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A Cheaper Hospital In Five Days

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Using easy-to-learn six sigma techniques, you can make your hospital more error-free, safe, and profitable.

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A Cheaper Hospital In Five Days

  1. 1. Get a Cheaper (More Profitable) Hospital in Five Days A Special Report by Jay ArthurIt should come as no surprise that a faster, better hospital will be cheaper to operate and moreprofitable. When you’re not dealing with all of the delays in the ED-Admission-Dischargeprocess, fewer patients will be boarded in the ED, reducing diversion and LWOBS. Morepatients can be seen more quickly, increasing revenue. When you’re not dealing with the extracosts of preventable falls, infections and medication errors, it will make the hospital more costeffective and profitable.Faster + Better = Cheaper and More Profitable!And there are other opportunities. Most hospitals have too many problems with rejected,appealed and denied claims costing millions! Lean Six Sigma can help reduce billing problemsamong other operational problems. And the process is simple.To reduce rejected, appealed and denied claims, use Six Sigma tools to focus the improvementeffort. 1. Analyze Claims using control charts and pareto charts • Rejected • Appealed • Denied© 2010 KnowWare International Inc. 888-468-1537 1 info@qimacros.com
  2. 2. 2. Analyze the Root Causes using the “Dirty 30 process” 3. Implement Countermeasures 4. Track ResultsReducing Denied Claims In Five DaysDenied claims mean no money for services rendered because the billing process failed in someway. Non-payment drives up the cost of healthcare and pushes many hospitals towardbankruptcy. In this case study, monthly denials were over $1 million (XmR chart). Charges Coded as Denials $3,000,000 UCL $2,552,122 $2,500,000 $2,000,000 $1,500,000 Denials (E) UCL CL $1,071,509 +2 Sigma Charges +1 Sigma $1,000,000 Average -1 Sigma -2 Sigma $500,000 LCL $- LCL $(409,103) $(500,000)10/02 11/02 12/02 01/03 02/03 03/03 04/03 05/03 06/03 07/03 08/03 09/03 $(1,000,000) 2002-2003© 2010 KnowWare International Inc. 888-468-1537 2 info@qimacros.com
  3. 3. Using Pareto Charts of DenialsUsing Excel PivotTables and the QI Macros, it was easy to narrow the focus to a few key areasfor improvement: Timely Filing (61%) and one insurer (67% of Timely Filling denials): Denial-No Appeal Charges n=12858108.93 $12,858,109 99% 100% 100% 97% 91% 90% $11,250,845 81% 80% $9,643,582 70% $7,849,569 $8,036,318 61% 60% Amount $6,429,054 50% 40% $4,821,791 30% $3,214,527 $2,516,508 20% $1,607,264 $1,295,032 $750,766 10% $336,270 $109,813 $150 $- 0% Timely Filing Medical No Auth Partial Auth Invalid Auth ET ES Necessity Memo Code Denials for Timely Filing by Insurer n=778 778 99% 99% 100% 100% 100% 100% 96% 98% 94% 93% 90% 90% 680.75 87% 84% 81% 80% 583.5 75% 70% 501 64% Number of Denials 486.25 60% 389 50% 40% 291.75 30% 194.5 20% 97.25 81 45 10% 27 24 24 18 15 14 11 7 4 4 1 1 1 0 0% Ins 1 Ins 2 Ins 3 Ins 4 Ins 5 Ins 6 Ins 7 Ins 8 Ins 9 Ins 10 Ins 11 Ins 12 Ins 13 Ins 14 Ins 15 Ins 16 Payer© 2010 KnowWare International Inc. 888-468-1537 3 info@qimacros.com
  4. 4. Analyze Root Causes and Initiate Countermeasures • In a half-day root cause analysis session, the team identified ways to change the process to work around the denials and change the contract process to 1) reduce delays that contribute to timely filling denials and work with the insurer to resolve excessive denials.Verify Results:After implementing the process changes the following Monday, denied claims fell by $380,000per month ($15 million/year). XmR chart below shows denials before and after improvement.© 2010 KnowWare International Inc. 888-468-1537 4 info@qimacros.com
