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  sidhu@berkeley.edu