SlideShare uma empresa Scribd logo
1 de 30
Baixar para ler offline
RowdMap at DATALAB at Health Datapalooza 2015
RowdMap at DATALAB at Health Datapalooza 2015
PhDs can use open health data
But the goal is to open it to the masses
and let 1000 flowers bloom.
Inother words, can these guysuse it?
Let’s give it a shot
Working with open
health data at
RowdMap, Inc.
for about a year
Government is releasing lots of data….
And it’s been hard work….
But now you don’t
need a PhD to use
this data in a
meaningful way …
For mechanics of how to do this:
http://goo.gl/Y64Fa2
Have an Idea? Attend Bootcamp:
HealthCare Entrepreneurs’ BootCamp
Tomorrow , 4:15pm
Lincoln 2-3-4
So… there’s a lot of data and talk out there
Government
performance
data
Government
provider etc.
data
Government
socio-demo
data
Consumer
web / social
data
Analysis-based derived
data
Sentiment as a Key Driver (psychographic) - measured by Index scores for:
- Domains (chronic, wellness, quality of care, customer satisfaction, customer
service);
- Brands (parent org and you individually)
Market Growth; Census;
Healthy Food; County
Health Rankings &
Indicators; Behavioral
Health Factors; etc.*
Dartmouth Atlas; STAR;
Hospital Compare; Actual,
Expected & Predicted
Readmissions; Part B & D,
etc.*
STAR; Price, Bid,
Rebate;
Hospitals, Nursing
Homes; Market, etc.*
* Dozens of Primary Data Sets, updated at various frequencies
When we say a lot…we mean a lot.
Let’s cut
through
the buzz
And it’s powerful, disruptive, game changing
David Wennberg,
RowdMap Advisory
Board
New Government
Released Referral Data
(Patient flows between
PCPS, specialists,
hospitals and post acute
centers)
Dartmouth Atlas for
Unwarranted Variation
(Decades of research and data on
unwarranted variation by condition
and geography to keep things
apples-to-apples for comparisons,
hence “Unwarranted” in the name)
New Government
Released Performance Data
(Individual providers, groups,
hospitals and post acute
centers including the new part
B&D)
Provider Pattern Intensity Profiles
and Risk Readiness for every
provider, hospital, post acute
center in the US. All preloaded
with no IT.
OPEN DATA –
Particularly powerful when pulled together
Affordable Care Act data to determine
Risk-Readiness of Providers / Networks
CMS: 50% of FFS
will be gone by 2018
The business context has changed- health plans,
government payers, providers, and hospital
systems need to develop Risk-Readiness SM
strategies to excel as they transition from fee-for-
service to pay-for value.
Featured Nationally
US CTO on
RowdMap:
“Visionary
Genius”
What you can do [without a PhD]
With mashups of gov’t data (CMS HHS, Gov, CDC)
Chronic prevalence & physician supply
Population Health Report
Population Report Card
Match practice patterns to the right
risk arrangements – PFV Readiness
Group Risk-Readiness SM Report
Physician Risk-Readiness SM Report
Hospital Risk-Readiness SM Report
Post Acute Center Risk-Readiness SM Report
Risk-Readiness SM Arrangement Match-Maker
Manage clinical care and costs –
Remove No Value Care
Group Unnecessary Cost Report
Physician Unnecessary Cost Report
Hospital Unnecessary Cost Report
Post Acute Center Unnecessary Cost Report
Unnecessary Cost Referral and Value Chain Report
What you can do [without a PhD]
With mashups of gov’t data (CMS HHS, Gov, CDC)
Chronic Prevalence &
Physician Supply
Match Practice Patterns to the right
Risk Arrangements – PFV Readiness
Manage Clinical Care and Costs –
Remove No Value Care
Diabetes Prevalence -
Westchester
Use this data to allocate providers and care management
resources around condition-specific population needs by zip.
Locate clinics, health fairs, etc. based on chronic needs.
Income
Obesity
Depression
Health Opportunity Index
Demand and Supply
Lots of diabetics
but few PCPs
Lots of diabetics
and lots of PCPs
What type of populations?
Medicare FFS Geo. Variation: http://go.cms.gov/1D8j7LE
CDC Behavioral Risk Factor Surveillance: http://1.usa.gov/1PzcisT
