Cancer prevention in primary care: predictors of patient counseling across four risk behaviors over 24 months.

OBJECTIVE: Rates of preventive counseling remain below national guidelines. We explored physician and patient predictors of preventive counseling across multiple cancer risk behaviors in at-risk primary care patients. METHODS: We surveyed 3557 patients, with at least one of four cancer risk behaviors: smoking, diet, sun exposure, and/or mammography screening, at baseline and 24 months. Patients reported receipt of 4A's (Ask, Advise, Assist, Arrange follow-up); responses were weighted and combined to reflect more thorough counseling (Ask=1, Advise=2, Assist=3, Arrange=4, score range 0-10) for each target behavior. A series of linear-regression models, controlling for office clustering, examined patient, physician and other situational predictors at 24 months. RESULTS: Risk behavior topics were brought up more often for mammography (90%) and smoking (79%) than diet (56%) and sun protection (30%). Assisting and Arranging follow-up were reported at low frequencies across all behaviors. More thorough counseling for all behaviors was associated with multiple visits and higher satisfaction with care. Prior counseling predicted further counseling on all behaviors except smoking, which was already at high levels. Other predictors varied by risk behavior. CONCLUSIONS: More thorough risk behavior counseling can be delivered opportunistically across multiple visits; doing so is associated with more satisfaction with care.

Determining the cost-effectiveness of a computer-based smoking cessation intervention in primary care.

PURPOSE: To evaluate the incremental effectiveness and cost-effectiveness of a staged-based, computerized smoking cessation intervention relative to standard care in an urban managed care network of primary care physicians. DESIGN: Decision-analytic model based on results of a randomized clinical trial. METHODOLOGY: Patient outcomes and cost estimates were derived from clinical trial data. Effectiveness was measured in terms of 7-day point-prevalence abstinence at 6 months post-intervention. Quality-adjusted life years (QALYs) and cost-effectiveness (CE) were calculated, with CE measured as cost per patient per life year saved and per quality-adjusted life years saved. CE estimates were adjusted to account for partial behavior change as measured in terms of progression in stage of readiness to quit. Sensitivity analyses were conducted to evaluate the robustness of key model assumptions. PRINCIPAL FINDINGS: Intervention patients were 1.77 times more likely to be smoke-free at 6 months follow-up than those in standard care (p=.078). The intervention generated an additional 3.24 quitters per year. Annualized incremental costs were $5,570 per primary care practice, and $40.83 per smoker. The mean incremental cost-effectiveness ratio was $1,174 per life year saved ($869 per QALY). When the intervention impact on progression in stage of readiness to quit was also considered, the mean incremental cost-effectiveness ratio declined to $999 per life year saved ($739 per QALY). CONCLUSIONS: From a physician's practice perspective, the stage-based computer tailored intervention was cost-effective relative to standard care. Incorporation of partial behavior change into the model further enhanced favorability of the cost-effectiveness ratio.

Assessment of parents' smoking behaviors at a pediatric emergency department.

The pediatric emergency department is an important source of treatment for children with complaints related to environmental tobacco smoke (ETS) and may provide a teachable moment to address parent smoking. Parents who smoke were recruited from a pediatric emergency department waiting room and completed an interview assessment used to develop intervention messages. Of the 715 parents in the final sample, 77% were women, 60% White, and 60% low income (

Randomized controlled trial of a computer-based, tailored intervention to increase smoking cessation counseling by primary care physicians.

