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On-Demand Clinical Intelligence. Clinical Looking Glass Training. Don’t just sit there! . Login and Change Password Open Internet Explorer Enter “ https://secure1.afms.mil/CLG ” in address Enter Username and Password

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on demand clinical intelligence

On-Demand Clinical Intelligence

Clinical Looking Glass Training

don t just sit there
Don’t just sit there! 

Login and Change Password

  • Open Internet Explorer
  • Enter “https://secure1.afms.mil/CLG” in address
  • Enter Username and Password
  • Under “Virtual Desktops” click on “SG-CLG” hyperlink for Citrix VDI Login
  • Enter “http://clgpoc.afms.mil/CLGNET” in address
  • Enter username: usually first initial+lastname
  • Enter generic password: clg123
  • Change password
  • Save (toolbar at the bottom)
  • Log out
today
Today
  • Introductions
  • Ground Rules
  • Why Clinical Looking Glass?
  • Introductory Training
  • HIPAA
welcome to the future
Welcome to the Future

The Future of Clinical Business Intelligence

Dr. Eran Bellin

Vice President, IT Clinical Research and Development

Montefiore Medical Center

ground rules
Ground Rules
  • Use cell phones outside
  • Follow me when teaching
    • There is time for hands on
  • Slow me down, ask questions
clg included data
CLG: Included Data

Labs

Meds

Procs

Diagnoses

Death

Orders

learning roadmap
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim and Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
clg core concepts
CLG Core Concepts

I

Analysis

Groups

  • Qualifying rules for inclusion
  • Index Date (I)
    • Patient specific start/enrollment date
  • Group Types
    • Cohorts – unique patients, 1 index instance per person
    • Event Collections – events, multiple index instances per person
  • 3) Sources
    • Event Canvas – most flexible
    • Smart Reports – subject specific
    • Upload – from non-CLG source
  • Analytic rules are non-qualifying
  • Method applied to one or more groups
  • Methods include:
    • Append study data
    • List / data grid
    • Crosstabs / pivots
    • Time to Outcome (survival)
    • Incidence Density
    • Time in Range
    • …more to come

“Reusable research objects”

study groups x analysis
Study = Groups X Analysis

I

I

Next Visit Alerts

% days A1C in control

5 yr visit hx per MD

2 yr history of HTN

2 year survival

Male diabetics

Female diabetics

when data are not patient centric
When Data Are Not Patient-Centric

1/1/2005

1/1/2007

1/1/2006

Patient #

1

0

Diabetes Control

2

0

0

= index date

3

0

(EG start therapy)

4

0

5

0

= outcome

6

0

(EG achieve lab value)

7

0

8

0

0

= patient experience

9

0

10

0

4 / 10 = 40%

What % of new diabetic patients were controlled in the year 2005?

patient based analysis of diabetes control
Patient-Based Analysis of Diabetes Control

Enrollment

2 Years

1 Year

Patient #

Diabetes Control

3

0

0

= index date

8

0

(EG start therapy)

9

0

1

0

= outcome

4

0

(EG achieve lab value)

7

0

0

= patient experience

5

0

10

0

2

0

(same data, re-sorted)

6

0

5 / 10 = 50%

What % of new diabetic patients were controlled within 1 year?

cohort paradigm patient centric
Cohort Paradigm: Patient-Centric
  • Subject specific follow-up periods
    • Contra-indications taken into account
    • Stop looking for outcome when patient is no longer at risk
  • Group summary is an aggregation of individual experiences
  • Epidemiologic methods are ideal for retrospective, observational studies
learning roadmap1
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim and Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
clinical scenario bactrim hyperkalemia
Clinical Scenario:Bactrim & Hyperkalemia
  • Does Bactrim (trimethoprim/sulfamethoxazole) cause hyperkalemia?
  • What is the mechanism?
  • Which patients are at risk for developing hyperkalemia while on Bactrim?
  • Is it okay for patients taking other meds that increase potassium (ACE inhibitors, ARBs, etc.) to take Bactrim?
  • When should you check potassium?
  • What are antibiotic alternatives to Bactrim?
  • How should TMP/SMX be dosed in renal insufficiency?
  • Is it okay for patients taking meds that increase potassium to use salt substitutes?

