K en Fyie University of Calgary and Alberta Bone and Joint Health Institute

1. Ken Fyie University of Calgary and Alberta Bone and Joint Health Institute Waiting Time Management Strategies for Scheduled Health Care Services Ottawa, Ontario – March 28, 2012 An Evaluation of the Primary-to-Specialist Referral System for Elective Total Joint Arthroplasty in Alberta

2. Outline • Motivation and research question • Methodology • Results • Discussion and next steps

3. Some Background

4. Some Background

5. The referral process Source: Marshall et al. (2012) – under submission Source: Marshall et al. (2012) – under submission • Voluntary Waits • Patient-related factors directly impacting the system’s ability to deliver care in a specified timeframe • Involuntary Waits • A system-related wait, caused by inability to meet demand

6. Motivation for this study • Inconsistent and incomplete measurement of waiting times • From referral made to musculoskeletal (MSK) assessment to surgical consultation • Little analysis about the context of delays • Few published analyses of referral processing inside clinics – a “black box” from the outside

7. Our research question... • Can the hip and knee referral process from primary care providers to orthopaedic specialists in Alberta be positively impacted by the introduction of an electronic referral tool? • We: • Qualitatively evaluate current referral practices • Quantitatively evaluate three system measures reflecting current quality of care

8. Methodology: Mixed Methods Study • Data collected in three stages: • Initial clinic visits, with semi-structured interviews • Retrospective patient chart sampling • Time and motion study of clinical staff • Patients are consulting for hip and knee osteoarthritis for first time • Primarily referred to clinics by GPs • Three volunteer hip and knee clinics in Alberta

10. Outcome Measurements • Accessibility: • 1) Waiting times(business days) – • Time referral made to time referral deemed complete • Time referral deemed complete to time of first surgical consult • 2) % of patients seeking next available surgical consult • 3) Estimate of involuntary and voluntary waiting times • Referral Appropriateness: • 4) % of referrals initially arriving complete and correctly directed • 5) Clinical rules for accepting referrals • 6) MSK screening usage • Efficiency: • 7) Time spent by clinic staff evaluating each referral

11. Results: AccessibilityWaiting Times varied across clinics • 11-15% of the referral made to surgical consultation waiting time is involuntary • Scheduling rules vary across clinics

12. Results: AccessibilityReferral date to acceptance date Red line: 90th percentile time Tan line: Mean waiting time Green line: Median waiting time Note: few patients with long waiting time drive results

13. Results: AccessibilityAccepted date to consult date Red line: 90th percentile time Tan line: Mean waiting time Green line: Median waiting time Note: few patients with long waiting time drive results

14. Results: AccessibilityNext available surgeon dominates • This is much higher than in literature (only 40%-70% in previous studies)

15. Results: Referral AppropriatenessIncomplete referrals are a problem • Why are referrals rejected? • Incomplete: referral variables not filled out • Rules vary depending on clinic • Most rejected referrals are due to incompleteness • Incorrectly directed: cannot be treated at specific clinic • Longest delays associated with this

16. Results: Referral AppropriatenessMSK screening reduces the queue • MSK screening results in fewer “currently non-surgical” patients seeing a surgeon • These assessments resulted in: • 29% of referred patients at clinic 1 • 26% of referred patients at clinic 3 • not seeing a surgeon for a surgical consultation

17. Results: EfficiencyReferrals are processed quickly • Clinic staff • Most referrals take ~9-14 minutes • Referrals with missing information take longer • Most staff have other work areas in addition to referral processing • Technology could increase efficiency (duplicate data entry, scanning information)

18. Discussion:Variation in clinical requirements • Clinical time tracking is consistent • Bone and Joint Clinical Network defined waiting times • Clinical processing rules vary • What is necessary on a referral form • How patients are prioritized • Whether triaging (MSK assessment) is available • Requirements prior to consult or surgery • Feedback to GPs

19. Discussion:Electronic Referral can produce better outcomes • Reduced waiting times: cut initial involuntary times by up to 20 days • All Alberta patients can choose next available surgeon • Consistent referral forms to minimize missing information: eliminate the 10-50% not initially accepted • Urgency scoring: get care to worse-off patients quicker • Reductions in certain tasks by clinic staff: save 8 minutes in scanning time

20. Next Steps • Electronic referral should be evaluated to determine how system outcomes change • Must account for multiple changes occurring at once • Voluntary waiting times should be separated • Basic standardization of the referral process should occur • Differing clinic processing rules need to be considered • Reduces variation, creates one consistent queue for patients

21. Concluding Remarks • Current referral practices show some inefficiencies and gaps in knowledge, producing worse system outcomes • Electronic referral and central intake can potentially improve referral processing and system outcomes • Future analysis needed when electronic referral is implemented

22. Acknowledgments • Alberta Bone and Joint Health Institute: • Tanya Christiansen • Karen Phillips • Stephen Weiss • Christopher Smith • Cy Frank • Betty Smith • University of Calgary: • Deborah Marshall • Tom Noseworthy • Aish Sundaram • Staff at three volunteer hip and knee clinics in Alberta • Funding provided in part from hSITE/NSERC and Alberta Health Services, and the Alberta Osteoarthritis AIHS Team Grant