Presentation on theme: "Taming of the Queue Workshop March 28 2012 Deborah Marshall, PhD Canada Research Chair, Health Systems and Services Research University of Calgary Alberta."— Presentation transcript:
Taming of the Queue Workshop March 28 2012 Deborah Marshall, PhD Canada Research Chair, Health Systems and Services Research University of Calgary Alberta Bone and Joint Health Institute Building a Decision Support Tool for Delivery of Health Services for Hip and Knee Osteoarthritis Patients
Co-Investigators from U Toronto and U Calgary: – Deborah Marshall (PI), Cy Frank, Tom Noseworthy, Sonia Vanderby, Dianne Mosher, Mike Carter, Tom Rohleder, Paul Rogers, Colleen Maxwell Partners: – Alberta Health Services – Alberta Bone Joint Strategic Clinical Network – Alberta Bone Joint Health Institute – Bone and Joint Canada Contributors: physicians, surgeons, health system administrators, clinic managers, other clinicians Project Team
When is System View Useful in Health Care? Many interrelated aspects of health care – Population and societal factors are important and “predictable” (aging population, disease morbidity) System Model for understanding vs. “answers” – Model building identifies gaps in knowledge and data – Process enhances understanding of relationships – Modular approach to examine changes to system in context of care delivery – Use of models as “flight simulators” – analysis of health policy options
Tool to enable policy makers, service planners and administrators, and clinicians to evaluate care quality and system performance Balancing the tradeoffs between accessibility, effectiveness and efficiency Inform choices about health system interventions Goal is a sustainable plan for OA care Objective: Create a decision-support tool for strategic service planning of care for OA patients - Across care continuum and sustainable
Why System Dynamics Model? Health Care is a System and it is Dynamic Examines how to balance demand for H&K OA health services, and supply and delivery of those services Considers resource constraints by changing the flow rate through feedback loops (current demand and backlog) Conceptually represents the “big picture” Population-level care delivery Capacity, flow rates, utilization, wait times Captures changes projected over time Enable users to explore numerous scenarios and compare results to inform decisions
Studying the Problem: Care Flows for Hip and Knee Replacement Inflow Rate Outflow Rate Demand for Replacement Patients Receiving Replacement Patients waiting for Replacement Stock
‘ Proof of Concept’ Model Demand from OA arrivals (incidence & population projections) Flow rates affected by stage durations Patient routings based on historic proportions Phase 1 Phase I + Resource use at each stage Costs associated with resources Phase 2 Phase II altered Key resources as inputs with availability affecting flow rates Phase 3 Phase III + Factors and feedback loops affecting patient routes & flow rates Phase 4 7 4 Phase Development Plan
Literature review initial process diagram Expert feedback & input via 6 workshops Refine process diagram Identify resources throughout process Identify other factors affecting patient flow 8 Hip & Knee Working Group 3 workshops Focus: surgical management process Arthritis Working Group 3 workshops Focus: medical management process Phase I Development Process
12 Model Component Information neededData source(s) Self directing incidence rates population projections duration of time self treating current population self treating Alberta Health Population Registry Ambulatory Care Classification System data Canadian Primary Care Sentinel Surveillance Network Discharge Abstract Database Physician Payments Statistics Canada Population projections Survey of Living Chronic Disease in Canada Primary Care current population in primary care duration of time in primary care referral proportions Physician Payments Rheumatology current population waiting for rheum & in rheum. care duration of wait for consult & in rheum care referral proportions Central Intake for Triage in Rheumatology Physician Payments Orthopaedics current populations waiting for screening & consult current populations in screening & in surgeon care Durations of wait times & time in care referral proportions Physician Payments Hip and Knee Replacement Central Intake Clinic data Acute care current population waiting for surgery duration of surgery wait & acute care LOS discharge proportions Operating Room Data Discharge Abstract Database Community care current community care populations durations of time spent in community care discharge proportions Discharge Abstract Database Home Care data ? Rehabilitation & Follow-up current population post surgery repair/revision rates duration of time until revision & time remaining in system Discharge Abstract Database Alberta Health Population Registry Literature Data Requirements and Sources
1.Case Definition of OA – Any diagnosis beginning code 715 or M15 to M19 (ICD9 & ICD10) in 4 data sources: physician claims, ACCS, DAD, Alberta Blue Cross 2.Identify First Incidence – Identify all OA - several scenarios tested different criteria – Cross referenced those with OA from the 4 data sources – First date of incidence identified 3.Determine Prevalence – Linked to AHW registry data Using the incident cases from step 2, can determine prevalence Prevalence rate = prevalent cases / total registry population 4.Determine incidence rates – Linked to AHW registry data Incident cases / (total mid-year registry population– previous year’s prevalence ) Incident rates calculated by age and gender and year Estimating OA Incidence and Prevalence in Alberta
Prevalence per 1000 population Prevalence nearly plateaus at about 8% after 15 years of data Range of OA Prevalence Estimates
Example of Questions that Health Policy Makers Would like to Address What resources are needed to: Meet the target wait times for hip and knee surgery? Meet current and future demand for OA services? What effect do acute and sub-acute utilization policies have on system performance? What are the resource requirements (human, financial, infrastructure) and how are they best deployed to achieve expected outcomes? What are the wait time and cost implications of changes in service demand and supply for OA?
Scenario 1 - Access What if a prevention program were initiated that reduced OA incidence by 10%? What would the effect be on… The number of OA patients in primary care? The annual number of hip and knee joint replacement surgeries? 17
Scenario 3 - Efficiency What if all new OA patients had to visit a screener before being eligible for a consult with an orthopaedic surgeon? What would the effect be on… – Patient flows leading to surgery? 21
Clinical Care Delivery - AHS Strategic Clinical Networks: – Establish quality standards, pathways and evidence-informed care models and interventions to create high performing health system System tools will be needed to meet AHS SCN mandate to transform OA health service delivery Health Policy - AHW Decision Makers: – Informing long term health care strategies about OA prevention, management and treatment – Inform human resources and reimbursement policies System tools to explore alternative scenarios and help inform long term strategies Implementation as the Meeting Ground of Decision Makers
Questions for Discussion (1) Would a system such as this be useful in guiding surgical scheduling practices in the clinic? Would practitioners be willing use this tool, and if not, why? What additional features would make it more useful? What assumptions have we made that may not work in current clinical practice? Is there a strong desire to provide more scheduling certainty to elective patients? What are the biggest barriers to providing a surgical ‘window when a decision to treat is made? What other specialties might benefit from a similar approach or tool?
Questions for Discussion (2) What policy questions about osteoarthritis management are of interest to you in your setting? How can the system dynamics model help inform decisions in your setting? What scenarios are relevant? What are the expected ‘bottlenecks’ in your system of care delivery for osteoarthritis? Are there important aspects of osteoarthritis care delivery missing in the osteoarthritis simulation? If so, what are they?