Trimethoprim and Hyperkalemia

Trimethoprim is commonly used in combination with sulfamethoxazole (TMP/SMX cotrimoxazole, Bactrim, Septra, others) for the treatment of a variety of infections such as urinary tract infections. Although this medication has been available for many years, a recognized, but little-known adverse effect is hyperkalemia. This document discusses the clinical data, mechanism and risk factors for trimethoprim-induced hyperkalemia.

Bactrim may cause hyperkalemia when combined with ACE ARBs

  • Is this happening in MHS?
  • Study Group:
  • Patients greater than 65 years old
  • Outpatient prescription for Bactrim during 2008 to 2011
  • Outpatient prescription for an ACE ARB within 365 days before the Bactrim prescription
  • Comparison Group:
  • Patients greater than 65 years old
  • Outpatient prescription for a macrolide (ERYTHROMYCIN STEARATE, ERYTHROMYCIN BASE, CLARITHROMYCIN, AZITHROMYCIN) during 2008 to 2011
  • Outpatient prescription for an ACE ARB within 365 days before the Bactrim prescription
  • Outcomes:
  • Potassium level of 5.5 or greater within 0 to 30 days of the Bactrim prescription start date.
login change pw go to study designer
Login, Change PW, go to Study Designer
  • Open Internet Explorer
  • Enter “http://clgpoc.afms.mil/CLGNET” in address bar
  • Enter username: first initial+lastname
  • Enter generic password: clg123
  • Change password
  • Save (toolbar at the bottom)
  • Open Study Designer (Analysis Menu)
  • Open Bactrim study

Wait here

study designer
Study Designer

I

Analysis

Groups

slide20
Demo
  • Study Designer overview
  • Results
  • Criteria
  • Group definition using:

Skip to Exercise 1

learning roadmap2
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim & Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Cohort
  • Browse a Cohort: List Method
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
exercise 1 modify a cohort
Exercise 1Modify a Cohort

See handout In-Class Exercise: Bactrim 18 to 65

  • Change Demographics to Age 18 to 65
  • Re-build your cohort
  • Rename and rerun the study “antibiot acearb hyperk for cls”
  • Observe Results
  • What conclusion can be made about Bactrim in this younger population?
learning roadmap3
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim and Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
demo replicate ckd study at mhs
Demo: Replicate CKD Study at MHS
  • Create a cohort of patients>=18 years who had at least one admission with Chronic Kidney Disease during the year 2009 ANDhad a hemoglobin lab test done with a value>12g per deciliter around 90 days of the admission date AND received an inpatient med order of Epoetin Alfa within 30 days of the admission date.
  • Next create a comparison group with the same criteria except the patients who did NOT received the inpatient med order of Epoetin Alfa.
  • Then use time to outcome method to track primary end point events of mortality (6 months), readmission with MI, CHF and STROKE.
slide31
Event Canvas Looks Like…

[Earliest of EV1-CKD-ADMIT (And) ]

EV1-CKD-ADMIT: [ All of [CKD : InpatAdmit] WHEN IN [YR2009] WITH [ageGTE18] ]

AND

EV2-HEM GT12 90 ARND: [ All of [HEM : LabTestDate] within 0 to 90 Days Around Event: EV1-CKD-ADMIT ]

AND

EV3-MED EPO 30 AFT: [All of [MED : MedOrderStartDate] within 0 to 30 Days After Event: CKD-ADMIT

