information management chapter 5. information management process identify current available data...
TRANSCRIPT
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Information Management
Chapter 5
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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
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INFORMATION MANAGEMENT PROCESS
• Analyze Data
• Interpret Data / Information
• Act on Information
• Report Data/Information/Knowledge/ Decision
• Collect More Data to Monitor/Analyze the Decision.
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INFORMATION
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
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DATA INVENTORY
PROCESS• Where data is collected in organization
• Collection Stepso What being collected, from where
• Analysis Steps
• Reason for Collecting this Datao Being used?o Duplicate Information?
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Electronic Medical Record /
Information Technology• Institute of Medicine (IOM) started the
movement in Aug 2003
• Four Goalso Inform clinical practiceo Interconnect cliniciansoPersonalize careo Improve population health
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Other IT Topics
• Impact of Health Information Management on Quality
o ICD-10oCodingoMeaningful use
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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
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CONFIDENTIALITY IN HEALTHCARE
• HIPAA• Access
o Without Written Authorization of Patiento With Written Authorization of Patient
• Security
o Sequestered records
• Consent - Release of Medical Information
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Committee Meeting Organization• Meeting
• Minutes
• Reminders
• Meeting Date• Agenda• Packet
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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)
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Epidemiological Concepts & Methods
• Concepts and Methods
- Causality- Cause & Effect
- Frequency- Rate- Proportion- Ratio
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Epidemiological Concepts and Methods
• Morbidity – rate of disease or proportion of diseased persons in a given location
I Incidence – rate during specific time period
I Prevalence – proportion in a defined population at one point in time
• Mortality – proportion of deaths in a population within a time range
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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
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Data Definition And Collection
• Reliability o Ability to reproduce the same resultso Test / Retest o Inter-rater Reliability
• Validityo Measure what you are supposed to
measureo Face Validityo Criterion Validityo Construct Validity
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Defining a Population
• Entire population – 100%
• Sampling o Nonprobabilityo Probability
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Nonprobability Sampling
• ConvenienceoUsing data readily available
• Quotao Set number of data sets
• PurposiveoDemonstrate a desired characteristico Expert samplingoMen vs Women
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Probability Sampling
• Simple Randomo All items have an equal chance of being
chosen
• Stratified Randomo Creating 2 or more homogeneous groups
and then randomly selecting itemso Men vs Women
• Systemic Randomo Every n’th case
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Types of Data
• Categorical (Attribute, Qualitative) (Descriptions of qualities or kind)oNominaloOrdinal
• Continuous (Variable, Quantitative)(Specific measurement units)o Interval
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20Type Categorical / Count Continuous / Measured
AKA AttributeDiscreteNominalOrdinalQualitative
VariableQuantitativeIntervalRatio
Examples # Members, Patients, Births, Procedures, Occurrences, Gender
Age, Height, Weight, Temperature, Time, Charges (money), LOS
Usually Reported as % in each category(whole numbers)
MeanMedianMinimum MaximumPercentiles(whole and fractional units)
Usual statistical test of difference between 2 groups
Chi Square T test
Usual display tools TableScorecardHistogramPareto
Run chartControl chartScorecard (not the best to use)(data display over time = use one of these tools – but only 1 item per line on graph)
See Section V page 51 for a similar comparison table
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Tools & Statistics
• What it is• When to use it• What does it say?
