2DM on the EHR problem list. Chart reviews (N=144) validated the performance of refining this EHR classification algorithm with external administrative data. Extraction using EHR data alone designated 3205 patients as newly diagnosed with T2DM with classification accuracy of 70.1%. Use of external administrative data on that preselected population improved classification accuracy of cases identified as new T2DM diagnosis (positive predictive value was 91.9% with that step). Laboratory and medication data did not help case classification. The final cohort using this 2-stage classification process comprised 1972 patients with a new diagnosis of T2DM. Data use from current EHR systems for CER and disease management mandates substantial tailoring. Quality between EHR clinical data generated in daily care and that required for population health research varies. As evidenced by this process for classification of newly diagnosed T2DM cases, validation of EHR data with external sources can be a valuable step.