Medicare FFS Part B: http://go.cms.gov/OCmyoy
Medicare FFS Part D: http://bit.ly/1mGyBxk
PCP Density –
Westchester
15
Demand and Supply
County Profiles
Largest Counties In Ohio
People use this data to calibrate expectations for profitability
by incorporating population health and provider performance
into product strategy. Use excess to subsidize operations in
counties with fewer high-performing resources
Risk
Scores
Total
Cost
PMPM
Reimbursement
Overall
Star
Chronic
Star
Health
Rank
MA Profit
Opportunity
- MA
Profit
Opportunity
- Exchange
MA
Eligibles
MA
Enrolled
Exchange
Subsidize
d
Exchange
Enrolled
Compare to National
and Regional
Benchmarks
Medicare FFS Geo. Variation: http://go.cms.gov/1D8j7LE
CDC Behavioral Risk Factor Surveillance: http://1.usa.gov/1PzcisT
Medicare FFS Part B: http://go.cms.gov/OCmyoy
Medicare FFS Part D: http://bit.ly/1mGyBxk
What you can do [without a PhD]
With mashups of gov’t data (CMS HHS, Gov, CDC)
Chronic Prevalence &
Physician Supply
Match Practice Patterns to the right
Risk Arrangements – PFV Readiness
Manage Clinical Care and Costs –
Remove No Value Care
At the core of Risk-Readiness SM is
Unwarranted Variation:
RowdMap applies the Dartmouth Atlas for Unwarranted
Variation methodologies to data on Medicare Parts B & D.
This research has been repeatedly validated over the last 30
years and we now have a national data set to apply the
methodologies at a large scale.
The estimated 30% of medical expense that
goes to unnecessary care. This unnecessary
spend drives billing in a fee-for-serve economic
model, but success in pay-for-value comes
from managing and mitigating these pockets
of variation.
Every provider has a unique
practice pattern that informs Risk-
Readiness SM
Pay for Value Readiness
Los Angeles, CA
Compare to National
or Regional
Benchmarks
Pay for Value Readiness
Provider Profiles
Identify highly efficient, Risk-Ready practices and
physicians to profitably grow into. Improve profitability of
lower performing practices with large panel sizes through
modified arrangements or performance improvement plans.
Medicare FFS Part B: http://go.cms.gov/OCmyoy
Medicare FFS Part D: http://bit.ly/1mGyBxk
Referrals: http://1.usa.gov/1FzoEOV
Identify high and low performing hospitals
and post-acute facilities— are there post
acute facilities that hospitals with poor
chronic readmits are routing members to?
Pay for Value Readiness
EOL Hosp Days: Which hospitals fewer end-of-life
days than their peers?
Chronic Admits: Which hospitals see their most
chronic population repeatedly/ with the most
frequency?
Cardiac Imaging: Which hospitals are more likely to
over-utilize cardiac imaging compared to their peers?
Dartmouth Atlas: http://bit.ly/1GXvlJp
CMS Hospital Compare: https://goo.gl/p8MtoI
CMS Hospital Readmissions: http://goo.gl/02KnQd
CMS Nursing Home Compare: https://goo.gl/3DpT8m
Pay for Value Readiness
Great profile for
aggressive risk
Tread carefully for
some risk
Match appropriate risk arrangements based on
provider practice patterns and
Population characteristics within a geography.
What you can do [without a PhD]
With mashups of gov’t data (CMS HHS, Gov, CDC)
Chronic Prevalence &
Physician Supply
Match Practice Patterns to the right
Risk Arrangements – PFV Readiness
Manage Clinical Care and Costs –
Remove No Value Care
Remove no-value Care
Manage Unnecessary Spend
Risk-Readiness℠ looks at a different
category of spending
Shift focus from clinical edits, audits, and recovery efforts
to identifying care that is clinically appropriate, but
unnecessary. Historical efforts have shown returns, but
they only look at a fraction of total spending. Unnecessary
care can account for up to 30% of total spending and
provides significantly larger opportunities for cost
containment and quality improvement.
Clinically Appropriate,
but Unnecessary Care
(30% of spend)
Claims Spend for a Health Plan
Necessary Utilization
(70%)
“It’s generally agreed that about
30 percent of what we spend on
health care is unnecessary. If we
