Connecting people to better healthcare. Malawi, May 19th 2017

Transcription

1 Connecting people to better healthcare Malawi, May 19th 2017

2 Delivery Financing Mobile health connects demand and supply Health insurance/savings Research and Advocacy Loans for providers Demand Higher Supply Higher Trust Mobile health Higher Quality standards Higher Access to treatment mhealth Patient Wallet M-TIBA Equity investments 1

3 Digitalization disrupts exchange in all markets Core drivers for this disruption Availability of (real time) data/information Reduction of transaction costs Enforcement of predictable contracts 2

4 Transformational change of M-PESA in Kenya Widely used Income redistribution Trusted Used by 85% of population 66% of Kenya s electronic payments USD 1.3 b per month transaction value Banks the unbanked Remittances from: Higher to lower income Urban to rural Healthy to sick Instant transaction No 1 brand in Kenya Source: Central Bank of Kenya, Safaricom financial results H1 2015, Centre for Brand Analysis 3

5 In 2016, we developed a payment platform that connects payers, patients and providers, built on MPESA, in partnership with Safaricom and CarePay Payers self, families, employers, donors, insurers, etc. Patients the people who need care Healthcare Providersclinics, hospitals, pharmacies, etc. Save, Receive Send & Spend Money and Entitlements for Healthcare only Overall progress 4

6 700,000 Fast uptake since launch last Summer: over people on M-TIBA, and counting! Number of registered vs activated lives in MHF # of registered lives vs # of activated lives 600, , , , , , , , , , , , , ,140 63,568 83, , ,480 4,296 11,728 23, ,693 70,337 53,129 May 702 1,409 June 3,632 July August 9,582 21,012 September October November December January February March April # of lives registered # of lives accepted terms and conditions 1. People connected to M-TIBA 5

7 370 providers are connected to M-TIBA; the number of transactions is growing 28th June, Clinic in Kibera Criteria >20-30 patients License Connectivity Quality improvement/ high potential for business & quality development (as observed by RM) Preferably being part of existing quality program March, clinics in Nairobi and Central region 6

8 Scalability Expansion across Africa is possible, with any telephone operators or other partners Based on unique identifiers, in Kenya for ex. M-TIBA is based on M-Pesa, which is in turn based on registered National Identity Cards Local data storage, privacy issues are taken care of in accordance with local laws & regulations Transactions per month December January February March 7

9 Advantage #1: Fast, actionable data.265% Total spendings divided by type consulation drugs inpatient laboratorium medical camp other procedures Distribution of saved amount per saving %.653% 3.072% 6.809% % KES KES KES KES KES 1-50 KES Chlorpheniram ine Syrup Paracetamol Syrup Cetrizine Tablets 10mg Ibuprofen Tablet (400mg) Omeprazole Tablet 20mg Top 10 medication (by transactions) Paracetamol Tablet (APC Co- Trimoxazole Amoxycillin Capsules Albendazole Tablet (400 Tenofovir 300mg + 3,356 3,337 2,855 4,070 3,525 4,959 5,859 5,563 6,794 7, Top 10 Diagnoses (by unique patients) Acute upper respiratory infections of multiple and Respiratory disorder, unspecified Vasomotor and allergic rhinitis Human immunodeficiency virus [HIV] disease Dermatophytosis Anaemia other/unspecified Unspecified intestinal parasitism Infectious gastroenteritis and colitis, unspecified Sweating problem Acute recurrent tonsillitis due to other specified organisms 1,901 1,801 1,801 1,704 1,704 1,556 2,695 2,302 4,321 7,

10 Advantage #2: introducing new financing types Health wallet post-paid Insurance with premium financing Out-of-pocket cash Risk-pooling via shared wallet Out-of-pocket Lipa na M-PESA Hybrid bundled product Health wallet pre-paid Insurance pre-paid Five new health financing types are created of which three are based on prepayment Financing types do not have to be sequential

11 Advantage #3: mobile-data segmentation Segments composed from different parameters, e.g. vulnerable groups, economic & financial behavior, health risks Segments not mutually exclusive and some yet to be quantified (work in progress by Safaricom and PharmAccess) Donors/payers are invited to design their own mobile wallet propositions for target segments (e.g. vouchers)

12 The Gertrudes outreach program Objective Nairobi Kenya Gertrudes Hospital Clinics is slums ~50,000 clients HIV/AIDS treatment ~2,500 patients M-Tiba as digital health platform Disclosure: Gilead Foundation is cofunding this program

13 The M-TIBA platform creates unprecedented insight in medical and financial aspects of the care process Money in Care process Data out 1. Patient falls ill Health financing products create money flow into the system Eg: savings, insurance, remittance, donor 2. Diagnostics of illness 3. Treatment of illness 4. Claim for diagnostics and treatment Data collected along the patient pathway 12 Socio-economic classification patient Diagnostics, procedure, test Treatment, medicines, adherence Claim data, financial

