1 / 48

Connecting Drugs and Lab Results to Prevent Inpatient Medication Errors

Connecting Drugs and Lab Results to Prevent Inpatient Medication Errors . Linking Pharmacy and Data for Better Care Part 3: Concepts and Prospects. January 20, 2011 1:30pm – 2:30pm CST Voice conferencing: 513-241-1028 Conference ID: 40278 Participant, Please mute your phone by pushing *6

parson
Download Presentation

Connecting Drugs and Lab Results to Prevent Inpatient Medication Errors

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Connecting Drugs and Lab Results to Prevent Inpatient Medication Errors Linking Pharmacy and Data for Better CarePart 3: Concepts and Prospects January 20, 2011 1:30pm – 2:30pm CST Voice conferencing: 513-241-1028 Conference ID: 40278 Participant, Please mute your phone by pushing *6 Gordon Schiff MD Associate DirectorCenter Patient Safety Research and Practice Brigham & Women’s Hospital -Boston Associate Professor of Medicine Harvard Medical School Clinical Director UIC TOP-MED CERTCo-investigator BWH CERT This project was supported by grant number U18HS016973 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

  2. Schiff Arch Intern Med 2003

  3. Hug JGIM 2010

  4. Feldstein Arch Int Med 2006

  5. - Speed is everything; CDS needs to be easy to use and not time consuming; must actually save time - Anticipate needs and delivery in real time. - CDS needs to fit into the user’s workflow. - Offer alternatives rather than trying to stop an action. -Simple interventions work best (single screen of info). -The more data elements requested, the less likely the guideline will be implemented -Signal to noise is bedeviling, important, improvable. CDS Lessons, Caveats Adapted from Bates, Ten Commandments for CDS. JAMIA 2003

  6. -Monitor impact of interventions and act on findings and lessons. Including frequencies, satisfaction, glitches Continuous improvement, incorporate users feedback -Think about who will be receiving messages, when -CDS often turned off, before, during after implementation Signal of paradigm failure -Its about leadership, policy, goals, communication change management, not technology per se Mandatory, supportive adoption (VA) More Lab-Pharmacy Link Relevant CDS Lessons

  7. Leapfrog Tests of CPOE Systems Most Fail Lab-Pharm Checks Metzger Health Affairs 2010

  8. Metzger Health Affairs 2010

  9. ItAin’t Just Alerts National Quality Forum (NQF), Driving Quality—A Health IT Assessment Framework for Measurement: A Consensus Report, 2010.

  10. National Quality Forum (NQF), Driving Quality—A Health IT Assessment Framework for Measurement: A Consensus Report, 2010.

  11. National Quality Forum (NQF), Driving Quality—A Health IT Assessment Framework for Measurement: A Consensus Report, 2010.

  12. Piecing Together the Global Picture

  13. Critical LabF/up POC Testing Teamwork Roles Handoffs Efficiency Med Legal Liability CDS Rules Alerts System vs. MD vs. Patient Responsibilities Anticoag Monitoring Test Timing Test Appropriateness Diagnosis Error SPC Rx Dosing Tight Control Data Mining Costs Tests Drugs Drug Marketing Safety PharmacoGenomics

  14. Linking Pharmacy and Data for Better Care Part 3: Lab↔Med Linkage Decision Support:Interactive Discussion on Use of Project Tools William Galanter MD/PhD Medical Director, Clinical Information SystemsChair Pharmacy & Therapeutics Committee Co-investigator UIC TOP-MED CERTDepartment of Medicine/Department of Pharmacy Practice University of Illinois at Chicago (UIC) This project was supported by grant number U18HS016973 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

  15. Outline -Background of Lab↔Med Linkage decision support -The development of high priority Lab↔Med pairs -Results of the first phase of pairs -Issues Cost/Benefit Regulators/Leap Frog/Meaningful use Relationship with CPOE Timing of report Dissemination Customization Bureaucracy Lack of lab testing -How can we help each other? -Where to go from here?

