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Appendix C Financing Mission-Critical Investments in Public Health Capacity Development Eileen Salinsky, MBA INTRODUCTION The Institute of Medicine (IOM) committee on Public Health Strate- gies to Improve Health is charged with examining ways to strengthen the public health system in three separate but related areas: measurement, the law, and funding. The committee commissioned this paper to inform its deliberations regarding optimal mechanisms for financing the governmental public health infrastructure in a manner that will best support the needs of the public during and after health care reform. Based on guidance from the committee, this paper seeks to • i dentify and describe priority investments in public health capacity that promise to strengthen the ability of state and local public health agencies to adopt an ecologically oriented, population-based ap- proach to disease prevention and health promotion that addresses the broad socioenvironmental determinants of health; • e xplore the extent to which categorical financing mechanisms have influenced the capacity deficits observed in these mission-critical areas; and • e xamine the funding sources that have been successfully used by in- novative public health agencies at the state and local level to finance these capacity-development priorities. 153

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154 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE DEFINITIONS AND METHODS For the purposes of this effort, the term capacity conveys a deliberately broad and flexible concept—the various attributes that enable the gov- ernmental public health infrastructure to pursue its mission of promoting physical and mental health and preventing disease, injury, and disability. As described in the committee’s first report, For the Public’s Health: The Role of Measurement in Action and Accountability, the governmental public health infrastructure comprises public health agencies at local, state, and federal levels and represents a relatively small—yet integral—component of the overall health system (see Figure C-1). This infrastructure is composed of three major components: (1) the public health workforce, (2) data and information systems, and (3) organizational capabilities to assess and re- spond to public health needs (Baker et al., 2005). Capacities lie at the heart of the logic model the committee has devel- oped to illustrate the series of steps linking inputs to outcomes in popula- tion health and represent the critical link between resources and processes (see Figure C-2). As such, the term capacity may be used to signify system attributes necessary to successfully implement particular actions in order to achieve particular goals (optimal capacity), or the term may be used to describe the manner in which resources are actually deployed and aligned (existing capacity). This paper focuses specifically on capacity within gov- ernmental public health agencies at the state and local level, while recogniz- Clinical- care Community delivery system Government Governmental Employers agencies Public Health (other than and business Infrastructure public health) Education The media sector FIGURE C-1 The health system. SOURCE: IOM, 2011. Figure C-1

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155 APPENDIX C In the context of the social and environmental determinants of health Processes, Processes/ Needs Intermediate Health Planning and interventions, interventions/ Resources Capacities assessment outcomes outcomes priority setting policies Across different geographic levels and including public health agencies and stakeholders, and with attention to equity and disparities among population groups FIGURE C-2 Logic model. SOURCE: IOM, 2011. Figure 3-1 from old pub, with modifications ing the broader systemic context in which these public-sector organizations operate. In light of the interstitial role played by governmental public health, the specific capacities needed for optimal performance of public-sector agencies are somewhat contingent on the nature and contributions of other health system partners, as well as population health needs. The term capacity-development needs or capacity deficits represent those attributes of optimal capacity determined to be inadequate in, or missing from, the existing capacity. The evidence base surrounding both the definition of optimal public health capacity and documentation of existing capacity levels is extremely limited (Beitsch et al., 2006; Bhandari et al., 2010; Erwin, 2008; Mays et al., 2009; Scutchfield et al., 2004, 2009). Therefore capacity-development needs are most commonly identified through subjective assessments by public health practitioners and other ex- perts. These needs are often characterized by insufficient resources (human, technological, or financial); inadequate capabilities, tools, or methods; or deficits in the scale, scope, or intensity of the activities through which these inputs are applied. The content of this paper is based on telephone interviews with mem- bers of a committee workgroup1 and other public health leaders,2 as well as an extensive literature review. Findings based purely on the views of the public health leaders interviewed are clearly identified as expert opinion or perceptions. Respondents were selected based on their broad expertise in public health agency capacity, performance, and financing, as well as their experiences implementing innovative practices. Many interview respondents were directly identified by workgroup members, and additional respondents were identified during initial interviews with these public health leaders. 1Leslie Beitsch, David Fleming, Glen Mays, David Ross, and Steven Teutsch. 2A complete list of interview respondents can be found following the reference list.

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156 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE Limitations in the scale and scope of this effort prevented a more inclusive sample of respondents; therefore, respondents selected were not intended to be representative of public health officials nationally. However, efforts were made to ensure geographic diversity and a mix of perspectives across local and state agencies. Interviews were conducted by either the au- thor or Alina Baciu (IOM Study Director) using a semistructured protocol, and each averaged approximately 1 hour in duration. Background materials (e.g., information on respondent’s organization, published research) were reviewed prior to the interviews in order to customize questions and prepare tailored probes. Preparatory interviews with workgroup members identified a draft set of mission-critical capacity-development priorities that were shared with other interview respondents in order to stimulate discussion. Respondents were asked to (1) comment on and suggest revisions to the capacity-devel- opment priorities identified in the discussion draft, (2) describe the effect of categorical funding on capacity development in these areas, (3) identify financing strategies that have been used successfully to build these capacities, and (4) share insights on alternative financing strategies that could be used to support these capacities in the future. Respondents were not asked to rank or prioritize among the capacity-development needs identified, but to the extent that particular issues were consistently highlighted or emphasized, these concerns are noted in the following narrative. Results from the interviews and literature review were synthesized to develop the findings summarized in the remainder of this paper. These find- ings are organized in three main areas • C apacity-Development Priorities, • I mpact of Categorical Funding on Gaps in Mission-Critical Capaci- ties, and • S trategies for Financing Mission-Critical Capacities. CAPACITY-DEVELOPMENT PRIORITIES Addressing public health capacity-development needs has the potential to catalyze and accelerate broader reform in the health system. Because the governmental public health infrastructure serves as the nexus of the entire health system, deficits in the mission-critical capacities of state and local agencies are likely to have a rate-limiting effect on systemwide effective- ness and efficiency. Conversely, strengthening these capacities can create a pace-setting effect for overall improvements in health system performance. The following identifies capacity-development priorities for state and local public health agencies based on the expert opinion of committee