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Simple Statistics
(Central Tendency)• Mean – average
• Median – middle
• Mode – most frequently occurring
• Range (Dispersion)– lowest to highest
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• 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:
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• 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
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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
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Weighted Means26
Score Weight Multiply
65 1 65
60 1 60
80 2 160
95 3 285
Total 7 570
Final Total 81.43 (570 divided by 7)
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Other Math You May Need
• Percentage of the whole:oWhat percent of the patients have
complications?o Total patients = 100oNumber of patients with comp. = 45
X% of 100 = 45
X% = 45 / 100 X = .45 or 45%
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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 = X55 = X
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Standard Deviation29
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STANDARD DEVIATION30
C BD AF
**
**
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• Data must be displayed in the proper manneroMust be concise and easily understood
by the reader
• Analysis could include use of statistics, simple or complex
Data Analysis Tools31
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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”
• 0.05 or less indicates statistically significantly different – NOT BY CHANCE
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10 0.500.250.05
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Scatter Diagrams Looking for the relationship of two variables
Positive Relationship Negative Relationship No Relationship
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See V 64 for more information on Scatter Diagrams
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Positive Correlation
0
20
40
60
80
100
120
0 1 2 3 4 5
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Negative Correlation
0
20
40
60
80
100
120
0 1 2 3 4 5
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No Relationship or Correlation
01020304050
60708090
100
0 1 2 3 4 5
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Calories vs Weight Gain
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
0 500 1000 1500 2000 2500 3000 3500 4000 4500
Calories Consumed
Weight gained
y=mx+b
n=13
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Regression Analysis• Mathematical version of a Scatter Diagram• Compare the distribution of two dispersions• Correlation Coefficient (r)
Strong No StrongNegative Relationship PositiveRelationship Relationship
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0- 1 + 1
(One up & One down)
(Both up or both down)
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• Most common tool but not always the best one
• Highlight the important information
• Clearly label the different parts/columns
• Stop Light approach
Nov Dec
General Consent 0 0
Entries Dated 100 90
Entries Signed 100 90
Entries Timed 0 55
Author Identified 100 95Abbrev. Used Correctly 60 70
Legible writing 40 59
2 Patient Identifiers 100 90
Data Analysis Tools - Tables
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Measure Description Nov Dec Year End
General 0.0% 0.80% 0.40%
Consent Informed NA NAResearch NA NA
Threshold 100%
Risk, Benefits, Anesthesia NA NA
Alternative Surgery NA NAThreshold 100%
Health History Significant 0.0% 13.3%Summary Diagnoses
Health history 0.0% 37.5%
Drug Allergies 0.0% 3.3%
Current 0.0%
Medication 10.8%
Past Surgical 0.0% 3.3%
Procedures
Past 0.0% 3.3%
Hospitilazation
Threshold 85%
Screening 40.0% 87.50%
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%
Falls Risk 0.0% 61.6%
Allergies 20.0% 65.8%
Abuse 0.0% 54.1%
Reassessment 0.0% 53.3%Threshold 85%
Med. Assess. 100.0% 86.6%
Physical 80.0% 72.5%
Medical System review 0.0% 15.0%
Assessment Findings 80.0% 75.8%
Diagnostics 100.0% 45.0%
Plan 0.0% 75.8%
Reassessment 20.0% 40.8%Threshold 85%
Open Record OPD MONTHLY RATE-BASED INDICATOR AGGREGATE DATA 2012
Red < 70
Yellow>70 but
< 85
Green >85
SCORECARD
EXAMPLE
Medical Record Review
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Histogram / Bar Chart
• Often confused with each other• Histogram = one stratified variable• Bar Chart = Discrete categories
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HISTOGRAM
100
80
60
40
20
0-16 17-30 31-50 51-65 >65
BAR CHART
100
80
60
40
20
CHF COPD MI Pneum
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• Illustrates the variability or distribution of the data
• Use with Count data unless over time
• Then move to Run Chart
Data Analysis Tools – Histogram/Bar Charts
0
10
20
30
40
50
60
70
80
90
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
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Gener
al C
onse
nt
Entrie
s Dat
ed
Entrie
s Sig
ned
Entrie
s Tim
ed
Autho
r Ide
ntifi
ed
Abbre
v. U
sed Cor
rectly
Legib
le w
ritin
g
2 Pat
ient
Iden
tifer
s0
20
40
60
80
100
120
OPD Open Record Audit Nov - Dec 2012
NovDec
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• Prioritizes a series of data sets or possible causes of problems
• Best if you use more than one
Data Analysis Tools – Pareto Diagram
0
2
4
6
8
10
12
14
16
Brown Yellow Green Red Blue Orange
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Pareto Diagram
0
5
1015
20
25
3035
40
45
50
Brown Yellow Green Red Blue Orange
100%
50%
25%
75%
Total Number
Available
Percent of the Whole
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Pareto Diagram
1512 10
73 3
0
5
1015
20
25
3035
40
45
50
Brown Yellow Green Red Blue Orange
100%
50%
25%
75%
x
xx
x x
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Pareto Diagram
1512 10
73 3
0
5
1015
20
25
3035
40
45
50
Brown Yellow Green Red Blue Orange
100%
50%
25%
75%
x
xx
x x
80%
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Pareto ChartPatient Transfer – In To XXX Hospital
23.8
47.6
71.485.7
100.0
0
20
40
60
80
100
0
2
4
6
8
10
No communicationwith referring
Hospital
No eforcement of"contac t
precaution"to allstaff
New machine forMRSA screeningresult within 2hr
(current result 48hrs)
All transfer-inpatients are not
treated as"sc reened and
c leared"
MRSA screeningshould be initiated
in Acc ident &Emergency.
