reducing hvis procedure costs through data transparency · 2017. 7. 20. · prathibha krishna...
TRANSCRIPT
Reducing HVIS Procedure Costs Through Data Transparency
Leslie Mulshenock, Director Of Heart & Vascular Informatics
Matthew Paul Esham, Heart & Vascular Information Technology Service Line Manager
Conflict of Interest Presenters
Leslie Mulshenock, MBA
Matthew Paul Esham
Has no real or apparent conflicts of interest to report.
Additional Contributors
Sangita Godbole - Senior Operational Business Analyst
Prathibha Krishna Reddy- Senior Operational Business Analyst
William Weintraub-Chief, Section of Cardiology
Billie Speakman- Vice President, Center for Heart & Vascular Health
Overview:
• In the current healthcare environment, costs matter.
• Sharing data consistently drives changes in behavior.
We’ll review:
• A brief history of supply costing.
• The value of attribution in data analysis.
• Communicating meaningful data.
Learning Objectives
• Analyze how a detailed attribute model using procedure and supply
case level data can be used to aggregate invasive lab visits to
compare costs between like procedures
• Analyze how using contrast agents can be evaluated against your
gross population to look for savings opportunities
• Analyze how using radial access in the heart catheterization lab can
result in a reduction in costs as well as a reduced length of stay
How Benefits Were Realized for the Value of Health IT
• Communication and transparency
of data is critical to understanding
current state of the patient
population as well as in driving
changes in support of better
population health.
• Use a basic data model to
analyze case level data, identify
opportunities and drive practice
changes and cost savings
through optimal care delivery.
http://www.himss.org/ValueSuite
Why Do Costs Matter?
In order to manage costs, risks, and survive with bundled payment models we need to know and understand costs and the drivers behind why they vary amongst patients.
Subsequently, we need to translate cost knowledge into better outcomes and an optimal patient care experience.
Accountable Care
Organizations
Bundled Payments
Population Health
Management
Organic Growth & Agile Development
• Our Proof Of Concept (POC) was created
using Pivot Tables & VLOOKUP Functions
• Supports advanced
visualizations.
• The POC work allowed us to justify
building a dedicated Data Mart
2012
2013
2014
2015
History Of Our Costing Project
• We knew we had a large degree of variability in our case to case costing based on finance data.
Orange indicates the case was an intervention.
Blue indicates only a diagnostic procedure was performed.
Circle size shows the sum of the billed price for an individual case or patient encounter.
History Of Our Costing Project • This variance was even greater when we looked at cost per
procedure by the major practitioner groups.
Exclusions
Heart Codes
Range: $44,852
Structural Heart
Range: $30,852
IABP/ICE
Range: $11,009
The Power Of Attributes
• Attributes allow us to easily convert case data into meaningful analysis.
• >1 Million Possible Attribute Combinations
• <25 Combinations drive value
Aggregate Cases By Attributes
Analyze Costs Within Groups
Review Cases
With Cost Outliers
Identify New Case Attributes
Type Outputs
Case Level
Elective vs. Emergent
Inpatient vs. Outpatient
Demographic Information
Supply
Consumption
Part Category
Procedural Physician
Visit Data
Length of Stay
ICD & DRG Codes
Registry Data
Elix Hauser Comorbidities
CPT 33967 Insertion of
intra-aortic balloon assist
device, percutaneous
Attribute Mapping & Logic
• Direct mappings allows for simple data relationships to be easily captured.
• Any combination of if, and , or logic can be used to build an attribute value
Sets
IABP Attribute = 1
Case
Description Is
“Diagnostic”
Case Type =
“Diagnostic”
Unless Supplies
With Category Type
= “Stent” Are Used
Then Case Type =
“Interventional”
Sets
Case Attributes
• We knew we had a large degree of variability in our case to case costing based on finance data.
CPT33967
CPT93451
Part45235
Part49005
Part34593
Part55509
Desc: Diagnostic
Case Data
Case ID Type ICE Contrast Contrast
15-100 Intervention 0 1 Iohexol
Visit Attributes
• The case level data is then merged with visit level data to capture length of stay, readmissions, and comorbidities, as well as multiple other data points.
Case ID Type ICE Contrast Contrast
15-100 Intervention 0 1 Iohexol
Visit Type
LOS (Days)
PRI Diagnosis
30Day Readmit
60Day Readmit Comorbidities
IP 2.4 410.21 0 1 4
Attributes Convert Data Into Knowledge
Attributes Convert Data Into Knowledge
Attributes Convert Data Into Knowledge
Radial Access Reduces Risks
• Radial access reduced the odds of major bleeding by 73% in
patients undergoing coronary angiography or intervention
compared to femoral access.
• Trend toward reduction in the composite of death, MI, or
stroke
• Clinically relevant 30% reduction in cardiovascular events Sanjit et al; Radial versus femoral access for coronary angiography or intervention and the impact on major bleeding and
ischemic events: A systematic review and meta-analysis of randomized trials; American Heart Journal: Volume 157, Issue 1,
January 2009, Pages 132–140
Data in this article has since been supported in randomized clinical trials.
American College of Cardiology PCI Registry Data
• The decreased risks and costs associated with radial access are driving nationwide changes
Radial Access Length Of Stay
• As we continue to work on discharge order sets and care extender coverage we are continuing to drive down our Radial Procedure Length of Stay.