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157 APPENDIX C members and input from other leaders in public health, as well as support- ing evidence drawn from a review of the literature. These priorities are not intended to represent an exhaustive compilation of all capacity gaps within the field of public health. Rather, this summary is meant to highlight a mission-critical subset of public health capacities that appear to be (1) necessary for mounting an effective response to the broad determinants of health, (2) underdeveloped in many, if not most, state and local health agencies, and (3) difficult to develop adequately given the current level and structure of public health funding. The capacity-development priorities described below are informed by and grounded in the • C ore functions and 10 essential services of public health, • perational Definition of a Local Health Department developed O by the National Association of County and City Health Officials (NACCHO), • S tate and local public health practice standards established by the Public Health Accreditation Board (PHAB), • C ore competencies for public health professionals established by the Council on Linkages between Academia and Public Health Practice, and • riority Areas for Improvement of Quality in Public Health identi- P fied by the U.S. Department of Health and Human Services. These references broadly define the general functions, services, capacities, competencies, and quality improvements needed to support public health practice (Council on Linkages, 2010; Honoré and Scott, 2010; NACCHO, 2005; PHAB, 2009; Public Health Functions Steering Committee, 1995). In contrast to these inclusive frameworks, the capacity-development priorities identified here are intended to emphasize specific high-yield op- portunities for strategic investments in public health capacity. In essence, the priorities described in this paper highlight those aspects of the governmental public health infrastructure believed to be particularly nascent, fragile, or efficacious. Mission-critical capacity-development needs appear pronounced in five general areas or domains • S urveillance and epidemiology, • C ommunity health improvement planning, • P artnership development, • P olicy decision support, and • P ublic communications.

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158 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE In general, interview respondents expressed a high degree of consensus regarding these capacity-development priorities. However, individual re- spondents often focused their remarks on specific aspects of these investment opportunities depending on the respondent’s unique experiences and areas of expertise. The few issues characterized by explicitly divergent viewpoints are noted in the following narrative. Surveillance and Epidemiology Surveillance and epidemiology are the foundation of public health practice, and deficits in this capacity domain can fundamentally undermine the effectiveness of governmental public health agencies. The type and mag- nitude of these capacity deficits appear to vary among states and localities depending on the specific public health surveillance systems, analytic tools, and epidemiologic workforce deployed in each jurisdiction (CSTE, 2009b). Despite these variations, the public health leaders interviewed for this paper strongly concurred that capacity-development needs related to surveillance and epidemiology are widespread and represent significant opportunities for improving performance at both the state and local level. As described more fully in For the Public’s Health: The Role of Mea- surement in Action and Accountability (IOM, 2011), existing public health information systems and related analytic activities do not adequately sup- port decision makers confronting important choices regarding the health of their communities. Although public health agencies at all levels of govern- ment engage in a broad variety of valuable activities to collect, analyze, and disseminate health information, these efforts often have limited relevance for decision makers seeking to intervene at the community level owing to critical deficiencies in the accuracy, breadth, and timeliness of information (Livingood et al., 2010; Luck et al., 2006). Respondents believed that additional investments are critically needed to enhance governmental public health’s capacity to perform the following • C onduct timely, community-level surveillance on disability, injury, behavioral health risks, and chronic diseases (including mental and oral health). • M onitor the accessibility and quality of health care services. • M easure important community characteristics, such as environ- mental health risks (e.g., infectious disease vectors, air and water quality) and other contextual factors that contribute to population health outcomes (e.g., community walkability, liquor store outlet density, and access to healthy foods).

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159 APPENDIX C These perceived gaps in surveillance and epidemiology capacity reflect limi- tations that have been widely documented in the peer-reviewed and grey literature (Ali et al., 2007; ASPHL, 2007; CDC, 2006, 2010; CSTE, 2009b; Malvitz et al., 2009; Mokdad, 2009). Taken collectively, research findings and respondent perceptions yield generally consistent conclusions regarding the need for additional invest- ments in surveillance and epidemiology capacity to address the deficits identified. Specific capacity-development needs vary somewhat depending on surveillance topic and jurisdiction. In general, investment opportunities include improvements to existing surveillance systems, the design and imple- mentation of innovative surveillance methods, and workforce development. Improved Relevance and Timeliness of Existing Surveillance Systems With the exceptions of reportable disease surveillance for specific com- municable diseases and disease registries for a limited number of conditions, public health surveillance is heavily reliant on either sample-based popula- tion surveys (e.g., Behavioral Risk Factor Surveillance System [BRFSS]) or administrative databases (e.g., vital statistics, hospital discharge data) that are not primarily designed for surveillance purposes (Love et al., 2008; Mokdad, 2009). Survey data are typically not valid at the community level and usually cannot be used to monitor racial and ethnic disparities or geographic variation within communities. Administrative data often lack relevant content and may be extremely dated. In both cases, the usefulness of these surveillance data sources could be improved through modifications in data variables, improved adherence to coding conventions, and enhanced data collection methods. Some states and communities have invested in enhancements to existing population health surveys and conducted community-specific survey ef- forts in order to develop valid, timely community-level estimates for a wide range of noncommunicable conditions and risk factors. These investments have included additions to survey instruments and increased sample sizes for BRFSS or other population health surveys (Drewnowski et al., 2007; Livingood et al., 2010). Others have proposed the use of improved small- area estimation techniques to develop community-level data (Congdon, 2009, 2010; Zhang et al., 2011). Addressing deficiencies within administrative datasets raises somewhat different challenges. A wide variety of data sources administered by state health agencies (e.g., claims data for public health insurance programs, hospital discharge databases, emergency department data, vital statistics, and disease and immunization registries) can be used to monitor rates of disease, injury, and health care utilization. However, access to these datasets

