Government Programs: Lessons from the CMS Physician Group Practice (PGP) Demonstration Project- Emphasis on Heart Failure 3 rd National Pay for Performance Summit February 28, 2008 F. Douglas Carr, MD, MMM Medical Director, Education & System Initiatives Billings Clinic

Outline Intro Billings Clinic PGP mechanics Focus on our approach to Heart Failure Performance Year 1 Results Observations Questions Barriers to Remote Monitoring

What is Billings Clinic? Group Practice –w/ 225 Physicians, 65 midlevels, 29 (~50 sub-) specialties (Allergy to Urology) –10 clinic locations –272 (220) bed tertiary hospital –Manage/support 7 CAHs –3000+ Committed Employees –3 rd largest employer in Montana Integrated Delivery System/ Medical Foundation –Board of Directors: community-based –Leadership Council (Internal Board): physician majority + senior administrators

Service Region Locations Riverton Fremont Casper Powell Park Cody Hot Springs Thermopolis Bighorn Lovell Greybull Washakie Worland Sheridan Johnson Buffalo Campbell Gillette Crook Lincoln Flathead Sanders Mineral Lake Glacier Missoula Ravalli Beaverhead Granite Deer Lodge Powell Toole Pondera Teton Lewis & Clark Cascade Jefferson Silver Bow Broadwater Madison Gallatin Park Sweet Grass Stillwater Meagher Wheatland Judith Basin Chouteau Liberty Hill Blaine Fergus Golden Valley Carbon Big Horn Yellowstone Musselshell Petroleum Phillips Valley Garfield Rosebud Treasure Powder River Carter Custer Fallon Prairie Wibaux Dawson McCone Richland Roosevelt Sheridan Daniels Missoula Butte Dillon Havre Lewistown Livingston Columbus Billings Red Lodge Hardin Roundup ForsythMiles City Baker Glendive Sidney Wolf Point Glasgow Weston Natrona Great Falls Kalispell I-15I-90 I-25 Williams Williston Divide McKenzie Dickinson Golden Valley Billings Dunn Stark Slope Bowman Adams Hettinger I-94 HWY 2 Scobey Big Timber Colstrip Bozeman Affiliate Management Services Columbus - Stillwater Hospital Colstrip - Colstrip Clinic Forsyth - Rosebud Healthcare Lovell - North Big Horn Hospital Red Lodge - Beartooth Hospital Big Timber - Pioneer Medical Center Livingston - Livingston Healthcare Scobey - Daniels Memorial Hospital Clinic Locations & Number of Providers Billings Clinic - Cody (7 MDs, 1 PA) Bozeman OB/Gyn (6 MDs, 2 NPs, 1 PA) Billings Clinic - Forsyth (1 PA) Billings Clinic- Main (200 MD, 47 PA) Billings Clinic - West (8 MDs, 1 PA) Billings Clinic - Miles City (10 MDs, 3 PAs) Billings Clinic - Red Lodge (4 MDs) Billings Clinic - Columbus (2 MDs, 1 NP) Billings Clinic - Heights (4 MDs, 1 PA) Counties with Affiliate or Branch Clinic Other Service Area Counties December 2007

Montana: 147,138 square miles and 922,002 people

CMS PGP Objectives Health Care Education and Research Encourage coordination of Part A & Part B Coordinate care for chronically ill and high cost beneficiaries in an efficient manner Decrease the growth in Medicare spending over the next 3 years

Everett, WA – Everett Clinic Marshfield, WI – Marshfield Clinic Springfield, MO – St Johns Danville, PA-Geisinger Billings, MT-Billings Clinic St. Louis Park, MN – Park Nicollet Winston-Salem, NC-Novant- Forsyth Physician Group Practices Integrated Delivery Systems Academic & Network Org. Middletown, CT – Integrated Resources for Middlesex Area (IRMA) Ann Arbor, MI - University of Michigan Bedford, NH-Dartmouth Hitchcock 10 Organizations

