2. Cheryl Ericson, MS, RN CDI Education Director HCPro, Inc. Danvers, MA Tactics for Reducing the RAC Target on Your Organization

3. Objectives Understanding of growing federal oversight of Medicare and Medicaid programs Increase awareness and understanding of PEPPER data Develop basic analysis skills for the interpretation of organizational PEPPER data Discuss the relationship between organizational PEPPER data and vulnerability to RAC scrutiny

4. Federal Government Oversight of Healthcare Billing Medicare fraud – Making false statements or representation of material facts to obtain some benefit or payment for which no entitlement would otherwise exist and may include Medicare abuse – Practices that either directly or indirectly result in unnecessary costs to the Medicare program. Abuse includes any practice that is not consistent with the goals of providing patients with services that are medically necessary, meeting professional standards, and are fairly priced and may include: Misusing codes on a claim Billing for services that were not medically necessary Medicare Fraud & Abuse: Prevention, Detection, and Reporting Fact Sheet ICN 006827 October 2011 https://www.cms.gov/MLNProducts/downloads/Fraud_and_Abuse.pdf

5. Center for Program Integrity (CPI) Serves as the Centers for Medicare & Medicaid Services (CMS) point for all national and statewide Medicare and Medicaid programs’ integrity fraud and abuse issues Promotes the integrity of Medicare and Medicaid programs though provider/contractor audits and policy reviews, identification and monitoring of program vulnerabilities, and providing support and assistance to states Oversees CMS collaboration with DOJ, DHHS Office of Inspector General, state law enforcement agencies, and other entities for the purposes of detecting, deterring, monitoring, and combating fraud and abuse as well as taking action against those that commit or participate in fraudulent or other unlawful activities

6. The False Claims Act The False Claims Act is the federal government’s primary civil remedy for improper or fraudulent claims. It applies to all federal programs, from military procurement contracts to welfare benefits to healthcare benefits... Specific intent to defraud the government is not required: the government need only establish that the claim submitted is false and that it was submitted knowingly, as defined in the statute. Thus, the False Claims Act covers activity that would not be included under the traditional definition of fraud, which requires actual knowledge and the intent to defraud. Medicare: Application of the False Claims Act to Hospital Billing Practices; The United States General Accounting Office (GAO), July 1998

7. Is Your Organization at Risk Under the False Claims Act? A recent article in Healthcare Highlights quotes Asst. U.S. Attorney Robert Trusiak as he discusses the False Claims Act & PEPPER data. – “… if hospitals receive [PEPPER data] information that their billing is way out of line, the government expects them to act on it.... When hospitals are outliers in a risk area, they are expected to audit medical records and find out if there’s a compliance problem or a reasonable explanation.... a hospital needs to police the PEPPER reports... to assess, analyze and explain billing outliers.”

8. Is Your Organization at Risk Under the False Claims Act? Failure to review PEPPER data can be interpreted as reckless disregard or deliberate ignorance in a False Claims Act case according to this article: – Some Compliance Programs May Fail to Reduce the Risk of False Claims, Sept. 27, 2011; Wolters Kluwer Law & Businesses 31 U.S.C. § 3729. While the False Claims Act imposes liability only when the claimant acts “knowingly,” it does not require that the person submitting the claim have actual knowledge that the claim is false. A person who acts in reckless disregard or in deliberate ignorance of the truth or falsity of the information, also can be found liable under the Act. 31 U.S.C. 3729(b).

9. Organizational Vulnerability What processes are in place at your organization to avoid reckless disregard and deliberate ignorance? What free resources are available to your organization to keep you informed? – CMS resources Provider compliance page – American Hospital Association (AHA) RACTrac – Program for Evaluating Payment Patterns Electronic Report (PEPPER) Data based on facility-specific paid Medicare claims

10. CMS Provider Compliance Page The Medicare Learning Network ® (MLN) Products Provider Compliance page contains educational products that inform Medicare fee-for-service (FFS) providers about how to avoid common billing errors and other improper activities when dealing with the Medicare program. Since 1996, the Centers for Medicare & Medicaid Services (CMS) has implemented several initiatives to prevent improper payments before a claim is processed and to identify and recoup improper payments after the claim is processed. The overall goal of CMS’ claim review programs is to reduce payment error by identifying and addressing billing errors concerning coverage and coding made by providers. https://www.cms.gov/MLNProducts/45_ProviderCompliance.a sp https://www.cms.gov/MLNProducts/45_ProviderCompliance.a sp

