Transcript From Simple to Sophisticated

From Simple to Sophisticated:
Using Event and Claims
Data to Drive Action
Tim C. Over
Senior Vice President, Specialty Operations
Ann D. Gaffey, RN, MSN, CPHRM, DFASHRM
SVP, Healthcare Risk Management and Patient Safety
Sedgwick
Too much?
Too little?
No idea what to
do with it?
Waste of time?
SIX CORE DATA BUILDING BLOCKS TO
CONSIDER…
…as you contemplate use of data
• Data governance
• Data acquisition
• Data sharing
• Integration
• Standardization
• Analytics
CSC White Paper: Transforming Healthcare Through Better Use of Data (2012)
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DATA – WHERE DO YOU EVEN BEGIN?
•
•
•
•
•
Event Data
Claims Data
Patient Satisfaction Data
Complaint Data
Billing Data
• Industry Benchmarks
• Newer Sources of Data
o Medicare Payment Data
o Sunshine Act Data
CAN YOU “MINE” YOUR DATA?
• Event data
– Medication Event
• Improper Order (Patient Allergic)
– Metadata in EHR
» Provider ignored an alert about a drug allergy
• Claims data
– Frequency of claims related to patient falls
• Facility with highest frequency
– Event location
» ??????
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ONE FACILITY’S JOURNEY – CLAIMS DATA
Data Analytics Summary - Loss Control Characteristics
• The loss leader in both claim
frequency and severity
(indemnity/expense dollars paid)
are events related to patient falls.
• Dollars paid on patient fall Claims
account for 47% of the total
severity.
• Most patient falls occurred at
Facility E, however the cost-driver
patient fall Claims originated from
Facility A.
Facility
Frequency
Severity
A
25
$834,455
B
28
$809,688
C
26
$585,951
D
16
$501,939
E
35
$326,077
TOTAL
130
$3,058,110
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Total Indemnity and Expense $ Paid
Frequency and Severity of Patient Fall Claims by Facility
$900,000
40
$800,000
35
$700,000
30
$600,000
25
$500,000
20
$400,000
15
$300,000
10
$200,000
$100,000
5
$0
0
A
B
C
D
E
ONE FACILITY’S JOURNEY – CLAIMS DATA
Data Analytics Summary - Loss Control Characteristics
The top injuries related to patient and visitor falls are:
Injury Type
Frequency
Severity
Fracture(s)
252
$6,468,661
Hematoma
28
$2,166,128
Laceration
25
$276,954
Abrasion
15
$103,926
Contusion
12
$16,000
TOTAL
332
$9,031,669
Top injuries related to patient and visitor falls by
Frequency and Severity
300
$7,000,000
252
$6,000,000
250
$5,000,000
200
$4,000,000
150
$3,000,000
100
$2,000,000
50
28
$1,000,000
25
15
12
0
$0
Fracture(s)
Hematoma
Laceration
Frequency
Abrasion
Contusion
Severity
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DOES THIS DATA HELP ME?
…OR DOES THIS HELP ME MORE?
Breakdown of Fall Events by Category and Policy Period
160
140
Number of Falls
120
100
80
60
40
20
0
Visitor
2003
0
2004
4
2005
27
2006
44
2007
57
2008
69
2009
55
2010
60
2011
83
2012
57
Patient
3
16
35
71
69
78
62
87
57
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HOUSTON, WE HAVE A PROBLEM!
Facilities with the highest frequency of patient/visitor fall events
2003-2013 Policy Periods
45
40
35
Number of falls
30
25
20
15
10
5
0
Patient
A
25
B
13
C
12
D
26
E
10
F
35
G
28
H
9
I
10
J
28
K
8
Visitor
31
40
36
20
29
4
7
22
20
1
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HOUSTON, WE HAVE A PROBLEM!
WHAT IS THIS TELLING US?
• CLAIMS DATA SHOWING
– Significant frequency with falls
– Spending lots of $$ on something that shouldn’t happen
so often
– It’s not just patients
BUT WE HAVE AN EXCELLENT FALL PREVENTION PROGRAM!
– Tons of data
– Lots of people looking at it
– What are we missing?
AN OUTSIDE SET OF EYES




The “best” facilities
The “worst” facilities
Is it REALLY best practices?
If yes, then what continues to be the
problem?
 Great data available
 Right idea, wrong approach?
A DREAM COME TRUE!
SLICING AND DICING
–
–
–
–
Data collection was detailed
Data was centralized
Data was analyzed…monthly
Date was NOT analyzed with a
longitudinal view of event
experience over time
– New analysis drove more
meaningful change
TAKING ADVANTAGE OF VOLUMES OF DATA
TAKING ADVANTAGE OF VOLUMES OF DATA
CAN DATA BE USED TO DRIVE CHANGE?
• Consider the urgency of your “problem”
– Is there a high potential for patient harm,
sooner rather than later?
– Is the intervention proposed expensive?
– Can it be tested easily?
– Can you develop metrics to measure
outcomes?
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IS IT POSSIBLE TO DEMONSTRATE
SUCCESS?
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DEMONSTRATING THE INTERVENTIONS WERE SUCCESSFUL
Frequency of Pressure Ulcers
Comparison of Actual Frequency vs. Forecast
70
60
# of Pressure Ulcers
50
40
30
20
10
0
Actual
Forecast
2001
21
2002
23
2003
3
2004
17
2005
26
2006
37
2007
64
2008
51
2009
31
2010
52
2011
26
2012
20
2013*
18
21
23
3
17
26
37
64
51
31
52
26
20
24
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ANOTHER SAMPLE METRIC
Incident Date to Report to Risk Management Date
A
B
C
D
E
F
G
H
I
L
K
L
M
N
O
P
R
S
T
U
V
W
X
Y
Z
AA
28
28
34
41
44
50
61
66
68
75
83
102
109
115
115
117
121
128
131
137
139
146
172
227
272
324
0
50
100
150
200
Number of Days
250
300
350
WHAT ABOUT BENCHMARKING?
Anupam, B., Seabury, S., Lakdawall, D.,and Chandra, A.
(2011). Malpractice Risk According to Medical Specialty.
New England Journal of Medicine, 365(7), 629-636
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USING DATA TO DRIVE ACTION
• Evaluate the availability, access and integrity of your data
• Consider what you ultimately want to measure when setting
up systems
• Use a system that allows for ease of data input and robust
analysis
• Ensure you have the right team in place to analyze the data
• Recognize there is more than one way to look at what’s in
front of you
• Be open to implementing small changes, and using rapid cycle
improvement opportunities to test and revise
Questions and Comments
Thank you!
Tim C. Over
SVP, Specialty Operations
[email protected]
Ann D. Gaffey
SVP, Healthcare Risk Management and Patient Safety
[email protected]
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