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160 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE for public health surveillance purposes is often hindered by organizational and financial barriers. When these datasets can be accessed, data are often at least 1 to 2 years out of date upon release (Friedman, 2007). In a survey of state chronic disease epidemiologists conducted by the Council of State and Territorial Epidemiologists (CSTE), a substantial num- ber of respondents reported problems in gaining access to Medicare and Medicaid claims data (97 percent and 82 percent of states, respectively), state emergency department data (56 percent of states), hospital discharge data (59 percent of states), and state mortality data (63 percent of states). For those state chronic disease epidemiologists able to gain access to these health datasets, problems regarding data timeliness were frequently report- ed. Timely access to mortality data from state vital statistics systems appears particularly problematic (CSTE, 2009a). Interview respondents noted that local health officials face similar (and perhaps more daunting) challenges in accessing health datasets maintained by state health agencies. Anecdotal accounts suggest that sources of nonhealth data that could be used to monitor environmental risks and other community characteristics related to health (e.g., traffic accident reports, liquor store license records) may be even more inaccessible than traditional health datasets. Whereas most health data are in electronic formats, data from other potentially relevant sources may not be digitized or stored in a manner that facilitates analysis. Also, state and local health officials are generally less familiar with these potential datasets and may not be experienced in the procedures needed to obtain and analyze this information. Additional training may be needed to help public health officials identify and access these potential sources of environmental and contextual surveillance data. Streamlined data reporting, processing, and release protocols, as well as improved intergovernmental coordination, could reduce the time lags and access barriers observed in the use of administrative datasets for surveillance purposes. Wider adoption of data standards and coding conventions (such as geocoding data with spatial references, accurate and complete inclusion of external cause of injury codes) could further enhance the analytic applica- tions of administrative data at the community level and facilitate linkages across datasets (CSTE, 2009b,c; Grigg et al., 2006; Krieger et al., 2002; Miner et al., 2005; Miranda et al., 2005). Accelerated Development of Interoperable Public Health Information Systems Public health surveillance is highly dependent on information reported by the clinical care delivery system. Yet public health surveillance systems have not adequately adapted to technological advances in the way that clinical health information is collected, processed, and stored (Public Health

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161 APPENDIX C Data Standards Consortium, 2007). Progress has been made in public health informatics, such as increased electronic reporting of communicable diseases and improved integration of child health data (CSTE, 2009b; Fehrenbach et al., 2004; Overhage et al., 2008; Public Health Informatics Institute, 2003). However, many public health information systems con- tinue to rely on antiqued, “stove-piped” mechanisms to both collect data from health care providers and to store data for analytic use (Public Health Data Standards Consortium, 2007; Staes et al., 2009). For example, CSTE reports that 47 percent of states have not yet implemented fully automated electronic laboratory reporting for reportable infectious diseases, and 59 percent have not developed web-based reporting for physicians and other providers (CSTE, 2009b). Broader dissemination of electronic health records (EHR) and signifi- cant investments in health information technology by hospitals and other health care facilities offer promising opportunities to strengthen public health surveillance (Birkhead, 2010; Cossman et al., 2008; Klompas and Yokoe, 2009; Lazarus et al., 2009; Magruder et al., 2004). Meaningful use criteria established by the EHR Incentive program sponsored by the Centers for Medicare and Medicaid Services (CMS) create additional incentives for the electronic exchange of public health information (Blavin and Ormond, 2011). However, state and local public health agencies have struggled to adapt public health surveillance systems to leverage these advances in health information technology and do not appear to have the capacity necessary to shape the development of EHRs in clinical settings to optimize their po- tential for surveillance purposes. Capacity developments needed to accelerate the design and implementa- tion of innovative public health surveillance methods include augmenting the number and skills of public health workers with specialized expertise in health informatics; investing in the design and implementation of new, interoperable public health information systems; and expanding the use of mobile communication technologies to facilitate electronic data capture and transfer (Kukafka et al., 2007; Magruder et al., 2005; Turner et al., 2008; Yasnoff et al., 2001). Several interview respondents indicated that the finan- cial cost of these capacity improvements has hindered development in this area. Information systems development represents a significant investment with costs associated with design, capital acquisition, training, and lost productivity during transition from the legacy system. Similarly, the labor market for skilled informatics personnel is highly competitive, resulting in salary levels that cannot typically be offered in public health agencies. Interview respondents noted, however, that both organizational and fi- nancial barriers block the development of more rational, sophisticated pub- lic health information systems. The business case for informatics develop- ments may be difficult to justify given that the benefits of these investments