CMS PGP Project Timeline Base Year: Calendar year 2004 Performance Year 1:April 1, March 31, 2006 Performance Year 2:April 1, March 31, 2007 Performance Year 3: A pril 1, March 31, 2008 Performance Year 4: April 1, 2008 – March 31, 2009

PGP Demo Concepts Medicare Fee For Service continues as before If PGP is able to reduce the growth of Medicare spending for the cohort under its care compared to a regional comparison, CMS will share part of its savings with PGP Budget neutral project for CMS Meeting Financial Target= “Gate” Once “Open”, PGP’s portion dependent on meeting Quality Measures

CMS PGP Beneficiary Assignment To be assigned to PGP: –PGP must provide to beneficiary at least one E&M office or other OP service plurality of E&M office/OP services provided in the year To be assigned to Comparison Group –Beneficiary must have at least one E&M Service –Cannot have had any E&M services at PGP during the current year or been assigned to the PGP previously. –Must reside in a service area county. –Service area counties must provide 1% of eligible beneficiaries.

PY-1 Billings Clinic versus Comparison Group Service Area Distribution Riverton Fremont Casper Park 10 V 12 % Hot Springs Thermopolis Bighorn 3 V 4 % Washakie Worland Sheridan 1 V 16 % Johnson Buffalo Campbell Gillette Crook Lincoln Flathead Sanders Mineral Lake Glacier Missoula Ravalli Beaverhead Granite Deer Lodge Powell Toole Pondera Teton Lewis & Clark Cascade Jefferson Silver Bow Broadwater Madison Gallatin Park Sweet Grass Stillwater Meagher Wheatland Judith Basin Chouteau Liberty Hill Blaine Fergus Golden Valley Carbon Big Horn Yellowstone Musselshell Petroleum Phillips Valley Garfield Rosebud Treasure Powder River Carter Custer Fallon Prairie Wibaux Dawson McCone Richland Roosevelt SheridanDaniels Missoula Anaconda Butte Dillon Bozeman Havre Lewistown 1 v 7 % 4 v 2 % 61v 40 % 5 v 3 % Hardin 2 v 1 % 2 V 3 % 8 v 4 % Baker 1 v 5 % Sidney Culbertson Wolf Point 2 v 3 % 16.4% of Assigned Beneficiaries in PY-1 are outside of the PGP Service area

CMS PGP Demonstration Project Bonus Sharing Methodology PGP Financial Target Calculation: 1.Identify comparison group in same counties 2.Calculate rate of growth of per capita expenditures from base to performance year 3.Comparison group growth rate is applied to the PGP’s base year 4.Individual risk adjustments (HCC) apply to both groups to account for case mix changes between years

CMS PGP Demonstration Project Bonus Sharing Methodology Medicare Savings = (Per Capita Target – PGP’s Performance Year Per Capita Expenditure) X (Assigned Beneficiaries) Bonus Sharing Formula –20% retained in Medicare Trust Fund –80 % eligible to PGP Percentage based on both financial and quality indicators and changes each performance year

PGP Project Financial Model SVNGS >2% 20%  CMS 80% Performance Pay 0.3 Q 0.7 E 0.4 Q 0.6 E 0.5 Q 0.5E Y1 Y2 Y3 Y4 Q: Quality E: Efficiency 0.5 Q 0.5 E

CMS PGP Quality Measures Year 1: Diabetes Year 2: Year 1 plus HF and CAD Year 3: Year 2 plus Hypertension and colorectal and breast cancer screenings + flu and pneumonia vaccines Total 32 Outpatient

Quality Measures: Diabetes % of patients in performance year with Claims Based Hgb-A1c tests LDL test Microalbumin testing or Dx/Tx for nephropathy Retinal exam by MD/OD: 1year/high risk, 2 years/low risk Chart/Hybrid Based HgbA1c ≤ 9.0% BP< 140/90 LDL<130 Complete foot exam documented Influenza vaccine Pneumoccocal vaccine

Quality Measures: HF % of patients in performance year with Claims Based LV-EF in same year if hospitalized for HF Chart/Hybrid Based Qualitative/quantitative LVF Assessment Visits Weight documented Visits BP documented HF Education documented in last 6 months LVSD on ß-blocker LVSD on ACEI HF/AF on Warfarin Influenza vaccine Pneumococcal vaccine

