0
Using	  Analy+cs	  to	  Track,	  Monitor,	            and	  Reduce	  Costs	  	                                  Anne	  Kir...
Learning	  Objec<ves	  •  Iden+fy	  warning	  signs	  of	  misuse	  and	  abuse	  and	  how	     claim	  managers	  can	  ...
Disclosure	  Statement	  	  •  Anne	  Kirby	  has	  no	  financial	  rela+onships	  with	     proprietary	  en++es	  that	 ...
Using	  Analy<cs	  to	  Track,	   Monitor,	  and	  Reduce	  Costs	                       Anne	  Kirby,	  RN	  Chief	  Comp...
Accepted	  Learning	  Objec+ves	  1.  Iden+fy	  warning	  signs	  of	  misuse	  and	  abuse	      and	  how	  claim	  mana...
Nothing	  to	  Disclose	  
Challenge	  for	  Claims	  Claims	  with	  long-­‐ac+ng	  opioid	  Rx	  cost	  	  9.3	  +mes	  more	  than	  claims	  with...
5	  Key	  Problems	  1.  Difficult	  to	  iden+fy	  claims	  with	  ques+onable	  	      drug	  use	  before	  cases	  turn	...
Addressing	  the	  Problems	  	  Rx	  Intelligence	  Analy+cs	  1.  Expedites	  file	  iden+fica+on	  	  2.  Flags	  poten+a...
Rx	  Intelligence	  Analy+cs	  Sample	  Dashboard	  
Demonstrated	  Impact	  Effect	  of	  successful	  peer-­‐to-­‐peer	  conversa+on	  (between	  pain	  management	  physicia...
Demonstrated	  Impact	                 •  Decreased	  Rx	  Refills	  within	  6-­‐8	  months	  of	  	                    Pe...
Connec+ng	  the	  Dots	            Where	  do	  we	  go	  from	  here?	                            Treati                 ...
Using	  Analy<cs	  to	  Track,	  Monitor,	  and	  Reduce	  Costs	            Jamey	  Masingill	           Vice	  President...
Accepted	  Learning	  Objec+ves	  1.  Iden+fy	  warning	  signs	  of	  misuse	  and	  abuse	      and	  how	  claim	  mana...
Nothing	  to	  Disclose	  
WC	  Combined	  Ra+o:	  1994-­‐2012F	  Call	  To	  Ac+on…	  
Priming	  the	  Pump	  by	  Extrac+ng	  “Old	  School”	     Thinking	  from	  the	  Claims	  Environment	  •  There	  is	 ...
U+liza+on	  
LT	  Closing	  Ra+o	  Triangles	   Lost	  Time	  	        2006	        2007	        2008	        2009	        2010	       ...
Impact	  of	  Reduced	  Claims	  Dura+ons	  
Notes	  Only	  Presenta+on	  Outline:	  •  Preparing	  the	  claims	  environment	  before	     implemen+ng	  your	  progr...
Using	  Analy<cs	  to	  Track,	  	             Monitor,	  and	  Reduce	  Costs	  Joe	  Anderson,	  Director	  of	  Analy<c...
Learning	  Objec<ves	  •  Iden+fy	  warning	  signs	  of	  misuse	  and	  abuse	  and	  how	     claim	  managers	  can	  ...
Disclosure	  Statement	  •  Nothing	  to	  disclose	  
What	  Is	  Predic<ve	  Analy<cs?	                       Predictive Analytics is making decisions with statistics and data...
How	  Can	  We	  Use	  It?	     •  As	  a	  PBM,	  we	  see	  some	  of	  the	  data	  going	  through	  the	  system,	  b...
The	  Problem	              A	  solu<on	  is	  needed	  that	  reduces	  prescrip<ons	  most	  efficiently.	  Prescrip<on	  ...
The	  Solu<on:	              Mul<variate	  Sta<s<cal	  Model	  	               to	  Predict	  High-­‐Cost	  Claims	  Our	 ...
Data	  Used	  in	  Sta<s<cal	  Models                        100%	                           90%	                         ...
The	  Risk	  Score	  Claim	       Risk	  Score	     Reason	  Allison	          6.5	          Mul+ple	  Neck	  Injury,	  Hi...
Predic<ons	  Become	  Interven<ons	  • Types	  of	  clinical	  interven+ons:	       •  Claims	  Professional	  Outreach	  ...
