Information
Management
Chapter 5
2
INFORMATION
MANAGEMENT PROCESS
• Identify Current Available Data Sources
• Identify Critical Information Needs
• Define Data Elements
• Determine Data Collection Plan
• Acquire/Collect Data
• Aggregate & Display Data
3
INFORMATION
MANAGEMENT PROCESS
• Analyze Data
• Interpret Data / Information
• Act on Information
• Report Data/Information/Knowledge/
Decision
• Collect More Data to Monitor/Analyze
the Decision.
INFORMATION
4
RESOURCES
• Access
o Authority, security, etc.
• Availability
o In the form/format needed
• Timeliness
o How close to real time is data collected
and/downloaded
• Internal/External
DATA INVENTORY
5
PROCESS
• Where data is collected in organization
• Collection Steps
o What being collected, from where
• Analysis Steps
• Reason for Collecting this Data
o Being used?
o Duplicate Information?
6
Electronic Medical Record /
Information Technology
• Institute of Medicine (IOM) started the
movement in Aug 2003
• Four Goals
o Inform clinical practice
o Interconnect clinicians
o Personalize care
o Improve population health
7
Other IT Topics
• Impact of Health Information Management
on Quality
o ICD-10
o Coding
o Meaningful use
8
CONFIDENTIALITY
IN HEALTHCARE
• Confidential information – information that
one keeps or entrusts to another with the
understanding it will be kept private and
not shared
• Protected/Privileged Information –
information that can not be obtained by
others or used in a court of law
CONFIDENTIALITY
IN HEALTHCARE
9
• HIPAA
• Access
o Without Written Authorization of Patient
o With Written Authorization of Patient
• Security
o Sequestered records
• Consent - Release of Medical Information
10
Committee Meeting Organization
• Meeting Date
• Agenda
• Packet
• Meeting
• Minutes
• Reminders
11
Epidemiological Contributions to QM
• Definition – The study of populations
•
•
•
•
Specifying good practice
Specifying good system design
Developing measurement tools
Developing and conducting measurement
and assessment ( monitoring)
12
Epidemiological Concepts & Methods
• Concepts and Methods
 Causality
Cause & Effect
 Frequency
Rate
Proportion
Ratio
13
Epidemiological Concepts
and Methods
• Morbidity – rate of disease or proportion of
diseased persons in a given location
Incidence – rate during specific time
period
Prevalence – proportion in a defined
population at one point in time
• Mortality – proportion
of deaths in a
population within a
time range
14
Data Definition And Collection
• Sensitivity – inclusion of all appropriate
items or descriptors
• Specificity – differentiate between included &
excluded items
• How specific/exclusive do you want the
measure to be?
• Usability – ease of use of tool or indicator
understood
• Recordability – ability to identify, capture &
measure needed information
• Stratification – breaking data down into
groups
15
Data Definition And Collection
• Reliability
o Ability to reproduce the same results
o Test / Retest
o Inter-rater Reliability
• Validity
o Measure what you are supposed to
measure
o Face Validity
o Criterion Validity
o Construct Validity
16
Defining a Population
• Entire population – 100%
• Sampling
o Nonprobability
o Probability
17
Nonprobability Sampling
• Convenience
o Using data readily available
• Quota
o Set number of data sets
• Purposive
o Demonstrate a desired characteristic
o Expert sampling
o Men vs Women
18
Probability Sampling
• Simple Random
o All items have an equal chance of being
chosen
• Stratified Random
o Creating 2 or more homogeneous groups
and then randomly selecting items
o Men vs Women
• Systemic Random
o Every n’th case
19
Types of Data
• Categorical (Attribute, Qualitative)
(Descriptions of qualities or kind)
o Nominal
o Ordinal
• Continuous (Variable, Quantitative)(Specific
measurement units)
o Interval
20
Type
Categorical / Count
AKA
Examples
Usually Reported as
Usual statistical test
of difference
between 2 groups
Usual display tools
Attribute
Discrete
Nominal
Ordinal
Qualitative
# Members, Patients, Births,
Procedures, Occurrences, Gender
% in each category
(whole numbers)
Chi Square
Table
Scorecard
Histogram
Pareto
See Section V page 51 for a similar comparison table
Continuous / Measured
Variable
Quantitative
Interval
Ratio
Age, Height, Weight, Temperature,
Time, Charges (money), LOS
Mean
Median
Minimum
Maximum
Percentiles
(whole and fractional units)
T test
Run chart
Control chart
Scorecard (not the best to use)
(data display over time = use one of
these tools – but only 1 item per line on
graph)
21
Tools & Statistics
• What it is
• When to use it
• What does it say?
