HHS 497 Health & Human Services WK3-A

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Editors’ note: This chapter features two case studies on the role data plays in trans- forming a nonprofit organization.

DEVELOPING A DATA-DRIVEN CULTURE: A CASE STUDY

Twenty years ago, few human services organizations made use of much data other than budget information used to ensure that costs were being cov- ered. Today, the amount of data that is collected, organized, and analyzed by human services organizations can rival that collected by any commercial business in the private sector. Depending on an organization’s capacity to manage it, this torrent of data can be overwhelming or it can be leveraged to improve strategic and operational decision making. This chapter will evalu- ate key factors that have been instrumental in fostering a data-driven culture at Heartland Family Service.

Heartland Family Service is a nonprofit human services organization founded in 1875, serving the Omaha–Council Bluffs metro area and sur- rounding communities in east central Nebraska and southwest Iowa. To fulfill its mission to improve the lives of individuals and families in the community through education, counseling, and support, Heartland Family Service operates over 40 programs in eight service categories: addictions, child abuse, community services and centers, domestic violence, early child- hood development, juvenile delinquency, mental health, and poverty and homelessness. These services are provided in diverse settings, including office-based outpatient, in-home, residential, and community-based drop-in

CHAPTER 7

Using Data to Drive Change and Achieve Impact

Greg Ryan, John Jeanetta, Michael Bedrosian, Francine Axler, Amy Friedlander, and Alex Lehr O’Connell

Making Strategy Count in the Health and Human Services Sector : Lessons Learned from 20 Organizations and Chief Strategy Officers, edited by Tine, MGA, JD, FCPP, FAAN Hansen-Turton, and Michael Mortell, Springer Publishing Company, 2013. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/ashford-ebooks/detail.action?docID=1572950. Created from ashford-ebooks on 2018-11-17 08:50:14.

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locations. With an annual budget of $22 million, the agency serves 37,000 community members each year.

In their article “Building Capacity to Measure and Manage Performance,” Matthew Forti and Kathleen Yazbak outline five key components of organi- zational capacity for measurement: leadership commitment, a spirit of learn- ing and improvement, outside expertise, a measurement director, and a flexible structure (Forti & Yazbak, 2012). The importance of each of these components has been evident in the evolution of the culture at Heartland Family Service since the early 1980s, when the agency first made a concerted effort to begin collecting and monitoring performance data.

Inception

In 1977, the Child Welfare League of American and Family Service America (now the Alliance for Children and Families) founded the Council on Accreditation (COA). COA was formed to define national standards of ser- vice quality for organizations that serve children and families and to ensure that those standards were being met. As this national accrediting body was being formed, the leadership at Heartland Family Service (then known as Family Service) was taking notice. They realized that if the agency was to be effective and to create lasting change for individuals and families in need, it was imperative that it become accredited. However, the accreditation pro- cess demanded that the organization demonstrate, in real and concrete ways, how it delivered services and created change. For the first time, leadership and staff were challenged to become very specific and systematic about how services were delivered.

To accomplish this goal, agency leaders identified local experts in quality improvement and recruited them to the board of directors. They tapped into the knowledge and expertise provided by national organizations such as the Alliance for Children and Families. And from this consultation they formed a quality council. The council was an internal team of staff representing all parts of the organization. The team reported directly to the president and CEO and monitored different kinds of information than had been typical up to that point. Instead of counting dollars collected and expenses paid, this group measured client satisfaction and staff safety. Instead of balance sheets and budget reports, it was file audits and clients served. Through proactive leadership and the efforts of a passionate group of staff, practices were estab- lished to ensure that the effectiveness of their services was being monitored on a regular basis. Their early efforts paved the way for the agency to remain continuously accredited from 1983 to this day.

