Illinois Health Care Spring It Technology Conference

Use of IT to Strengthen Care and Agenda
Reimbursement in Challenging Times
• Challenges & Why Important (Why First)
Stepping up to the Quality Imperative – Polish your
Stars with Six Sigma and "Shine"
› We spend too much on health care
Therefore we will have change to spend less?
Our health care system is not right – therefore we will change it to
Illinois Health Care Assoc. Spring IT Conference
be more right?
Spring 2009
• Quality and Revenue Improvement

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P
Presenter: John Sheridan – P id t – eHDS
t J h Sh id President HDS › Immediate & Continuous Culture Change

| 4/6/2009 | © eHealth Data Solu
Jsheridan@ehds.biz › Risk Management – Shine your Stars!
• Lessons / Compliance
• Summary - Discussion
2

Disclosures The challenges we face!

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ealth Data  Solutio
• John Sheridan is president of a company that
assists managers using data to improve care and We have met the
organization performance. enemy and he is us.
• This presentation does not mention any specific
product or software application which is

/2009  |   © eHe
represented by Mr. Sheridan.
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Step by step – 1. Target Declines – 2. Call in
Do the right thing! Therapy – 3. Manage the Schedule for MDS
Facility: Iowa Place
Time: Q4‐08
QI/QM: 9.1 ADL decline

• Reimbursement 9 residents decline in ADL
9 residents decline in ADL
Resident Case Mix Opportunity on Residents who have declined in their ADL Score on the assessment (and addressed with

› Evidence for more care directs care and service BLACK, JESSICA
BRAXTON, JORDAN
Assessme
Therapy
Potential Payment Payment

to residents and improves Case Mix CRIMENI, JANINE
DAVIDSON, JANINE
nt
ADL RUG Case RUG Case Payment Days Days
Case
DINNOCENZO, JANE Referenc Scor Opportun Case Mix Opportun
Using RUGs to improve Quality Measures DUNN, JANE
Resident Name SSN
e e
Code Mix Code Mix Source
ity Points ity
Mix
Points
– Evaluate residents who decline in ADL and Mobility Scores ENGLE, JANINE
EVANKO, JANE
Date
Inde
x
Index Q4‐2008 Added Q1‐2008

– ADL decline, mobility worsening – are the 5-Star key measures FLEISSNER, JESSICA
BLACK, JESSICA
349‐11‐ 10/23/20
9999 08 15 RAC 1.28 Medicare

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– Evaluate potential for restorative care
p 349‐45‐ 11/14/20


BRAXTON, JORDAN
BRAXTON JORDAN 9999 08 4 CA1 0 92 RAA 1 040 M di id
0.92 1.040 Medicaid 47 5.64
5 64 45 5.40
5 40

• Quality and Integrity CRIMENI, JANINE
349‐70‐ 11/11/20
9999 08 17 CC2 1.49 RAD 1.62 Medicaid 50 6.5 42 5.46

› Get Ready for Medicare and Medicaid Audit
349‐90‐ 12/14/20
DAVIDSON, JANINE 9999 08 10 IB2 0.85 RAB 1.2 Medicaid 17 5.95 75 26.25
350‐18‐ 10/8/200
DINNOCENZO, JANE 9999 8 12 PD1 0.84 RAB 1.2 Medicaid 84 30.24 8 2.88

All data are real examples that have been de-identified.
5 6

Case Study on IT Evaluation for Optimum Why Use IT?

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Therapy and Restorative Care Opportunity F-287 Automated Data Processing Requirement

ealth Data  Solutio
CMI 34 Interval Comparison ‐ Minnesota Place
RUG
(1) All Payer Q3‐ (2) All P
(1) All P Q3 (2) All Payer Q4‐
Q4 Q3 ‐
Q3 Q4 ‐
Q4 • Intent F 287
F-287
Group
08 08
CMI Days CMI Points Days CMI Points
Potential
1.022
Potential
1.046 › …to enable a facility to better monitor a
All 6,920 6,873.48 5,954 6,050.50
7,071.06 6,230.11
resident’s decline and progress over time.
0.99 1.02 0.0286 0.0302 Computer-aided data analysis facilitates a more
Restorative Care 148.90 107.77
efficient, comprehensive and sophisticated

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Therapy 48.68 71.84
review of health data.
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Total
› Th primary purpose of maintaining th
The i f i t i i the

Opportunity 197.58 179.61

assessment data is so a facility can monitor
Evaluate Residents and apply restorative care to maintain status and to assist improvement. resident progress over time. The information
Where declines have occurred, evaluate and apply therapy (Parts A or B) where appropriate.
should be readily available at all times.

