A Narrative Review of Slow Medicine Outcomes.

BACKGROUND: Primary care practice in the United States suffers from short consultation duration and distracting electronic health record tasks. This leads to patient and physician dissatisfaction and physician burnout, as well as potentially unnecessary referrals and interventions. Slow medicine - providing longer and higher-quality consultations - has been proposed to improve medical care quality and patient outcomes. However, definitive outcome data for US settings are lacking. METHODS: Following a structured narrative approach, we identified, reviewed, and synthesized existing reports (peer-reviewed and grey) to determine if there is sufficient evidence to support systematic evaluation of slow medicine in the US. We assessed whether longer versus shorter face-to-face primary care consultations were associated with quantitative patient outcomes including utilization; prevention; visit elements; medication adherence and prescription volume; mortality; and costs. RESULTS: We found suggestive evidence of substantial savings in hospital use and costs in varied geographic and clinical settings. However, this evidence lacks investigative rigor such as convincing prospective or natural randomization. CONCLUSIONS: With potentially significant health and financial benefits from slow medicine and little risk to subjects, randomized trials, natural experiments, and mixed methods evaluations are strongly indicated. We discuss the need for modified payment practices to facilitate a slow medicine approach.

Multivariate Risk Adjustment of Primary Care Patient Panels in a Public Health Setting: A Comparison of Statistical Models.

We compared prospective risk adjustment models for adjusting patient panels at the San Francisco Department of Public Health. We used 4 statistical models (linear regression, two-part model, zero-inflated Poisson, and zero-inflated negative binomial) and 4 subsets of predictor variables (age/gender categories, chronic diagnoses, homelessness, and a loss to follow-up indicator) to predict primary care visit frequency. Predicted visit frequency was then used to calculate patient weights and adjusted panel sizes. The two-part model using all predictor variables performed best (R = 0.20). This model, designed specifically for safety net patients, may prove useful for panel adjustment in other public health settings.

Increasing Colorectal Cancer Screening at Community-Based Primary Care Clinics in San Francisco.

CONTEXT: Adult colorectal cancer screening (CRCS) can lower disease incidence and mortality. However, widespread implementation is inconsistent, especially in the public sector. While specific interventions to increase CRCS have been identified, firsthand accounts of CRCS improvement efforts using multiple techniques in public sector settings are lacking. OBJECTIVE: A program evaluation was conducted to assess the effect of implementing a culture of continuous quality improvement (QI) on CRCS practices and prevalence. A multipronged incremental effort over more than a decade to increase CRCS at the San Francisco Department of Public Health is described. SETTING: Community-based primary care clinics. PARTICIPANTS: Departmental activities and 5 clinics providing full-scope primary care to CRCS-eligible adults who participated in departmental activities and outreach interventions were assessed. MAIN OUTCOME MEASURES: Departmental and clinic-specific CRCS activities and prevalence. RESULTS: Efforts included departmental prioritization; data-driven QI incorporating routine data sharing (monthly reports and data walls); departmental and clinic-specific QI committees; panel management (a team approach to generation of eligibility lists prior to scheduled visits, routinely offering screening during appointments or mailing test kits for patients without appointments); and departmental mail and phone outreach events. Screening ranged from 36.6% to 54.4% in 2010; in 2013, it ranged from 43.6% to 70.2%. Increases occurred consistently over that time in 3 of the 5 clinics and ranged from 1.1% to 14.5%; decreases occurred during 2 intervals in 2 clinics and ranged from 2.3% to 4.3%. CONCLUSION: CRCS prevalence can be markedly improved in the public sector with a data-driven panel management approach supported by departmental and clinic-specific QI committees and group outreach events. Continued prioritization of and focus on CRCS is required to ensure long-term success. Even small increases will result in avoidable morbidity and mortality associated with this highly preventable disease.

Assessing and increasing patient panel size in the public sector.