Leadership commitment, outside expertise, and a spirit of growth and improvement fostered by the accreditation process were critical factors that set Heartland Family Service on its journey to become data-driven. Without strong, visionary, and supportive leadership determined to realize the value of accreditation, it is hard to imagine that a group of staff would have gotten

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together to start monitoring service quality on their own. Without the exper- tise provided by local quality improvement professionals, or national organi- zations providing guidance and technical assistance, it is hard to imagine that effective practices would have been established. And without a focus on learning and improvement rather than deficiencies and faults, it is hard to imagine that staff would have tolerated such scrutiny of their performance.

Leaders wanting to strengthen a datacentric culture within their organi- zation could start by setting a goal of becoming accredited through one of a number of national accreditation bodies. COA accredits a variety of human services and behavioral health organizations; the Joint Commission is geared toward health care organizations; and the Commission on Accreditation of Rehabilitative Facilities (CARF) is a third alternative. For organizations that are already accredited, the Baldrige Criteria for Performance and Excellence could be used to challenge a culture that has gotten complacent with regular accreditation cycles. The Baldrige Criteria have more recently gained popu- larity among human services agencies as a way to benchmark their perfor- mance both within and outside of the human services sector.

Expansion

Because the quality council reported directly to the president and CEO and was integral to the accreditation process, it played an increasingly impor- tant role in the operation of the agency. In addition, members of the qual- ity council were seen as leaders within their respective job roles across the agency, and membership on the council was viewed as a staff development opportunity. Third, beginning in the late 1990s, United Way was leading a national effort to move beyond merely tracking outputs to identifying and measuring outcomes (Hendricks, Plantz, & Prichard, 2008). Instead of simply counting the number of clients served, meals provided, or sessions attended, human service organizations were being challenged to identify how their services created tangible positive changes for clients. This challenge forced organizations to be more sophisticated in their approaches to measurement, data management, and analysis. Instead of simply distributing a survey and averaging results, organizations were expected to collect information mul- tiple times during the delivery of services and compare scores across time, analyzing the differences. The combination of internal stress on the quality council and external pressure to track more complex information resulted in two significant changes in the structure of the data monitoring and report- ing systems at Heartland Family Service.

The amount of information the agency needed to track for accredita- tion purposes, the new United Way initiative, and other internal and exter- nal reporting requirements added up to more than a single team of staff could manage. So the quality council was disbanded in favor of four qual- ity improvement teams (QITs), each designed to manage a specific type of performance data. The Outcomes QIT was developed in direct response to

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the United Way’s effort to measure outcomes. The Record Review QIT met the accreditation-related need for internal file audits. The Utilization Review QIT helped manage program capacity. And the Internal Care Monitoring QIT was responsible for measuring satisfaction among clients and employ- ees and ensuring a safe workplace. In addition to building capacity for man- aging a wider variety of data, this reconfiguration provided opportunity for more staff involvement. Whereas the quality council was made up of 9 to 12 members, the new QIT structure included 40 or more members. With increased staff involvement, the value of measurement and analysis was being communicated to an ever-widening audience within the organization and was permeating deeper into the culture of the agency.

The second change that was implemented during this expansion period was the hiring of a director of quality improvement. Not only was this role needed to manage the rising number of staff involved and increasing com- plexity of the performance measurement process, but it also showed how dedicated agency leaders were to using data to make strategic and opera- tional decisions at all levels and in all facets of the organization. The direc- tor became an important champion of the structural changes the agency implemented in going from a single quality council to multiple QITs. The position has always had special support from the president and CEO, which gave the director the necessary authority to hold the agency accountable for supporting the growing culture. And although proficiency with measure- ment and data was an obvious requirement, it was equally important for the person selected for the role to be an excellent communicator and con- nector, allowing him or her to help translate the concepts and language of outcomes and quality improvement into everyday tasks and practices that all staff could understand and to which they could relate. In this way, the director became a respected resource for helping program managers and vice presidents promote the success of their programs and craft competitive funding applications.