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CMS has 8 initiatives for Healthcare
Recovery Audit Contract Expansion
financial integrity -
• CMS p g
programs related to health care financial integrity: g y
› The Medicare Accountability Contractor (MAC) conversion for payers
› The Zone Program Integrity Contractor (ZPIC)
› The NCCI (National Correct Coding Initiative)
› The Medicaid Integrity Contractor (MIC) - Medicaid Payment Integrity
› PROBES - After data analysis, Contractors must verify if billing
problems exist through probe reviews.

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› PERM – Payment Error Rate Measurement – states participate every

three years
› CERTs – Comprehensive Error Rate Testing
Inpatient Hospital – 85 percent ($823.3 million) RAC - Fees › The RAC – Medicare Payments from 10/1/2007 forward – Automatic
Inpatient Rehab – 6 percent ($59.7 million) Region A –12.45 Percent and Complex reviews for appropriate care and correct coding
Outpatient Hospital – 4 percent ($44 million) Region B – 12.50 Percent
Physicians – 2 percent ($19.9 million) Region C – 9 Percent
SNFs – 2 percent ($16.3 million) Region D – 9.49 Percent
DME – 1 percent ($6.3 million)
9 10
Ambulance/Lab/Other – < 1 percent ($5.4 million)

Prevent/Reduce Recoupment

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of Medicare and Medicaid Dollars UB-04 / MDS Exceptions [RAC Recovery Audit Contract]

ealth Data  Solutio
Coun
• CMS estimates 10.4 billion in Medicare errors and
UB‐04 ‐ MDS Exception Report
t
51 Principal Diagnosis does not have a matching ICD9 code or explicit diagnosis field not set on corresponding MDSs
a federal 18.0 billion in Medicaid errors. 43
33
Excluded service
No admission MDS corresponding to admission date
21 RUG in claim does not match RUG in corresponding MDS
19 Therapy level for patient exceeds therapy cap
• Check your electronic records of bills (UB-04) with 16
16
Rehab therapy RUG but no therapy charges
Non‐rehab RUGs but with therapy charges
those of clinical assessments (MDS). 14
13
Claim type and dates inconsistent with corresponding MDSs
Unjustified automatic exception modifier

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13 No qualifying hospital stay before admission
12 Speech therapy but no dysphagia or other allowed diagnosis
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• Checks whether Principal and Admitting 11 Therapies on same day may indicate a need for a procedure code modifier

10 No corresponding MDSs for claim
Diagnoses are supported by the care documented 5
4
Admission date is greater than 30 days from qualifying hospital stay
Missing occurrence entries for speech therapy
and present in the record. 3
3
Therapy cap modifier missing after therapy cap reached
Missing occurrence entries for physical therapy
› Prevent/reduce RAC recoupment of Medicare 2
2
Missing value code for physical therapy
Missing value code for speech therapy
and Medicaid $. 1
1
Missing occurrence entries for occupational therapy
Outpatient claim dates overlap with part A claim dates without required condition code

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1 Invalid ICD9 code(s)

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Challenges and Obstacles The Steps for Buy-In

• Too much Data – What can we do? • Recognition of a need
• It’s just the data!
• Too little time • Discussion about the need
• We need to do what is in front of us now
• I only know what I know • Find a solution to the need
• Excellence demands growth

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› use of new technology and new methods is challenging
› growing pains may cause us to seek relief • Support implementation of the solutions
no pain, no gain to resolve the need
• Can-do spirit!

13 14

Information, Technology and Management National Quality Forum – A National Consensus

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www.qualityforum.org

ealth Data  Solutio
• Serious Reportable Events - Transparency & accountability are critical in
• Source of Data reducing medical errors (data in the IT systems)
• Management of a Discipline › “Tens of thousands of lives are forever changed each year as a result of
healthcare errors. There is a critical need to enhance health system capacity,
› Concentrated area of knowledge about so that all patients will receive care that is safe and effective.”
- NQF President and CEO Janet Corrigan
tools and tool sets
› Backup and redundancy • There are 28 Events – CMS plans to recoup $ for "Never Events"

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›
› Access The SRE list includes:

Injuries caused by care management rather than the underlying disease
› Timeliness – “Fall & Fracture” or “High Risk Pressure Ulcer”
Errors that occur from failure to follow standard care or institutional practices and
• Evaluation and Analysis policies

› A discipline of all management ›
›
The events are largely preventable, but also very serious.
The errors are of concern to the public and healthcare providers and warrant
careful investigation that should be targeted for mandatory public reporting.

