1. Clinical Indicators of Diagnoses The road to establishing a Clinical Indicator Team

2. Clinical indicators of diagnoses What are they? Facility approved clinical indicators that will establish the definition of diagnoses that are  Highly targeted for review by insurance companies  Frequently inconsistent, incomplete, conflicting, missing or weak in their documentation  Conditions that are often queried by CDI for further specificity or clinical relevance.

3. Clinical indicators of diagnoses What are they? Facility approved clinical indicators that will establish the definition of diagnoses that are  Highly targeted for review by insurance companies  Frequently inconsistent, incomplete, conflicting, missing or weak in their documentation  Conditions that are often queried by CDI for further specificity or clinical relevance.

4. Clinical indicators of diagnoses Who benefits?  CDI, coding, DRG appeals and denials management, PI and other users of the clinical documentation What are the benefits?  Everyone will be on the same page.  Consistency though out the medical record  Reduce the number of CDI queries and coding retro queries  Reduce the potential of DRG denials  Provide additional backup to fight a DRG denial  Better quality outcomes

5. Clinical indicators of diagnoses The “To do list”  Establish the purpose and goals of the clinical indicators team  Gather data to determine what diagnoses to start with - data from DRG denials, RAC denials, and PI - top CDI queries, mortality indicators - enlist coding for CM and PCS coding roadblocks they are having  Prioritize the top diagnoses to be targeted  Get a head start on the evidence based clinical indicators of the top diagnoses  Start a list of others to invite to be on the team - coding, PI, data abstractors, DRG and RAC denials team

6. Clinical indicators of diagnoses The “To do list”  Start a list of physicians that you would like to invite to participate on the clinical indicator team - find out who are the leads in their specialty service  Have physician education plan outline - Physician-to-Physician  Need good organizational skills to keep track of meeting dates, contacting committee members about the meeting and of their responsibilities

7. Clinical indicators of diagnoses What needs to be accomplished by the clinical indicator team for each diagnosis?  Definition  Evidence based clinical indicators  Documentation needed to support clinical validity  Education plan for physicians

8. Clinical indicators of diagnoses Example: Acute Respiratory Failure Patients admitted to Brookhaven Memorial Hospital Medical Center should meet the following clinical indicators, as established by the Clinical Indicator Team, when documenting the diagnosis of Acute Respiratory Failure. Clinical indicators Please document the above clinical indicators in the medical record. If above indicators are not present, the findings to support the diagnosis must be documented in the medical record.

9. Clinical indicators of diagnoses Summary  The Clinical Indicator Team should be focused on the quality of the documentation.  The need to support and validate the diagnoses documented within the medical record is the priority, not reimbursement.  Quality outcomes, hospital profiles, value-based purchasing, and mortality rates will all improve when the documentation is improved by clear, consistent, and complete documentation.

10. Thank you

11. References Wilk, D. (2016, May). Facilitywide Clinical Indictors for Quality, Compliance and Reimbursement. Presented at ACDIS Conference, Atlanta, Georgia

12. 2016 ACDIS Recap Drowning in a sea of data? Strategically navigating data in CDI Cynthia Hiddink RN, BSN, CCDS 7/22/2016

13. OBJECTIVES Learn how to use data to identify opportunities and areas of focus. Better Understand utilization of analytical tools to turn data into actionable insights.

14. Where does your data come from? EMAR Written progress notes Quality department Provider actions CDI activities Coding The boss

15. Traditional use of data in CDI Query rate (overall and by CDI specialist/physician) Physician response rate (overall and by CDI specialist/physician) Physician agreement rate (overall and by CDI specialist/physician) CC/MCC capture rates MS-DRG shifts Case-mix index changes

16. Ask the question first Why is our LOS so long in this particular DRG? Pull DRG with LOS over 5 days during a set time frame. Analyze Note trends, day of week of admission, date and time of discharge order, MD lack of specificity… All data is actionable if you can drill down to the issue at hand.