Quality Measures: CAD % of patients in performance year with Claims Based Lipid profile Chart/Hybrid Based LDL<130 Antiplatelet Rx Lipid Rx Hx MI, on ß-blockers last visit DM &/or LVSD on ACEI

Quality Measures: Preventive Care % of patients in performance year with Claims Based ♀ y.o. w/ mammogram in current or prior year Chart/Hybrid Based “Screened” for colon Cancer BP documented Last BP<140/90 If BP is >140/>90  documented plan of care

PGP Quality Thresholds: Absolute or Relative Targets The higher of 75% compliance, or the Medicare mean, or … 70 th percentile of Medicare HEDIS  10 % reduction in gap between administrative baseline and 100% compliance, or…

Base Year Data: Where does the $ go? Components of Medicare Expenditures For Billings Clinic Inpatient40% Hospital OP24% Part B22% SNF 7% Home Health 3% DME 4%

CMS PGP Mantra Quality Measures are OUTPATIENT driven. Financial Savings are INPATIENT driven.

Base Year Data: What Diagnoses? HCC 80: CHF  1,945 discharges HCC 92: Heart Arrhythmias  1,898 HCC 15-19: Diabetes  1,683 HCC 108: COPD  1,887 HCC 79: Card-Resp Failure  1,305 HCC 105: Vascular Disease  969 HCC 131: Renal Failure  743

CMS PGP Patient Focus Areas METABOLIC DISEASE: DIABETES HTN CARDIOLOGY: HF CAD Needless Admissions: 5 Wishes Nursing Home Psychiatry Medication Reconciliation PREVENTIVE CARE: Colorectal & Breast Cancer Screening Immunizations

EMR: Vehicle for Process Improvement Chronic Disease Management –Disease Registry –Disease Management Modules (DM, HF, CAD, HTN) –Clinical Guidelines –Reports for organization and providers –Patient information Health Maintenance –Cancer, Osteoporosis, etc. Screening –Immunizations Patient Safety –Medication reconciliation during transitions of care Health Care Education and Research

Heart Failure Cost Savings Goal: Decrease ‘All Cause’ Admissions 10-20%  50% –Existing HF Clinic: 200  750 patients –Technology leverage Quality Improvements –HF Clinic Re-design: Expand RNs, daily IP/OP coverage, Mid-level –Adopt new Treatment Guidelines –HF Management POC Modules in Cerner –Feedback to providers with patient report cards –HF Registry build > 3,000 –Effective Patient Education Health Care Education and Research CMS Quality Measures: □ □ Ejection Fraction Test □ □ Blood Pressure Screen □ □ Patient Education □ □ ACE/ARB Therapy □ □ Beta Blocker Therapy □ □ Smoking Status

Heart Failure Disease Module: Alerts for Providers

E-form for Heart Failure Registry and Tel- Assurance Program Enrollment

E-form for documenting Smoking Status and Education

E-form for documenting Heart Failure Education

Heart Failure Point-of-Care Summary Screen

1997 – 2005 : HF Program Prior to PGP Outpatient tele-management program (POTs), within cardiac rehab –HF inpatient pathway  provider referral Physician-directed Nurse management –2.6 FTEs (RNs); M-F –150+ patients: discharged at 1 year if stable –Reduced HF hospitalizations by about 10-20%? PGP/CMS-RTI stats 2004: 1800 HF patients, 1900 admissions How to have a greater impact?