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15 16

2008/9 Hospitals are Not Paid for Some SREs /
NQF is the Basis for the QMs and QI/QMs
Never Events (Pay for Performance) – When will Iowa emerge?
• 2003: Minnesota is the first state to require reporting entire NQF list.
› Now required b CA CT IL IN MA NJ OR VT WA and WY
N i d by CA, CT, IL, IN, MA, NJ, OR, VT, WA, d WY.
› Other states are considering implementation of the SREs.
• October 1, 2008: CMS reduced payment to treat a list of
complications CMS deems preventable with good care.
› Many of these complications are included on NQF’s SREs list.
› The Medicare payment provision encourages the adoption of
evidence-based patient safety practices aimed at preventing hospital

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acquired conditions.
conditions


• The CMS plan
› Respond to unintended negative consequences with appropriate
corrections and interventions.
› Extend the SRE Medicare and Medicaid payment reduction to SNFs.
› OIG’s work plan for 2009 is laying the foundation. This process produced the QMs
17 18

Summary of Why SNF Health Care – One Framework

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ealth Data  Solutio
Admin./ED’s Should Work to Improve Quality & Assure Reimbursement
• Use of Information Technology
1. The Quality Committee recommends approval of written policy on quality and quality
improvement that is approved by the organization’s team and then effectively
communicated to all staff and all associated providers.
› A logical management system – feedback loop 2. The Quality Committee sets the agenda for the facility’s discussion on quality.
of analytics 3. Each Admin/ED has the responsibility to assure that quality receives appropriate time for
discussion not only at QA Meetings, but in all activities regarding care.
4. The Admin/ED oversight at her/his facility Quality Committee includes measures for

/2009  |   © eHe
› Source of data for the analytics quality and resident/patient safety as part of the performance evaluation of the ED, RVP
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and Division VP.

5. The Admin/ED must act with the Quality Committee to improve the quality literacy of the
facility staff and volunteers (IT is the source of data)
› Tools and tool sets to express the analysis 6. The Quality Committee aligns the mandate for quality improvement in the organization
and recommends how this mandate is measured and enforced.

Board Engagement in Quality: Findings of a Survey of Hospital and System Leaders - H. Joanna Jiang, PhD,; Carlin
Lockee,; Karma Bass, FAHE; and Irene Fraser,PhD; Journal of Healthcare Management 53:2 March/April l 2008

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Suggested QA Process Overview - (IT Dashboard)
1. Each Department Presents Their Own QA Information Outcomes Measurement
2. HSKP – Upkeep of Cleaning Schedules, etc. (automated) (K-Tags)
a. Laundry – temperature and maintenance logs for laundry equipment
b. Maintenance – review of performance for water temperatures, fire & safety systems, call lights,
Outcomes need to be reviewed in the context of a
preventative maintenance on specialized equipment
t ti i t i li d i t continuous monitoring and improvement process.
ti it i di t
c. Dietary – audits of food temperatures, dish-machine temperatures, & sanitation levels
d. Activities – review of participation (F-249)
3. Customer Service Review This approach requires an organization to follow
a. Review results of satisfaction surveys – online presentation – look at history through IT five essential steps:
b. Discussion of plan for focused resolution of any issues
1) identify important aspects of care,
4. Grievance/Concern Form Review
2) implement indicators of performance,
a. Review summary of concern forms received in last month – trend analysis, etc.

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b. Discussion of plan… 3) collect and analyze data,


5. Loss Control Review – examine recent losses – plan review and development 4) isolate common and special causes, and
–(IT reports to insurer) 5) develop and implement solutions that improve either a process
6. Infection Control – review of data from last month(s). Analyze distribution map. (IT) or an outcome.
7. Incident Report – online review of IT data Fall analysis – use projector
8. QI/QM Review – IT data – use projector and review control charts – Coordinate Care Plans
Donabedian A. Explorations in quality assessment and monitoring. Volume I: the definition of quality and
9. Survey/Complaint – review issues occurring in last month. approaches to its assessment. Ann Arbor, Mich.: Health Administration Press.
10. Medical Records – review select audits completed in last month (IT based)
21 22

