Maximizing Reimbursement Using Midas+ Tools · CHF, Pneumonia, COPD, THA/TKA, and CABG clinical...

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Maximizing Reimbursement Using Midas+ Tools Lynn Smith, Clinical Excellence Executive, Midas+ Care Performance

Transformation Group

Barb Schork, Midas+ DataVision Product Specialist

Objectives

• Identify and discuss the basics of the three regulatory programs affecting annual Medicare reimbursement

• Describe resources available in Midas+ to assist Midas+ clients in assessing the potential for regulatory financial penalties

• Understand the function and benefits of the Readmission Penalty Forecaster

CMS Programs with the Potential for Financial Penalties

• Value-Based Purchasing (VBP)

• Hospital Readmissions Reduction Program (HRRP)

• Hospital Acquired Complications Reduction Program (HACRP)

Estimated Penalties

Source: The Advisory Board Care Transformation Center, 6/18/14

Payment Adjustment Hierarchy

Payment reductions are made in a hierarchical order:

1. VBP 2. HRRP 3. HACRP

But there’s a catch . . . • VBP and HRRP payment adjustments are

made independently of each other. • They are each applied to the base operating

DRG payment amount. • HAC adjustments are made after VBP and

HRRP.

Here’s a simplified example of how it works:

• Base Operating DRG Payment Amount = $1,000,000

• -2% adjustment for VBP = $20,000 • -3% adjustment for HRRP = $30,000 • Net = $950,000 • -1% adjustment for HACRP = $9,500 • Net = $940,500 • Total Penalties = $59,500 (5.95%)

Both VBP and HRRP are applied to the full $1 million

Value-Based Purchasing

What is Value-Based Purchasing? As described by CMS:

“Hospital Value-Based Purchasing (VBP) is part of the Centers for Medicare & Medicaid Services’ (CMS’) long-standing effort to link Medicare’s payment system to a value-based system to improve healthcare quality, including the quality of care provided in the inpatient hospital setting. The program attaches value-based purchasing to the payment system that accounts for the largest share of Medicare spending, affecting payment for inpatient stays in over 3,500 hospitals across the country. Participating hospitals are paid for inpatient acute care services based on the quality of care, not just quantity of the services they provide.”

Value-Based Purchasing Program FFY 2017

[CATEGORY NAME] [VALUE]

[CATEGORY NAME] [VALUE]

[CATEGORY NAME] [VALUE]

[CATEGORY NAME] [VALUE]

[CATEGORY NAME] [VALUE]

Clinical Care

Track Your Hospital’s Performance

Track Corporate Performance

See How Far the Dots Need to Move

Set Targets to Move the Dots

If One Measure Improves by 1%

90% lower estimated loss

+7 awarded points

Hospital Readmissions Reduction Program (HRRP)

HRRP

• Includes unplanned readmissions for AMI, CHF, Pneumonia, COPD, THA/TKA, and CABG clinical cohorts

• Payment determination is based on performance from 7/1/12 through 6/30/15

Readmissions Cost $$$$$$$

Condition

Number of 2011 Medicare

Readmissions

Cost of 2011 Medicare

Readmissions

All-cause 1,800,000 $24.0 billion

CHF 134,500 $1.7 billion

Septicemia 92,000 $1.4 billion

Pneumonia 88,000 $1.1 billion

Source: AHRQ H.CUP Statistical Brief #172, April 2014

Impact of Readmissions • CMS estimates that 1 in 5 Medicare patients

return to the hospital within 30 days of discharge (~2,000,000 annually)

• 139,000 had 3 or more readmissions* • CMS also estimates that 65% of the annual

cost for readmissions is potentially avoidable

* 2012

Why Readmissions? • Readmissions on the decline at 19% 2007-2011

− 2007-2011 = 19% − 2012 = 18.5% − 2013 = 17.9% − Est. 150,000 fewer 2012-2013

• According to CMS, reduction in inpatient readmissions does not seem to be correlated to substituting OP ED or OBS stays