Perc
enta
ge
Num
ber of V
ote
Main Concerns
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• 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
Drill Down with Paretos49
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Aug Sept Oct Nov0
5
10
15
20
25
Percent of Patients requir-ing > 1 hour in Recovery
Room
Clinical Non-clinical0
50
100
150
200
250
Reason for Prolong Re-covery Time
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Pain
Hypot
herm
ia
Cardi
o
Resp
Rate
LOC
Mot
or
Bleed
ing
0
10
20
30
40
50
60
70
80
Pareto - Clinical Delay in Recovery Time
Unit RN MD Assess Porter File Bed CCU/ICU
05
1015202530354045
Pareto - Non-Clinical Delay in Recovery Time
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Not reassessed Pt not medicated Med did not work Pt not assessed Pt not complain0
5
10
15
20
25
30
Pain Delay in Recovery52
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• Monitors variation in data/
• processes over time
• Use with continuous /measured data
Data Analysis Tools – Run Chart
0
10
20
30
40
50
60
70
80
ADC
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• Breaks down single variables into its meaningful parts
• Helps to focus on where the problem really lies
Data Analysis Tools - Stratification
0
10
20
30
40
50
60
Jan Feb Mar Apr May Jun
Total FallsMed UnitSurg Unit
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Average Daily Census
If one wanted to see the Average Daily Census Over the Year, a Run chart will show this better than a Histogram
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What type of data is this?
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Average Daily Census
0
10
20
30
40
50
60
70
80
Jan
FebM
ar AprM
ay Jun
July
AugSep O
ctNov Dec
ADC
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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
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Number of CHF Patients vs AMI Patients for 1st Half of
Year
0
10
20
30
40
50
60
Jan Feb Mar Apr May Jun
CHFAMI
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Number of CHF Patients vs AMI Patients for 1st Half of
Year
0
10
20
30
40
50
60
Jan Feb Mar Apr May Jun
CHFAMI
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Events Reported (Patients with unknown status – considered negative who had positive screening at XXX)
0
1
2
Jan Feb Mar Apr May Jun Jul Aug Sept Oct
Repo
rted
Eve
nt
2012
Total Number of Reported Events per Month
# of Events Target
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Prevention & Control of Infection Program61
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• Statistically illustrates the upper & lower control limits of a process & the variation of the process within those limits
Data Analysis Tools – Control Chart
R Chart Title
RUCL=0.395
CL=0.187
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
6/88am
10am 12pm 2pm 6/98am
10am 12pm 2pm 6/108am
10am 12pm 2pm 6/118am
10am 12pm 2pm 6/128am
10am 12pm
Date/Time/Period/Number
RangeUCL+2 sigma+1 sigmaAverage-1 sigma-2 sigmaLCL
n=19
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Control Charts
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As easy as: Run charts with the Bell Curve
turned on its side
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Control Charts64
0102030405060708090
100
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
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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
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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
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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
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Based on Variation
And Spread of Data
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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
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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)
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Special Cause Rules -Use with both run chart & control
chart
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• 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
Special Cause Rules - Outside
limit (Astronomical Value)
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• 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
Special Cause Rule – 7 or 8 in a
row (Shift)
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Shift – Dot on Mean72
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• 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
Special Cause Rule – 6 or 7 in a
row
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Trend – Dot Next To Each Other74
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R Chart Title
RUCL=0.395
CL=0.187
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
6/88am
10am 12pm 2pm 6/98am
10am 12pm 2pm 6/108am
10am 12pm 2pm 6/118am
10am 12pm 2pm 6/128am
10am 12pm
Date/Time/Period/Number
RangeUCL+2 sigma+1 sigmaAverage-1 sigma-2 sigmaLCL
n=19
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Catheter-Related BLOOD-STREAM INFECTION(CRBSI) NICU
1 case CRBSI identified
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HEALTHCARE-ASSOCIATED INFECTION RATE
ADULT ICU
11.02
14.23
3.73
33.22
24.65
21.98
13.96
7.87
22.06
13.98
18.94
22.39
17.9
11.49.7
7.7 7.7
10.9
19.9
17.7
11.7 9.55 9.71
0
5
10
15
20
25
30
35
Ra
te /
10
00
ICU
P
AT
IEN
T D
AY
S
KFMMC-AICU- 2011 KFMMC -AICU-2012 CDC median Rate 23.9 kfmmc 2011 median rate (18.8)
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.
