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Utilizing Metrics and Benchmarking to
Persuade for Neurosurgical Quality &
Safety FTEs
Patricia D. Miller, MHSA, BLA, CMPE
Agenda
• Introduction & Background
• Disclosures
– I have no disclosures or financial interests related to this presentation.
• Topic Discussion
– Identify a Need
– Choose the Right Metric
– Find Benchmarking Data
– Persuade for Approvals & Recruitment
– Identify Funding Sources
– Questions
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Identifying a Need
8/10/2019 4Raft Photo- This Photo by Unknown Author is licensed under CC BY
• What needs are not being met?
– Revenue Cycle Process
• What area does the need cover?
– Inpatient, Outpatient, Non-Clinical
• What positions/roles would help fill the gap?
– Scope
– Job duties
– Credentials
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Identifying a Need
Choosing the Right Metric
• All Positions
– FTEs
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THE UNIVERSITY OF KANSAS HEALTH SYSTEM
DEPARTMENT STAFFING ANALYSIS TOOL - INPUT SECTION
Annual Work RVUs 60,000
Staff Name Position Title MGMA Staffing Group FTE Level
Employee A Scheduler Front Office Support Staff 1.00 Employee P APRN 1.00
Employee B Admin Assistant Front Office Support Staff 1.00 Employee Q APRN 1.00
Employee C Admin Assistant Front Office Support Staff 1.00 Employee R APRN 1.00
Employee D Front Desk/CheckoutFront Office Support Staff 1.00
Employee E Front Desk/CheckoutFront Office Support Staff 1.00
Employee F Admin Assistant Front Office Support Staff 0.50
Employee G Admin Assistant Front Office Support Staff 1.00
Employee H Admin Assistant Front Office Support Staff 1.00
Employee I Biller/Coder Business Operations Support Staff 1.00
Employee J Biller/Coder Business Operations Support Staff 1.00
Employee K RN Clinical Support Staff 0.80
Employee L RN Clinical Support Staff 1.00
Employee M Practice Manager Business Operations Support Staff 1.00
Employee N Medical Assistant Clinical Support Staff 1.00
Employee O Biller/Coder Business Operations Support Staff 1.00
Choosing the Right Metric
• Inpatient
– Staffing Ratios
– Average daily census
– Additional Considerations
– Disease Complexity
– ICU versus Step-down or Floor patient
– Resident obligations
– Facility Identified Initiatives (bed management, avoiding diversion, throughput)
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Choosing the Right Metric
• Hybrid position
– Inpatient > Outpatient
• Re-admission rate
• LACE Score
– Additional factors
• Nurse to patient ratios
• Credentials/licensure needed
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MR#____________ UNIT____________
DOS____________ LACE Index Scoring Tool for Risk Assessment of Hospital Readmission
Step 1. Length of Stay Length of stay (including day of admission and discharge): _________ days
Length of stay (days) Score (circle as appropriate)
1 1
2 2
3 3
4-6 4
7-13 5
14 or more 7
Step 2. Acuity of Admission Was the patient admitted to hospital via the emergency department?
If yes, enter “3” in Box A, otherwise enter “0” in Box A
Step 3. Comorbidities
Condition (definitions and notes on reverse)
Score (circle as appropriate)
If the TOTAL score is between 0 and 3 enter the score into Box C. If the score is 4 or higher, enter 5
into Box C
Previous myocardial infarction +1
Cerebrovascular disease +1
Peripheral vascular disease +1
Diabetes without complications +1
Congestive heart failure +2
Diabetes with end organ damage +2
Chronic pulmonary disease +2
Mild liver or renal disease +2
Any tumor (including lymphoma or leukemia)
+2
Dementia +3
Connective tissue disease +3
AIDS +4
Moderate or severe liver or renal disease +4
Metastatic solid tumor +6
TOTAL
Step 4. Emergency department visits How many times has the patient visited an emergency department in the six months
prior to admission (not including the emergency department visit immediately preceding the current admission)? ___________
Enter this number or 4 (whichever is smaller) in Box E Add numbers in Box L, Box A, Box C, Box E to generate LACE score and enter into box below.
