open models healthcare v5 7
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THE FUTURE OF OPEN MODELS FOR DIABETES CARE
2012 DiabetesMine Innova1on Summit
Ikhlaq Sidhu, Megha Raghavan UC Berkeley
Fung Institute for Engineering Leadership UC Berkeley
Macro Market Forces in Healthcare
• Healthcare Spending: $2.2T in US$6.6T Globally
• Growing Need: Baby Boomer + Diabesity
• 18% of the US economy!
• Price Pressure and Declining Margins
• Chaos!
Source: Centers for Medicare & Medicaid Services, Office of the Actuary: Data from the Na1onal Sta1s1cs Group, October 2010
Year
$0
$1
$2
$3
$4
$5
10%
15%
20%
25%
2000 2005 2010 2015 2020
2019: $4.6T
2011: $2.7T
Total NaDonal
Health Expenditures
2
$2,729 $2,870 $2,902 $3,129
$3,353 $3,470 $3,677 $3,696 $3,737
$3,970 $4,063 $4,079
$4,627 $5,003
$7,538
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
Per
Capi
ta S
pend
ing
- PP
P Ad
just
ed
Total Health Expenditure per Capita, U.S. and Selected Countries, 2008
Source: Organisation for Economic Co-operation and Development (2010), "OECD Health Data", OECD Health Statistics (database). doi: 10.1787/data-00350-en (Accessed on 14 February 2011). Notes: Data from Australia and Japan are 2007 data. Figures for Belgium, Canada, Netherlands, Norway and Switzerland, are OECD estimates. Numbers are PPP adjusted.
Macro Trend #2: A Larger Market but with Lower Margins
Annual Revenue Growth
Source: 2011 free cash flow and revenue growth projected by JPMorgan for 12 large medtech companies: ABT, BCR, BAX, BSX, COV, EW, ISRG, JNJ, MDT, STJ, SYK, ZMH.
0%
4%
8%
12%
16%
20%
2004 2006 2008 2010
4
Approximate Breakdown
• Services = 80% • Devices / equipment = 8%
• Pharma = 12%
Predic1on:
• Target across sectors • Volume Business
Outline
• The current state of diabetes data and soiware
• Why this is a problem
• What we can learn from other diabetes therapies and open standards in IT
• Recent Progress • Key ques1ons
Diabetes Data and Soiware Today
• Ver1cal • Closed • Proprietary • Not Standardized
Diabetes Data and Soiware Today
Source: Timothy Bailey, Journal of Diabetes Science & Technology 2007; photo provided by Dr. Bruce Buckingham
WHY IS THIS A PROBLEM?
SMBG data downloading
• 45% of 907 type 1s never download their meter
• 75% of 1,165 type 2s never download their meter
• Only 37% of type 1s are sa1sfied with downloading
Source: dQ&A pa1ent panel, 3Q2010. Self Monitoring of Blood Glucose Data from dQ&A
Pa1ents Don’t Download!
• Data from the T1D Exchange – 25,000 pa1ents with type 1 diabetes at 69 leading clinical centers across the US.
• Blood glucose meter downloading: – 68% never download – 21% download less than once a month
• CGM downloading: – 43% never download – 35% download less than once a month
Source: n=25,000 pa1ents in the Helmsley Charitable Trust T1D Exchange
Burden on doctors to see and analyze data
…but there is a shortage of providers
• New York: 1.8 million people with diabetes, only 600 diabetes educators (2nd highest # in US)
• “Overall, there appear to be only one-‐half the endocrinologists required to the fill the needed posi1ons in the U.S.” – ~4,000 endocrinologists to care for the ~25-‐100 million pa1ents who could poten1ally be seen
Source: D Jornsay, AADE 2012 Annual Mee1ng, Las Vegas; A Stewart, J Clin Endocrin Metab 2008
…and providers have li{le 1me with pa1ents!
• In a study of pa1ents with type 2 diabetes, medical residents spent an average of only five minutes during visits discussing diabetes!
• Average primary care visit length in 2005: 21 minutes
• Best case: Four hours per year with an endocrinologist vs. 8,756 hours of self-‐management
Source: Barnes et al., Diabetes Educ 2004; Chen et al., Archives of Internal Medicine 2009
SOFTWARE CAN HELP BRIDGE THE GAP, BUT…
HOW DO YOU GET MORE PATIENTS TO USE IT?
What we can learn from
• 1. Characteris1cs of other commercially successful diabetes therapies
• 2. Open standards in informa1on technology
1. Where is industry growth coming from?
GLP-‐1s
DPP-‐4s
Insulin
Insulin pumps CGM Others Share of Overall Diabetes Industry Growth
1. Why are DPP-‐4s so successful?
• Easy for pa1ents – once per day pill • Li{le thinking/educa1on required • Low HCP hassle – no training needed, not 1me consuming
• Low adherence barriers for pa1ents • Standardized – all DPP-‐4s are pre{y much the same
2. What can we learn from IT?
And, who made the money?
1970’s: Ver1cal, proprietary, closed
1980s: IBM was late so they offered an open architecture (5150)
• Higher volume • Best in class components • Horizontal
1990s: IBM tries to go back to proprietary OS and loses market share
Late 70s Perfect storm: Chaos +
growing market
Takeaways from the IT Case
1. Open standards modularity: It will happen. (Usually demanded by customers.)
2. It only takes one single player (to change the landscape of the industry)
3. Change is irreversible once it happens – IBM example in the PC market
What are the parallels to diabetes healthcare?
In personal compu1ng, the drivers of mass adop1on were: – Ver1cal closed to open standard (1980) – Giving power to user (1980 to 1990) – Widespread Network Connec1vity (1995-‐2000) – Mobile compu1ng and mobile data (2005+)
Introduc1on of Open Standards
Interconnec1vity & Networks
0
2
4
6
8
10
1975 1980 1985 1990
US PC Sales Units
0
50
100
150
1975
1980
1985
1990
1995
2000
2005
2010
2015
US PC Sales Units Millions of Units
Mobile Data
Source: ETForecasts
Recent Progress
Recent Progress
The Future?
Automa1c Wireless Transmission
• A single standardized report
• Accessible on any device
• Ac1onable insights • Data analy1cs
Key Ques1ons
• Could open standards improve diabetes care? • What is preven1ng more open standards in diabetes care?
• Why don’t more pa1ents use soiware and download data? How can this be addressed?
• ____ is the biggest problem with obtaining/interpre1ng diabetes data. It could be solved by ____
Master of Engineering
Fung InsDtute for Engineering Leadership
Ikhlaq Sidhu Chief Scien1st and Founder, Fung Ins1tute Faculty Director, Center for Entrepreneurship & Technology Academic Director, Engineering Leadership Professional Program 2009 Emerging Area Professor Award [email protected]