Presentation on theme: "4th Annual Healthcare Informatics Symposium"— Presentation transcript:
1 4th Annual Healthcare Informatics Symposium Design and Implementation of a Diabetes Medication Computer Assisted Decision Support (CADS) System4th Annual Healthcare Informatics SymposiumApril 29th, 2011Richard ‘RJ’ KedzioraIn partnership with several leading researchers and endocrinologists (Rodbard &Vigersky) at Walter Reed Army Medical Center with support and funding from the Army Telemedicine and Advanced Technology Research Center (TATRC), we have developed and published a CADS application for the management of patients with Type 2 Diabetes who are on oral agents. The CADS program simplifies the work of the primary care provider by automatically making medication recommendations based on an established consensus algorithm integrating the essential information necessary including the patient’s blood glucose data upload from home, current and previous medications, diagnoses, and current laboratory data. Medication regimen recommendations include modifying the existing regimen, increasing or decreasing the current medication(s) used and/or adding additional oral agents to better control the patient’s diabetes. A one-year multi-site IRB-approved, randomized controlled trial is scheduled to begin the summer of 2011 to test the clinical efficacy of the system. Additional work is scheduled to expand the rules to include Type 1 Diabetes and multiple daily insulin doses (MDI). This presentation will provide an overview of the system and discuss the process of designing and implementing the clinical algorithms within the Comprehensive Diabetes Management Program (CDMP), an open source disease management application. Particular attention will be focused on the decisions and challenges in implementing the complex clinical rules and the technology chosen to implement the solution.
2 Funding / Disclosures Founding Partner/Owner - Estenda Solutions Funding fromU.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. MurthaPI on grant COL. Robert Vigersky M.D. at Walter Reed Army Medical Center
3 The ProblemNot enough endocrinologist to treat patients with diabetes – most care is managed by primary care doctorsMost patient’s not goal (A1C 6.5 – 7%)SMBG IssuesSMBG not used effectively by patients / providersSMBG perception is that it is not used to adjust medicationsLarge number of drug and combinationsTherapy is not adjusted frequently enough
4 Potential Medication Combinations Drug classes include: biguanide, DPP-4 inhibitor, GLP-1 agonist, secretagogue, TZD, AGI, and basal insulinExcluded: Colesevelam and Bromocriptine68 potential treatment combinations8 mono26 dual31 triple3 quadrupleDual : (M + DPP-4, M + TZD, TZD + GLP-1)Triple : (M + DPP-4 +TZD, M + GLP-1 + AGI)
5 The Solution - CADSDesigned 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 byCOL. Robert Vigersky, M.D. - Director, Diabetes Institute, Endocrinology Service, Department of Medicine, Walter Reed Army Health Care System, Washington DCDavid Rodbard, M.D. – Biomedical Informatics Consultants, LLC, Potomac, Maryland
6 JourneyMultiple facilitated group clinical chart reviews to reach consensusInitial standalone prototype development using CLIPS and Microsoft ASP – early 2000sExperimented with DROOLS moved to table-driven algorithm coded in JavaProduction system coding and integration with CDMPClinical Trial 2011 – 2012 and beyondFDA Validation
7 Input Age, Gender, Type of Diabetes Self-managed blood glucose data (SMBG)Current and past medicationsAdverse ReactionsLabs (A1C, ALT, Creatinine)Significant DiagnosesRenal, Hepatic, Gastrointestinal, CardiacTarget A1C
11 SMBG Testing Protocol For 3 months Twice daily (or more depending on DR. discretion)Once a weekBefore meals (x3) and bedtime = 4 testsOnce a monthBefore and 2 hours after meals (x3), bedtime and night at approximately 3AM = 8 tests
12 Pre-Analysis Availability of SMBG SMBG correlation with most recent A1cIdentification of problem time-frames based on SMBG dataHypoglycemiaHyperglycemiaVariabilityTime frames – before breakfast, after lunch
13 Analysis Overall quality of glycemic control Effectiveness of SMBG testingInappropriate medication combinationsExisting Medication ContraindicationsAge, Gender, Labs, DiagnosesBased on SMBG profile analysis and medication effectivenessFirst, address HypoglycemiaThen address HyperglycemiaStill make recommendations if not enough data, but mark as suspect
14 Algorithm for Treatment of Type 2 Diabetes Diet and ExerciseIf A1C > 6.5%Monotherapy or Combination TherapyAdequateNot adequateFollow-up q 3 moOther Oral CombinationsAdequateNot adequateFollow-up q 3 moOral Agent Plus Insulin at Bedtime(Glargine or NPH)AdequateNot adequateFollow-up q 3 moSplit-Mixed Insulinor Lispro or Aspart qac+ Glargine or NPH qhs
15 RecommendationsModify the existing regimen because of contraindicationsIncrease or decrease the dosage of current medication(s)Add additional oral agents/basal insulin5+ medications or 4 with hyperglycemia - recommendation to consult endocrinologistContraindications related to age, labs and diagnosesIncrease only if patient is not already on ½ max of FDA recommended dosage.
16 Additional Output Where testing can be improved FDA 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 PeriodMin, Max, Average, Standard Deviation% high, % low based on thresholds
17 Sensitivity to being authoritarian Suggestion vs. CommandMultiple suggestionsEducation of clinicians
23 Algorithm Development Started with Expert Rules SystemInitially used CLIPSMigrated to DROOLSFinal solution - Table-driven logic with algorithm coded in JavaNumber of combinationsAbility for versioning and customization by individual non-rule experts
25 Next StepsA one-year multi-site IRB-approved, cluster-randomized controlled trialExpand rule base to includeInsulin dependant Type 2Type 1Expanded pattern recognition and treatment plansPost-prandial fluctuationsTrends during day or nightHypoglycemia followed by rebound "Somogyi reaction“Dawn Phenomenoncluster-randomized, controlled, clinical trial involving 30 PCPs who will each recruit approximately 19 patients from their respective geographic site.There will be up to 570 patients and 30 primary care providers in 3 geographic regionsTrial – recently extended to a second year – controls become test subjects
26 PublicationRodbard and Vigersky, Design of a Decision Support System to Help Clinicians Manage Glycemia in Patients with Type 2 DiabetesJournal of Diabetes Science and Technology,Volume 5, Issue 2, March 2011
28 CDMP BackgroundComplete 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:
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