17. Next level opportunities RW of DRG doesn’t correlate with LOS HGB drop/EF/VS LOS variances Single CC/MCC Evaluation of admission source Resource allocation Time in EMAR/allocation Timing of admissions Prioritization of CDI work list and flow Denials prevention Quality – PSI, mortality (actual vs expected) Predictive analytics

18. Denials prevention data driven opportunities Acute respiratory failure with short LOS or without ABG PNA with no CXR Sepsis with short LOS Malnutrition with short LOS Extensive OR unrelated to procedure AKI without CC or with short LOS CVA with infarction with MCC and short LOS

19. Would you rather? See this : Or this

20. Visualization of data makes it easier to convey Body Copy here:

21. Using data with Physicians SOI/ROM LOS average geometric mean expected Readmission rates Observed over expected mortality ratio

22. Peer to peer comparison Competition is the best motivator

23. Quotes from the experts “Physicians will be engaged if they understand how documentation and coding impacts their personal profile,” Judy Schade, RN, MSN, CCM, CCDS, CDI Specialist at Mayo Clinic Hospital in Phoenix. “Physicians are by nature competitive, and so they aim to be high achievers. CDI programs can use this to their advantage.” Judy Schade, RN, MSN, CCM, CCDS, CDI Specialist at Mayo Clinic Hospital in Phoenix. “Be transparent so physicians can see the benefits—both financial and quality-related—of precise documentation,” Karen Newhouser, RN, BSN, CCDS, CCS, CCM, CDIP, Director of Education at Med-Partners in Tampa. “Then, drill down into the data to identify individual metrics, comparing physicians against one another within the facility and within a particular specialty or service line,” Michelle McCormack, RN, BSN, CCDS, CRCR, Director of CDI at Stanford (California) Health Care.

24. Celebrate small victories Make your goal in small achievable steps Keep moving the mark forward

25. Conclusion Data becomes information that turns into action focused education. Success is monitored to prove better documentation and quality.

26. 2016 ACDIS conference Boosting buy-in: Using data to drive physician engagement June 30, 2016– CDI Journal - Volume 10, Issue 3

27. HCCs: Hierarchical Condition Categories BERNADETTE SLOVENSKY RN MSN CCDS STONY BROOK MEDICINE JULY 22, 2016

28. Risk Adjustment  Risk adjustment is a corrective tool used by actuaries to level the playing field regarding the reporting of patient outcomes, adjusting for the differences in risk among specific patients  It allows for the adjustment of expected volumes to account for the case mix of the facility or the category being compared

29. Hierarchical Condition Categories (HCC)  Risk Adjusted Predictors of healthcare costs  A Hierarchical Condition Category is a grouping of similar condition categories (CCs) based on disease. Only the most severe manifestation of the disease is coded.  Condition Category (CC) is a grouping of similar diagnosis codes into diseases that are related clinically and with respect to cost.  Initially used to set rates for Medicare Advantage (MA) Plans  Now used to:  Set rates for small group markets for ACA exchange plans  Risk adjustment for many VBP measures 29

30. CMS Hierarchical Condition Categories (HCCs)  Each HCC has a score intended to predict the resources required to treat a patient for one year via a risk coefficient score, which when multiplied by a payment factor results in a payment amount to the MA organization.  The payment factor is unique to each MA organization, based in part on its bid.  The HCC payment is based on the organization’s bid amount and the MA’s beneficiary's actual risk score.

31. CMS Hierarchical Condition Categories (HCCs)  Diagnosis codes within each HCC are related both clinically and in cost to the fee-for-service Medicare program.  A patient may have multiple HCCs.  In the CMS-HCC model some conditions have more than one HCC, which differ by severity of the condition (diabetes and cancer)

32. CMS Hierarchical Condition Categories (HCCs)  There are two HCC models  CMS-HCCs for patients enrolled in Medicare Advantage plans  HHS-HCCs were created for the Affordable Care Act (ACA) exchanges. It builds upon the CMS-HCC model but is more complex. It is also referred to as the commercial model.  This presentation will focus on the CMS-HCC model.

