Publications

CONTEXT

Counseling smokers to quit smoking and providing them with pharmaceutical cessation aides are among the most beneficial and cost-effective interventions that clinicians can offer patients. Yet assistance with quitting is not universally covered by health plans or offered by all clinicians. Analysis of stakeholders' perspectives and interests can identify the barriers to more widespread provision of cessation services and suggest strategies for the public policy agenda to advance smoking cessation.

METHODS

Review of literature and discussions with representatives of stakeholders.

FINDINGS

All stakeholders-health plans, employers, clinicians, smokers, and the government-face barriers to broader smoking cessation activities. These range from health plans' perceiving that covering counseling and pharmacotherapy will increase costs without producing commensurate health care savings, to clinicians' feeling unprepared and uncompensated for counseling. Like other preventive measures aimed at behavior, efforts directed at smoking cessation have marginal status among health care interventions. State governments can help correct this status by increasing Medicaid coverage of treatment and expanding coverage for state employees. The federal government can promote the adoption of six initiatives recommended by a government subcommittee on cessation: set up a national quit line, develop a media campaign to encourage cessation, include cessation benefits in all federally funded insurance plans, create a research infrastructure to improve cessation rates, develop a clinician training agenda, and create a fund to increase cessation activities through a new $2 per pack cigarette excise tax. Both the federal and state governments can increase cessation by adopting policies such as the higher cigarette tax and laws prohibiting smoking in workplaces and public places.

CONCLUSIONS

Public policy efforts should assume greater social responsibility for smoking cessation, including more aggressive leadership at the state and federal levels, as well as through advocacy, public health, and clinician organizations.

Malaria case management in Africa is characterized by presumptive treatment and substantial overtreatment. We evaluated an integrated team-based training program on malaria case management. Surveillance data 120 days before and after training were compared at eight health facilities in Uganda. After training, the proportion of patients with suspected malaria referred for blood smears increased from 38.3% to 54.6% (P=0.04) in persons<5 years of age years and from 34.1% to 53.4% (P=0.02) in those>or=5 years of age. The proportion of patients with negative blood smears prescribed antimalarial drugs decreased from 47.9% to 19.6% (P<0.001) in persons<5 years of age and from 38.8% to 15.6% (P<0.001) in those>or=5 years of age. Training did not improve the proportion of patients with positive blood smears prescribed antimalarial drugs, the proportion of patients prescribed appropriate antimalarial drugs, or the diagnostic accuracy of microscopy. Integrated team-based training may improve malaria case management and reduce the number of unnecessary antimalarial treatments.

We previously demonstrated the role of a phospholipid transfer protein (PLTP) gene variation (rs2294213) in determining levels of high-density lipoprotein cholesterol (HDL-C) in hypoalphalipoproteinemia (HypoA). We have now explored the role of PLTP in hyperalphalipoproteinemia (HyperA). The human PLTP gene was screened for sequence anomalies by DNA melting in 107 subjects with HyperA. The association with plasma lipoprotein levels was evaluated. We detected 7 sequence variations: 1 previously reported variation (rs2294213) and 5 novel mutations including 1 missense mutation (L106F). The PLTP activity was unchanged in the p.L106F mutation. The frequency of the rs2294213 minor allele was markedly increased in the HyperA group (7.0%) in comparison with a control group (4.3%) and the hypoalphalipoproteinemia group (2.2%). Moreover, rs2294213 was strongly associated with HDL-C levels. Linear regression models predict that possession of the rs2294213 minor allele increases HDL-C independent of triglycerides. These findings extend the association of rs2294213 with HDL-C levels into the extremes of the HDL distribution.

A survey-based COPD severity scoring algorithm could prove useful for targeted disease management and risk-adjustment. For this purpose, we sought to prospectively validate a COPD severity score that had previously been cross-sectionally validated. Using a population-based sample of 267 adults with self-reported physician-diagnosed COPD, we examined the extent to which this COPD severity score predicts future respiratory hospitalizations, emergency department (ED) visits, and outpatient visits. Structured telephone interviews, conducted at baseline and on an annual basis in two subsequent years, determined COPD severity scores and health-care utilization. A basic predictive model for respiratory-specific health-care utilization was developed using sociodemographics, tobacco history, and medical comorbidity data in multivariate logistic regression analysis. The added predictive value of the COPD severity score over and above this basic model was then evaluated by testing the change in model concordance indices. Our analysis demonstrated that the COPD severity score did, in fact, increase the concordance-index of models predicting future respiratory hospitalizations (increase from 80% to 87%; P = 0.03), ED visits (64% to 82%, P = 0.003), and outpatient visits (59% to 77%, P < 0.0001). In a separate analysis, both a greater baseline severity score and worsening of the severity score over time were prospectively associated with each outcome studied (P < 0.05 for each). In conclusion, the COPD severity score adds predictive value in estimating future respiratory-specific health-care utilization and is longitudinally responsive to evolving changes in COPD status over time. This severity score may be used to adjust for disease severity or to identify high-risk populations.