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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


Direct and purchased care

Direct and Purchased Care


Clg value

CLG Value


Clg introductory training

CLG Introductory Training


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


On demand clinical intelligence

Demo

  • Study Designer overview

  • Results

  • Criteria

  • Group definition using:

    Skip to Exercise 1


Tto method criteria entry

TTO Method Criteria Entry


Tto results demographics

TTO Results - Demographics


Tto results target event

TTO Results – Target Event


Tto results all events

TTO Results – All Events


Tto results patient list

TTO Results – Patient List


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


Clinical scenario 2 chronic kidney disease

Clinical Scenario 2Chronic Kidney Disease


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.


On demand clinical intelligence

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


    Diagnosis summary report inputs

    Diagnosis Summary Report Inputs


    On demand clinical intelligence

    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


    On demand clinical intelligence

    Q & A


    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


    Ckd events diagram

    CKD Events Diagram


    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


    Define groups in event canvas

    Define groups in Event Canvas


    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 generating results

    TTO: generating 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 all events1

    TTO Results: All Events


    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


    Tto a dvanced vs simple m ode

    TTO: Advanced vs Simple Mode


    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


    Punch line follow up is the same

    Punch line: Follow-up is the Same


    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 rule set

    TIR Rule Set


    Tir method

    TIR Method


    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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