Changes that Heartland Family Service implemented during this expan- sion phase demonstrated a maturing of the organization’s data-driven cul- ture. Leadership remained flexible in their approach to dealing with the changing needs of the agency. They understood that these new data chal- lenges could not be addressed with the same structure and practices that had created their initial success. They also understood that a more complex structure required guidance and oversight from a director dedicated to managing the process. External expertise, this time from the United Way, was once again an important factor in refining the agency’s understanding of performance management. And the spirit of learning and improvement originally fostered by the quality council was perpetuated as more staff became involved in the process through the QITs.

Every organization eventually gets to a point at which it is necessary to consolidate the management of measurement and evaluation systems into a specific person’s role. This consolidation should not relieve the rest

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of the staff from continuing to foster a datacentric culture. Instead, this role is intended to accelerate the culture by creating more opportunities for involvement, increasing everyone’s knowledge and expertise through train- ing, clarifying roles and responsibilities, and ensuring that responsibilities are met systematically and regularly. A good measurement director needs change management skills that are at least as good as his or her proficiency with data.

Refinement

Over the last 3 years, Heartland Family Service has continued to refine its data-driven culture. Decades of regularly monitoring, reporting on, and improving performance across all different facets of the organization have been useful and rewarding. But the work has also often led to fragmented data silos within which it is difficult to relate performance data in one aspect of the organization to another.

For example, the agency’s juvenile evaluation program is required to complete interdisciplinary psychosocial assessments within 10 working days of receiving a referral. This is a demanding time frame in light of the number of professionals involved in each assessment. Key performance indi- cators for this program include the number of assessments completed per month and the percentage of those assessments that are completed on time. Without regard to any other factors, the more assessments completed and the higher the on-time percentage of completed assessments, the better. But at what cost? Without taking into account wear and tear on staff, it could appear that the sky is the limit when it comes to these performance indica- tors. Monitoring staff satisfaction alongside the productivity data described above would paint a more complete and accurate picture of the program’s performance, but historically this has been difficult—because these groups of data have been managed separately.

Three years ago, the agency began experimenting with the balanced scorecard concept (Kaplan & Norton, 1992). A balanced scorecard is a diverse collection of performance indicators reflecting the most critical measures across all parts of an organization. Rather than concentrating solely on financial metrics, a balanced scorecard brings together data from a variety of areas such as human resources, quality improvement, programs and ser- vices, clients, volunteers and stakeholders, and fulfillment of mission. Much of this data was already being tracked separately within each functional area, but the balanced scorecard created an opportunity for these measures to be monitored side by side. This led to new thinking about the relation- ships between different parts of the agency. Limits placed on the number of indicators that could be included on the scorecard also challenged agency leaders to identify the critical few measures that provided the most informa- tion about how a department was performing.

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As this concept has been refined over the last several years, programs are now encouraged to implement their own scorecards. These program- level scorecards are designed both to meet the day-to-day management needs of the program and to connect the program’s work back to the agen- cy’s strategic initiatives and overall performance. Making these connections between data collected at all levels and across all parts of the organiza- tion reinforces for agency staff the value of measuring and monitoring performance.

Another factor that can either facilitate or frustrate a data-driven culture is the types of tools and data systems that are available to help manage and make sense of all the information that is collected and stored. At Heartland Family Service, the quality improvement reporting system has gone through many iterations of development. Initially, performance was reported in word processing templates. Aggregating data across the agency based on these templates was labor-intensive, time-consuming, and error-prone. Eventually, the reporting templates were re-created in spreadsheet software in order to leverage pre-populated formulas and reduce errors. But data aggregation was still a difficult task. Next, advanced spreadsheet programming was used to automate the aggregation process. In addition, visually based inter- active dashboards were created to assist program staff in analyzing their results, identifying trends, and making ad hoc comparisons in their data. As the agency’s quality reporting system has evolved, QITs have been able to go from checking to make sure the math is right to evaluating whether changes in procedures are resulting in improvements for clients.