22
Simple Statistics
(Central Tendency)
• Mean – average
• Median – middle
• Mode – most frequently occurring
• Range (Dispersion)– lowest to highest
• 2 4 6 8 10
Mean:
Median:
• 2 4 6 8 100
Mean:
Median:
• 2 4 6 7 8 10
Mean:
Median:
• 2 4 6 6 8 10
Mode:
• 2
4 4 6 6 8 10
Mode:
• 2 4 4 6 6 6 8 8 10
Mode:
• 2 4 6 8
10
Range:
• 102 104 106 108 110
Range:
• 0, 0, 0, 0, 0, 0, 2, 8, 12
• Mean =
Median =
• Mode =
Range =
• 392, 625, 17, 495, 89, 234, 106, 322, 982
25
Weighted Means
• A mean where some values contribute more
than others.
• Weighted means can help with decisions
where some things are more important than
others
• Use a table to make sure you have all the
numbers correct
26
Weighted Means
Score
Weight
Multiply
65
1
65
60
1
60
80
2
160
95
3
285
7
570
Total
Final Total
81.43
(570 divided by 7)
27
Other Math You May Need
• Percentage of the whole:
o What percent of the patients have
complications?
o Total patients = 100
o Number of patients with comp. = 45
X% of 100 = 45
X% = 45 / 100
X = .45 or 45%
28
Other Math You May Need
• Percentage of the whole:
o If 55% of the patients have complications,
how many patients would that be?
o Total patients = 100
55% of 100 = X
0.55 x 100 = X
55 = X
29
Standard Deviation
30
STANDARD DEVIATION
31
Data Analysis Tools
• Data must be displayed in the proper
manner
o Must be concise and easily understood by
the reader
• Analysis could include use of statistics,
simple or complex
32
Data Comparison Between 2 Groups
• Chi Square (X2)
o Use with Count data
• T-Test (t)
o Use with Continuous data
• Both give you a “p score”
0 0.05
0.25
0.50
1
• 0.05 or less indicates statistically significantly
different – NOT BY CHANCE
33
Scatter Diagrams
 Looking for the relationship of two variables
 Positive Relationship
 Negative Relationship
 No Relationship
See V 64 for more information on Scatter Diagrams
34
Positive Correlation
120
100
80
60
40
20
0
0
1
2
3
4
5
35
Negative Correlation
120
100
80
60
40
20
0
0
1
2
3
4
5
No Relationship or
Correlation
36
100
90
80
70
60
50
40
30
20
10
0
0
1
2
3
4
5
37
38
Regression Analysis
• Mathematical version of a Scatter Diagram
• Compare the distribution of two dispersions
• Correlation Coefficient (r)
-1
Strong
Negative
Relationship
(One up &
One down)
0
No
Relationship
+1
Strong
Positive
Relationship
(Both up or
both down)
39
Data Analysis Tools - Tables
Nov
• Most common tool
but not always the
best one
• Highlight the
important
information
• Clearly label the
different
parts/columns
• Stop Light approach
General Consent
Dec
0
0
Entries Dated
100
90
Entries Signed
100
90
Entries Timed
0
55
100
95
60
70
40
59
100
90
Author Identified
Abbrev. Used
Correctly
Legible writing
2 Patient Identifiers
Ope n Re cord OPD MONTHLY RATE-BASED
40
SCORECARD
EXAMPLE
Medical
Record
Review
Me a sure
INDICATOR AGGREGATE DATA 2012
De scription
0.0%
0.80%
NA
NA
Research
NA
NA
Thre shold
100%
Risk, Be ne fits,
Anesthesia
NA
NA
Alternative
Surgery
NA
NA
Thre shold
100%
Health History
Summary
Significant
0.0%
13.3%
Health history
0.0%
37.5%
Drug Allergies
0.0%
3.3%
Current
0.0%
Diagnoses
10.8%
Medication
Red
< 70
3.3%
0.0%
3.3%
Screening
40.0%
87.50%
Procedures
Past
Hospitilazation
85%
Reason for visit
20.0%
85.0%
Nursing
Pain
40.0%
49.1%
Assessment
Nutritional
20.0%
76.6%
Social/Econ
20.0%
79.1%
0.0%
61.6%
20.0%
65.8%
Abuse
0.0%
54.1%
Reassessment
0.0%
53.3%
100.0%
86.6%
80.0%
72.5%
Falls Risk
Allergies
Thre shold
Green
>85
0.0%
Past Surgical
Thre shold
Yellow
>70 but
< 85
De c
Informed
General
Conse nt
Nov
85%
Med. Assess.
