Tobacco Cessation Counseling Among Underserved Patients: A Report from CaReNet

TABLE 3
LOGISTIC REGRESSION RESULTS: PATIENT FACTORS ASSOCIATED WITH LIKELIHOOD OF RECEIVING SMOKING CESSATION COUNSELING

Discussion

These findings demonstrate that although smoking is more common in CaReNet’s Medicaid and uninsured patients, providers gave cessation advice less often to these patients. The actual prevalence of tobacco use may be even greater than we think because providers may underreport it, but our results are similar to national trends.⁴ The decreased rate of tobacco counseling in underserved patients is in contrast to the findings in a study that were based on patient recall,¹¹ rather than the provider-report methodology of NAMCS. However, our counseling results are consistent with a national NAMCS analysis, which found that tobacco use was addressed more frequently with HMO-insured patients than Medicaid patients.¹³ In that study, the overall primary care counseling rate (33%) was similar to that of CaReNet providers (37%). To the best of our knowledge, our finding of a lower rate of tobacco counseling in uninsured patients has not been previously reported.

Our study does not address why providers are less likely to advise Medicaid or uninsured patients to quit smoking. It is possible that tobacco interventions, such as pharmacologic aids and comprehensive cessation programs, may not be available to these groups because of cost. Providers may simply be reflecting this situation by not addressing cessation. Even so, cost and access barriers do not explain why providers would be less likely to give simple cessation advice to disadvantaged smokers. One possibility is that these findings may indicate a lower quality of care for these patients. Other preventive care measures have been shown to be performed less often in uninsured patients,¹⁶ and several studies have documented a lower quality of care for Medicaid and uninsured patients with chronic diseases.^17-19

Limitations

A major limitation of our study is that the uninsured or Medicaid groups may have included sicker or more complex patients at the surveyed visits, thus there may have been less time to devote to tobacco cessation advice during that clinic visit. Unfortunately, the NAMCS instrument does not readily measure disease severity or case mix. In our analysis, we controlled for the presence of 1 or more chronic diseases (limited in NAMCS to 4 specific conditions), but this is only a crude measure of patient complexity. If patients in one of the payment groups were sicker, they might have had more frequent clinic visits, and tobacco cessation may have been addressed at higher rates over time than were found in this cross-sectional study. However, even in the presence of major morbidities, the uninsured often lack continuity because of their tenuous access to care.

If the payer mix of residents and faculty was significantly different, and residents addressed tobacco use at a different rate than faculty, this could explain some of the counseling differences. Unfortunately, this NAMCS instrument is anonymous and cannot identify the type of provider. Similarly, it is possible that the type of visit (acute care, chronic care, or prevention) may account for some of the findings. However, NAMCS also does not specify type of visit and there may be considerable overlap at any given encounter.

Our study administered NAMCS to the practices that make up CaReNet, and the results are not necessarily generalizable to other populations. There is substantial regional variation in health care access programs for the uninsured²⁰; therefore the uninsured patients in CaReNet may not be representative of uninsured in primary care elsewhere. Also, the demographics of CaReNet include higher percentages of Hispanics and Medicaid recipients compared with a national analysis of primary care trends.²¹ CaReNet more closely resembles community health centers,²² except CaReNet has a greater number of Hispanic patients and fewer black patients, reflecting the particular demographics of Colorado. However, the smoking prevalence rates we found in the privately insured, Medicaid, and uninsured groups were similar to national patterns.

Conclusions

Our study argues for the inclusion of a separate payment category that clearly identifies the uninsured in NAMCS and other data collection instruments. Future studies on tobacco counseling rates should be designed to differentiate factors associated with the lower rate of counseling in disadvantaged populations, such as patient complexity, competing demands, lack of access to cessation resources, or lower standards of care. Identification of these factors may be valuable in implementing interventions to improve the rate of counseling for these patients.