Waits in Healthcare:

Transcription

1 Waits in Healthcare: Improving Access to Quality Cancer Care in BC Celebrate Research Week March 11 th,

2 Introduction Overall Goal To increase the efficiency of the cancer system and enhance patient outcomes through the development, testing, and implementation of modern management practices, especially from the field of Operations Research (O.R.) CIHR and MSFHR grant funded research project $1.5 Million over 5 years 2

3 The CIHR Team Oncologists Administrators Statisticians Faculty Researchers / Post-Doc. Fellows PhD Students BCCA UBC Operations Research Professionals 3

4 Project Presentations Today Three different types of waits: The good waits: waiting for optimal start of treatment Prostate Cancer Decision Making The bad waits: waiting during an appointment Improving Patient Flow and Resource Utilization at BCCA s Ambulatory Care Unit The ugly waits: waiting to start treatment Modelling Radiation Therapy Treatment 4

5 The good waits: Prostate Cancer Decision Making Mariel S. Lavieri Martin Puterman Steven Shechter Scott Tyldesley

6 Why the Good Waits? Maximum impact when treatment is delivered at the right moment Optimal treatment strategy: wait until ideal point has been reached 6

7 Combining Hormone and Radiotherapy High risk localized prostate cancer patients are often treated with hormone therapy prior to their radiotherapy treatment - Goal: starve tumour cells of testosterone (main fertilizer) resulting in tumour regression Patients monitored periodically - PSA (blood test) used to predict regression Maximal tumor regression probably occurs when PSA reaches its nadir level (Gleave, La Bianca and Goldeberg, 2000) - Key assumption - The nadir is the ideal time to start RT Cancers regress at different rates (difficult to predict) 7

8 Tumour Regression as a Function of PSA Tumor Tumour Size PSA RT Time 8

9 Tumour Regression as a Function of PSA RT Tumour Size RT Tumour Size RT Time Time Tumour Size RT Time 9

10 Tradeoffs Tolerance Responsiveness Why start RT now? - Avoid progression - Risk of cells becoming resistant - Toxicity of hormone therapy Why wait? - Maximum reduction of tumor size under hormone therapy - More information 10

11 Current Protocol High-intermediate or high risk patient? Offer hormone therapy prior to radiation therapy Start radiation therapy if: 8 months of hormone therapy have been received or PSA levels start to rise or PSA 1 ng/ml or PSA < 0.05 ng/ml after 4 months 11

12 Objectives To improve on a one size fits all duration of pre RT hormone treatment by developing a model to estimate anticipated time to maximal regression and RT start time for individual patients To provide a formal decision making approach formal decision making approach for RT starts for such patients in a population based on anticipated PSA progression 12

13 PSA Progression PSA vs time PSA Time t nadir 2 ln( PSA ) = α + β t + γt + v v ~ N(0, V ) 13

14 Description of the Problem Population N((α,β,γ),R) {(α i,β i,γ i ),R i }??? Time PSA Month Month Month Month

15 Updating the Curve Parameters PSA PSA vs time Time from NAH start (days) minimum 15

16 Description of the Problem (Cont.) Cluster 1 N((α 1,β 1,γ 1 ),R 1 ) Population N((α,β,γ),R) Cluster 2 N((α 2,β 2,γ 2 ),R 2 ) {(α i,β i,γ i ),R i }??? P j??? Cluster 3 N((α 3,β 3,γ 3 ),R 3 ) 16

17 Our Model Initial Beliefs (based on Population Characteristics) Observe PSA Update Curve Parameters Estimate Nadir No P(treating at the right time) Receive Treatment Yes Start RT? 17

18 Comparing Decision Rules 18

19 The Tool 19

20 The Tool 20

21 The Tool 21

22 Results By using a threshold to decide whether to start RT, we might be able to: - Identify earlier when the nadir is reached - Deliver treatment closer to the optimal time - Improve overall outcomes 22

23 The bad waits: Improving Patient Flow and Resource Utilization at BCCA s Ambulatory Care Unit Vincent Chow Pablo Santibáñez Colleen McGahan John French Martin Puterman Scott Tyldesley

24 Why the Bad Waits? Negatively affects patients experience, but does not necessarily have harmful clinical impact Delays the day of the appointment: - Although secondary to quality of care - One of the most common sources of patient dissatisfaction Thomas S, Glynne-Jones R & Chait I (1997) Is it worth the wait? A survey of patients satisfaction with an oncology outpatient clinic. European Journal of Cancer Care 6: Gourdji I, McVey L & Loiselle C (2003) Patients satisfaction and importance ratings of quality in an outpatient oncology center. Journal of nursing care quality 18(1):