Physical
Medical
System review
Assessment
Findings
Diagnostics
Plan
Reassessment
Thre shold
85%
0.0%
15.0%
80.0%
75.8%
100.0%
45.0%
0.0%
75.8%
20.0%
40.8%
Ye a r End
0.40%
41
Histogram / Bar Chart
• Often confused with each other
• Histogram = one stratified variable
• Bar Chart = Discrete categories
HISTOGRAM
BAR CHART
100
100
80
80
60
60
40
40
20
20
0-16
17-30 31-50 51-65
>65
CHF
COPD
MI
Pneum
42
Data Analysis Tools –
Histogram/Bar Charts
• Illustrates the
variability or
distribution of the
data
90
80
70
60
50
East
West
North
40
30
20
• Use with Count
data unless over
time
10
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
• Then move to
Run Chart
43
OPD Open Record Audit Nov - Dec 2012
120
100
80
60
Nov
Dec
40
20
0
General Consent
Entries Dated
Entries Signed
Entries Timed Author Identified Abbrev. Used
Correctly
Legible writing
2 Patient
Identifers
44
Data Analysis Tools –
Pareto Diagram
• Prioritizes a
series of
data sets
or possible
causes of
problems
16
14
12
10
8
• Best if you
use more
than one
6
4
2
0
Brown
Yellow
Green
Red
Blue
Orange
45
Pareto Diagram
100%
50
45
40
35
30
25
20
15
10
5
0
75%
50%
25%
Brown
Total
Number
Available
Yellow
Green
Red
Blue
Orange
Percent of
the Whole
46
Pareto Diagram
50
45
40
35
30
25
20
15
10
5
0
x
x
100%
x
x
75%
x
15
12
50%
10
25%
7
3
Brown
Yellow
Green
Red
Blue
3
Orange
47
Pareto Diagram
50
45
40
35
30
25
20
15
10
5
0
x
x
x
80%
x
75%
x
15
12
50%
10
25%
7
3
Brown
Yellow
100%
Green
Red
Blue
3
Orange
48
Pareto Chart
Patient Transfer – In To XXX Hospital
100.0
85.7
8
0
60
47.6
4
2
80
71.4
6
100
40
20
23.8
No communication No eforcement of
with referring
"contact
Hospital
precaution"to all
staff
New machine for
MRSA screening
result within 2hr
(current result 48hrs)
Main Concerns
All transfer-in
patients are not
treated as
"screened and
cleared"
MRSA screening
should be initiated
in Accident &
Emergency.
0
Percentage
Number of Vote
10
49
Drill Down with Paretos
• Can use pareto charts to drill down to find a
specific area to make improvements
• For example: Patients requiring greater then
1 hour in Recovery Room
50
Percent of Patients requiring > 1
hour in Recovery Room
25
20
15
10
5
0
Aug
Sept
Oct
Nov
Reason for Prolong Recovery
Time
250
200
150
100
50
0
Clinical
Non-clinical
51
Pareto - Clinical Delay in
Recovery Time
80
70
60
50
40
30
20
10
0
Pareto - Non-Clinical Delay in
Recovery Time
50
40
30
20
10
0
Unit RN
MD Assess
Porter
File
Bed CCU/ICU
52
Pain Delay in Recovery
30
25
20
15
10
5
0
Not reassessed
Pt not medicated
Med did not work
Pt not assessed
Pt not complain
Data Analysis Tools –
Run Chart
• Monitors
variation in
data/
• processes over
time
• Use with
continuous
/measured
data
80
70
60
50
40
30
20
10
0
Ja
n
Fe
b
M
ar
Ap
r
M
ay
Ju
n
Ju
ly
Au
g
Se
p
Oc
t
No
v
De
c
53
ADC
54
Data Analysis Tools Stratification
• Breaks down
single variables
into its
meaningful
Total Falls parts
60
50
40
30
Med Unit
Surg Unit
• Helps to focus
on where the
problem really
lies
20
10
0
Jan
Feb
Mar
Apr
May
Jun
55
Average Daily Census
What type of data is this?