11. CMS Provider Compliance Page Downloads available from this site include: – Medicare Fraud & Abuse: Prevention, Detection, and Reporting Fact Sheet – Provider Compliance MLN Products – Provider Compliance MLN Matters ® Articles SE1121: RAC DRG Coding Vulnerabilities for Inpatient Hospitals http://www.cms.gov/MLNMattersArticles/Downloads/SE1 121.pdf http://www.cms.gov/MLNMattersArticles/Downloads/SE1 121.pdf – Medicare Quarterly Provider Compliance Newsletter Archive – How to sign up for electronic mailing lists

12. CMS Provider Compliance Page Understanding common errors/issues identified by CMS audit programs allows an organization to review its own practices for the similar vulnerabilities These resources also provide guidance that can be used by an organization to appeal denials – Remember that Coding Clinic, First Quarter 2004, states, if there is conflicting physician documentation, and the coder fails to query the attending physician to resolve the conflict, hospitals are encouraged to code the attending physician’s version. However, the failure of the attending physician to mention a consultant’s diagnosis is not a conflict. So, if the consultant documents a diagnosis and the attending physician doesn’t mention it at all, it is acceptable to code it. A conflict occurs when 2 physicians call the same condition 2 different things – for example, the attending physician documents a sprained ankle and the orthopedist refers to the same injury as a fracture. MLN Matters SE1121: Recovery Audit Program DRG Coding Vulnerabilities for Inpatient Hospitals

13. Medicare Quarterly Provider Compliance Newsletter Medicare Learning Network –... Help providers understand the major findings identified by Medicare Administrative Contractors (MACs), Recovery Auditors, Program Safeguard Contractors, Zone Program Integrity Contractors, and other governmental organizations, such as the Office of Inspector General.... is designed to help FFS providers, suppliers, and their billing staffs understand their claims submission problems and how to avoid certain billing errors and other improper activities, such as failure to submit timely medical record documentation, when dealing with the Medicare FFS program. – First issue (Volume 1, Issue 1) October 2010

14. October 2011: Volume 2, Issue 1 RAC audit finding – Validation of MS-DRG with ventilator support of 96 or more hours – Improper coding MS-DRG 853, Infectious and parasitic disease with operating room procedure and MCC MS-DRGs 231, 233 & 235, Coronary bypass with percutaneous transluminal coronary angioplasty (PTCA) w/MCC MS-DRGs 100, 101, Coding of seizures Nervous system disorders MS-DRG 840, Lymphoma and non-acute leukemia w/MCC

15. RAC Audit Outcomes American Hospital Association (AHA) RACTrac survey – www.aha.org/advocacy- issues/rac/ractrac.shtml www.aha.org/advocacy- issues/rac/ractrac.shtml – Developed RACTrac in response to a lack of data and information provided by CMS on the impact of RAC on providers – Collects data from hospitals that voluntarily submit data on a quarterly basis to assess the impact of RAC on hospitals nationwide

16. AHA RACTrac Types of information available: – Volume of hospitals reporting RAC activity 85% through September 2011 – Volume of types of reviews by RAC region Automated denials, complex denials, medical record requests – Amount of Medicare payment denials to date – RAC region trends Types of reviews, types of denials, types of errors, volume of appeals, etc.

17. AHA RACTrac Major findings through CY 3 rd Quarter 2011: – Medical necessity accounts for the majority of complex denials surpassing inpatient coding One-day stays with care rendered in the wrong setting – Top MS-DRGs: 312 Syncope & collapse 247 Perc cardiovasc proc w/ drug-eluting stent w/o MCC 69 Transient ischemia (TIA) 313 Chest pain 249 Perc cardiovasc proc w/ non-drug-eluting stent w/o MCC

18. Double Vulnerability DRGs where a symptom is the principal diagnosis are vulnerable to both medical necessity denials and DRG assignment denials. These types of cases should be worked in collaboration between UR/CM and CDI. If these patients are adequately screened and approved as appropriate for inpatient care, then it is probably a lack of documentation leading to the symptom DRG. – 312 Syncope & collapse – 69 Transient ischemia (TIA) – 313 Chest pain

19. How to Reduce the RAC/Federal Audit Target on Your Organization Keep current of national audit findings and work your PEPPER data each and every quarter! – The federal government expects every organization to be familiar with its PEPPER data and to review its results for potential vulnerabilities to overpayment. Who is reviewing your organization’s data?

