translating clinical care into value based reimbursement ...€¦ · •lack of translation can...

© 2016 Nuance Communications, Inc. Al l rights reserved.

Anthony F Oliva DO MMM CPE FACPE

Vice President and Chief Medical Officer

JA Thomas and Associates a Nuance Communications Company

Translating Clinical Care into Value Based Reimbursement: CDI a Strategic Imperative

© 2016 Nuance Communications, Inc. Al l rights reserved.

Ian Morrison’s “The Second Curve”

– Theory made simple:

– You must ride the first curve -- a company's

traditional business carried out in a familiar

corporate climate -- to the all-important second

curve.

– The second curve is the future -- of new

technologies, new consumers, and new markets that

will combine to bring about a sweeping and

irrevocable alteration in the way every business

must organize and function.

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Examples of first to second curve transitions in other industries

– Mainframe computers to PC’s

– Land based telephone systems to Mobile

technology

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What does this look like for Healthcare

– First curve designed around the provider

– Professional authority confers economic

control (Starr – The Social Transformation of American

Medicine)

– Those with the knowledge controls both supply

and demand – Supply - Control entry to those with knowledge

– Education, Licensing

– Demand - Primary and secondary inducible demand

– Therefore the provider drives the first curve

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Pressures driving the second curve

– Cost can not continue to be subsidized by systems

created to pay

– Third Party Payers, Managed Care

– All an attempt to control cost from first curve

demand

– Consumers have knowledge challenging the holders

of the “Grail”

– Transparency questions previous assumptions about

quality

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Have you invested into a comprehensive clinically

based documentation improvement program?

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Key Strategy:Clinical Documentation Improvement

– A key strategy to managing the transition

between first and second curve

– Optimization of revenue in current fee for

service infrastructure while helping to define

accurately the severity of the population that

you will be responsible to care for in the

second curve.

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Lets examine the problem

– It is not a coding problem it is a

documentation problem

– Not all the providers fault

– Physicians: I document well, I don’t know

what the problem is?

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Current Clinical Documentation and Coding ProcessesLittle Operational Integration of Workflow

The Physician World The HIM / Revenue / Compliance World

EHRAnalytics

Quality

ReportingComplianceCodingDocumentation

Patient

Encounter

•The Clinical information we as physicians document is

often very different than the required documentation in

the coding and regulatory world

•Lack of translation can lead to

•Decreased Revenue

•Compliance on Denial Risk

•Poor Provider Profiling ***

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The Risk to Providers

• The only way your clinical performance is adjudicated by those outside of your medical staff is through BILLING DATA!!!

• If you do not get the billing data correct then your performance will be adjudicated incorrectly…

• This will be vital in the changing healthcare environment

– In a population based payment system those that have less than expected performance in quality and cost will be marginalized

© 2016 Nuance Communications, Inc. Al l rights reserved.

© 2016 Nuance Communications, Inc. Al l rights reserved.

“Feds to Allow Use of Medicare Data

To Rate Doctors” – USA Today 12/5/11

The federal government announced

that Medicare will now allow use of its

extensive medical claims database by

employers, insurance companies and consumer groups to produce report

cards on local doctors and hospitals.

…By analyzing masses of billing records, experts can glean such critical information as how

often a doctor has performed a particular procedure and get a general sense of problems such

as preventable complications.

Compiled in an easily understood format and released to the public, medical report cards

could become a very powerful tool for promoting quality care and reducing waste…

Announced by Marilyn Tavenner – Acting Administrator of CMS

© 2016 Nuance Communications, Inc. Al l rights reserved.

© 2016 Nuance Communications, Inc. Al l rights reserved.

Clinical impact of a successful program

© 2016 Nuance Communications, Inc. Al l rights reserved.

CareChex

– CareChex is a publically available website, www.carechex.com, developed by Comparion Analytics

– The website looks at all hospitals in the US, using MedPar data, and ranks them using 6 variables and 37 different clinical areas (Overall hospital care, Surgical Care, Ortho, Cardiology, Etc.)

– Risk adjusted mortality, severity adjusted complications, risk adjusted inpatient quality indicators (AHRQ-IQI), patient safety indicators (AHRQ-PSI), core measures (CMS), and patient satisfaction (HCAHPS)

– Full access review of the database allows review of individual indicator and specific hospital performance

– The following review show how JA Thomas partner facilities performed against the CareChex database as a whole using overall hospital care

– Further segmented review of overall mortality and inpatient quality, both of which use mortality as an endpoint, is reviewed as well using overall hospital care

© 2016 Nuance Communications, Inc. Al l rights reserved.

All JATA Hospital FFY 2014 vs CareChex Database

• Review of Mortality

• Overall Quality Rating, Overall

Mortality Rating, and Overall

Inpatient Quality Indicators

• JATA partner facilities

outperform the expected

distribution of the database

at all percentile levels10%

25%

50%

37%

69%

87%

35%

70%

94%

34%

69%

96%

36%

67%

93%

0%

20%

40%

60%

80%

100%

120%

% JATA hospitals ranktop 10%

% Jata Hospitals RankTop 25%

% Jata Hospital RankTop 50%

% JATA Hospitals at each Benchmark Level for Mortality Rating

CareChex FFY11 FFY 12 FFY 13 FFY 14

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What do JATA CDI new start hospitals look like?

• This shows that the year prior to

implementation Nuance CDI hospitals as a

group were middle performers with a wide

range from very low to very high

• For new starts in each of the most

recent available fiscal years the mean

overall performance was near the

midpoint

• Significantly, the average and range of

hospitals is fairly similar in all years meaning

that most new hospitals are falling into a

random variation similar to all hospitals in the

database.

Mean

Low

Range

High

Range

FFY 12 50.30 0.71 98.27

FFY 13 47.10 3.84 98.63

FFY 14 54.56 0.16 96.83

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Impact on outcomes comparing year prior to implementation to the year following

• For Hospitals that implemented

in FFY 12 and 13 we evaluated

the Overall Rank, Mortality

Rating, and InPatient Quality

Rating averages for all hospital

in the two years prior and one

year after implementation

• In comparing the transition year

prior to implementation vs the

year following implementation

there is significant improvement

in the year following in all

measures

-15.00%

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

20.00%

MortalityRating

InPatientQuality Rating

ExpectedMortality

FFY 2013 Implementations

Improvement Year Prior to Implementation

Improvement Year After Implementation

-20.00%

-10.00%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

Mortality Rating InPatient QualityRating

ExpectedMortality

New Implementations FFY 2012

Improvement Year Prior to Implementation

Improvement Year After Implementation

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Delay is the

Deadliest form

of Denial C. Northcote Parkinson