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On-Demand Clinical Intelligence
Clinical Looking Glass Training
Don’t just sit there!
Login and Change Password
1. Open Internet Explorer
2. Enter “https://secure1.afms.mil/CLG” in address
3. Enter Username and Password
4. Under “Virtual Desktops” click on “SG-CLG” hyperlink for Citrix VDI Login
5. Enter “http://clgpoc.afms.mil/CLGNET” in address
6. Enter username: usually first initial+lastname
7. Enter generic password: clg123
8. Change password
9. Save (toolbar at the bottom)
10. Log out
Today
1. Introductions
2. Ground Rules
3. Why Clinical Looking Glass?
4. Introductory Training
5. HIPAA
Welcome to the Future
The Future of Clinical Business Intelligence
Dr. Eran BellinVice President, IT Clinical Research and Development
Montefiore Medical Center
Ground Rules
• Use cell phones outside• Follow me when teaching
– There is time for hands on• Slow me down, ask questions
CLG: Included Data
Labs
Procs
Orders
Meds
DiagnosesDeath
Direct and Purchased Care
Direct Care Purchased Care
% of Encounters in CLG/HSDW
50% 50%
Has a Facility Value Yes No (All are “No Valid Match
Found”)
Associated Labs Yes No
Associated Meds Yes No
ICD9 Diagnoses Yes Yes
CPT and ICD Procedures Yes Yes
Disposition Yes No (all are “No Valid match
Found”)
CLG Value
Quick
Answers
Clinician
Empowerment
Culture
Change
• Ad hoc inquiry• Comparison studies• Patient work lists• Self service
• Performance awareness• Evaluation of interventions• Professional achievement• Creative potential
unleashed
• Measurable success• Clinical unit empowerment• Satisfied patients• Improved health
CLG Introductory Training
Learning Roadmap
Level: Introductory
1. CLG Core Concepts2. View Outcome Comparison Study
3. Modify a Cohort (Bactrim and Hyperkalemia)
4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Study (Congestive Heart Failure)
6. Smart Reports
CLG Core Concepts
1) Analytic rules are non-qualifying2) Method applied to one or more groups3) Methods include:
• Append study data• List / data grid• Crosstabs / pivots• Time to Outcome (survival)• Incidence Density• Time in Range• …more to come
1) Qualifying rules for inclusion2) Index Date (I)
• Patient specific start/enrollment date
3) 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
Groups I
“Reusable research objects”
Analysis
Study = Groups X Analysis
Male diabetics I
2 year survival
Female diabetics I
% days A1C in control
5 yr visit hx per MD
2 yr history of HTN
Next Visit Alerts
When Data Are Not Patient-Centric
1/1/2005 1/1/2006 1/1/2007
0
0 = index date
(EG start therapy)
0000
00
000
1
2
3
4
5
6
7
8
9
10
Patient #
What % of new diabetic patients were controlled in the year 2005? 4 / 10 = 40%
Diabetes Control
= outcome(EG achieve lab value)
0 = patient experience
Patient-Based Analysis of Diabetes Control
Enrollment 1 Year 2 Years
0
0 = index date
= outcome
(EG start therapy)
(EG achieve lab value)
0 = patient experience
0
0
0
0
0
0
00
0
1
2
3
4
5
6
7
8
9
10
Patient #
What % of new diabetic patients were controlled within 1 year? 5 / 10 = 50%
Diabetes Control
(same data, re-sorted)
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 Roadmap
Level: Introductory
1. CLG Core Concepts
2. View Outcome Comparison Study3. Modify a Cohort (Bactrim and Hyperkalemia)
4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Study (Congestive Heart Failure)
6. Smart Reports
Clinical Scenario:Bactrim & Hyperkalemia
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.
Bactrim may cause hyperkalemia when combined with ACE ARBs• 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.
Login, Change PW, go to Study Designer
1. Open Internet Explorer
2. Enter “http://clgpoc.afms.mil/CLGNET” in address bar
3. Enter username: first initial+lastname
4. Enter generic password: clg123
5. Change password
6. Save (toolbar at the bottom)
7. Open Study Designer (Analysis Menu)
8. Open Bactrim study
Wait here
Study Designer
Demo
• Study Designer overview• Results• Criteria• Group definition using:
Skip to Exercise 1
TTO Method Criteria Entry
TTO Results - Demographics
TTO Results – Target Event
TTO Results – All Events
TTO Results – Patient List
Learning Roadmap
Level: Introductory
1. CLG Core Concepts
2. View Outcome Comparison Study
3. Modify a Cohort (Bactrim & Hyperkalemia)4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Cohort
6. Browse a Cohort: List Method
7. Build a Study (Congestive Heart Failure)
8. Smart Reports
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 Roadmap
Level: Introductory
1. CLG Core Concepts
2. View Outcome Comparison Study
3. Modify a Cohort (Bactrim and Hyperkalemia)
4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Study (Congestive Heart Failure)
6. Smart Reports
Clinical Scenario 2Chronic Kidney Disease
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 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.