25 Outline The Ambulatory Care Unit Process Modelling Incorporating Patient Input Conclusions 25

26 The Ambulatory Care Unit 26

27 Background Multiple visit types: - New patients diagnosed with cancer - Follow-up patients in active treatment or regular check-up Multiple physicians: - Oncologists - Residents/Students Complex process: - 15 to 25 clinics per day - 45 exam rooms patient visits per day with over 50,000 visits last year 27

28 The Appointment Process Simplified ACU Process Diagram 1 Patient arrives and checks in ACU Reception 2 Patient goes to Waiting Room until called for appointment 3 Nurse calls patient into Exam Room 4 Physicians (oncologist and/or resident/student) go into Exam Room and interact with patient 5 Physicians prepare patient Orders 6 Orders are sent to Nursing Station to be processed (or filed if processed off-line) 7 Patient leaves Exam Room and may go back to Waiting Room for Appointment Card 8 Nurse brings Appointment Card to patient 9 Patient leaves ACU Station F Reception B 1 Waiting Room Patient Waiting for Exam Room Patient Waiting for Physician Physician Examination #1 Patient Waiting for Physician Physician Examination #2 Patient Waiting for Discharge Non Value Added Times 28

29 Potential Problems During a clinic: - Physicians may get an emergency call - Patient information (tests) may not be available - An appointment may last longer than anticipated - Patients may arrive late (or even miss the appointment) These can cause: - Delays for patients (considerable wait times) - Overcrowding (space issues, lack of exam rooms) - Inefficient use of physicians time - Clinics overtime (run late into next clinic) 29

30 Process Modelling 30

31 Simulation Model 31

32 Testing Different Configurations Changes in the process: - Clinic punctuality - Appointment order - Appointment duration - Add-ons Changes in the system: - Exam room allocation: dedicated vs. dynamic More than 100 scenarios were tested 32

33 Results 120% Wait Time and Clinic Duration for Selected Scenarios 100% % of Current Level 80% 60% 40% 20% 0% Current Clinic On Time Clinic On Time Clinic On Time Clinic On Time Sched Work Ins Sched Work Ins Sched Work Ins Average Wait Time Average Clinic Duration Appt dur +15% Appt dur + 30% Changes to Current State Significant reductions in wait time can be achieved with minor impact on current clinic durations 33

34 Room Allocation: Dedicated (current) # rooms Clinics RT SYS Exam Rooms 34

35 Room Allocation: Dynamic (proposed) # rooms Clinics RT SYS Exam Rooms Potential to free up to 26% of current exam rooms for other duties by pooling resources 35

36 Incorporating Patient Input 36

37 Patient Survey Patient input is key to: - Understand patients perception of their wait experience - Influence & determine criteria for testing configurations - Ensure the design of the system incorporates what matters to the patients Survey content: - Experience: Wait times in ACU Environmental factors of wait areas - Preferences: Place to wait Be informed of current/expected wait times Maximum reasonable time to wait 37

38 Main Survey Findings Satisfaction level higher than 80% for each category Privacy Wait area noise level Reception crowdedness Wait area pleasant Examination room pleasant Examination room too small More time with physician Entertainment facilities Wait time in examination room Wait area too crowded Wait time in wait area 38

39 Main Survey Findings Experience - Improve patient satisfaction with: length of time waited (24% felt some dissatisfaction in at least one wait area) area they wait in (17% felt wait area was too crowded) - More than half (56%) of the patients waited longer than they felt was reasonable in either the wait area or exam room 39

40 Main Survey Findings Preferences - Vast majority (78%) of patients agreed being informed makes wait easier - High percentage of patients (53%) would prefer not to wait in the exam room Wait area Examination Room Portion in each No preference - Reasonable maximum wait should be minutes 53% 13% 12% 22% 40

41 Conclusions 41

42 Benefits of This Research Significant reduction in patient wait times and exam room utilization can be achieved Most important factors: - Clinic punctuality - Schedule add-ons (avoid double-booking) - Appropriate appointment duration - Pooling exam room resources 42

43 The ugly waits: Modelling Radiation Therapy Treatment Pablo Santibáñez Vincent Chow John French Martin Puterman Scott Tyldesley

