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Meyer

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Meyer

  1. 1. Modelling the cost of ART for prevention Gesine Meyer-Rath1,2, Mead Over3, Lawrence Long21 Center for Global Health and Development, Boston University, Boston, US. 2 Health Economics and Epidemiology Research Office, University of Witwatersrand, Johannesburg, South Africa. 3 Center for Global Development, Washington DC, US. Health Economics and Epidemiology Research Office HE RO 2 Wits Health Consortium University of the Witwatersrand
  2. 2. PreventionThings are changing = Prevention Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  3. 3. What’s in a projection model?• Epidemiological function – captures the impact of medical policies on the biological consequences, both beneficial and adverse• Cost function – captures the economic consequences of the policy Kahn, Marseille, Bennett, Williams & Granich, October 14, 2011 Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  4. 4. Identities vs. functions• Cost accounting identity – Too rigid to model large scale changes over periods of more than a few years – Not appropriate to model ART as prevention• Cost function – More plausible characterisation and projection of cost Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  5. 5. The cost accounting identity tends toover-estimate costs at different prices on Economizing Total Cost accounting the higher Cost identity priced input saves costs TCAI TCF TC0 Cost function Price of i’th input (e.g. Tenofovir)
  6. 6. The cost accounting identity tends tounder-estimate costs at different scales Total Diminishing Cost Cost returns function eventually increase costs TCF TCAI TC0 Cost accounting Fixed identity cost Annual output (e.g. patient-years)
  7. 7. Use of cost functions in the literature• Reviewed 8 literature databases from1988-2011 + References + Grey literature for ART costing• Included all with a modelled cost• Compared by: economic evaluation method, type of model, time horizon, outcome metric, input cost Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  8. 8. Results: Literature Review• 45 published articles, 1 conference abstract and 4 reports – 38 for single countries – 4 for wider regions – 8 were global• 5, all for single countries, considered the impact of ART on transmission Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  9. 9. Results: Literature Review - including transmissionPaper, year (country) AnalysisOver 2004 (India) HIV/AIDS treatment and prevention in India: Modelling the costs and consequencesGranich 2009 (South Africa) Impact of universal voluntary testing and immediate treatment (UTT) on HIV incidence and prevalence and annual costLong EF 2010 (United States) The cost effectiveness and population outcomes of expanded HIV screening and ART in the USHontelez 2011 (South Africa) Incremental cost benefit of ART initiation at CD4 cell count threshold < 200 vs. <350Schwartländer 2011 (Int.) Incremental cost effectiveness of “investment approach” to achieving universal access to HIV prevention, treatment, care and support by 2015Granich 2012 (South Africa) Expanding ART for Treatment and Prevention of HIV in South Africa: Estimated Cost and Cost-Effectiveness 2011-2050 Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  10. 10. Factors influencing costPaper Factors influencing input cost (Including in sensitivity analysis, SA)Over (2004) Time on treatment (first 3 years vs. year before death); health state (symptomatic, non-AIDS | AIDS); unstructured vs. structured treatment provision; SA: Cost not includedGranich (2009) Drug cost by FL/ SL, otherwise constant unit cost; No SALong EF (2010) One regimen cost only; health state (untreated symptomatic | untreated symptomatic | treated symptomatic | untreated AIDS | treated AIDS); SA: Cost not includedHontelez (2011) On ART cost by baseline CD4 cell count (100|200|350) for first 3 years, then uniform; drug cost by FL/ SL; SA: Cost varied by +/- 33%Schwartländer (2011) “Average cost per patient of antiretroviral therapy is assumed to decline by about 65% between 2011 and 2020, with a large proportion of the cost savings after 2015 coming from an increasing shift to primary care and community-based approaches and cheaper point-of-care diagnostics”; No SAGranich (2012) Drug cost by FL/SL; Laboratory cost by first year on regimen or > 1 year; Inpatient / outpatient cost based on treatment status; SA: Varied ART, monitoring, inpatient costs based on data available for South Africa. Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  11. 11. Potential determinants of a cost function• Most modelled estimates of ART to date use cost accounting identities, with minimal use of cost functions• If a more flexible cost function where to be used, which variables should be included? Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  12. 12. Treatment characteristics• Regimens, health states and time on treatment• More complex = higher treatment costs• Distribution into first and second line• Distribution across CD4 count strata• Time on treatment dictating likelihood of an event Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  13. 13. Factor pricesThe development of the price of d4T+3TC+NVP 2000 - 2008MSF Campaign for Access to Essential Medicines: Untangling the Web of Antiretroviral PriceReductions. 