Changing  Healthcare  Using  Data:    A  Case  Study  of  One  Small  Health  System's  Odyssey  To  Achieve  Material  Improvements  

North  Memorial  Health  Care  J  Kevin  Croston,  MD  FACS  CMO, President  -­‐  Physician  OrganizaEon

Poll  QuesEon  #1  What  is  your  primary  area  of  focus?  q Physician/clinical  care  provider  q Quality  q  InformaEon  system  q Finance  q AdministraEve  execuEve  q Other  

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ObjecEves  You  will  learn:  

– How  to  shiQ  to  a  data-­‐driven  decision  making  culture  •  KPA  

– How  to  make  the  data  meaningful  so  providers  can  make  beTer  decisions  

•  Permanent  processes  and  teams  –  Examples  of  successes  and  challenges  

•  Pregnancy  –  ReducEon  of  pre  39-­‐week  unnecessary  inducEons  

•  Cardiovascular  care  •  Revenue  cycle  process  –  professional  billing  •  Catheter  associated  urinary  tract  infecEons  (CAUTI)  

About  North  Memorial  StaEsEcs  (2012)  

Number  of  Licensed  Beds  

648  

Annual  InpaEent  Admissions    

33,718  (includes  nursery  4,852)  

Emergency  Room  Visits    

87,684  

InpaEent  Surgeries     8,722  

OutpaEent  Surgeries     19,181  

Providers  in  MulE-­‐Specialty  Clinics  

300  

Total  FTEs   4,281  

•  Minneapolis-­‐based  two-­‐hospital  health  system  

•  Provides  full  conEnuum  of  services  

•  Level  I  Trauma  Center  •  CommiTed  to  developing  

clinical  effecEveness  guidelines  to  deliver  the  highest  quality  care  at  a  lower  cost  

North  Memorial  SituaEon      

Challenges  •  Tough  regional  compeEtors  •  Declining  payment  stream  •  Data  created  confusion  

“data  rich  -­‐  informa/on  poor”  

•  Clinicians  and  execuEves  clamoring  for  answers  

•  Hospital-­‐centric  decisions  (not  enterprise  based)  

 

Opportuni@es  •  Strong  improvement  and  

quality  culture  •  Insighiul  and  supporEve  

leadership  •  Recognized  substanEal  

changes  were  required  for  survival  

Key  Process  Analysis  (KPA)  

KPA  Results  

North  Memorial  Resources  Consumed  

CumulaEve  %  

%  of  Total  Resources  Consumed  for  each  clinical  work  process  

Key  Findings:        

Number  of  Care  Process  Family  (e.g.,  ischemic  heart  disease,  pregnancy,  bowel  disorders,    spine,  heart  failure)  

•  80%  of  all  in-­‐pa@ent  resources  are  represented  by  18  Care  Process  Family  

80%  

50%  

•  50%  of  all  in-­‐pa@ent  resources  are  represented  by  7  Care  Process  Family  

Poll  QuesEon  #2  What  percent  of  your  quality  improvement  efforts  are  priori@zed  using  a  similar  varia@on/resources  analysis?  q 76-­‐100%  q 51-­‐75%  q 26-­‐50%  q 0-­‐25%  q Unsure  

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How  North  Made  Data  Meaningful  People    •  Formed  permanent  teams    

–  Clinical  OperaEons  Leadership  Team  (COLT)  

–  Guidance  Teams  (ex.  Women  &  Newborn,  Primary  Care,  Cardiovascular,  OPPE,  InfecEous  Disease)  

•  Repurposed  resources  without  adding  FTEs  

•  Selected  medical  leadership  to  champion  the  vision  and  process  

Processes  •  Data  organizaEon  -­‐  EDW  •  Data  governance    •  OrganizaEonal  team  

structure  to  support  outcomes  improvement  processes  

•  Ensured  hospitals  and  clinics  were  included  in    consistent  change  while  maintaining  autonomy  

•  ArEculated  the  vision    

Care  Process  Model  (CPM)  Core  Work  Group  

Pregnancy  (OB)  Team  Structure  

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Knowledge Manager Cathy  Anderson, R.N.