Interactive Telephone System with Web-enabled Data Tracking Evanston Northwestern Hospital by Randy Williams, MD in late 1990’s Utilizes daily monitoring system for patients via Interactive Voice data collection Validated, proven system that manages by exception Allows for 1 RN to follow patients Has demonstrated reduction of all-cause hospitalization some hospitals

Interactive Telephone System with Web-enabled Data Tracking Patients call daily between 4 AM and Noon Data appears immediately on a web server HF “Care Coaches” (RNs) call outliers –Manage per HF protocols (diuretic ∆) –Refer to HF Clinic MD/NPP or PCP Goal: coordinate care w/“Tx Physician”

Recorded Questions 1.Have you noticed more swelling in the last day? 2.Did you wake up short of breath last night? 3.Did you sleep in a chair or prop up with pillows more than usual last night? 4.Have you had any lightheadedness or dizziness in the last day? 5.Please enter this morning’s weight. Have you felt more sort of breath in the last day?

The Challenges of Patient Adherence 17% Other 19% Failure to Seek Care 16% Inappropriate Rx Rx Noncompliance 24% Diet Noncompliance 24% Vinson J Am Geriatr Soc 1990;38:1290-5

Disease Severity / Future Financial Risk # of At Risk Individuals Care Mgmt Targets Existing Approach to Chronic Population Care Management Top 5-10% of population Unmet Need and Unmanaged Risk

Pharos Target Population Disease Severity / Future Financial Risk # of At Risk Individuals Telephonic Enhanced Adherence Monitoring The Target Population

Current model of HF Program 6 RNs providing 7day/week coverage for IP education/enrollment and OP care management. IP Care: –Focused on ADHF patients (Case ID: referral, registry, admit Dx, BNP, etc.) –Core Measures documentation assisted by new Cerner Powerforms –Discharge planning: Euvolemia & Early follow-up visit (5 days) –Opportunity for enrollment for other patients with HF OP care: –RN triage and intervention (pre-approved protocols for diuretics/electrolyte management) –~500 patients w/ HF use TelAssurance© Daily telephone call in, IVR system 5 questions + weight  variances precipitates RN follow-up –Minimum # (~50) called at least monthly, unable to use TA Midlevel : Available for post-hospital, emergent, and Rx Titration per physician discretion

Billings Clinic Service Area Riverton Fremont Casper Powell Park Cody Hot Springs Thermopolis Bighorn Lovell Greybull Washakie Worland Sheridan Johnson Buffalo Campbell Gillette Crook Lincoln Flathead Sanders Mineral Lake Glacier Missoula Ravalli Beaverhead Granite Deer Lodge Powell Toole Pondera Teton Lewis & Clark Cascade Jefferson Silver Bow Broadwater Madison Gallatin Park Sweet Grass Stillwater Meagher Wheatland Judith Basin Chouteau Liberty Hill Blaine Fergus Golden Valley Carbon Big Horn Yellowstone Musselshell Petroleum Phillips Valley Garfield Rosebud Treasure Powder River Carter Custer Fallon Prairie Wibaux Dawson McCone Richland Roosevelt SheridanDaniels Missoula Anaconda Butte Dillon Bozeman Havre Lewistown Livingston Big Timber Columbus Billings Red Lodge Hardin Roundup Forsyth Miles City Baker Glendive Sidney Culbertson Wolf Point Glasgow Primary Secondary Tertiary Population Sq. Miles Yellowstone 136,029 2,635 Secondary 54,006 26,101 Tertiary 341,927 92,630 TOTAL: 531, ,366 Source: Claritas, Inc Population Estimate US Census Bureau Land Area Sizes

All Cause Hospitalizations in HF Patients - Per 1000 (using hospital and clinic for determining HF Population (HCC 80)) Residents of Yellowstone and Contiguous Counties only

Heart Failure Primary Dx Hospitalizations – Per 1000 (using hospital and clinic data for determining HF Population (HCC 80))

>50% reduction in hospitalizations or ~ 6/100/month enrolled in TA Total: # 516 Medicare: ~80%

Estimated Cost Savings to Medicare Upper Est.: $2,770,000 Lower Est.: $1,736,000

PGP PY-1 Results Press Release by CMS July 2007 (Q2PY3!) 1° result is improved Diabetes quality measures across all org, most are > national benchmarks Process Improvements were applied to all patients/payers; no restriction of services Aggregate Savings to CMS of ~$21M over ~225,000 beneficiaries 2/10 orgs (Marshfield Clinic & U Michigan) achieved >2%  $7+M in bonus payments

