Laboratory test u,liza,on in Microbiology: where do we begin? Christopher Naugler Associate Professor Department of Pathology and Laboratory Medicine University of Calgary Disclosure -­‐ COIs I par,cipate in laboratory research sponsored by AbboF Laboratories Ltd. Honoraria: •
•
•
•
•
•
•
•
•
AbboF Pharmaceu,cals University of Alberta University of Calgary Alberta Society of Clinical Chemists Ontario Society of Clinical Chemists LifeLabs McGill University Alberta Society of Pharmacists Consul,ng: KPMG, AbboF Laboratories Ltd. –  Other: Stock in Merus Labs, Tekmira –  Book on appropriate lab tes,ng Chemistry/hematology tests Vitamin D in Alberta Objec,ves •  To iden,fy goals: geSng the most bang for your buck •  To emphasize the importance of the laboratory-­‐physician partnership •  To describe the challenges and gains experienced in the course of laboratory u,liza,on projects Caveats •  High level overview •  Based on my involvement with: –  Choosing Wisely Canada –  Choosing Wisely Alberta –  Alberta Laboratory U,liza,on Office –  Clinical labs, Alberta Health Services –  New research Calgary Volumes -­‐ All Micro Tests 10000 15.0 0 14.5 01/2012 02/2012 03/2012 04/2012 05/2012 06/2012 07/2012 08/2012 09/2012 10/2012 11/2012 12/2012 01/2013 02/2013 03/2013 04/2013 05/2013 06/2013 07/2013 08/2013 09/2013 10/2013 11/2013 12/2013 01/2014 02/2014 03/2014 04/2014 05/2014 06/2014 07/2014 08/2014 09/2014 10/2014 11/2014 12/2014 Number of Specimens 100000 19.0 90000 18.5 80000 70000 17.5 60000 50000 17.0 40000 16.5 30000 16.0 20000 15.5 # SPEC Posi,vityRate(%) Posi6vity Rate Calgary Posi6vity Rate for All Microbiology Tests 18.0 Ques,on and answer •  How have test volumes changed over ,me in your lab? GeSng the most bang for your buck •  Which u,liza,on management strategies work? •  Which physician groups should be targeted? •  Which tests should be targeted? What does the literature say? •
•
•
•
•
Many gaps Small sample sizes Uncontrolled studies Not enough quality studies for meta-­‐analysis No direc,on as to why some studies worked and others didn’t What can you expect? •  Educa,on: 1-­‐5% •  Audit and feedback: 10% •  Administra,ve interven,ons: 10-­‐20% –  Test restric,ons: 50%+ –  Vitamin D: 97% in Alberta Which physicians groups to target? •  High u,lizers •  Greatest prac,ce variance Total expenditures by specialty • Naugler C, Thomas R, Turin TC, Guo M, Vaska M. Am J Clin Pathol in press
Laboratory tes,ng costs by physician 450 410 400 Number of family doctors 350 300 250 200 181 157 150 100 142 119 111 85 56 50 62 40 36 31 17 20 14 13 0 Yearly cost of laboratory tests ($CDN) 8 3 7 2 18 Which tests to target •
•
•
•
Most common Most expensive Greatest prac,ce variance Where CPGs exist Ques,on and answer •  What tests would you target? The laboratory-­‐physician partnership •  Usually physicians are not involved in lab u,liza,on decisions •  Very liFle data on knowledge and aStudes of physicians •  Very liFle data on which approaches are most acceptable to physicians Q1: How important do you consider the issue of laboratory test overuse? 