DENIALS MANAGEMENT: A CASE STUDY

Patricia Kroken, FACMPE, CRA Jennifer Kroken, MBA Imagine Users Meeting 2010 Charlotte, NC

Hospital-based case study

 Radiology Consultants of North Dallas  17 radiologists  Primarily hospital-based  Also read at numerous imaging centers  13.5 billing/collections staff  ImagineRadiology installed 2004  “Denial” = claim denied for payment on first pass  May eventually be paid

Research

 Very little published data to support development of baseline comparison or benchmark  General consensus 15-30% denial rates  Not radiology-specific  Anecdotal: 15% in radiology “not bad”

Denials management

 Goals  Reduce first pass denials by identifying and correcting root causes  Improve follow-up processes for denied claims  Identify compliance risks  Denials management does not just involve sending appeal letters

Six Sigma

 Developed by Motorola  Measured error rates for manufacturing processes  Established framework for breakthrough process improvement  Utilizes a series of defined steps that can be continuously repeated until a process is maximized

Radiology Billing is Process-Driven

Demographics Radiology Reports Matched Coding Charge Entry Claims Submission Payment Secondary ins Patient co-pay Self pay

•Payment plan •Payment •File insurance

Collection Agency Payment Bad debt write-off Small balance write-off Insurance Follow-up

•Correspondence •Denial •No activity

Research Re-file

Methodology: Six Sigma DMAIC

DMAIC for Denials Project

 Define  Denied claims represent an opportunity to improve profitability  Processes surrounding claims submission and follow up appear to be inefficient  Measure  Categories of denied claims

DMAIC for Denials Project

  Analyze    Processes in place for claims preparation, submissions and follow-up Potential risk and/or gains from addressing certain denial categories Root causes of why denials are occurring Improve    Implement technology to eliminate manual processes and standardize Train those involved regarding standardized processes Change workflow and transition to paperless environment

DMAIC for Denials Project

 Control  Verify standardization of denials management processes  Continue to measure to ensure replication of results  Define—circular process starts again

Logic and Organization

  Compliance denials   Practice potentially placed at risk Could be in violation of regulations  Coding (including bundling/unbundling)   Medical necessity Duplicate claims Administrative   Usually due to process error or omission Theoretically preventable  Eligibility      Missing/incorrect information Prior authorization Timely filing Non-covered service Denied—no reason given

Condense Categories

 Use general areas identified under compliance and administrative categories    Denial categories set up in system maintenance Insurance company variations assigned to categories by payment poster posting denials  Note: also found to improve payment posting production when compared to using hundreds of insurance company categories EOBs/denials scanned into system and accessible from workstations  Removes objection of having to see insurance denial reason

Results: Total Denials

RCND Denials as % of Practice

10% 12% 10% 8% 6% 4% 2% 0% 2004 2005 8% 2006 8% 7% 2007 2008 7% 6% 2009

Comments: Total Denials

 Baseline in 2004: 10% denials rate  Aggressive editing software had already improved the percentage to some degree at the time the project started  In some cases improvement in one category might be offset by increases in another  Changes in Medicare LCDs or payor edits  Payor computer problems (BCBS in early 2009)  Consistent improvement annually to 6% 2009

Results: Coding

4,26% 4,50% 4,00% 3,50% 3,00% 2,50% 2,00% 1,50% 1,00% 0,50% 0,00% 2004 2,39% 2005

RCND Coding Denial Trend (as % of practice)

0,61% 2006 0,68% 2007 0,70% 2008 0,41% 2009

Comments: Coding Denials

 Coding denials 2004: 4.26% of all procedures  42.6% of denials  Represented a potential compliance risk  Financial plus risk management priority  From 2006-present: fewer than 1% of all procedures denied for coding issues  2009 denial rate .41% of total or 7% of denied procedures

Coding: Root Cause Corrections

 Physician dictation  Often a cause for inaccurate or under-coding problems  Review of dictation patterns identified issues  Physician leadership supported educational and “enforcement” efforts  Reports compared to objective resource  ACR Communications Guidelines

Coding: Root Cause Corrections

 Physician education  Discussion of coding basics  History/reason for exam  Number of views  Separate paragraphs for complex studies  Example: CT of chest, abdomen and pelvis  Complete/limited ultrasound dictation elements  If it isn’t dictated, it didn’t happen  No assumption coding or “protocol”

