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BackgroundDespite guidelines recommending not to continue cancer screening for adults > 75 years old, especially those with short life expectancy, primary care providers (PCPs) feel ill-prepared to discuss stopping screening with older adults.ObjectiveTo develop scripts and strategies for PCPs to use to discuss stopping cancer screening with adults > 75.DesignQualitative study using semi-structured interview guides to conduct individual interviews with adults > 75 years old and focus groups and/or individual interviews with PCPs.ParticipantsForty-five PCPs and 30 patients > 75 years old participated from six community or academic Boston-area primary care practices.ApproachParticipants were asked their thoughts on discussions around stopping cancer screening and to provide feedback on scripts that were iteratively revised for PCPs to use when discussing stopping mammography and colorectal cancer (CRC) screening.ResultsTwenty-one (47%) of the 45 PCPs were community based. Nineteen (63%) of the 30 patients were female, and 13 (43%) were non-Hispanic white. PCPs reported using different approaches to discuss stopping cancer screening depending on the clinical scenario. PCPs noted it was easier to discuss stopping screening when the harms of screening clearly outweighed the benefits for a patient. In these cases, PCPs felt more comfortable being more directive. When the balance between the benefits and harms of screening was less clear, PCPs endorsed shared decision-making but found this approach more challenging because it was difficult to explain why to stop screening. While patients were generally enthusiastic about screening, they also reported not wanting to undergo tests of little value and said they would stop screening if their PCP recommended it. By the end of participant interviews, no further edits were recommended to the scripts.ConclusionsTo increase PCP comfort and capability to discuss stopping cancer screening with older adults, we developed scripts and strategies that PCPs may use for discussing stopping cancer screening.

Intensive management programs may improve health care experiences among high-risk and complex patients. We assessed patient experience among (1) prior enrollees (n = 59) of an intensive management program (2014-2018); (2) nonenrollees (n = 356) at program sites; and (3) nonprogram site patients (n = 728), using a patient survey based on the Consumer Assessment of Healthcare Providers and Systems in 2019. Outcomes included patient ratings of patient-centered care; overall health care experience; and satisfaction with their usual outpatient care provider. In multivariate models, enrollees were more satisfied with their current provider versus nonenrollees within program sites (adjusted odds ratio 2.36; 95% confidence interval 1.15-4.85). [ABSTRACT FROM AUTHOR]

Background: The extent that organizational learning and resilience for the change process, that is, adaptive reserve (AR), is a component of building practice capacity for continuous quality improvement (QI) is unknown. Purpose: The aim of the study was to examine the association of AR and development of QI capacity. Methodology: One hundred forty-two primary care practices were evaluated at baseline and 12months in a randomized trial to improve care quality. Practice AR was measured by staff survey along with a validated QI capacity assessment (QICA). We assessed the association of baseline QICA with baseline AR and both baseline and change in AR with change in QICA from 0 to 12 months. Effect modification by presence of QI infrastructure in parent organizations and trial arm was examined. Results: Mean QICA increased from 6.5 to 8.1 (p < .001), andmean ARincreased from 71.8 to 73.9 points (p < .001). At baseline, there was a significant association between AR and QICA scores: The QICA averaged 0.34 points higher (95% CI [0.04, 0.64], p = .03) per 10-point difference in AR. There was a significant association between baseline AR and 12-month QICA--which averaged 0.30 points higher (95% CI [0.02, 0.57], p = .04) per 10 points in baseline AR. There was no association between changes in AR and the QICA from 0 to 12 months and no effect modification by trial arm or external QI infrastructure. Conclusions: Baseline AR was positively associated with both baseline and follow-up QI capacity, but there was no association between change in AR and change in the QICA, suggesting AR may be a precondition to growth in QI capacity. Practice Implications: Findings suggest that developing AR may be a valuable step prior to undertaking QI-oriented growth, with implications for sequencing of development strategies, including added gain in QI capacity development from building AR prior to engaging in transformation efforts. [ABSTRACT FROM AUTHOR]

Background: Despite guidelines recommending not to continue cancer screening for adults > 75 years old, especially those with short life expectancy, primary care providers (PCPs) feel ill-prepared to discuss stopping screening with older adults. Objective: To develop scripts and strategies for PCPs to use to discuss stopping cancer screening with adults > 75. Design: Qualitative study using semi-structured interview guides to conduct individual interviews with adults > 75 years old and focus groups and/or individual interviews with PCPs. Participants: Forty-five PCPs and 30 patients > 75 years old participated from six community or academic Boston-area primary care practices. Approach: Participants were asked their thoughts on discussions around stopping cancer screening and to provide feedback on scripts that were iteratively revised for PCPs to use when discussing stopping mammography and colorectal cancer (CRC) screening. Results: Twenty-one (47%) of the 45 PCPs were community based. Nineteen (63%) of the 30 patients were female, and 13 (43%) were non-Hispanic white. PCPs reported using different approaches to discuss stopping cancer screening depending on the clinical scenario. PCPs noted it was easier to discuss stopping screening when the harms of screening clearly outweighed the benefits for a patient. In these cases, PCPs felt more comfortable being more directive. When the balance between the benefits and harms of screening was less clear, PCPs endorsed shared decision-making but found this approach more challenging because it was difficult to explain why to stop screening. While patients were generally enthusiastic about screening, they also reported not wanting to undergo tests of little value and said they would stop screening if their PCP recommended it. By the end of participant interviews, no further edits were recommended to the scripts. Conclusions: To increase PCP comfort and capability to discuss stopping cancer screening with older adults, we developed scripts and strategies that PCPs may use for discussing stopping cancer screening. [ABSTRACT FROM AUTHOR]

