Brain to Brain Cycle

1. Brain to Brain Cycle Dr. Bill Bartlett Consultant Clinical Scientist Dept Clinical Biochemistry & Immunology Heart of England NHS Foundation Trust Birmingham B9 5SS Bill.Bartlett@heartofengland.nhs.uk

3. Information Management Measurement Knowledge Management Our Business: -

4. 70 to 80% of decisions in diagnosis based on laboratory outputs. 70 – 80% of the interactions of health care professionals involve laboratory outputs. Importance of Laboratory Medicine Our Work and the Quality of Our Work Under pins the Delivery of High Quality Health Care

5. What do we do for a living? • We save lives. • We help diagnose, monitor & treat disease • We screen for disease • We carry out and support R&D • We teach

6. We Use Our Brains & Help Others User use Theirs We Use Our Brains & Help Others User use Theirs How do we do these things We Measure

7. Brain to Brain Cycle Bill.Bartlett@heartofengland.nhs.uk

8. What Is It? • Phrase was first used by George Lundberg in the context of laboratory testing. • (JAMA 1981:245:1762-1763) • Refers to a process that ideally links a clinical problem to an appropriate action, taken on the patients behalf, based on the results of laboratory tests. • Question - Answer - Interpretation -Action.

9. Appropriate Post-analytical Processes Information Processing & Flow Data Integrity Appropriate Analytical Processes Appropriate Pre-analytical Processes Knowledge

10. The Process: - • Ask the right questions. • Interpret the answers. • Collate the information. • Arrive at working diagnosis. • Request: - • Pathology • Radiology • Other Opinions • Admit? • Wait I don’t feel well Doc! What is the nature and cause of his disease?

11. Output • Information • Questions • INPUT • Information • Samples Analytical Phase Pathology: Request to Result What is the Process

12. 9 Steps

13. Phases Pre - Analytical Analytical Post -Analytical

14. Value in Understanding the Cycle • manage the process to reduce complexity. • remove the choke points, consolidate and automate • become pro-active in helping clinicians to: - • use the laboratory services appropriately. • use the product of the process which is information.

15. How will managing the cycle impact on healthcare? • Delivery of a more efficient diagnostic process: - • better targeting of resources • shorter bed stays? • faster processing of patients?

16. Brain to Brain Cycle • Complex. • Applies to every request • Every cycle results in costs outside of pathology (e.g. longer bed stays?) • Any error reinitiates cycle • Information flows and accuracy are critical. • Complex analytical processes = time • Repeat cycles = cost! • Need to use information generated. Failure to do so = unnecessary cost • Wrong results or misinterpretation = cost

17. Intelligent Requesting • Deal with the Analytical Aneurysm. • Provide informative reports, to the right place, in the right time frame. Managing the Cycle How do we dispose of the complexity and increase effectiveness? • Understand Process and simplify • Direct skills into value added processes. Diagram Courtesy of Dr CG Fraser, Dundee

18. Requesting & ReportingThe Key to a Patient Focus? • Need to help users: - • Ask the right questions. • Provide the right inputs. • Apply the outputs effectively. • We need to: - • deliver the required outputs to the right place within the required time frame.

19. To Be Effective We Need To Ensure That: - • the correct questions are asked. • the correct inputs are provided. • valid analytical processes are applied. • useful outputs are delivered in an appropriate time frame. • our outputs are applied effectively.

20. Asking the right questions. • Requestors have varying degrees of knowledge, experience, expertise. (Nurse/Pharmacist/Doctor). • Tools: - • Brain - limited capacity/ exposure • Books, Journals - Volume • Protocols (NSFs) - Volume • Triage systems – Presentation panels (Headache, gut ache etc, chest pain) • Expert systems • Additional inputs, previous results, Hx, Rx

21. User Education • Less emphasis on laboratory medicine in medical curricula • Exponential rise in the size medical evidence base. • Fewer people with increased demands on their time. More protocol driven processes required?