If one wanted to see the Average Daily
Census Over the Year, a Run chart will show
this better than a Histogram
56
Average Daily Census
80
70
60
50
40
30
20
10
Ja
n
Fe
b
M
ar
A
pr
M
ay
Ju
n
Ju
ly
A
ug
Se
p
O
ct
N
ov
D
ec
0
ADC
57
Number of CHF Patients vs AMI
Patients for 1st Half of Year
 Have Categories of patients:
1. CHF
2. AMI
 This is Nominal Data since there is no real
order here
 Could use a Histogram to show this
58
Number of CHF Patients vs AMI
st
Patients for 1 Half of Year
60
50
40
CHF
AMI
30
20
10
0
Jan
Feb
Mar
Apr
May
Jun
Number of CHF Patients vs
st
AMI Patients for 1 Half of Year
59
60
50
40
CHF
AMI
30
20
10
0
Jan
Feb
Mar
Apr
May
Jun
60
Events Reported (Patients with unknown status –
considered negative who had positive screening at XXX)
Total Number of Reported Events per Month
# of Events
Target
Reported Event
2
1
0
Jan
Feb
Mar
Apr
May
Jun
2012
Jul
Aug
Sept
Oct
61
Prevention & Control of Infection Program
62
Data Analysis Tools –
Control Chart
• Statistically
illustrates the
upper &
lower control
limits of a
process & the
variation of
the process
within those
limits
63
Control Charts
 As
easy as:
 Run charts with the Bell Curve
turned on its side
64
Control Charts
100
90
80
70
60
50
40
30
20
10
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
65
PROCESS VARIATION
• Variation – change or deviation in
form, condition, appearance, extent,
etc. from former or usual state, or from
an assumed standard
• Clinical Variation – can be positive
or negative
66
PROCESS VARIATION
• Random/Common Cause - Intrinsic to the
Process Itself
 Common Cause Variation
 What you would expect to happen with
random variation
 Do not try to improve the process unless the
mean is not where it needs to be
67
Based on Variation
And Spread of Data
 Special Cause - Extrinsic to the Usual
Process; Related to Identifiable
Characteristics. Example - Sentinel Events
 Special Cause Variation
 What you would not expect to happen
 If a pattern or trend exists
 Need to investigate and make changes
 Good = try to get it to repeat
 Bad = try to eliminate it from happening again
68
Special Cause / Trend Rules
• Run charts & Control charts both use
Trend/Special Cause rules
• Basically theses show trends, shifts, & other
changes in the data
• Run & Control chart rules are basically the same
but with difference in the number of data points
• Control Charts are more precise in identifying
special cause variation
Special Cause Rules Use with both run chart & control chart
69
 Outside the Upper and Lower Control limits on a
Control chart
 or an outrageous value compared to the other
ones on a Run chart (Astronomical Value)
 Six or Seven consecutive points going up
or going down (Trend)
 Seven or Eight consecutive points above or below
the mean (Shift)
70
Special Cause Rules - Outside limit
(Astronomical Value)
• Any dot that is
outside of the
upper or lower
control limit (or
in a run chart an
astronomical
value)
• Control limits are
mathematically
calculated
based on the
mean of the
data
71
Special Cause Rule – 7 or 8 in a row
(Shift)
• Seven or
Eight dots in
a row either
above or
below the
mean
• If a dot in
the run
lands on the
mean, it is
skipped &
not
counted
72
Shift – Dot on Mean
73
Special Cause Rule – 6 or 7 in a row
• Six or Seven
dots in a row
going up or
gong down
• If two dots
are side by
side in a run
of data, one
of those is
not counted
74
Trend – Dot Next To Each Other
75
76
77
Catheter-Related BLOOD-STREAM INFECTION(CRBSI) NICU
1 case CRBSI
identified
79
HEALTHCARE-ASSOCIATED INFECTION RATE
Rate / 1000 ICU PATIENT DAYS
ADULT ICU
35
1 case developed CRUTI ,AND
2 RTA cases developed VAP,
with the same organism isolated
from the tracheal
aspirate(A.baumanii MDR)
IC Practitioner focused on
Environmental screening &
audit on hand hygiene practices.
