Data-Driven Management Strategies in Public Health Collaboratives
The objective of this article is to demonstrate a data-driven management approach to effectively implement quality improvement (QI) in public health collaboratives. Using a modeled simulation, this article utilizes network data to demonstrate strategic management approaches.
Design: This article uses simulated data to demonstrate the application of data-driven management strategies. This simulation was developed using examples from real-world data on public health collaboratives.
Setting and Participants: The simulation represents a community that is just getting started working collaboratively on a public health issue. In this urban community, a number of organizations have been working both individually and in partnerships with one another for years to address the social and economic needs of its growing homeless population, led in large part by the efforts of local public health department.
Main Outcome Measure: The main outcome measure is the “network” of organizational partners. Operationalizing networks as the outcome measures allows managers to think about how to implement action strategies to improve the outcome (networks as collaboration).
Methods: These data are analyzed in PARTNER, a social network analysis program designed for use by managers and facilitators of public health collaboratives. Social Network Analysis is the study of the structural relationships among interacting units and the resulting effect on the network.
Results: Network data provide a data-driven methodology for engaging in Strategic Collaborative Management. Such data can inform strategy for improving connectivity, trust, resource distribution, and increase successful strategic planning of action steps for QI.
Conclusions: Data-driven strategic approaches to practical decision-making and program implementation are currently lacking in public health systems improvement. Such an approach leads to QI strategies, gives health departments a plan of action to meet accreditation standards, and contributes to the field in terms of improved measurement and assessment techniques.
KEY WORDS: data-driven management decisions, public health collaboratives, social network analysis, strategic collaborative management