Objectives: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which veterans will be mostly reliant on VA services in the future. This study examined whether machine learning methods can better predict future reliance on VA primary care compared with traditional statistical methods., Study Design: Observational study of 83,143 VA patients dually enrolled in fee-for-service Medicare using VA and Medicare administrative databases and the 2012 Survey of Healthcare Experiences of Patients., Methods: The primary outcome was a dichotomous measure denoting whether patients obtained more than 50% of all primary care visits (VA + Medicare) from VA. We compared the performance of 6 candidate models-logistic regression, elastic net regression, decision trees, random forest, gradient boosting machine, and neural network-in predicting 2013 reliance as a function of 61 patient characteristics observed in 2012. We measured performance using the cross-validated area under the receiver operating characteristic (AUROC) metric., Results: Overall, 72.9% and 74.5% of veterans were mostly VA reliant in 2012 and 2013, respectively. All models had similar average AUROCs, ranging from 0.873 to 0.892. The best-performing model used gradient boosting machine, which exhibited modestly higher AUROC and similar variance compared with standard logistic regression., Conclusions: The modest gains in performance from the best-performing model, gradient boosting machine, are unlikely to outweigh inherent drawbacks, including computational complexity and limited interpretability compared with traditional logistic regression.

Background: Mobile health (m-health) utilizes widespread access to mobile phone technologies to expand health services. Community health workers (CHWs) provide first-level contact with health facilities; combining CHW efforts with m-health may be an avenue for improving primary care services. As part of a primary care improvement project, a pilot CHW program was developed using a mobile phone-based application for outreach, referral, and follow-up between the clinic and community in rural Zambia., Materials and Methods: The program was implemented at six primary care sites. Computers were installed at clinics for data entry, and data were transmitted to central servers. In the field, using a mobile phone to send data and receive follow-up requests, CHWs conducted household health surveillance visits, referred individuals to clinic, and followed up clinic patients., Results: From January to April 2011, 24 CHWs surveyed 6,197 households with 33,304 inhabitants. Of 15,539 clinic visits, 1,173 (8%) had a follow-up visit indicated and transmitted via a mobile phone to designated CHWs. CHWs performed one or more follow-ups on 74% (n=871) of active requests and obtained outcomes on 63% (n=741). From all community visits combined, CHWs referred 840 individuals to a clinic., Conclusions: CHWs completed all planned aspects of surveillance and outreach, demonstrating feasibility. Components of this pilot project may aid clinical care in rural settings and have potential for epidemiologic and health system applications. Thus, m-health has the potential to improve service outreach, guide activities, and facilitate data collection in Zambia.

Background: Although tenofovir (TDF) is a common component of antiretroviral therapy (ART), recent evidence suggests inferior outcomes when it is combined with nevirapine (NVP)., Methods: We compared outcomes among patients initiating TDF + emtricitabine or lamivudine (XTC) + NVP, TDF + XTC + efavirenz (EFV), zidovudine (ZDV) + lamuvidine (3TC) + NVP, and ZDV + 3TC + EFV. We categorized drug exposure by initial ART dispensation by a time-varying analysis that accounted for drug substitutions and by predominant exposure (>75% of drug dispensations) during an initial window period. Risks for death and program failure were estimated using Cox proportional hazard models. All regimens were compared with ZDV + 3TC + NVP., Results: Between July 2007 and November 2010, 18,866 treatment-naive adults initiated ART: 18.2% on ZDV + 3TC + NVP, 1.8% on ZDV + 3TC + EFV, 36.2% on TDF + XTC + NVP, and 43.8% on TDF + XTC + EFV. When exposure was categorized by initial prescription, patients on TDF + XTC + NVP [adjusted hazard ratio (AHR): 1.45; 95% confidence interval (CI): 1.03 to 2.06] had a higher post-90-day mortality. TDF + XTC + NVP was also associated with an elevated risk for mortality when exposure was categorized as time-varying (AHR: 1.51; 95% CI: 1.18 to 1.95) or by predominant exposure over the first 90 days (AHR: 1.91, 95% CI: 1.09 to 3.34). However, these findings were not consistently observed across sensitivity analyses or when program failure was used as a secondary outcome., Conclusion: TDF + XTC + NVP was associated with higher mortality when compared with ZDV + 3TC + NVP but not consistently across sensitivity analyses. These findings may be explained in part by inherent limitations to our retrospective approach, including residual confounding. Further research is urgently needed to compare the effectiveness of ART regimens in use in resource-constrained settings.