33.22
30
25
24.65
21.98
20
22.06
17.9
14.23
11.02
18.94
17.7
15
10
22.39
19.9
11.4
11.7
10.9
9.7
7.7
5
13.98
13.96
7.7
9.55
9.71
7.87
3.73
0
KFMMC-AICU- 2011
KFMMC -AICU-2012
CDC median Rate 23.9
kfmmc 2011 median rate (18.8)
79
Rate / 1000 HOSPITAL DAYS
HEALTHCARE-ASSOCIATED INFECTION
HOSPITAL WIDE RATE
8
7
6
5
4
3
2
1
0
6.7
19 infections with 30
organisms
5.11
2.7
2.5
2.2
3.4
3.14
2.47
JA
N
FE
B
4.2
3.01
3.06
2.9
3.2
2.18
2.1
2.98
3.55
2.25
2.7
3
2.46
2.85
2.14
2.05
M
AR
2011 KFMMC
AP
R
M
AY
JU
N
JU
L
2012 KFMMC
AU
G
SE
P
OC
T
NO
V
CDC ( up to 6.7 )
DE
C
80
Process Analysis Tools
• A method of analyzing the data utilizing diagrams
of a healthcare process
• Measure process variations & look for ways to
improve the process & the administrative or clinical
outcome
• Tools include a cause & effect diagram, flowchart,
process mapping, tree diagram, interrelationship
diagrams, affinity diagram, and many other such
tools
• Frequently used in RCA and FMEAs
81
CAUSE AND EFFECT DIAGRAM
(Ishikawa)
• Purpose
• Steps
82
Cause & Effect Diagram
Effect
Cause
83
Cause & Effect Diagram
4 or 5 M’s
o Manpower
o Materials
o Machines
o Methods
o Management
5 P’s
o People
o Provisions
(supplies)
o Policies
o Procedures
o Place
(environment)
84
People
Physical
Environment
Transportation
Not enough to do the work
Bed not clean
MD communication
Tubing system
Other department delays
Access nurse
Technical difficulties
with text pager
Not adhering to process
Reluctance to discharge
Why Bed Assignment
Cannot be Made in <
30 minutes
Patient education
Discharge order
Transportation
Too many discharges
Current patient
waiting for tests
Waiting for test
results
Discharge Summary
Transcriptions
Waiting for oxygen,
visiting nurse
Process
Not wanting
discharge
Waiting for education
Waiting to talk to MD
Patients
85
Gantt Chart
• Project Planning
Tool
• Includes list of
tasks and estimates
of time, people &
resources to
complete task
• Actions down left
side
• Horizontal bars to
indicate time
frames
Wk 1
Data collection
Data Analysis
Prepare Reports
Present Reports
Wk 2
Wk 3
Wk 4
Wk 5
Wk 6
Survey Process
Chapter 7
88
New Objectives
• Facilitate evaluation & selection of appropriate
accreditation or recognition programs
o The Joint Commission (TJC)
o Det Norske Vertis (DNV)
o Healthcare Facility Accreditation Program (HFAP)
• American Osteopathic Association (AOA)
o National Committee for Quality Assurance (NCQA)
o Magnet
o Baldrige
• http://www.jointcommission.org/assets/1/6/Compar
ison_Document2013.pdf
• Facilitate communication with accreditation and
accrediting and regulatory bodies
88
New Objectives
• Develop / Provide survey preparation training
(accreditation, licensure, equivalent)
• Aid in evaluating survey readiness for
accrediting and regulatory bodies
• Aid in evaluating the readiness to apply for
external quality awards
• Coordinate survey process (accreditation,
licensure, equivalent)
89
Determine Survey Readiness
• Assess compliance with standards
o Review of documentation
o Onsite mock surveys
o Verbal interaction with staff
o Review of medical records
o Assessment of service/support systems
90
Accreditation Survey Readiness
• Leadership
• Readiness/ Regulatory Team
o Mock Surveys
o Implementation of new standards
o Knowledge readiness
• Communication !!!!!!!!!
