Use of Information for Decision Making Performance of Routine Information System Management (PRISM) Assessment Training Session 6: Use of Information for Decision Making MEASURE Evaluation Date:

Session objectives Explain the importance of using data to inform program planning and policy development Define data demand and data use Identify barriers for using data/information Discuss and learn strategies for using data in program management, implementation, and decision making.

The value of data ―National policymaker, Nigeria … without information, things are done arbitrarily, and one becomes unsure of whether a policy or program will fail or succeed. If we allow our policies to be guided by empirical facts and data, there will be a noticeable change in the impact of what we do. ―National policymaker, Nigeria The quote on this slide is how a national policymaker in Nigeria summarized the value of data during a data use assessment interview with MEASURE Evaluation. This statement nicely summarizes why we are here today to discuss the importance of improving data-informed decision making.

Evidence-informed decisions lead to better health outcomes Data-informed decision making process The framework presented here illustrates the entire cycle of evidence-informed decision making. This approach illustrates the ideal. This data-informed decision making process relies on multiple inputs, activities, and systems to function effectively. Even in the best-designed M&E system, you often find that data are not being used as often as they should be. So there must be other, more fundamental elements in the decision-making context that may affect this process. In the inner circle of this graphic are the activities that need to take place: Demand for data to manage a health program or develop a health policy is clearly stated. This leads to a data collection effort. The data are analyzed, synthesized, and made available to those who use them to make a decision. A decision based on data is better than one that is not, and leads to some improvements in the health system. The outer circle explains the way in which the activities that make up this process get done. The information or M&E system needs to secure the technical and human capacity to understand the demand for data, and manage, analyze, and distribute the data. There needs to be coordination among: Many people with different job functions At different levels of the health system With varying levels of understanding about each other’s work Who together ensure that information is made available and in a format that is easily understood, and can be interpreted and used Finally, there need to be management systems and organizational support that promote collaboration among those who produce the data and those who use the data, in order for the data-informed decision making process to be complete. DATA Evidence-informed decisions lead to better health outcomes

Data demand Data demand starts with a question or problem that a stakeholder has about a type of health service or a particular health problem. To address this question or make a decision, stakeholders need to educate themselves about the available data or a summary of data sources to develop an informed solution. Therefore, data demand comes from decision makers who specify what kinds of information they need to inform a decision-making process and how to seek it out. If the information they need to inform a decision doesn’t exist or is not available, they take steps to get it. ENGAGE PARTICIPANTS: Why do you think we should concern ourselves with the demand for data? SAY: To motivate key decision makers to use data, we first want to know: Does information exist that is specific to their needs? Do they know how to navigate the vast amount of information available to focus only on what they need to know to run their health program? Those of us who design information systems need to link our efforts to specific and significant decisions being made about health services today in this country and in this context. Using an approach that first considers the demand for data will encourage greater data use by key decision makers. With PRISM, we are primarily focused on the use of information and data quality. The data need to be available and to have good quality. While demand is not explicitly expressed as an outcome of RHIS performance, the concept assumes that improving use should lead to an increase in demand for information. Demand refers to the value the decision maker places on the information, whether or not she or he is using it. The decision maker demands information if she or he: Understands what information is needed to inform the decision Proactively seeks out the information needed

Data use At health policy and management levels, data are used to: Create or revise a program or strategic plan Develop or revise a policy Advocate support for a policy or program Allocate resources Monitor a program Establish accountability Strengthen service delivery Now, let’s take a minute to discuss exactly what we mean by using data to inform program and policy decision making. ENGAGE PARTICIPANTS: How do you think data can be used for health programs or policies? [CLICK ANIMATION] SAY: Those are some great ideas about how data can be used. Some uses for data that we came up with are to: Create or revise a program or strategic plan Develop or revise a policy Advocate support for a policy or program Allocate resources Monitor a program A common data use approach for each of these tasks is that each review of data is linked to a specific decision-making process. Using data to populate a report to send to the national level or to a donor is not data use. That is data reporting. The presentation of data at a technical conference is also not data use as we define it. That is data dissemination. Both data reporting and data dissemination are important precursors to data use, but they are not linked specifically to decision-making processes.

What determines data demand and use? SYSTEMS APPROACH TECHNICAL APPROACH INDIVIDUAL BEHAVIOR POLITICS CULTURE SOCIETY Be sure to note that the political, cultural, and social contexts are important determinants of data demand and information use, because decision making, the sharing of information, and data collection and reporting all occur within these contexts. This concept of the three main determinants of data demand and information use is taken from the PRISM Framework. Decision making occurs in political, cultural, and social contexts

Data are often underused because of… Organizational structures Lack of a “data culture” among decision makers Low staff motivation Lack of technical skills and technology, particularly at local levels Ad hoc and unsustainable training Structural constraints: roads, telecommunications Unclear staff roles and poor flow of information Poor funding for M&E Political interference Reasons for underuse of data: Organizational structures can hinder efficient data management processes. Lack of a “data culture” among decision makers and low staff motivation. Lack of technical skills and information technology, particularly among staff at local levels. Training is often ad hoc and not sustainable. Structural constraints: roads, telecommunication Unclear staff roles and poor flow of information. Poor funding for M&E Political interference

Working toward a culture of information Commitment and support for high-quality data and information use at all program levels Share information between levels―feedback Establish information as an integral part of planning, problem-solving, and choosing alternatives Empower people to ask questions, seek improvements, learn and improve quality through useful information

How to access the PRISM Series This slide deck is one of nine in the PRISM Series Training Kit, which also includes a Participant’s Manual and a Facilitator’s Manual. Also in the PRISM Series is a Toolkit (the centerpiece of the series) and a User’s Kit. The PRISM Series is available in its entirety on MEASURE Evaluation’s website, here: https://www.measureevaluation.org/prism

MEASURE Evaluation is funded by the United States Agency for International Development (USAID) under the terms of Cooperative Agreement AID-OAA-L-14-00004. It is implemented by the Carolina Population Center, University of North Carolina at Chapel Hill, in partnership with ICF International; John Snow, Inc.; Management Sciences for Health; Palladium; and Tulane University. The views expressed in this presentation do not necessarily reflect the views of USAID or the United States government. www.measureevaluation.org