33. CMS Hierarchical Condition Categories (HCCs)  In the model, ICD codes map to clinically related hierarchical condition groups that are broadly organized into body systems.  ICD-10 diagnosis codes are assigned to one of 189 HCCs.  Codes collected from the current year are used to predict risk for the next year. Codes collected from:  Inpatient hospital stays  Hospital outpatient claims  Physician office claims  Clinically trained non-physicians, e.g., NPs, PAs, Therapists, Certified Wound Care Practitioners, Podiatrists, Psychologists

34. What Type of Conditions Map to a CMS HCC?  High Cost Medical Conditions (Current Cancer, heart disease, hip fracture)  Highest weighted: HIV, sepsis, opportunistic infections & cancer  Acute, Chronic, status codes, etiology and manifestation  Amputaion, COPD, diabetic neuropathy  Common Conditions, rare conditions, curable and non curable diseases, congenital and acquired…BUT  They must be monitored, evaluated, assessed or treated (MEAT)

35. MEAT for the Chronic Condition  Monitor  Signs, Symptoms, Disease Progression, Disease Regression  Evaluate  Review of test results, medication effective, response to treatment  (stable, improving, exacerbation, worsening, poor)  Assess/Address  Ordering tests, discussion, review records, counseling  Treatment  Referral, medication, planned surgery, therapies, other modalities Example: “CHF well controlled with Lasix and ACE inhibitor. Will continue current medications” “Major Depression – recurrent episode. Patient continues with feelings of hopelessness and anhedonia despite current medication regiment of Zoloft 50 mg daily, Will increase dose to 100 mg daily and monitor”

36. Hierarchical Condition Categories  Every code assigned should be at the most specific level possible based on documentation.  HCCs include diagnoses that are not CCs or MCCs in the MS-DRG grouping system. So, it is important to capture all diagnoses with the greatest specificity possible.  In the inpatient setting, we tend to focus on capturing CCs and MCCs; we need to code all conditions present with the greatest specificity possible. 36

37. Where does the data Come from?  Most of the data that feeds into HCCs comes from Outpatient Encounters  Not All of HCCs are CC/ MCC  HCC’s include 9548 ICD-10 Codes  42% are CCs  16% are MCCs  That Leaves 42% that are neither CC or MCC

38. HCCs That Are Not CCs/MCCs  Some cancer diagnoses, e.g., Secondary Merkel cell carcinoma, C7B.1  DM except that with ketoacidosis or hyperosmolarity or other coma  Sickle cell without crisis  Many psychiatric diagnoses including alcohol and drug dependence  AMI—except initial episode of care  ‘X’ codes for suicide  Status codes including:  Asymptomatic HIV status  Tracheostomy status  Gastrostomy status  Colostomy status  Amputation status  Long-term (current) use of insulin 38

39. Coding HCCs E11.00 Type 2 diabetes mellitus with hyperosmolarity without nonketotic hyperglycemic-hyperosmolar coma (NKHHC) 17 E11.01 Type 2 diabetes mellitus with hyperosmolarity with coma 17 E11.21 Type 2 diabetes mellitus with diabetic nephropathy 18 E11.22 Type 2 diabetes mellitus with diabetic chronic kidney disease 18 Physician documentation and coding are critical for facilities operating under a risk-adjustment system: Medicare Advantage Hospital inpatient VBP Accountable Care Organizations (ACOs) Not all CCs and MCCs designated in the MS-DRG grouping system are included in the HCC code list.. Only E11.00 and E11.01 are MCCs Z89.611 Acquired absence of right leg above knee189 Z89.612 Acquired absence of left leg above knee189 Z89.619 Acquired absence of unspecified leg above knee189 Z91.15 Patient's noncompliance with renal dialysis134 Z93.0 Tracheostomy status82 Z93.1 Gastrostomy status188 Z93.2 Ileostomy status188 Z93.3 Colostomy status188 Z93.4 Other artificial openings of gastrointestinal tract status 188 Z93.50 Unspecified cystostomy status188 None of these codes is a CC/MCC

40. Common Medicare Risk Adjustment Coding/Documentation Errors  Most specific ICD-10 code not assigned  Discrepancies between diagnosis codes billed and diagnoses in the medical record  Clinical documentation does not indicate if diagnoses are being monitored, evaluated, or treated  Status of patient’s cancer unclear, e.g., use of “history of”  Chronic conditions not documented as “chronic”  Diabetic complications not appropriately documented  Record contains non-standard abbreviations or up and down arrows to indicate diagnoses  Unspecified and symptom diagnoses are not considered HCCs 40

41.  Questions????