Billings Clinic PY-1 Results Achieved 8/10 Diabetes targets, 20/22 total points (91%) Did not exceed the 2% threshold, thus no bonus received in 1 st year Inpatient costs reduced } vs. Comparison Outpatient costs higher } “ “ (HF and many other programmatic efforts not functional until PY-2)

Challenges Our Issues –Cultural change management –EMR enhancements: Not off-the-shelf (“certification”); Registry build –PC Model: Access, Documentation, Process Redesign –Medication Reconciliation –Care Management –Robust Advance Directives implementation CMS/Methodology –Investment in resources/infrastructure (cash flow, risk) –Financial bar high, demo too short (  5 years?) –Data abstraction requirements –Lack of real-time data from CMS –Attribution of beneficiaries –Comparison group selection –Risk Adjustment (HCC): coding specificity,

Working with CMS

What have we learned from playing with CMS? Delay in receiving data fails to support the improvement process Initial results reflect the delay between process improvements and clinical outcomes. Quality improvement may also not inherently be more efficient, especially in the short-term. Coding specificity will play a significant role in national programs that attempt to track quality with claims data (e.g.. PQRI)

Observations on HCC risk adjustment scores Base Year Variation among the 10 PGP groups: to PY-1 results were significantly influenced by the Δ between attributed and comparison groups HCC scores tend to increase “2%/year in managed care markets”; demo range: 0.5% to 6.5% Future of CMS Value Based Purchasing initiatives (P4P) likely to hinge on greater specificity of charge data –Future Medical Home management fee likely will be risk adjusted –MS-DRG and HCC risk drivers are similar: specificity & comprehensive, emphasis on some “usual suspects”

Statistical Challenges for Rural Counties? Risk Adjustments for rural counties, especially with beneficiary numbers 17%) The net financial effects for Billings Clinic are greatly related to the change in Risk Adjustment. (-3% relative to comp group)

Observations Look more broadly at interventions –HF as 1° Dx is 13% of all admissions for HF patients PGP lessons may be hidden in the details –2/10 achieved financial targets in 1st year –Success in individual programs may be lost in the overall analysis –After PY1, all groups are more aware that HCC risk adjustment is a CSF Premier analysis of HF is limited to a more narrow hospital/episode of care perspective

Observations DM by providers, not intermediaries, allows for direct intervention and best integration of care and QI into the care delivery system Medical Home: Is the infrastructure sufficient to achieve the outcomes? Not all diseases have same monetary impact or ROI/timeline –HF vs. Diabetes, COPD, CAD, HTN, Cancer Prevention The “Tyranny of FFS”

…….Any Questions?

Barriers to wide-spread adoption of remote monitoring to chronic care Payment systems –FFS promotes piece-work, lack of accountability of outcomes –No FFS recognition of DM or care coordination activities 3 rd Party vs. Provider-based DM –Providers can better integrate DM into clinical treatment –Coordination of IP/OP –Greater clinical accountability for the total care of patient –EHR interface/ communication with all providers

Barriers to wide-spread adoption of remote monitoring to chronic care Provider integration –Coordination among specialties –Outpatient + Inpatient –EHR is the vehicle for coordination and guideline use at POC Dissemination of guidelines POC alerting/ordering/documentation –Other infrastructure (human resources) required for DM –Registry build and maintenance –Organizational change management

Barriers to wide-spread adoption of remote monitoring to chronic care Provider Acceptance –Professional change management (Team Process) –Workflow change –Accountability/feedback (report cards) Patient Acceptance –Passive  “Activated” (Wagner Chronic Care Model) –“Selling” is not skill set in Health Care –Enrollment is always less than reported 3 rd party: 10% Provider: 20% “Seller”: 30+%

Barriers to wide-spread adoption of remote monitoring to chronic care HIT –Interface/interoperability –Registry build and maintenance –Current EHR “certification” doesn’t include supporting accepted quality measures –Quality measures are not uniform –Reporting capabilities lagging Geographic –Ideal for the model/technology –Increases provider interaction complexity