Monitoring Readmissions in DataVision • More than 500 distributed DataVision

readmission measures • DataVision Readmission Toolpack

Distributed Readmission Measures - Server • CMS Readmissions Reduction measures • Readmissions by clinical population • Overall readmissions

Readmission Measures - Web Comparative Trend Analyses and SPC Charts

DataVision Readmission Toolpack • Use for distributed or user-defined indicators • Modify selection criteria for same clinical

condition or all-cause • Exclude elective readmissions, discharge

disposition of death • Select specific encounter types

New Midas+ Risk Model for Readmissions • Acute Care, Inpatient, and Medicare

populations • Encounter-level risk adjustment • Readmissions to any facility on your server

within 309 Midas+ Clinical Clusters • Observed and expected values – non-adjusted • Observed and expected values adjusted for

admissions back to ANY facility

Readmission Penalty Forecaster

Confusion about Readmissions…

• Publicly reported data – consumer availability • Hospital Reimbursement Penalties

7/2010 6/2013 FY 15

7/2011 6/2014 FY 16

7/2012 6/2015 FY 17

7/2013 6/2016 FY 18

NOTE: The 12 months immediately prior to the origination of the performance period is included for patient risk factors

How Performance Periods Line up with Payment Adjustment Periods

FY=Oct1-Sept 30

CURRENT

Readmission Penalty Forecaster • Uses Medicare Part A & B Claims Data

– Includes risk Factors and risk coefficients • Also includes Midas+ data from January 2014

through latest harvested quarter

• RPF measures available to Readmission Penalty

Forecaster clients only; delivered as a service including quarterly presentations

Readmission Penalty Forecaster (continued)

• CMS claims data used when possible • Supplemented with data from each

subsequent quarterly harvest • Adjusted to account for “non-same” hospital

readmissions • Patient-level files provided

HRRP Penalties Forecasted to Impact More Hospitals in Future

• Acute Myocardia Infarction • Pneumonia • Heart Failure • Total Hip and Knee • COPD • CABG

FY 2014 64% US hospitals had penalties and 18 had a full 2% reduction of their base operating

DRG

FY 2015 FY 2016

CMS estimates only 39 hospitals will be subject

to maximum 3% reduction in

FY 2015

FY 2017 Midas+ Xerox

estimates 80% of all hospitals will be

penalized in FY 2017

Excessive Readmission Ratios Values > 1.0 = Financial Penalties

Your Hospital ERR Other Hospitals

HRRP Penalties Predicted to Impact More Hospitals in the Future

• Acute Myocardial Infarction

• Pneumonia • Heart Failure • Total Hip and Knee • COPD • CABG

Excess Readmission

Ratios > 1 in ANY one of the

clinical cohorts results in financial

penalties

Excess Readmission Ratio = Predicted /Expected

A Primer on Predicted and Expected

Predicted FY 2016

Excess Readmission Ratio = Predicted /Expected

=

Your patients’ risk factors for FY 2016 Part A & B Claims

(July 1, 2010 – June 30, 2014) x

Risk Coefficients

(July 1, 2011 – June 30, 2014)

+

Your hospital

provider Intercept

(July 1, 2011 - June 30, 2014)

Expected FY 2016 = +

Your patients’ risk factors for FY 2016 Part A & B Claims

(July 1, 2010 – June 30, 2014)

x

Risk Coefficients

(July 1, 2011-June 30, 2014)

Average hospital provider intercept for all Section(d) Hospitals in US

(July 1, 2011 – June 30, 2014)

Moving Target

• Unlike VBP, Medicare does not give credit to a hospital for reducing readmissions from the previous year . . . if their rate is still higher than what CMS believes is appropriate (expected).

