Teodoro Landerer, natural de San Mateo, de unos 40 años de edad,

In the United States, public health services are delivered through the collective actions of governmental and private organizations that vary widely in their re-sources, missions, and operations. This complexity in interorganizational and intergovernmental structure has led to the widespread perception among policy makers and administrators that public health agencies defy meaningful descrip-tion and comparison. Nevertheless, obtaining a better understanding of the orga-nizational and operational attributes of public health delivery systems is a critical step in elucidating pathways for the improvement of public health services.

To facilitate the production of such evidence, researchers developed a new empirical method of classifying and comparing public health delivery systems, based on their organizational structure and functional characteristics.¹⁰ This research used the IOM definition of a public health delivery system, which en-compasses the full array of governmental and nongovernmental organizations that contribute to the delivery of essential public health services for a defined community or population. The typology focuses on delivery systems operat-ing at the local level, but it can be extended to state-level systems. Related typologies developed in the health services research literature have proved ex-tremely valuable for policy and administrative decision making, as well as for ongoing research. For example, the typologies of hospital networks and sys-tems developed by Shortell, Bazzoli, and colleagues over the past two decades have served in numerous policy and administrative applications concerning the regulation, coordination, and improvement of hospital-based health care services.^{49, 50}

A typology of public health systems can enhance policy and adminis-trative decision making as well as public health research. A typology allows

“apples to apples” comparisons across communities to determine how public health services are organized and delivered. Such comparisons can form the basis of public health performance assessment activities and inform the devel-opment of performance standards for public health agencies, such as those be-ing used as part of state and national accreditation programs for public health agencies.

To develop the typology, researchers collected data through a national longitudinal survey of local public health agencies serving communities with at least 100,000 residents. The survey measured the availability of twenty core public health activities in local communities and the types of organizations contributing to each activity. In each community, the collection of organiza-tions that contributed to public health activities was defined as the local pub-lic health delivery system. Cluster analysis was used to group these local pubpub-lic health delivery systems, based on observed similarities in three characteristics:

(1) the scope of activities delivered in the community, (2) the range of orga-nizations contributing to these activities, and (3) the division of effort within the system, as indicated by the proportion of the total community effort to perform public health activities contributed by the local governmental public health agency. Data were collected first in 1998 and again in 2006 in order to examine changes in the structure of delivery systems over time.

Results of the study identified seven public health system configurations that can be grouped into three tiers, based on the scope of public health ac-tivities performed (differentiation). Three of the seven system configurations were identified as highly differentiated, meaning that they offered a broad and encompassing scope of activities. These systems generally performed more than two-thirds of the activities in each of the three IOM domains of assess-ment, policy developassess-ment, and assurance. As such, these systems were labeled

“comprehensive” in their scope of activities. Another two system configura-tions were identified as moderately differentiated because they performed about half the activities in each IOM domain. These systems were labeled

“conventional” in differentiation because they aligned closely with the scope of services performed in the study’s median community. The final two sys-tem configurations performed a relatively narrow scope of activities and were therefore labeled “limited” in differentiation. Public health systems frequent-ly migrate from one configuration to another over time, with an overall trend toward offering a broader scope of services and engaging a wider range of or-ganizations. The prevalence and attributes of each system configuration are summarized in table 6.1.

Tier I: Comprehensive 1. Concentrated comprehensive 1998: 12.5%

2006: 21.4%

• Broad scope of activities performed

• Wide range of organizations participating in activities

• Local public health agency shoulders much of the effort in performing activities

2. Distributed comprehensive 1998: 5.1%

2006: 3.9%

• Broad scope of activities performed

• Wide range of organizations participating in activities

• Effort in performing activities is distributed across participating organizations

3. Independent comprehensive 1998: 6.6%

2006: 11.6%

• Broad scope of activites performed

• Narrow range of organizations participating in activities

• Local public health agency shoulders much of the effort in performing activities Tier II. Conventional

4. Concentrated conventional (transitory system) 1998: 3.4%

2006: 3.0%

• Moderate scope of activities performed

• Moderate range of organizations participating in activities

• Local public health agency shoulders much of the effort in performing activities

• Highly transitory system 5. Distributed conventional

(modal system) 1998: 46.7%

2006: 30.9%

• Moderate scope of activities performed

• Moderate range of organizations participating in activities

• Effort in performing activities is distributed across participating organizations

Tier III. Limited 6. Concentrated limited 1998: 12.3%

2006: 18.0%

• Narrow scope of activities performed

• Limited range of organizations participating in activities

• Local public health agency shoulders much of the effort in performing activities 7. Distributed limited

1998: 13.4%

2006: 11.2%

• Narrow scope of activities performed

• Moderate range of organizations participating in activities

• Effort in performing activities is distributed across participating organizations

Source: Data from Mays GP, Scutchfield FD, Bhandari MW, Smith SA. Understanding the

organization of public health delivery systems: An empirical typology. Milbank Q. 2010;88(1):81–111.

Which system confi gurations work best in delivering public health ac-tivities? Th e answer is likely to depend in part on the institutional, political, and community context, but the public health system typology provides an empirical framework for examining this question systematically. By studying communities that change from one system confi guration to another, it is pos-sible to investigate how measures of public health performance and outcomes change in response, using statistical and econometric methods to control for general temporal trends and other confounding factors that infl uence perfor-mance and outcomes over time. Th is type of study, known as a diff erence-in-diff erence analysis, revealed that systems moving to one of the three com-prehensive confi gurations over the 1998–2006 period showed the largest gains in the perceived eff ectiveness of public health activities, as reported by lo-cal public health offi cials in these communities (fi gure 6.3). Th ese compre-hensive systems also showed larger reductions in preventable mortality in the communities they served, compared with systems that moved to con-ventional or limited confi gurations. Surprisingly, the systems with the largest defi cits in performance and outcomes were not those that moved to limited

Figure 6.3. Diff erences in self-rated public health eff ectiveness across seven confi gurations of public health systems. Note: Horizontal lines indicate 95 percent confi -dence intervals for the estimates shown in the bar graphs. Source: Data from Mays GP, Scutchfi eld FD, Bhandari MW, Smith SA. Understanding the organization of public health delivery systems: An empirical typology. Milbank Q. 2010;88(1):81–111.

Configurations 1 – 2

Configuration 3

Configurations 4 – 5

Configuration 6

Configuration 7

0 10 20 30 40 50 60 70

configurations; rather, the systems that moved to one of the two conventional configurations had the largest deficits. One possible explanation is that con-ventional systems may support too many public health activities with too few organizational partners and resources, resulting in lower overall effectiveness.

By comparison, limited systems may focus their limited resources on a smaller scope of high-priority activities. Clearly, much more research is needed to elu-cidate structural and organizational mechanisms that can be used to improve public health system performance. The typology developed through this anal-ysis can facilitate comparative studies to identify which delivery system con-figurations perform best in which contexts.

Research Example: Understanding Variation