AMDS Partners and Stakeholders Meeting · HEI # Tests (excluding wastage) •HIV+ Infants (37%) are...

AMDS Partners and Stakeholders Meeting CHAI HIV Diagnostics Forecasting Overview

29-30th September, 2014

• Introduction

• Overview of Global Diagnostics Forecasting

• Overview of Country Forecasting Methodologies

• Forecasting Example: EID Commodities

• FORLABS Introduction

• Recommendations for Future Diagnostics Forecasting

• Appendix

2

Agenda

CHAI operates programs in more than twenty-five countries around the world

Historically, CHAI has supported forecasting and procurement in these countries to promote access to high-quality medicines and diagnostics for HIV,

TB, Malaria, and Essential Child Medicines.

• CHAI country teams have historically procured commodities for EID under the UNITAID Pediatric Project

• EID quantifications were developed in coordination with Ministries of Health, country teams, and CHAI global team staff using:

– CHAI Global EID Forecasting Tool

– Country team-originated tools

• Many of these tools have subsequently been transitioned to Ministries of Health

CHAI works extensively with its program countries on HIV diagnostics forecasting, particularly for EID

CHAI’s work also supports forecasting for other HIV diagnostics, including rapid test kits, viral load monitoring, and CD4 Point of Care staging and

monitoring.

• Introduction






• Appendix

5

Agenda

CHAI’s global diagnostics forecasts estimate the market size for CD4, viral load, and EID testing in 21 high-burden countries

The global forecasts are generated by a number of sources, including:

Country and WHO-reported patient numbers

Country testing guidelines and scale-up plans

Assumptions regarding market dynamics (i.e., timing of introduction of POC, actual scale-up rates)

These global forecasts are primarily shared with suppliers to inform them of existing demand and expected future market trends

Forecasts are updated on an annual basis

CHAI’s global diagnostics forecasts provide market intelligence to suppliers

- Approach -

A “bottom-up” market forecast of viral load using country current capacity and scale-up plans demonstrates significant growth

- Global Viral Load Forecast -

1

-

5

10

15

20

25

2013 2014 2015 2016 2017 2018 2019

Mill

ion

s Total Viral Load Demand

Plasma volumes DBS volumes POC volumes Need

To generate the forecast, a number of countries were consulted in detail regarding their scale-up plans. Publically-available patient numbers, test volumes, and guidelines were used to estimate growth for the remaining

countries.

The CD4 market is expected to continue to grow modestly alongside the scale-up of viral load

0

5

10

15

20

25

30

2013 2014 2015 2016

Mill

ion

s o

f Te

sts

CD4 conventional CD4 POC

- Global CD4 Forecast -

As more POC products become available on the market, CHAI expects that some POC scale-up will begin to cannibalize some conventional testing volumes.

Though the EID DBS market is well-established, coverage remains low and there is a large loss to follow up

Coverage of EID remains low in most countries, in part due to poor linkage between PMTCT programs and infant care.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2013 2014 2015 2016

Mill

ion

s o

f Te

sts

EID DBS volumes EID POC volumes EID unmet need

- Global EID Forecast -

• Introduction






• Appendix

10

Agenda

Laboratory management within countries silo-ed, with divisions across disease areas and among partners

Complex commodity and equipment needs require highly specialized knowledge to make accurate forecasts

Poor understanding of demand and wastage due to extensive system decentralization and lack of device connectivity

Lack of standardized forecasting methodology

List of specific testing commodities and anticipated consumption rate not always available

Lack of inventory visibility, particularly at facility level

Management of laboratory systems in most countries is highly fragmented, complicating diagnostics forecasting

Countries lack supply chain consolidation and rigorous oversight of laboratory management, further challenging diagnostics forecasting and

procurement for HIV and TB.

- Key Challenges-

Consumption, morbidity, and country testing targets can be used to generate demand forecasts for various diagnostic tests

- Key Forecasting Methodologies-

Consumption data-based: Quantity of each product dispensed or consumed by facilities and labs over a given time period (i.e., 12 months)

Morbidity and target-based: Prevalence related to specific target disease (i.e., HIV prevalence in infants under 18 months for EID testing), modified by country program performance plans

1

3

CHAI relies on service data, consumption data, and country targets (performance plans) in its diagnostics forecasts to minimize wastage and more

accurately model growth.