Measuring	  Effec<veness	                                              Statistical Confidence that                         ...
Analy<cs	  From	  a	  Provider’s	  Perspec<ve	  •  Finding	  common	  ground	  	     with	  analy+cs	  and	  providers	  •...
Common	  Ground	  –	  Data	  Collec<on	  •    Personal	  medical	  history	  •    Family	  history	  •    Social	  history...
Common	  Ground	  –	  Risk	  Assessment	                        Stroke	      Modifiable	  risk	  factors	                  ...
Common	  Ground	  –	  Outcome	  Predictors	                      Stroke	       •  Poor	  strength	  recovery	  predictors	...
Common	  Ground	  –	  Outcome	  Predictors	                      Stroke	       •  Nega+ve	  predictors	  for	  return	  to...
Common	  Ground	  –	  Language	  •    Data	  collec+on	  •    Risk	  assessment	  	  •    Risk	  factors	  •    Outcome	  ...
Embracing	  Challenges	  	                     Avoid	  Blame	  	  •  Comprehensive	  claim	  evalua+on	  •  Interven+ons	 ...
Embracing	  Challenges	  	                                             Validate	  Success	       •  Hill	  Physicians	  Me...
Embracing	  Challenges	  	                                             Validate	  Success	                             	  ...
Embracing	  Challenges	  	                                           Validate	  Success	       •  Diabe+c	  pa+ents	  	   ...
Embracing	  Challenges	  	                    Be	  Responsive	  •  A	  provider’s	  ques+ons	     –  Is	  my	  prac+ce	  s...
Embracing	  Challenges	                           Reward	  Posi<ve	  Outcomes	       •  Should	  providers	  be	  rewarded...
Takeaways	  •  Common	  ground	     –  Data	  collec+on	     –  Risk	  assessment	     –  Outcome	  predictors	     –  Lan...
Ques<ons?	  
Upcoming SlideShare
Loading in...5
×

Using analytics to_track_monitor_and_reduce_costs_final

413

Published on

Third-Party Payer Track, National Rx Drug Abuse Summit, April 2-4, 2013. Using Analytics to Track, Monitor and Reduce Costs presentation by Anne Kirby, James Masingill, Joe Anderson and Dr. Robert Hall

Published in: Economy & Finance, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
413
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
39
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transcript of "Using analytics to_track_monitor_and_reduce_costs_final"

  1. 1. Using  Analy+cs  to  Track,  Monitor,   and  Reduce  Costs     Anne  Kirby   Chief  Compliance  Officer  and  Vice  President,  Medical   Review  Services,  Rising  Medical  Solu+ons     James  Masingill   Vice  President,  Claims  Opera+ons,  Market  First  Comp   Insurance  Company   Joe  Anderson     Director  of  Analy+cal  Services,  Progressive  Medical   Dr.  Robert  Hall   Medical  Director,  Progressive  Medical    
  2. 2. Learning  Objec<ves  •  Iden+fy  warning  signs  of  misuse  and  abuse  and  how   claim  managers  can  take  ac+on.  •  Tell  how  payers  can  use  effec+ve  analy+cs  to  iden+fy   relevant  trends.  •  Explain  how  Pharmacy  Benefit  Managers  can  use   analy+cs  with  strong  clinical  programs.  •  Describe  the  role  and  benefits  of  predic+ve  analy+cs  in   the  workers’  compensa+on  industry.  
  3. 3. Disclosure  Statement    •  Anne  Kirby  has  no  financial  rela+onships  with   proprietary  en++es  that  produce  health  care  goods   and  services.  •  James  Masingill  has  no  financial  rela+onships  with   proprietary  en++es  that  produce  health  care  goods   and  services.    •  Joe  Anderson  has  no  financial  rela+onships  with   proprietary  en++es  that  produce  health  care  goods   and  services.    •  Robert  Hall  has  no  financial  rela+onships  with   proprietary  en++es  that  produce  health  care  goods   and  services.     3
  4. 4. Using  Analy<cs  to  Track,   Monitor,  and  Reduce  Costs   Anne  Kirby,  RN  Chief  Compliance  Officer/VP  of  Medical  Review  Services   Rising  Medical  Solu+ons  
  5. 5. Accepted  Learning  Objec+ves  1.  Iden+fy  warning  signs  of  misuse  and  abuse   and  how  claim  managers  can  take  ac+on.  2.  Tell  how  payers  can  use  effec+ve  analy+cs  to   iden+fy  relevant  trends.  3.  Explain  how  Pharmacy  Benefit  Managers  can   use  analy+cs  with  strong  clinical  programs.  4.  Describe  the  role  and  benefits  of  predic+ve   analy+cs  in  the  workers’  compensa+on   industry.  