22. Evidence into practice? • Job of the lab medicine specialist to work with clinicians to turn evidence into practice. • Take the evidence and build it into the requesting interface. • Integrate systems with expert systems

23. Electronic/Intelligent Requesting • Accurate flows of information. • Time efficient. • Linking requesting with results. • Linking requesting with care pathways. • Ability to see outstanding requests. • Building in protocols and links to information sources. • Enable the partially informed requestor. • Closing the loop between electronic systems.

24. Brain to Brain Cycle Bill.Bartlett@heartofengland.nhs.uk

25. Big Expensive User And for my next request, I would like to tick all the boxes.

26. What’s in a Request? • Decide what is to be measured • Decide in what sample to measure it, (blood, urine, faeces, tissue, CSF, etc) • Apply knowledge about the stability of the analyte (requirement for sample stabilisers, preservatives, cold transport etc) • Decide where to sample from (e.g. arterial versus venous sampling, swabs from which areas to identify infections)

27. What’s in a Request? • Identify the most appropriate time to take the sample (knowledge of biological rhythms, effects of drugs on analysis, effects of feeding on analytes (e.g. blood glucose)) • When to involve and inform the people who know how to measure the analyte • Initiate the request for analysis • Take the appropriate samples • Ensure that the samples and relevant information are passed to the laboratory

28. Phases Pre - Analytical Analytical Post -Analytical

29. Ward Work Station GTE PAS PAS NHS No, DoB Name Hard Copy & Bar code Intranet/Web Pathology 01 Pathology 01 Ice Server Requesting Module Lab Work Station Hard Copy & Bar code PDF SQL Requests SQL Results Web/VPN Cell Path GP Work Station Blood Bank FTP TELNET Microbiology Telepath Chemistry Hard Copy & Bar code Immunology GP Clinical System ICE Client Haematology

31. Phases Pre - Analytical Analytical Post -Analytical

32. Pre-analytical Phase • Critical Phase • Garbage in Garbage out • Labour intensive • Complex Processes • Errors • Choke Points • Automation

33. Automation

34. Phases Pre - Analytical Analytical Post -Analytical

35. 3600 electrolytes /hr • 3200 photometric test/hr • 22- 44 reagent slots per P800 • 340 tests/h • up to 340 samples/h • 50 reagent channels (slots) Current Capacity • Heartlands: 6800/hr Chemistry 340/hr immunoassay:- Solihull: 1700/hr chemistry, 170/hr immunoassay: - SWA/ Modular PE • ISE 900/1800 module • ISE tests (Na, K, Cl) • ISE 900: up to 900 tests/h • P 800 module • Photometric tests • Throughput: up to 800 tests/h • 22-44 channels, (reagent slots) • flexible setting • E 170 module • Immunology, ECL technology • Throughput:up to 170 tests/h • 25 channels (reagent slots)

36. Mass Spectrometry

37. Near Patient Testing

38. What is acceptable performance? • Accuracy • Imprecision • Short/Long term • Within lab/between lab • Within organisation • Turn around time • Failure rates

39. Fitness for purpose: - How do you assess this? • Analytical Goals • Method design and validation against goals • Analytical goals • Clinical decision limits • Reference change values • Practicability • Process design and validation against goals

40. Phases Pre - Analytical Analytical Post -Analytical

41. Apply Outputs Effectively. • Combine information, data and knowledge to provide a meaningful report to the point of care. • Enriched reports to aide medics. • Disease probabilities based on nosology • Graphical representations • Novel reporting formats based on pattern recognition? • Hyperlinks to data sources decision aides. • Automatic referral to areas of expertise (local/national) • Information for patients.

42. Pacific Knowledge Systems • www.pks.com.au. • Tailors the report to the patient

43. Traditional focus of laboratory systems

44. New systems functionality will address these areas and more (e.g.): - • Integrated lab handbooks • Logistics planning/ordering • Integration with expert systems • Billing • Document control • Data mining • Knowledge and information management • Surveillance • Audit • Web Enabled.

45. The Beginning Or The End