Published Online: March 14, 2014
Rebecca J. Williams, DrPh; Andrew L. Masica, MD; Mary Ann McBurnie, PhD; Leif I. Solberg, MD; Steffani R. Bailey, PhD; Brian Hazlehurst, PhD; Stephen E. Kurtz, PhD; Andrew E. Williams, PhD; Jon E. Puro, MHA-PA; and Victor J. Stevens, PhD
Objectives: Physicians can help patients quit smoking using the 5 As of smoking cessation. This study aimed to (1) identify the proportion of known smokers that receive smoking cessation services in the course of routine clinical practice; (2) describe demographic and comorbidity characteristics of patients receiving the 5 As in these systems; and (3) evaluate differences in performance of the 5 As across health systems, gender, and age categories.
Study Design: Electronic medical records of 200 current smokers from 6 unique health systems (N = 1200) were randomly selected from 2006 to 2010. Primary care encounter progress notes were hand coded for occurrences of the 5 As.
Methods: Bivariate comparisons of delivery of the 3 smoking-cessation services by site, gender, and age category were analyzed using χ² tests.
Results: About 50% of smokers were advised to quit smoking, 39% were assessed for their readiness to quit, and 54% received some type of assistance to help them quit smoking. Only 2% had a documented plan for follow-up regarding their quitting efforts (arrange). Significant differences were found among sites for documentation of receiving the 5 As and between age groups receiving assistance with quitting. There was no statistically significant difference between genders in receipt of the 5 As.
Conclusions: Documentation of adherence to the 5 As varied by site and some demographics. Adjustments to protocols for addressing cessation and readiness to quit may be warranted. Health systems could apply the methodology described in this paper to assess their own performance, and then use that as a basis to guide improvement initiatives.
Am J Manag Care. 2014;20(3):e82-e89
Health systems could benefit from an analysis of the 5 As, using patient records to assess their own performance and to guide future smoking cessation initiatives.
Results could help with the training of healthcare providers to apply the 5 As of smoking cessation framework to all patients.
Smoking cessation initiatives and policies for a healthcare organization could be generated around findings.
Health systems could benefit from an analysis of patient demographics and use those to help with smoking cessation.
Tobacco use remains the leading cause of preventable death in the United States, and yet nearly 46 million people currently smoke cigarettes.1-3 Primary care physicians can greatly facilitate smoking cessation among their patients, and this effort can be a cost-saving clinical preventive service.4-6 Well-accepted, evidencebased guidelines for delivering tobacco-cessation treatments in the primary care setting have been shown to be effective and are recommended as standard care.7-13 Physicians are encouraged to help patients quit by implementing the 5 As of smoking cessation, which include (1) asking all patients about their smoking status; (2) providing personalized advice to quit; (3) assessing smokers’ readiness to quit; (4) assisting motivated patients in their quit attempts, and (5) arranging follow-up contacts for those receiving assistance to quit.
Despite these recommendations and the fact that almost 70% of smokers are interested in quitting,14 the overall proportion of patients who receive counseling remains low15 and there is substantial variation in the use of the 5 As framework across clinical practices and demographic groups.7,14,16,17 Provision of the first 2 As (ask and advise) has been steadily increasing,8,18 but delivery of assess, assist, and arrange has been inconsistent.7,8,10,12,15,19 The rate of cessation help is often lower for Hispanic patients than for non-Hispanic whites; and younger smokers are less likely to receive cessation assistance compared with older smokers.20
Little is known about adherence to the 5 As since the 2008 publication of updated recommendations on treating tobacco use and dependence. 7,8,10,12,19 Prior studies assessing provision of the 5 As have generally relied on patient questionnaires, or data collection was limited to specific coded fields within patient medical records.8-10,12,19 Additionally, prior work in assessing the 5 As has been done within a single health system, limiting feasibility of extending findings to other health systems.
This paper extends previous work by leveraging comprehensive medical record data, including coded data fields (eg, diagnosis codes), progress notes, and patient educational materials about smoking, which were handed out to the patient during a visit to assess implementation of the 5 As. A random sample of 200 smokers from each of 6 different health systems across the United States was used. The data reported here were generated by a manual chart review process involving the Comparative Effectiveness Research Hub (CER Hub), a network of asthma and smoking cessation researchers from each of the 6 health systems used for this study (www.cerhub.org).21 Smoking cessation activities based on the 5 As were implemented within the 6 health systems that collectively make up the CER Hub.