The next step in Heartland Family Service’s journey to becoming increas- ingly datacentric is to implement a unified data system that will consolidate client data across all of its programs. Up to this point, programs have used all different kinds of tools for managing client data. Some programs have used spreadsheet software, some have developed simple desktop databases, and others have used an enterprise-level database. By moving everyone to a uni- fied data system, leadership and decision-makers will have better access to more comprehensive, up-to-date, and accurate information about the clients the agency serves. Clearly, having the right tools in place plays an important role in supporting a data-driven culture.

Incorporating ideas from external experts, including ideas such as the balanced scorecard concept, continues to be an important strategy for refining the agency’s datacentric culture. A flexible infrastructure that can incorporate new tools and solutions has become increasingly important as the agency’s capacity for data analysis has grown more sophisticated. Finally, a strong spirit of continual growth and constant improvement is especially important at this mature stage to ensure that the agency does not become complacent.

Depending on the size of the organization and the types of services being provided, data systems do not need to be complex. For a small organization providing straightforward services such as information and referral, well- organized paper-based tally sheets paired with a simple spreadsheet could be an effective way of tracking the most important data needed to optimize

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Chapter 7 using data to drive Change and aChieve iMPaCt 141

performance. As the level of complexity and amount of data increase, it becomes increasingly necessary to invest in enterprise-level databases that provide more power and flexibility when it comes to data entry, manage- ment, analysis, and reporting. At the extreme end of complexity, large organ- izations require ways to connect and relate data between databases, often creating data warehouses that coordinate data across software applications. Regardless of the level of sophistication, it is useful to manage data in some type of electronic system in order to leverage tools that can automate routine data management tasks.

Conclusion

Of all the lessons learned during the journey that Heartland Family Service has taken to become a data-driven organization, the most surprising is that after a clear and compelling direction was set and supported by leadership, there were very few radical breakthroughs in the evolution of the culture. Instead, by and large, the culture was created, strengthened, and sustained through thousands of tiny improvements brought about by a wide range of people over many years. Often the changes were so simple and obvious as to hardly even be celebrated as improvements: A simple revision to a com- plicated record review checklist that saves a reviewer 10 minutes of flipping back and forth in a client file during an audit; adding the previous quarter’s data to a quarterly report in order to put current performance into context; sharing client success stories on the agency’s intranet to remind staff how their work makes a difference. None of these changes by itself was all that revolutionary, but taken together they create a kind of positive momentum that persists in an organization.

Knowledge is power. And one of the richest sources of knowledge is the data that an organization collects about its people, clients, services, and finances. The challenge is to create an environment in which every person has the capability to extract knowledge from the data at his or her disposal. By employing the key components identified by Forti and Yazbak and adapt- ing ideas that have served Heartland Family Service well on its journey, you, too, can accelerate your organization’s capacity to become data-driven.

USING DATA AND INFORMATION SYSTEMS TO DRIVE AN INTEGRATED HEALTH AND HUMAN

SERVICES ENTERPRISE: THE PUBLIC HEALTH MANAGEMENT CORPORATION APPROACH

Today’s social service environment depends on the effective use of data to measure the impact of the services rendered to clients. Data are at the center of every measurable and sustainable program. Funders, whether at the federal, state, or local level, require increasingly detailed reporting on utilization of

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services, including data regarding client participation, adherence to program guidance, and completion of interventions. The Public Health Management Corporation (PHMC) recognizes this and has created a model of data collec- tion and information system development that complements existing data- bases maintained by funders or regulators but that also goes well beyond the obvious basic financial drive. The PHMC model incorporates specific, measurable, attainable, realistic, and timely program metrics into every sys- tem developed. This approach to system development is central to PHMC’s mission of improving the health and welfare of residents in its region.

