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Database Use & Abuse Shoo K. Lee, MBBS, FRCPC, PhD Director, Canadian Neonatal Network Director, Centre for Healthcare Innovation & Improvement University of British Columbia
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Centre for Healthcare Innovation and Improvement Growth of Vermont-Oxford Network
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Centre for Healthcare Innovation and Improvement Neonatal Networks Australia-New Zealand Neonatal Network Canadian Neonatal Network European Neonatal Network International Neonatal Network Israel Neonatal Network South American Neonatal Network Vermont-Oxford Neonatal Network
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Centre for Healthcare Innovation and Improvement Victoria Vancouver New Westminster Edmonton Calgary Saskatoon Regina Winnipeg Montreal Ottawa Kingston Toronto London Hamilton Halifax St John’s Canadian Neonatal Network Quebec City Sherbrooke Moncton Frederickton St John
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Centre for Healthcare Innovation and Improvement Canadian Perinatal-Neonatal Research Networks
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Centre for Healthcare Innovation and Improvement
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Relationship between Networks Canadian Neonatal Network (CNN) Canadian Perinatal Network (CPN) NICE-Team Integrated Database System Data Project NICE-Team is CIHR-funded to provide: - Database support and management - Network coordination - Data analysis services - Training awards - Resource of experienced multi- disciplinary researchers who can assist investigators
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Centre for Healthcare Innovation and Improvement Why join Databases and Networks? Audit – outcomes and resource use Research – clinical trials, health services, population health, translational research Quality improvement Professional guidelines Education and Training Policy and resource allocation decisions Advocacy International collaborations
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Centre for Healthcare Innovation and Improvement Database Use – A Looking Glass
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Centre for Healthcare Innovation and Improvement Database Abuse – Distortions and Illusions
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Centre for Healthcare Innovation and Improvement Descriptive Data - Uses Tells the Simple Facts Reader does all the interpretation
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Centre for Healthcare Innovation and Improvement Gestational age distribution
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Centre for Healthcare Innovation and Improvement Birth weight distribution
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Centre for Healthcare Innovation and Improvement Descriptive Data - Abuses Are the Data complete, accurate and unbiased? Reader may interpret incorrectly Often does not provide answers to address specific policy questions
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Centre for Healthcare Innovation and Improvement Garbage In - Garbage Out
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Centre for Healthcare Innovation and Improvement Crude Outcome Incidences - Uses Answers specific questions Permit longitudinal and trend analysis Surveillance and monitoring tool Early warning - emerging events and trends
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Centre for Healthcare Innovation and Improvement Survival to discharge home
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Centre for Healthcare Innovation and Improvement IVH incidence by GA
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Centre for Healthcare Innovation and Improvement Crude Outcome Incidences - Abuses Similar to descriptive data
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Centre for Healthcare Innovation and Improvement Outcome Comparisons - Uses Increased level of complexity Benchmark against industry standards Sentinel for monitoring patient safety Potential for improving quality and efficiency Provides management tool – measure performance, use carrot and stick Competitive advantage
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Centre for Healthcare Innovation and Improvement Mortality rates among Canadian NICUs
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Centre for Healthcare Innovation and Improvement Comparison of Outcomes - Abuses Lack of appropriate risk-adjustment Why do comparisons at all? - wrong interpretation - inappropriate change in practice patterns - competitive advantage/disadvantage - “gaming” system Fear-mongering Potential for inappropriate shifts in patterns of patient use
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Centre for Healthcare Innovation and Improvement Benchmarking & Risk Adjustment Promise of overcoming problems associated with comparison of crude outcomes Permit population based data analysis and interpretation, and design of system to provide optimal quality and efficiency of care
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Centre for Healthcare Innovation and Improvement Risk Adjustment Epidemiologic baseline population risks Diagnostic groups Therapeutic intensity (NTISS) Physiologic illness severity (CRIB, SNAP) True measure of illness severity at admission (TRIPS?) Where is the state of the art/science?
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Centre for Healthcare Innovation and Improvement SNAP-II and Mortality
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Centre for Healthcare Innovation and Improvement TRIPS (higher score is worse) TRIPS VariableTRIPS Score Points Temperature ( o C) 37.6 36.1 – 36.5 or 37.2-37.6 36.6 – 37.1 810810 Respiratory status Severe (apnoea, gasping, intubated) Moderate (RR >60/min or SpO2 <85) None (RR 85) 14 5 0 Systolic BP (mm Hg) <20 20-40 >40 26 16 0 Response to noxious stimuli None, seizure, muscle relaxant Lethargic response, no cry Withdraws vigorously, cries 17 6 0
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Centre for Healthcare Innovation and Improvement Mortality Change associated with TRIPS Change
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Centre for Healthcare Innovation and Improvement Which score to use? ROCGACRIBSNAPTRIPS Mortality0.650.90*0.910.85/0.91 IVH0.72na0.80 BPDna0.770.85na Limits<1500g* 12 hour One use All babies 12 hour One use Out-born 1 minute Repeat
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Centre for Healthcare Innovation and Improvement Risk-adjusted Outcome Comparisons - Uses “True” comparison of outcomes Separate outcome differences due to patient differences from those due to practice differences Permits study and design of practice change to improve outcomes New tool that may overcome some of the disadvantages of randomized clinical trials
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Centre for Healthcare Innovation and Improvement NICU Mortality Comparisons
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Centre for Healthcare Innovation and Improvement Risk adjusted outcome comparisons - abuses Definitions - do we mean the same thing? Measurement criteria – were they the same? Consistency - were criteria applied consistently? Was the treatment the same? Was risk-adjustment appropriate?