11th edition, July 2008 Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  14. 14. Scale• Marginal and average cost for hygiene outreach in 2000 Int’l $• Adjustment for scale used in WHO- CHOICE generalized CEA• Modelled on world-wide GPS data (clinic and population density)• Calculated transport cost of goods, fixed and supervision costs; health centre cost excludedJohns B, Baltussen R: Accounting for the cost of scaling-up health interventions.Health Econ. 13: 1117–1124 (2004) Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  15. 15. Experience of facility and program Menzies et al, 2011, PEPFAR data. Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  16. 16. Scope and distribution• Analysis of cost of ART provision amongst different models of care• 4 settings in South Africa (GP/ MP/ EC)• Annual per patient Rosen et al: The outcomes and outpatient costs of different models cost in each of antiretroviral treatment delivery in South Africa. Trop Med Intern Health 13(8):1005-15 setting (2008) Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  17. 17. Quality of care• “In care and (not)responding”defined by VL, CD4and new WHOstage 3/ 4conditions• “No longer incare” pt died orwas lost to follow-up in the first 12months Rosen et al: The outcomes and outpatient costs of different models of antiretroviral treatment delivery in South Africa. Trop Med Intern Health 13(8):1005-15 (2008) Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  18. 18. Technical efficiency• Production of good/service without waste• Incentives: Salaries (private vs. public)• Non financial incentives: Encouragement and supervision• Technical changes: take into account things not currently used / invented Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  19. 19. Worked example of how a flexiblefunction can alter cost projections• Use the example of Granich et al’s 1999 article on Universal Test and Treat in South Africa• Change only one assumption: – Instead of constant returns to scale, allow for increasing returns to scale at the facility level• Requires data or theory on the size distribution of ART facilities Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  20. 20. Steps in the analysis• Use empirical size-rank distribution of South African ART treatment facilities in 2010• Project the size-rank distribution of facilities to expand to full-coverage and then to shrink as need declines• Generate a family of facility-specific average cost functions scale elasticities < 1.0• Project future cost at each scale elasticity Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  21. 21. Current and projected sizedistributions of ART facilities in SA Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  22. 22. Health Economics and Epidemiology Research Office HE RO 2Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  23. 23. Family of South African facility-specific averagecost curves with scale-elasticities from 0.5 to 1.0 Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  24. 24. With a scale–elasticity of 0.7, peak costsand cumulated costs will be 40% greater Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  25. 25. Conclusions on the potential value of flexible cost functions • A flexible cost function can give very different cost projections over the long run • Depending on the elasticity of scale alone, the cost of UTT could be up to 75% greater than projected under the constant returns assumption • It behooves modelers to pay as much attention to their cost specifications as to their epidemiologic ones. Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  26. 26. Annex slides
  27. 27. Peak costs and cumulated costs vary with the assumed scale-elasticity Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  28. 28. Calibration of the average cost function to South African data for 2010/11:How we fit the family of average cost functions Value of σ Value of (σ – 1) Percent increase in total Percent decrease Cost of using an entire ART facility to treat a cost associated with a in average total single patient 1% increase in output cost associated (Scale elasticity) with a 1% increase in Derived from Meyer- Deflated to match output Rath et al Granich et al costs Constant returns 1.0 0 $924 $800 to scale 0.9 -0.1 $1,976 $1,711 0.8 -0.2 $4,187 $3,625 Increasing returns 0.7 -0.3 $8,791 $7,611 to scale 0.6 -0.4 $18,296 $15,840 0.5 -0.5 $37,763 $32,695 Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand
  29. 29. Impact on peak-year and cumulated cost of a Universal Test andTreat policy in South Africa of alternative assumptions regarding economies of scale in ART service delivery Value of σ Costs of Universal Test and Treat policy Total cumulated cost without discounting in Per cent increase in total cost constant 2010 USD associated with a one per cent Per cent of total increase in output (Scale Peak cost in billions Total cost in billions above constant elasticity) of USD of USD returns to scale Constant returns to 1.0 $3.5 $74.6 0.0% scale 0.9 $83.6 12.0% $3.8 0.8 $93.6 25.4% $4.1 Increasing returns to 0.7 $104.8 40.4% scale $4.4 0.6 $117.2 57.0% $4.7 0.5 $131.0 75.4% $5.1 Health Economics and Epidemiology Research Office HE RO 2 Health Economics and Epidemiology Research Office Wits Health Consortium University of the Witwatersrand

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