PHMC, headquartered in Philadelphia, Pennsylvania, is a large, pri- vate, nonprofit health and human services agency. Since its inception in 1970, PHMC has invested heavily in its infrastructure and core management support services, including information systems technology. At PHMC, the information systems (IS) group and the Center for Data Innovation (the Center) are charged with continually improving the quality of the data col- lected to improve the services delivered to clients. To achieve this, PHMC has created a model of data collection and system development that is fueled by teamwork, collaboration, and commitment to the PHMC mission. The model is guided by one unified principle—building information systems that will help enhance the client experience and increase client success rates. Working with various program, quality management, and fiscal staff, the PHMC model creates systems addressing the requirements of funding agen- cies but that remain tightly aligned with the goals of the programs they sup- port. Several case examples follow that illustrate PHMC’s unique approach to developing rigorous program data collection and information systems. As you will see, the end result of the PHMC model is enhanced social service delivery for the most vulnerable populations.

Case Example #1

PHMC operates a network of substance abuse treatment programs (behavio- ral health treatment programs) providing a range of comprehensive services throughout the city of Philadelphia. These treatment programs target the most at-risk and vulnerable population groups: low-income women, women with children, adolescents, and individuals caught up in the criminal justice system. Each of the treatment programs utilizes a holistic approach to ser- vice delivery. The goal of all of these programs is to help individuals living with addiction to drugs or alcohol develop the skills and support they need to become free of their disease. PHMC’s goal is to link clients with specific needs to additional services such as primary care, aftercare case manage- ment, early intervention, and specialized employment services.

To meet the needs of these high-risk clients cost-effectively, PHMC built a comprehensive data collection system called the client registry service (CRS). The CRS quickly and easily stores client and service data including

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Chapter 7 using data to drive Change and aChieve iMPaCt 143

authorizations, financial history, drug screening results, contacts, and pro- gress notes. These data are connected directly to PHMC’s fee-for-service bill- ing system, reducing the effects of human error on clients by automatically linking intake data to financial claim data. This allows the immediate gen- eration of claims to multiple payers. Most importantly, the CRS helps clients get services faster by allowing for the ad hoc exporting of data so that any issues in treatment can be analyzed and addressed quickly when clients are most receptive to behavior change.

Case Example #2

Since 1985, PHMC has directed the Health Care for the Homeless program. Funded primarily by the Federal Department of Health and Human Services, this program has the primary goal of improving the health status of homeless persons by improving their access to primary health care, drug and alco- hol treatment, and mental health services in order to increase their ability to obtain permanent housing, stable employment, and access to needed social supports.

To develop an information system that allowed for gathering data on a very hard-to-reach population, the PHMC model was utilized for this pro- gram. PHMC staff worked collaboratively with several partners, including service providers, case managers, and funders, to develop a system that would allow program managers to capture data on more than 85,000 home- less clients and manage productivity 24/7 without relying on IS program- mers. The end result was that the system enabled case managers to do their jobs better and faster while adhering to the mission of the program of provid- ing targeted services. PHMC’s model was extremely effective in capturing data for this population group and has built on this core capability by design- ing and implementing an electronic health record to support the provision of primary care services by PHMC nursing staff at the city’s homeless shelters.

Case Example #3

The County of Philadelphia maintains an early intervention program known as ChildLink. This program provides service coordination to help children from birth to age three who have developmental delays or disabilities and their families living in Philadelphia. PHMC’s ChildLink program works in partnership with parents and early intervention specialists to evaluate each child's needs, identify outcomes, and develop an Individualized Family Service Plan (IFSP) comprising supports and services appropriate for each eligible child and family. The program serves approximately 9,000 clients annually. To meet the needs of this program, PHMC developed a system to automate the coordination of provider services and monitor compliance with the IFSP. As with other PHMC data collection systems, the system was

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designed to facilitate the export and exchange of data for detailed analysis of the program’s performance at the client level and to be compatible with funder-mandated reporting systems.