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162 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE are likely to accrue to organizational units that are not directly responsible for maintaining surveillance systems and are unlikely to bear the costs of upgrades. Several respondents also raised concerns that the policies and procedures imposed by centralized agencies within state government respon- sible for overseeing information systems often slow or prevent innovation by public health agencies. Absent a dedicated source of funding to catalyze public health information systems development, these organizational barri- ers can be difficult to overcome. Increased Number and Competencies of Epidemiologists Workforce deficiencies related to epidemiology capacity compound the surveillance-related capacity-development needs described above. CSTE estimates that approximately 1,500 additional epidemiologists are needed nationwide for optimal surveillance and epidemiology capacity in all pro- gram areas at the state level (CSTE, 2009b). In addition to the need for more staff dedicated to epidemiological analyses, CSTE cites the need for more extensive training of epidemiology personnel,3 expanded consultative support for epidemiology at the state level to meet local needs, increased use of analytic tools (such as cluster detection software and geographic information systems), and better coordination of epidemiology resources across program areas. Categorical funding appears to encourage a distributed model for epidemiology capacity wherein states embed epidemiology capacity within discrete programs, rather than developing a centralized epidemiology unit to serve as a cross-cutting resource. Program-based epidemiology personnel often dedicate only a portion of their time to epidemiology activities and typically have limited epidemiological training and expertise. This type of distributed model may deter integrated analyses and can hinder the devel- opment of more sophisticated epidemiology capacity if robust coordinating mechanisms are not implemented (CSTE, 2009b; Duffy and Siegel, 2009). Although similar epidemiology workforce requirements are not avail- able for local health agencies, NACCHO reports that a minority of local health departments engages in surveillance and epidemiology activities for noninfectious diseases. Agencies serving populations under 100,000 rarely employ professionals occupationally classified as epidemiologists (NACCHO, 2009).4 3Respondents noted that substantial on-the-job training is often needed for new staff (even those with academic training in epidemiology) owing to inadequate experience in descriptive epidemiology, practical surveillance, and investigation techniques. 4Staff classified as epidemiologists may not have graduate level training in epidemiology.

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163 APPENDIX C COMMUNITY HEALTH IMPROVEMENT PLANNING For surveillance and epidemiology capacity to have a meaningful ef- fect on population health outcomes, the information gleaned through these activities must be interpreted and translated into actionable interven- tions. Historically this decision making and response has occurred within programmatic silos and has sometimes resulted in a failure to intervene, duplication of efforts across programs, or a suboptimal alignment of public health resources relative to community need. Comprehensive community health improvement planning is widely viewed as a more effective approach to the assessment of health needs across a broad range of outcomes and detriments and the allocation of resources to address these needs. Community health improvement planning has been conceptualized and implemented in a variety of ways. Typically these strategic planning activities include at least three distinct phases: the completion of a com- munity health assessment,5 the identification of health priorities, and the development of an action plan to respond to priorities identified (Jacobs and Elligers, 2009). The evidence base regarding the optimal nature and scale of investments in each of these phases is underdeveloped (Friedman and Parrish, 2009; Myers and Stoto, 2006). However, the need for some level of capacity in community health assessment and related health improvement planning is widely recognized. Because these activities are often viewed as fundamental elements of public health practice, PHAB will not consider a health agency for national accreditation if the organization has not devel- oped a community health assessment, a community health improvement plan, and an agency strategic plan. The public health leaders interviewed for this paper believe that additional capacity development is needed to ensure that community health improve- ment planning efforts are effective in improving community health outcomes. Deficits were observed in all three stages of community health improvement planning identified above, with development needs cited related to public health agencies’ capacity to • c onduct comprehensive community health assessments (CHAs), • f acilitate participatory priority setting involving multiple stakehold- ers, and • i dentify cost-effective, community-based interventions to prevent disease, injury, and disability. These perceived gaps in capacity for community health improvement 5While a variety of formal definitions have been developed, the term community health as- sessment typically refers to a systemic effort to collect, analyze, and disseminate information on the health of a community (Friedman, 2010; Myers and Stoto, 2006).

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194 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE existing categorical programs were necessary to minimize the ob- stacles hindering the development of cross-cutting capacity. While most focused on reducing or eliminating categorical restrictions, others emphasized the need for explicit guidance encouraging the coordination of resources across programs and incentivizing the development of shared capacities. These respondents felt that clear guidance on permissible or preferred approaches to resource al- location would be necessary, given the long history of categorical restrictions. For example, some respondents suggested categori- cal programs should allow higher indirect cost rates in order to recognize and fund the core capacities upon which programmatic activities rely. E stablish incentives that promote diversified funding for strategic • investments. Many respondents indicated that increased support from local, state, federal, and private sources would be needed to build robust capacity in state and local health agencies. Several respondents suggested that financing policies should create in- centives for additional investments by each of these stakeholder groups and promote a more efficient alignment of public health resources. A few respondents focused specifically on the creation of either federal matching grants for state investment in local health department capacity or state matching grants for local investments in public health capacity. Proponents of matching grants suggested that these types of funding mecha- nisms would promote a shared commitment to capacity investments across multiple levels of government. Requiring local, state, and federal partners to have “skin in the game” was viewed as a necessary ingredient for diver- sifying funding, and perhaps more importantly, for establishing a shared vision regarding performance expectations and accountability processes. Respondents recognized that match-based funding would need to be care- fully structured to both achieve these goals and protect against potential drawbacks. For example, some respondents suggested that match rates could be customized to accommodate the relative affluence of individual states or localities, and preferential rates could be used to create incentives for specific types of investments, regional collaboration, agency accredita- tion, or other desired practices. CONCLUSION A clear consensus emerged from the respondent interviews regarding the need for improved and expanded capacity in state and local health agencies related to surveillance and epidemiology, community health improvement