Cohort 1: CKD-W-HEM>12-WITH-MED

Cohort 2: CKD-W-HEM>12-WITHOUT-MED

  • [Earliest of EV1-CKD-ADMIT (And) ]
  • EV1-CKD-ADMIT: [ All of [CKD : InpatAdmit] WHEN IN [YR2005] WITH [age>18] ]
  • AND
  • EV2-HEM: [ All of [HEM : LabTestDate] within 0 to 90 Days Around Event: EV1-CKD-ADMIT ]
  • AND
  • EV3-MED: [NOT All of [MED : MedOrderStartDate] within 0 to 30 Days After Event: CKD-ADMIT ]
learning roadmap4
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim and Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
clinical scenario 3 congestive heart failure
Clinical Scenario 3Congestive Heart Failure

Exercise 2: Building a Study

    • Build a Cohort
      • Discharges in March 2012 with CHF
    • Add Two Methods
      • List
      • Add outcome: readmission
  • See handout: In-Class Exercise Two
learning roadmap5
Learning Roadmap

Level: Introductory

  • CLG Core Concepts
  • View Outcome Comparison Study
  • Modify a Cohort (Bactrim & Hyperkalemia)
  • Events, Attributes and Sets (Chronic Kidney Disease)
  • Build a Study (Congestive Heart Failure)
  • Smart Reports
smart reports
Smart Reports
  • Smart Reports in CLG are:
    • Focused reports usually oriented around a single subject
    • Utilize CLG objects (groups, sets)
    • Often have an operational orientation
diagnosis summary report
Diagnosis Summary Report
  • A focused report that shows
    • all diagnoses and associated procedures for a cohort of patients
      • for index event
      • and subsequent/prior events
  • A way to explore patterns of care
  • The coding of this care
    • indirect
    • purchased care
slide38
Demo

Diagnosis Summary Report for a CHF Cohort

don t forget
Don’t Forget!
  • CLG Help
  • HIPAA guidance
  • Citing CLG
  • Performance Improvement vs. Research
clg help
CLG Help
  • Online manuals
    • CLG User Manual
    • Ad hoc Reports
    • Events Definitions
  • Streaming Video
  • Manuals and videos are also available for download from the Web at: http://exploreclg.montefiore.org/clg-resources/becoming-a-clg-user/MHC-Resources.aspx
  • See http://exploreclg.montefiore.org for more information
clg and hipaa
CLG and HIPAA

CLG gives you access to most all patient data.

Discuss: why is this risky?

  • HIPAA Protections:
  • Most analysis done with “limited data set”
  • Supervisor authorization required to access identifiers
  • You are challenged when requesting identifiers:
    • QI Project
    • IRB approved research
    • Patient worklist
  • Off-site use of CLG requires encryption tool
  • You are audited annually
citing clg
Citing CLG

Dozens of posters and manuscripts enabled by CLG.

Give CLG a shout out!

Find methods verbiage in your training folder

or request it from CLGMHSAdministrator.

pi vs research
PI vs. Research

What distinguishes Performance Improvement from Research?

  • In your Training Packet:
  • Registering PI Projects with QM Dept
  • The QI-Research Divide and the Need for External Oversight
  • Oversight of QI: Focusing on Benefits and Risks
  • (request from CLGMHSAdministrator if needed)
  • Institutional Review Board (IRB):
  • Special addendum needed if project accesses data via CLG
learning roadmap advanced
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
review map the ckd study
Review: Map the CKD Study
  • Study Group: patients>=18 years who had at least one admission with Chronic Kidney Disease during the year 2005 AND had a hemoglobin lab test done with a value>12g per deciliter around 90 days of the admission date AND received an inpatient med order of Epoetin Alfa within 30 days of the admission date.
  • Comparison Group: same as study group but without Epoetin Alfa within 30days of the admission
  • Outcomes: mortality within 6mo, readmission within 6mo all cause, with MI, with CHF.

Exercise: fill in the CLG Study Template handout

study designer1
Study Designer

I

Analysis

Groups

review map the ckd study1
Review: Map the CKD Study
  • Study Group: patients>=18 years who had at least one admission with Chronic Kidney Disease during the year 2005 AND had a hemoglobin lab test done with a value>12g per deciliter around 90 days of the admission date AND received an inpatient med order of Epoetin Alfa within 30 days of the admission date.
  • Comparison Group: same as study group but without Epoetin Alfa within 30days of the admission
  • Outcomes: mortality within 6mo, readmission within 6mo all cause, with MI, with CHF.