Case Example #4

PHMC’s Center for Data Innovation provides an unmatched set of infor- mation on local community economic and health needs that can be used to develop focused programs supported by actual community data. The Center for Data Innovation combines current data initiatives at PHMC with external programs to monitor, track, and evaluate the health of the public.

The primary data source within the Center is the community survey. The community survey has served as a key data resource in developing priorities and rationales for strategic plans for health and human service providers since 1983. The survey collects data from over 10,000 households in Bucks, Chester, Delaware, Montgomery, and Philadelphia counties every 2 years, providing a rich data set for longitudinal analyses of a variety of health, economic, and community topics affecting adults and children. The survey is one of the largest local surveys in the country; no other population survey collects the depth of public health information at small levels of geography that allow for analysis by legislative district, neighborhood, and clusters of census tracts and ZIP codes.

One of the primary goals of the Center for Data Innovation is to enhance the capacity of health and human services programs by improving access to and increasing utilization of data. To meet this goal, the center worked with PHMC’s IS team to create tools that would allow users access to the data in a “friendly” way. The tools were created using the PHMC model of meeting funding requirements but with a commitment to aligning with the goals of the program. Two online analysis tools were created utilizing over 40 health variables that can be examined by six demographic subgroups for any geo- graphic area in the five-county region of Southeastern Pennsylvania for each survey year from 2000 through 2012. Users can compare their service area with the county and the region on a set of key health indicators.

The data and online tools help to expand organizations’ planning, fund- ing, and marketing capabilities and are used as critical tools to support fund development and community health needs assessments. There are infinite uses for data of this type including strategic planning, target area analysis, policy and program development, community health needs assessments, market analysis, and program evaluation. Currently, over 350 organizations such as major health departments, nonprofit organizations, and hospitals and health systems utilize PHMC’s Community Health Data Base for health data. In addition, Pennsylvania legislators utilize the data to support policies that improve the health and well-being of residents, and the academic com- munity utilizes the data for ground-breaking research in the areas of nurs- ing, criminal justice, social work, and more.

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Case Example #5

PHMC operates five federally qualified health center (FQHC) sites, each of which provides comprehensive health care to homeless and public housing residents and their surrounding communities regardless of an individual’s insurance status or ability to pay. FQHCs are the only culturally compe- tent, affordable, accessible health care providers for over 19 million of the nation’s most vulnerable residents. By providing access to cost-effective primary care and prevention services, FQHCs have been shown to reduce emergency room visits by 20% and hospitalizations by 10% (Falik et al., 2006) when compared with private practices. Funding authorized by the Patient Protection and Affordable Care Act is poised to double the nation’s network of FQHCs to serve 40 million patients annually by 2015. Such expansion will require careful assessment of existing capacity and demonstration of need sufficient to qualify for grant funding in an increasingly competitive funding environment.

In response to changes in legislation, PHMC analyzed data from the 2010 Census, along with surveillance data on disease prevalence, outcomes, and health disparities, and identified a neighborhood in Eastern North Philadelphia as prime for investment. Specifically, this predominantly Latino community had seen rapid population growth in the previous dec- ade. With over 80% of the population living below 200% of the federal pov- erty level (the federal designation for low-income in the FQHC program), the area met and exceeded the high bar set to compete for federal funding. Community and client surveys collected demonstrated very high preva- lences of chronic conditions such as diabetes, hypertension, and asthma and high utilization of emergency rooms, indicating poor management of those conditions. Data from existing FQHCs on their market penetra- tion that were made publicly available for the first time in 2010 revealed over 133,000 residents of the area who were low-income and had not vis- ited an existing FQHC grantee for even a single visit in the previous year (The Health Foundation of Greater Cincinnati & the American Academy of Family Physicians, 2010).