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195 APPENDIX C planning, partnership development, policy decision support, and public communication. Respondents indicated that additional investments are needed to increase the number and skills of the public health workforce (particularly for personnel with expertise in informatics, communications, financial management, epidemiology, and other analytic competencies), to develop interoperable surveillance systems, and to improve the evidence base surrounding public health interventions and management best practices. Historically categorical funding mechanisms have created obstacles to the development of cross-cutting capacities and have often fostered a frag- mented, inefficient alignment of public health resources. Categorical funding streams have also contributed to ossification within the governmental public health infrastructure, limiting agencies’ ability to use scientific advancements and adapt to evolving population health needs. Perhaps most importantly, the dominance of these restrictive funding mechanisms has perpetuated a narrow vision for the potential role and contributions of state and local public health agencies—implying that their mission is merely the sum of categorical parts, rather than a comprehensive, holistic strategy to prevent disease and promote health. Despite these challenges, innovative public health leaders have success- fully used categorical funding in tandem with more flexible funding from local, state, and private sources to build capacity in mission-critical areas. These exploratory findings suggest that diversified funding is needed to sup- port strategic investments in public health capacity development. Additional study may be needed to fully characterize the existing portfolio of funding mechanisms currently supporting state and local agencies and to identify the optimal level, mix, and structure of financing needed to ensure adequate capacity development in mission-critical areas. Respondents suggested that public health finance policy should be re- focused to encourage additional investments across all levels of government and to promote a more efficient coordination of public health resources. Finance policies should reduce categorical restrictions that hinder the de- velopment of cross-cutting capacity, dedicate funds to capacity-development priorities, and create financial incentives for rational investments. REFERENCES Abarca, C., C. M. Grigg, J. A. Steele, L. Osgood, and H. Keating. 2009. Building and measur- ing infrastructure and capacity for community health assessment and health improvement planning in Florida. Journal of Public Health Management & Practice 15(1):54-58. Ali, R., D. Wheitner, E. O. Talbott, and J. V. Zborowski. 2007. Connecting environmental health data to people and policy: Integrating information and mobilizing communities for environmental public health tracking. Journal of Community Health 32(5):357-374. Anderson, L. M., R. C. Brownson, M. T. Fullilove, S. M. Teutsch, L. F. Novick, J. Fielding, and G. H. Land. 2005. Evidence-based public health policy and practice: Promises and limits. American Journal of Preventive Medicine (5 Suppl):226-230.

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197 APPENDIX C Brooks, R. G., L. M. Beitsch, P. Street, and A. Chukmaitov. 2009. Aligning public health financ- ing with essential public health service functions and National Public Health Performance Standards. Journal of Public Health Management & Practice 15(4):299-306. Brownson, R. C., J. E. Fielding, and C. M. Maylahn. 2009. Evidence-based public health: A fundamental concept for public health practice. Annual Review of Public Health 30:175-201. Byrne, C., J. B. Crucetti, M. G. Medvesky, M. D. Miller, S. J. Pirani, and P. R. Irani. 2002. The process to develop a meaningful community health assessment in New York State. Journal of Public Health Management & Practice 8(4):45-53. CBO (Congressional Budget Office). 2010. Fiscal Stress Faced by Local Governments. Wash- ington, DC: CBO. CDC (Centers for Disease Control and Prevention). 2006. Recommendations for Future Efforts in Community Health Promotion. Atlanta, GA: CDC. CDC. 2010. Community Health Assessment and Group Evaluation (CHANGE): Building a Foundation of Knowledge to Prioritize Community Health Needs. Atlanta, GA: CDC. Cheadle, A., C. Hsu, P. M. Schwartz, D. Pearson, H. P. Greenwald, W. L. Beery, G. Flores, and M. C. Casey. 2008. Involving local health departments in community health partnerships: Evaluation results from the Partnership for the Public’s Health Initiative. Journal of Urban Health 85(2):162-177. CMO (Chief Marketing Officer) Council. 2010. State of Marketing: Outlook, Intentions and Investments for 2010. Palo Alto, CA: CMO Council. Congdon, P. 2009. A multilevel model for cardiovascular disease prevalence in the U.S. and its application to micro area prevalence estimates. International Journal of Health Geo- graphics 8:6. Congdon, P. 2010. A multilevel model for comorbid outcomes: Obesity and diabetes in the United States. International Journal of Environmental Research and Public Health 7(2):333-352. Cossman, R. E., J. S. Cossman, W. L. James, T. Blanchard, R. K. Thomas, L. G. Pol, A. G. Cosby, and D. M. Mirvis. 2008. Evaluating heart disease prescriptions-filled as a proxy for heart disease prevalence rates. Journal of Health Human Services Administration 30(4):503-528. Costich, J. F., P. A. Honoré, and F. D. Scutchfield. 2009. Public health financial management needs: Report of a national survey. Journal of Public Health Management & Practice 15(4):307-310. Council on Linkages. 2005. Public Health Systems Research: Summary of Research Needs. Council on Linkages between Academia and Public Health Practice. Washington, DC: Public Health Foundation. Council on Linkages. 2010. Core Competencies for Public Health Professionals. Council on Linkages Between Academia and Public Health Practice. Washington, DC: Public Health Foundation. Cousins, J. M., S. M. Langer, L. K. Rhew, and C. Thomas. 2011. The role of state health departments in supporting community-based obesity prevention. Preventing Chronic Disease 8(4):A87. http://www.cdc.gov/pcd/issues/2011/jul/10_0181.htm (accessed August 12, 2011). CSTE (Council of State and Territorial Epidemiologists). 2009a. National Assessment of Epi- demiology Capacity: Supplemental Report on Chronic Disease Epidemiology Capacity. Atlanta, GA: CSTE. CSTE. 2009b. National Assessment of Epidemiology Capacity. Atlanta, GA: CSTE. CSTE. 2009c. State Injury Indicators Report, Fourth Edition—2005 Data. Atlanta, GA: CSTE. Curtis, D. C. 2002. Evaluation of community health assessment in Kansas. Journal of Public Health Management & Practice 8(4):20-25.