The study aims are 3-fold: (1) identify the proportion of known smokers that receive smoking cessation services in the course of routine clinical practice; (2) describe demographic and comorbidity characteristics of smokers receiving smoking cessation services in these systems; (3) evaluate differences in performance of the 5 As across health systems, and also across gender and age categories. Health systems could benefit from an analysis of the 5 As, using patient records to assess their own performance and to guide future smoking cessation initiatives.
Data were collected from 6 health systems, representing unique demographic and geographic populations. The 6 sites constitute a convenience sample of medium-sized healthcare organizations. While this group cannot be seen as a representative sample for the United States, this group does have some geographic diversity, and represents a fairly diverse patient population in terms of race, ethnicity, and socioeconomic status. Each health system also has a distinctive technology infrastructure and electronic medical record (EMR) system. The Institutional Review Board at each health system approved the study protocol. Descriptions of participating health systems are provided in Table 1.
The medical records of 200 current smokers in each of the 6 selected health systems were randomly selected for this study (N = 1200). Inclusion criteria included patients 12 years and older who were identified as (1) a current smoker at any point during the years 2006 to 2010, regardless of “quitting” events and (2) having at least 1 primary care visit in each of the 5 study years. We classified patients as “current smokers” if (1) they received any of the following International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9- CM) diagnosis codes related to tobacco-use disorders: 305.1, 649.01, 649.02, 649.03, 649.04, or 989.84, at any primary care visit or (2) had an update to their social history indicating “current smoker” during the study period. Smoking-related comorbidities during the observation period were also documented for each participant, and ethnicity and race information was extracted from each patient’s medical record.
Coding of the 5 As
A single primary-care encounter from each of the 1200 medical records, as described above, was hand coded for documentation of the 5 As. An “encounter” included all data linked to the encounter (eg, vital signs, reasons for visit, medications and procedures ordered, diagnoses) as well as progress notes and patient education materials printed out for the patient. Encounter records were formatted as XML computer language files according to a schema conforming to Health Level Seven International’s (HL7’s) Clinical Document Architecture (CDA) standard.22,23 These records were de-identified and uploaded onto a secure Web server, where they were accessed by project staff using a Web-based application called Manual Coder that is part of the CER Hub. Users of Manual Coder sequence through encounter records in a data set and have the ability to highlight text elements representative of the study measures (in this instance, components of the 5 As) and then select the code appropriate to the highlighted text from a list. The applied codes, as well as the highlighted content from the encounter record, can be extracted from the database for analysis of either site-specific or aggregate data.
Coding staff from each site were trained on using Manual Coder for coding the 5 As by webinar conferencing during a 3-week period. Following this training, staff were provided written instructions along with a pilot set of 10 encounter records to code using Manual Coder. Results were tabulated and reviewed in a subsequent webinar session during which discrepancies and errors in coding were discussed. Once consensus was established on the pilot records, 1 to 2 project staff at each site coded the data set from their respective health system (N = 200 records each). During the course of the coding process, questions about specific data elements were communicated to the lead investigator. Responses from the investigator were used to update the written instructions, and communicated in real time by e-mail and in a weekly meeting for project staff. The coding process at all project sites was completed in 1 month. The completed codings were reviewed by the lead trainer, who checked for and adjudicated discrepancies with the coding instructions. Mapping of the 5 As coding definitions from the medical record encounter, as documented by a healthcare provider, is displayed in Table 2.
Comorbidities were assessed using groups of ICD-9-CM codes recorded at primary care encounters during the observation period. The categories of codes used for this analysis included cancer (all types except skin cancer), cardiovascular disease (CVD), asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, and stroke.
Available data allowed for bivariate (contingency table) comparisons of delivery of smoking cessation services by site, gender, and age category (12-24, 25-49, and 50+ years) using χ² tests. All P values are 2-sided with significance defined at the .05 level.
Demographic and Comorbidity Characteristics of Smokers
Demographics of participants are displayed in Table 3. Fifty-six percent (56%) of smokers in the combined sample were male and 53% were 50 years and older. Sixty-three percent (63%) of the sample had a recorded race, with white representing the largest racial group (40%). The comorbidities with the highest reported rates were hypertension (21%) and diabetes (8%).
The gender distribution among the 6 health systems was approximately even except for site B, where 68% of smokers were female, and site D, where 93% of smokers were male. Smokers aged 12 to 24 years were the least represented across all sites (only 6% of the sample). Sites B, C, and D had a larger proportion of smokers belonging to the 50 years and older group. Patient race varied considerably between the 6 health systems, representing the local populations at each site.
Proportion of Smokers Receiving the 5 As
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