  5. 5. Reducing Rejected Claims In Five DaysIn software we have a saying that “finding a bug in a computer program is like finding acockroach in your hotel room. You don’t say: Oh, there’s a bug. You say: The place is infested.”The same is true of rejected claims. Start with a line or control chart of rejects:Use a series of Pareto charts to narrow your focus:© 2010 KnowWare International Inc. 888-468-1537 5 info@qimacros.com
  6. 6. Rejected claims are the frequent type of error; appeals tie up accounts receivable, and denialsresult in lost revenue. How can we use Lean Six Sigma? Start with rejected claims.Categorize Rejected Claims Rejects by Type n=152268067.28 $152,268,067 99% 99% 100% 100% 96% 97% 93% 95% 90% 90% $133,234,559 86% 80% 80% $114,201,050 70% 67% $95,167,542 60% Amount 53% $76,134,034 50% 40% 40% $57,100,525 $40,418,050 30% $38,067,017 27% 20% $20,435,973 $20,410,036 $20,135,403 $19,993,417 $19,033,508 $9,999,612 10% $5,440,543 $4,163,173 $3,098,585 $2,266,610 $1,941,177 $1,789,756 $917,622 $893,878 $364,234 $- 0% ge Co m 6 7 8 9 10 11 12 13 14 15 qd o qd D D D D nf ai ra D D D D D D Re Re sI Cl ve In o fo up nf In ct D t I o rre er N dd co id A ov In Pr TypeDuplicate claims accounts for 27% of rejected claims. The next four bars of the pareto chartcombined with duplicate claims accounts for 80% of all rejected claims. Each of these five barsof the pareto chart is an improvement story requiring root cause analysis. Let’s take duplicateclaims down to the next level of pareto chart.© 2010 KnowWare International Inc. 888-468-1537 6 info@qimacros.com
  7. 7. Duplicate Claims Verification n=72 72 99% 100% 96% 97% 93% 94% 90% 92% 90% 63 60 83% 80% 54 70% 45 60% Claims 36 50% 40% 27 30% 18 20% 9 5 10% 1 1 1 1 1 1 1 0 0% Medicare PTBAL billed for pt billed Denied IC second bill UK Unknown Forward to portion after secondary being sent Secondary insurance again after for pt portion Carrier pmt primary paymentIn this example, secondary payments for Medicare patients accounts for 83% of the duplicateclaims. The team investigated 72 of these secondary payments and found that they had beenpaid, but incorrectly coded in accounting. Simple process changes reduced duplicate claims by$24 million.Teams Continued With the Other Four “Big Bars”No Coverage turned out to be caused by charges after policy termination (44%).© 2010 KnowWare International Inc. 888-468-1537 7 info@qimacros.com
  8. 8. No Coverage by Code n=460 460 98% 99% 100% 100% 100% 97% 98% 95% 96% 92% 89% 90% 402.5 85% 80% DZ Codes 80% 345 74% CAT Charges after Policy Termination CIP Cannot Identify Patient 70% 67% COV Coverage 287.5 COV Treatment not Covered 60% DEP Dependent Claims IAP Invalid Alpha Prefix 230 50% 202 IP# Invalid Policy Number 44% LIM Limits Exceeded NCD No Coverage for DOS 40% 172.5 NF No Fault NSC No Service Coverage 30% 115 106 O Other PE Presumptive Eligibility 20% 57.5 34 26 22 21 10% 14 10 5 5 5 3 3 2 1 1 0 0% SC T V CD O P P F # T M S EP U PE D IP IA N CI RE CB CA CO ST EN LI D N N EP DInvalid Insurer info led to SSN incorrect and wrong primary insurer (51%). Invalid Insurer Info n=257 257 100% 89% 90% 224.875 86% 83% 80% 80% 192.75 76% 68% 70% 160.625 60% SSI - Social Security Incorrect 60% OIN - Other Insurer Primary Claims 128.5 51% VOU - Voucher 50% CAT Charges after Policy Termination CIP Cannot identify Patient 40% 96.375 NAME - Correct Pts Name 77 ADR - Incorrect Ins Address 30% NCD - Treatment not Covered 30% 64.25 54 PTB - No MCR Part B 20% 28 32.125 23 22 20 10% 9 8 8 8 0 0% SSI OIN VOU CAT CIP NAME ADR NCD PTB OTHER CodePatient Info rejects led to analysis of Other Insurance (41%) and students missing from parent’sinsurance (39%).© 2010 KnowWare International Inc. 888-468-1537 8 info@qimacros.com