eliminate the unneeded care, there
are more than enough resources in
our system to cover everybody.”
-Dr. Elliott Fisher,
Dartmouth Institute for Health Policy
Remove no-value Care
Manage Unnecessary Spend
RowdMap tackles the 30% of the U.S. health care spend
that goes to clinically appropriate, but unnecessary care
Over $9B in
Orange County, CA
How much unnecessary spend is in your market?
Over $66B in Florida
$850 Billion Unnecessary Spend* in 2014
Least Unnecessary
Spend
Most
Unnecessary Spend
RowdMap tackles the 30% of U.S. health care
spend that goes to clinically appropriate, but
unnecessary care. RowdMap’s models
identify the cost-savings opportunities in a
geography based on the collective intensity
of care delivered by doctors in that area.
* Unnecessary Spend =
(Dartmouth Avg cost) * (Population) *
(RowdMap Network Opportunity Index)
Remove no-value Care
Manage Unnecessary Spend
Unnecessary Spend in Florida
In Broward Co. alone,
there is over $7.6B in
unnecessary spend.
Let’s look at which hospitals, groups and physicians
account for this and for what conditions
Physician Marketshare
by Major Clinical Categories
Remove no-value Care
Manage Unnecessary Spend
Match appropriate risk arrangements based on provider practice
patterns and Population characteristics within a geography.
Hospital Marketshare
by Major Clinical Categories
Provider Group Marketshare
by Major Clinical Categories
Unnecessary Spend in Broward
By condition across hospitals,
groups and physicians
This Physician.
Let’s start here
This GroupThis Hospital
Circulatory
Muscular-
skeletal
Respiratory
Remove no-value Care
Manage Unnecessary Spend
All contents are proprietary to RowdMap, Inc. and are being provided on a confidential basis.
Any use, reproduction or distribution of this information, in whole or in part, or the disclosure of any of its contents
without the prior written consent of the Company, is prohibited.
Physicians Driving Unnecessary Care in Broward
Musculoskeletal care is major contributor to unnecessary spend in Broward. Let’s
take a physician who is not an outlier but in the middle of the pack such as Dr.
Spend*. Let’s walk through what his clinically acceptable, but medically
unnecessary, practice pattern creates in unnecessary spend.
Remove no-value Care
Manage Unnecessary Spend
Referral Patterns and Physician Value Chains
Identify high performing providers and downstream
referral patterns. Encourage referrals to
high-performing specialists.
Remove no-value Care
Manage Unnecessary Spend
Least Unnecessary
Spend
Most
Unnecessary Spend
Option 2: Reinforce
highest-performing referral
and care pathways.
Increase the number of patient interactions
with green dot doctors.
Option 1: Change provider behavior.
Requires lots of provider education. Requires
payer to make up a significant portion of a
provider’s revenue. Increase the number of
green dot doctors.
Zoom to zip
Remove no-value Care
Manage Unnecessary Spend
If had same ratio as :
• His decompression rate would drop from
6.01 to 0.436 per patient.
• Which translates to 2,608 fewer
decompressions per year.
• At an average cost of $332 per
decompression, this represents potential
savings of over $850K
If decompression to fusion rate were
average for orthopedic surgeons:
• He would have 1629 fewer decompressions
for a potential savings of $540K.
*Actual physician names have been changed.
For every 10 back fusions, does
103 decompressions
For every 10 back fusions,
does 2 decompressions.
Dr. Save*
Dr. Spend’s
Dr. Spend*
Dr. Save*
That’s one physician, with one procedure, in one clinical condition.
This savings would not be picked up in unit cost or utilization analysis,
but cumulatively dwarfs fraud, waste and abuse outliers.
Intense practice patterns like this power FFS arrangements
but success in Pay for Value comes from identifying Risk-Ready providers.
Dr. Spend*
Start with Data for Business Context then add Tech.
The ACA at your finger tips
For Payers & Providers