20. What Is PEPPER? A free resource released quarterly for short-term acute care hospitals through QualityNet – Access is restricted to QualityNet – Identify your facility’s administrator to request the quarterly report or to obtain access to QualityNet – Basically, hospitals are expected by Medicare to review this report

21. PEPPER Basics Provides a quarterly analysis of hospital-specific paid Medicare inpatient claims (MS-DRG) that are vulnerable to improper payment – Potential overpayments – Potential underpayments Use an Internet browser to search “PEPPER Resources” www.pepperresources.orgwww.pepperresources.org – User’s Guide – Training & Resources – Distribution Schedule

22. Microsoft Office Excel® The PEPPER report is distributed as an Excel ® file – Each workbook (file) has pages, which are accessed by the tabs at the bottom of the screen These are the tabs

23. Definitions Page The MS-DRG target areas included in PEPPER are defined on the Definitions Page and generally fall into one of two categories – Coding-focused MS-DRG assignment CC/MCC capture rates – Medical necessity Short-stay (one or two days) admissions Readmissions Top one-day stays medical DRGs Top one-day stays surgical DRGs

24. Definitions Page Each MS-DRG target will have two additional pages useful for in-depth analysis – Two years of historical data by quarters with jurisdictional (MAC) outlier value Quarters with < 11 cases will not have data points – A graph depicting the organization’s historical data compared to the outlier threshold(s) for its corresponding jurisdiction, corresponding state, and the nation

25. Definitions Page DRG target area definition – MS-DRGs used to create the numerator (top number) and denominator (bottom number) – Volume of quarterly paid Medicare claims within each MS-DRG target for the particular organization determines the percentage (%) or “rate” of occurrence within each target, normalizing for bed size These percentages will be used to rank each organization in comparison to the others. Percent is a relative term for ranking and doesn’t range from 0% to 100%. In fact, there is usually a small amount of variance among percentages. Even an organization with what could be considered a relatively low occurrence rate could rank higher than the comparison organizations.

26. Coding Focus Targets The numerator (top number) consists of those discharges prone to MS-DRG coding errors The denominator (bottom number) includes the numerator MS-DRGs as well as the MS-DRGs to which the claim is often reassigned Numerator Denominator

27. Coding Focused Target Example Respiratory infections Are cases being inaccurately assigned to the higher-weighted respiratory infections (MS- DRG 177 & 178) compared to simple pneumonia (MS-DRG 193, 194, 195)? MS-DRG 177 & 178 MS-DRG 177, 178, 179 & 193, 194, 195

28. Medical Necessity Target The numerator (top number) consists of those discharges within an MS-DRG that is prone to unnecessary admissions The denominator (bottom number) includes all discharges for the applicable MS-DRGs Numerator Denominator – Having fewer than 11 cases (no data point) is a positive in these targets

29. Medical Necessity Target Example Transient ischemic attack (TIA) What proportion of TIA (MS-DRG 69) claims are being billed at an inpatient level of care that can be treated in a lesser setting (e.g., as outpatient observation)? MS-DRG 069 MS-DRGs 061 - 069

30. Compare Page Summary of an organization’s paid Medicare claims data for each target during a particular quarter as benchmarked against other facilities – The volume of discharges for each target – The percent (%) of cases for each target based on the target definition – How each target ranks by percentile in comparison to other organizations Jurisdiction, state, and the nation – Associated total value ($) of the paid claims (sum of payments)

31. Compare Page Description Number of target discharge s Percent Hospital Sum of payments Jurisdiction percentile/ occurrence rate State percentile/ occurrence rate National percentile/ occurrence rate Name of target area DRGs used to create ratio Discharges within the description DRGs RatioRank within MAC jurisdiction Rank within state Rank within national comparison Amount of money at risk

