Connecting the Dots How Many Denials Walking Do You Have?

Transcription

1 Connecting the Dots How Many Denials Walking Do You Have? Lincoln Fish, Co-Founder and Senior Vice President, Avadyne Health Revenue Cycle. Perfected.

2 Could this happen at your facility? A $6 million revenue loss due to missed appeal deadlines A $2 million loss due to writing off denied Medicare line items with missing modifiers $25K+ per week in lost revenue due to repeated failure to obtain pre-authorization

3 Revenue Cycle Today Same fundamentals Bigger consequences

4 What are we going to cover today? Where is the Revenue Cycle broken? What is a Stable Revenue Cycle? What is a First Pass Denial? What is a Denial Walking? Creating your Scorecard Data for Communication

5 Takeaways Scorecards Denials Productivity Communication Strategies

6 Where is the Revenue Cycle Broken? And Follow-up 18% = US Cost of Healthcare Admin 5% to 8% = Cost of Healthcare Admin, Other Countries

7 Where is the Revenue Cycle Broken? And Follow-up Bad demographic data Bad patient insurance Lack of insurance pre-authorization

8 Where is the Revenue Cycle Broken? And Follow-up Lack of concurrent insurance authorization Failure to obtain additional authorizations

9 Where is the Revenue Cycle Broken? And Follow-up Use of wrong code Delay in billing Attachment of wrong visits to bills

10 And where are $$ ultimately lost? And Follow-up Untimely appeal of claim Pre-mature write-off/lack of attempt to appeal

11 And where are $$ ultimately lost? And Follow-up Could have been denied and it is too late to appeal Open balance too small and too old for cost/benefit write-off

12 What is the Revenue Cycle? Revenue Cycle is the sum of all activities a hospital performs which can affect reimbursement A denial can originate almost anywhere on this line!

13 What is a Stable Revenue Cycle? A Stable Revenue Cycle is one where Every patient is handled as a potential Denial Walking Each employee is accountable to the revenue cycle A Communication Framework has been established Success is measured by consistent outcomes

14 What exactly is a Denial? Revenue Cycle. Perfected.

15 What exactly is a denial? A denial is any non-contractual rejection of payment!

16 What exactly is a denial? Yes, it s a zero-pay But it s also Any claim with any line item denied Any claim with partial pays on any line item Basically, any claim with a charge that was not paid as expected

17 What exactly is a denial? If you start treating claims not fully paid as denials, you will generate more revenue

18 So how should we measure Denials? The Old Way: Denial Write-offs The New Way: FPD Rate

19 What is a First Pass Denial? Revenue Cycle. Perfected.

20 What is a First-Pass Denial? Any Denial which requires specialized work to resolve (not just a rebill) Occurs within 90 days of bill FPD Rate KPI is by number of accounts, not dollars FPD Volume is by dollars Not just Zero Pays

21 First Pass Denial Rate First Pass Denial Rate is a KPI It is the KPI for measuring Denial Avoidance Denial write-offs is no way to measure Denial Avoidance or full denial impact on Revenue Cycle Goal: Identify volume of accounts that went through the expensive, slow-paying denial process

22 First Pass Denial Rate Definition Patient Account #1 First Bill: June Bill Paid: June Calculate FPD: Sep

23 First Pass Denial Rate Definition Patient Account #1 First Bill: June Bill Paid: June Calculate FPD: Sep Patient Account #2 First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep

24 First Pass Denial Rate Definition Patient Account #1 First Bill: June Bill Paid: June Calculate FPD: Sep Patient Account #2 First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep Patient Account #3 First Bill: June Bill Denied: June Bill Paid: August Calculate FPD: Sep

25 First Pass Denial Rate Definition Patient Account #1 Formula: Patient Account #2 First Bill: June Bill Paid: June Calculate FPD: Sep [Total Number of Accounts Initially Denied] 2 [Total Number of Accounts First Billed 90 Days Ago] First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep Patient Account #3 First Bill: June Bill Denied: June Bill Paid: August Calculate FPD: Sep

26 First Pass Denial Rate Definition Patient Account #1 Patient Account #2 First Bill: June Bill Paid: June Calculate FPD: Sep Formula: [Total Number of Accounts Initially Denied] 2 3 [Total Number of Accounts First Billed 90 Days Ago] First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep Patient Account #3 First Bill: June Bill Denied: June Bill Paid: August Calculate FPD: Sep Days

