Your SlideShare is downloading. ×
Healthbus deck
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Introducing the official SlideShare app

Stunning, full-screen experience for iPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Healthbus deck

68
views

Published on

High level pitch for claims in the cloud service that HealthBus team is offering.

High level pitch for claims in the cloud service that HealthBus team is offering.

Published in: Health & Medicine

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
68
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. BAAASBenefit Analytics as a Service Subscription Based Base Price of Population + Transaction Volume Super Simple to Setup Super Simple to Use (just drop X12) Enables collaboration with customers
  • 2. Just-Drop-It Processing Simple Integration (Everyone already does this) Drop 834 (member eligibility) Drop 837 (claim) Drop 835 (claim payment) Simple and easy to configure Benefit Structure
  • 3. Simple Integration Three files have all the data we need All payers can generate these files ($0 implementation and integration required at customer) Asynchronous processing of file types Super quick and can scale out or in if necessary Designed so no transactions fail
  • 4. Benefit Analytics Allow basic ‘queries’ to start with What’s total cost of my population that received acupuncture v. those who did not for one year What’s total cost for 9 months before and after for those who had a natural birth v. those who had a cesarean Analyze data for other meaningful patterns Hospital XYZ is billing 150% of your other hospitals Trend Analysis for predicting future utilization
  • 5. V1 Monetization Strategy Monthly Subscription Based Base of Total Population * Fixed Amount (these come in the 834 files) Plus Total Claims * Fixed Amount (these come in the 837 files)
  • 6. Road Map V2: Better V3: Services V1: Benefit V4: Optimize Claim Review Analytics benefits Processing Processing
  • 7. V1: Benefit Analytics Accept Flat Files for Initial Setup Payer Drops 834s Payer Drops 837s Payer Drops 835s Allows Queries and Displays Graphs Learns meaningful queries across customers
  • 8. V2: Claims Pricing Attempt to reverse engineer rules (aka edits) Member responsibility Provider contracts Pricing schedules Payer configures edits Payer Drops 834s Payer Drops 837s Payer Picks up 835s
  • 9. V3: Services Review Pricing Based on Claim Pricing rules Payer Drops 278 Request Payer Picks up 278 Response Charged per 278 Request Transaction
  • 10. Potential OtherTransactions + Revenue Member Correspondence Inpatient + Outpatient Pricing Claims Payment Premium Billing Capitation Fraud Detection
  • 11. Other Perks Basic restful API against public data sets useful for health care enterprise CMS Pricing (Price for Service with geographic multipliers) NPPES Data (National Provider Database) Grow the API over time, managing this for enterprises is painful