Identify QIs-73.5% of Measures Improved Identify - QI/QMs

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Long Term Care Aggregate Quality of Care Performance
QI/QM Residents Population 2007 2006
Accidents
1.1 Fractures 44 1,109 4.00% 4.90%
that are…

ealth Data  Solutio
1.2 Falls 327 1,155 28.30% 26.30%
Behavior/Emotional Patterns
2.1 Depression 516 1,170 44.10% 47.10%
2.2 Affect on others 330 1,150 28.70% 31.60%
2.2‐Hi Affect on others high risk 308 968 31.80% 35.70%
2.2‐Lo Affect on others low risk 25 215 11.60% 9.20%
2.3 Depression w/o therapy
23D i / h 129 1,155 11.20%
1 155 11 20% 13.80%
13 80%

Directly Related to the Survey F-Tags
Clinical Management
3.1 Medications 896 1,155 77.60% 79.30%
Cognitive Patterns
4.1 Cognitive impairment 66 270 24.40% 27.70%
Elimination/Incontinence

F-Tag Standard QI/QM
5.1 Incontinence low risk 462 864 53.50% 51.70%
5.2 Catheter 112 1,155 9.70% 13.20%
5.3 Incontinence w/o plan 224 613 36.50% 42.60%
5.4 Impaction 0 1,155 0.00% 0.10%

248 Activities Little or No Activity
Infection Control
6.1 Urinary tract infection 198 1,155 17.10% 19.90%
Nutrition/Eating

314
7.1 Weight loss 198 1,089 18.20% 19.20%
7.2 Tube feeding
7.3 Dehydration
83
1
1,155 7.20%
1,155 0.10%
7.10%
0.00% Pressure Ulcers High Risk Pressure Ulcers

/2009  |   © eHe
Pain Management
8.1 Pain 92 1,155 8.00% 11.90%

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Prevent Accidents Falls (Last 30 Days)
Physical Functioning
9.1 ADL decline 299 1,066 28.00% 31.50%
9.2 Bed or chair 69 1,150 6.00%
, 6.00%


325
9.3 Mobility worse 259 848 30.50% 32.80%
9.4 ROM decline
Psychotropic Drug Use
10.1 Psychotropic drug use
163

183
1,146 14.20%

1,050 17.40%
17.50%

18.40%
Nutrition Weight Loss (5% - 30 Days)
10.1‐Hi Psychotropic drug use high

329
risk 67 252 26.60% 33.10%
10.1‐Lo Psychotropic drug use low
risk 140 920 15.20% 14.50%
Unnecessary Drugs 9+ Medications
10.2 Antianxiety/hypnotic use 275 1,050 26.20% 27.30%
10.3 Frequent hypnotic 83 1,155 7.20% 8.40%
Quality of Life
11.1 Physical restraints 15 1,155 1.30% 3.00%
11.2 Little or no activity 110 1,150 9.60% 10.20%
Skin Care
12.1 Pressure ulcers high risk 160 847 18.90% 21.10%
12.2 Pressure ulcers low risk 9 429 2.10% 5.30%

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Post‐Acute Care
13.1 Short‐stay delirium 29 887 3.30% 3.30%
13.2 Short‐stay pain 130 895 14.50% 16.90%
13.3 Short‐stay pressure ulcers 153 808 18.90% 18.70%
23 24

QI/QMs and F-Tag 323 / F-324 QI/QMs and F-Tag 314

Level of Harm Residents Affected Level of Harm Residents Affected
Inspectors Determined: (Least>Most) (Few>Some>Many) Inspectors Determined: (Least>Most) (Few>Some>Many)
3=Actual Harm Few Give residents proper 2=Minimal harm Few
Make sure each resident is
treatment to prevent or potential for
being watched and has Facility 1.8%
new bed (pressure) actual harm
assistance devices when Fx sores or heal existing
needed: prevent accidents. USA 1.9% sores.
6%

Adequate supervision Prevent and/or heal

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13.60%
pressure ulcers

Assistance devices to

Facility 11.8%
11 8%
Falls
prevent accidents
NC State Coach Valvano
USA 12.9% 12.90%
was cognizant of the fact
that today's success is
0.0% 3.5% 7.0% 10.5% 14.0% 17.5% tomorrow's failure.
0.00% 2.00% 4.00% 6.00% 8.00% 10.00%12.00%14.00%
Q4 – 2007 Fractures & Falls
Q4-07 High Risk Pressure Ulcers
25 26