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HEALTHCARE-ASSOCIATED INFECTION
HOSPITAL WIDE RATE
5.11
2.25
3.4
2.18
4.2
2.14
3.55
2.85
3.063.012.983.14
2.1
3
2.472.05
2.462.9
3.22.7
2.7 2.5 2.2
6.7
0
1
2
3
4
5
6
7
8
JANFEB
MARAPR
MAYJUN
JULAUG
SEPOCT
NOVDEC
Ra
te /
10
00
HO
SP
ITA
L D
AY
S
2011 KFMMC 2012 KFMMC CDC ( up to 6.7 )
19 infections with 30 organisms
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• 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
Process Analysis Tools80
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• Purpose
• Steps
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CAUSE AND EFFECT DIAGRAM
(Ishikawa)
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Cause & Effect Diagram
Effect
Cause
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Cause & Effect Diagram
5 P’so Peopleo Provisions
(supplies)o Policieso Procedureso Place
(environment)
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4 or 5 M’soManpoweroMaterialsoMachinesoMethodsoManagement
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Why Bed Assignment Cannot be Made in <
30 minutes
Physical Environment
People
Process Patients
Transportation
Transportation
Waiting for education
Waiting to talk to MD
Not wanting discharge
Bed not clean
Technical difficulties with text pager
Tubing system
Patient education
Too many discharges
Current patient waiting for tests
Waiting for test results
Discharge order
Discharge Summary
Transcriptions
Waiting for oxygen, visiting nurse
Not enough to do the work
Other department delays
Not adhering to process
MD communication
Access nurse
Reluctance to discharge
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Gantt Chart85
• 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 Wk 2 Wk 3 Wk 4 Wk 5 Wk 6
Data collection
Data Analysis
Prepare Reports
Present Reports
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Survey Process
Chapter 7
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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 Magneto Baldrige
• http://www.jointcommission.org/assets/1/6/Comparison_Document2013.pdf
• Facilitate communication with accreditation and accrediting and regulatory bodies
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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)
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Determine Survey Readiness
• Assess compliance with standardso Review of documentation
o Onsite mock surveys
o Verbal interaction with staff
o Review of medical records
o Assessment of service/support systems
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Accreditation Survey Readiness
• Leadership
• Readiness/ Regulatory Teamo Mock Surveyso Implementation of new standardso Knowledge readiness
• Communication !!!!!!!!!
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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.
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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
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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
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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 permittedo Acute, skilled, subacute, long term, etc.
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The Joint Commission• Organizations
o Hospitalso Critical Access hospitalso Home Careo Ambulatory Surgeryo Primary Care medical Homeo Behavioral healtho Long Term careo Laboratoryo Disease Specific Care certification
• Core Measures for hospital programs • Other quality measurement systems for
other types of organizations
http://www.jointcommission.org/
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Det Norske Vertis (DNV)
• National Integrated Accreditation for Healthcare Organizations (NIAHO) – standards
• CMS Conditions of Participations plus ISO 9001 standards
• Hospitals & Critical Access Hospitals
• Primary Stroke Center certification
http://www.dnvusa.com/industry/healthcare/index.asp
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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• Critical Access Hospitals
• Focus: CMS plus patient safety & quality of care standards
http://www.hfap.org/
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National Committee for Quality
Assurance (NCQA)• Health Plans, including:
o Health Maintenance Organizations (HMO), o Managed Care Organizations (MCO), o Preferred Provider Organizations (PPO) and o 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
http://www.ncqa.org/
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Commission for Accreditation of
Rehabilitation Facilities (CARF)• Promotes quality, value, & optimal
outcomes of services to the following types of facilitieso Aging Serviceso Behavioral Healtho Business & Service Mgmt Networkso Child & Youth Serviceso Employment & Community Serviceso Medical Rehabilitationo DMEPOS (medical equipment, etc)
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www.carf.org
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Baldrige Performance Excellence Award
• Managed by the National institute of Standards & Testing (NIST) – o an agency of the U.S. Department of Commerce
• Seven Categories of Criteriao Leadershipo Strategic planningo Customer Focuso Measurement, Analysis and Knowledge Managemento Workforce Focus (environment & engagement)o Operations Focuso Results (outcomes)
http://www.nist.gov/baldrige/
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Magnet Recognition Program
• Developed by American Nurses Credentialing Program to recognize healthcare organizations for nursing excellence
• Five Model Components (14 Forces of Magnetism)o Transformational Leadershipo Structural Empowermento Exemplary Professional Practiceo New Knowledge, Innovation & Improvementso Empirical Quality Results
http://www.nursecredentialing.org/Magnet.aspx
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