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

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

<p>Abstract</p> <p>Background</p> <p>Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process.</p> <p>Discussion</p> <p>We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence.</p> <p>Summary</p> <p>In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.</p

The HIV-1 transmission bottleneck

It is well established that most new systemic infections of HIV-1 can be traced back to one or a limited number of founder viruses. Usually, these founders are more closely related to minor HIV-1 populations in the blood of the presumed donor than to more abundant lineages. This has led to the widely accepted idea that transmission selects for viral characteristics that facilitate crossing the mucosal barrier of the recipient’s genital tract, although the specific selective forces or advantages are not completely defined. However, there are other steps along the way to becoming a founder virus at which selection may occur. These steps include the transition from the donor’s general circulation to the genital tract compartment, survival within the transmission fluid, and establishment of a nascent stable local infection in the recipient’s genital tract. Finally, there is the possibility that important narrowing events may also occur during establishment of systemic infection. This is suggested by the surprising observation that the number of founder viruses detected after transmission in intravenous drug users is also limited. Although some of these steps may be heavily selective, others may result mostly in a stochastic narrowing of the available founder pool. Collectively, they shape the initial infection in each recipient