CONTEXT: Panel management is a central component of the primary care medical home, but faces numerous challenges in the safety net setting. In the San Francisco Department of Public Health, many of our community-based primary care clinics have difficulty accommodating all patients seeking care. OBJECTIVE: We evaluated patient panel size in our 7 clinics providing cradle-to-grave primary care services to more than 25,000 active patients. DESIGN: We adjusted panel size for age, gender, diagnoses, homelessness, and substance abuse; set related policies; and assessed the effects on our clinics. On the basis of our previous data and targets set by other safety net providers, we established a minimum of 1125 patients per full-time paid primary care provider (ie, full-time equivalent [FTE]) in April 2009. We calculated the target panel size each clinic would have if all their providers reached the minimum panel size goal and compared it with the panel size attained by the clinic. RESULTS: Nine months after establishing panel size policy, providers reached 82% of the aggregate target panel size. Five of the 7 clinics increased their adjusted panel size per FTE in the range of 2% to 23%. Two data-oriented and innovative clinics with some of the highest adjusted panel sizes per FTE largely maintained their panel size. Two clinics that had the lowest adjusted panel size per FTE realized a 23% and 8% respective gain; both clinics reduced barriers to new patient appointments. Two clinics acquired new providers and experienced a concomitant drop in panel size per FTE while the new clinicians expanded their panels. One of these clinics had difficulty managing high no-show rates and creating effective appointment templates. CONCLUSIONS: Routine data generation, review of data with administrators and providers, data-driven policies and panel size standards, and interventions to bolster team-based care are important tools for increasing capacity at our primary care clinics.

Creating a medical home in the San Francisco department of public health: establishing patient panels.

Patients with a medical home tend to fare better. One of the first steps toward establishing a medical home is to create panels by designating a clinic responsible for each patient. In 2006, we defined active clinic panels (all patients assigned to a clinic and seen there for one or more outpatient medical visits during the past 2 years) for the San Francisco Department of Public Health's 13 community- and four public hospital-based primary care clinics and began automatically assigning previously unassigned patients to clinics based on utilization. In 2007, we created a Web-based user interface for managing panels from within the electronic medical record. Providers and medical directors can now view and verify their panels and link to patient demographic and utilization data. Through April 2008, 14 508 patients have been auto-assigned to a clinic; on average 320 patients were assigned monthly. A total of 82,637 primary care patients were on a clinic panel, and 73.6 percent of them were active. Patient demographics, panel size, and productivity vary considerably by clinic. By establishing active panels and providing Web-based access to panel data, we can systematically assign patients a clinical home; enable providers to manage their panels; accurately measure utilization, capacity, and productivity; assess patient characteristics; and generate clinical quality indicators based on an accurate denominator. These management tools will allow us to set policies and work toward our goal of establishing a medical home for San Franciscans who rely on publicly funded care.

Highly active antiretroviral therapy use and HIV transmission risk behaviors among individuals who are HIV infected and were recently released from jail.

We evaluated highly active anti-retroviral therapy (HAART) use and risk behaviors among 177 inmates who were HIV infected and were released and reincarcerated in San Francisco, Calif, jails over a 12-month period. During the month preceding reincarceration, HIV transmission risk behaviors were common among respondents, and 59% of those with a history of antiretroviral use were not taking HAART. HAART discontinuation was independently associated with homelessness, marijuana use, injection drug use, and not receiving community medical care. Postrelease interventions for inmates who are HIV infected are needed.

Attempted suicide among transgender persons: The influence of gender-based discrimination and victimization.

To determine the independent predictors of attempted suicide among transgender persons we interviewed 392 male-to-female (MTF) and 123 female-to-male (FTM) individuals. Participants were recruited through targeted sampling, respondent-driven sampling, and agency referrals in San Francisco. The prevalence of attempted suicide was 32% (95% CI = 28% to 36%). In multivariate logistic regression analysis younger age (<25 years), depression, a history of substance abuse treatment, a history of forced sex, gender-based discrimination, and gender-based victimization were independently associated with attempted suicide. Suicide prevention interventions for transgender persons are urgently needed, particularly for young people. Medical, mental health, and social service providers should address depression, substance abuse, and forced sex in an attempt to reduce suicidal behaviors among transgender persons. In addition, increasing societal acceptance of the transgender community and decreasing gender-based prejudice may help prevent suicide in this highly stigmatized population.