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198 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE Dannenberg, A. L., R. Bhatia, B. L. Cole, C. Dora, J. E. Fielding, K. Kraft, D. McClymont- Peace, J. Mindell, C. Onyekere, J. A. Roberts, C. L. Ross, C. D. Rutt, A. Scott-Samuel, and H. H. Tilson. 2006. Growing the field of health impact assessment in the United States: An agenda for research and practice. American Journal of Public Health 96(2):262-270. Drewnowski, A., C. D. Rehm, and D. Solet. 2007. Disparities in obesity rates: Analysis by ZIP code area. Social Science & Medicine 65(12):2458-2463. Duffy, R. E., and P. Z. Siegel. 2009. Increasing chronic disease epidemiology capacity without increasing workforce: A success story in Ohio. Journal of Public Health Management & Practice 15(2):123-126. Easterling, D. 2003. What have we learned about community partnerships? Medical Care Research and Review 60(4 Suppl):S161-S166. Erwin, P. C. 2008. The performance of local health departments: A review of the literature. Journal of Public Health Management & Practice 14(2):E9-E18. Erwin, P. C., S. B. Greene, G. P. Mays, T. C. Ricketts, and M. V. Davis. 2011. The association of changes in local health department resources with changes in state-level health outcomes. American Journal of Public Health 101(4):609-615. Fehrenbach, S. N., J. C. Kelly, and C. Vu. 2004. Integration of child health information systems: Current state and local health department efforts. Journal of Public Health Management and Practice Suppl(Nov):S30-S35. Fielding, J. E., C. E. Sutherland, and N. Halfon. 1999. Community health report cards. Results of a national survey. American Journal of Preventive Medicine 17(1):79-86. Finison, L. J. 2007. Community Health Data Scan for Connecticut. New Britain: Connecticut Health Foundation. Friedman, D. J. 2007. Assessing Changes in the Vital Records and Statistics Infrastructure. Silver Spring, MD: National Association for Public Health Statistics and Information Systems. Friedman, D. J., and R. G. Parrish, 2nd. 2006. Characteristics, desired functionalities, and datasets of state web-based data query systems. Journal of Public Health Management & Practice 12(2):119-129. Friedman, D. J., and R. G. Parrish. 2009. Is community health assessment worthwhile? Journal of Public Health Management & Practice 15(1):3-9. Friedman, D. J., and R. G. Parrish. 2010. The population health record: Concepts, definition, design, and implementation. Journal of the American Medical Informatics Association 17:359-366. Grier, S., and C. A. Bryant. 2005. Social marketing in public health. Annual Review of Public Health 26:319-339. Grigg, M., B. Alfred, C. Keller, and J. A. Steele. 2006. Implementation of an Internet-based geographic information system: The Florida experience. Journal of Public Health Manage- ment & Practice 12(2):139-145. Harris, J. K., K. E. Beatty, J. D. Lecy, J. M. Cyr, and R. M. Shapiro, 2nd. 2011. Mapping the multidisciplinary field of public health services and systems research. American Journal of Preventive Medicine 41(1):105-111. Honoré, P. A., and J. F. Costich. 2009. Public health financial management competencies. Journal of Public Health Management & Practice 15(4):311-318. Honoré, P. A., and T. Schlechte. 2007. State public health agency expenditures: Categorizing and comparing to performance levels. Journal of Public Health Management & Practice 13(2):156-162. Honoré, P. A., and W. Scott. 2010. Priority Areas for Improvement of Quality in Public Health. Washington, DC: HHS. Honoré, P. A., E. J. Simoes, W. J. Jones, and R. Moonesinghe. 2004. Practices in public health finance: An investigation of jurisdiction funding patterns and performance. Journal of Public Health Management & Practice 10(5):444-450.

