Quantification in Resource-limited settings

2. Quantification in Resource-limited settings February 28, 2007 Laila Akhlaghi

3. Pharmaceutical Supply Management System

4. What Is Quantification? • A process that involves estimating— • Quantities of a specific item needed for a procurement • Financial requirements needed to purchase the items • Estimating needs within a given context— • Finances • Human resources capacity • Storage capacity • Capacity to deliver services

5. Objectives of Good Commodity Quantification • Consistent availability • Adequate supplies for projected scale-up/rollout • Minimal wastage • No overstocking • Cost-effectiveness • Rational adjustments • Easy management • Meeting demand • Satisfied clients

6. Applications of Quantification Methods (1) • Calculate needs for— • Procurement (for example, central bulk purchases) • Forecasting (for example, for manufacturers) • Global Fund for AIDS, Tuberculosis, and Malaria (GFATM) Procurement and Supply Management (PSM) plan and other donors • Plan for new or expanding programs • Prepare and justify a drug budget • Optimize medicines budgets based on priority health problems to be treated and the most cost-effective treatment approaches

7. Applications of Quantification Methods (2) • Estimate storage needs • Calculate emergency needs for disaster relief and epidemics • Resupply an existing supply network that has become depleted of products • Compare current medicines consumption with public health priorities and usage in other health systems

8. Quantification Methods • Consumption method • Morbidity method • Adjusted-consumption method • Service-level projection

9. Consumption Method • Uses data on medicines consumption • Predicts future needs most accurately when current usage patterns will continue • Requires reliable consumption data • Consumption data may or may not reflect rational prescribing or rational use of medicines • Comparison with morbidity-based method allows an estimate of the extent to which current consumption— • Addresses priority health needs • Reflects rational use of medicines

10. Morbidity Method • Used for new programs or for programs where consumption data are not available • Forecasts the quantity of medicines needed for prevention/treatment of specific diseases based on projections of disease incidence • Requires accurate information on the population, morbidity, and clinic attendance, and uses standard treatment guidelines (STGs) to project needs • Most complex and time-consuming of all four methods • Calculations can be complex

11. Adjusted-Consumption Method • Used for new sites or new programs • Can be population-based or service-based • Uses data from an existing system to extrapolate requirements for a new system based on population coverage or the service level to be provided • Can be difficult to match/adjust for all variables—for example, prescribing practices

12. Service-Level Projection • Used for estimating budget needs • Does not estimate quantities of medicines needed • Uses the average medical supply procurement cost per attendance or bed-day in different types of health facilities in one system to project needs for similar types of facilities in another system • Limitations: variations in facility use, attendance, treatment patterns, supply system efficiency

13. Forecasting Challenges in Resource-Limited Settings • Lack of knowledge or tools • Lack of data collection mechanisms • Lack of coordination • Complicated forecasts • Antiretrovirals for HIV • Antimalarials for malaria

14. Typical Practices • Lack of data collection mechanism and/or analysis • Based on previous orders/requests, plus a percentage • Stock-outs not reviewed/included • Buffer/safety stock is not included • Consideration for filling the supply pipeline is not included

15. Data Collection and Reporting: Lessons Learned (1) • Inaccurate or lack of data is universally identified as a major constraint to successful quantification • Aggregating patient data to report can be problematic, especially as programs scale up/roll-out • Can be difficult to extract and aggregate data needed from manual tools, especially for pediatrics • Sites can lose motivation to report if supplier is not responsive or products and quantities supplied are inappropriate to needs

16. Data Collection and Reporting: Lessons Learned (2) • A concerted and coordinated team effort is needed to: • Develop and sustain a system for data collection • Harmonize tools and reporting systems • Develop, print and disseminate tools to sites • Provide standard operating procedures for, and advise and train sites on data collection and aggregation • Support efficient reporting by sites • Give consistent and responsive feedback to sites • Consider and plan for computerized tools • Involve users in tool development and provide responsive feedback

17. Coordination Mechanism for Procurement and Quantification (1) • Mechanism to inform decision making at the central level for effective procurement and quantification • Should be inclusive of all stakeholders— • CMS • National committees (malaria, AIDS, TB, etc…) • MOH • Donors • Facility staff • Public and private sectors • Monitors and coordinates implementation of activities