• 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.
[Earliest of EV1-CKD-ADMIT (And) ] EV1-CKD-ADMIT: [ All of [CKD : InpatAdmit] WHEN IN [YR2005] WITH [age>18] ]
ANDEV2-HEM: [ All of [HEM : LabTestDate] within 0 to 90 Days Around Event: EV1-CKD-ADMIT ]
ANDEV3-MED: [NOT All of [MED : MedOrderStartDate] within 0 to 30 Days After Event: CKD-ADMIT ]
[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
Event Canvas Looks Like…
Cohort 1: CKD-W-HEM>12-WITH-MED
Cohort 2: CKD-W-HEM>12-WITHOUT-MED
Learning Roadmap
Level: Introductory
1. CLG Core Concepts
2. View Outcome Comparison Study
3. Modify a Cohort (Bactrim and Hyperkalemia)
4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Study (Congestive Heart Failure)6. Smart Reports
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 Roadmap
Level: Introductory
1. CLG Core Concepts
2. View Outcome Comparison Study
3. Modify a Cohort (Bactrim & Hyperkalemia)
4. Events, Attributes and Sets (Chronic Kidney Disease)
5. Build a Study (Congestive Heart Failure)
6. 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
• 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
Diagnosis Summary Report Inputs
Demo
Diagnosis Summary Report for a CHF Cohort
Don’t Forget!
• CLG Help• HIPAA guidance• Citing CLG• Performance Improvement vs.
Research
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 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
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
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
Q & A
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method
8. HANDS ON: Individual Clinical Questions
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 Diagram
Study Designer
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 Diagram
Epoetin Alfa
Effects of Epoetin Alfa on Hemoglobin Levels in CKD
CKD Patients With Epoetin Alfa
Admissions
Lab Test
Med Order
>= 18 Years Old
2005 When In
Within
Within
Around 90 Days Admissions(90 Days Before & After)
30 Days After Admissions
CKD Events Diagram
Epoetin Alfa
Effects of Epoetin Alfa on Hemoglobin Levels in CKD
CKD Patients With Epoetin Alfa
Admissions
Lab Test
Med Order
>= 18 Years Old
2005 When In
Within
Within
Around 90 Days Admissions(90 Days Before & After)
30 Days After Admissions
NOT
Epoetin Alfa
Effects of Epoetin Alfa on Hemoglobin Levels in CKD
CKD Patients With Epoetin Alfa
Admissions
Lab Test
Med Order
>= 18 Years Old
2005 When In
Within
Within
Around 90 Days Admissions(90 Days Before & After)
30 Days After Admissions
NOT
Mortality within 6 Months
Readmission within 6 Months
X
X
CKD Events Diagram
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method
8. HANDS ON: Individual Clinical Questions
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
Gatifloxacin was prescribed between 1/1/04 – 3/6/06
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 DURING an admission for CHF in 2009
Temporality:WITHIN Event
HGB test > 12 WITHIN 90 days of the inpatient admission for CKD
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method
8. HANDS ON: Individual Clinical Questions
Event Collections: Non-Unique Patients
MRN INDEX …
111 5/1/10
111 3/13/10
111 1/5/10
222 4/1/10
333 4/15/10
333 4/30/10
MRN INDEX …
111 5/1/10
222 4/1/10
333 4/30/10
Cohort: Latest of …Event Collection: All of …
• Good for process of care, productivity and throughput analysis• Only difference in Event Canvas is “ALL” at the root condition (INDEX)
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups5. Time to Outcome
• Simple Mode• Advanced Mode
6. List Method
7. Time in Range
8. HANDS ON: Individual Clinical Questions
Demo: Upload Cohort
• Get template• Paste in MRN and index• Optional to submit end dates• Upload• Validate unmatched MRN’s
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method
8. HANDS ON: Individual Clinical Questions
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
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 Study1) 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: 1. Time to Outcome2. List3. Time in Range
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 DescriptionEach method has some method-specific required info
Select Study Groups
Click … button to go to Event Canvas to define a cohort/event collection
Click + to add new groups
Enter group names
Define groups in Event Canvas
TTO: Define the Outcome
1. Click on Methods Tab2. Click on the ? Outcome shape
TTO: Define the Outcome
1. You will see a dropdown of Event Definitions2. Choose one or the […] button to go to Event
Definition Builder
TTO: Define New Event as Outcome
Right-click on event definitions to add a new event definition
TTO: Event Definition Builder
1 2
3
1. Enter a name for this Event Definition2. Choose an Event3. Right click on the Definition icon to add defining Event