• Currently that savings is 1.15 days on average
Changing Practice Based On Data
Changing Practice Based On Data
Radial Access Average Procedure Costs
• The primary driver in the direct supply cost is the savings resulting from not using a closure device.
Opportunity Cost FY 2015
• Using a target of 50% Radial we can calculate the possible opportunity using last Fiscal Year’s volume.
Radial Opportunity Cost FY 2016
• Using education and by sharing performance data we have reduced our lost opportunity dollars by 61% in the first half of FY16
Note: Data is for first half of FY16. FY begins in July.
Administrative Data Versus Clinical
• The more expensive “Kidney Safe” contrast was used 29% of the time while our clinical data showed less than half those patients may have benefited from it.
Elevated Creatinine was identified as:
Males with greater than 1.3 mg/dL
Females with greater than 1.1 mg/dL
Administrative Data Versus Clinical
• The more expensive “Kidney Safe” contrast was used 29% of the time while our clinical data showed less than half those patients may have benefited from it.
Talking To Our Clinicians
• The majority of our clinicians were not aware of the cost differential between Iodixanol and other available contrasts
• Consumption data created awareness.
• Physicians & Staff were educated so that the less expensive contrast was pulled unless the Iodixanol was specifically requested.
• Discussion and regular review of the data at monthly and quarterly practice meetings drive awareness and improve appropriate usage of Iodixanol.
Data & Discussion Changed Usage
• Discussion and regular review of the data at monthly and quarterly practice meetings drive awareness and improve usage
Cath
Iodixanol
Usage
29.0%
To
14.3%
Data & Discussion Changed Usage
• Discussion and regular review of the data at monthly and quarterly practice meetings drive awareness and improve usage
VIR
Iodixanol
Usage
15.6%
To
10.9%
Contrast Outcomes
• We looked at three outcomes when evaluating whether the change in contrast usage had any negative impacts
• Length of stay
• Readmissions
• Increase in Acute Kidney Injury
• Impact on cost
Length Of Stay Outcome
• The length of stay and variance between the groups show no negative impact post the change in usage.
Readmissions
• Readmissions correlated with the number of comorbidities. Contrast agents were shown not to have any impact on readmission rates.
Acute Kidney Injury
• Increased use of other contrast did not have negative impact on creatinine rise based on initial analysis.
Elevated Creatinine was identified as:
CI-AKI indicator of 25% relative rise in
creatinine at 72 hours was used to
identify patients at risk.
Calendar Year 2013
2014
Total Cases 2794 2858
Total Elevated Creatinine Cases 6.0% 5.3%
Cath Contrast Costing
• The average cost differential between Iodixanol and other contrasts was $280
Cath Contrast Costing
Cath Contrast Costing
Average
Annual Cath
Contrast
Baseline
Savings Of
$151,231
Interventional Cost Per Case
42
$ 3,158 $ 2,956
$ 2,038
Return On Investment
• 3 Year Costs < $500,000
• 2 Database Servers & Licenses
• 1 Person 50% Project Manager
• 1 Person 50% Requirements Analyst
• 2 People 100% Data Analyst/DBA
• 3 Year Savings Estimates
• Diagnostic = $460,327
• Intervention = $3,257,603
Total 3 Year Savings Estimated At
$3,717,930
43
Why Data Matters
• In order to successful manage a population; we must be able to do all of the following:
• Track utilization & allocation of resources
• Understand costs associated with providing care
• Manage the acute episode and post acute care provided to the patient to sustain health
• Compare treatment interventions against best practice care guidelines
• Analyze outcomes to determine successes and failures, improvements and opportunities
How to Communicate with Providers
• Consistent Communication Mechanism
– Data is shared at routine attending meetings
– Analysis: “The Why” is also shared
• Collegial Environment
– Data generates discussions versus mandates regarding choices
• Provider Engagement in contracts & vendor negotiations
– Enables optimal pricing based on product functionality so patient need versus cost drives choice
• Encourage Positive Deviance
Data
Analysis
Communication
Change
What’s Next?
• Same Day Discharge for Low Risk Outpatient Procedures
• Implementation of Agile Clinical Pathways
• Reducing Procedural Readmissions (AMI, HVIS)
• Risk prediction Models for Adverse Events, LOS, Costs & Readmissions
Individual Performance
versus Peers
• Eliminate unnecessary variations
in care
• Identify Opportunities
• Increased engagement in
individual performance
• Improved Population Health
A Summary of How Benefits Were Realized for the Value of Health IT Savings can be generated by performing
a basic analysis of cost data and sharing
findings to providers in conjunction with
relevant clinical information.
Understanding the composition of your
current patient population and how and
WHY it changes overtime is critical to
population health management.
http://www.himss.org/ValueSuite
Roadmap for Success
• Development of a Conceptual & Common Data Model
• Create a stable data environment which can facilitate consistent, real time updates-AGILE
• Align priorities to critical service and organizational needs.
• Ensure appropriate resources within services are allocated to data development and report out.
• Support a collegial environment and a continuous culture of learning and performance improvement driven by data analysis and provider engagement.
• Ensure Transparency with the data-make sure the audience can understand and interpret the display.
Questions
• Leslie Mulshenock, MBA
• Matthew Paul Esham