  6. 6. Nothing  to  Disclose  
  7. 7. Challenge  for  Claims  Claims  with  long-­‐ac+ng  opioid  Rx  cost    9.3  +mes  more  than  claims  without      (Journal  of  Occupa+onal  &  Environmental  Medicine)  •  Very  manual  process    •  Case  selec+on  not  always  on  target  •  Trea+ng  physicians  and  pain  mgmt   peer  reviewers  used  drug  names     inconsistently  •  If  a  person  was  taking  1  or  2  opioids,   it  was  likely  they  were  taking  upwards     of  7  or  8  other  drugs  
  8. 8. 5  Key  Problems  1.  Difficult  to  iden+fy  claims  with  ques+onable     drug  use  before  cases  turn  into  large  losses  2.  Too  +me  consuming  for  adjuster     to  find  at-­‐risk  cases  3.  Not  enough  to  have  a  pharmacist     contact  a  trea+ng  physician  4.  Data not  comprehensive  enough – need integrated approach  5.  Viewing  opioids  in  a  vacuum  –  need  to     look  at  other  constella+on  of  drugs      
  9. 9. Addressing  the  Problems    Rx  Intelligence  Analy+cs  1.  Expedites  file  iden+fica+on    2.  Flags  poten+ally     problema+c  claims  early    3.  Adds  another  level  of     interven+on  4.  Looks  beyond  just  opioids    5.  Uses  data  to  intervene  
  10. 10. Rx  Intelligence  Analy+cs  Sample  Dashboard  
  11. 11. Demonstrated  Impact  Effect  of  successful  peer-­‐to-­‐peer  conversa+on  (between  pain  management  physician  and  prescribing  physician)   Fills  before   interven<on   Fills  aFer   interven<on  
  12. 12. Demonstrated  Impact   •  Decreased  Rx  Refills  within  6-­‐8  months  of     Peer-­‐to-­‐  Peer  Review       65%    Claims   •  Decreased  Opioid  Rx  Refills   71%    Claims   •  Decrease  of  All  Injury  Related  Drugs   •  Opioids,  Muscle  Relaxants,  Hypno<cs  &     57%     An<-­‐Anxiety  meds  Claims  
  13. 13. Connec+ng  the  Dots   Where  do  we  go  from  here?   Treati ng Pain Mgmt Physi PeerClai cian Reviewerms UR NursePerson PATIPharmac TCM ENTy Benefit NurseMgr Clinical Pharmaci st
  14. 14. Using  Analy<cs  to  Track,  Monitor,  and  Reduce  Costs   Jamey  Masingill   Vice  President  of  Claims   Markel-­‐FirstComp  Insurance  
  15. 15. Accepted  Learning  Objec+ves  1.  Iden+fy  warning  signs  of  misuse  and  abuse   and  how  claim  managers  can  take  ac+on.  2.  Tell  how  payers  can  use  effec+ve  analy+cs  to   iden+fy  relevant  trends.  3.  Explain  how  Pharmacy  Benefit  Managers  can   use  analy+cs  with  strong  clinical  programs.  4.  Describe  the  role  and  benefits  of  predic+ve   analy+cs  in  the  workers’  compensa+on   industry.  
