Quality Improvement in Public Health: Monitoring & Evaluation links policy decisions to program development

Issue:  How do we know that a policy or program is making a difference? What makes a good performance management plan?  Description:  Public health is a data-driven enterprise.  Yet the evidence supporting an organizational or program change doesn’t mean that there’s the infrastructure, workforce skill, or revenue streams to effect implementation, scaling-up processes, and sustainability.  Lessons Learned: Well-designed monitoring & evaluation (M&E) highlihts what is working; it also allows planners and implementers to identify missteps early, learn from mistakes, meet challenges, and productively change course to achieve both short-term goals and long-term impact. This presentation will look at 5 guiding principles for M&E and examine a framework for linking M&E data with action.  M&E approaches articulate timeframes, consider both data sources and uses, recognize constraints that inhibit effective data use, and include technical, behavioral, and organizational factors. Concrete examples will be discussed to highlight typical challenges. For example, M&E findings related to 33 criteria were used to enhance patient decision-making to enroll in directly observed therapy (DOT) and to identify which process components were most crucial. Although meeting all the standards was not consistently associated with a patient's accepting DOT, not meeting the standards was almost invariably strongly associated with patient refusal. Conclusion: Effective policy planning and program development requires strategic and rigorous monitoring and evaluation. M&E is solution-focused.