32. Compare Page When an organization’s percentage of cases within a target reaches a particular percentile ranking or “threshold,” it is referred to as an outlier – Organizations whose data falls at or above the 80 th percentile are identified as high outliers and may be vulnerable to overpayment Percentages that qualify as a high outlier will appear in red bold Both coding and medical necessity targets will have an upper threshold

33. Compare Page – Organizations whose data falls at or below the 20 th percentile are identified as low outliers and may be vulnerable to underpayment Percentages that qualify as a low outlier will appear in green italics Only coding focus targets have a lower threshold as there is essentially no risk associated with having too few cases in a medical necessity target area

34. Compare Page Identification of outliers – The range of percentages for organizations within a target may be narrow or wide All organizations have a percentage in the range of XX%– XX% – 25%–41% – 11%–63% – It is not the actual percent (ratio) of cases that matters, rather it is how the percent value ranks against other organizations (i.e., in which percentile does the percentage fall?)

35. The ‘Bar’ Is Always Shifting For the most recent quarter (bottom), organizations with a ratio < 24.0% are low outliers and those with a ratio ≥ 42.3% are high outliers What qualifies as an outlier changes each quarter in relation to how organizations rank If an organization maintained a ratio of 42.4%, it would be a high outlier in all but three quarters denoted with

36. Interpreting Your Organizational Data

37. Reviewing Your PEPPER Data Scan your compare page for any red bold and green italics The target(s) associated with any value in red bold will need additional review – Depending on your organization, it may be reasonable for it to be a high outlier on a particular or all coding targets Academic medical center? Tertiary care center? Specialty hospital?

38. Reviewing Your PEPPER Data An academic medical center is likely to be a high outlier in many targets at the state, jurisdiction, and national level A tertiary care center may be a high outlier within its state and maybe its jurisdiction without being a high outlier in the nation A small community hospital that refers out most complicated cases will probably not be a high outlier

39. Compare Page TargetDescription Number of target discharge s Percent Hospital Sum of payments Jurisdiction percentile/ occurrence rate State percentile/ occurrence rate National percentile/ occurrence rate Name of target area DRGs used to create ratio Discharges within the description DRGs RatioRank within MAC jurisdiction Rank within State Rank within national comparison Amount of money at risk

40. Percent (%) Column Coding TargetDescription Number of Target Discharges Percent (Occurrence Rate) Respiratory infections Proportion of discharges with DRG = 177 (respiratory infections & inflammations w/ MCC), 178 (respiratory infections & inflammations w/ CC) compared to discharges with DRG = 177, 178, 179 (respiratory infections & inflammations w/o CC/MCC), 193 (simple pneumonia & pleurisy w/ MCC), 194 (simple pneumonia & pleurisy w/ CC), 195 (simple pneumonia & pleurisy w/o CC/MCC) 1313.1% 1823.1% 2952.0% Knowing the volume of cases may be of use if you want to identify the cases used by Medicare. The percent doesn’t have much meaning outside the context of organizational ranking.

41. Hospital Jurisdiction (MAC) Percentile Coding TargetDescription Percent (Occurrence Rate) Hospital Jurisdiction Percentile Respiratory infections Proportion of discharges with DRG = 177 &178 compared to discharges with DRG = 177, 178, 179, 193, 194 & 195 13.1%2.7 23.1%57.7 52.0%92.6 Pepperresources.org has a link identifying the number of hospitals within each MAC jurisdiction J11 Palmetto GBA: includes North & South Carolina, Virginia, & West Virginia, with a total of 219 acute care hospitals Being a high outlier within the MAC can lead to MAC audits

42. Hospital State Percentile Column Coding TargetDescription Percent (Occurrence Rate) Hospital State Percentile Respiratory infections Proportion of discharges with DRG = 177 &178 compared to discharges with DRG = 177, 178, 179, 193, 194 & 195 13.1%11.1 23.1%59.9 52.0%95.0 Know your organization: Is it concerning to be an outlier within your state? Or is your hospital a referral site for these types of patients so you expect an “over” representation of them at your organization?

