4TH ANNUAL HEALTHCARE INFORMATICS SYMPOSIUM

APRIL 29TH, 2011

RICHARD ‘RJ’ KEDZIORA

Design and Implementation of a Diabetes Medication Computer

Assisted Decision Support (CADS) System

Funding / Disclosures

Founding Partner/Owner - Estenda SolutionsFunding from

U.S. Army Medical Research and Materiel Command (USARMC) AMEDD Advanced Medical Technology Initiative (AAMTI) program.

Congressionally Directed Medical Research Programs administered by Air Force in partnership with University of Pittsburgh Medical Center - sponsored by the honorable U.S. Representative John P. Murtha

PI on grant COL. Robert Vigersky M.D. at Walter Reed Army Medical Center

The Problem

Not enough endocrinologist to treat patients with diabetes – most care is managed by primary care doctors

Most patient’s not goal (A1C 6.5 – 7%)SMBG Issues

SMBG not used effectively by patients / providers SMBG perception is that it is not used to adjust

medications

Large number of drug and combinationsTherapy is not adjusted frequently enough

Potential Medication Combinations

Drug classes include: biguanide, DPP-4 inhibitor, GLP-1 agonist, secretagogue, TZD, AGI, and basal insulin

Excluded: Colesevelam and Bromocriptine68 potential treatment combinations

8 mono 26 dual 31 triple 3 quadruple

The Solution - CADS

Designed for primary care doctors to assist in better decision-making in modifying patient’s drug regimen to bring their blood glucose into better control.

Currently Type 2 (Type 1 planning)Idea, concept and rules developed by

COL. Robert Vigersky, M.D. - Director, Diabetes Institute, Endocrinology Service, Department of Medicine, Walter Reed Army Health Care System, Washington DC

David Rodbard, M.D. – Biomedical Informatics Consultants, LLC, Potomac, Maryland

Journey

Multiple facilitated group clinical chart reviews to reach consensus

Initial standalone prototype development using CLIPS and Microsoft ASP – early 2000s

Experimented with DROOLS moved to table-driven algorithm coded in Java

Production system coding and integration with CDMP 2009-2010

Clinical Trial 2011 – 2012 and beyondFDA Validation

Input

Age, Gender, Type of DiabetesSelf-managed blood glucose data (SMBG)Current and past medications

Adverse Reactions

Labs (A1C, ALT, Creatinine)Significant Diagnoses

Renal, Hepatic, Gastrointestinal, Cardiac

Target A1C

SMBG Testing Protocol

For 3 months Twice daily (or more depending on DR. discretion) Once a week

Before meals (x3) and bedtime = 4 tests Once a month

Before and 2 hours after meals (x3), bedtime and night at approximately 3AM = 8 tests

Pre-Analysis

Availability of SMBGSMBG correlation with most recent A1cIdentification of problem time-frames based

on SMBG data Hypoglycemia Hyperglycemia Variability

Analysis

Overall quality of glycemic controlEffectiveness of SMBG testingInappropriate medication combinationsExisting Medication Contraindications

Age, Gender, Labs, Diagnoses

Based on SMBG profile analysis and medication effectiveness First, address Hypoglycemia Then address Hyperglycemia

Algorithm for Treatment of Type 2 Diabetes

Monotherapy or Combination TherapyMonotherapy or Combination Therapy

Diet and ExerciseDiet and Exercise

If A1C > 6.5%

Adequate Not adequate

Follow-up q 3 mo

Other Oral CombinationsOther Oral Combinations

Oral Agent Plus Insulin at BedtimeOral Agent Plus Insulin at Bedtime(Glargine or NPH)(Glargine or NPH)

Split-Mixed InsulinSplit-Mixed Insulinor or LisproLispro or or AspartAspart qacqac+ + GlargineGlargine or NPH or NPH qhsqhs

Adequate Not adequate

Follow-up q 3 mo

Adequate Not adequate

Follow-up q 3 mo

Recommendations

Modify the existing regimen because of contraindications

Increase or decrease the dosage of current medication(s)

Add additional oral agents/basal insulin5+ medications or 4 with hyperglycemia -

recommendation to consult endocrinologist

Additional Output

Where testing can be improvedFDA Warnings

Rosiglitazone use has been severely restricted by the FDA because of concerns that it causes an increased number of cardiovascular events. Continued use requires your patient be enrolled in a risk evaluation and mitigation strategy program established by GlaxoSmithKline. You should consider switching this patient to pioglitazone at an equivalent dose…

SMBG Profile by Time Period Min, Max, Average, Standard Deviation % high, % low based on thresholds

Algorithm Development

Started with Expert Rules System Initially used CLIPS

Migrated to DROOLSFinal solution - Table-driven logic with

algorithm coded in Java Number of combinations Ability for versioning and customization by individual

non-rule experts

Next Steps

A one-year multi-site IRB-approved, cluster-randomized controlled trial

Expand rule base to include Insulin dependant Type 2 Type 1

Expanded pattern recognition and treatment plans

Post-prandial fluctuations Trends during day or night Hypoglycemia followed by rebound "Somogyi reaction“ Dawn Phenomenon

Publication

Rodbard and Vigersky, Design of a Decision Support System to Help Clinicians Manage Glycemia in Patients with Type 2 Diabetes Journal of Diabetes Science and Technology, Volume 5, Issue 2, March 2011

Thank you!

Richard ‘RJ’ Kedziorarkedziora@estenda.com Office: (610) 834-2908Cell: (610) 772-3989

CDMP Background

Complete customizable web-based clinical application for management of patients with chronic disease.

Based on the Chronic Care Model, it was originally designed for military healthcare to better manage patients with diabetes.

Evolved into a generalized chronic disease and population health management system supporting the Patient Centered Medical Home model. 

For details visit: http://cdmp.estenda.com