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199 APPENDIX C Honoré, P. A., R. L. Clarke, D. M. Mead, and S. M. Menditto. 2007. Creating financial trans- parency in public health: Examining best practices of system partners. Journal of Public Health Management & Practice 13(2):121-129. Honoré, P. A., P. J. Fos, T. Smith, M. Riley, and K. Kramarz. 2010. Decision science: A scientific approach to enhance public health budgeting. Journal of Public Health Management & Practice 16(2):98-103. Honoré, P. A., P. J. Fos, X. Wang, and R. Moonesinghe. 2011. The effects on population health status of using dedicated property taxes to fund local public health agencies. BMC Public Health 11(1):471-480. IOM (Institute of Medicine). 2011. For the Public’s Health: The Role of Measurement in Action and Accountability. Washington, DC: The National Academies Press. Irani, P., C. Bohn, C. Halasan, M. Landen, and D. McCusker. 2006. Community health as- sessment: Driving the need for current, easily accessible population health data. Journal of Public Health Management & Practice 12(2):113-118. Jacobs, L. M., and J. J. Elligers. 2009. The MAPP approach: Using community health status assessment for performance improvement. Journal of Public Health Management & Practice 15(1):79-81. Kassler, W. J., and Y. P. Goldsberry. 2005. The New Hampshire public health network: Creat- ing local public health infrastructure through community-driven partnerships. Journal of Public Health Management & Practice 11(2):150-157. Keane, C., J. Marx, and E. Ricci. 2003. Local health departments’ mission to the uninsured. Journal of Public Health Management & Practice 24(2):130-149. Kegler, M. C., J. E. Painter, J. M. Twiss, R. Aronson, and B. L. Norton. 2009. Evaluation findings on community participation in the California Healthy Cities and Communities program. Health Promotion International 24(4):300-310. Keller, L. O., M. A. Schaffer, B. Lia-Hoagberg, and S. Strohschein. 2002. Assessment, program planning, and evaluation in population-based public health practice. Journal of Public Health Management & Practice 8(5):30-43. Klompas, M., and D. S. Yokoe. 2009. Automated surveillance of health care-associated infec- tions. Clinical Infectious Diseases 48(9):1268-1275. Koivusalo, M. 2010. The state of Health in All Policies (HiAP) in the European Union: Potential and pitfalls. Journal of Epidemiology and Community Health 64(6):500-503. Krieger, N., J. T. Chen, P. D. Waterman, M. J. Soobader, S. V. Subramanian, and R. Carson. 2002. Geocoding and monitoring of U.S. socioeconomic inequalities in mortality and cancer incidence: Does the choice of area-based measure and geographic level matter? The Public Health Disparities Geocoding Project. American Journal of Epidemiology 156(5):471-482. Kukafka, R., J. S. Ancker, C. Chan, J. Chelico, S. Khan, S. Mortoti, K. Natarajan, K. Presley, and K. Stephens. 2007. Redesigning electronic health record systems to support public health. Journal of Biomedical Informatics 40(4):398-409. LaPelle, N. R., R. Luckmann, E. H. Simpson, and E. R. Martin. 2006. Identifying strategies to improve access to credible and relevant information for public health professionals: A qualitative study. BMC Public Health 6:89-102. Lazarus, R., M. Klompas, F. X. Campion, S. J. McNabb, X. Hou, J. Daniel, G. Haney, A. DeMaria, L. Lenert, and R. Platt. 2009. Electronic support for public health: Validated case finding and reporting for notifiable diseases using electronic medical data. Journal of the American Medical Informatics Association 16(1):18-24. Leep, C., L. M. Beitsch, G. Gorenflo, J. Solomon, and R. G. Brooks. 2009. Quality improve- ment in local health departments: Progress, pitfalls, and potential. Journal of Public Health Management & Practice 15(6):494-502.

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200 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE Lhachimi, S. K., W. J. Nusselder, H. C. Boshuizen, and J. P. Mackenbach. 2010. Standard tool for quantification in health impact assessment: A review. American Journal of Preventive Medicine 38(1):78-84. Libbey, P., and B. Miyahara. 2011. Cross-Jurisdictional Relationships in Local Public Health: Preliminary Summary of an Environmental Scan. Princeton, NJ: RWJF. Livingood, W. C., L. Razaila, E. Reuter, R. Filipowicz, R. C. Butterfield, K. Lukens-Bull, L. Edwards, C. Palacio, and D. L. Wood. 2010. Using multiple sources of data to assess the prevalence of diabetes at the subcounty level, Duval County, Florida, 2007. Preventing Chronic Disease 7(5):A108. Livingood, W. C., M. Morris, B. Sorensen, K. Chapman, L. Rivera, P. Street, L. M. Beitsch, S. Coughlin, N. Winterbauer, C. Iusan, and D. Wood. 2011. Funding of Essential Ser- vices for Local Public Health. Paper read at PHSSR Keeneland Conference, April 12-14, Lexington, Kentucky. http://www.cdc.gov/pcd/issues/2010/sep/09_0197.htm (accessed August 12, 2011). Love, D., and G. H. Shah. 2006. Reflections on organizational issues in developing, imple- menting, and maintaining state web-based data query systems. Journal of Public Health Management & Practice 12(2):184-188. Love, D., B. Rudolph, and G. H. Shah. 2008. Lessons learned in using hospital discharge data for state and national public health surveillance: Implications for Centers for Disease Control and Prevention tracking program. Journal of Public Health Management & Practice 14(6):533-542. Lovelace, K. 2000. External collaboration and performance: North Carolina local public health departments, 1996. Public Health Reports 115(4):350-357. Luck, J., C. Chang, E. R. Brown, and J. Lumpkin. 2006. Using local health information to promote public health. Health Affairs 25(4):979-991. Lutz, B., R. Molloy, and H. Shan. 2011. The housing crisis and state and local government tax revenue: Five channels. Regional Science and Urban Economics 41(4):306-319. Madamala, K., K. Sellers, J. Pearsol, M. Dickey, and P. E. Jarris. 2010. State landscape in public health planning and quality improvement: Results of the ASTHO survey. Journal of Public Health Management & Practice 16(1):32-38. Magruder, S. F., S. H. Lewis, A. Najmi, and E. Florio. 2004. Progress in understanding and us- ing over-the-counter pharmaceuticals for syndromic surveillance. Morbidity and Mortality Weekly Report 53(Suppl):117-122. Magruder, C., M. Burke, N. E. Hann, and J. A. Ludovic. 2005. Using information technology to improve the public health system. Journal of Public Health Management & Practice 11(2):123-130. Maibach, E. W., L. C. Abroms, and M. Marosits. 2007. Communication and marketing as tools to cultivate the public’s health: A proposed “people and places” framework. BMC Public Health 7:88. Malvitz, D. M., L. K. Barker, and K. R. Phipps. 2009. Development and status of the National Oral Health Surveillance System. Preventing Chronic Disease 6(2):A66. http://www.cdc. gov/pcd/issues/2009/apr/08_0108.htm (accessed August 12, 2011). Mays, G. P., and F. D. Scutchfield. 2010. Improving public health system performance through multiorganizational partnerships. Preventing Chronic Disease 7(6):A116. http://www.cdc. gov/pcd/issues/2010/nov/10_0088 (accessed March 1, 2011). Mays, G. P., and S. A. Smith. 2009. Geographic variation in public health spending: Correlates and consequences. Health Services Research 44(5 Pt 2):1796-1817. Mays, G. P., S. A. Smith, R. C. Ingram, L. J. Racster, C. D. Lamberth, and E. S. Lovely. 2009. Public health delivery systems: Evidence, uncertainty, and emerging research needs. American Journal Preventive Medicine 36(3):256-265.

