Trends in smoking documentation rates in safety net clinics.

OBJECTIVE: To assess the impact of provider incentive policy on smoking status documentation. DATA SOURCES: Primary data were extracted from structured electronic medical records (EMRs) from 15 community health centers (CHCs). STUDY DESIGN: This was an observational study of data from 2006 to 2013, assessing changes in documentation of smoking status over time. DATA EXTRACTION METHODS: We extracted structured EMR data for patients age 18 and older with at least one primary care visit. PRINCIPAL FINDINGS: Rates of documented smoking status rose from 30 percent in 2006 to 90 percent in 2013; the largest increase occurred from 2011 to 2012 following policy changes (21.3% [95% CI, 8.2%, 34.4%] from the overall trend). Rates varied by clinic and across patient subgroups. CONCLUSIONS: Documentation of smoking status improved markedly after introduction of new federal standards. Further improvement in documentation is still needed, especially for males, nonwhite patients, those using opioids, and HIV + patients. More research is needed to study whether changes in documentation lead to improvements in counseling, cessation, and patient outcomes.

Patient characteristics associated with poor inhaler technique among a cohort of patients with COPD.

BACKGROUND: Inhaled therapies are the cornerstone of pharmacologic management for COPD. Each device requires a unique series of steps to be most effective, making appropriate instruction in inhaler technique a key part of the management of COPD. OBJECTIVES: Examine characteristics of patients and devices associated with poor technique among patients with COPD. METHODS: Cross-sectional study of subjects with COPD using at least one of: metered dose inhaler, Advair Diskus, Spiriva Handihaler, identified from the COPD Outcomes-based Network for Clinical Effectiveness and Research Translation (CONCERT) registry. Technique was assessed face-to-face using manufacturer-provided dummy inhalers, with standardized checklists for each device. We used logistic regression to model associations with poor inhaler technique, defined as an error in ≥20% of the steps, as a function of patient characteristics, with educational attainment the primary predictor. RESULTS: 688 individuals meet eligibility criteria, 65.5% had poor technique for at least one device. In adjusted analyses, Black race was associated with poor technique (OR 3.25, 95%CI 1.86-5.67) while greater than high school education was associated with decreased odds of poor technique (OR 0.35, 95%CI 0.17-0.70 for trade school/some college, OR 0.25, 95%CI 0.11-0.61 for college or more, p ≤ 0.001 for test of linear trend). The percentage of errors varied between devices, with subjects making proportionally the most errors for MDIs. CONCLUSIONS: Poor inhaler technique is common among individuals with COPD, varies between devices, and is associated with race and educational attainment. Tailored educational interventions to teach inhaler technique should be part of the process of initiating and monitoring inhaled therapies.

Respiratory and Bronchitic Symptoms Predict Intention to Quit Smoking among Current Smokers with, and at Risk for, Chronic Obstructive Pulmonary Disease.

RATIONALE: Smoking cessation is the most important intervention for patients with chronic obstructive pulmonary disease (COPD). What leads smokers with COPD to quit smoking remains unknown. OBJECTIVES: We sought to examine the association between respiratory symptoms and other markers of COPD severity with intention to quit smoking among a cohort of patients with probable COPD. METHODS: We conducted a cross-sectional study of subjects with COPD or fixed airflow obstruction clinically diagnosed on the basis of pulmonary function testing. The subjects were identified in the COPD Outcomes-based Network for Clinical Effectiveness and Research Translation multicenter registry. The primary outcome was the intention to quit smoking within the next 30 days (yes or no), which was examined using model building with multivariable logistic regression, clustered by study site. MEASUREMENTS AND MAIN RESULTS: We identified 338 current smokers with COPD via the registry. Of these subjects, 57.4% (n = 194) had confirmed airflow obstruction based on pulmonary function testing. Nearly one-third (29.2%; n = 99) intended to quit smoking in the next 30 days. In adjusted analyses, compared with subjects without airflow obstruction based on pulmonary function testing, subjects with Global Initiative for Chronic Obstructive Lung Disease stage I/II COPD were more likely to be motivated to quit (odds ratio [OR], 1.85; 95% confidence interval [CI], 1.37-2.49), with no association found for subjects with Global Initiative for Chronic Obstructive Lung Disease stage III/IV disease. Among the entire cohort, frequent phlegm (OR, 2.10; 95% CI, 1.22-3.64), cough (OR, 1.74; 95% CI, 1.01-2.99), wheeze (OR, 1.73; 95% CI, 1.09-3.18), and higher modified Medical Research Council dyspnea score (OR, 1.26 per point; 95% CI, 1.13-1.41) were associated with increased odds of intending to quit smoking. Low self-reported health was associated with decreased odds of intending to quit (OR, 0.75; 95% CI, 0.62-0.92). CONCLUSIONS: Frequent cough, phlegm, wheeze, and shortness of breath were associated with intention to quit smoking in the next 30 days, with a less clear relationship for severity of illness graded by pulmonary function testing and self-rated health. These findings can be used to inform the content of tobacco cessation interventions to provide a more tailored approach for patients with respiratory diseases such as COPD.

Using the CER Hub to ensure data quality in a multi-institution smoking cessation study.

Comparative effectiveness research (CER) studies involving multiple institutions with diverse electronic health records (EHRs) depend on high quality data. To ensure uniformity of data derived from different EHR systems and implementations, the CER Hub informatics platform developed a quality assurance (QA) process using tools and data formats available through the CER Hub. The QA process, implemented here in a study of smoking cessation services in primary care, used the 'emrAdapter' tool programmed with a set of quality checks to query large samples of primary care encounter records extracted in accord with the CER Hub common data framework. The tool, deployed to each study site, generated error reports indicating data problems to be fixed locally and aggregate data sharable with the central site for quality review. Across the CER Hub network of six health systems, data completeness and correctness issues were prevalent in the first iteration and were considerably improved after three iterations of the QA process. A common issue encountered was incomplete mapping of local EHR data values to those defined by the common data framework. A highly automated and distributed QA process helped to ensure the correctness and completeness of patient care data extracted from EHRs for a multi-institution CER study in smoking cessation.