Mais conteúdo relacionado

Mais de RowdMap has joined Cotiviti

What's Next in Healthcare Delivery Systems: High-Value Care
What's Next in Healthcare Delivery Systems: High-Value CareWhat's Next in Healthcare Delivery Systems: High-Value Care
What's Next in Healthcare Delivery Systems: High-Value CareRowdMap has joined Cotiviti
 
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...RowdMap has joined Cotiviti
 
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...RowdMap has joined Cotiviti
 
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...RowdMap has joined Cotiviti
 
RowdMap HIMSS 2016 - No Value Care Meets No IT Needed
RowdMap HIMSS 2016 - No Value Care Meets No IT NeededRowdMap HIMSS 2016 - No Value Care Meets No IT Needed
RowdMap HIMSS 2016 - No Value Care Meets No IT NeededRowdMap has joined Cotiviti
 
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...RowdMap has joined Cotiviti
 
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...RowdMap has joined Cotiviti
 
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...RowdMap has joined Cotiviti
 
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...RowdMap has joined Cotiviti
 
Using Technology & Data Infrastructure to Realize the Potential of SIM Reforms
Using Technology & Data Infrastructure to Realize the Potential of SIM ReformsUsing Technology & Data Infrastructure to Realize the Potential of SIM Reforms
Using Technology & Data Infrastructure to Realize the Potential of SIM ReformsRowdMap has joined Cotiviti
 
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...Fifty Shades of Variation: Building a Network of High Quality Performers as Y...
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...RowdMap has joined Cotiviti
 
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...RowdMap has joined Cotiviti
 

Mais de RowdMap has joined Cotiviti (20)

What's Next in Healthcare Delivery Systems: High-Value Care
What's Next in Healthcare Delivery Systems: High-Value CareWhat's Next in Healthcare Delivery Systems: High-Value Care
What's Next in Healthcare Delivery Systems: High-Value Care
 
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...
Making out Like Bandits: The Unexpected Rise of PCP & Urgent Care and the Hid...
 
Health:Further Public Good from Market Forces
Health:Further Public Good from Market ForcesHealth:Further Public Good from Market Forces
Health:Further Public Good from Market Forces
 
RowdMap at the Cape
RowdMap at the Cape RowdMap at the Cape
RowdMap at the Cape
 
RowdMap Health Datapalooza Innovation Showcase
RowdMap Health Datapalooza Innovation ShowcaseRowdMap Health Datapalooza Innovation Showcase
RowdMap Health Datapalooza Innovation Showcase
 
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...
RowdMap Health Datapalooza Creating a Virtual Cycle: designing networks to mi...
 
NCVHS Data Access and Use Joshua Rosenthal
NCVHS Data Access and Use Joshua RosenthalNCVHS Data Access and Use Joshua Rosenthal
NCVHS Data Access and Use Joshua Rosenthal
 
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...
Health Datapalooza - Creating a Virtuous Cycle: Design and Curate a Risk-Read...
 
Are You Risk-Ready?
Are You Risk-Ready?Are You Risk-Ready?
Are You Risk-Ready?
 
RowdMap Risk-Readiness® Summary Slides
RowdMap Risk-Readiness® Summary SlidesRowdMap Risk-Readiness® Summary Slides
RowdMap Risk-Readiness® Summary Slides
 
RowdMap Risk-Readiness® for Providers
RowdMap Risk-Readiness® for ProvidersRowdMap Risk-Readiness® for Providers
RowdMap Risk-Readiness® for Providers
 
RowdMap HIMSS 2016 - No Value Care Meets No IT Needed
RowdMap HIMSS 2016 - No Value Care Meets No IT NeededRowdMap HIMSS 2016 - No Value Care Meets No IT Needed
RowdMap HIMSS 2016 - No Value Care Meets No IT Needed
 
RowdMap in a Nutshell - HIMSS 16
RowdMap in a Nutshell - HIMSS 16RowdMap in a Nutshell - HIMSS 16
RowdMap in a Nutshell - HIMSS 16
 
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...
Capturing Your Hidden Value: Using Newly Released Government Benchmark Data t...
 
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...
Network as Strategic Advantage: Curating a Risk-Ready Network to Succeed in a...
 
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...
Using Newly-Released HHS Benchmark Data to Negotiate and Succeed in Value and...
 
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...
Using Government Benchmarks to Succesfuly Set up an Accountable Care Orginiza...
 