100 90 80 70 51.63% 60 % 43.14% 50 40 30 20 10 2.61% 1.96% 0.65% 0 Very Unimportant Unimportant Neutral Important Very Important Q4: Who is responsible for addressing issues regarding appropriate laboratory u6liza6on? Please check all that apply. Individual Medical Doctors (MDs) Alberta Medical Associa6on (AMA) 96.69% 66.89% Provincial Government (Alberta Health Services, Alberta Health) 71.52% 78.81% Diagnos6c laboratories Pa6ents 57.62% Q5: Which of the following are acceptable approaches to improving the quality of laboratory tes6ng (ie. Reducing unnecessary and duplicate tes6ng)? Please check all that apply. Con6nuing educa6on for healthcare providers (ie. Guidelines and recommenda6ons for different laboratory tests) 98.03% Audit and feedback of test ordering prac6ces to individual physicians 84.21% User pay for certain tests Restric6ng certain tests to specific specialist groups Specialized test requisi6on forms for certain tests 50.66% 38.16% 45.39% Modifying the format of test requisi6on forms (ie. Removal of certain tests) 51.32% Restric6ng the test frequency of certain tests 55.92% Pathologist approval required for certain tests 36.18% Posi6ve incen6ves (“gain-­‐sharing”) for changes in test ordering prac6ces 34.87% The challenge of iden,fica,on of inappropriate tests •  What data is available? •  Probably secondary lab data: –  Who is being tested? –  Who is ordering tests? –  What is the variance of test ordering in similar circumstances? –  What is the compliance with CPGs? –  What is the posi,vity rate? PSA tes,ng in the city of Calgary Gorday, W, Sadzradeh H, de Koning L, Naugler C. Sociodemographic variables associated with PSA tes,ng. Clin Biochem 2014;47:164-­‐169. Colon Cancer Screening •  There is marked varia,on in screening rates throughout Calgary, related to a number of sociodemographic factors •
Crouse AL, Sadrzadeh H, de Koning L, Naugler C. Clin Biochem 2015;48:105-­‐109. Redundant laboratory tests •
Morgen E, Naugler C. Am J Clin Pathol in press The challenge of measurement •  Not as simple as it sounds •  Two superimposed paFerns: –  Long term (year over year) trend –  Short term (seasonal) trend Linear Regression Model 20000 19000 18000 17000 16000 15000 14000 y = 100.66x + 13624 R² = 0.34 13000 FEB MAR APR MAY JUN JUL AUG SEP JAN FEB MAR APR MAY JUN JUL AUG SEP 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2010 2015-­‐05-­‐08 2011 DEC JAN 8 NOV SEP 7 OCT AUG 6 DEC JUL 5 NOV JUN 4 OCT MAY 3 DEC APR 2 NOV MAR 1 OCT FEB 11000 JAN 12000 2012 28 Calgary Volumes -­‐ Urine Cultures Calgary Posi6vity Rate for Urine Cultures Calgary Volumes -­‐ Blood Cultures Calgary Posi6vity Rate for Blood Cultures Calgary Volumes – Throat Cultures Calgary Posi6vity Rate for Throat Cultures The winning condi,ons step 1 •  Pick a test to address –  High volume –  High cost –  High variance –  Gather data –  Tie to published recommenda,ons where possible •  Choosing Wisely Canada •  CPGs The winning condi,ons step 2 •  Buy-­‐in from: –  Physician champions (content experts, professional groups) •  Demonstrate prac,ce gaps and varia,on •  Demonstrate harm of over-­‐tes,ng –  Misuse of public funds –  Direct pa,ent harm –  Misdirected clinical effort The winning condi,ons step 3 •  Present a united front to administrators and poli,cians –  Laboratory –  Physician groups –  Health department The winning condi,ons step 4 •  Be prepared for push-­‐back –  Poli,cians –  Physicians –  Public Ques,on and answer •  What has worked or not worked in your lab? Ques,ons? Tes,ng algorithm example •  >1000 flow cytometry tests on peripheral blood for lymphocytosis •  An algorithm incorpora,ng Age, CBC and Ferri,n can eliminate 25% of flow cytometry tests with >97% specificity •  Healey R, Naugler C, De Koning L, Patel J. Leuk Lymphoma, in press