1. CORE LABORATORY QA PROGRAM

2. Why have a QA Program? JCAHO Standard PI.1.10: The organization collects data to monitor its performance. Standard PI.2.10: Data are systematically aggregated and analyzed. Standard PI.3.10: Information from data analysis is used to make changes that improve performance and patient safety and reduce the risk of sentinel events.

3. Why have a QA Program? CLIA ’88 Standard 493.1239: a-The laboratory must establish written policies and procedures for ongoing mechanism to monitor, assess and correct problems identified in the general laboratory systems requirements. b-The general laboratory systems quality assessment must include a review of the effectiveness of corrective actions taken to resolve problems, revisions of policies and procedures necessary to prevent recurrence of problems. c-The laboratory must document all general laboratory systems quality assessment activities.

4. Monitor Operational Systems Pre-analytical: test orders, collection, transportation, preparation for analysis Pre-analytical: test orders, collection, transportation, preparation for analysis Analytical: test analysis Analytical: test analysis Post-analytical: availability of results (TAT), test reports, transmission of results, comments and interpretations, notification of critical results Post-analytical: availability of results (TAT), test reports, transmission of results, comments and interpretations, notification of critical results

5. Quality Assurance (QA) Monitors Taking A Pulse Monitor all operational systems. Define a target. Identify failures. Revise, delete, add monitors as identified. Multi-departmental, as needed.

6. Taking Pulses Pre-analytical 1-Requisition entry monitor- 1% of reqs entered in each area by each shift. 2-AM Phlebotomy TAT- time last floor is drawn for both rounds and % patients drawn. 3-Unlabeled/mislabeled specimens- overseen by hospital committee. 4-Urine Cancellations- shared specimens between Microbiology and Core Lab.

7. Taking Pulses Pre-analytical 5-Phlebotomy Error Rate- number of PSN events. 6-Phlebotomy Scripting- quarterly measure of phlebotomist competency. 7-Pneumatic Tube Performance- monitor tube failures. 8-Phlebotomy Cancellations- % AM and POE requests cancelled due to action by phlebotomy.

8. Taking Pulses Analytical TAT; Process to Result: 1-AM Blood Drawing- CMP,H8ED,PTT 2-Core Lab Stat- CMP,H8ED, PTT 3-Core Lab Superstats- Heme-8, PTT 4-Stats from Weinberg- H8ED,PTT 5-Pre-Op Superstats- PTT,K,HCG

9. Taking Pulses Analytical TAT; Process to Result: 6-Weinberg Outpatients- H8ED,H8,Diff, Plt Estimates 7-Critical Care Lab- K 8-Adult ED Lab- CMP,ABG,HCG, Troponin,H8ED,PTT, UDip, Rapid Strep 9-Affiliate Stats- CMP,H8ED,PTT 10-Inpatient Routines- CMP,H8ED,PTT 11-Outpatient Routines- CMP,H8ED,PTT

10. Taking Pulses Post-analytical 1-Critical Action Value Read Back- read back of result and patient name. 2- Critical Action Value TAT- time of initial result to initial call to clinician. 3- BMS Specimen Cancellations- % specimens cancelled. 4- Antibiotic Cancellations- number of test without dosage information.

11. Taking Pulses Post-analytical 5-Coagulation Patient Safety- number of patients with 3 consecutive CAV PTT 6-Communication Errors- add-on errors, result errors, etc. 7-PDS Result Review- comments, interpretations, reference ranges, etc. 8-Patient Result Review- accuracy of results in patient’s medical record.

12. Performance Improvement Changes/improvements to current services. Failures/problems identified. Compliants from customers. QA Monitor identified failure. Implementation of new services.

13. Performance Improvement PDSAPlanDoStudyAct

14. PDSA Plan: Set a goal- what is the aim, what are we trying to accomplish? Focus Group- who should be on the Team to make PDSA happen? Measures- what data needs to be collected, who will collect data, how is data obtained, what is the frequency of data collection? Choose one small change- make a change in current process.

15. PDSA Do: Document what actually happened after a change was made, including any problems or unexpected outcomes. Document Observations- are the data telling us what we need to know?

16. PDSA Study: Complete analysis of data- what have we learned? Compare data analysis to expected outcomes- did original outcomes improve?

17. PDSA Act: Change Successful- how will the change be implemented, how is the change communicated? Implement QA Monitor to ensure change remains effective.

18. PDSA Act: Change Unsuccessful- what was the source of failure, how should we proceed (next steps)? Implement next PDSA cycle. Implement next PDSA cycle.