Using Technology & Data Infrastructure to Realize the Potential of SIM Reforms
Using Technology & Data Infrastructure to Realize the Potential of SIM ReformsUsing Technology & Data Infrastructure to Realize the Potential of SIM Reforms
Using Technology & Data Infrastructure to Realize the Potential of SIM Reforms
 
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...Fifty Shades of Variation: Building a Network of High Quality Performers as Y...
Fifty Shades of Variation: Building a Network of High Quality Performers as Y...
 
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...
Unexpected Transparency: Underserved Populations, Unwarranted Variation and U...
 

Último

Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationGiorgio Carbone
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxDwiAyuSitiHartinah
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructuresonikadigital1
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introductionsanjaymuralee1
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptaigil2
 
Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Vladislav Solodkiy
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityAggregage
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerPavel Šabatka
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?sonikadigital1
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...PrithaVashisht1
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Guido X Jansen
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionajayrajaganeshkayala
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.JasonViviers2
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxVenkatasubramani13
 
SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024Becky Burwell
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)Data & Analytics Magazin
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best PracticesDataArchiva
 

Último (17)

Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - Presentation
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructure
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introduction
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .ppt
 
Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayer
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual intervention
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptx
 
SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices
 

RowdMap at DATALAB at Health Datapalooza 2015

  • 3. PhDs can use open health data But the goal is to open it to the masses and let 1000 flowers bloom. Inother words, can these guysuse it? Let’s give it a shot Working with open health data at RowdMap, Inc. for about a year
  • 4. Government is releasing lots of data…. And it’s been hard work…. But now you don’t need a PhD to use this data in a meaningful way … For mechanics of how to do this: http://goo.gl/Y64Fa2 Have an Idea? Attend Bootcamp: HealthCare Entrepreneurs’ BootCamp Tomorrow , 4:15pm Lincoln 2-3-4
  • 5. So… there’s a lot of data and talk out there
  • 6. Government performance data Government provider etc. data Government socio-demo data Consumer web / social data Analysis-based derived data Sentiment as a Key Driver (psychographic) - measured by Index scores for: - Domains (chronic, wellness, quality of care, customer satisfaction, customer service); - Brands (parent org and you individually) Market Growth; Census; Healthy Food; County Health Rankings & Indicators; Behavioral Health Factors; etc.* Dartmouth Atlas; STAR; Hospital Compare; Actual, Expected & Predicted Readmissions; Part B & D, etc.* STAR; Price, Bid, Rebate; Hospitals, Nursing Homes; Market, etc.* * Dozens of Primary Data Sets, updated at various frequencies When we say a lot…we mean a lot.
  • 8. And it’s powerful, disruptive, game changing David Wennberg, RowdMap Advisory Board
  • 9. New Government Released Referral Data (Patient flows between PCPS, specialists, hospitals and post acute centers) Dartmouth Atlas for Unwarranted Variation (Decades of research and data on unwarranted variation by condition and geography to keep things apples-to-apples for comparisons, hence “Unwarranted” in the name) New Government Released Performance Data (Individual providers, groups, hospitals and post acute centers including the new part B&D) Provider Pattern Intensity Profiles and Risk Readiness for every provider, hospital, post acute center in the US. All preloaded with no IT. OPEN DATA – Particularly powerful when pulled together Affordable Care Act data to determine Risk-Readiness of Providers / Networks
  • 10. CMS: 50% of FFS will be gone by 2018 The business context has changed- health plans, government payers, providers, and hospital systems need to develop Risk-Readiness SM strategies to excel as they transition from fee-for- service to pay-for value.
