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An Introduction to Operations Research or How can I make my health program better?

An Introduction to Operations Research or How can I make my health program better? Dr. Mark Micek, MD, MPH December 4, 2008. The Issue. It is difficult to… …effectively deliver scientifically proven health interventions in the “real world” …translate research into health program settings

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An Introduction to Operations Research or How can I make my health program better?

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  1. An Introduction to Operations Research or How can I make my health program better? Dr. Mark Micek, MD, MPH December 4, 2008

  2. The Issue • It is difficult to… …effectively deliver scientifically proven health interventions in the “real world” …translate research into health program settings • Why? • Research generally occurs in controlled settings • Homogenous sample, controlled setting • Health programs exist in a complex setting • Heterogeneous clients, multiple settings • Dependent on external context of care-delivery system • i.e. policy, resource availability ($ and personnel), community perceptions

  3. Example of difficulty translating proven treatment into practice • HAART reduces mortality among patients with HIV • BUT many eligible HIV-positive people don’t start HAART

  4. Example of difficulty translating proven treatment into practice • Short-course ARV therapy can decrease mother-to-child HIV transmission • BUT few HIV+ women receive treatment Data from: Evaluation of United Nations-Supported Pilot Projects for the Prevention of Mother-to-Child Transmission of HIV: Overview of Findings. UNICEF, New York, 2003.

  5. How can we improve the performance of our programs in an evidence-based way? • Use the principles of Operations Research

  6. What is OR?Generic definition • “Use of systematic research techniques for program decision-making to achieve a specified outcome.” • [Population Council, 2006] • Goal = find a best possible solution to improve performance of the organization • Early examples in military, business • Use data, statistics, mathematical modeling • Goal (health care) = “to increase the efficiency, effectiveness, and quality of services delivered by providers, and the availability, accessibility, and acceptability of services desired by users” • [Population Council, 2002]

  7. 3 Core Principles of OR • Study health programs • Actively try to make the program better • Use results to improve the program Corollary: requires collaboration between managers and researchers

  8. Core principle of OR #1:Study health programs • Health program is key to health care delivery • OR usually focuses on existing program • Research problem = program problem • Research intervention = program solution • Feasible within context of entire system • Assures problems and solutions are defined by realities of the health program system • Without involvement of a health program, it’s not OR

  9. Health program as system Health Program Under managers’ control Effects of Health Program Inputs Process Outputs Outcomes Impact • Raw Materials: • Finances • Costs • Staff • Facilities • Activities: • Trainings • Supervision • Logistics • Reporting • Record keeping • Patient flow strategies • Products of program activities: • # condoms distributed • # people tested for HIV • # enrolling for HIV care • Change in health/well-being • HIV/STD incidence • # deaths • Effect on knowledge or behavior: • # youth using condoms • # women using pMTCT services • # starting ART • % adhering to ART

  10. Health programs are complex systems Test for HIV Enroll in HIV clinic CD4 testing Start HAART (if eligible) Adhere to HAART Schedule appt with clinician Pt returns to get blood drawn Enroll in HIV clinic Return for appt with clinician Clinician orders CD4 Time and drop-off Time and drop-off Time and drop-off Time and drop-off Return for appointment with clinician Schedule appt for results Blood drawn Time and drop-off Time and drop-off

  11. Core principle of OR #2:Actively try to make the program better • Better “understanding” of situation is not enough • Better can mean… • Improve access to services • Improve quality • Limit costs (find cost-effective strategies) • Improve health • Without actively trying to improve the program, it’s not OR

  12. Core principle of OR #3:Use results to improve program • Using results can mean… • Implement new strategy on local / national scale • Influence national / international policy • Dissemination of results, develop “best practices” • OR successful only if results used to improve the program • Published papers are NOT a valid indicator of OR success

  13. Corollary: OR requires collaboration between managers and researchers • Program managers/policy-makers • Should be involved in ALL ASPECTS of research process • Understand health care system • Help ensure problem is important, solution is feasible • Help ensure results will be implemented • Researchers • Understand of research methodology • Responsible of recommending and implementing appropriate research techniques • Can be the same person

  14. Broad methodologies of OR • Modeling (classic) • Develop mathematical model to mimic health care system • Manipulate to find the best possible “solution” • Optimize efficiency • Maximize Y given constraints X • Intervention-based (Population Council) • Design/test best way to deliver services • Similar to quality improvement (IHI/WHO)