  16. 16. Nothing  to  Disclose  
  17. 17. WC  Combined  Ra+o:  1994-­‐2012F  Call  To  Ac+on…  
  18. 18. Priming  the  Pump  by  Extrac+ng  “Old  School”   Thinking  from  the  Claims  Environment  •  There  is  no  right  or  wrong…only  grey  •  Reduce  ac+vity  checks  and  surveillance    •  Targeted  and  directed  case  management  •  Own  your  data   –  Driven  down  to  unit  and  individual  levels  •  Adherence  to  established  best  prac+ces  •  Valida+on  process  
  19. 19. U+liza+on  
  20. 20. LT  Closing  Ra+o  Triangles   Lost  Time     2006   2007   2008   2009   2010   2011   2012   12   28.00%   22.90%   26.10%   26.00%   28.90%   26.20%   34.70%   24   64.80%   63.90%   69.90%   68.70%   70.20%   72.70%   36   82.80%   84.20%   86.00%   85.40%   88.20%   48   91.30%   92.30%   92.90%   93.30%   60   95.90%   95.20%   96.20%   72   97.60%   97.20%   84   98.30%  
  21. 21. Impact  of  Reduced  Claims  Dura+ons  
  22. 22. Notes  Only  Presenta+on  Outline:  •  Preparing  the  claims  environment  before   implemen+ng  your  program.    Analy+cs  and  program   will  only  be  effec+ve  if:   –  Extract  “old  school”  thinking  from  claims  processing   –  Reduce  ac+vity  checks  and  inves+ga+ons   –  Redeploy  those  resources  into  added  medical  exper+se  /   interven+on  tools  •  Using  claims  triangles  to  track  and  improve   performance  •  Importance  of  integrated  approach  from  mul+ple   angles  to  effec+vely  tackle  prescrip+on  drug  problem    •  Impact  on  overall  costs  
  23. 23. Using  Analy<cs  to  Track,     Monitor,  and  Reduce  Costs  Joe  Anderson,  Director  of  Analy<cs  Robert  Hall,  MD,  Medical  Director  Progressive  Medical,  Inc.  
  24. 24. Learning  Objec<ves  •  Iden+fy  warning  signs  of  misuse  and  abuse  and  how   claim  managers  can  take  ac+on.  •  Tell  how  payers  can  use  effec+ve  analy+cs  to  iden+fy   relevant  trends.  •  Explain  how  Pharmacy  Benefit  Managers  can  use   analy+cs  with  strong  clinical  programs.  •  Describe  the  role  and  benefits  of  predic+ve  analy+cs  in   the  workers’  compensa+on  industry.  
  25. 25. Disclosure  Statement  •  Nothing  to  disclose  
  26. 26. What  Is  Predic<ve  Analy<cs?   Predictive Analytics is making decisions with statistics and data.Company   Goal  of  predic<ve  analy<cs   Result  Target   Iden+fy  new  mothers  as  quickly  as   Delivered  coupons  to  young   possible  to  get  them  in  the  habit  of   mothers  before  their  family  even   shopping  at  Target.   knew  they  were  expec+ng.  Nemlix   Determine  which  movies  customers   Improved  their  predic+ons  by  10%;   will  like  based  on  what  they  have   a  $1  million  prize  was  awarded.   already  rated.  Oakland   Choose  the  best  baseball  players   20  consecu+ve  wins;  the  book  and  Athle+cs   available  for  the  next  season,  with  a   film  Moneyball  are  based  on  this.   limited  budget.  Sources:  Duhigg,  C.,  How  Companies  Learn  Your  Secrets,  The  New  York  Times  Magazine.  2012  February  16  Lohr,  S.,  A  $1  Million  Research  Bargain  for  NeElix,  and  Maybe  a  Model  for  Others,  The  New  York  Times,    2009  September  21  Mahler,  J.,  Smaller  Markets  and  Smarter  Thinking,  The  New  York  Times,  2011  October  14  
  27. 27. How  Can  We  Use  It?   •  As  a  PBM,  we  see  some  of  the  data  going  through  the  system,  but  not  all   of  it.   •  Each  company  in  the  industry  can  use  analy+cs  with  their  own  data:   –  Imagine  if  Nemlix  wants  to  know  whether  you’ll  enjoy  the  movie  Moneyball   –  Nemlix  doesn’t  know  if  you  have  read  the  book  Moneyball,  if  you  studied   sta+s+cs  or  if  you’re  an  Oakland  Athle+cs  fan   –  They  do  know  if  you  like  other  baseball  movies,  other     Brad  Pir  movies  and  other  movies  based  on  nonfic+on  books  Image source: http://www.managedcaremag.com/archives/1208/1208.pbm-functions.html