  • 11. Featured Nationally US CTO on RowdMap: “Visionary Genius”
  • 12. What you can do [without a PhD] With mashups of gov’t data (CMS HHS, Gov, CDC) Chronic prevalence & physician supply Population Health Report Population Report Card Match practice patterns to the right risk arrangements – PFV Readiness Group Risk-Readiness SM Report Physician Risk-Readiness SM Report Hospital Risk-Readiness SM Report Post Acute Center Risk-Readiness SM Report Risk-Readiness SM Arrangement Match-Maker Manage clinical care and costs – Remove No Value Care Group Unnecessary Cost Report Physician Unnecessary Cost Report Hospital Unnecessary Cost Report Post Acute Center Unnecessary Cost Report Unnecessary Cost Referral and Value Chain Report
  • 13. What you can do [without a PhD] With mashups of gov’t data (CMS HHS, Gov, CDC) Chronic Prevalence & Physician Supply Match Practice Patterns to the right Risk Arrangements – PFV Readiness Manage Clinical Care and Costs – Remove No Value Care
  • 14. Diabetes Prevalence - Westchester Use this data to allocate providers and care management resources around condition-specific population needs by zip. Locate clinics, health fairs, etc. based on chronic needs. Income Obesity Depression Health Opportunity Index Demand and Supply Lots of diabetics but few PCPs Lots of diabetics and lots of PCPs What type of populations? Medicare FFS Geo. Variation: http://go.cms.gov/1D8j7LE CDC Behavioral Risk Factor Surveillance: http://1.usa.gov/1PzcisT Medicare FFS Part B: http://go.cms.gov/OCmyoy Medicare FFS Part D: http://bit.ly/1mGyBxk PCP Density – Westchester
  • 15. 15 Demand and Supply County Profiles Largest Counties In Ohio People use this data to calibrate expectations for profitability by incorporating population health and provider performance into product strategy. Use excess to subsidize operations in counties with fewer high-performing resources Risk Scores Total Cost PMPM Reimbursement Overall Star Chronic Star Health Rank MA Profit Opportunity - MA Profit Opportunity - Exchange MA Eligibles MA Enrolled Exchange Subsidize d Exchange Enrolled Compare to National and Regional Benchmarks Medicare FFS Geo. Variation: http://go.cms.gov/1D8j7LE CDC Behavioral Risk Factor Surveillance: http://1.usa.gov/1PzcisT Medicare FFS Part B: http://go.cms.gov/OCmyoy Medicare FFS Part D: http://bit.ly/1mGyBxk
  • 16. What you can do [without a PhD] With mashups of gov’t data (CMS HHS, Gov, CDC) Chronic Prevalence & Physician Supply Match Practice Patterns to the right Risk Arrangements – PFV Readiness Manage Clinical Care and Costs – Remove No Value Care
  • 17. At the core of Risk-Readiness SM is Unwarranted Variation: RowdMap applies the Dartmouth Atlas for Unwarranted Variation methodologies to data on Medicare Parts B & D. This research has been repeatedly validated over the last 30 years and we now have a national data set to apply the methodologies at a large scale. The estimated 30% of medical expense that goes to unnecessary care. This unnecessary spend drives billing in a fee-for-serve economic model, but success in pay-for-value comes from managing and mitigating these pockets of variation. Every provider has a unique practice pattern that informs Risk- Readiness SM Pay for Value Readiness
  • 18. Los Angeles, CA Compare to National or Regional Benchmarks Pay for Value Readiness Provider Profiles Identify highly efficient, Risk-Ready practices and physicians to profitably grow into. Improve profitability of lower performing practices with large panel sizes through modified arrangements or performance improvement plans. Medicare FFS Part B: http://go.cms.gov/OCmyoy Medicare FFS Part D: http://bit.ly/1mGyBxk Referrals: http://1.usa.gov/1FzoEOV
  • 19. Identify high and low performing hospitals and post-acute facilities— are there post acute facilities that hospitals with poor chronic readmits are routing members to? Pay for Value Readiness EOL Hosp Days: Which hospitals fewer end-of-life days than their peers? Chronic Admits: Which hospitals see their most chronic population repeatedly/ with the most frequency? Cardiac Imaging: Which hospitals are more likely to over-utilize cardiac imaging compared to their peers? Dartmouth Atlas: http://bit.ly/1GXvlJp CMS Hospital Compare: https://goo.gl/p8MtoI CMS Hospital Readmissions: http://goo.gl/02KnQd CMS Nursing Home Compare: https://goo.gl/3DpT8m
  • 20. Pay for Value Readiness Great profile for aggressive risk Tread carefully for some risk Match appropriate risk arrangements based on provider practice patterns and Population characteristics within a geography.
  • 21. What you can do [without a PhD] With mashups of gov’t data (CMS HHS, Gov, CDC) Chronic Prevalence & Physician Supply Match Practice Patterns to the right Risk Arrangements – PFV Readiness Manage Clinical Care and Costs – Remove No Value Care
