Hope in the Pipeline: Virtual Implementation to assess new diagnostic tools 43 rd Union World Conference on Lung Health – November 2012 J2J Lung Health Media Training Ivor Langley, Liverpool School of Tropical Medicine, UK Hsien-Ho Lin, National Taiwan University
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Hope in the Pipeline: Virtual Implementation to Assess New Diagnostic Tools
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Hope in the Pipeline: Virtual Implementation to assess new diagnostic tools
43rd Union World Conference on Lung Health – November 2012J2J Lung Health Media Training
Ivor Langley, Liverpool School of Tropical Medicine, UKHsien-Ho Lin, National Taiwan University
TB diagnostics – some challenges and opportunities - the challenges for TB diagnosis
ACCESS TO DIAGNOSISCase detection is only around 45-80% in many parts of the world
McNerney R, and Daley P (2011), Towards a point-of-care test for active tuberculosis: obstacles and opportunities, March 2011 | Volume 9 www.nature.com/reviews/micro
The introduction and scale-up of new tools for the diagnosis of Tuberculosis (TB) in developing countries has the potential to make a huge difference to the lives of millions of people particularly those living in poverty e.g.
LED FluorescenceMicroscopy GeneXpert MTB/RIF
Small PM, Pai M. (2010), Tuberculosis diagnosis - time for a game change. N Engl J Med. 2010; 363(11): 1070-1.
Ziehl NeelsenMicroscopy
Sensitivity 35-75%Specificity 99-100%Turnaround 24-48hrsCost per test $1.50Time per test ~60minsExtra Investment nil
Sensitivity 40-80%Specificity 99-100%Turnaround 24-48hrsCost per test $1.50Time per test ~55minsExtra Investment $1,250
Sensitivity 80-95%Specificity 98-99%Turnaround <12hrsCost per test $10-$17Time per test ~2hrsExtra Investment $9k-18k
Point of Care?
?Sensitivity ?Specificity ?Turnaround <1hrCost per test ?Time per test ?Extra Investment ?
TB diagnostics – some challenges and opportunities - hope in the pipeline
……to identify the most effective, sustainable, and appropriate TB diagnostic technology and algorithm for each individual context
…. by projecting the impacts on patients, the health system, and the community.
TB diagnostics – how modelling can help? - the challenge for policy makers
Frank Cobelens, Susan van den Hof, Madhukar Pai, S. Bertel Squire, Andrew Ramsay, Michael E. Kimerling (2012); Which New Diagnostics for Tuberculosis, and When?, The Journal of Infectious Diseases, DOI: 10.1093/infdis/jis188
* Mann G, Squire SB, Bissell K, Eliseev P, Du Toit E, Hesseling A, et al. (2010), Beyond accuracy: creating a comprehensive evidence base for TB diagnostic tools. Int J Tuberc Lung Dis. 2010; 14(12): 1518-24.
Do HIV+ patients benefit? Will it benefit the poor? Will drug resistant patients benefit?
How many more TB treatments required? Will it reduce wastage – false positive?
How much will it cost? What is the affect on the number of samples collected? Will it overcome bottlenecks or just move them on? Where to place the new test in the diagnostic algorithm
What will the impact be on TB incidence and prevalence?
What is the increase in patients diagnosed and cured?
How many patients will benefit if rolled out?
Where to start? How much will it cost? Is it cost effective?
How will staff be impacted?
Will it reduce patient visits and waiting time? How much quicker will patients be treated?
Will it mean more patients seek diagnosis?
What if? - New test performance changes, targeted differently, numbers grow or fall?
Will it contribute to achieving the 2015/ 2050 millennium development goals for TB?
TB diagnostics – how modelling can help? - the projected impacts that policy makers want to understand
Critical evidence is provided by :- Laboratory TestsDemonstration StudiesExplanatory Trials (Does it work?)Pragmatic Trials (Does it work in normal practice in a particular context?)