Using and Interpreting SPC Charts* – A First Step
Statistical Process Control Charts Key Terms

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to Cost Effective Continuous Improvement

ealth Data  Solutio
• Using Statistical Process Control to facilitate Variation: amount, rate, extent, or degree of change*
, , , g g
quality improvement
Standard Deviation: the typical distance from
• Correctly identify quality deficiencies the mean (average)
Benchmark against state norm, other facilities, In a “normal distribution,” 68% of scores will fall within 1
standard deviation of the mean.
and your historical data.

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95% will fall within 2 standard deviations
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Create trend and SPC charts to measure change 99 73% will fall within 3 standard deviations
99.73%

over time. 99.9999998% will fall within 6σ (standard deviations)
Inclusive of the Upper and Lower “control” limits
Use these tools to empower and validate your
quality committee.
* "variation." Dictionary.com Unabridged (v 1.1). Random House, Inc. 23 Mar. 2007. <Dictionary.com
http://dictionary.reference.com/browse/variation>.

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Page 77
*Using statistics to identify and target quality improvement
27 28

Hypothetical Example of “Your” Data
• Incontinence w/o Plan Evaluating Quality Step by Step Using SPC
› Strategy: Red – Needs
Improvement
› 7.9% gap (UPB-LPB)
› 14 periods above national
norm 1.
1 Review QI/QMs monthly
› 0 periods equal to or below

›
national norm
8 occasions special cause
2. Group and categorize the QI/QMs
› Note: Graph starts at 40%
3. Calculate from the previous month
• Pressure Ulcers High 4. Review trends vs. month-to-month QI/QMs
Risk
› Strategy: Yellow 5. Review the SPC chart to determine:

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› 3.5% gap
g p
Is any change normal variation, or
an ariation

› 0 periods above national norm
› 14 periods equal to or below
national norm Is there a process problem?
› 2 occasions special cause
› Note: Graph starts at 8% Is quality improving?
› Extra-Note: pressure ulcer Are the interventions working?
SOW goal = 6.0% - therefore
with respect to where we
“should” be we are RED

29 30

Statistical Process Control SPC Key Terms, continued

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ealth Data  Solutio
SPC can tell you whether the variation in your QI/QM SPC presents a Dynamic Display
scores is due to chance or because of a special cause or Variation in a process is measured by asking:
Is it “normal” or the result of a “special” cause?
meaningful changes over time.* Does the process need to be re-evaluated?
Common Cause Variation – random, due to regular, natural, or
Originally developed for the manufacturing field, SPC has ordinary causes. Common Cause Variation is expected to occur.
Example: acuity of residents.
also been effectively applied to healthcare. Special Cause Variation – due to irregular or unnatural causes.

/2009  |   © eHe
When special causes are present, a process will be “out of control”
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or “unstable”. E ample resident falls
unstable Example:

Process = “controlled”: outcomes can be predicted within LIMITS

= ? Process ≠ “controlled”: the SPC chart will tell you WHEN to assist
and explain WHY.

The risk of “tampering” with a controlled process must be balanced
against the risk of “under controlling”…

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Page 88
*JCAHO and ISO require SPC charts as proof of QA/QI 31 32

SPC Key Terms, Continued.
• Data Points: plotted over time Example: Incontinence
• Mean: average of data points over time
• Upper Control Limit (UCL): + 3 standard deviations from the mean In 2006, an average of 60.3% residents triggered 5.1 each month
• Lower Control Limit (LCL): – 3 standard deviations from the mean
Percent of Residents with 5.1 per month
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
% 54 52 45 88 54 50 57 48 71 70 60 68
with
LRI

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4/6/2009
33 34

Example 1
Trends and SPC

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ealth Data  Solutio
A trend is also an indicator of a special cause.
Trend: an unusually long series of consecutive increases
or decreases in the data.
Many people infer trends that are not really present
because the consecutive data points are not long enough
to be statistically significant.

/2009  |   © eHe
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The
Th consecutive “ ” of data points must be, minimally
ti “run” f d t i t tb

i i ll
between 5-7, depending on the size of the data base.
Points above / below the average
• Is this process stable?
Points in an increasing or decreasing trend
• Is this level of incontinence acceptable?
Points above / below state or national norm

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Page 99
35 36

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