Advanced Laboratory Analytics — A Disruptive Solution for Health Systems

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As US healthcare systems grapple with the recent upheavals in care payment and delivery, they are turning to advanced analytics as their “central nervous systems” for driving care and financial performance.

Laboratory information — spanning chemistry, pathology, microbiology and molecular testing, for example — is among the best sources of data for these advanced analytics, including clinician decision support, predictive analytics, population health management, and personalized medicine. When strategically harnessed and integrated to create a patient-centric lab data lake, laboratory information can form an affordable yet competitively powerful advanced analytics solution well suited for many health systems — i.e., a disruptive option.

L. Eleanor J. Herriman, MD, MBA, Chief Medical Informatics Officer of Viewics, explains why laboratory data should be a core strategic component for achieving success in value-based healthcare.

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  • physician executive with 20 years of varied healthcare industry

    experience. Before joining Viewics, Eleanor was a faculty member at Harvard

    Business School’s Institute for Strategy and Competitiveness. Other prior career

    experience includes: market research and strategy services to the pathology and

    laboratory industries at G2 Intelligence (a Plain Language Media business),

    healthcare strategy consulting at Bain & Company, and multiple start-up medical

    technology ventures.

    Dr. Herriman holds a Doctor of Medicine degree from Baylor College of Medicine

    and was awarded the Presidents Scholarship with honors in Neurology, Psychiatry

    and Neuropathology. Dr Herriman also holds a Masters in Business Administration

    from Harvard University Graduate School of Business Administration as a Baker

    Scholar and a Bachelors of Science in electrical engineering from Rice University,

    Magna Cum Laude with a minor in bioengineering.
  • In Addition to Bundled Pay,
  • Advanced Laboratory Analytics — A Disruptive Solution for Health Systems