Coding: Root Cause Corrections

 Custom workbooks by physician  ACR Communication Guideline  How physician’s reports compared to ACR parameters  Indication/reason for study  Views, contrast, limited/complete study  Impression  Samples of that physician’s problematic reports  Difficult to code  Would have to be down-coded  Difficult to appeal based on available documentation  Samples of “good” reports containing all elements

Coding: Root Cause Corrections

 Temporarily: administrative employee at hospital reviewed reports daily  Returned those without histories, views, etc. for re dictation  Physician leadership reinforced the program!

 Ongoing: feedback and/or updates  Changes in dictation requirements for complete vs. limited ultrasound studies  Problems and/or trends

Results: Medical Necessity Denials

0,60% 0,50% 0,40% 0,30% 0,20% 0,10% 0,00% 0,29% 2004 2005

RCND Medical Necessity Denials (as % of practice)

0,51% 0,46% 0,42% 0,45% 0,23% 2006 2007 2008 2009

Comments: Medical Necessity Denials

 Consistently less than 1% of total procedures  Less improvement year-to-year  Changes in LCDs  PET  Vascular procedures  Vertebroplasty/kyphoplasty  Improvements in coding documentation supported medical necessity  Denied claims did not show deficiency in dictation but still denied

Results: Eligibility

RCND Eligibility Denials (as % of practice)

1,26% 1,40% 1,20% 1,00% 0,80% 0,60% 0,40% 0,20% 0,00% 2004 0,26% 0,46% 2005 0,55% 2006 1,10% 2007 2008 0,36% 2009

Comments: Eligibility

 Administrative denial  Usually human error  Controllable in imaging center setting, but not hospital-based  Solution  Use available technology  Front-end editing  Value-added clearinghouse with automated eligibility checks

Comments: Eligibility

 Industry: 45% of denials due to eligibility  Clearinghouse database: 29% of claims denied for eligibility  RCND 2004: less than 1% denial rate  Eligibility denials rose 2007-2008  Value-added clearinghouse added end of 2008  Eligibility dropped nearly 50% 2008-2009  Checks eligibility for 200+ health plans

Results: Eligibility

2008-2009 Eligibility by Top Payors

800 700 600 500 400 300 200 100 0 Blue Cross Medicare Medicaid United Healthcare 2008 2009

Comments: Eligibility

 2008-2009 dramatic gains in top payors  BCBS experienced internal computer issues in early 2009 so improvement less dramatic  Substantial gains  Medicare  Medicaid  United Healthcare

Results: Timely Filing

RCND Timely Filing Denials (as % of practice)

2,22% 2,50% 2,00% 1,50% 1,00% 0,50% 0,00% 2004 1,66% 2005 1,55% 2006 0,45% 2007 0,32% 2008 0,06% 2009

Comments: Timely Filing

 Timely filing 2004: 2.2% of total claims  Impacted by conversion to new software  Staff member resistance to changing systems = “former employee”  United Healthcare impacted  Timely filing 2009: .06% of total claims  .01% of total denials  Approximately 11 days from DOS to claim release

Discussion and Conclusions

 Root cause corrections reduce denials  Higher number of clean claims = less work on the back end and faster cash flow  Hospital-based practices will have a higher rate of administrative denials  No control over data gathering processes  High-turnover positions  Lack of experience/education  Imaging centers should theoretically be able to eliminate administrative

Prioritizing the Program

 Medical necessity  Frequently high dollar procedures  Both financial and compliance risk  Coding  Physician education/behavior modification efforts pay off quickly  Coder education/certification emphasis  Eligibility  Use available technology!

Final Thoughts

 Technology is critical and available  You can’t manage what you can’t measure  Need high volume processing—can’t be done manually  Billing and collections activities involve a series of defined processes  Determine where problems originate  Reduce variability in processes and improve results  As one process stabilizes and demonstrates control, move to the next

Thanks!

Pat Kroken, Albuquerque, NM 505-856-6128 [email protected]

Jennifer Kroken, Dallas, TX 817-403-3355 [email protected]

Healthcare Resource Providers P.O. Box 90190 Albuquerque, NM 87199