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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 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 • 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 • Introductions • Ground Rules • Why Clinical Looking Glass? • Introductory Training • HIPAA
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 • Use cell phones outside • Follow me when teaching • There is time for hands on • Slow me down, ask questions
CLG: Included Data Labs Meds Procs Diagnoses Death Orders
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 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 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 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 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 • 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 • 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 • 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 • 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 I Analysis Groups
Demo • Study Designer overview • Results • Criteria • Group definition using: Skip to Exercise 1
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 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 • 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 • 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.
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 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 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 • 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 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
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
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 • 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 Designer I Analysis Groups
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 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