  • 22. Remove no-value Care Manage Unnecessary Spend Risk-Readiness℠ looks at a different category of spending Shift focus from clinical edits, audits, and recovery efforts to identifying care that is clinically appropriate, but unnecessary. Historical efforts have shown returns, but they only look at a fraction of total spending. Unnecessary care can account for up to 30% of total spending and provides significantly larger opportunities for cost containment and quality improvement. Clinically Appropriate, but Unnecessary Care (30% of spend) Claims Spend for a Health Plan Necessary Utilization (70%) “It’s generally agreed that about 30 percent of what we spend on health care is unnecessary. If we eliminate the unneeded care, there are more than enough resources in our system to cover everybody.” -Dr. Elliott Fisher, Dartmouth Institute for Health Policy
  • 23. Remove no-value Care Manage Unnecessary Spend RowdMap tackles the 30% of the U.S. health care spend that goes to clinically appropriate, but unnecessary care Over $9B in Orange County, CA How much unnecessary spend is in your market? Over $66B in Florida $850 Billion Unnecessary Spend* in 2014 Least Unnecessary Spend Most Unnecessary Spend RowdMap tackles the 30% of U.S. health care spend that goes to clinically appropriate, but unnecessary care. RowdMap’s models identify the cost-savings opportunities in a geography based on the collective intensity of care delivered by doctors in that area. * Unnecessary Spend = (Dartmouth Avg cost) * (Population) * (RowdMap Network Opportunity Index)
  • 24. Remove no-value Care Manage Unnecessary Spend Unnecessary Spend in Florida In Broward Co. alone, there is over $7.6B in unnecessary spend. Let’s look at which hospitals, groups and physicians account for this and for what conditions
  • 25. Physician Marketshare by Major Clinical Categories Remove no-value Care Manage Unnecessary Spend Match appropriate risk arrangements based on provider practice patterns and Population characteristics within a geography. Hospital Marketshare by Major Clinical Categories Provider Group Marketshare by Major Clinical Categories Unnecessary Spend in Broward By condition across hospitals, groups and physicians This Physician. Let’s start here This GroupThis Hospital Circulatory Muscular- skeletal Respiratory
  • 26. Remove no-value Care Manage Unnecessary Spend All contents are proprietary to RowdMap, Inc. and are being provided on a confidential basis. Any use, reproduction or distribution of this information, in whole or in part, or the disclosure of any of its contents without the prior written consent of the Company, is prohibited. Physicians Driving Unnecessary Care in Broward Musculoskeletal care is major contributor to unnecessary spend in Broward. Let’s take a physician who is not an outlier but in the middle of the pack such as Dr. Spend*. Let’s walk through what his clinically acceptable, but medically unnecessary, practice pattern creates in unnecessary spend.
  • 27. Remove no-value Care Manage Unnecessary Spend Referral Patterns and Physician Value Chains Identify high performing providers and downstream referral patterns. Encourage referrals to high-performing specialists.
  • 28. Remove no-value Care Manage Unnecessary Spend Least Unnecessary Spend Most Unnecessary Spend Option 2: Reinforce highest-performing referral and care pathways. Increase the number of patient interactions with green dot doctors. Option 1: Change provider behavior. Requires lots of provider education. Requires payer to make up a significant portion of a provider’s revenue. Increase the number of green dot doctors. Zoom to zip
  • 29. Remove no-value Care Manage Unnecessary Spend If had same ratio as : • His decompression rate would drop from 6.01 to 0.436 per patient. • Which translates to 2,608 fewer decompressions per year. • At an average cost of $332 per decompression, this represents potential savings of over $850K If decompression to fusion rate were average for orthopedic surgeons: • He would have 1629 fewer decompressions for a potential savings of $540K. *Actual physician names have been changed. For every 10 back fusions, does 103 decompressions For every 10 back fusions, does 2 decompressions. Dr. Save* Dr. Spend’s Dr. Spend* Dr. Save* That’s one physician, with one procedure, in one clinical condition. This savings would not be picked up in unit cost or utilization analysis, but cumulatively dwarfs fraud, waste and abuse outliers. Intense practice patterns like this power FFS arrangements but success in Pay for Value comes from identifying Risk-Ready providers. Dr. Spend*
  • 30. Start with Data for Business Context then add Tech. The ACA at your finger tips For Payers & Providers