14 Data Patient journeys insight 13 13

15 Patients who ever received ART # of HIV diagnosed patients ever on ART % of HIV diagnosed patients ever on ART divided by sex 164 Male patients on ART Female patients not on ART patients on ART patients not on ART 0% 20% 40% 60% 80% 100% % of HIV diagnosed patients on ART divided by age groups 0-3y y 16+ According to the Kenyan guideline 100 % of the people should be on ART, in the smiles program 93 % of the patients received treatment. unknown % 20% 40% 60% 80% 100% patients on ART patients not on ART 14

16 First and second line regimens # of HIV patients on first and second line treatment HIV patients on first and second line treatment divided by sex Male Female st line 2nd line unusual 1st line 2nd line unusual 0% 20% 40% 60% 80% 100% HIV patients on first and second line treatment divided by age groups y 4-15y st line 2nd line * ART based on last treatment If ART is optimal 100% is on 1 st line % 20% 40% 60% 80% 100% unusual 15

17 Viral load tests # of HIV diagnosed patients on ART who did a viral load test 110 Female % of HIV patients on ART with a VL test - by sex % 20% 40% 60% 80% 100% Patients with one viral load test Patients without a viral load test Patients with more than one viral load test % of HIV patients on ART with a VL test - by age 0-3y y Patients with one viral load test Patients without a viral load test Patients with more than one viral load test % 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Patients with one viral load test Patients without a viral load test Patients with more than one viral load test Not all HIV patients have already a full year follow-up in the program 16

18 Drugs toxicities tested by HIV patients on ART # of Full Heamogram and Haemoglobin tests by HIV patients currently on AZT Patients on AZT Patients on TDF # of Serum Creatinine, Urea + Electrolytes + Creatinine (UEC), and/ or 3 Creatinine test by patients currently on TDF # of ALT liver and liver function tests by HIV patients currently on NVP Patients on NVP patients with no test patients with 1 test patients with no tests patients with 1 test patients with no tests patients with 1 test patients with 2 tests patients with 3 tests patients with 2 test patients with 3 test patients with 2 tests patients with 3 tests Patients on 2e line ART # of lipid glands test done by HIV patients on 2e line ART (in year one) N 1 # of glucose test by HIV patients on 2e line ART (in year one) patients with 1 test Patients on 2e line ART * ART based on last treatment Not all HIV patients have already a full year follow-up in the program 17

19 Provider initiated HIV testing HIV testing by TB, STI and Pregnancy # of TB patients performing a HIV test 5% # of STI diagnoses followed by a HIV test 7% HIV testing for pregnant/laboring women 5% HIV I & II Rapid Test HIV I & II Rapid Test no test HIV I & II Rapid Test 95% * N = 1105 * N = 59 * According to the Kenyan guideline 100 % of the * According to the Kenyan guideline 100 % of the patients who developed TB should be tested on HIV. patients who developed a STI should be tested on In the smiles program currently 5% of the TB HIV. In the smiles program currently 7% of the STI diagnosed patients have been tested on HIV. diagnosed patients have been tested on HIV. * Patients already diagnosed as HIV, excluded from this analysis 93% * STI includes: Other and unspecified syphilis, Gonococcal infection, Chlamydial infection of pelviperitoneum and other genitourinary organs, Urogenital trichomoniasis, Herpesviral infection of genitalia and urogenital tract, Anogenital (venereal) warts, Candidiasis of vulva and vagina, Orchitis and epididymitis, Balanitis, Other female pelvic inflammatory diseases, Other inflammation of vagina and vulva, Gonorrhoea female, Gonorrhoea malex * N = % * According to the Kenyan guideline 100 % of the pregnant women should be tested on HIV. In the smiles program currently 5 % of the STI diagnosed patients have been tested on HIV. * Woman tested for HIV when: pregnancy (diagnosis code Z33) 18

20 HIV diagnosed women in reproductive age - Family planning % of HIV diagnosed women in reproductive age (15-49 years) with a family planning consultation Distribution of # of family planning consultations for HIV diagnosed women in reproductive age (15-49 years old) 2% women without a family planning consultation women with at least one family planning consultation * N = % women without any family planning consultation women with one family planning consulation women with two family planning consultations women with three family planning consultations * According to the Kenyan guideline sexual active HIV diagnosed women should have 4 family planning consultations per year. In the smiles program currently 2 % of the HIV diagnosed women in reproductive age has had a family planning consultation. * A consultation has been counted as family planning consultation when diagnosis code was registrated as Family planning consultation or a visit included the following item codes: Family planning consultation, Implant Removal, Implant Insertion, Family planning consultation, Condoms, insertion Of Iucd, Removal Of Iucd, Microgynon Tablets * Be aware that from the Carepool database it is impossible to know if women are sexual active. 19

21 April May June July August September October November December January February March April 2017: Partnership with NHIF launched 800 Gertrudes Smiles, average costs per month per enrollee

22 The Great Escape To those who regularly visit Sub-Saharan Africa, the pace of change is indeed astonishing, and there are many reasons to be optimistic about the region. We should, however, also realize that very little has changed for the poor in rural settings, and that the lives of those who left for urban slums are extremely difficult. To include these groups in the great escape from poverty is the big challenge ahead. Joep Lange, July

23 Thank you! 22