The area had been served for over 30 years by the Congreso de Latinos Unidos (Congreso), a robust education, health, and social services provider that had only primary care missing from its on-site resources. Sharing PHMC’s focus on data-driven, impact-oriented service provision, Congreso was already tracking the outcomes of its programs, through the Efforts to Outcomes (ETO™) social services platform. This allowed Congreso to dem- onstrate the positive steps their clients had been able to take towards eco- nomic independence, including obtaining necessary industry certifications, gaining and retaining employment, obtaining a GED or associate’s degree, purchasing a home, and other indicators of success.

Armed with a multifaceted analysis of existing need and capacity, a long history of providing efficient, effective, culturally competent care, and an ideal community partner in Congreso, PHMC competed for and won federal

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146 Making strategy Count in the health and huMan serviCes seCtor

funding to open a new FQHC site. The Congreso Health Center began serving patients in December 2012. By connecting data collected through the PHMC’s electronic health record system and Congreso’s ETO platform, the partnership will be able to track client outcomes across health and social service programs, truly demonstrating an impact on the whole person and the whole community.

Deep Dive: Putting It All Together and Examining Real-Time Data Across Programs With the Goal of

Improving Client Outcomes

So what does PHMC do with all of the various data systems it has devel- oped? PHMC connects individual data systems through one enterprisewide data integration warehouse called PHMC Connect. Data for PHMC Connect are first aggregated into standard reporting metrics to ensure that key indi- cators are measured across programs. Each night, data from individual pro- grams are selected and transferred automatically to the Connect warehouse.

PHMC Connect was created by applying the PHMC model of team- work, collaboration, and commitment to the PHMC mission. Connect allows PHMC senior management and nontechnical users to filter comprehensive information regarding PHMC services using a variety of filters, including age, gender, ethnicity, location, and diagnosis. Aggregate information from PHMC programs can be culled and is immediately ready for presentation. Alternatively, a deep dive of the data can be conducted, and the standard metrics developed for Connect can be examined at the program level and compared with other programs at PHMC.

PHMC Connect demonstrates that using tested techniques similar to those employed in the design of individual program systems produces a uni- fied system. For example, rather than writing a client specification and then coding and deploying to that specification, the design team based Connect on a core prototype comprising client demographics. This prototype facilitated ongoing quality projects in each source program database, simultaneously improving the source data and the aggregates in the warehouse. Connect is a stellar example of PHMC’s IS philosophy: A data system should be seen as a process, not as a product, and should be created in collaboration with pro- viders, program managers, and financial staff to meet the changing needs of clients. By integrating these processes into each of its programs, PHMC promotes the efficient operation of the programs. And by using the same approach to look across programs, PHMC seeks to provide coordinated care to its clients to create a healthier community.

REFERENCES

Falik M., Needleman, J., Herbert, R., Wells, B., Politzer, R., & Benedict, M. B. (2006). Comparative effectiveness of health centers as regular source of care. Journal of Ambulatory Care Management, 29(1), 24–35.

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Forti, M., & Yazbak, K. (2012). Building capacity to measure and manage performance. Boston, MA: The Bridgespan Group. http://www.bridgespan.org/getattachment/d0076a96- 47e9-4c4c-9ad4-106d4a3aa270/Building-Capacity-to-Measure-and-Manage-Perfor.aspx

The Health Foundation of Greater Cincinnati & the American Academy of Family Physicians. (2010). Uds mapper. Retrieved from http://www.udsmapper.org

Hendricks, M., Plantz, M. C., & Prichard, K. J. (2008). Measuring outcomes of United Way– funded programs: Expectations and reality. Nonprofits and Evaluation: New Directions for Evaluation, 119(Fall), 13–35. doi:10.1002/ev.266

Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard—measures that drive perfor- mance. Harvard Business Review, January–February, 71–79.

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http://www.bridgespan.org/getattachment/d0076a96-47e9-4c4c-9ad4-106d4a3aa270/Building-Capacity-to-Measure-and-Manage-Perfor.aspx

http://www.udsmapper.org

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