  9. 9. Patient Info Required Rejects n=153 153 100% 98% 96% 92% 90% 133.875 86% 80% 80% 114.75 70% 95.625 60% Claims 76.5 50% 63 41% 59 40% 57.375 30% 38.25 20% 19.125 10 9 10% 6 3 3 0 0% Other Insurance Students Other Other Babies Auto Demographic DependentsResultsHalf-day root cause analysis sessions for each of the “big bars” on these pareto charts andsubsequent improvements resulted in dramatic improvement in “first pass yield” of insuranceclaims. • 72% reduction in ED billing errors • 60% reduction in impacted charges© 2010 KnowWare International Inc. 888-468-1537 9 info@qimacros.com
  10. 10. Reducing Appealed Claims in Five DaysDelayed payments caused by appealed claims can put a hospital in a financial crunch. In 2003,appealed claims spiked due to Medicare Part B changes. The recent healthcare reform legislationand subsequent changes will most likely cause further spikes. Reject Appeals Chart $17,681,040 $15,681,040 UCL $15,045,583 $13,681,040 $11,681,040 Reject Appeals Reject Appeals UCL +2 Sigma +1 Sigma $9,681,040 Average CL $8,363,312 -1 Sigma -2 Sigma $7,681,040 LCL $5,681,040 $3,681,040 LCL $1,681,040 $1,681,040 10/02 11/02 12/02 01/03 02/03 03/03 04/03 05/03 06/03 07/03 08/03 09/03 Date/Time/Period© 2010 KnowWare International Inc. 888-468-1537 10 info@qimacros.com
  11. 11. Use Pareto Charts to Analyze Appealed Claims:There is a number of ways to analyze appeals data: by patient and appeal type: Reject Appeals n=100359738.510001 $100,359,739 99% 100% 100% 100% 100% 100% 96% 98% 95% 90% $87,814,771 $81,343,021 81% 80% $75,269,804 70% $62,724,837 60% Charges $50,179,869 50% 40% $37,634,902 30% $25,089,935 20% $13,997,941 $12,544,967 10% $1,361,097$1,346,122$1,077,005 $906,352 $243,241 $33,063 $32,456 $19,441 $- 0% ED- 1 2 3 4 5 6 7 8 9 InPatient FC Reject Appeals n=100359738.51 $100,359,739 100% 100% 92% 90% $87,814,771 80% 80% $75,269,804 70% $64,562,998 $62,724,837 64% 60% Amount $50,179,869 50% 40% $37,634,902 30% $25,089,935 $15,341,703 20% $12,302,541 $12,544,967 $8,149,240 10% $3,256 $- 0% Auth Precert Medical Necessity No Cert/Recert for days Timely Filing FC Notification Type© 2010 KnowWare International Inc. 888-468-1537 11 info@qimacros.com
  12. 12. Auth/Precert Appeals by Patient Type n=5498 5498 100% 100% 98% 93% 90% 4810.75 88% 80% 80% 4123.5 70% Number of FB Memos 3436.25 60% 2839 2749 52% 50% 40% 2061.75 1543 30% 1374.5 20% 687.25 429 309 266 10% 105 7 0 0% In Out S V R E F Patient TypeFrom these pareto charts, authorization and pre-certification of admissions from the ED are themost common and costly appeals. Root cause analysis required team members from the ED andadmissions to identify and reduce Auth/Precert appeals.Reducing Appealed Claims Cycle Time Appeals Delays 40000 35000 Number of Appeals 30000 25000 20000 15000 10000 5000 0 0- 180 - 360 - 540 - 720 - 900 - 1,080 1,260 1,440 1,620 1,800 1,980 2,160 2,340 2,520 180 360 540 720 900 1,080 - - - - - - - - - 1,260 1,440 1,620 1,800 1,980 2,160 2,340 2,520 2,700 Days© 2010 KnowWare International Inc. 888-468-1537 12 info@qimacros.com
  13. 13. Using the simple tools of Lean (Post-it Notes), it was possible to redesign the appeals process to: • Reduce touches per account from 21 down to 11 • Minutes per touch (16 minutes) • 2.97 hours saved per account • Accelerate payment by 50 daysOther ExamplesIn 2002, rural hospital, Thibodaux Regional Medical Center, used Lean Six Sigma to reduced“discharged not final billed” from $3.3 million to $600,000. They also reduced net accountsreceivable from 73 days to 62 days resulting in an increased cash flow of $2 million per year. Asecond wave of projects saved an addition $489,000 per year in inventory costs.In 2006, North Shore Long Island Jewish Health System used Six Sigma to reduce oncologybilling errors (missing charges) from 50 percent to only 2.5 percent. This resulted in increasedrevenue of $4 million per year. They also reduced turnaround time for charge entry from 3.7 to2.4 days and DOS-to-billing from 13.6 days to 6.8 days. The biggest factor in timely filing ofbills: missing information. Biggest culprit, pharmacy:© 2010 KnowWare International Inc. 888-468-1537 13 info@qimacros.com