  16. Synchronous Alerts (synchronous to CPOE) CPOE Clinical Data Alert Registration EMR Rules Engine

  17. Alerts for Contraindication Alert EMR Post-Alert Post-Alert Post-Alert* (61) Post-Alert Lab results Provider MODERATECrClest 30-50 MILDCrClest50-60 SEVERECrClest<30 ALL *P=<0.001 Proportion of patients with renal dysfunction receiving Metformin when order started by clinician 4-months pre-alert vs.. 4-months post-alert Pre-Alert (63) 100% 80 60 40 20 0 Galanter et al. J Am Med Inform Assoc. 2005 May-Jun;12(3):269-74

  18. Synchronous Alerts Alert EMR Lab results Provider Patient Days on Elevated K+ vs. time Synch Alerts

  19. Asynchronous (to CPOE) Alerts CPOE Registration Clinical Data Clinical Inbox Alert Alert Alert Alert Alert Pharmacy Printer Nurse Physician EMR Rules Engine

  20. Asynchronous Alerts Alert Post-Alert 100% 80% Lab results 60% Proportion of patients Provider Pre-Alert 40% 20% 0 0 1 12 24 Hours Compliance with alert recommendationsLow [Mg++] when on Digoxin EMR Galanter et al. J Am Med Inform Assoc. 2004 Jul-Aug;11(4):270-7.

  21. Asynchronous Alerts Alert 100 EMR 80 60 40 Lab results 20 Provider P=0.05 0 5000 10000 15000 20000 25000 0 Exposure to Metformin after a new eGFR <60 % Patients receiving Metformin Post Pre Minutes after new lab

  22. Asynchronous Alerts Alert EMR Lab results Provider Discontinuation rate of K+ Supplementation with ↑K+ 100% 50% 0% hours

  23. Asynchronous Alerts Alert EMR Lab results Provider Discontinuation rate of K+ Supplementation with ↑K+ 100% 50% 0%

  24. The timing of Lab↔Med CDS? Synchronous -Requires CPOE -Compliance is a problem -Immediate feedback Real-time asynchronous -Requires a 24o communication channel -Immediate feedback Non real-time asynchronous reports -Does not require CPOE (~<20% of US Hospitals in 2009*) -Can use a dedicated team for a short period of time, thus adds reliability -delayed feedback *Health Affairs, 28, no. 2 (2009): 404-414 Clin Pediatr (Phila). 2009;48:389-396.

  25. Non real-time asynchronous Alerts EMR Rules Engine Clinical Inbox Alert Alert Alert Alert Alert Pharmacy Printer Nurse Physician

  26. Development of an Asynchronous Daily Lab↔Med Report Collaborators University of Illinois at Chicago Bruce L. Lambert, Ph.D., Rob Didomenico, PharmD, Mike Koronkowski, PharmD, Shengsheng Yu, MS, Fang-Ju Lin, BPharm, MS, Jessie Moja, MD Brigham and Women’s Hospital Gordon D. Schiff, MD Stroger Hospital Shane Borkowsky, MD, Mary Wisniewski RN, MSN University of Washington Beth Devine PharmD, MBA, PhD, Tom Payne, MD Cerner Corporation David McCallie MD, Margaret Kolm MD

  27. Results of the Delphi Exercise Top 24 pairs Yu, S. Galanter WL, Didomenico, RJ, Borkowsky S, Schiff G, Lambert B. Consensus list of priority drug-lab linkages for an inpatient asynchronous alert program: Results of a Delphi survey. Am J Health-Syst Pharm. 2011. Mar 1;68. In press.