  15. Intervention-based OR Act Plan Study Do

  16. Steps in intervention-based OR • Identify program problem • Usually determined in ongoing program • Routine data (M&E, surveillance) vs. program evaluation • Under control of program manager • Generate program solution • Review workflow, talk to staff/clients • Consider exploratory study if causes/solution unknown • Must be feasible • Test program solution • Level of intervention: facility vs. individual • Data measurement: routine vs. added procedures • Allocation: non-randomized (quasi-experimental) vs. randomized (experimental) • Use/disseminate results • Continue/expand successful interventions • Influence national/international policy • OR not typically “generalizable” but can be relevant for similar programs (“best practices”)

  17. Common OR study designs(Experimental/quasi-experimental) Pre-post control /non-equivalent control group Simple time-series (some control for time) Step-wedge time-series (better control for time)

  18. Example 1: HIV testing in pMTCT program in Rwanda Program problem: • 18% of women tested for HIV in a pMTCT program in Rwanda did not return for results • System has 2-3 day delay in getting HIV test results • What is a potential solution? • How could we test this solution? Source: An Approach to Rapid Scale-up: Using HIV/AIDS Treatment and Care as an Example. WHO. Geneva, 2004.

  19. Example 1: HIV testing in pMTCT program in Rwanda Problem: 2-3 day delay in getting HIV test results  18% did not return for results Potential solution: Same-day results Test of solution: Time series, dropout ~0 post-intervention Source: An Approach to Rapid Scale-up: Using HIV/AIDS Treatment and Care as an Example. WHO. Geneva, 2004.

  20. Example 2: Low number of people starting ART per month

  21. Example 2: Low number of people starting ART per month • What is the program’s problem? • Do we need more information to determine what the cause of the problem is? • What is the program’s solution? • Do we know enough to develop a solution? • What should our next step be?

  22. Identify steps required to start ART

  23. Using programmatic data:Where are patients lost? Step 1 Step 2 Step 3 Step 4

  24. Using programmatic data:What are priorities to address?

  25. Why do HAART-eligible patients not start ARVs (step 4)? • Poor follow-up also reported as reason for not starting HAART in other studies • Giordano TP et al, Factors Associated with the Use of Highly Active Antiretroviral Therapy in Patients Newly Entering Care in an Urban Clinic. JAIDS, 32:399-405.

  26. Reasons for poor follow-up Pre-HAART procedure too cumbersome Dissatisfaction with services Trouble paying transportation costs Poor understanding of clinic procedures Stigma of going to HIV clinic Death Potential solutions Change workflow around HAART-eligible patients Improve counseling Improve relationship between patients and health care workers Decentralize ARV services Improving rates of starting ARVs in HAART-eligible patients

  27. Number of HIV+ pregnant women enrolled at ART site <30 days after HIV testing 2500 2000 Total HIV + 1500 Enrolled 1000 34% 22% 76% 500 74% 0 Beira Chimoio Nhamatanda Catandica Off-site ART clinic On-site ART clinic 30% 75% On-site ART vs. Off-site ART clinic: OR 7.2 (CI 5.9-8.8, p<0.001)

  28. ART-eligible starting ART (Total and <90 days), Sofala and Manica, 2004-2007 100.0% 90.0% ART Total 80.0% ART <90days 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Caia Beira Manica Chitobe Gondola Chimoio Marromeu Catandica Ponta Gea 1o de Maio Nhamatanda Espungabera Integrated Integrated Vertical Vertical Total stated on ART: Vertical 50% vs. Integrated 65% (p<0.001) ART <90 days: Vertical 37% vs. Integrated 59% (p<0.001) N=9,193

  29. Other examples of OR

  30. OR resources • Designing HIV/AIDS Intervention Studies: An Operations Research Handbook. Andrew A. Fisher and James Foreit. The Population Council, New York, 2002. Available at: http://www.popcouncil.org/pdfs/horizons/orhivaidshndbk.pdf • An Approach to Rapid Scale-up: Using HIV/AIDS Treatment and Care as an Example. World Health Organization, Geneva, 2004. Available at: http://www.who.int/entity/hiv/pub/prev_care/en/rapidscale_up.pdf • The Breakthrough Series: IHI’s Collaborative Model for Achieving Breakthrough Improvement. Institute for Health Care Improvement. Cambridge, MA, 2003. Available at http://www.ihi.org/NR/rdonlyres/BCA88D8F-35EE-4251-BB93-E2252619A06D/0/BreakthroughSeriesWhitePaper2003.pdf • Population Council / Horizons program on HIV/AIDS OR: http://www.popcouncil.org/horizons/

  31. Next session: December 18th, 2008 Listserv: itechdistlearning@u.washington.edu Email: DLinfo@u.washington.edu

  32. Next session: December 18th, 2008 Robert Harrington Opportunistic Infections

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