Trends in health care inflation & the cost of providing oncology treatment in South Africa (and a part of the solution)

Transcription

1 Trends in health care inflation & the cost of providing oncology treatment in South Africa (and a part of the solution) Emile Stipp Chairman: IAAHS Chief Health Actuary: Discovery Session Number: TBR10

2 Agenda Insurer Overview Drivers of medical inflation Insurer: impact of high cost cases Oncology Experience Overall view of oncology in the insurer Drivers of oncology inflation High cost drug impact One part of the solution

3 Insurer Overview Drivers of medical inflation Insurer: impact of high cost cases Oncology Experience Overall view of oncology in the Insurer Drivers of oncology inflation High cost drug impact One part of the solution

4 Drivers of medical inflation 3-year average annual increase in expenditure relative to inflation 12% + 12% 10% + 10% 8% + 8% CPIX + 6% + 6% 4% +4% CPIX- 2% + 2% 0% CPIX -2% -2% Oncology GP Specialist Allied Health Hospital Chronic and acute medication CPIX Admin fee

5 Redirecting spend toward areas of highest clinical need: High-cost treatment Trans-catheter Aortic Valve Implantation Gleevec Alternative to open heart surgery for high risk patients 37 cases funded so far R321,000-R552,000 per case Patients responding well: R355,000 per year for 4-6 years Patients not responding well: R710,000 for 18 months

6 Redirecting spend toward areas of highest clinical need: Spend on oncology drugs, Total cost ( ): Top 10 oncology drugs by cost (Rm) Gleevec : Unique claimants and total expenditure Amount paid (Rm) Number of unique patients Amount paid Number of unique patients

7 Impact of high cost cases: Funding considerations Funding ability of 10,000 healthy members: High Allied benefit users 277 high Allied benefit users for 1 year Gleevec treatment 234 cancer suffers for 1 year TAVI cases 227 TAVI cases * Defined as members in Resource Utilisation Band 1 (350,000 lives during 2011)

8 Drivers of medical inflation 3-year average annual increase in expenditure relative to inflation + 12% 12% + 10% 10% 8% + 8% CPIX + 6% + 6% 4% +4% CPIX- 2% + 2% 0% CPIX -2% -2% Oncology GP Specialist Allied Health Hospital Chronic and acute medication CPIX Admin fee

9 Insurer Overview Drivers of medical inflation Insurer: impact of high cost cases Oncology Experience Overall view of oncology in the Insurer Drivers of oncology inflation High cost drug impact

10 Overall oncology paid from 2008 to 2011 Insurer Oncology Benefit Change Total Paid MOB (Rand) 1,000,000, ,000, ,000, ,000, ,000, ,000, ,000, ,000, ,000,000 R474,634, R546,667, R802,361, R942,507, Executive & Comprehensive plans: R400K benefit threshold - all additional treatment funded at 80% of the DH Rate With the exception of PMB s Priority, Saver and Core plans R200K benefit threshold - all additional treatment funded at 80% of the DH Rate With the exception of PMB s 100,000, Year KeyCare plans Cancer care within the KeyCare Oncology Network (Tier 1 / PMB) Paid MOB (Rand) Linear (Paid MOB (Rand))

11 Oncology PLPM and cost per claimant month Insurer Oncology Benefit Change Paid MOB per Life per Month (Rand) ,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 Cost per claimant month PLPM Cost per claimant month Linear (PLPM) 0

12 Breakdown of components contributing to oncology PLPM 100% 90% 13% 13% 14% 15% 80% 16% 17% 70% 60% 50% 13% 10% 23% 24% 7% 5% 40% 30% 20% 58% 60% 56% 56% 10% 0% Drugs Hospitals Radiotherapy Other Hospital: Includes radiation equipment fees, oncology treatment administered in hospital & facility costs Other: includes facility and professional fees

13 Cost of Specialty Drugs in Oncology 350,000, ,000,000 69,814, ,000,000 8,141,244 Amount Paid (Rand) 200,000, ,000, ,000, ,634, ,225, ,906,444 50,000, Benchmarked against 2008 Due to increased % of total drug spend

14 Review of high cost drugs for specific oncology conditions Drug DTPMB Yes / No Unique Patients ( ) Total Cost ( ) Average Cost / Patient (2008) Average Cost / Patient (2010) Δ Average Cost Per Patient ( ) Gleevec Yes ,670, , , % Velcade No 58 11,321, , , % Sandostatin Yes 60 14,869, , , % Herceptin No ,985, , , % Nexavar No 43 7,463, , , % Erbitux No 66 10,233,927 58, , % Vidaza No 28 4,636, , % Sutent No 45 4,988,683 53, , % Alimta Yes ,802,106 65,078 81, % Avastin No ,901,841 69,020 70, % Temodal No ,583,674 67,833 62, % Caelyx Yes ,561,322 40,483 55, % Eloxatin Yes ,982,860 38,322 47, % Mabthera Yes ,171,889 49,015 47, % Campto Yes ,795,958 37,856 39, % Thalidomide Yes ,221,408 33,900 38, % Oxaliwin * Yes 207 7,479,436 7,316 35, % Taxotere Yes ,119,502 27,734 34, %

15 Specialty drugs in oncology: patients claiming 0.50 Patients Claiming Claimants / 1000 Lives Specialty Drugs - All Specialty Drugs - Oncology

