The San Francisco Community Vital Signs: using web-based tools to facilitate the mobilizing for action through planning and partnerships process.

A coalition of local public health system stakeholders in San Francisco developed a community assessment and strategic planning tool, the San Francisco Community Vital Signs (SFCVS). The SFCVS builds on the Mobilizing for Action through Planning and Partnerships (MAPP) model by incorporating Internet-based technology into local public health system evaluation and strengthening. This article describes the overlap between the SFCVS and MAPP processes, the manner in which information technology facilitated the SFCVS process, and a template for infusing a Web-based platform into the MAPP model. Internet-based applications helped to implement many (16 of 41; 39%) of the components of the SFCVS process. Of these 16 process measures, the majority (10; 63%) required the use of Web-based technology. The SFCVS demonstrates that a MAPP-like process can leverage the Internet to augment the functionality of public health activities.

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.

Prediction model to maximize impact of syphilis partner notification--San Francisco, 2004-2008.

BACKGROUND: Syphilis cases increased 55% in San Francisco from 2007 (n = 354) to 2008 (n = 548). The San Francisco Department of Public Health interviews syphilis patients to identify sex partners needing treatment, but interviewing resources are limited. We developed and validated a model to prioritize interviews likely to result in treated partners. METHODS: We included data from interviews conducted from July 2004 through June 2008. We used multivariate analysis to model the number of treated partners per interview in a random half of the data set. We applied the model to the other half, calculating predicted and observed proportions of partners successfully treated and interviews conducted if limiting interviews by syphilis patient characteristics. RESULTS: In 1340 patient interviews, 1665 partners were named; of those, 827 (49.7%) were treated. Ratios of treated partners were significantly higher among patients aged <50 years, compared with >or=50 years (ratio 1.4; 95% confidence interval [CI], 1.0-1.9); patients with primary/secondary syphilis, compared with early latent (ratio 1.4; 95% CI: 1.1-1.8); and patients diagnosed at the municipal sexually transmitted disease clinic, compared with elsewhere (ratio 1.7; 95% CI: 1.4-2.1). Limiting interviews to patients aged <50 years would reduce interviews by 14% and identify 92% of partners needing treatment. Limiting interviews to primary/secondary syphilis patients would reduce interviews by 35% and identify 68% of partners needing treatment. CONCLUSIONS: Our model can provide modest efficiencies in allocating resources for syphilis partner notification. Health departments should consider developing tools to maximize impact of syphilis prevention and control activities.

The effectiveness of patient-delivered partner therapy and chlamydial and gonococcal reinfection in San Francisco.

BACKGROUND: Patient-delivered partner therapy (PDPT) has been evaluated in randomized trials. No analysis has examined the impact of PDPT once implemented programmatically. METHODS: We examined the association between receiving PDPT and Chlamydia trachomatis and Neisseria gonorrhoeae reinfection within 1 year in patients diagnosed at San Francisco City Clinic between October 31, 2005 and March 31, 2008. Propensity score modeling was used to control for the difference between persons who did and did not receive PDPT. RESULTS: There was no significant difference between patients who received PDPT and those that did not in the crude cumulative risk for repeat infection with C. trachomatis or N. gonorrhoeae. Using propensity score analysis, the adjusted relative risk was 0.99 (0.86-1.14) for chlamydial reinfection and 0.90 (0.72-1.11) for gonococcal reinfection. Further analysis looking at men who have sex with men, men who have sex with women, and females showed no significant reductions in relative risk of reinfection for C. trachomatis or N. gonorrhoeae in these sub populations. CONCLUSIONS: Continued evaluation of PDPT on reinfection rates in real world settings as well as cost-effectiveness analyses of PDPT are needed to assess this alternative method of partner treatment.

Who should receive life support during a public health emergency? Using ethical principles to improve allocation decisions.

A public health emergency, such as an influenza pandemic, will lead to shortages of mechanical ventilators, critical care beds, and other potentially life-saving treatments. Difficult decisions about who will and will not receive these scarce resources will have to be made. Existing recommendations reflect a narrow utilitarian perspective, in which allocation decisions are based primarily on patients' chances of survival to hospital discharge. Certain patient groups, such as the elderly and those with functional impairment, are denied access to potentially life-saving treatments on the basis of additional allocation criteria. We analyze the ethical principles that could guide allocation and propose an allocation strategy that incorporates and balances multiple morally relevant considerations, including saving the most lives, maximizing the number of "life-years" saved, and prioritizing patients who have had the least chance to live through life's stages. We also argue that these principles are relevant to all patients and therefore should be applied to all patients, rather than selectively to the elderly, those with functional impairment, and those with certain chronic conditions. We discuss strategies to engage the public in setting the priorities that will guide allocation of scarce life-sustaining treatments during a public health emergency.

Impact of housing on the survival of persons with AIDS.

BACKGROUND: Homeless persons with HIV/AIDS have greater morbidity and mortality, more hospitalizations, less use of antiretroviral therapy, and worse medication adherence than HIV-infected persons who are stably housed. We examined the effect of homelessness on the mortality of persons with AIDS and measured the effect of supportive housing on AIDS survival. METHODS: The San Francisco AIDS registry was used to identify homeless and housed persons who were diagnosed with AIDS between 1996 and 2006. The registry was computer-matched with a housing database of homeless persons who received housing after their AIDS diagnosis. The Kaplan-Meier product limit method was used to compare survival between persons who were homeless at AIDS diagnosis and those who were housed. Proportional hazards models were used to estimate the independent effects of homelessness and supportive housing on survival after AIDS diagnosis. RESULTS: Of the 6,558 AIDS cases, 9.8% were homeless at diagnosis. Sixty-seven percent of the persons who were homeless survived five years compared with 81% of those who were housed (p < 0.0001). Homelessness increased the risk of death (adjusted relative hazard [RH] 1.20; 95% confidence limits [CL] 1.03, 1.41). Homeless persons with AIDS who obtained supportive housing had a lower risk of death than those who did not (adjusted RH 0.20; 95% CL 0.05, 0.81). CONCLUSION: Supportive housing ameliorates the negative effect of homelessness on survival with AIDS.

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.