Quality Brand & Documentation · March 19, 2019 3 Quality Brand & Documentation Confusion Frustration Mistrust in the process The Documentation Gap

Quality Brand & Documentation

Helping your physicians look as good as they are

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• Quality is generally measured as:

• For Risk Adjusted Mortality Index (RAMI), expected is based on coding which is based on documentation

• A lack of specific or accurate documentation will result in a gap between the clinical picture known by the physician and the clinical picture based on ICD-10 coding

March 19, 2019


Observed outcome

Expected outcome

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Confusion

Frustration

Mistrust in the process

The Documentation Gap

• How do we start this work?

• How do we address the gap?

• How do we make this a priority?

• How do we know it’s working? (measure improvement)

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Our goals for today’s discussion

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Coding & CDI

Compliance

Epic

Quality

Medical Informatics

Physicians & APPs

Finance

How do we get started: you need a team

How do we start this work?How do we address the gap?How do we know it’s working?How do we make this a priority?

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Documentation occurs

Quality and Coding/CDI reviews

Opportunities presented to

monthly Physician Champion meeting

Physician Champion provides

department education

Coding tip sheets updated

Epic preference lists optimized

Learning system is ready for the “next”

patient

Clinical guideline is created

Workflow pilot developed

Biweekly Documentation

SWAT Team meetings

Quality Assurance

Monthly QBD Core Team meeting

How do we address the gap: you need a plan


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Monthly Physician Champion meetings


• Leveraging knowledge and experience from Coding & CDI experts

• Focus is on accounts that are already billed• Doesn’t impact current inpatients

• Allows for freedom of discussion

• Could use LOS>GMLOS without CC/MCC as an indicator for chart review (requires Case Management involvement)

• Champions can be MDs or lead APPs but must be engaged to be successful

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Monthly Physician Champion meetings


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Clinical guidelines and coding tip sheets


• Coordination of language

• Coding tip sheets are used to help identify indicators and understand variations in physician language

• Example: cerebral edema; “salt bomb”

• Clinical guidelines are used for conditions that benefit from added structure

• Heart failure – acute, chronic, systolic, diastolic

• Renal failure – kidney injury, renal insufficiency, ATN

• Encephalopathy – dementia, delirium, AMS

• Respiratory failure – acute, chronic, hypoxic, hypercapnic

• Can be inserted into query templates

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Clinical guidelines and coding tip sheets


• Very misunderstood• Why are you asked to agree with pathology or

radiology?

• Myth: just pick the first choice

• Myth: always say clinically undetermined

• “Queries are your friend!”• A necessary tool

• Helps physicians to use CMS coding language based on indicators

• Last opportunity to clarify your documentation

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Queries


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The Documentation Gap

Clinical guidelines

Coding tip sheets & Queries


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Tools


• Adding common diagnoses to Epic’s diagnosis preference list with specificity “built in”

• Working with Physician Champions to bring concepts back to their departments and share learnings

• Identifying opportunities where a change in workflow could have a positive impact

• How do we address queries most timely and efficiently?

• How do we leverage documentation done in the clinic?

• How do we capture most accurate and specific documentation for short LOS?

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Tools


• Difference between E&M and Inpatient coding

• Need for MEAT criteria for each diagnosis• Measure, Evaluate, Assess, Treat

• Threshold for MEAT• Generally a low threshold

• “Chronic systolic heart failure stable, will continue same dose of Lasix and ACE inhibitor”

• “Hyperlipidemia, lipid profile ordered”

• Can’t just list problems

• Using terms like suspected, likely, probable

• Impact of secondary diagnoses to expected mortality

• Importance of Present on Admission status

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Documentation education


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Quality assurance


• Bi-weekly meeting to build strategy and vision• Includes senior leadership from HIM, Epic, Compliance, Finance,

Medical Informatics, Quality

• Monthly Core Team Meeting• Larger group of stakeholders

• Focus is on updates, pushing data out

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Quality assurance


• Improvement can be very hard to measure• Case Mix Index (CMI)

• Can fluctuate due to medical/surgical mix or variations in patient acuity

• Comorbid and Major Comorbid Conditions (CC/MCC) capture rate• Only one diagnosis needed to maximize rate which undercuts importance of secondary diagnoses

• Normalized CMI (nCMI)

• Created by Cleveland Clinic to help control differences in relative weights across DRGs

• Similar to CC/MCC capture rate in that it only needs one diagnosis to maximize score

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How do we know it’s working: measurements


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• Each Diagnosis Related Group (DRG) has a relative weight assigned by CMS

• Most DRGS have 3 “levels” (MCC, CC, or neither) but some only have 2 (MCC, no MCC)

