Gritman Medical Center

1
Gritman Medical Center

• Ben Wood
• Tessa Scholl
• Marc Boisvert
• Mimi Sproul
• Darren Schnider

2
Problems

• Delays
• Internal
• Common among users of manual systems
• Every time someone comes in contact with a
  process, there is a 5 chance that an error will
  occur within the step
• Unneeded queues build up
• Charts are not taken by staff frequently because
  it reduces productivity
• Every process that has a 95 chance of success
  (1- 5 of error) requires additional time in
  auditing to fix
• Up to 10 minutes hands on time in system
• Days out of system if returned by payee
• External
• People do not pay

3
Problems (continued)

• Faster collections from insurance and payee
• Problems
• Extended time for bill insurances
• Non clean bills
• Ideal scenario
• Collections would take place immediately post
  treatment
• Problems solved
• Possible error processing claims
• Delay before Final DRG can be sent
• Improved personnel allocation
• Can be done with automated coding and billing
  system

4
Scope Statement

• Modeling current billing process to determine
  accounts receivable days and chart processing
  times
• Examining possible reengineering and mistake
  proofing of system
• Determining NPVs of implementing new systems

5
Objectives

• Reducing AR time
• Reducing delay of collections from insurance and
  self pay account to increase TVOM
• Emergency Room Coding Record Keeping
• Finding the best solution to decrease lag time
• Five Day Window
• Reducing it to 3 days
• Additional Improvements
• Institutional clean claims increased 10
• Increased billing productivity by 70
• Decreased error leads to less auditing time
• http//www.medassets.com/casestudies/pages/foxcha
  secancercenter.aspx
• http//www.medassets.com/casestudies/pages/wellm
  onthealthsystems.aspx

6
Findings

• Apparent long wait times in 6.5 day window
  processes
• Enough errors in billing to make AR age 57.37
  days average
• Industry findings that AR can be reduced
  dramatically, to at most 30 days

7
Recommendations

• Automate billing system
• Add a new financial councilor
• Decrease self-pay time
• If the system is unable to be automated, use
  improved business rules
• Able to reduce queue times and improve throughput

8
Road map of remaining presentation

• Model Description
• Model Inputs
• Sensitivity Analysis
• Additional improvements
• Emergency room
• Current process and improvement
• New billing program example
• Accounts to concentrate on

9
Model Description

• Gathered Information and assumptions
• Inputs
• Hours worked, chart processing times, staffing
  schedules, average payee payment periods and 90
  patient types
• Information collected from actual Gritman medical
  staff member
• Model Purpose
• Accurately model current billing cycle through
  Gritman medical center
• Sensitivity Analysis
• Individual changes made and reviewed for
  improvement

10
Sensitivity Analysis

• Our purpose is to reduce Gritmans AR by 40 to
  improve costs
• Changed general business rules reducing process
  time while keeping old system
• We are also investigating 30, 20, 10 and
  comparing each NPV to find the break even point

11
Model Inputs

• 5 Types of Patients
• Out-patient Sleep Study OP Sleep Study
• Out-patient Laboratory/Out-patient Radiology
  OPL/OPR
• In-patient/Out-patient Surgery/Observation
  IP/OPS/Observation
• Emergency Room ER
• Therapy/Series/Adult Day Health
  Therapy/Series/ADH
• 3 Categories of Payment Amounts
• gt1,500
• 1,500 - 7,500
• lt7,500
• 6 Payment Options
• Medicare
• Medicaid
• Blue Cross
• Commercial
• Self-Pay
• Charity

12
Current Emergency Room Process
13
Proposed Emergency Room process
14
Comparison of Processes
This new process reduces both time and error
increasing revenue
15
Sage Intergy EHR system
16
Largest AR issues

• Average of AR

17
Largest AR issues

• The highlighted percentages are how many more
  days each of the corresponding insurances are
  taking over the average

18
Comparison
19
Pro-Active Bill Collection Example

• Different communication forms will reduce
  collection time of accounts
• Increase the likely-hood of collection on a
  Self-pay Account
• Students are less likely to receive/respond to
  letters
• Should collect email at admissions
• Send out an email on day 15 reiterating the 15
  bill reduction if paid within the 20 days
• On day 18 call and remind
• Ask if bill can be paid by credit/debit card

20
Automated Solution Example

• XactiMed Revenue Cycle Solutions
• MedAssets Solutions
• Automated System
• DHMC Dartmouth-Hitchcock Medical Center NH
• JPS John Peter Smith Hospital Fort worth, TX

Decreased A/R Times Decreased A/R Times Decreased A/R Times
Medical Facility Original Now Reduction
DHMC Medicare 27 19 30
JPS third party AR 30 22 27
JPS Commercial AR Fell an average of 90.4 days Fell an average of 90.4 days 44
Fox Chase Cancer Center 73.1 40.8 56
Average Average 39
Target for Gritman Target for Gritman 40
21
5 Day Window Reduction

• Current Process for IP/OP Surgery
• Admission Patient Documentation Manual
  Discharge On Site or Off Site Coder if
  Off Site Hold Charge Entry .
  Auditing Final DRG AR Queue
  Billed to Payee
• Steps 10 Time 6 days
• New Process with automated billing and coding
• Admission Patient Documentation Manual
  Discharge Billed to Payee
• Steps 4 Time 3 days
• This minimum time is designated by Federal
  regulation and is out of the scope of this
  project to reduce

22
NPV

• Present Value with 40 reduction
• 980,000
• NPV of -1.89 million
• About 400,000 per year reduction in costs
• Factors to consider
• Doesnt account for savings of reducing employee
  costs
• Reduction of employee time for billing none value
  added for other processes
• Doesnt account for additional financial
  counselor