Managing the Dynamics of Drug Supply, Demand, and Health Services Utilization

1. Managing the Dynamics of Drug Supply, Demand, and Health Services Utilization A New Multi-Purpose Tool for Forecasting Drug Requirements and Resource Management Hanif Nazerali, Khalid Mohamed, Martin Oteba, and Joseph Mwoga Ministry of Health, Uganda

2. Challenges in the Uganda setting • Uganda is changing from a drug kit system (push) to an order-based system (pull) • Drug funding is decentralized and increasing rapidly through a SWAp* but management capacity is still limited • Health services are utilized only when drugs are available, and this depends on good forecasting, a responsive supply system, and efficient resource management • Forecasting in this dynamic environment requires innovative approaches *Sector-wide approach

3. New multi-purpose tool • Reports drug use indicators and other performance indicators • Identifies most common outpatient conditions and the most prescribed drugs • Forecasts PHC drug requirements and costs for 1000 outpatient cases using dual methods (prescription demand and stock consumed) • Quantifies gaps between current demand and actual supply per 1000 cases (or oversupply) • Validates records and accounts for resources

4. Study design and methods • Retrospective review of outpatient registers, stock records, and service statistics for a specified period in a cross-section of health facilities • Data entered into a customized database, with defined lists of diagnoses, drugs, and current prices (MS Access and linked Excel spreadsheets) • Performance indicators analyzed by individual facility, level, district

5. Study sample • A systematic sample of 200-400 encounters per health facility depending on level, at intervals over a 12-month period • Total 6,400 outpatient encounters at 24 health facilities in 4 districts • Comprehensive stock record review for all drugs issued during the 12-month period • Consumption data was obtained from 21/24 health facilities, and for 9 of the top 12 drugs, on average, from the 21 facilities.

6. Demographic data, diagnoses, & prescriptions for each encounter Consumption data for a specified period from stock records Health facility service statistics (e.g. OP encounters in the study period) Drug use indicators including average cost per case Ranked diagnoses and drugs by frequency per 1000 encounters Comparison of standardized drug requirement per 1000 cases based on prescriptions (demand) and consumption (supply) Customized DatabaseInputs Outputs

7. RESULTS (1)Prescribing indicators Cost in Uganda Shillings (approx 2000 USh = 1 Euro = 1 US$)

8. RESULTS (2)Prescribing in malaria/ARI

9. RESULTS (3)Most prescribed drugs

10. RESULTS (4)Demand and supply Notes: (a) Demand for CQ inj and Procaine inj is overestimated due to known errors in interpretation of dose units. (b) Includes for ampicillin 250mg at factor 3/8(c) Includes for tetracycline 250mg at factor 1/4

11. Discussion –Key Findings • Over-prescribing of injections and antibiotics overall, but some facilities are within the expected norms for injections • Cost per case is associated with high use of injections, AB, no. of drugs • Malaria with ARI is common, and ARI is treated with antibiotics regardless of classification (pneumonia or not) • 10-16 Core drugs account for 75% of prescriptions and overall cost • Demand per 1000 provides a precise forecast for core requirements while supply is unstable and consumption data are missing or unreliable

12. Conclusions and recommendations • This is a useful and robust tool that will focus available resources towards meeting demand for core drug requirements • The same tool highlights potential cost savings ensuing from better specificity of diagnosis and improved prescriber behaviour e.g. reduced injection use • A more expensive anti-malarial treatment regimen will have a dramatic impact on resource use • Repeat assessments will measure the effect of interventions, changes in resources, systems or management

13. Abstract