OBJECTIVE: The primary care visit represents an important venue for intervening with a large population of smokers. However, physician adherence to the Smoking Cessation Clinical Guideline (5As) remains low. We evaluated the effectiveness of a computer-tailored intervention designed to increase smoking cessation counseling by primary care physicians. METHODS: Physicians and their patients were randomized to either intervention or control conditions. In addition to brief smoking cessation training, intervention physicians and patients received a one-page report that characterized the patients' smoking habit and history and offered tailored recommendations. Physician performance of the 5As was assessed via patient exit interviews. Quit rates and smoking behaviors were assessed 6 months postintervention via patient phone interviews. Intervention effects were tested in a sample of 70 physicians and 518 of their patients. Results were analyzed via generalized and mixed linear modeling controlling for clustering. MEASUREMENTS AND MAIN RESULTS: Intervention physicians exceeded controls on "Assess" (OR 5.06; 95% CI 3.22, 7.95), "Advise" (OR 2.79; 95% CI 1.70, 4.59), "Assist-set goals" (OR 4.31; 95% CI 2.59, 7.16), "Assist-provide written materials" (OR 5.14; 95% CI 2.60, 10.14), "Assist-provide referral" (OR 6.48; 95% CI 3.11, 13.49), "Assist-discuss medication" (OR 4.72;95% CI 2.90, 7.68), and "Arrange" (OR 8.14; 95% CI 3.98, 16.68), all p values being < 0.0001. Intervention patients were 1.77 (CI 0.94, 3.34,p = 0.078) times more likely than controls to be abstinent (12 versus 8%), a difference that approached, but did not reach statistical significance, and surpassed controls on number of days quit (18.4 versus 12.2, p < .05) but not on number of quit attempts. CONCLUSIONS: The use of a brief computer-tailored report improved physicians' implementation of the 5As and had a modest effect on patients' smoking behaviors 6 months postintervention.

Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms.

BACKGROUND: Treating multiple health behavior risks on a population basis is one of the most promising approaches to enhancing health and reducing health care costs. Previous research demonstrated the efficacy of expert system interventions for three behaviors in a population of parents. The interventions provide individualized feedback that guides participants through the stages of change for each of their risk behaviors. This study extended that research to a more representative population of patients from primary care practice and to targeting of four rather than three behaviors. METHODS: Stage-based expert systems were applied to reduce smoking, improve diet, decrease sun exposure, and prevent relapse from regular mammography. A randomized clinical controlled trial recruited 69.2% of primary care patients (N = 5407) at home via telephone. Three intervention contacts were delivered for each risk factor at 0, 6, and 12 months. The primary outcome measures were the percentages of at-risk patients at baseline who progressed to the action or maintenance stages at 24-month follow-up for each of the risk behaviors. RESULTS: Significant treatment effects were found for each of the four behaviors, with 25.4% of intervention patients in action or maintenance for smoking, 28.8% for diet, and 23.4% for sun exposure. The treatment group had less relapse from regular mammography than the control group (6% vs. 10%). CONCLUSION: Proactive, home-based, and stage-matched expert systems can produce relatively high population impacts on multiple behavior risks for cancer and other chronic diseases.

Multiple behavioral risk factor interventions in primary care. Summary of research evidence.

BACKGROUND: An important barrier to the delivery of health behavior change interventions in primary care settings is the lack of an integrated screening and intervention approach that can cut across multiple risk factors and help clinicians and patients to address these risks in an efficient and productive manner. METHODS: We review the evidence for interventions that separately address lack of physical activity, an unhealthy diet, obesity, cigarette smoking, and risky/harmful alcohol use, and evidence for interventions that address multiple behavioral risks drawn primarily from the cardiovascular and diabetes literature. RESULTS: There is evidence for the efficacy of interventions to reduce smoking and risky/harmful alcohol use in unselected patients, and evidence for the efficacy of medium- to high-intensity dietary counseling by specially trained clinicians in high-risk patients. There is fair to good evidence for moderate, sustained weight loss in obese patients receiving high-intensity counseling, but insufficient evidence regarding weight loss interventions in nonobese adults. Evidence for the efficacy of physical activity interventions is limited. Large gaps remain in our knowledge about the efficacy of interventions to address multiple behavioral risk factors in primary care. CONCLUSIONS: We derive several principles and strategies for delivering behavioral risk factor interventions in primary care from the research literature. These principles can be linked to the "5A's" construct (assess, advise, agree, assist, and arrange-follow up) to provide a unifying conceptual framework for describing, delivering, and evaluating health behavioral counseling interventions in primary healthcare settings. We also provide recommendations for future research.

