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Using CDSS FOR Appropriate Dosing of Antibiotics with Reduced Renal Function

Using CDSS FOR Appropriate Dosing of Antibiotics with Reduced Renal Function. Presented By: Kwavi Agbeyegbe, Sam Ruffing, Michael Peterson MED INF 406-DL FALL 2010. Identify the Problem.

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Using CDSS FOR Appropriate Dosing of Antibiotics with Reduced Renal Function

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  1. Using CDSS FOR Appropriate Dosing of Antibiotics with Reduced Renal Function Presented By: Kwavi Agbeyegbe, Sam Ruffing, Michael Peterson MED INF 406-DL FALL 2010

  2. Identify the Problem • Antibiotics are one of the most widely used classes of drugs in hospitals and account for one-third of total pharmacy cost. • Suboptimal dosing decisions are the most common reason for inappropriate antibiotic prescribing in the hospital setting, with the majority of errors occurring in the prescribing phase. • It is believed 25-50% of all prescribed antibiotics are inappropriate in respect of drug choice, dose administered or duration of treatment (Ena,1998)

  3. Identify the Problem • Antibiotics which are eliminated from the human body by renal excretion, are inappropriately dosed in an estimated 18-26% of patients (Nicholas,2009). • The estimated prevalence of impaired renal function (GFR<60 ml/min/1.73m2) is 13% for men and 36% for women over the age of 65. • Dosing of renal cleared antibiotics is very complex, it requires complicated dosing algorithms and pharmacokinetic monitoring.

  4. Antibiotics • Antibiotics are eliminated from our bodies by basically two routes. • * Renal elimination • * Metabolized by the liver • Antibiotics can be cleared by one route, both routes, or any proportion of either route. • Our CDSS will focus on antibiotics that required a reduction in dosage or kinetic monitoring when renal function is diminished. • Examples: Quinolones , Aminoglycosides and Vancomycin.

  5. Renal Function Renal Function Decreasing as patients get older (COOK, 2007) Different Calculation Methods: Glomular Filtration Rate (GFR), Creatinine Clearance (CrCl)

  6. Negative Effects • Adverse Drug Events: Nephrotoxicity, Ototoxicity, Cardiotoxicity…. • Economic Cost: Increased length of stay, higher cost for monitoring, increased medication costs. • Societal Cost: Increased Insurance cost, Loss of antibiotic efficacy, lower quality of care.

  7. Antibiotic Dosing Model • Our CDSS Antibiotic dosing model requires data from multiple sources: ADT, Lab, Pharmacy, EMR, Clinics • Baseline data required: Age, sex, height, allergies, diagnosis, infection site, current drug therapy, WBC with diff, albumin. • Lab work-up: Scr, BUN, cultures • Loading dose based on ideal body weight, and dosing interval determined by renal function.

  8. Monitoring Parameters • Trough and Peak levels at steady state • Measuring SrCr every two days or every day in unstable renal function • Weigh patient every two to seven days • Measure and monitor urine output daily • When the patient is on an aminoglycoside baseline and weekly audiograms, and check for tinnitus or vertigo daily.

  9. HMS ADT HMS EMR HMS Nursing Doc Epic Clinic EPIC Radiology EPIC Pharmacy EPIC Beaker LIS Interface Engine Physician/ Pharmacist TheraDoc Knowledge Base Antibiotic Assistant Clinical Alerts ADE Assist ICP Assist Alerts

  10. EPIC uses HL7, ANSI X 12, XML HMS is ODBC compliant CCOW Real time interface TheraDoc-HL7, LOINC, NHSN, PHIN, MS, SNOMED-CT and Rx Norm

  11. 1. Physician selects an Antibiotic-Initial Order • 2. All known needed data elements are pulled to one screen: • Allergies • Current/Past Renal Dx • Serum Creatinine, BUN, WBC w/diff and albumin results • Demographics • Radiology results-Chest X-rays findings • Pathology findings if relevant 4. Physician selects agree/change If order selection is changed drop down box with reasons will require completion Once order is completed: Peak and trough dates and times will be ordered eMAR will populate Antibiotic Selections with peak and trough draw times 3. Recommendations include Antibiotic dosage/ selection Peak / trough levels ordered Repeat BUN/Creatinine ordered

  12. Alerts To : Physician and Pharmacist Micro results on culture and sensitivity with new recommendations for Antibiotic choice, if appropriate To: Nurses/phlebotomist Alerts for peak and trough times for drawing To: Physicians Alerts from nursing documentation/Lab that may signal signs and symptoms of toxicity

  13. Evaluation • To implement a knowledge-based clinical decision support system for clinical information systems, it is crucial to verify and validate the knowledge base. (Kim, Kim, Cho, Lee, & Kim, 2010).

  14. Evaluation • The requirements of the CDSS should meet the user requirements and also satisfy all the regulatory specifications. • Methods and techniques used in the Verification and Validation should be designed carefully with verification taking place before validation. • Software validations should not be left to the closing phases of the project.

  15. Verification and Validation • Building the system right • Building the right system

  16. Verification • Requirements Specification gathering • Functional design • Internal systems design • Code verification

  17. Verification • Walk through • Buddy Checks • Inspection

  18. ValidationTesting Strategy • Black box testing • Equivalence partitioning testing

  19. Validation • User Acceptance Testing/Validation • Functional Testing/Validation • Integration Testing/Validation • Code Validation

  20. Verification levels with corresponding Validation tests. Verify Verify Verify Code Verification Code Validation Verify

  21. Under-testing vs Over-testing • However, the FDA is realistic enough to recognize that a developer cannot test forever. • Under-testing vs. Over-testing

  22. Benefits of Verification and Validation Benefits of Verification and Validation (Chojnowski, 2008)

  23. System limitations • Physician autonomy • Computer literacy • IT Support Availability • Impact on workflow

  24. System limitations • Training • Buy-in from clinicians and administrative staff • Lack of standards for CDSS development

  25. Future Extensions • Study the prescribing behavior and structure of errors when physicians override the default value. • Open source Standard for development of CDSS • Post-implementation review

  26. Conclusion • Stakeholders have to be informed and involved prior, during and after implementation. • CDSS is more effective when combined with CPOE. • CDSS System review concludes aided drug dosing provides an overall benefit. • To increase adoption, CDSS should be integrated into existing workflow.

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