Journal of the American Board of Family Medicine最新文献

When the goal is to help patients improve their quality of life, it makes sense to focus directly on the activities and relationships that are most important to each patient. This can be accomplished most effectively by following a three-step process that includes 1) connecting with the patient around what matters to them, 2) co-creating a goal-oriented plan, and 3) collaborating with patient, family, team members, and consultants to increase the probability of success. Once this approach has been mastered and the necessary systems, processes, and relationships are in place, this should not take more time than a problem-oriented approach, and it will almost certainly be more satisfying for both physician and patient. The impact on population-based quality metrics is uncertain. Though fewer patients may choose to follow standard recommendations, those who do may be more likely to adhere to them.

Background: Access to dermatologists is limited in parts of the US, making primary care clinicians (PCCs) integral for early detection of skin cancers. A handheld device using elastic scattering spectroscopy (ESS) was developed to aid PCCs in their clinical assessment of skin lesions.

Methods: In this prospective study, 3 PCCs evaluated skin lesions reported by patients as concerning and scanned each lesion with the handheld ESS device. The comparison was pathology results or a 3-dermatologist panel examining high resolution dermatoscopic and clinical images. PCCs reported their diagnosis, management decision, and confidence level for each lesion. Evaluation of results included sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and Area Under the Curve (AUC).

Results: A total of 155 patients and 178 lesions were included in the final analysis. The most commonly patient-reported concerning feature was "new or changing lesion" (91.6%). Device diagnostic sensitivity and specificity were 90.0% and 60.7%, respectively, based on biopsy result or dermatologist panel reference standard; comparatively, PCC sensitivity was 40.0% and 84.8% specificity without the use of the device. Device NPV was 98.9%, and device PPV was 13.6%. The device recommended patient referral to dermatology with 88.2% concordance with the dermatologist panel. AUC for the device and PCCs were 0.815 and 0.643, respectively.

Conclusions: The use of the ESS device by PCCs can improve diagnostic and management sensitivity for select malignant skin lesions by correctly classifying most benign lesions of patient concern. This may increase skin cancer detection while improving access to specialist care.

Introduction: Many patients offered case management services to address their health and social needs choose not to engage. Factors that drive engagement remain unclear. We sought to understand patient characteristics associated with engagement in a social needs case management program and variability by case manager.

Methods: Between August 2017 and February 2021, 43,347 Medicaid beneficiaries with an elevated risk of hospital or emergency department use were offered case management in Contra Costa County, California. Results were analyzed in 2022 using descriptive statistics and multilevel logistic regression models to examine 1) associations between patient engagement and patient characteristics and 2) variation in engagement attributable to case managers. Engagement was defined as responding to case manager outreach and documentation of at least 1 topic to mutually address. A sensitivity analysis was performed by stratifying the pre-COVID-19 and COVID-19 cohorts.

Results: A total of 16,811 (39%) of eligible patients engaged. Adjusted analyses indicate associations between higher patient engagement and female gender, age 40 and over, Black/African American race, Hispanic/Latino ethnicity, history of homelessness, and a medical history of certain chronic conditions and depressive disorder. The intraclass correlation coefficient indicates that 6% of the variation in engagement was explained at the case manager level.

Conclusions: Medicaid patients with a history of housing instability and specific medical conditions were more likely to enroll in case management services, consistent with prior evidence that patients with greater need are more receptive to assistance. Case managers accounted for a small percentage of variation in patient engagement.

Purpose: Direct primary care (DPC) critics are concerned that the periodic fee precludes participation from vulnerable populations. The purpose is to describe the demographics and appointments of a, now closed, academic DPC clinic and determine whether there are differences in vulnerability between census tracts with and without any clinic patients.

Methods: We linked geocoded data from the DPC's electronic health record with the social vulnerability index (SVI). To characterize users, we described their age, sex, language, membership, diagnoses, and appointments. Descriptive statistics included frequencies, proportions or medians, and interquartile ranges. To determine differences in SVI, we calculated a localized SVI percentile within Harris County. A t test assuming equal variances and Mann-Whitney U Tests were used to assess differences in SVI and all other census variables, respectively, between those tracts with and without any clinic patients.