Service data-based: Number of tests run for particular diagnostic test (this is useful in understanding wastage) 2

There are advantages and limitations to each forecasting methodology

Advantages

Forecast if patient numbers/ demographics are not known

Realistic predictor of growth

Best reflects repeat testing, quality control, and lab training requirements

13

Consumption-Based Morbidity-Based Service Statistics-Based

Based on historical consumption of commodities in time period (e.g., average monthly consumption)

Limitations

✕ Fails to meet true testing demand

✕ Often cannot account for scale-up or stock outs

✕ Consumption data is difficult to collect and manage

Based on number of patients, demographic information, testing guidelines, and usage rates per test

Advantages

Model scale up based on changes in guidelines

Accounts for full demand

Limitations

✕ Targets uncertain or aspirational

✕ Patient #, demographics difficult to collect

✕ Guidelines not always followed

✕ Does not capture repeat testing, quality control, training at the lab

Historical data captured at the program or facility level that details the number of tests performed

Advantages

Forecast if patient numbers/ demographics are not known

Use for all testing (non-HIV)

Limitations

✕ Fails to meet true testing demand

✕ Often cannot account for scale-up or stock outs

✕ Does not capture repeat testing, quality control, training at the lab

✕ Data may be difficult to capture

Use with caution

Use with caution

Most models rely on a combination of different forecasting methods and do not rely on morbidity or service statistics-based forecasts alone.

• Number of baseline and monitoring tests per patient per year for each type of test

• Different guidelines for different populations of patients, e.g. on different drug regimens

• Testing algorithms, e.g. serial vs. parallel • How many controls are performed per test

• Current ART patient numbers by site • Future ART patient targets by site • Adult vs. pediatric patient numbers • HIV prevalence rate • Loss-to-follow-up at diagnosis • Attrition over time • Migration from Pre-ART to ART

• Which instruments are used in the country and key characteristics (e.g., throughput)

• Which instruments are placed at each site • Which sites refer samples to different sites

for testing • Which products are used for each

instrument • Amount of each product used for 1 test • Pack size, price, and expiry for each product

• Product wastage as a result of spillage, incorrect measurement, expiries, or damage (typically ~3-10%)

• Assumptions on % of testing used for EQA and training

• Lead time stock, or stock on hand in between order and receipt of new stock (minimum stock)

• Buffer stock, or stock on hand kept to guard against delayed deliveries, increased consumption, or other unexpected events

• Full stock level calculation

14

Liaising with the laboratory to make assumptions and collect inputs for is critical to generate accurate and efficient forecasts

If commodities are not accurately forecast, their procurement will not be consistent with program needs, jeopardizing patient care.

- Sample Forecast Inputs -

Test

ing

req

uir

emen

ts

Pa

tien

t d

emo

gra

ph

ics

Sto

ck C

on

sid

era

tio

ns

Inst

rum

ent

an

d P

rod

uct

Lis

t

Liaising with the laboratory to make assumptions and collect inputs is critical to generating accurate, efficient forecasts

• Introduction






• Appendix

15

Agenda

•National targets • EID Algorithm •MTCT rate • Consumption Data • Scale Up plan

(growth expected) •Machine

downtime • Stock Outs

• Sample Rejection Rate

• Loss from Labs & Central Stores

• # Controls • Loss from Labs

& Central Stores

- Need - - Procurement -

# Reagents # Consumables bundles

• Product Type • # EID Sites • Stock Level •Buffer Stock

• # Labs Sites • Stock Level •Buffer Stock • Loss from Labs &

Central Stores • Product Type • Platform

# Tests (including controls)

1

2 3

# DBS kits # Samples

(including wastage)

Target # HEIs

# Tests (excluding controls)

# Samples (excluding wastage)

Example: Quantification of EID Commodities

Calculation of total demand in terms of # Samples to be collected and # Tests to be performed

Calculation of total # of product packs to be procured to fulfill the demand

Data Input

Output Intermediate Output

Starting point

Target # HEI

# Tests (excluding wastage)

• HIV+ Infants (37%) are tested again (with new sample) to Confirm HIV-Positivity

• HIV- infants (63%) are tested again at the end of breast feeding

• 50% HIV- infants lost between 1st and 2nd test

# Tests (including wastage)

# Samples (including wastage) # Samples

(excluding wastage)

3,860

5,790

5,790

• HIV+ Infants (37%) are tested again (with new sample) to Confirm HIV-Positivity

• HIV- infants (63%) are tested again at the end of breast feeding

• 50% HIV- infants lost between 1st and 2nd test

• 12 Controls Used for Every 96 Tests

6,510

5,850

• 1-3% samples rejected

• 10% Buffer Stock • 3-5% Qtrly Loss from Labs

& Central Stores (%)