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Centre for Healthcare Innovation and Improvement Incidence of BPD by GA
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Centre for Healthcare Innovation and Improvement ROP Diagnosis and Treatment
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Centre for Healthcare Innovation and Improvement
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How do we use data for quality improvement?
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Centre for Healthcare Innovation and Improvement Quality Improvement – Current paradigm
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Centre for Healthcare Innovation and Improvement Is this good enough? Why do some units have better results? Are all their practices “best”? Are their practices applicable to you? Might you copy something that is harmful? Is this shot-gun approach efficient? At best, this is a subjective and unscientific approach Is there another way?
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Centre for Healthcare Innovation and Improvement Factors affecting IVH variations Synnes et al - 4 NICU practices accounted for IVH variation: (a) Antenatal steroids (b) C-section vs Vaginal delivery (c) Treatment for hypotension (d) Treatment for acidosis Implication – change in clinical practice may reduce IVH rates in some hospitals MacNab et al – developed Bayesian statistical methods using Markov Chain Monte Carlo hierarchical modeling to identify risk factors specific to each hospital
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Centre for Healthcare Innovation and Improvement Log odds plot for risk factor small for gestational age, two-level hierarchical model C, Canadian NICU data 1996-97.
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Centre for Healthcare Innovation and Improvement Residual NICU effects, means and 95% CI limits, two-level hierarchical models, Canadian NICU data 1996-97.
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Centre for Healthcare Innovation and Improvement Probability of being NI free
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Centre for Healthcare Innovation and Improvement Anderson-Gill Model for NI recurrence
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Centre for Healthcare Innovation and Improvement Adjusted probability for developing nosocomial infection for PICC lines
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Centre for Healthcare Innovation and Improvement The EPIC paradigm
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Centre for Healthcare Innovation and Improvement New Method for Quality Improvement Clinical TrialsCQI EQI
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Centre for Healthcare Innovation and Improvement EPIC – Phase 1 Baseline data collection Training of Infection Teams – MD, RN, QI Review of published literature Meeting to share findings Identify Critical Pathways & Incidents Qualitative research – identify Failure Modes Data analysis – identify practice differences associated with outcome variation Develop Change Strategy
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Centre for Healthcare Innovation and Improvement EPIC – Phase 2 Staff communication and training – group sessions, information packages Prepare supporting materials, e.g. prompts printed on order sheets Publicize information, posters, newsletters Implement EPIC 3-monthly feedback – Control Charts Revise strategies, reinforce change
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Centre for Healthcare Innovation and Improvement The EPIC Network & Database Approach Health Authority
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Centre for Healthcare Innovation and Improvement Integrative Processes
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Centre for Healthcare Innovation and Improvement Comparing Outcomes
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Population and Policy Implications
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Centre for Healthcare Innovation and Improvement
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Daily Level 3 Bed Utilization in B.C.
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Centre for Healthcare Innovation and Improvement Mortality by hospitals
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Centre for Healthcare Innovation and Improvement Mean SNAP-II
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Manpower
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Centre for Healthcare Innovation and Improvement Neonatologist/1000 births
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Centre for Healthcare Innovation and Improvement Normative values
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Centre for Healthcare Innovation and Improvement Watkins Criteria for Hypotension
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Centre for Healthcare Innovation and Improvement Hypotension Criteria and Incidence
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Evaluate Expert Guidelines
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Centre for Healthcare Innovation and Improvement Cost-effectiveness ROP screening
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Develop new clinical guidelines
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Centre for Healthcare Innovation and Improvement Cost-effective IVH Screening
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Assess guideline use
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Centre for Healthcare Innovation and Improvement Antenatal Steroid Use 1996-97: incidence of use = 59% among infants 24-34 weeks gestation Variation in use: Inborn 25% – 96% Outborn8% - 94% Potential to decrease neonatal deaths by 10%
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Planning and Policy
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Centre for Healthcare Innovation and Improvement Choice of transport system
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Regional variations in outcomes and resource allocation planning
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Planning for future
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Centre for Healthcare Innovation and Improvement 10 year Projections
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Centre for Healthcare Innovation and Improvement Summary Databases can be useful But use data and interpretation with CARE Clinical input is vital Database should meet your needs and goals Societal versus institutional goals
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Centre for Healthcare Innovation and Improvement Concerns Public impact of information Privacy and confidentiality Conformity versus innovation Barrier to clinical trials “Big brother” control Not “real” hypothesis-driven research Not high quality evidence (e.g. clinical trials) Research versus Quality Improvement Clinician versus “real” researchers
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www.canadianneonatalnetwork.org
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