4 TH ANNUAL HEALTHCARE INFORMATICS SYMPOSIUM APRIL 29 TH, 2011 RICHARD RJ KEDZIORA Design and...
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Transcript of 4 TH ANNUAL HEALTHCARE INFORMATICS SYMPOSIUM APRIL 29 TH, 2011 RICHARD RJ KEDZIORA Design and...
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’ [email protected] 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