LACE Score Risk of Readmission: > 10 High Risk
A
L
E
LACE
C
Choosing the Right Metric
• Non-Clinical, administrative position– Clinic Volume
– Call Volume
– Multidisciplinary coordination (ENT-N/S, N/S-Neuro-Onc, TBI)
– System identified initiatives- patient access,
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Choosing the Right Metric
• Non-Clinical, administrative position
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Finding Benchmarking Data
National
• Survey Data
• MGMA• https://data.mgma.com/DataDive/rdPage.aspx?rdReport=Basic.Comp&DatasetId=95&inpBucket=&inpChapter=&inpCut=&inpMeasures=&inp
Metric=-
1&inpQtile=&inpRegion=&inpRollup=SpecCompProvA&inpSort=&inpSpec=709&inpSubVar1=ALLCATS&inpSubVar2=ALLCATS&rbSubVar2
=1&rdRnd=69741
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Finding Benchmarking Data• Survey Data
• Industry Specific Survey Data
• NERVES• https://nerves.memberclicks.net/index.php?option=com_content&view=article&id=40:socio-economic-survey-&catid=20:site-content&Itemid=138
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Finding Benchmarking Data
• ANA
• Nursing to Patient ratio
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Finding Benchmarking Data
• Administrative Data
MGMA Encounter information
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Finding Benchmarking Data
• Shiftboard scheduling software
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Finding Benchmarking Data
• Vizient
• Mortality Index
• Re-Admissions
• Average Length of Stay
• Direct Cost
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Finding Benchmarking Data
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THE UNIVERSITY OF KANSAS HEALTH SYSTEM
DEPARTMENT STAFFING ANALYSIS TOOL - INPUT SECTION
Annual Work RVUs 60,000
Staff Name Position Title MGMA Staffing Group FTE Level
Employee A Scheduler Front Office Support Staff 1.00 Employee P APRN 1.00
Employee B Admin Assistant Front Office Support Staff 1.00 Employee Q APRN 1.00
Employee C Admin Assistant Front Office Support Staff 1.00 Employee R APRN 1.00
Employee D Front Desk/CheckoutFront Office Support Staff 1.00
Employee E Front Desk/CheckoutFront Office Support Staff 1.00
Employee F Admin Assistant Front Office Support Staff 0.50
Employee G Admin Assistant Front Office Support Staff 1.00
Employee H Admin Assistant Front Office Support Staff 1.00
Employee I Biller/Coder Business Operations Support Staff 1.00
Employee J Biller/Coder Business Operations Support Staff 1.00
Employee K RN Clinical Support Staff 0.80
Employee L RN Clinical Support Staff 1.00
Employee M Practice Manager Business Operations Support Staff 1.00
Employee N Medical Assistant Clinical Support Staff 1.00
Employee O Biller/Coder Business Operations Support Staff 1.00
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Specialty Type Surgical Single Specialties
MGMA Staffing Group Department FTEs
Current Staffing Levels per
10,000 WRVUs
Current Staffing per 10,000
WRVUs Percentile
Median Staffing Levels per
10,000 WRVUs
Variance to
Median
Business Operations Support Staff 4 0.666666667 46 0.74 -0.07
Front Office Support Staff 7.5 1.25 30 1.97 -0.72
Clinical Support Staff 2.8 0.466666667 11 1.27 -0.80
Ancillary Support Staff 0 0 10 0.53 -0.53
THE UNIVERSITY OF KANSAS HEALTH SYSTEM
DEPARTMENT STAFFING ANALYSIS TOOL
0.666666667
1.25
0.466666667
0
0.74
1.97
1.27
0.53
46
30
11 10
0
5
10
15
20
25
30
35
40
45
50
0
0.5
1
1.5
2
2.5
Business Operations Support Staff Front Office Support Staff Clinical Support Staff Ancillary Support Staff
MG
MA
Perc
en
tile
Sta
ffin
g L
ev
el
Per
10,0
00 W
RV
Us
Current Staffing Levels per 10,000 WRVUs Median Staffing Levels per 10,000 WRVUs Current Staffing per 10,000 WRVUs Percentile
Successful Approvals & Recruitment
• Bring the Data
- What to bring?
- Be well positioned to argue the data points
Funding Sources
• Align Funds with Position Requested
– Operational Budget
• Re-sourcing available FTEs in a new way
• Shared resources/Split costs with another department/division
– University Dollars or State appropriated funds
– Grants & Clinical Trials
– Philanthropic Dollars
Thinking Outside the Box
• Job title and duties don’t exist?
– No Problem.
– Create one.
Summary
• Identify a Need
• Determine type of position
• Evaluate duties & requirements
• Gather operational data
• Record Metrics
• Find Benchmarks
• Align with Funding Sources
• Bring the Data
• Create Positions if Necessary
Questions?