Attributes4. Click Save or Save as, X to exit
Note, the Event Definition itself has no reference to 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 Point
Note, the analysis definitions available to terminate the evaluation window are only earliest/latest types
TTO: Other Options
And then click Run Method to generate results
TTO: generating results
TTO Results: Demographics
• 4 tabs:– Demographics– Target Event– All Events– Patient List
TTO Results: Target Event
X axis = timeY = percent of group achieving the result
Below this are point estimates with % of each group achieving the result within specified periods
TTO Results: All Events
TTO Results: Patient List
1. Click on the tab of the group you want to see the patient list for2. Time to = time to first event3. Occurred = 1 occurred , 0 did not occur4. Total = total number of outcomes occurred5. Outcome Event Date = date of first outcome
TTO Results: Exporting Patient List
1. Choose Export type (excel 2003, 2007 or csv2. Click the Export button3. After results are exported, pull the dropdown next to
View the exported results and choose data file.4. An excel window will open
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method
8. HANDS ON: Individual Clinical Questions
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
Simple Mode Advanced ModeEvent Definitions (Evs) Analysis Definitions (ADs)
Only One Event in EVs Multiple Events in ADs
No Temporality ADs have Temporality Built In (WhenIN, WITHIN)Note: Only ADs with earliest or latest at the root are accessible in TTO
TTO: Advanced vs Simple Mode
Take a look
Demo• Method 2:
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
Click the To Advance label to get to TTO advanced mode
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
Original Outcome: time to next “follow-up” defined as either
next clinic visit, ORnext glucose test
Is the CLG criterion line defined correctly?
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
Punch line: Follow-up is the Same
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method8. HANDS ON: Individual Clinical Questions
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 (TIR)
Research Question:
What percent of the last year did this cohort spend in the following hematocrit value ranges:
Must interpolate between lab values.
Time in Range (TIR)
Range Label Lab value limits Meaning
Too High Hct >= 32 Bad
Normal Hct >= 29 and Hct < 32
Good
Too Low Hct < 29 Bad
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
Interpolation Rules
Time
Hem
ato
crit
32 -
29 -
X
X
X
X
X
Consider 1 patient’s Hct’s
interpolationcarry forward
missing missing
TIR Interpolation Rules (cont.)
Time
Hem
ato
crit
32 -
29 -X
X
X
X
X
Add quality categories
interpolationlifespan
missing missingLow
Target
High
TIR Interpolation Rules (cont.)
Take a look
Demo
control of Hematocrit over 2011
Go to: Questions
TIR Rule Set
TIR Method
TIR Method
3.35% of cohort’s patient days spent in “good” category (aka “Target”)
Learning Roadmap ADVANCED
Level: Advanced
1. Review of Introductory Concepts
2. Temporality in Groups
3. Event Collections
4. Upload Groups
5. Time to Outcome• Simple Mode• Advanced Mode
6. Time in Range
7. List Method8. HANDS ON: Individual Clinical Questions
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
• 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
Click on … button to create a new 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
One row per patient with potentially multiple outcomes per row in adjacent columns
List Mode Advanced: Long View
Multiple rows per patient , one for each outcome
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
Utilize earliest or latest at the root.
Note, we can use a WHEN IN with calendar dates
List Method Advanced, Covariates
• To show multiple covariates, successively create and choose analysis definitions:
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
Note primary care measures last LDL and last systolic BP next to each other on the same line
LDL Value LDL Test Date Systolic Value Systolic Date
Transferring Files from VDI to Local
From the military virtual desktop use your Email:
1.Save the files (.xls, .pdf) from CLG to a preferred location on the military virtual desktop. – Recommended locations: Desktop or My Documents
2.Using Internet Explorer navigate to webmail – webmail.health.mil
3.Login to webmail
7. Compose a new mail message
8. Address mail message to yourself.
9. Attach relevant files to mail message by browsing for files saved to preferred location, refer to step 2.
10. Complete the “Subject” and “Body” of the mail message.
11. Send the message
12. Access mail message from your Email on your local workstation
13. Save files to a preferred location on your local workstation.
Transferring Files from VDI to Local
Q & A