    1. 1. Advanced  Laboratory  Analytics  — A  Disruptive  Solution  for  Health  Systems Eleanor  Herriman,  MD,  MBA Chief  Medical  Informatics  Officer  
    2. 2. L. Eleanor  J.  Herriman,  M.D., M.B.A. • Physician  executive  with  20  years  of  varied  healthcare  experience • Former  faculty  member  at  Harvard  Business  School’s  Institute  for   Strategy  and  Competitiveness   • Market  research  and  strategy  services  to  the  pathology  and   laboratory  industries  at  G2  Intelligence • Healthcare  strategy  consulting  at  Bain  &  Company Education • Doctor  of  Medicine  degree  from  Baylor  College  of  Medicine • Presidents  Scholarship  with  honors  in  Neurology,  Psychiatry  and   Neuropathology • Masters  in  Business  Administration  from  Harvard  University   Graduate  School  of  Business  Administration  as  a  Baker  Scholar Chief  Medical  Informatics  Officer
    3. 3. Agenda The  Age  of  Advanced  Analytics Lab  Analytics  Rule The  Lab  Disruptive  Solution
    4. 4. Medical  Payment  and  Delivery  is  Undergoing  a  Massive  Upheaval     Traditional  Model:  Fee  For  Service New  Model:  Value-­Based  Care Diabetic  Patient Set  Fee  Split  Between  Providers: Bottom  Line  and  Outcomes  are  Drivers $  One  Year  Diabetic  Care  $ Fee  For  Service: Paid  by  Volume  Regardless  of  Quality   $$ $ $ $ $$$ $ $ $ Diabetic  Patient
    5. 5. Population  Health  is  the  “New  Mandate”   “There  is  nothing  more  important  [in  healthcare]  than  the   transition  from  traditional  medicine  to  population  health  and   the  implications  that  will  have.  No  outcome,  no  income.” Dr.  David  Nash Founding  Dean,  Jefferson  School  of  Population  Health
    6. 6. Providers  and  Services  Now  Driven  by  Bottom  Line  and   Outcomes Laboratory • Operational  efficiencies • Testing  utilization  management • Demonstrate  value  of  testing  to   payers,  health  organizations Healthcare  Providers • Decrease  avoidable  clinical   costs • Improve  outcomes • Project  and  manage  population   costs Requires  New,  More  Advanced  Analytical  Tools  
    7. 7. Health  System  “C-­Suite”  – Key  Issues     Substantially  Reduce  Costs • Targeting  15%  OpEx cuts • Move  to  less  expensive   settings  (inpatient  to  out,   nursing  home  to  post-­ acute,  home  care) • Restructure  care  delivery   and  work  “top  of  license” Integrate  Care  Delivery • Across  settings  – hospitals   and  physician  groups   merging  to  care  for   populations • Across  service  lines  – coordinated  delivery  for   bundled  care     • Across  license  tiers  – coordinated  care  teams   with  RNs,  mid-­levels,  etc.     Maximize  Quality • Ensure  achievement  of   quality,  reimbursement-­ linked  targets     • Minimize  occurrence  of   poor  quality  /  unpaid   events     • Consumer  satisfaction  and   transparency  
    8. 8. Overburdened  Clinicians  are  Struggling  with  Decision  Making Clinicians   struggling   to  make   optimal   decisions Patient   information   overload Complexity  of   molecular   testing,   genomics New  models   require     forecasting   costs  and  risks “The  pace  at  which   new  knowledge  is   produced  outstrips   the  ability  of  any   individual  clinician   to…manage   information  that   could  inform   clinical  practice.”   IOM,  2012 IOM  (Institute  of  Medicine).  2012.  Best  care  at  lower  cost:  The  path  to   continuously  learning  health  care  in  America.  
    9. 9. The  Age  of  Advanced  Analytics   •Integrate  predictive,   population  and/  or   personalized  tools  to   guide  provider   decisions   •Molecular  /  genetic   testing  to  optimize   therapeutic  decisions •Machine  learning   applications  that  predict   readmissions,  adverse   events,  mortality,  ER   visits     •Predict  costs  for  cohort,   episode,  … •Patient  risk triage  tools   •Chronic  care  – provider   gap  management  tools •Care  coordination  tools   – tracking  across  settings,   providers Population   Management   Analytics   Predictive   Analytics Clinical   Decision   Support Personalized   Medicine   Analytics  
    10. 10. Rapid  Adoption  Driven  by  Value  Based  Care  (VBC) Health  system  analytics The  missing  key  to   unlock  value-­based  care Findings  from  the  Deloitte  Center  for  Health  Solutions  2015   US  Hospital  and  Health  System  Analytics  Survey
    11. 11. Advanced  Analytics  Showing  Results  and  Increasing   Investment A  March  2015  survey  on  analytics  in   healthcare: The  top  analytical  priority  for  providers  in   clinical  analytics  and  data  capture.  Risk   management,  quality  improvement,  and   business  process  innovation  are  key   areas  for  analytics  in  payer   organizations. The  report  highlighted  that  by  using   analytics,  82%  of  the  respondents  saw   improved  patient  care,  with  63%  seeing   reduced  readmission  rates   Market  research  and  surveys   further  indicate  that: 65%  of  healthcare  providers  and   60%  of  healthcare  payers  plan  to   increase  analytics  spend  in  2015
    12. 12. Predictive  Analytics  Adoption  Taking  Off “Virtually  every  major  healthcare  delivery  system  in  the   country  is  either  considering,  or  in  the  early  stages  of   implementing  predictive-­analytics  programs.” Melanie  Evans,  “Data  collection  could  stump  next  phase  of  predictive  analytics.”   Modern  Healthcare,  July  12,  2014
