Smoking Cessation Interventions After Lung Cancer Screening Guideline Change

Introduction: Recent guideline changes for lung cancer screening with low-dose computed tomography recommend smoking cessation interventions be done in parallel with screening. The purpose of this study is to determine the post-guideline rates of smoking cessation interventions among patients eligible and ineligible for lung cancer screening.Methods: Using electronic health records collected from a large ambulatory care system in northern California between 2010 and 2017, authors identified new patients who were current smokers aged 55–80 years visiting a primary care provider, and grouped patients into lung cancer screening–eligible heavy smokers, screening-ineligible moderate smokers, and screening-ineligible light smokers. Screening-eligible smokers versus screening-ineligible smokers were compared in receipt of smoking cessation interventions before (2010–2013) and after (2014–2017) the guideline change, overall and by intervention type (formal counseling, informal counseling, pharmacotherapy) using hierarchical generalized linear models. Analyses were conducted in 2018–2019.Results: After the guideline change, the likelihood of receiving any smoking cessation intervention (OR=1.44, 95% CI=1.28, 1.61, p<0.05), informal counseling (OR=1.29, 95% CI=1.15, 1.46, p<0.05), and pharmacotherapy (OR=1.24, 95% CI=1.02, 1.50, p<0.05) during a new patient visit significantly increased, with the increase not varying by level of smoking. For formal counseling, the post-guideline increase was greater for screening-eligible heavy smokers (OR=3.15, 95% CI=1.18, 8.36, p<0.05) and moderate smokers (OR=3.58, 95% CI=1.29, 9.95, p<0.05) relative to light smokers.Conclusions: Smoking cessation interventions increased after new lung cancer screening guidelines. Given the sizable adverse impacts of smoking on morbidity and mortality, small increases in implementation of smoking cessation interventions could have substantial public health benefits

The association between Asian patient race/ethnicity and lower satisfaction scores

Background Patient satisfaction is increasingly being used to assess, and financially reward, provider performance. Previous studies suggest that race/ethnicity (R/E) may impact satisfaction, yet few practices adjust for patient R/E. The objective of this study is to examine R/E differences in patient satisfaction ratings and how these differences impact provider rankings. Methods Patient satisfaction survey data linked to electronic health records from two large outpatient centers in northern California – a non-profit organization of community-based clinics (Site A) and an academic medical center (Site B) – was collected and analyzed. Participants consisted of adult patients who received outpatient care at Site A from December 2010 to November 2014 and Site B from March 2013 to August 2014, and completed Press-Ganey Medical Practice Survey questionnaires (N = 216,392 (Site A) and 30,690 (Site B)). Self-reported non-Hispanic white (NHW), Black, Latino, and Asian patients were studied. For six questions each representing a survey subdomain, favorable ratings were defined as top-box (“very good”) compared to all other categories (“very poor,” “poor,” “fair,” and “good”). Using multivariable logistic regression with provider random effects, we assessed whether the likelihood of giving favorable ratings differed by patient R/E, adjusting for patient age and sex. Results Asian, younger and female patients provided less favorable ratings than other R/E, older and male patients. After adjustment, Asian patients were less likely than NHW patients to provide top-box ratings to the overall assessment question “likelihood of recommending this practice to others” (Site A: Asian predicted probability (PP) 0.680, 95% confidence interval (CI): 0.675–0.685 compared to NHW PP 0.820, 95% CI: 0.818–0.822; Site B: Asian PP 0.734, 95% CI: 0.733–0.736 compared to NHW PP 0.859, 95% CI: 0.859–0.859). The effect sizes for Asian R/E were greater than the effect sizes for older age and female sex. An absolute 3% decrease in mean composite score between providers serving different percentages of Asian patients translated to an absolute 40% drop in national ranking. Conclusions Patient satisfaction scores may need to be adjusted for patient R/E, particularly for providers caring for high panel percentages of Asian patients

Changes in Treatment Content of Services During Trauma-informed Integrated Services for Women with Co-occurring Disorders

The experience of trauma is highly prevalent in the lives of women with mental health and substance abuse problems. We examined how an intervention targeted to provide trauma-informed integrated services in the treatment of co-occurring disorders has changed the content of services reported by clients. We found that the intervention led to an increased provision of integrated services as well as services addressing each content area: trauma, mental health and substance abuse. There was no increase in service quantity from the intervention. Incorporation of trauma-specific element in the treatment of mental health and substance abuse may have been successfully implemented at the service level thereby better serve women with complex behavioral health histories

Do Preventive Visits Among Seniors Lead to Better Completion of Recommended Preventive Services?