43. Hospital National Percentile Column Coding TargetDescription Percent (Occurrence Rate) Hospital National Percentile Respiratory infections Proportion of discharges with DRG = 177 &178 compared to discharges with DRG = 177, 178, 179, 193, 194 & 195 13.1%0.3 23.1%60.0 52.0%95.2 How do you compare to other hospitals within the United States? It is much harder to rationalize outlier status within this comparison group as you may be a “flagship” within your state, but not within the nation. Being an outlier within national ranking can make your organization a RAC target.

44. Sum of Payments: The Bottom Line Coding TargetDescription Number of Target Discharges Sum of Payments Respiratory infections Proportion of discharges with DRG = 177 &178 compared to discharges with DRG = 177, 178, 179, 193, 194 & 195 13 $133,361 ($10,258) 18 $244,949 ($13,608) 29 $407,445 ($14,049) If an organization is a high outlier, there is a potential of overpayment by Medicare. This column shows how much $$$$ is vulnerable to RAC recoupment.

45. Sum of Payments: Medical Necessity Medical Necessity Target Description Number of Target Discharges Sum of Payments One-day stays excluding transfers Proportion of discharges with LOS of ≤ 1 day excluding patient discharge status code of 02, 07, or 20 and excluding one-day stays that have prior observation (revenue code 760 or 762) of > 24 hours 123$633,361 308$1,244,949 529$3,407,445 Medical necessity targets that are high outliers are the most vulnerable to RAC audit and recoupment due to the strong potential of overpayment by Medicare.

46. Identifying Trends: Graph Page As they say, a picture is worth a thousand words – The data and outlier status are helpful when looking at a particular quarter, but all the data is relative, so it is often difficult to identify trends by looking at the raw numbers – The graph page associated with each target translates a series of data points into a picture that easily reveals trends

47. Respiratory Infection Graph: Low Outlier Hospital data High outlier line Low outlier line This organization is below the low outlier threshold and is therefore a low outlier.

48. Respiratory Infection Graph: Variable Movement It is difficult to identify a trend as the data is all over; could be a lack of volume issue. High outlier line Low outlier line

49. Respiratory Infections: High Outlier This organization is consistently a high outlier for respiratory infections. Does it make sense for the organization to be a high outlier for respiratory infections? Hospital data

50. Respiratory Infections: Intervention Hospital data

51. Key Targets for Particular Areas Clinical documentation improvement – Medical DRGs with CC or MCC Can demonstrate the success of the department – Surgical DRGs with CC or MCC Can demonstrate the success of the department – Respiratory infections Queries/education for the identification of the organism associated with pneumonia – Queries/education for symptom Pdx TIA, syncope, chest pain, and atherosclerosis

52. An Academic Medical Center

53. CDI Focus on Surgical Cases

54. CC/MCC Capture Although CDI departments are about more than the money, the CC/MCC capture rates also reflect severity (Medicare severity diagnosis- related groups = MS-DRG), so monitoring the CC/MCC capture trends can demonstrate the positive impact of CDI or the impact of a process change (e.g., we have specifically been targeting surgical DRGs), as well as provide an opportunity for improvement if the trend turns negative

55. Key Targets for Particular Areas Utilization review – One-day stays excluding transfers Some Medicare inpatient-only surgical DRGs may appear on this list and generally do not require additional review – One-day stays for medical DRGs – Symptom DRGs TIA, syncope, and chest pain These often correlate with one-day stays and often these DRGs will appear on the top one-day stay DRG lists

56. Symptom DRGs Although symptom DRGs are often targeted for medical necessity, they can also represent an opportunity for CDI – Monitor your PEPPER data for symptom DRGs and review these cases to verify the Pdx as these are often short-stay admissions that may not receive concurrent review Consider creating a “discharge without review” work list to capture short stays prior to billing. Often physicians will not document a condition unless it is verified by studies (e.g., labs, imaging). Reinforce the use of “suspected, likely, probably, evidence of,” etc. in the discharge summary when the underlying cause is based on clinical presentation, even if not supported by studies.