  28. 28. The  Problem   A  solu<on  is  needed  that  reduces  prescrip<ons  most  efficiently.  Prescrip<on  Drug  Deaths  and   Time  Constraints  on  Nurses,   Increasing  Costs   Adjustors,  Clinicians  •  More  people  are  dying  from   •  Cannot  examine  or  intervene  on   prescrip+on  drug  use.   every  claim  •  Prescrip+on  drug  prices  are  rising.   •  Cannot  determine  which  claims  will  •  Workers’  compensa+on  in  par+cular   have  high  long-­‐term  costs   has  seen  increases  in  use  of   •  Too  many  “false  posi+ves”  from   prescrip+on  pain  killers.   individual  clinical  triggers  (i.e.  only   10%  of  claims  with  morphine   equivalence  of  90mg  result  in  high   long-­‐term  costs)  
  29. 29. The  Solu<on:   Mul<variate  Sta<s<cal  Model     to  Predict  High-­‐Cost  Claims  Our  original  model,  since  refined:   Correlate  early  data   …  with  resul<ng  long-­‐ about  an  injured   term  spend  of  that   worker…   injured  worker.   Workers  injured  in  2007   Resul+ng  pharmacy  costs  in  2009-­‐2010  
  30. 30. Data  Used  in  Sta<s<cal  Models 100%   90%   80%   70%   Pharmacy  Behavior:  Medica+ons,   Percent  of   Number  of  Prescribers,  Number  of   Significance   60%   Pharmacies   (Aggregated  across  mul<ple   Injury:  Body  part,  nature  of  injury   variables)   50%   Prescriber:  Demographics  of  trea+ng   40%   prescriber   30%   Geographic  and  Other  Demographics   20%   10%   0%   1   4   6   9   12   18   24   Months  Since  Date  of  Injury  
  31. 31. The  Risk  Score  Claim   Risk  Score   Reason  Allison   6.5   Mul+ple  Neck  Injury,  High  Total  Medica+on  Use  (Including   Narco+cs)  Bob   5.4   Con+nued  Medica+on  Use,  High  Risk  Prescriber:  Allergy  and   Immunology  Specialist  Cindy   5.0   Mul+ple  Prescribers  in  Early  Months,  High  Days  Supply  of   Various  Medica+ons  Dwayne   4.5   High  Risk  State  and  Moderate  Injury  Risk:  Dislocated  Disc  Elaine   3.9   Prescriber  Risk:  Pain  Management  Specialist,  High  Narco+cs   Use  To-­‐Date  Frank   3.1   Moderate  Injury  Risk,  Demographic  Risk,  and  Prescriber  Risk:   Pain  Management  Specialist  
  32. 32. Predic<ons  Become  Interven<ons  • Types  of  clinical  interven+ons:   •  Claims  Professional  Outreach   •  Physician  Outreach   •  Drug  U+liza+on  Evalua+on   •  Peer-­‐to-­‐Peer  Review    • Interven+ons  should  be  completed  as  soon  as  possible     to  avoid  any  developing  complica+ons.  
  33. 33. Measuring  Effec<veness   Statistical Confidence that Intervention Changes this Outcome100%   90%   96%   80%   70%   70%   60%   50%   55%   40%   30%   20%   10%   0%   Cost  per  Claim   Morphine  Equivalence  per  Claim  Prescrip+ons  per  Claim  
  34. 34. Analy<cs  From  a  Provider’s  Perspec<ve  •  Finding  common  ground     with  analy+cs  and  providers  •  Embracing  challenges  that     can  arise  with  analy+cs  
  35. 35. Common  Ground  –  Data  Collec<on  •  Personal  medical  history  •  Family  history  •  Social  history  •  Physical  examina+on  •  Diagnos+c  studies  
  36. 36. Common  Ground  –  Risk  Assessment   Stroke   Modifiable  risk  factors   Non-­‐modifiable  risk  factors   •  High  blood  pressure     •  Age     •  Atrial  fibrilla+on     •  Gender     •  High  cholesterol     •  Race     •  Diabetes     •  Family  history     •  Atherosclerosis     •  Previous  stroke   •  Circula+on  problems     •  Fibromuscular  dysplasia     •  Tobacco   •  Alcohol   •  Patent  foramen  ovale   •  Physical  inac+vity     •  Obesity    Source: National Stroke Association, Am I at Risk for a Stroke? Stroke Risk Factors. 2013 March 18
