1. INTRODUCTION TO OPERATIONS RESEARCH Niranjan Saggurti, PhD Senior Researcher Scientific Development Workshop Operations Research on GBV/HIV AIDS 2014, Melbourne, July 22, 2014

2. Goal of Operations Research To increase the efficiency, effectiveness and quality of services delivered by providers To increase the availability, accessibility and acceptability of services desired by clients To use information collected to strengthen provision of services

3. Operations Research Process It involves 5 critical steps: 1.Problem identification and diagnosis 2.Strategy selection 3.Strategy testing and evaluation 4.Information dissemination 5.Information utilization

4. Categories of Operations Research Studies Exploratory or Diagnostic Studies  Problem isn't known Field Intervention Studies  Program approach not known Evaluation Studies  Impact not known Cost-Effectiveness Studies  Cost and effectiveness not known

5. Steps in Operations Research

6. Problem Identification Is it an important problem? To whom is it important? How can the problem be addressed by the program? What health improvements will result from solving this problem?

7. Is the Problem Researchable Do I need to do research to solve the problem? Can the problem be corrected by common sense and experience? Do I have enough time, money and qualified persons to do research? Will decision makers listen to research results? What ethical issues need to be considered?

8. Stating an OR Problem Describe the problem in terms of health issues facing the specified population(s) Describe the nature and extent of the problem Identify other program strategies that have been tried to solve similar problems Restate the problem as a question to be answered through research

9. Strategy to Solve the Problem Once an operations research problem has been identified, defined and justified a range of strategies for solving the problem can be suggested.

10. Choosing a Strategy to test Feasibility Can the program afford it? Can it be easily implemented? Will it be effective? Is there enough time to test it? Do the staff and managers want to test it?

11. Research Hypotheses, Objectives and Variables

12. Hypotheses Hypotheses is a statement that specifies the expected relationship between two or more variables that can be tested through collecting information and conducting experiment E.g. Contraceptive use will be higher in villages where the fieldworker is married than in villages where the field worker is unmarried.

13. Objectives Objectives relate to reasonable and expected contributions of the study to broad social, economic or health concerns An ultimate objective is that the study will provide program administrators/ mangers and policy makers with information that can be used to improve service delivery activities or reformulate policy.

14. Independent variables Programmatic factors that can be manipulated Strategy being tested The “cause”

15. Dependent Variables Characteristics we expect to change Outcomes and/ or impact being measured The “effect”

16. Types of Study Designs to Test Hypotheses

17. True and Quasi-Experimental Design Quasi-Experimental Design Does not use random assignment Open to many threats to validity At best, only suggestive of causality True Experimental Design Uses random assignment Protects against threats to validity Demonstrates causality

18. Units of Study in Operations Research Individuals: clients, providers, the general public Groups: facilities (e.g. clinics), villages, districts  Note: When unit of study is a group, the group not the individual must be used as variance measure

19. Symbols = Between groups not randomly assigned RA Experimental Group Control Group = Random Assignment of cases to the groups = The passage of time = Intervention = Observation = A single group of subjects X O X and O in a row - - - - - - - - - - - - - - -

20. Classic Experimental Design RA Experimental GroupO 1 XO 2 Control GroupO 3 O 4 Time

21. Pretest-Posttest Non-Equivalent Control Group Design No random assignment Experimental GroupO 1 XO 2 Control GroupO 3 O 4 Time - - - - - - -

22. Time Series Design Repeated measures on the same group over time No control or comparison group Experimental GroupO 1 O 2 O 3 X O 4 O 5 O 6 Time

23. Non-Experimental Designs Case Study Experimental Group X O 1 One Group Pre-test/Post-test Experimental Group O 1 X O 2 Time

24. Good Design to Study Integrated Services PROGRAM X YES PROGRAM X NO PROGRAM Y YES X+YY PROGRAM Y NO X0

25. Overview of Data Collection Methods Quantitative methods describe what people do (e.g, how many people are using IUD). Need a lot of people for statistical analysis if the rates of usage is low. Qualitative methods explore why people think and behave as they do (e.g., why difficult to use IUD). Need a lot of in-depth information from few people.

26. Ensure Results are Used Plan a utilization strategy that anticipates what actions are needed to change the way services are currently implemented Allow sufficient time, funds and qualified persons to do a good job