Background: Under the Affordable Care Act, the annual preventive visit became fully covered by Medicare. We assessed whether the use of preventive visit, as compared to frequent use of routine nonpreventive primary care visit, is associated with higher completion rates of recommended preventive care services. Methods: Primary care patients (aged 65–85 years) in a large, mixed-payer ambulatory care organization between 2011 and 2014 were identified (N = 184,576). We examined preventive care services recommended by U.S. Preventive Services Task Force guidelines or the National Committee for Quality Assurance. Services were categorized as: 1) Preventive Screening –– colorectal cancer screening, breast cancer screening; 2) Management of Chronic Conditions –– annual monitoring for patients on persistent medications (ACE inhibitors/ARBs or diuretics), coordinated diabetes care; and 3) Preventive Counseling –– smoking cessation counseling, discussion of end-of-life care planning. We estimated the likelihood of completing each service by preventive visit status (yes/no) and the frequency of nonpreventive primary care visits. We used a mixed-effect multivariate logistic regression, controlling for patient demographic and clinical characteristics and provider characteristics, with patient random effects to take into account clustering across multiple observations per patient. Odds ratios (OR) were generated. A statistical significance level of 0.01 was used. Results: Seniors who had a preventive visit, versus those who did not, were more likely to have completed recommended services for Preventive Screening (OR: 1.77–1.85), Management of Chronic Conditions (OR: 1.32–1.48) and Preventive Counseling (OR: 3.04–3.95). The likelihood of completing preventive services increased with the frequency of nonpreventive primary care visits for some services, but to a much smaller degree, for one (OR: 1.21–1.25), two (OR: 1.10–1.95), three (OR: 1.23–2.29) and four or more (OR: 1.29–2.92) versus no nonpreventive visit. Predicted probability of completing “discussion of end-of-life planning,” for example, was larger with one preventive visit (without nonpreventive visit) (31.12%) than with 4+ nonpreventive primary care visits (without preventive visit) (21.95%). Conclusion: Seniors with preventive visits were more likely to complete recommended preventive services than those who make frequent nonpreventive visits. This was particularly prominent for Preventive Counseling services, which are time-consuming and thus difficult to be handled during routine nonpreventive visits. Annual preventive visit may be necessary for improved preventive care for senior

The Effects of Spousal Health on the Decision to Smoke: Evidence on Consumption Externalities, Altruism and Learning Within the Household

Married individuals are healthier than single individuals though the reasons are not well understood. Individuals with spouses/or partners are less likely to smoke. We explore the relationship between health and marital status by analyzing three potential channels through which marriage affects smoking, i.e., consumption externalities (one spouse's smoking affects the other spouse's welfare), altruism (one spouse reduces smoking in response to the other spouse's bad health), and learning about risks of smoking from the health experience of one's spouse. We find spousal health does not affect smoking due to altruism or learning within the household but do find evidence for consumption externalities. Copyright Springer Science + Business Media, Inc. 2006Smoking, Spousal interactions, Altruism, Learning, Consumption externalities,

Impact of Physician Practice Style on Costs, Clinical Quality, Patient Experience, Physician Productivity, and Physician Time

Background: During acute care visits, some primary care physicians (PCPs) typically focus on the presenting problem (“the focused”); others typically address additional issues (“max-packers”). Processes and outcomes may vary between these distinct practice styles. Max-packers, by managing additional conditions or preventive services during an acute care visit, may reduce the number of future visits and encourage up-to-date screening but may require more visit or charting time or increase testing and referrals. The focused, on the other hand, are expected to better manage patient flow. This study compares resource use (“costs”), clinical quality, patient experience, physician productivity and physician time for focused and max-packing PCPs. Methods: We used administrative electronic health record (EHR) data and Press-Ganey surveys of a large ambulatory group practice. Our study population included 302 PCPs in 2011–2013 (828 PCP-years). The outcome variables were costs (per-visit PCP evaluation and management [E&M], and per-episode and annual costs except for inpatient care), clinical quality metrics pertinent to primary care practice, patient experience (patient-reported satisfaction with the care provider and wait time), physician productivity (work RVUs and panel size), and physician EHR open time away from office. All outcome measures were risk-adjusted to account for patient mix in PCP panels. PCPs were classified into three tertiles based on the average number of “other conditions” (identified through diagnosis codes) addressed per acute care episode. We compared PCP-years in the top third (max-packer) and bottom third (the focused). Results: Max-packing was associated with higher per-visit E&M costs, higher total per-episode costs, but lower annual total costs. Compared to the focused, max-packers had higher scores for clinical quality and overall patient satisfaction, generated more work RVUs per clinical full-time equivalent, but had more EHR open time away from office and their patients had longer wait times in clinics. Conclusion: Physician typical practice styles impact multiple dimensions of care delivery. Organizations with potentially competing priorities (affordability, care quality, patient experience, productivity and efficiency) should consider organizational structures and physician incentives with balancing metrics and appropriate risk adjustments that encourage physician behavior achieving primary organizational goals