1. The impact of a limited subsidy on access to antiretroviral therapy (ART) and patient outcomes in Singapore Barnaby Young Infectious Diseases registrar Communicable Diseases Centre, Institute of Infectious Diseases and Epidemiology, Tan Tock Seng Hospital, Singapore

2. Overview Financing of public healthcare in Singapore – and how HIV funding changed in early 2010 ‘Before-and-after’ analysis – Examine the hypothesis that funding changes improved ART practice and patient outcomes Some considerations for long-term affordability

3. GDP PPP, 60,410 Int$ per capita, ranked third 4 GINI co-efficient 0.459, second highest 5,6 HIV prevalence in general pop 0.1-0.3% 1 HIV prevalence in MSM 3-4% 2 Healthcare performance ranked sixth globally 3 1 Chua 2012, 2 Griensven 2010, 3 WHO 2000, 4 IMF 2013, 5 DSS 2012, 6 OECD 2012, Singapore

4. M & M & M Medisave (1984) National savings scheme – employer/employee Inpatient and outpatient bills within limits Medishield (1990) Basic medical insurance scheme Co-payment for critical illness Medifund (1993) Endowment fund established to cover medical bills which ‘the patient could not afford after exhausting all other means of payment’ cpf.gov.sg, accessed 18/6/13

5. Limits of the 3 Ms MedisaveMedishieldMedifundDrug subsidy Prior to 2009Withdrawal for ART capped at $250 per month ExcludedAntiretroviral therapy and HIV viral load excluded Nil 2010  Increased to $550 per month ExcludedIncludedNil cpf.gov.sg, accessed 18/6/13

6. Methods CDC  primary HIV treatment site in Singapore HIV sentinel cohort database – Cohort of 50% of patients newly presenting for care at CDC from 2005 (randomly selected) Extracted data for 1 st year of care, divided into two cohorts i.2005-2008 ii.2010-2011

7. 2005-82010-11P-value Subjects389256 Age42 (IQR 32-51)42 (IQR 31-50)NS Male94% NS Race -Chinese -Malay -Indian 80% 15% 2% 77% 14% 7% MSM41%56%<0.001 IVDU4%3%NS Primary education45%42%NS No income at dx31%33%NS Median CD4 + at dx181 (13%)241 (15%)<0.05 CD4 + <20053%46%NS

8. Proportion starting ART in 1 st year

9. Time to ART after a diagnosis of AIDS (CD4 + <200)

10. Initial ART prescribed (for 2NRTI + NNRTI/PI combinations)

11. Outcomes at 1 year 2005-82010-11P-value Deaths18 (4.6% )1 (0.4%)<0.01 Hospital admission (Number - mean) 1.050.72<0.01 Retention in care90%97%<0.01 Started ART60%71%<0.01 Time from diagnosis of AIDS to ART (days - median) 3915<0.01 Viral load in 1 st year of therapy 28%93%<0.001 Virologically suppressed (<1000 copies/ml) 94%96%NS

12. Analysis of outcomes by year

13. Income No incomeIncome Subjects192407 Cohort: -2005-8 -2010-11 114 78 250 157 Age45 (IQR 32-58)39 (IQR 31-48)<0.05 Primary education65%36%<0.001 Baseline CD4+<200 62%46%P<0.001 Hospital Admissions 1.380.75<0.001 Deaths12 (6.3%)5 (1.2%)<0.001 Lost to follow up13 (6.8%)22 (5.4%)NS

14. Proportion with AIDS who start ART * p<0.05

15. Conclusion Outcomes markedly improved between the two cohorts This correlated with improved access to ART – Earlier initiation after AIDS diagnosis, and at higher CD4 counts – Timing and rapidity of changes suggests this was due to the increased funding available

16. Conclusion Improvements seen in both income groups – but greater magnitude in lower income due to late diagnosis Patient data regarding Medifund, Medisave utilisation and other financial sources in each cohort would be helpful – ?ART purchased locally or overseas

17. Limitations Retrospective study Financial data based on a spot estimates of salary only (no income group heterogeneous) – Loss of income due to illness Not known why some with low CD4+ counts did not start ART  standard practice (pre- Zolopa 2009), ?too ill, psychosocial or financial

18. Future studies Means testing thresholds for Medifund eligibility has not been made public ART expensive, particularly for second-line therapies Concern over a ‘sandwiched group’ who do not qualify for Medifund assistance, and need to pay a significant proportion of household income for medical bills

19. Acknowledgments Co-investigators: Dr Arlene Chua, Dr Ng Oon Tek, Ms Ho Lai Peng, Dr Lee Cheng Chuan, A/Prof Leo Yee Sin Madeline Chua, Adriana, Chin Mei for data extraction The medical social workers at CDC