    13. 13. Challenges  in  Advanced  Analytics  Adoption • Technology  interoperability  /  data  integration   expensive,  lengthy  and  difficult  due  to  variation   in  terminology,  data  structures,  etc. • IT  resources  overwhelmed • Lack  of  analytics  experts  -­ What  to  do  with  “big   data”  after  creating  datalake /  EDW?   • Need  for  analytics  NOW  – urgency  of  move  to   value-­based  reimbursement  /  population  health Multiple  studies  have  highlighted   this  to  be  the  #1  challenge  in  the   adoption  of  analytics   McKinsey  report  -­ 2018  U.S.   shortage  of  190,000  skilled  data   scientists  and  1.5  M  advanced  big   data  analysts     Interoperability  between   technologies  is  one  of  the  major   factors  impacting  the  adoption  of   analytics
    14. 14. Lab  Analytics  Rule
    15. 15. Lab  Data  Rule  in  Advanced  Analytics Lab  data Radiology   data Medication   data Physician   exam  data Claims  data Timely Structured Ubiquitous   (settings,   providers) Predictive   potency Personalized   med  apps Population  care   apps
    16. 16. Lab-­based  Advanced  Analytics   •“Smart”  test  panels  by  disease   indication • Interpretive,  integrative  lab   reports   •Molecular  /  genetic  testing  to   optimize  therapeutic  decisions •Test-­driven  therapy  selection •Lab-­based  predictive   algorithms  for  readmissions,   adverse  events,  mortality,  ER   visits     • Diabetes  care  management   lab  tools    – testing  pathways,   missing  Dx,  registries •Real-­time  antibiograms •Blood  product  personalized   utilization Population   Management   Analytics   Predictive Analytics Clinical Decision Support Personalized   Medicine   Analytics  
    17. 17. Lab  Test  Results  for       Mr.  Jones   App  pulls  data  from  lab   LIS,  Path  etc.  systems     Probability  that  Mr.   Jones  will  experience   event  X  (readmission,   death,  adverse  event,   disease  progression) Care  protocol   specific  to   event   activated  – outcome   optimized Trained   computer   prediction   engine App  delivers  probability   score  to  clinicians  via   EHR,  mobile  device,  etc. Lab-­based  Predictive  Analytics  
    18. 18. • 11%-­14%  of  U.S.  adults  have  chronic   kidney  disease  (CKD)  and  are  at  higher   risk  for  cardio  events  and  renal  failure • Proven  therapies  to  improve  outcomes   in  CKD  patients  exist,  but  they  have   clinical  risks  and  add  costs • CKD  clinical  decision  is   challenging  due  to  the   heterogeneity  of  kidney  diseases,   variability  in  rates  of  progression,   and  the  competing  risk  of  cardio   mortality   CKD  Patient’s  Labs • Est  GFR,  albuminuria,  serum  calcium • Serum  phosphate,  serum  bicarbonate,   and  serum  albumin Risk  prediction • Single  score • Individualized • Risk  of  developing  renal  failure • ROC  =  91% Clinical  intervention • Lower  risk  patients  followed  by  PCPs • Higher  risk  patients  treated  by   nephrologists  and  closely  monitored Renal  Failure  Prediction  Application
    19. 19. Lab  Advanced  Analytics  Diabetes  Program Basic   Management Ensure  abnormal  tests   not  “missed” Test  value  protocols  for   referral  to   endocrinologist PGx test    to  increase   patient  statin  adherence   (KIF6  from  Medco,   Celera) Avoid   Admissions,   ERs Biomarker  prediction   panels  for  cardio,  renal,   coagulation,  etc. Aggressive,  precise   treatment  for  all  other   disorders  – e.g.  use   PGx and  MDx in   GERD,  COPD,  etc.   Better   Management  of   Infections Rapid,  targeted  therapy   guided  by  point  of  care   MDx for  inpatient   infections,  including   decub ulcers,  UTIs   Pathogen  surveillance   program  with  frequent     antibiograms -­ community  PCPs Avoid  Adverse   Events Consider  preemptive   pharmacogenetic   testing    of  diabetics  for   key  genes Quality  program  for   bedside  /  critical  care   glucometers  for     hospital  glycemic   control
    20. 20. The  Lab  Disruptive  Solution
    21. 21. Health  System  Advanced  Analytics  Needs  and  Capabilities Large  Health  Systems • Needs • ACO-­level  analytics • Enterprise-­wide  coordination • Distribute knowledge  IP • Capabilities • EMR  integration • Analytics  group • Substantial  IT  budget  -­ $Bs Mid-­Size  Health  Systems • Needs •Program-­based  analytics •Condition-­centered  coordination         •Insource  expertise •Capabilities •Some  integration •Limited  internal  analytics •IT  analytics  budget  <  $500M Small  Systems  /  Hospitals • Needs •Application  targeted  analytics •Professional  services   • Capabilities •Little  IT  integration •Small  analytics  cap  budget  – need  SAAS
    22. 22. Health  System  Advanced  Analytics  – Disruptive  Opportunities Large  Health  Systems Enterprise  Data  Warehouse  +   Advanced  Analytics Mid-­Size  Health  Systems   Lab-­Driven,  Advanced  Analytics   Programs Small  Systems  /  Hospitals Lab-­Based  Point  Solutions “Disruptive”  – simpler  solution  that  fits  user’s   needs  at  lower  cost  point        
    23. 23. Lab  Integration  Platform Genomic   Variant +   Lab  Data Infectious   Disease Hospital   Re-­ admission Test   Algorithm   Rx   Support Renal   Failure   Prediction Mortality     Prediction Blood   Product   Analytics Personalized   Medicine Predictive  Analytics Architecture  for  Lab-­Based  Advanced  Analytics  System LIS Path Micro,  MDx,  … EMR Billing Population  Health Chronic   disease   mgmt
    24. 24. Thank  you Click  to  watch  on-­demand  webinar eleanor.herriman@viewics.com

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