27 First Pass Denial Rate Definition Patient Account #1 Patient Account #2 First Bill: June Bill Paid: June Calculate FPD: Sep Formula: [Total Number of Accounts Initially Denied] 2 3 [Total Number of Accounts First Billed 90 Days Ago] First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep Patient Account #3 FPD Rate = 66% First Bill: June Bill Denied: June Bill Paid: August Calculate FPD: Sep Days

28 First Pass Denial Rate Definition Patient Account #1 Patient Account #2 First Bill: June Bill Paid: June Calculate FPD: Sep Formula: [Total Number of Accounts Initially Denied] 2 3 [Total Number of Accounts First Billed 90 Days Ago] Patient Account #3 First Bill: June Bill Denied: June Rebill Denied: August Calculate FPD: Sep Key Features: Value does not change with subsequent denials First Bill: June Bill Denied: June Bill Paid: August Days Calculate FPD: Sep Resolution does not alter the fact that the account incurred an FPD

29 FPD Rate is your REAL Denial Rate Example: Hospital A $250MM Net Revenue $2MM in Denial Write-offs Denial W/O Rate Hospital A.8% Hospital B Hospital C FPD Rate

30 FPD Rate is your REAL Denial Rate Example: Hospital B $500MM Net Revenue $5.6MM in Denial Write-offs Denial W/O Rate Hospital A.8% Hospital B 1.1% Hospital C FPD Rate

31 FPD Rate is your REAL Denial Rate Example: Hospital C $120MM Net Revenue $450K in Denial Write-offs Denial W/O Rate Hospital A.8% Hospital B 1.1% Hospital C.4% FPD Rate

32 FPD Rate is your REAL Denial Rate Example: Hospital A $250MM Net Revenue $2MM in Denial Write-offs 220K Accounts Billed Denial W/O Rate FPD Rate Hospital A.8% 15.4% Hospital B 1.1% Hospital C.4% 34K Accounts With a First Pass Denial Under-posted denial write-offs

33 FPD Rate is your REAL Denial Rate Example: Hospital B $500MM Net Revenue $5.6MM in Denial Write-offs 434K Accounts Billed Denial W/O Rate FPD Rate Hospital A.8% 15.4% Hospital B 1.1% 12.4% Hospital C.4% 54K Accounts With a First Pass Denial Correctly posted denial write-offs, yielding higher Denial Write-Off Rate

34 FPD Rate is your REAL Denial Rate Example: Hospital C $120MM Net Revenue $450K in Denial Write-offs 109K Accounts Billed Denial W/O Rate FPD Rate Hospital A.8% 15.4% Hospital B 1.1% 12.4% Hospital C.4% 40.3% 44K Accounts With a First Pass Denial Severely under-posted denial write-offs

35 FPD Rate is your REAL Denial Rate Industry denial measures are misleading: Write-off rate fails to include all denied accounts Zero-pays fails to include all denied accounts Denial W/O Rate FPD Rate Hospital A.8% 15.4% Hospital B 1.1% 12.4% Hospital C.4% 40.3% Poor EOB posting fails to include all denied accounts Arguable & Vague Unarguable & Laser-Precise

36 FPD Rate: Black & Denial Accounting Counts every account that went through the process Immune to timing issues and variable adjustment posting practices Success for any denial avoidance initiative can be determined in 90 days Measure your FPD Rate every month

37 What s a Denial Walking? Revenue Cycle. Perfected.

38 So what s a Denial Walking? A Denial Walking is any patient currently in your facility whose claim is certain to get denied

39 So what s a Denial Walking? Examples of Denials Walking Failure to obtain preauthorization Uncorrected demographic information Unverified insurance information

40 So what s a Denial Walking? If you treat every patient as a potential Denial Walking, you will generate more revenue

41 Creating your Scorecard Data for communication Revenue Cycle. Perfected.

42 Creating your Scorecard When you receive an 835 or EOB, what are you doing with it? OR Posting it to your system immediately Entering it into a workflow or spreadsheet program Sending it to a specific person/department for processing Putting it in a pile

43 Creating your Scorecard The first step in sorting is posting it somewhere! Cash posters can use a simple spreadsheet Other options include core systems, external workflow tools, etc. The key is to make sure it s being watched and worked

44 Sample: initial denial posting Account Number Denied Amount Reason Code $ $ $ 8, $ $ $ $ 1,

45 Creating your Scorecard The second step in sorting is classification Classify by CAS code Can be done by posters or someone assigned to that duty Critical for directing for correction

46 Sample: denial posting classified Account Number Denied Amount Reason Code Denial Type $ Technical $ Technical $ 8, Technical $ Clinical/Technical $ Technical $ Technical $ 1, Clinical/Technical

47 Creating your Scorecard The third step is recording what we ve discovered We ve done our research What have we learned? How do we capture the information Responsible area & party Root cause