# DBS

332

# Reagents

93

# Consumables

9

DBS Bundles - 20 tests Reagent Kits - 48 tests or 96 tests Lab Consumables Bundles – 960 tests P

rod

uct

s


- Need - - Procurement -

2013


Confirmatory Test

First Test

HIV- or Not tested

3rd Test

Tests

3,860

3,860

710

1,220

(37%) (63%)

36.8%

2013

5,790 Total Tests

Target # HEI

# Tests (excluding wastage)

• HIV+Infants(37%)aretestedagain(withnewsample)ToConfirmHIV-Posi vity

• HIV-infants(63%)aretestedagainattheendofbreastfeeding

• 50%HIV-infantslostbetween1stand2ndtest

# Tests (including

wastage)

# Samples (including

wastage) # Samples (excluding

wastage) 3,860

5,790

5,790

• HIV+Infants(37%)aretestedagain(withnewsample)ToConfirmHIV-Posi vity

• HIV-infants(63%)aretestedagainattheendofbreastfeeding

• 50%HIV-infantslostbetween1stand2ndtest

• 12ControlsUsedforEvery96Tests

6,510

5,850

• 1-3%samplesrejected

• 10%BufferStock• 3-5%QtrlyLossfromLabs&CentralStores(%)

#DBS

332

#Reagents

93

#Consumables

9

DBSBundles-20testsReagentKits-48testsor96testsLabConsumablesBundles–960testsP

roducts

-Need- -Procurement-

The target number of exposed infants translates in a much higher number of tests needed in consideration of the national testing algorithm for EID

End of Breastfeeding

Exposed Infants Exposed babies

• Introduction






• Appendix

19

Agenda

FORLABS – the new diagnostic forecasting tool

• Software developed in collaboration with USAID, JSI, SCMS and CHAI

• Uses consumption, service statistics and morbidity data to forecast product need for lab services

• Reports can be generated for individual diagnostic areas (CD4, Chem, Heme, VL, ect.), as well as

aggregated tests

• Provide a summary of instrument utilization rates by platform/sites (test numbers or estimated test

numbers vs. instrument capacity)

• Provide a summary of instrument diagnostic contribution (number and % of tests performed on

each instrument platform)

• Report on comparison of forecast accuracy among methodologies against observed consumption

• Offer in a dashboard a graphical representation of various reports

Capabilities

• Introduction






• Appendix

21

Agenda

A more standardized and automated forecasting could facilitate access to lower prices of diagnostics

Laboratorynetwork

TestsandPrices

FORLABS–DataCollected

Manufacturers/Donors

MarketValue

MarketNeeds

MarketOpportuni es

CapacityandProduc on

Informexpectedrevenuesandmarketvalueforexis ngand

newproducts

Informproductdesignwithkeymarketneedsandnecessarytes ng

capabili es

Informthedevice’srelevancetothe

context

Informproduc onandcapacityplanning

throughtransparentdemandpa erns

Tesng&Commodity

Forecasng

ProduconPlanningandM

arketStrategy

Demandandactualtes ngvolumes

Commercializa on&Regulatory

MarketIntelligence

Onlin

eM

arket

Dashboard

• Typesoflabs• Loca onsoflabs• Instrumentspersite

• Testsrunpersite• Pricepertest/commodity

• byhealthfacilitylevel• bytesttype• bytargetpa ents• bysector(pub/priv)

• Distributors• Supplychain• Procurementprac ce• Regulatorypathways

NewProducts/Pricing

Intelligence

LowerManufacturingCosts(LowerPrices)EarlierEntryofNewDiagnos cs

Outcome

HigherTransparencyandPredictability

Outcome

Other Key Recommendations for Future of HIV/TB Diagnostics Forecasting and Procurement

Increase use of test-based commodity calculators: Molecular diagnostic tests require dozens of commodities. Countries should be able to leverage tools that translate the number of tests desired into the appropriate number of specific commodities to order.

Integrate Forecasting into LIMS: Lab Information Management Systems (LIMS) can integrate service delivery and consumption data to produce more accurate and efficient forecasts.

Encourage use of consumption data in forecasting: Where possible, consumption data should be used to calibrate morbidity and target-based forecasts against proven demand.

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2

3

Promote use and development of standardized, web-based forecasting tools: Web-based forecasting tools can capture consumption data in real-time from separate labs, generating a more accurate understanding of demand. Where possible, countries should adopt forecasting tools that aggregate demand for multiple diagnostic tests.

4

Improve integration of forecasting across test types and disease areas: To take advantage of economies of scale as well as the integration of testing platforms, countries should move towards a more holistic approach towards forecasting for HIV/TB diagnostics.

5

Conclusion

Questions?

AMDS Partners and Stakeholders Meeting · HEI # Tests (excluding wastage) •HIV+ Infants (37%) are...

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