Modelling (Virtual Implementation) complements trials by applying the evidence to other contexts to predict impactsProjecting patient effects across a wide spectrum of measuresProjecting health system effects and costsProjecting impacts of scale-upAssessing cost effectiveness and sustainabilityProjecting TB incidence and other transmission impacts
SB. Squire, ARC. Ramsay, S. van den Hof, KA. Millington, I. Langley, G. Bello, A. Kritski,A. Detjen, R. Thomson, F. Cobelens, GH. Mann, Making innovations accessible to the poor through
implementation research, INT J TUBERC LUNG DIS 15(7):862–870, doi:10.5588/ijtld.11.0161
TB diagnostics – how modelling can help? - complementing trials
TRAMSMISSION MODEL Community & DiseaseTransmission Impacts
OPERATIONAL MODELPatient & Health System Effects
Berkeley Madonna WITNESS simulation tool
Virtual implementation – What is it? - bringing together operational, transmission, and cost effectiveness modelling
Katsaliaki K, Mustafee N (2010), Applications of simulation within the healthcare context. Journal of the Operational Research Society. 2010; doi:10.1057/ jors.2010.20mall PM,
The operational component of virtual implementation is:-
A. Detailed - to take account of the complex interactions that affect outcomes, cause bottlenecks, and limit capacity
B. Visual- to give a representation of the operation that enables non modellers (e.g. policy makers) to engage with the modelling and assist in its validation – not a ‘black box’.
C. Flexible- so the effects of many new and existing diagnostics options and contexts can be modelled. Also enabling ‘what if?’ questions to be addressed.
D. Output rich - so outcomes can be analysed using readily available database and statistical tools e.g. matching the WHO output requirements for monitoring implementations of Xpert MTB/RIF
E. Powerful – to enable many iterations of the process to be rapidly completed e.g. simulating 5-10 years of TB diagnosis in under an hour of real time
Virtual implementation – What is it? - operational modelling
SB. Squire, ARC. Ramsay, S. van den Hof, KA. Millington, I. Langley, G. Bello, A. Kritski, A. Detjen, R. Thomson, F. Cobelens, GH. Mann, Making innovations accessible to the poor through implementation research, Int J Tuberc Ling Dis
• Diagnostic accuracy is only one step in the whole diagnostic pathway
• In order to understand the transmission impact of a new tool, we have to understand the operational context where it is implemented
Dowdy DW, Cattamanchi A, Steingart KR, Pai M (2011), Is Scale-Up Worth It? Challenges in Economic Analysis of Diagnostic Tests for Tuberculosis. PLoS Med 8(7): e1001063
Virtual implementation – What is it?- from diagnostic tool to diagnostic pathway
TRAMSMISSION MODEL Community & DiseaseTransmission Impacts
Virtual implementation – What is it?-expanded transmission component
Sensitivity
Lin HH, Langley I, Mwenda R, et al. (2011), A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools. Int J Tuberc Lung Dis 15(8):996–1004, doi:10.5588/ijtld.11.0062
TRAMSMISSION MODEL Community & DiseaseTransmission Impacts
TRANSMISSION MODEL Community & DiseaseTransmission Impacts
OPERATIONAL MODELPatient & Health System Effects
TB Incidence rate
Time to start treatmentDiagnostic default rateOutput Input
Input Output
Lin HH, Langley I, et al. (2011), A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools. Int J Tuberc Lung Dis 15(8):996–1004, doi:10.5588/ijtld.11.0062
Virtual implementation – What is it? - bringing together operational, transmission, and cost effectiveness modelling
Combining the outputs to calculate the Incremental Cost Effectiveness Ratio (ICER)
Virtual implementation – What is it?-transmission modelling – what models cannot do
• Tell the future -- The future is molded by unpredictable events. -- Models seek to simplify a complex world. -- Comparisons are usually more useful than precise point estimates.
• Tell us which sets of assumptions are “right” -- Models can use different sets of assumptions to make different
projections, but cannot tell which projections are the right ones.
• Make decisions for people -- Decision-making is a political process; models seek only to bring
evidence into that process, and highlight where assumptions are being made.
• A measure of the cost effectiveness of a new intervention which enables interventions to be compared and prioritised.
• ICER = Incremental costs of the interventionIncremental DALY’s averted
• The ICER can be compared to theo ICER of alternative interventions in TB diagnosticso ICER of other health interventions (e.g. in malaria diagnosis)o Willingness to pay threshold of countries e.g. some have proposed
using the GDP per capita as a threshold (Tanzania $529)
Virtual implementation – Case Study – Tanzania - calculating the Incremental Cost Effectiveness Ratio (ICER)
Virtual implementation – Case Study – Tanzania - Cost effectiveness and sustainability analysis
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
LED
Additional Annual Cost to Health Service (Sustainable?)
NOTE: The size of the circle and the num-ber in the circle represent the benefits measured in DALY's averted per year of the new tool relative to LED fluorescence microscopy (Benefit)