Exercise: fill in the CLG Study Template handout

ckd events diagram1
CKD Events Diagram

2005

When In

Admissions

>= 18 Years Old

Within

Around 90 Days Admissions

(90 Days Before & After)

CKD Patients With Epoetin Alfa

Lab Test

Within

30 Days After Admissions

Med Order

Epoetin Alfa

Effects of Epoetin Alfa on Hemoglobin

Levels in CKD

ckd events diagram2
CKD Events Diagram

2005

When In

Admissions

>= 18 Years Old

Within

Around 90 Days Admissions

(90 Days Before & After)

CKD Patients With Epoetin Alfa

Lab Test

Within

30 Days After Admissions

NOT

Med Order

Epoetin Alfa

Effects of Epoetin Alfa on Hemoglobin

Levels in CKD

ckd events diagram3
CKD Events Diagram

2005

When In

Admissions

>= 18 Years Old

Within

Around 90 Days Admissions

(90 Days Before & After)

CKD Patients With Epoetin Alfa

Lab Test

Within

30 Days After Admissions

NOT

Med Order

Epoetin Alfa

Effects of Epoetin Alfa on Hemoglobin

Levels in CKD

Mortality within 6 Months

X

Readmission within 6 Months

X

learning roadmap advanced1
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
temporality in groups
Temporality in Groups
  • WHEN IN
    • a calendar period (e.g., 1/1/12 – 3/31/12)
    • a clinical duration (e.g., admit – discharge)
  • WITHIN
    • time from another event (e.g., 30d before admit)
temporality when in calendar duration
Temporality: WHEN IN Calendar Duration

Gatifloxacin was prescribed between 1/1/04 – 3/6/06

temporality when in duration
Temporality:WHEN IN Duration

Durational Events

  • Events with inherent start and stop times

(e.g. Inpatient Admissions, Medication Orders)

Create a cohort of patients who had an ejection fraction of < 35 DURINGan admission for CHF in 2009

temporality within event
Temporality:WITHIN Event

HGB test > 12 WITHIN 90 days of the inpatient admission for CKD

learning roadmap advanced2
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
event collections non unique patients
Event Collections: Non-Unique Patients

Event Collection: All of …

Cohort: Latest of …

  • Good for process of care, productivity and throughput analysis
  • Only difference in Event Canvas is “ALL” at the root condition (INDEX)
learning roadmap advanced3
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • List Method
  • Time in Range
  • HANDS ON: Individual Clinical Questions
demo upload cohort
Demo: Upload Cohort
  • Get template
  • Paste in MRN and index
  • Optional to submit end dates
  • Upload
  • Validate unmatched MRN’s
learning roadmap advanced4
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
time to outcome simple mode
Time to OutcomeSimple Mode

Compare hospitalization rates of well-controlled vs. poorly controlled diabetics

Well Controlled Diabetics = 1 hBa1c >9.5 June 2002-June 2003, subsequent hBa1c <7 within 180-365 days of initial bad test

Poorly Controlled Diabetics = 1 hBa1c >9.5 June 2002-June 2003, no subsequent hBa1c < 7 within 180-365 days of initial bad test

take a look
Take a Look

Demo

  • New study
  • Cohort definitions: controlled vs. uncontrolled diabetics
  • TTO simple mode: outcome is inpatient admission
    • Method options
  • Export patient list

Finished study:

Skip to: Advanced Mode

create new study
Create New Study

1) Click the “+” next to the work studies in Management Panel

2) Study Designer Shows you 3 tabs:

Main – for entering study name and description – this is where you first land

Groups – this is where you can define up to eight study groups (cohorts or event collections)

Methods – you can apply three method types to your study:

Time to Outcome

List

Time in Range

define outcome
Define outcome

Start = either from index date or with blackout period (where outcomes are ignored)

Outcome = an Event Definition (simple mode) or Analysis Definition (advanced) mode

End = Risk window (for Event Definition only)

Method Name and Description

Each method has some method-specific required info

select s tudy g roups
Select Study Groups

Click … button to go to Event Canvas to define a cohort/event collection

Click + to add new groups

Enter group names

tto define the o utcome
TTO: Define the Outcome
  • Click on Methods Tab
  • Click on the ? Outcome shape
tto define the outcome
TTO: Define the Outcome
  • You will see a dropdown of Event Definitions
  • Choose one or the […] button to go to Event Definition Builder
tto define new event as outcome
TTO: Define New Event as Outcome

Right-click on event definitions to add a new event definition

tto event definition builder
TTO: Event Definition Builder

1

2

3

  • Enter a name for this Event Definition
  • Choose an Event
  • Right click on the Definition icon to add defining Event Attributes
  • Click Save or Save as, X to exit

Note, the Event Definition itself has no reference to temporality

tto temporality
TTO: Temporality

1) After creating or choosing your Event Definition, click the down arrow

2) Optional Blackout Period: If you want to ignore outcomes for a certain number of days from index

3) Enter Risk window

tto define end p oint
TTO: Define End Point

Note, the analysis definitions available to terminate the evaluation window are only earliest/latest types

tto other options
TTO: Other Options

And then click Run Method to generate results

tto results demographics1
TTO Results: Demographics
  • 4 tabs:
    • Demographics
    • Target Event
    • All Events
    • Patient List
tto results target event1
TTO Results: Target Event

X axis = time

Y = percent of group achieving the result

Below this are point estimates with % of each group achieving the result within specified periods

tto results patient list1
TTO Results: Patient List
  • Click on the tab of the group you want to see the patient list for
  • Time to = time to first event
  • Occurred = 1 occurred , 0 did not occur
  • Total = total number of outcomes occurred
  • Outcome Event Date = date of first outcome
tto results exporting p atient l ist
TTO Results: Exporting Patient List
  • Choose Export type (excel 2003, 2007 or csv
  • Click the Export button
  • After results are exported, pull the dropdown next to View the exported results and choose data file.
  • An excel window will open
learning roadmap advanced5
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
tto advanced mode
TTO: Advanced Mode

Scenario

Study Group: controlled

Comparison Group: uncontrolled diabetics

Outcome: time to next “follow-up” defined as either

  • next clinic visit, or
  • next glucose test

Advanced because: two events in combo outcome

take a look1
Take a look

Demo

  • Method 2:
add a new m ethod to your s tudy
Add a New Method to Your Study

1) Click on Methods Tab, then click on the “+”

2) You will see the New Method dialog. Select Time to outcome as Method Type

how to get to tto advanced mode
How to Get to TTO Advanced Mode

Click the To Advance label to get to TTO advanced mode

tto advanced mode1
TTO Advanced Mode

Choose an AD from the dropdown or click the … button to enter the Analysis Definition canvas

ad based on earliest of 2 events
AD Based on Earliest of 2 Events

Original Outcome: time to next “follow-up”

defined as either

  • next clinic visit, OR
  • next glucose test

Is the CLG criterion line defined correctly?

run method vs run all
Run Method vs. Run All

You can have multiple methods in a study.

Click Run Method to run only the current method, Run All to run all methods in the study

Be sure to press the Save icon to save results once our study is finished running

learning roadmap advanced6
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
time in range tir
Time in Range (TIR)

TIR Summarizes for each Individual the amount of time spent in a particular range of values

TIR Summarizes for the ENTIRE cohort of patients the %time spent in a particular range of values

Used Mainly for Event Types with Continuous Values (Labs, Findings)

time in range tir1
Time in Range (TIR)

Research Question:

What percent of the last year did this cohort spend in the following hematocrit value ranges:

Must interpolate between lab values.

interpolation rules
Interpolation Rules

Linear interpolation between lab values

Interpolation Interval:

  • define max distance between values to allow interpolation

Carry Forward:

  • Define how long to assume constant lab value if next result is beyond the interpolation interval
tir interpolation rules cont
TIR Interpolation Rules (cont.)