• Medicare uses the national readmission rate to help decide what is appropriate for each hospital

• Hospitals must not only reduce their readmission rates but do so better than the industry did overall – Status quo may leave you behind the pack even if you

started out ahead

Forecaster – Corporate Summary

Individual Hospital View

Cohort Detail

Patient-level Files - RPF

Client Findings - Forecaster

• Interesting trends in “non-same” readmits • The amount of excess readmissions only has to be

1 (in a single cohort) to initiate penalty • Need process improvement with post acute care

providers • The expected value is consistently lower for FY 17

than FY 16 • Above average in FY 16 is not a guarantee for FY

17 – moving target

Compare & Contrast DataVision Readmission Penalty Forecaster

DATA INCLUSION Inpatient, acute care, cohort level Inpatient, acute care, cohort level

FACILITY Readmissions only to same facility Readmissions to same facility with adjustment for “non-same”

DATA SOURCE Hospital’s Midas+ data: ADT/DAB Primary: CMS claims Secondary: Hospital’s Midas+ data

PAYER All patients with Medicare as payer (any position in the hierarchy)

• CMS Claims – Medicare as principal/secondary

• DV data – Medicare as principal

FREQUENCY Updated nightly, close to concurrent

• Quarterly for Midas+ data • Annually for CMS claims data

COMPARATIVE Midas+ Comparative Database All participating hospitals included in CMS claims data (Expected)

ANALYTICS Built in Toolpacks Executive level insights

Compare & Contrast (continued)

DataVision Readmission Penalty Forecaster

CHALLENGES Weaker proxy measure for estimating CMS financial penalties and excess readmissions

Not all patients can be identified by MRN; Midas+ uses matching logic to re-identify them where possible

STRENGTHS • Reflective of patient management at your facility

• Useful for evaluating case management and/or quality of care

• Cohort-level data

• High degree of accuracy in predicting excess readmissions & associated penalties

• Excess readmission data provided at the cohort level

In short . . . • DataVision and the Forecaster both provide identification of

readmissions at cohort and patient level • DV more qualitative – RPF more quantitative • Readmissions critical to hospital reimbursement for the

foreseeable future • Additional population cohorts may be added by CMS • Related publicly reported data will continue to grow as the

shift from volume to value promotes transparency • Tracking readmissions continues to be a priority at Midas+

to support our clients in meeting regulatory challenges

Hospital Acquired Conditions Reduction Program

Hospital Acquired Conditions Reduction Program (continued)

• Points are awarded based on national decile ranking for each measure (lower is better)

• For FFY 2017: – AHRQ PSI 90 Domain 1 (25%)* – CLABSI – CAUTI – SSI Domain 2 (75%)* – MRSA (1/14-12/15)

– CDI * Proposed

HACs are Expensive

Type of Infection

Estimated Annual

Infections

Estimated Cost per Infection

Estimated Total Annual

Cost

SSI 290,485 $25,546 $7.4 billion

CLABSI 248,678 $36,441 $9.1 billion

VAPs 250,205 $9,969 $2.4 billion

CAUTIs 561,667 $1,006 $565 million

Source: Advance Healthcare Network Executive Insight, March 8, 2011

But, things are improving . . .

• HACs declined 17% 2010-2013

• 1.3 million fewer HACs

• Estimated 50,000 fewer mortalities

• $12 billion in cost savings

• Largest impact on cost savings = ADEs and PrUs

Source: AHRQ, Publication #15-0011-EF, 2013

Estimated Cost Savings = $9 B

HAC Projected P4P Cost Savings

(2014)

Estimated Lives Saved

ADE $2,375,000,000 9,500

Pressure Ulcers $1,062,500,000 4,525

VAP $ 210,000,000 1,438

CLABSI $ 170,000,000 1,850

SSI $ 161,700,000 217

Post-op VTE $ 160,000,000 2,080

CAUTI $ 106,000,000 2,470

Source: AHRQ, Publication #15-0011-EF, 2013

Cost Distribution of HAIs

Source: urotoday.com, May 31, 2011

Tracking Hospital Acquired Conditions • Nearly 200 distributed DataVision

complication and infection measures

New Midas+ Risk Model for Complications

• Acute Care, Inpatient, and Medicare populations

• Encounter-level risk adjustment

• 163 complications within 29 Midas+ complication groups

• Overall and individual complication rates

• Observed and expected values

Coding Is Important, Too • Accurate identification of POA/NPOA and accurate

coding are essential to avoid under- or over-counting – ICD-10 codes include combinations of conditions or

complications

– All parts of a combination must be present to use that code

– Combination codes take precedence over unbundled diagnoses

– Requires greater specificity by providers

A Simple Example • Pressure Ulcer:

- Site (part of the body) - Location (Right/Left) - Stage

ICD-9 ICD-10

707.03 Pressure ulcer, lower back AND 707.22 Pressure ulcer stage II

•L89.132 Pressure ulcer of right lower back, stage 2 OR •L89.142 Pressure ulcer of left lower back, stage 2 OR •L89.152 Pressure ulcer of sacral region, stage 2

MS-DRG Coding Analysis • Provides coding ratio benchmarks to help

prevent over- or under-coding • Individual and corporate-level reports

available

Analysis of Coding Trends

Things to Think About:

Evaluating Healthcare Quality “There’s a story told about a guy searching beneath a streetlight for his car keys. When asked, he admits that he lost them in a distant, dark corner of the parking lot. When asked why he isn’t looking where he lost them, he replies, ‘The light is better here.’ That story captures quality metrics in health care today. In too many cases, we’re looking at what we can easily measure—where the light is good—instead of measuring what matters most to patients. . .

“Accountability is a fraught term in health care, used too often as a cover to seize financial advantage. Every person who helps deliver health care is accountable—to patients. But no caregiver can possibly know whether the obligation to patients is being met without measuring the results of care.”

Scott Wallace, Visiting Professor at Dartmouth

“Suppose you are an auto mechanic. You are paid on the basis of how many cars you fix and what work you do. . . Now suppose you are being paid on the basis of outcome, in this case the number of breakdowns and accidents that occur in the cars you have worked on. There may be some marginal improvements you can make, but the outcomes are mostly affected by factors you can’t control, like the weather, road conditions and drivers who are young or old or DUI. The only way to protect yourself is to avoid these high-risk drivers and conditions to begin with. . . Eventually you may even close up shop because you are in an area that simply is prone to accidents. This will be an unavoidable unintended consequence in health care if we continue down this ill-advised road.”

Thomas Gustavino, MD, retired orthopedic surgeon

Pay for Quality

In Support of the ACA

For decades before the passage of the Affordable Care Act, health care costs outstripped inflation, without corresponding improvements in health care quality. Our system didn’t incentivize quality or efficiency. We paid providers for the quantity of care, not the quality of care. And we were not using technology to deliver smarter care. . . The health care law creates new Accountable Care Organizations (ACOs) that incentivize doctors and other providers to work together to provide more coordinated care to their patients. . . The health care law’s Hospital Readmissions Reduction Program reduces Medicare payments to hospitals with relatively high rates of potentially preventable readmissions to encourage them to focus on this key indicator of patient safety and care quality. . . in 2012 the nationwide rate of hospital readmissions of Medicare patients declined to about 17.8 percent. This translates to over 70,000 fewer preventable hospital readmissions.”

Kathleen Sibelius, former US Secretary of Health and Human Services

And a Disparate View “Pay-for-performance programs aim to upgrade health care quality by tailoring financial incentives for desirable behaviors. While Medicare and many private insurers are charging ahead with pay-for-performance, researchers have been unable to show that it benefits patients. Findings from the new field of behavioral economics challenge the traditional economic view that monetary reward either is the only motivator or is simply additive to intrinsic motivators such as purpose or altruism. Studies have shown that monetary rewards can undermine motivation and worsen performance on cognitively complex and intrinsically rewarding work, suggesting that pay-for-performance may backfire. . .

“Using clinical audits for financial reward or punishment, rather than a collegial and reflective effort to upgrade care, amplifies these challenges to performance measurement. Payment incentives may mutate honesty and goodwill into legal trickery, leaving the clinical data needed for real quality improvement as accurate as a tax return.”

Pay-for-Performance Toxic to Quality? Insights from Behavioral Economics, Himmelstein et. al, Intl J Health Serv, April 2014

Thanks for attending. Are there any questions? Lynn Smith, Clinical Excellence Executive, Midas+ Care Performance

Transformation Group, lynn.smith@xerox.com

Barb Schork, Midas+ DataVision Product Specialist, barbara.schork@xerox.com