Outcomes Analyst Ashley Nguyen

Data Architect Joel  Zwinger

Data Provisioning Data Analysis Key:   Subject Matter Experts

Clinical  Director  Lead    Linda  Engdahl  R.N.  

 

Physician Lead Dr. Jon Nielsen

Quality/ Work Flow Expert

Mike Choi

Nurse Expert Barb  Pavek , R.N.

Knowledge Manager Bethany Hjelle, R.N.

Nurse Expert Tanya  Thomas, R.N.

Nurse Expert Sally  Walstrom, R.N.

Nurse Expert Maureen  Ehlers, R.N.

Women  &  Children  AnalyEcs  

Pre-­‐39  Week  ElecEve  InducEons  

Women  and  Newborn      Pre-­‐39  Week  ElecEve  InducEons  

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ObjecEve   Health  Catalyst  SoluEon   Results  to  date  •  Define  exisEng  workflows  

and  idenEfy  improvement  opportuniEes  

•  Establish  baseline  metrics  and  measures  

 •  Define  evidence  based  

standards  for  elecEve  inducEons  

 •  Reduce  rates  of  pre-­‐39  

week  deliveries  from  1.2%  to  0.6%  to  qualify  for  a  payer  partner  bonus  

 

•  Late-­‐BindingTM  Data  Warehouse  Plaiorm  

 •  Cohort  Finder  

•  Key  Process  Analysis  applicaEon  (KPA)  

•  Early  inducEon  advanced  applicaEon  

 •  CollaboraEve  IT  and  clinical  

care  workgroups            

•  Adopted  evidence  based  guidelines  and  standardized  workflows    

 •  Established  elecEve  

delivery  baseline  measurements  to  track  quality  improvement  gains  

•  Established  a  permanent  collaboraEve  team  

 •  Reduced  early-­‐term  

deliveries  from  1.2%  to  0.3%  

 •  $200K  payer  partner  bonus  

payment    

“We  wouldn’t  have  had  a  chance  to  do  some  of  the  things  we’ve  done  in  last  18  months  to  enhance  care,  reduce  waste  and  lower  costs  without  Catalyst.  It’s  amazing  how  differently  and  effec/vely  we  can  gather  and  use  data  now.”    -­‐Jon  Nielsen,  MD,  Medical  Director  Women  and  Children’s  Services  at  North  Memorial  Health  Care  

 

MAJOR  LEARNING:  

FOLLOW  THE  PLAN!    

Cardiovascular  Care  Challenges  •  Difficulty  replicaEng  first  

clinical  program  success    •  Department  vs  condiEon-­‐

based  issue  •  Difficulty  understanding  

importance  of  guidance  teams  

•  OrganizaEonal  readiness    •  Physician  leaders  changed  

weekly  

 Lessons  Learned  •  Inspire  knowledge  

leadership  and  organizaEonal  readiness  –  Include  the  right  people  in  

the  development  of  the  care  model  

–  Know  when  you  should  and  shouldn’t  be  involved  

–  Require  buy-­‐in  for  the  methodology    

–  Focus  of  project  did  not  line  up  with  opportuniEes  based  on  KPA  analysis  

.    

Professional  Billing  ApplicaEon  

   Professional  Billing  ApplicaEon    

Professional  Billing  Efforts  

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ObjecEve   Health  Catalyst  SoluEon   Results  to  date  •  Ensure  accurate  and  

complete  charge  capture  of  professional  services  performed  in  the  hospital    

•  Address  physician  concerns  that  charges  were  not  reflecEng  actual  services  rendered  

•  Reduce  manual  data  pulls  by  professional  coders  to  determine  which  provider  notes  to  review  

•  Deliver  provider  educaEon  to  improve  clinical  data  capture  

•  Late-­‐BindingTM  Data  Warehouse  Plaiorm  

•  Professional  Billing  applicaEon  to  idenEfy  revenue  cycle  and  educaEonal  opportuniEes    

