Training in Facility-Based Quantification for HIV/AIDS-Related Commodities

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(No Transcript)
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Quantification in Resource-limited settings
February 28, 2007

• Laila Akhlaghi

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Pharmaceutical Supply Management System
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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

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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

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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

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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

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Quantification Methods

• Consumption method
• Morbidity method
• Adjusted-consumption method
• Service-level projection

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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

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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

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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
  variablesfor example, prescribing practices

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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

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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

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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

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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

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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

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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

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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

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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)

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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

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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

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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

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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)

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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

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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

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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

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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

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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.

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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 intelligenceavailability 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