• CMI is based on this weight

• Weight variations or medical/surgical mix significant impact CMI even if there is no CC or MCC captured

Case Mix Index (CMI)

DRGs 001 and 002Heart Transplant or Implant of Heart Assist System W MCC = 29.7170Heart Transplant or Implant of Heart Assist System W/O MCC = 16.9233

DRGs 077, 078, 079Hypertensive Encephalopathy W MCC = 1.7449Hypertensive Encephalopathy W CC = 1.1544Hypertensive Encephalopathy W/O CC/MCC = 0.8529


• CC or MCC coded will result in 100% capture for that patient

• No CC or MCC coded will result in 0% capture

• Primary diagnosis generally cannot be a CC or MCC, it must be a secondary diagnosis

• Some DRGS only have two options (MCC or no MCC)

• Only one diagnosis needed to maximize rate which undercuts importance of secondary diagnoses

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Comorbid and Major Comorbid Conditions (CC/MCC) capture rate


• MCC coded results in nCMI of 100

• CC coded results in score of 1-99 depending on where relative weight of DRG with CC is between other two DRGs

• No CC or MCC coded results in nCMI of zero

• Normalizes out relative weights across DRGs

• Only one diagnosis needed to maximize rate which undercuts importance of secondary diagnoses

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Normalized CMI (nCMI)


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Month 1:

2 patients: #1 is not sick at all, #2 is very sick

• Pt #1 is healthy 25 y/o marathon runner and has no CC/MCC diagnoses

• Pt #2 is intubated due to acute respiratory failure

nCMI = 50MCC/CC capture = 50%

Month 2:



• Pt #2 is intubated due to acute respiratory failure but MD spends more time documenting 2 other CC/MCC diagnoses that are present

nCMI = 50MCC/CC capture = 50%

Lots of documentation improvement

work in between month

1 and 2

CMI would also not change

The improvement doesn’t show up in these measurements

How do we know it’s working: measurements


• Average number of CC/MCC diagnoses per discharge that are Present on Admission (POA)

• Adult inpatients only

• Excludes SNF, rehab, psych, primary diagnosis, and diagnoses with POA status other than Y/W/1

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Coding Density

Coding Density © Ochsner Health System 2019


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Coding Density

Month 1:



• Pt #1 is intubated due to acute respiratory failure

Coding Density = 0.5

Month 2:



• Pt #2 is intubated due to acute respiratory failure but MD spends more time documenting 2 other CC/MCC diagnoses that are present

Coding Density = 1.5

Lots of documentation improvement

work in between month

1 and 2



• nCMI and CC/MCC capture provide a 2D image of documentation improvement

• Both max out with 1 CC/MCC

• Both are heavily affected by acuity of patient population

• Coding Density provides 3rd dimension• Sicker patients often have more than 1 CC/MCC

• Capturing more secondary POA diagnoses generally improves expected mortality

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No

rma

lize

d C

MI (y

)

CC/MCC Percent Capture (x)

Coding Density



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How do we make this a priority: show the changing landscape


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Look as good as you are!Your inpatient documentation is your inpatient quality

• Expected mortality

• Expected complication rate

• Complications “in documentation only”

Your inpatient documentation

Inpatient coding (based on

documentation)

MEDPAR(CMS National

Database)

How do we make this a priority: show the changing landscape

Complication Review/ Hardwiring Documentation Improvement

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Complication Review

- AHRQ (Agency for Healthcare and Research Quality) has a list of diagnoses that are

interpreted as “harm” and they should never happen to patients while in our care. (Patient Safety

Indicators)

- Inclusion codes are the “harm” codes

- Exclusion codes can explain the reason for the “harm” code, and prevent an artificial complication

- We have developed a review process that ensures that if the inclusion code is present, the exclusion

code is also present, if applicable

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Complication Review

- Complication review is coordinated at the system level by a subject matter expert

- PI Coordinators and VPMA’s assist with reviews on each campus

- The subject matter expert is being trained to submit queries directly to physicians/APP’s

- There is a focus group at Jeff Highway working to reduce PSI-03 (Hospital Acquired Pressure Injuries)

- Spreadsheet with thorough review of each case is on Nursing G drive

- SOS reports are cross checked to the pressure injuries

- Mini RCA’s completed on each pressure injury

- Regular feedback at UBMD meeting

- Working with EPIC team on continuous documentation improvement

- Coding Collaborative team is working together to resolve many issues; example: rebill process

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Are queries always our friends?

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Working together, we built a better query

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QUESTIONS

Documents

Quality Brand & Documentation · March 19, 2019 3 Quality Brand & Documentation Confusion Frustration Mistrust in the process The Documentation Gap