Results: We included 322 patients and 772 appointments. Patients were seen an average of 2.4 times and were predominantly female (58.4%). More than a third (37.3%) spoke Spanish. There was a mean of 3.68 ICD-10 codes per patient. Census tracts in which DPC patients lived had significantly higher SVI scores (ie, more vulnerable) than tracts where no DPC clinic patients resided (median, 0.60 vs 0.47, p-value < 0.05).

Conclusion: This academic DPC clinic cared for individuals living in vulnerable census tracts relative to those tracts without any clinic patients. The clinic, unfortunately, closed due to multiple obstacles. Nevertheless, this finding counters the perception that DPC clinics primarily draw from affluent neighborhoods.

Heart failure with reduced ejection fraction (HFrEF) is a commonly seen clinical entity in the family physician's practice. This clinical review focuses on the pharmacologic management of chronic HFrEF. Special attention is paid to the classification of heart failure and the newest recommendations from the American Heart Association concerning the use of guideline-directed medical therapy. β blockers, ACE inhibitors, ARBs, mineralocorticoid receptor antagonists are discussed in detail. The new emphasis on sacubitril-valsartan and SGLT2i's as therapies for HFrEF are reviewed, followed by a brief discussion of more advanced therapies and comorbidity management.

Background: The NASEM Primary Care Report and Primary Care scorecard highlighted the importance of primary care physician (PCP) capacity and having a usual source of care (USC). However, research has found that PCP capacity and USC do not always correlate. This exploratory study compares geographic patterns and the characteristics of counties with similar rates of PCP capacity but varying rates of USC.

Methods: Our county-level, cross-sectional approach includes estimates from the Robert Graham Center and data from the Robert Wood Johnson County Health Rankings (CHR). We utilized conditional mapping methods to first identify US counties with the highest rates of social deprivation (SDI). Next, counties were stratified based on primary care physician (PCP) capacity and usual source of care (USC) terciles, allowing us to identify 4 types of counties: (1) High-Low (high PCP capacity, low USC); (2) High-High (high PCP capacity, high USC); (3) Low-High (low PCP capacity, high USC); and (4) Low-Low (low PCP capacity, low USC). We use t test to explore differences in the characteristics of counties with similar rates of primary care capacity.

Results: The results show clear geographic patterns: High-High counties are located primarily in the northern and northeastern US; High-Low counties are located primarily in the southwestern and southern US. Low-High counties are concentrated in the Appalachian and Great Lakes regions; Low-Low counties are concentrated in the southeastern US and Texas. Descriptive results reveal that rates of racial and ethnic minorities, the uninsured, and social deprivation are highest in counties with low rates of USC for both high PCP and low PCP areas.

Conclusions: Recognizing PCP shortages and improving rates of USC are key strategies for increasing access to high-quality, primary care. Targeting strategies by geographic region will allow for tailored models to improve access to and continuity of primary care. For example, we found that many of the counties with the lowest rates of USC are found in non-Medicaid expansion states (Texas, Georgia, and Florida) with high rates of uninsured populations, suggesting that expanding Medicaid and improving access to health insurance are key strategies for increasing USC in these states.

The average panel for family physicians dropped from about 2400 to about 1800 patients from 2013 to 2022. Likely reasons for this decline: 1) fewer people seeking primary care, and 2) fewer people receiving their care through a long-term continuity relationship with a primary care clinician.

Quite a lineup showcasing JABFM's emphasis on research and information for family medicine to improve patients' lives. Articles cover many topics: telemedicine, a clinical decision support tool, control of cardiovascular risk factors, opioid dose reduction, cancer survivorship care, patient engagement with case management/navigation, primary care physician capacity and usual source of care, marketing practices of Medicare Advantage programs, review articles (new diabetes medicine and treatment CHF with reduced ejection fraction), and more.