Assessing the transtheoretical model of change constructs for physicians counseling smokers.

Baseline data from a population-based sample of 259 primary care physicians were used to examine the interrelations of 3 central constructs of the Transtheoretical Model of Change (TTM; stages of change, self-efficacy, and decisional balance) in regard to smoking cessation counseling behavior. In this article we explore the potential use of the TTM for future interventions to help understand and guide physicians' behavior change toward increasing adoption of smoking cessation interventions with their patients. It was hypothesized that self-efficacy and the decisional balance of counseling would be significantly related to physicians' stages of change, which in turn would be related to self-reported physician counseling behavior. Principal components analyses were conducted to examine the self-efficacy and decisional balance constructs. Coefficient alphas were.90 for self-efficacy and.84 and.78 for the pros and cons scales, respectively. Consistent with the TTM, analyses of variance revealed that later stages of physicians' readiness to provide smoking cessation counseling were associated with higher self-efficacy scores. Earlier stages showed significantly higher cons and lower pros of smoking cessation counseling. Structural equation modeling procedures supported the hypothesized path analysis model in which 3 constructs related to stage of readiness, which in turn related to reported physicians' counseling behavior.

An academic detailing intervention to disseminate physician-delivered smoking cessation counseling: smoking cessation outcomes of the Physicians Counseling Smokers Project.

BACKGROUND: Little is known about the effectiveness of interventions to disseminate smoking cessation interventions among a population of primary care physicians. This study's objective was to determine the effect of a community-based academic detailing intervention on the quit rates of a population-based sample of smokers. METHODS: This community-based, quasi-experimental study involved representative samples of 259 primary care physicians and 4295 adult smokers. An academic detailing intervention was delivered to physicians in intervention areas over a period of 15 months. Analyses were performed on the data from the 2346 subjects who reported at least one physician visit over 24 months. Multivariate regression analyses were conducted to determine the impact of the intervention on self-reported smoking quit rates, reported by adjusted odds ratios. RESULTS: Among smokers reporting a physician visit during the study period, there was a borderline significant effect for those residing in intervention areas versus control areas (OR = 1.35; 95% CI.99-1.83; P = 0.057). Among a subgroup of 819 smokers who reported a visit with an enrolled physician, we observed a significant effect for those residing in intervention areas (OR = 1.80; 95% CI 1.16-2.75; P = 0.008). CONCLUSION: An academic detailing intervention to enhance physician delivered smoking cessation counseling is an effective strategy for disseminating smoking cessation interventions among community-based practices.

Physician recruitment for a community-based smoking cessation intervention.

OBJECTIVE: Our goal was to describe a strategy to recruit a population-based sample of physicians into a trial to test an approach to disseminate physician-delivered smoking cessation interventions. STUDY DESIGN: The 3-phase population-based recruitment trial included: (1) a print-based promotional appeal, (2) in-person presentations with by the principal investigator (PI), and (3) follow-up calls by the PI and paid physician recruiters. Participation requirements were kept minimal to facilitate recruitment. POPULATION: All primary care physicians statewide were targeted; 3 counties were chosen as intervention areas and 2 counties as control areas. A subsample of physicians was targeted in the larger control areas through a matching process. OUTCOME MEASURED: We measured physician recruitment rate. RESULTS: Eighty-one percent (n=259) of all eligible physicians were successfully recruited into our study. CONCLUSIONS: The full multistep process was important in getting participation agreement. By using an intensive recruitment strategy and minimizing research demands, it is possible to recruit community-based primary care physicians for research projects that will help them enhance the preventive services they provide to their patients.