48 Creating your Scorecard Responsible Area What area of our organization was responsible for generating this denial? Is there an individual or department connected with it? If we capture this information here, we can begin to standardize our account notes as well

49 Responsible Area & Party Account Number Denied Amount Reason Code Denial Type Responsible Area Resp. Party $ Technical PreRegistration Bob $ Technical PreRegistration John $ 8, Technical PreRegistration Sue $ Clinical/Technical PreRegistration Sue $ Technical Care Management Frank $ Technical PreRegistration Bob $ 1, Clinical/Technical Coding Sally

50 Creating your Scorecard Root Cause Is the reason given on the 835/EOB correct? If yes, can we get more specific? If no, let s choose from our list of available root cause codes

51 Root Cause Account Number Denied Amount Reason Code Denial Type Responsible Area Resp. Party Root Cause $ Technical PreRegistration Bob Technical: Incorrect Insurance Recorded $ Technical PreRegistration John Analysis: OP Cath Underpaid $ 8, Technical PreRegistration Sue Analysis: MRI Not Authorized $ Clinical/Technical PreRegistration Sue Analysis: Paid on Prior Contract Rates $ Technical Care Management Frank Analysis: MRI Not Authorized $ Technical PreRegistration Bob Analysis: Paid on Prior Contract Rates $ 1, Clinical/Technical Coding Sally Clinical: Day Not Medically Necessary

52 Creating your Scorecard The fourth step is getting it fixed Presumably, someone in the organization can fix it Can we send a request to a specific individual? Are we watching for the response to that request? Have we established thresholds for response times

53 Creating your Scorecard Are we tracking everything that has come in? We can use our spreadsheet to organize requests and appeals It s critical to establish a process for reviewing all outstanding items and following up

54 Sample denial posting with info. request Account Number Denied Amount Reason Code Denial Type Requested info/correction from $ Technical Billing $ Technical Billing $ 8, Technical Financial $ Clinical/Technical Medical Records $ Technical Patient Access $ Technical Financial $ 1, Clinical/Technical Medical Records

55 Info Request Tracking Account Number Denied Amount Reason Code Denial Type Responsible Area Resp. Party Root Cause Requested info Requested Info Dat $ Technical PreRegistration Bob Technical: Incorrect Insurance Recorded Billing 3/10/ $ Technical PreRegistration John Analysis: OP Cath Underpaid Billing 3/15/ $ 8, Technical PreRegistration Sue Analysis: MRI Not Authorized Financial 3/22/ $ Clinical/Technical PreRegistration Sue Analysis: Paid on Prior Contract Rates Medical Records 4/1/ $ Technical Care Management Frank Analysis: MRI Not Authorized Patient Access 5/20/ $ Technical PreRegistration Bob Analysis: Paid on Prior Contract Rates Financial 6/13/ $ 1, Clinical/Technical Coding Sally Clinical: Day Not Medically Necessary Medical Records 2/14/08

56 Data for Communication Linc remember to show: Denials Scorecard Responsible Area Bar Graph Responsible Area Detail

57 Data for Communication People point fingers, data informs Let your data be the bad guy So every patient is a potential Denial Walking But data-driven communication can reduce impact

58 The average hospital office worker in the US costs $185 per day

59 A few numbers $185 Average Cost for a business office worker $100 Common balance cut-off for write-off 20 Minimum denials for a given worker 35% Percentage of those denials recovered $700 Dollars collected 378% Daily ROI $133,900 Yearly net revenue gain

60 To your team, it can become just Monopoly Money

61 Distributing Work Revenue Cycle. Perfected.

62 People need the right work Think about how work is getting to your team Are you evaluating which work they re getting? The distribution may be costing you money

63 What is a Workpool? It is a group of work with like characteristics which can be worked by the same team Any criteria can be used to define a workpool The work is sorted by priority There is generally limited segmenting of work within the pool

64 Queuing Theory: Consider Costco At Costco, you have to pick a line And hope that it was the right choice In a bank, or now at many retailers, you get in a single line And when a teller/cashier becomes available, you go there

65 Queuing Theory: Consider Costco Retailers estimate that applying queuing theory can speed up the customer s experience by as much as 38% The only reason it isn t more common is that it requires additional line management BUT YOU CAN APPLY IT EASILY!

66 Why Worklists are Inherently Inefficient Worklists are based on old paper models where there were few choices By pre-assigning work to a list, it is not possible to sort completely by priority If a particular worklist is not completed, the work needs to be redistributed to others who already have lists and who do you give it to?