16 Specialty drugs in oncology: annual cost per patient Annual Cost Per Patient ,000 70,000 72,092 Paid Per Patient Per Annum (Rand) 65,000 60,000 55,000 50,000 45,000 40,000 55,267 42,942 60,721 44,408 48,435 35,000 30, All SD Oncology SD

17 Specialty Drug Cost Factor (SDCF) The SDCF for Specialty Drugs in Oncology is 17.0, which means that the average annual cost of providing Specialty Drugs for Oncology patients (R72 092) is 17-fold that of providing chronic drugs to patients not on Specialty Drugs (R4 239). Drug Category 2010 Cost Per Patient Per Annum Specialty Total Amount Paid Drugs Patients Treated All Chronic Total Amount Paid Drugs Patients Treated SDF 17.0

18 What does the future hold? Cumulative Effect of High Cost Drug Influx Count of drugs (Cumulative) S21 HCD other

19 Observations We have over the last number of years redirected expenditure towards oncology in South Africa the health benefits of some of the newer therapies are clear The major cost driver is the price of oncology drugs despite the increased volume of usage (diseconomy of scale) Cost increases adversely affect Insurer sustainability We continue engaging with pharma, DoH, Regulators and oncologists in an attempt to secure affordable pricing for SA One part of the solution: an integrated wellness program

20 The drivers of morbidity and mortality The Oxford Health Alliance s model 3 Behaviours Smoking No exercise Poor diet 4 Diseases Cancers, Diabetes, Lung disease, Heart disease 50% of deaths worldwide Source:1Bradshaw, et al, MRC Policy Brief no 1, March 2003.

21 Problem is one of behavioural economics Benefits are immediate, price is hidden Sickness Benefits are hidden, price is immediate Wellness Under consumption of preventive care Lack of information Over-optimism Hyperbolic discounting True efficacy of different health and wellness approaches is not well understood People tend to overestimate their abilities and health status Future rewards of a healthy lifestyle are significantly undervalued relative to cost today

22 A Case Study: The Vitality Wellness Programme in South Africa Know how healthy you are Set personal health goals Enjoy rewards

23 Vitality studies conducted VIP studies Cross-sectional study of Discovery Health members from 2003 to 2007 Determine the impact of engagement on medical claims experience and healthcare costs Risk-adjusted for covariates such as age, gender chronic status and health plan Done in conjunction with Harvard, University of Cape Town, University of the Witwatersrand and the Sports Science Institute of South Africa

24 VIP Study 1: Vitality engagement is correlated with lower healthcare costs Risk-adjusted hospital admission costs for engaged vs not engaged Not Engaged benchmark

25 VIP Study 2: Vitality engagement reduces the cost of managing chronic disease Risk-adjusted hospital cost for chronic members: engaged vs not engaged 100% Hospital cost per non-vitality member 90% 80% 70% 60% % 40% 30% 20% 10% 0% Multiple metabolic conditions Hypertension Dyslipidaemia Cancer Mental illness Beneficiaries with single conditions P = for multiple metabolic conditions, all single conditions are not statistically significant

26 VIP Study 3: Fitter people spend less time in hospital and incur lower healthcare costs 1. Admission per patient* 9.6% lower in highly active individuals vs inactive 2. Length of stay in hospital On average 0.57 days shorter for highly active individuals vs inactive 3. Cost per patient Medical costs once hospitalised R5,052 lower for highly active individuals vs inactive Thousands NR INACTIVE LO MED HI NR INACTIVE LO MED HI NR INACTIVE LO MED HI Fit people make better patients admissions, length of stay and costs are risk-adjusted

27 Vitality studies conducted Longitudinal study Longitudinal study tracking members of the Vitality Wellness Program between 2003 and 2007 who were on the plan for at least 36 months in the period member months of data Show the impact of engagement on medical claims experience comparing participant against themselves over the period

28 The longitudinal Vitality study - results Evidence of lower morbidity for members with any level of engagement Trends in claims; Year 1 = 100 * Year 1 Year 2 Year 3 Year 4 Year 5 (N=202,858) (N=142,918)

29 The longitudinal Vitality study - results Lower morbidity for engaged members Inactive After Active Trends in claims; Year 1 = 100 * 180 Inactive Before Active Year 1 Year 2 Year 3 Year 4 Year 5 Inactive to Inactive Inactive to Active Active to Active Active to Inactive

30 Data shows increasing engagement over time Engagement levels amongst longitudinal study test participants over the investigation period % 20% % of members % 13% 28% 22% % 30% 0 Year 1 Year 5 High engaged Low engaged Medium engaged Not engaged

31 Conclusion For cancer, and several other major lifestyle-related diseases, an integrated wellness program offers a potential way to mitigate the costs of expensive treatments But there is clearly still a need for a multi-sector approach to the problem of increasing incidence and costs of cancer treatment

32 References Lambert EV, da Silva R, Patel D, Fatti L, Kolbe-Alexander T, Noach A, et al. Fitnessrelated activities and medical claims related to hospital admissions South Africa, 2006, Preventing Chronic Disease 2009, Vol 6(4) Patel D, Lambert EV, da Silva R, Greyling M, Kolbe-Alexander T, Noach A, et al. Participation in Fitness-Related Activities of an Incentive-Based Health Promotion Program and Hospital Costs: A Retrospective Longitudinal Study, American Journal of Health Promotion, January 2011 Patel D, Lambert EV, da Silva R, Greyling M, Nossel C, Noach A et al. The Association between Medical Costs and Participation in the Vitality Health Promotion Programme among 948,974 Members of a South African Health Insurance Company, American Journal of Health Promotion, September 2009