18. Coordination Mechanism for Procurement and Quantification (2) • Challenges • Building consensus among MOH, donors, facility staff, CMS, and other stakeholders • Lack of accurate data • Quantifying for children • Delayed implementation of recommendations

19. Complicated Quantification: ARV and ACT Products • Often have a short shelf life • Are expensive • Require secure storage • Require refrigeration or temperature control • Pediatric formulations • Inappropriate pack sizes • Limited options on formulations • New product; little experience with use • Proliferation of substandard quality medicines (ACTs)

20. Complicated Quantification: Treatment of HIV • Scientific field is rapidly evolving • Effect of stock-outs is serious • ART is for life • ARVs are used for prevention and treatment • Multiple drug therapy is required • Three or more medicines, and all must be available • Can be fixed-dose combinations, patient packs, and/or single products • Multiple regimens are used • Resistance evolves quickly and is inevitable

21. Complicated Quantification: Treatment of Malaria • Standard treatment guidelines changes due to resistance and new products (ACTs) • Failure of first-line medicines does not always mean patient will be transitioned to second-line treatment • Multiple regimens are used • Simple malaria (uncomplicated) • First line • Second line • Severe malaria • Intermittent preventive therapy (IPT) • Bednets impregnated with insecticide

22. Complicated Quantification: HIV Programmatic Issues (1) • Lack of data: • Historical data (consumption) • Deaths • Loss to follow-up • Transfers out • Changes in regimen • Weight; pregnancy; treatment failure; adverse drug reactions (ADRs); co-morbidities • Pediatrics • Changes in dose; wastage of liquids

23. Complicated Quantification: HIV Programmatic Issues (2) • Unpredictability in Scaling Up Rate • Political push for rapid and enormous scale-up • Limited capacity to deliver services • Limited capacity of supply systems • Availability and demand for HIV testing • Client demand for ART • Level of funding available by government or delays in disbursement of donor funds • Unpredictability in Product Use • Profile of enrolling clients compared with continuing clients • Prescribing practices • Client characteristics (weight; pregnancy; co-morbidities; treatment-naïve; treatment failure; ADRs; resistance; high-risk or low-risk HIV exposure; pediatric issues)

24. Complicated Quantification: Malaria Programmatic Issues • Lack of data on: • Population/conditions to treat • Dose dependent on patient weight/age group • Population data does not match with treatment guideline recommendations • Endemic areas/epidemics/refugee populations • Quantity of second-line therapies • Depend on treatment failure of first-line therapy • Previous consumption • Incidence of malaria not readily available • Need to use incidence of fevers • Sharing of bednets

25. Complicated Quantification: Supply Issues (1) • New and imperfect market • Supply and demand forces are influenced by factors not usual in a “perfect” competitive environment • Oligopoly • Rapidly changing market • Prequalification or regulatory approval • Special pricing and donations • Unpredictable and long lead times, shortages • Lengthy public sector procurement process

26. Complicated Quantification: Supply Issues (2) • Suppliers’ preference for long-term forecasts and assurances of procurement • Capacity of manufacturers to meet demand (2) • Problems in meeting demand for active ingredients • Inaccurate forecasting leading to insufficient production • Lack of flexibility to increase production to meet short-term needs • Lack of incentives to manufacture with limited guaranteed markets

27. Complicated Quantification: Supply Issues (3) • Demand • Characterized by extreme uncertainty • Financing • Major purchasers mainly using donor funding • Public and not-for-profit sector demand are increasing relative to private sector demand • Variable user “demand” for, prescribing and use of, and response to ACTs

28. Summary (1) • Quantification requires a multitude of data from various sources. • Several different tools can be used to manage data collection and reporting. • A concerted and coordinated team effort is needed to inform stakeholders on data needs and to support sites in data collection and reporting for quantification.

29. Summary (2) The success of quantification can be improved by— • A team approach to making assumptions and decisions and share information on— • Potential changes in demand and prescribing practices • Potential changes in rate of scale-up or roll-out • Market intelligence—availability of product • Epidemiological data sets and consumption data sets • New science • Successful problem-solving approaches (and failures) • Cross-checking data, information, and projected needs • Using ongoing monitoring of projected vs. actual needs to adjust assumptions