  28. First Phase of Lab↔Med pairs implemented at UIMCC

  29. The Report Abe Lincoln MR#0123456789 Richard Daley MR#0123456789 Ronald Reagan MR#0123456789

  30. Performance of AlertsFirst 100 days of First Phase

  31. Example Pt on ACE Aware of lab, forgot to act on med Report Asked to stop ACE

  32. Example Not aware of lab, can’t act on med

  33. Example Not aware of prior result, not aware of result,can’t act on med K+ Creatinine

  34. Example No good indication, poor f/u labs, aware of result,acted on one med, forgot the other Stop Aldactone Stop ACE Admitted, placed on ACE/Aldactone for HTN?

  35. Issues Cost/Benefit -How to calculate ROI? -Problem of small numbers -Very few “abnormal links” turn into clinically relevant events -Severe ADE’s are rare -How many FTE to implement?

  36. Issues Regulators and measures of Quality CMS Quality Indicators? Leap Frog -Only interested in synchronous alerts -No credit for asynchronous CDS work Meaningful use “for eligible hospitals and CAHs at §495.6(g)(10)(ii) to “Implement one clinical decision support rule.” “In the proposed rule, we said that clinical decision support at the point of care is a critical aspect of improving quality, safety, and efficiency.” -Does Asynchronous CDS count? Is it a rule?

  37. Issues Relationship with CPOE Can supplement CPOE with Synch CDS Can supplement CPOE without Synch CDS Can add safety without CPOE -A quick win Can work in a hybrid paper/CPOE system Is independent of CPOE -Only need lab and pharmacy IS systems and a server to link the two.

  38. Issues Timing of report Frequency -Running it very frequently will decrease the potential lag from problem to resolution, but manpower may become unmanageable, assurance of resolution may be lost -Running it daily would allow strong assurance of resolution, but long lag times. Time of day -running immediately after labs are reported will increase yield -Giving clinicians some time to act will decrease annoyance and work in managing the report.

  39. Issues • Dissemination • Customization -Technical • -Cultural • -Clinical • Bureaucracy

  40. Issues • Customization -Technical • -EMR/ (Lab/Pharm systems) vendor's • -database/data model • -Variable names/tests (POCT/Normal's/panels) • -Types of tests; Critical care panel, ABG, VBG • -Formulary issues • -Drug databases (multum, FDB, etc...) • -Cultural • -Practice Variation • -Control and ownership • -Clinical • -Patients/Dz’s/specialties • -Lab differences • -Changes in sensitivity/specificity based on • clinical differences

  41. Issues Dissemination Bureaucracy -Committee’s -Vetting (To vet was originally a horse-racing term, referring to the requirement that a horse be checked for health and soundness by a veterinarian before being allowed to race. Thus, it has taken the general meaning "to check".) -Med/legal -Institutional priorities -TJC -Meaningful Use -Patient Safety Goals

  42. Issues Variation or Lack of lab testing -Variations in lab testing will change the sensitivity, annoyance, workload -If there is a problem and no one is measuring it, the report will not work -In the long run ancillary order decision support can help with this

  43. Issues Where to go from here? -TOPMED Cert -Validation of what we have implemented -More pairs to be added -Try to measure value -How can we help any interested sites? -Potential dissemination for other venues; NH, Ambulatory

  44. Issues How can we help each other? -Suggestions for us? -What help can we give you?

  45. Some Topics for Discussion Issues Cost/Benefit Regulators/Leap Frog/Meaningful use Relationship with CPOE Timing of report Dissemination Customization Bureaucracy Variation/Lack of lab testing How can we help each other? Where to go from here?

  46. Resources Clinical logic for the first set of alerts can be found at; http://www.uic.edu/com/dom/gim/TOPMED/Logic-Phase1.pdf A list of all the pairs can be found at; http://www.uic.edu/com/dom/gim/TOPMED/Pairs.pdf An excellent source of references and an explanation of the Delphi process can be found in the reference below when available; Yu et al. Consensus list of priority drug-lab linkages for an inpatient asynchronous alert program: Results of a Delphi survey. AJHP. 2010 In press.

More Related