  14. 14. How to Get a Cheaper Hospital in Five DaysFrom working with teams in various industries, I’ve developed a simple method for achievingbreakthrough improvement on transactional processes like billing. I call it the Dirty ThirtyProcess. I used it in the case study presented in this white paper.The Dirty 30 Process for Better BillingThe secret is to:1. Quantify the cost of correcting these rejected, appealed and denied transactions2. Understand the pareto pattern of rejected, appealed and denied transactions3. Analyze 30-50 rejected, appealed or denied transactions to determine the root cause4. Revise the process and system system to prevent the rejected, appealed or denied claim.Process: Typical root cause analysis simply does not work because of the level of detail requiredto understand each error. Detailed analysis of 30 errors in each of the top error “buckets” (i.e.,The Dirty Thirty) led to a breakthrough in understanding of how errors occurred and how toprevent them. Simple checksheets allowed the root cause to pop out from analysis of this smallsample. As expected, the errors clustered in a few main categories. The Dirty Thirty process hasfour steps:1. Focus: Determine which rejected, appealed or denied error buckets to analyze first formaximum benefit. (This analysis takes 2 to 3 days.)2. Improve: Use the Dirty Thirty approach to analyze root causes (4 hours per error type—facilitator with team) and determine process and system changes necessary to prevent theproblem.3. Sustain: Track the rejected, appealed and denied claims after implementation of the changes.4. Honor: Recognize and reward team members© 2010 KnowWare International Inc. 888-468-1537 14 info@qimacros.com
  15. 15. InsightsUsing the basic tools of Six Sigma, anyone can learn to use what I call The Dirty Thirty Processin a day or less to find the root causes of transaction errors. Once a team has found the rootcauses of these errors, it’s just a matter of changing the processes and systems to eliminate theseerrors.Hundreds of people spend their lives fixing the fallout from these rejected, appealed and deniedclaims. And they all think they’re doing meaningful work, not just fixing things that shouldn’t bewrong to begin with.ConclusionUntil you get to where you can prevent errors, every system could benefit from a simple, yetrigorous approach to analyzing and eliminating errors. The Dirty Thirty process is ideal becausethe data required to implement it is collected by most systems automatically. Then all it takes is 4to 8 hours of analysis to identify the root cause of each error.Need Guidance?The first project may seem scary, but we can facilitate your improvement teams to achievebreakthroughs in patient flow. Once you’ve learned how, you’ll find it easy to continue. Haven’tyou waited long enough to get a faster hospital in five days or less?Jay Arthur, the KnowWare Man, works with hospitals that want to get faster, better and cheaperin a matter of days using the proven methods of Lean Six Sigma. Jay is the author of Lean SixSigma Demystified and the QI Macros SPC Software for Excel. Jay has worked with healthcarecompanies to reduce denied claims by $3 million per year, appealed claim turnaround time andlab turnaround times by 30-70 percent.To get a faster hospital in five days, call: Jay Arthur at 888-468-1537Email: jay@qimacros.comWeb: www.qimacros.comMail: KnowWare, 2253 S. Oneida St. Ste 3D, Denver, CO 80224© 2010 KnowWare International Inc. 888-468-1537 15 info@qimacros.com

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