Consider 1 patient’s Hct’s

interpolation

carry forward

X

32 -

Hematocrit

X

X

29 -

X

X

missing

missing

Time 

tir interpolation rules cont1
TIR Interpolation Rules (cont.)

Add quality categories

interpolation

lifespan

High

X

32 -

Hematocrit

X

Target

X

29 -

X

X

Low

missing

missing

Time 

take a look2
Take a look

Demo

control of Hematocrit over 2011

Go to: Questions

tir method1
TIR Method

3.35% of cohort’s patient days spent in “good” category (aka “Target”)

learning roadmap advanced7
Learning Roadmap ADVANCED

Level: Advanced

  • Review of Introductory Concepts
  • Temporality in Groups
  • Event Collections
  • Upload Groups
  • Time to Outcome
    • Simple Mode
    • Advanced Mode
  • Time in Range
  • List Method
  • HANDS ON: Individual Clinical Questions
list method advanced topics
List Method: Advanced Topics

Scenario: CHF cohort, look for latest troponin values, latest sysBP, latest LDL

  • Method 1 for basics (as needed)
  • Method 2: advanced mode with long view
  • Method 3: multiple ADs for covariates

Go to: Orders with text

demo study designer list advanced mode all troponin within 60 days
Demo: Study Designer List, Advanced mode, all Troponin within 60 days
  • Utilizes analysis definitions – all, first or last instance of an AD value can be used
  • Analysis definitions can utilize temporality
  • You can use multiple events in an AD
  • Users can add multiple outcomes to the same list method

Click on To Advanced

study designer list advanced mode
Study Designer: List – Advanced Mode

Click on … button to create a new Analysis Definition

list method analysis definition
List Method:Analysis Definition

Note analysis definition can utilize all, earliest or latest at the root

Note analysis definition can utilize within or when in

list mode advanced wide view
List Mode Advanced: Wide view

One row per patient with potentially multiple outcomes per row in adjacent columns

list mode advanced long v iew
List Mode Advanced: Long View

Multiple rows per patient , one for each outcome

list method advanced covariates
List Method, Advanced -- Covariates
  • Utilizing earliest or latest at the root of analysis definitions you can create a patient list with covariate measures such as:
    • Last systolic blood pressure
    • Last LDL
    • First hba1c > 7
    • Date of last colonoscopy
list method advanced covariates examples
List Method Advanced – Covariates Examples

Utilize earliest or latest at the root.

Note, we can use a WHEN IN with calendar dates

list method advanced covariates1
List Method Advanced, Covariates
  • To show multiple covariates, successively create and choose analysis definitions:
list method advanced covariates2
List Method Advanced, Covariates
  • Note multiple analysis definitions and their attributes on left panel.
  • Choose attributes from each AD and drag over to the right panel. Run in wide mode
list method covariates output
List Method, Covariates output

LDL Value

LDL Test Date

Systolic Date

Systolic Value

Note primary care measures last LDL and last systolic BP next to each other on the same line

transferring files from vdi to local
Transferring Files from VDI to Local

From the military virtual desktop use your Email:

  • Save the files (.xls, .pdf) from CLG to a preferred location on the military virtual desktop.
    • Recommended locations: Desktop or My Documents
  • Using Internet Explorer navigate to webmail
    • webmail.health.mil
  • Login to webmail
transferring files from vdi to local1
Transferring Files from VDI to Local
  • Compose a new mail message
  • Address mail message to yourself.
  • Attach relevant files to mail message by browsing for files saved to preferred location, refer to step 2.
  • Complete the “Subject” and “Body” of the mail message.
  • Send the message
  • Access mail message from your Email on your local workstation
  • Save files to a preferred location on your local workstation.
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