67 The Practical Advantage to Workpooling Assumptions for this example These are follow-up accounts There are 21 accounts Total value of all accounts is: $1.470MM $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

68 The Practical Advantage to Workpooling Let s Alpha Split the Work $100,000 $100,000 $100,000 The 21 accounts are alpha-split in three lists Each worker gets seven accounts The value of the three lists is the same $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $90000 $80,000 $70,000 $60,000 $50,000 $40,000

69 The Practical Advantage to Workpooling Let s Alpha Split the Work Susan, Lisa, and John each have similar work Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

70 The Practical Advantage to Workpooling Let s Alpha Split the Work Each worker gets to exactly one account per hour All accounts are completed Total of accounts worked: $1.470MM Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

71 The Practical Advantage to Workpooling Let s Alpha Split the Work But that s not how it works in the real world Susan and John struggled on their accounts Collectively, we got to 13 accounts, total value: $990K Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

72 The Practical Advantage to Workpooling What s up Next? Susan s next account is $90,000 John s is $50,000 Lisa s is below $40,000 Why is our slowest person working the next most valuable account? Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

73 The Practical Advantage to Workpooling What s up Next? Susan s next account is $90,000 John s is $50,000 Lisa s is below $40,000 While a much faster person will work a much smaller account? Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

74 The Practical Advantage to Workpooling Now let s assume the same people get through the same number of accounts But this time, all the accounts are in a Workpool So each worker takes the next account off the top $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

75 The Practical Advantage to Workpooling So now let s assume the same people get through the same number of accounts But this time, all the accounts are in a Workpool So each worker takes the next account off the top $100,000 Susan $100,000 Lisa $100,000 John $90,000 Lisa $90,000 John $90,000 Lisa $80,000 Lisa $80,000 John $80,000 Lisa $70,000 John $70,000 Lisa $70,000 Lisa $60,000 John $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

76 The Practical Advantage to Workpooling Same people Same number of total accounts worked in the same time Total value of accounts worked: $1.080MM $100,000 Susan $100,000 Lisa $100,000 John $90,000 Lisa $90,000 John $90,000 Lisa $80,000 Lisa $80,000 John $80,000 Lisa $70,000 John $70,000 Lisa $70,000 Lisa $60,000 John $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

77 The Practical Advantage to Workpooling Same people Same number of total accounts worked in the same time Total value of accounts worked: $1.080MM And the next account up will be worked by whomever is ready next! $100,000 Susan $100,000 Lisa $100,000 John $90,000 Lisa $90,000 John $90,000 Lisa $80,000 Lisa $80,000 John $80,000 Lisa $70,000 John $70,000 Lisa $70,000 Lisa $60,000 John $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

78 There is a clear winner! $100,000 Susan $100,000 Lisa $100,000 John $90,000 Lisa $90,000 John $90,000 Lisa $80,000 Lisa $80,000 John $80,000 Lisa $70,000 John $70,000 Lisa $70,000 Lisa $60,000 John $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000 Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

79 There is a clear winner! $100,000 Susan $100,000 Lisa $100,000 John $90,000 Lisa $90,000 John $90,000 Lisa $80,000 Lisa $80,000 John $80,000 Lisa $70,000 John Resolved $70,000 Lisa $70,000 Lisa $60,000 John $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000 $1,080,000 Susan Lisa John A-K L-R S-Z $100,000 $100,000 $100,000 $990,00 $90,000 $90,000 $90,000 $80,000 $80,000 $80,000 Resolved $70,000 $70,000 $70,000 $60,000 $60,000 $60,000 $50,000 $50,000 $50,000 $40,000 $40,000 $40,000

80 The Workpool Advantage $1,080,000 > $990,000 Same workers Same amount of time 9% productivity boost

81 The Workpool Advantage $1,080,000 > $990,000 Same workers Same amount of time 9% productivity boost And real numbers are much higher!

82 So what will 9% do for you? Per Year Worklist Workpool Accounts Resolved 100, ,000 Dollars Collected $100,000,000 $109,000,000

83 So what will 9% do for you? Per Year Worklist Workpool Accounts Resolved 100, ,000 Dollars Collected $100,000,000 $109,000,000 This model assumes you can t get to everything But if you can, workpooling will increase cash flow!

84 Implementing Workpooling Simply log who takes which account Accounts must be worked in order Technology can make this happen If you have no other method, keep a common spreadsheet and each worker can log each account checked out

85 So what have we learned? Determining what s a denial is not as simple as we think First Pass Denial Rate is more useful than just write-offs Your facility may have numerous Denials Walking You are already doing the work needed to track all this, now just record it, and monitor it You can use data as the bad guy if necessary Linc didn t date much in college