Every 2 years, BPHC conducts a random-digit–dialed, citywide community health surveillance survey of 2,500 to 3,000 Boston residents — the Boston Behavioral Risk Factor Surveillance Survey (Boston BRFSS) (14,17). In 2001, BPHC added a question to assess whether a respondent lived in public housing, subsidized housing, or neither. Adding this question allowed BPHC to monitor the health of vulnerable public housing residents. Residents of public housing in Boston have a significantly higher prevalence of asthma than other city residents have (18). To address this and other health disparities, BPHC, the Boston Housing Authority, and other partners developed interventions to reduce exposure to pests, pesticides, and secondhand smoke among public housing residents. These interventions, and others, contributed to a decline in self-reported asthma symptoms among public housing residents (S.N.S, unpublished data, 2013).

A similar strategy was used by LACDPH to better characterize caregivers in Los Angeles County. In 2007, LACDPH expanded its random-digit–dialed, countywide Los Angeles County Health Survey (LACHS) of 8,000 households to include a series of questions on caregiving for the elderly and disabled (15,19,20). Data on the prevalence and costs of caregiving helped local agencies apply for grants and prioritize resources for their aging populations.

Even with limited funding, many states and local jurisdictions have the capacity to add additional variables to existing population surveys like the BRFSS.

Augment sample size. In 2009, BPHC was awarded grants from the Centers for Disease Control and Prevention (CDC) that included funding for administration of the BRFSS in 2010 and 2012 to a grant-specific sample of the Boston population (different from the sample of the Boston BRFSS described previously) consisting of 1,500 city residents (21). Leveraging this opportunity, BPHC used grant funds, which could have been used to support program activities, to expand the sample size to 2,000, a number that, based on a priori power analysis, would allow for more stable point estimates of neighborhood variables important for evaluating the impact of local interventions.

Combine data years. The number of completed Boston BRFSS surveys (2,500–3,000) is sufficient for monitoring general population health trends in Boston but lacks power to conduct subgroup analyses in smaller neighborhoods. To mitigate this shortcoming, BPHC generates neighborhood and subgroup estimates by combining survey data from several years. Combining data across years requires consistent survey methodology, survey instruments, and weighting procedures across time.

Generate small-area estimates. With multiple municipalities in Los Angeles County, program planning and resource-allocation decisions often require granular, geographically subdivided health data that are not readily available through existing sources. The LACHS provides relatively precise point estimates for many health indicators in larger regions but lacks the sample size and data for producing similarly precise estimates for cities or council districts. Recently, LACDPH applied small-area estimation to generate stratified estimates of obesity and smoking prevalence by city and city council district using data from the LACHS, the US Census, and the LA County Population Estimates and Projection System. Small-area estimation applies statistical procedures to generate a series of dependent variable projections based on regression modeling; the method uses multiple sources of information that provide data not available from a single source (22,23). Small-area estimation has several limitations: 1) the estimates are only as good as the model assumptions and the quality of data used; 2) in many instances, no amount of supplemental information can compensate for extremely small sample sizes; and 3) diagnostics for checking nonlinear models are generally not well developed for this method (23).

Enact regulatory mandate. In 2006, Boston’s Board of Health passed a data collection regulation that requires all acute-care hospitals and community health centers in Boston to collect data on race, ethnicity, preferred language, and educational attainment in a standardized format from patient self-report for all patient encounters. The regulation also requires that sociodemographic data for every inpatient, outpatient, and emergency department patient encounter be shared with BPHC. That same year, the Massachusetts Department of Public Health (MADPH) passed a similar statewide regulation. BPHC and MADPH aligned their standards so that institutions in Boston could collect data in a single format to satisfy both local and statewide regulations. Although the new regulations required high levels of technical assistance, training, and coordination among agencies, the newly consistent data will help agencies to understand where racial and ethnic subpopulations in Boston seek medical care.

Embed requirements in contracts. In Los Angeles County, data collection is often standardized through the subcontracting process. Wherever feasible, LACDPH embeds standardized data collection requirements in its subcontracts with funded partners. To gauge and identify program gaps in clinical preventive services in the ambulatory care setting, LACDPH includes requirements in subcontracts with clinical organizations, calling for participating clinic networks to collect and provide certain data on patient demographics and clinical indicators.

Collect primary health assessment data. To address health disparities in regions of Los Angeles County that have high rates of poverty and obesity, LACDPH conducted 2 health and nutrition examination surveys (LA HANES) during 2010–2012. These surveys recruited low-income adults who relied on multipurpose public health centers for preventive services, health education, and community programming. The first survey (n ~ 720; response rate, 74%) was conducted during the first 15 months of a regional, 2-year, CDC-funded obesity prevention initiative. The second survey (n ~ 1,500; response rate, 69%) was completed approximately 12 months later. The surveys collected data on self-reported sociodemographic characteristics, self-reported health behaviors, and measured height and weight, waist circumference, blood pressure, and urinary cotinine (28,29).

Preliminary data from LA HANES spurred several policy and program planning discussions, including how LACDPH might prepare for changes in the delivery of public health services as a result of ACA. That nearly half of all black and Hispanic/Latino residents had a blood pressure measurement in the prehypertensive or hypertensive range underscored the need for more tailored approaches to detect and treat this risk factor for cardiovascular disease in these subpopulations (29).

Collect primary program data. In 2011, BPHC cosponsored the launch of a new bicycle-share program in Boston with an aim to include residents from low-income neighborhoods as well as the city’s center, which is generally composed of high-income neighborhoods. BPHC leveraged its support to have 4 of the 61 initial stations strategically placed in low-income neighborhoods, and it distributed subsidized program memberships to hundreds of eligible low-income residents.

Registration for program membership was available online through the bicycle-share vendor website or via telephone if Internet was not accessible. To understand the characteristics of program members, BPHC asked the vendor to include a question about race and ethnicity on the online registration page. Although adding this one question necessitated reprogramming on the part of the vendor, the data collected by making this one addition documented the volume of subsidized memberships and demonstrated the increased program reach to black and Hispanic/Latino populations. Among program members who disclosed their racial and ethnic identity, the percentage that self-reported as black or Hispanic/Latino was nearly threefold higher among subsidized members than among nonsubsidized members.