91
Coordination of Survey
• Have a process in place and tested for when
ANY surveyors come through the front door
• Have a headquarters (war room) for all
information to flow through
• Have scribes (with a phone) to write down all
that the surveyor asks or looks at
• If documentation is needed, call war room to
get the information – NOT the scribe
• Have a separate person to accompany the
surveyor.
92
Coordination of Survey
• NEVER leave the surveyor alone, even in the
restroom or outside for a smoke
• When surveyors leave in the evening, key
personnel stay and meet to discuss the day and
determine if work needs to occur before the
next day to “make things better” or find things
the surveyor wants that were not found that
day.
• Notify all managers/other appropriate staff
what the surveyors looked at that day and
what the next day will be like
93
End of Survey
• Typically, the CEO determines who hears the
exit interview
• After the exit interview, staff should be
informed of the results
• Regardless of what the results are,
celebrate !
• Then buckle down the next day or so and
start an action plan for what has to been
done to clear any citations
94
Licensure
• Mandatory act of granting and receiving a
license to provide healthcare services in a state
in the U.S.
• Usually the state Department of health Services
grants the license and monitors the license
• Onsite survey to determine compliance with all
applicable state and federal laws and
regulations
• License specifies the number of beds permitted
o Acute, skilled, subacute, long term, etc.
95
The Joint Commission
• Organizations
o
o
o
o
o
o
o
o
o
http://www.jointcommission.org/
Hospitals
Critical Access hospitals
Home Care
Ambulatory Surgery
Primary Care medical Home
Behavioral health
Long Term care
Laboratory
Disease Specific Care certification
• Core Measures for hospital programs
• Other quality measurement systems for other
types of organizations
96
Det Norske Vertis (DNV)
• National Integrated Accreditation for
Healthcare Organizations (NIAHO) –
http://www.dnvusa.com/industry/healthc
standards
are/index.asp
• CMS Conditions of Participations plus ISO
9001 standards
• Hospitals & Critical Access Hospitals
• Primary Stroke Center certification
97
Healthcare Facility Accreditation
Program (HFAP)
• American Osteopathic Association (AOA) sponsors
this accreditation
• All Acute Care facilities (general, specialty, LTAC)
• Behavioral/mental health
• Ambulatory care/office-based surgery
• Ambulatory Surgery Centers
• Clinical laboratories
• Primary Stroke Centers
http://www.hfap.org/
• Critical Access Hospitals
• Focus: CMS plus patient safety & quality of care
standards
National Committee for Quality
98
Assurance (NCQA)
• Health Plans, including:
o
o
o
o
•
•
•
•
http://www.ncqa.org/
Health Maintenance Organizations (HMO),
Managed Care Organizations (MCO),
Preferred Provider Organizations (PPO) and
Point of Service (POS) plans
Managed Behavioral Health Organizations (MBHO)
Disease Management accreditation or certification
Wellness & Health Promotion
Health Effectiveness Data and Information Set
(HEDIS)
o Evaluate the structure and functions of medical and
quality management systems in managed care
organizations
99
Commission for Accreditation of
Rehabilitation Facilities (CARF)
• Promotes quality, value, & optimal outcomes of
services to the following types of facilities
o Aging Services
www.carf.org
o Behavioral Health
o Business & Service Mgmt Networks
o Child & Youth Services
o Employment & Community Services
o Medical Rehabilitation
o DMEPOS (medical equipment, etc)
Baldrige Performance
Excellence Award
100
http://www.nist.gov/baldrige/
• Managed by the National institute of
Standards & Testing (NIST) –
o an agency of the U.S. Department of Commerce
• Seven Categories of Criteria
o
o
o
o
o
o
o
Leadership
Strategic planning
Customer Focus
Measurement, Analysis and Knowledge Management
Workforce Focus (environment & engagement)
Operations Focus
Results (outcomes)
101
Magnet Recognition Program
http://www.nursecredentialing.org/Magnet.aspx
• Developed by American Nurses Credentialing
Program to recognize healthcare organizations
for nursing excellence
• Five Model Components (14 Forces of
Magnetism)
o
o
o
o
o
Transformational Leadership
Structural Empowerment
Exemplary Professional Practice
New Knowledge, Innovation & Improvements
Empirical Quality Results
102
Susan Mellott
PhD, RN, CPHQ, FNAHQ
mellottandassoc@att.net
mellottandassociates.com