57. Med DRG Description Hospital one-day stay count Total discharges for DRG Proportion of one-day stays to total discharges for DRG 392 Esophagitis, gastroent & misc digest disorders w/o MCC 2810825.9% 641 Nutritional & misc metabolic disorders w/o MCC 219023.2% 309 Cardiac arrhythmia & conduction disorders w/CC 196728.4% 287 Circulatory disorders except AMI, w/ card cath w/o MCC 188920.2% 292 Heart failure & shock w/CC 1812114.9% 313 Chest pain 162759.3% 310 Cardiac arrhythmia & conduction disorders w/o CC/MCC 145425.9% 847 Chemotherapy w/o acute leukemia as secondary dx w/CC 133933.3% 948 Signs & symptoms w/o MCC 112347.8% 303 Atherosclerosis 113333.3%

58. Med DRG Description MAC one- day stay count Total discharges for DRG Proportion of one-day stays to total discharges for DRG 313 Chest pain (#6) 5,40311,89045.4% 392 Esophagitis, gastroent & misc digest disorders w/o MCC (#1) 3,36818,71118.0% 310 Cardiac arrhythmia & conduction disorders w/o CC/MCC (#7) 3,1169,87831.5% 312 Syncope & collapse (N/A) 2,97911,62025.6% 287 Circulatory disorders except AMI, w/ card cath w/o MCC (#4) 2,52910,59923.9% 69 Transient ischemia (N/A) 2,2157,38430.0% 641 Nutritional & misc metabolic disorders w/o MCC (#2) 2,03011,53917.6% 812 Red blood cell disorders w/o MCC (N/A) 1,7177,62722.5% 690 Kidney & urinary tract infections w/o MCC (N/A) 1,45015,3339.5% 309 Cardiac arrhythmia & conduction disorders w/CC (#3) 1,4348,89016.1%

59. Symptom DRGs Talk to the medical staff – MUSC is a stroke referral site and provides telemedicine consults – Patients were receiving TPA at an outside hospital, but being discharged with a dx of TIA due to a lack of findings on imaging/resolved symptoms – TIA patients don’t typically receive TPA – TPA is a “clot buster” reestablishing cerebral blood flow so symptoms are resolved upon presentation at MUSC – Discovered “aborted stroke” was a more appropriate diagnosis for this population

60. Key Targets for Particular Areas Utilization review – One-day stay MS-DRG targets Any part of an inpatient stay that occurs before midnight is counted as one day – Two-day stay MS-DRG targets These are new targets as many organizations are slow at discharging patients extending their stay beyond one day without significantly changing the treatment plan or demonstrating the initial acuity of the patient

61. Key Targets for Particular Areas Case management – Three-day skilled nursing facility qualifying admissions Patients who spend three consecutive midnights as an acute inpatient qualify for Medicare to cover some SNF days – many cannot afford SNF care unless Medicare covers it – 30-day readmissions – VBP This is also a UR issue as many patients with frequent admissions have chronic conditions that can often be treated in the outpatient setting (observation) rather than as an inpatient

62. 30-Day Readmissions Avoidable readmissions are receiving more attention as heart failure, COPD, and AMI readmissions will impact hospital reimbursement as a VBP metric. CDI can impact this metric by reviewing HF and COPD records to ensure the severity of the condition is accurately represented in the medical record (i.e., What is the patient’s current respiratory status in comparison to his/her baseline?) You would expect that patient to be in acute on chronic respiratory failure to necessitate an admission for these conditions.

63. 30-Day Readmissions Be aware of admissions for fluid volume overload in a patient with HF and ESRD as they default to a Pdx of HF – Look for clues like “missed dialysis” – Check renal consult notes – Look for evidence of evaluation of left ventricular systolic function (LVS) – Query the provider to specify which disease process (HF or ESRD) led to the fluid volume overload to avoid incorrect Pdx assignment

64. 30-Day Readmissions General guidelines – Advise providers to document when a patient leaves prior to completion of the treatment plan Against medical advice (AMA) – Advise providers to document when a patient was/is noncompliant with the outpatient/discharge treatment plan Failed to fill prescriptions Missed follow-up appointment

65. Next Steps Review PEPPER User Guides Look for upward trends and spikes Develop process improvement methods Be proactive/educate – ignorance is NOT a defense Share internal auditing of high outlier MS- DRG results with all key players Review medical records with coding, utilization review/case management, and CDI

66. In order to receive your continuing education certificate for this program, you must complete the online evaluation which can be found in the continuing education section at the front of the workbook. Questions?