44 Why the Ugly Waits? Delay could be detrimental to patients health: - Evidence in medical literature supporting a relationship between increased waiting time to start treatment and inferior clinical outcomes for radiotherapy Mackillop, WJ (2007) Killing time: The consequences of delays in radiotherapy. Radiotherapy and Oncology 84: 1-4 Chen Z, King W, Pearcey R, Kerba M and Mackillop WJ (2008). The relationship between waiting time for radiotherapy and clinical outcomes: A systematic review of the literature. Radiotherapy and Oncology 87(1): 3-16 Adds to the psychological stress 44

45 Outline Background Waiting for RT Treatment Modelling RT Treatment Towards a Cancer System Model 45

46 Background 46

47 Radiation Therapy (RT) One of the treatment options for cancer - Others: chemotherapy, hormone therapy, surgery Uses radiation (high-energy rays) to kill or shrink tumour cells: - External beam radiation - Internal (radioactive seeds) Requires sophisticated imaging, planning and equipment to precisely deliver treatment Usually involves several consecutive sessions 47

48 Radiation Therapy (RT) 48

49 Radiation Therapy (RT) 49

50 Waiting for Radiation Therapy Treatment 50

51 Wait Definition Wait time measurement: need to know when the clock starts and stops 51 Decision & Patient ready RT Treatment starts RT Treatment ends Wait for Treatment

52 Wait Time Targets Health ministers benchmark: - 4 weeks from ready for treatment until the start of treatment Canadian Association of Radiation Oncology (CARO) recommended standard * (also WTA): - Consultation within 10 working days of initial referral to Radiation Oncologist - Treatment within 10 working days of consultation Wait Time Alliance Report Card (2007) rated A BC s Cancer Care performance (80-100% of population treated within government approved pan-canadian wait time benchmark) (*) Emergency cases: immediate to 24 hrs. Urgent cases: based on individual need 52

53 Wait Time Challenges Starting point definition: - Simple rules do not capture complex patient mix - Differences between single and multi modality treatment - Patient choice (elective delay) Accurate information: - Availability of time stamps data - Consistency in definitions Delays in other parts of the process 53

54 Modelling Radiation Therapy Treatment 54

55 Why Modelling? Wouldn t it be easier to add more capacity? - Perhaps, but where and of what type? - Might not be efficient solution - Need for a long-term strategy - Advanced analytics can help to better target efforts 55

56 Why Modelling? Highly complex process to model: - Multiple types of patients Tumour group Priority Intent (curative vs. palliative) - Different treatment options Single modality Combined (and co-dependant) with others - Patient-specific treatment duration - Technical considerations - Variable demand 56

57 RT Treatment Process Patient population comprises multiple types of patients Different types of patients need different RT machines 57

58 RT Treatment Process 58 t t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 10 t + 11 t + 12 t + 13 t + 14 t + 15 t + 16 t + 17 t + 18 t + 19 t + 20 t + 21 t + 22 Minimum start date WAIT Treatment duration

59 What is Our Team Doing? Over the last few months, we have: - Studied the RT treatment process - Retrieved, processed and analyzed related data - Considered other areas/processes that are connected 59

60 What is Our Team Doing? Currently developing a computer simulation model that will allow us to: - Replicate treatment process at a very detailed level - Develop what-if scenarios to examine impact of process changes in patient wait times Different operating policies Assess capacity needs Focus improvement efforts more efficiently 60

61 The Entire Picture: From Diagnosis to Treatment Significant delays could exist in processes prior to RT treatment Outside BCCA Within BCCA Chemo, hormone therapy 61 Diagnosis New Referral First Onc consult RadOnc consult Requisition Date Ready-to-Treat Simulator RT Treatment starts RT Treatment ends Wait for Treatment Labs, medical imaging, etc.

62 Towards a Cancer System Model 62

63 RT Treatment Model ACU & PR Arrivals NP / ROC Appt. Patient Review Follow Up Treatment Units First Treatment Last Treatment Others Imaging Planning 63

64 Towards a System Wide Model Arrivals Population AB SI VI FV VA GP, Imaging, Surgery Triage NP / ROC Appt. Patient Review Follow Up Recur. First Treatment Last Treatment Imaging Planning RT NP / ROC Appt. In Treat. Follow Up Follow Up First Treatment Last Treatment SYS Pathology Pharmacy Diagnostic Imaging Surgery Inpatient Units 64

65 Waits in Healthcare: Improving Access to Quality Cancer Care in BC Celebrate Research Week March 11 th,