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201 APPENDIX C Mays, G. P., F. D. Scutchfield, M. W. Bhandari, and S. A. Smith. 2010. Understanding the organization of public health delivery systems: An empirical typology. Milbank Quarterly 88(1):81-111. Merrill, J., M. Caldwell, M. L. Rockoff, K. Gebbie, K. M. Carley, and S. Bakken. 2008. Find- ings from an organizational network analysis to support local public health management. Journal of Urban Health 85(4):572-584. Merrill, J. A., J. W. Keeling, R. V. Wilson, and T. V. Chen. 2011. Growth of a scientific com- munity of practice public health services and systems research. American Journal of Preventive Medicine 41(1):100-104. Meyer, J., and L. Weiselberg. 2009. County and City Health Departments: The Need for Sus- tainable Funding and the Potential Effect of Health Care Reform on Their Operations. Princeton, NJ: RWJF and NACCHO. Michaelis, A. P. 2002. Priority-setting ethics in public health. Journal of Public Health Policy 23(4):399-412. Miner, J. W., A. White, A. E. Lubenow, and S. Palmer. 2005. Geocoding and social marketing in Alabama’s cancer prevention programs. Preventing Chronic Disease 2(Spec no):A17. http://www.cdc.gov/pcd/issues/2005/nov/05_0073.htm (accessed August 12, 2011). Miranda, M. L., J. M. Silva, M. A. Overstreet Galeano, J. P. Brown, D. S. Campbell, E. Coley, C. S. Cowan, D. Harvell, J. Lassiter, J. L. Parks, and W. Sandele. 2005. Building geo- graphic information system capacity in local health departments: Lessons from a North Carolina project. American Journal of Public Health 95(12):2180-2185. Mokdad, A. H. 2009. The Behavioral Risk Factors Surveillance System: Past, present, and future. Annual Review of Public Health 30:43-54. Myers, S., and M. Stoto. 2006. Criteria for Assessing the Usefulness of Community Health Assessments: A Review of the Literature. Santa Monica, CA: RAND. NACCHO (National Association of County and City Health Officials). 2005. Operational Definition of a Functional Local Health Department. Washington, DC: NACCHO. NACCHO. 2009. 2008 National Profile of Local Health Departments. Washington, DC: NACCHO. NACCHO. 2011. Local Health Department Job Losses and Program Cuts: State-Level Tables from the 2010 National Profile Study. Washington, DC: NACCHO. National Prevention Council. 2011. National Prevention Strategy. Washington, DC: National Prevention Council. NYSACHO (New York State Association of County Health Officials). 2001. Preserve Ar- ticle Six State Aid and State Grant Funding for Local Public Health Activities. Albany: NYSACHO. Overhage, J. M., S. Grannis, and C. J. McDonald. 2008. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. American Journal of Public Health 98(2):344-350. Parker, E., L. H. Margolis, E. Eng, and C. Henriquez-Roldan. 2003. Assessing the capacity of health departments to engage in community-based participatory public health. American Journal of Public Health 93(3):472-476. Paul-Shaheen, P. A., B. A. Schillo, G. E. Beane, and E. F. Kleinau. 1997. The challenge of developing community profiles for use in community health assessment: Lessons from Michigan’s experience. Journal of Public Health Management & Practice 3(3):16-28. PHAB (Public Health Accreditation Board). 2009. Proposed Local Standards and Measures: For PHAB Beta Test. Alexandria, VA: PHAB. Pirani, S., and T. Reizes. 2005. The Turning Point Social Marketing National Excellence Col- laborative: Integrating social marketing into routine public health practice. Journal of Public Health Management & Practice 11(2):131-138.

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204 FOR THE PUBLIC’S HEALTH: INVESTING IN A HEALTHIER FUTURE ADDENDUM: INTERVIEW RESPONDENTS Name and Title Organization/Prior Experience Susan Allan, Director Northwest Center for Public Health Practice, former Public Health Director, State of Oregon; and Health Director, Arlington County, Virginia Kaye Bender, President Public Health Accreditation Board Bobbie Berkowitz, Dean Columbia School of Nursing, former Deputy Director, WA State Department of Health; and Chief of Public Health Nursing, Seattle & King County Public Health Gus Birkhead, Deputy Office of Public Health, NY State Department of Commissioner Health Leah Devlin Former Director, NC Division of Public Health Paul Halverson, Director Arkansas Department of Health Peggy Honoré, Director Public Health System, Finance, and Quality Program, OASH, HHS Paul Kuehnert, Director Kane County (IL) Department of Health Pat Libbey University of WA School of Public Health, former NACCHO Director Pat McConnon Council of State and Territorial Epidemiologists Michael Meit Walsh Center for Rural Analysis/NORC Tom Milne Milne and Associates, former Director of NACCHO Bruce Miyahara Miyahara and Associates, former Director WA State Department of Health; and Director Seattle & King County Public Health Herminia Palacios, Harris County Public Health & Environmental Executive Director Services, Texas Bobby Pestronk, Executive NACCHO, former director Genesee County Health Director Department (Flint, MI) Phred Pilkington, Director Cabarrus Health Alliance (NC) Doug Scutchfield University of Kentucky School of Public Health Kathy Vincent Former Staff Assistant to the State Health Officer, Alabama Department of Public Health