  37. 37. Common  Ground  –  Outcome  Predictors   Stroke   •  Poor  strength  recovery  predictors   –  Severe  arm  weakness  at  onset  of  stroke   –  No  hand  strength  4  weeks  aLer  stroke   •  30-­‐day  mortality   –  EKG  abnormali+es   –  Brainstem  stroke   –  Elevated  blood  glucose  in  non-­‐diabe+c  pa+ents  Source: Zorowitz, R., Baerga, E., Cuccurullo, S., Stroke Rehabilitation, Physical Medicine and Rehabilitation BoardReview. New York. Demos Medical Publishing. 2004
  38. 38. Common  Ground  –  Outcome  Predictors   Stroke   •  Nega+ve  predictors  for  return  to  work   –  Low  Barthel  Index  score   •  Ac+vi+es  of  daily  living   –  Prolonged  length  of  stay  in  rehabilita+on   –  Aphasia  (language/communica+on  deficits)   –  Prior  alcohol  abuse  Source: Zorowitz, R., Baerga, E., Cuccurullo, S., Stroke Rehabilitation, Physical Medicine and Rehabilitation BoardReview. New York. Demos Medical Publishing. 2004
  39. 39. Common  Ground  –  Language  •  Data  collec+on  •  Risk  assessment    •  Risk  factors  •  Outcome  predictors  •  Interven+ons  •  Behavior  •  Effec+veness  
  40. 40. Embracing  Challenges     Avoid  Blame    •  Comprehensive  claim  evalua+on  •  Interven+ons  may  need  to  be  mulNfaceted  
  41. 41. Embracing  Challenges     Validate  Success   •  Hill  Physicians  Medical  Group   –  2,200  physicians   –  332,000  pa+ents   –  Predic+ve  modeling   •  Management  of  chronic  diseases   –  Prospec+ve  Risk  Score   •  Likelihood  of  pa+ent  using  physician  resources  in  future   •  RNs  are  assigned  to  call  pa+ents  with  high  risk  scores  Source: Emswiler, T. and Nichols, L., Hill Physicians Medical Group: Independent Physicians Working to Improve Qualityand Reduce Costs, The Commonwealth Fund. 2009 March
  42. 42. Embracing  Challenges     Validate  Success        0.5  x  In-­‐pa+ent  days  over  last  365  days        In-­‐pa+ent  days  over  last  90  days     +      2  x  ER  days  over  last  365  days          ER  days  over  last  90  days          2  x  (Prospec+ve  Risk  Score  +  adjustment  factor)     = Priority  Score  Source: Emswiler, T. and Nichols, L., Hill Physicians Medical Group: Independent Physicians Working to Improve Qualityand Reduce Costs, The Commonwealth Fund. 2009 March
  43. 43. Embracing  Challenges     Validate  Success   •  Diabe+c  pa+ents     –  High  Priority  Score   –  Contacted  by  nurse  case  managers   –  Reminders  for  screenings   •  Eyes   •  Kidneys   •  Cholesterol   –  Counseling  with  diabetes  educator  Source: Emswiler, T. and Nichols, L., Hill Physicians Medical Group: Independent Physicians Working to Improve Qualityand Reduce Costs, The Commonwealth Fund. 2009 March
  44. 44. Embracing  Challenges     Be  Responsive  •  A  provider’s  ques+ons   –  Is  my  prac+ce  style  being  ques+oned?   –  Will  the  care  of  my  pa+ents  be  affected?   –  Where  is  the  evidence?   –  Why  now?  
  45. 45. Embracing  Challenges   Reward  Posi<ve  Outcomes   •  Should  providers  be  rewarded?   –  Pay  for  performance   •  Physician  payments  at  the  group  level  (not  individual)   •  Mee+ng  absolute  benchmarks   •  Soon  auer  performance  period   –  Preferred  provider  status   •  Recogni+on   •  Increased  referrals  Source: Gamble, M., GAO: 3 Ways CMS Can Incentivize Physicians Like Private Payors, Beckers HospitalReview, ASC COMMUNICATIONS. 2012 January 7; 2013 March 11
  46. 46. Takeaways  •  Common  ground   –  Data  collec+on   –  Risk  assessment   –  Outcome  predictors   –  Language  •  Embracing  challenges   –  Avoid  blame   –  Validate  success   –  Be  responsive   –  Reward  posi+ve  outcomes  
  47. 47. Ques<ons?  
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×