•  Automated  data  capture  for  efficient  and  complete  revenue  cycle  analysis  

 •  Starter  set  value  stream  

mapping  to  idenEfy  workflow  process  gaps  

•  IntuiEve  applicaEon  for  professional  coders  to  opEmize  workflow  

•  6%  increase  in  billing  for  notes  that  had  sufficient  clinical  data    

•  PotenEal  $5.7M  charges    over  3  years  from  unbilled  services  

•  25%  improvement  in  professional  coder  efficiency,  allowing  Eme  for  provider  educaEon    

•  Health  Catalyst  delivered  results  in  6  weeks  vs.  consulEng  firm  who  was  unable  to  deliver  data  capture  and  applicaEon    

“The  Health  Catalyst  Professional  Billing  Applica/on  has  given  me  what  I  need  to  be  successful.  Now  I  can  finally  accomplish  what  I  was  hired  to  do!”    Nancy  Young,  Manager  Professional  Coding,  North  Memorial  Professional  Services  

 

Catheter-­‐Associated  Urinary  Tract  Infec@ons  (CAUTI)  

•  According  to  the  CDC  urinary  tract  infecEons  (UTIs)  are  the  most  common  type  of  healthcare-­‐associated  infecEon  •  Cause  of  450,000  annual  infecEons  leading  to  

13,000  deaths  •  Increasing  lengths  of  stay  by  as  many  as  four  days,  

and  increasing  healthcare  costs  by  as  much  as  $500  million  per  year  naEonally.    

•  CMS  has  proposed  expansion  of  CAUTI  measures  beyond  current  ICU  areas  to  include  medical  units,  surgical  unites  and  medical/surgical  units    

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CAUTI  ApplicaEon  

CAUTI  Surveillance    

ObjecEve   Health  Catalyst  SoluEon   Results  to  date  

•  Scalable  CAUTI  soluEon  to  meet  proposed  CMS  regulatory  measures    

•  Leverage  NaEonal  Healthcare  Safety  Network  (NHSN)  definiEons  and  calculaEon  algorithms  

•  ShiQ  clinical  resources  from  surveillance  to  intervenEon  

   

•  Late-­‐Binding™  Data  Warehouse    

•  CAUTI  ApplicaEon                

•  Clinical  Improvement  Services  

 •  Starter  set  to  idenEfy  

workflow  process  gaps  

•  Automated  data  capture  for  efficient    hospital  surveillance  

 

•  50  percent  esEmated  reducEon  in  CAUTI  surveillance  acEviEes  

 •  PotenEal  to  convert  from  

manual  to  electronic  tracking  for  NHSN  required  catheter  days  reporEng    

•  Rapid  Eme  to  value  with  10-­‐week  implementaEon    

•  InfecEon  prevenEonists  can  now  focus  on  intervenEon  instead  of  data  provisioning  

“We’re  extremely  strapped  for  /me  in  the  infec/on  preven/on  world  and  CMS  is  coming  out  with  new  regula/ons  every  year.  The  more  we’re  out  there  preven/ng  –  rather  than  measuring  –  infec/ons,  the  bigger  a  difference  we  can  make,  educa/ng  clinicians  and,  as  a  result,  increasing  pa/ent  safety  and  quality.”  ~  Terra  Menier,  R.N.,  Infec/on  Preven/on  Prac//oner    

Conclusions  •  Spend  a  lot  of  Eme  up  front  with  teams  before  they  start  down  this  quality  improvement  journey.  Working  on  the  fly  comes  with  major  problems.  

•  Don’t  ignore  the  warning  signs  (Cardiovascular).  •  Commit  one  physician  to  the  team.  An  outside  champion  may  try  to  prop  up  a  team.    

•  SEck  to  the  plan  and  moEvate  people  to  work  together.  

•  Communicate  successes  and  explain  reasons  for  success.  Hold  on  to  those  principles  rather  than  jumping  to  the  next  “shiny  object.”  

•  Financial  improvements  do  follow  improvements  in  quality  of  care.    

Thank  You!  

 Please  submit  your  QuesEons  

and  Answers  

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