European Collaboration for Healthcare Optimization An ...€¦ · Q1 Q2 Q3 Q4 Q5 PCI and burden of...

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www.echo-health.eu ECHO European Collaboration for Healthcare Optimization An international project on healthcare performance

Transcript of European Collaboration for Healthcare Optimization An ...€¦ · Q1 Q2 Q3 Q4 Q5 PCI and burden of...

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ECHO –

European Collaboration for Healthcare Optimization An international project on healthcare performance

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The concept

• ECHO has set about the task of bringing together patient-level data from Austria, Denmark, England, Portugal, Slovenia and Spain, making them comparable.

• ECHO is expanding the usual approach in healthcare performance international comparison (built upon average values), adding variation within and across countries.

• Performance dimensions : utilization of effective care, equitable access to effective care, hospital undesirable outcomes, potentially avoidable hospitalizations, utilization of low-value procedures, technical efficiency.

• Healthcare areas or hospital providers are flagged as good- or poor performers – not a diagnostic tool but a screening tool

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Geographicapproach Hospital-specificapproach

Researchquestion

Doestheplaceofresidence

influencethepopulationexperienceofgettinghigh-value

care?

Istheexposuretohigh-qualityand

safecaredependantontheproviderwhereapatientisassisted?

Mainendpoint

StandardisedrateorStandardisedUtilizationRatioandExcesscasesforhospitaladmissionsorprocedures

AdjustedriskandObservedtoExpectedRatio,analysingeventsamenabletohealthcarequality

Denominator

Populationlivinginapre-definedgeographicalarea

Patientstreatedinahospital

Mainaudience

Policy-makersManagersClinicians

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MESSAGES FROM ECHO WITH IMPACT IN POLICY MAKING

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UNEVEN UTILIZATION OF EFFECTIVE PROCEDURES

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Burden of ischemic disease

Each dot represents a healthcare area – age-sex standardized rate. Q1 to Q5 represent quintiles of ischemic

disease rates. Q1 the lowest burden, Q5 the highest burden.

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PCI utilization across welfare levels

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Red line represents utilization in the most affluent areas; blue line represents utilizations in the worse-off

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UNEVEN UTILIZATION OF LOW-VALUE PROCEDURES

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DENMARK ENGLAND PORTUGAL SLOVENIA SPAIN

SR 40.13 19.55 7.02 21.45 8.58

EQ5-95 1.66 4.69 46.80 3.54 35.36

SCV 0.16 0.28 2.19 0.20 1.26

Dots represent areas – age-sex standardized rates (natural scale on the left, normalized scale on the right).

SR: standardized rate; EQ5-95: ratio between the 5th and 95th percentile. SCV: Systematic Component of Variation.

C-section in low risk deliveries

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Excess-cases per Local Authority

Excess-cases with regard to the reference area. compares each area with those in the 10th percentile.

The darker the colour the more the number of cases that could be avoided.

Minimisation to p10

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SYSTEMATIC VARIATION IN UNDESIRABLE EVENTS AFTER SURGERY

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PTE & DVT after surgery

Denmark England Portugal Slovenia Spain

aIR 1,43 7,55 0,87 4,36 1,87

EQ 25-75 2,11 1,48 3,84 2,04 3,16

Dots represent hospitals - adjusted incidence of Pulmonary Thromboembolism and Deep Venous Thrombosis

(natural scale on the left, normalized scale on the right). Table: aIR: adjusted incidence rate; EQ25-75: ratio

between the 1st and 3rd quartile.

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RISK-ADJUSTED CASE FATALITY RATES - (CABG)

Dots represent hospitals - adjusted case-fatality rate in patients undergoing CABG. Hospitals beyond the

upper confidence interval represent either alerts (beyond the red line) or alarms (beyond the dashed-line)

Conversely, those hospitals beyond the lower confidence intervals are good or the best performers.

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Trends on undesirable events’ rates

Bubbles represent hospitals – trends in adjusted case-fatality rate in patients undergoing PCI. The bigger the

bubble the more the number of patients treated. Colours represent the position of each hospital with regard to the

benchmark and the confidence intervals – from orange the highest case-fatality rates, to dark-blue the lowest.

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UNEVEN OUTCOMES VS. UNEVEN RESOURCES USE

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LESS MORTALITY

Hospitals are classified according to resources use (length of stay (LOS) as a proxy) and Outcomes (e.g. case

fatalities). A common benchmark has first to be estimated for both resources use and outcomes (blue diamond)

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Each dot represents the hospital behaviour in terms of Length of Stay and Mortality rates, in patients with

Myocardial Infarction. Denmark highlighted.

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METHODOLOGICAL ISSUES

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• Building a homogeneous knowledge infrastructure

http://www.echo-health.eu/handbook/infrastructure.html

• Developing comparable indicators across different languages

http://www.echo-health.eu/handbook/getting-indicators.html

• Dealing with population size heterogeneity

http://www.echo-health.eu/handbook/unit_analysis.html

• Using proper analyses meant to elicit systematic and unwarranted variation

http://www.echo-health.eu/handbook/metrics.html

• Building common performance benchmarks

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POPULATION SIZE HETEROGENEITY

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Knee replacement

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Rate 89.9 57.9 27.3 70.6 48.8

RV5-95 1.9 2.5 8.7 2.1 4.1

< 50,000 2% 80% 65% 7%

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Former 278 units New 42 areas

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STATISTICS ELICITING UNWARRANTED AND SYSTEMATIC VARIATION

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Extremal Quotient vs. Component of Sytematic Variation

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COMPONENT OF SYSTEMATIC VARIATION

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Coefficient of Variation

Coefficient of Variation vs. EB statistic

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Variance partitioning: spatial fraction of variance

SFV: 0.55

SFV: spatially correlated /heterogeneity + spatially correlated

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BENCHMARKING

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National, international, aspirational benchmarking

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Individual data vs. aggregated data: more to less sensitivity

CABG Spain : on the left individual logit-based benchmarking; on the right, aggregated

Poisson-based benchmarking

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Pooling data vs. applying external coefficients

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CABG Spain – England: on the left pooled benchmarking; on the right English estimates are

applied to Spanish data

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more at www.echo-health.eu

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BUILDING A HOMOGENOUS INFRASTRUCTURE

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PATIENT ALLOCATION

TO THE AREA OF RESIDENCE

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BUILDING COMPARABLE INDICATORS

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Mapping-out codes across disease classifications

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Variance partitioning: spatial fraction of variance

SFV: 0.55

SFV: spatially correlated /heterogeneity + spatially correlated

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POTENTIALLY AVOIDABLE HOSPITALIZATIONS IN CHRONIC CONDITIONS

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DENMARK ENGLAND PORTUGAL SLOVENIA SPAIN

SR 93.36 56.15 33.96 61.86 47.02

EQ5-95 1.46 1.38 2.01 2.25 2.44

SCV 1.09 0.14 0.17 0.14 0.11

Potentially avoidable hospitalizations

Dots represent areas – age-sex standardized rates (natural scale on the left, normalized scale on the right).

SR: standardized rate; EQ5-95: ratio between the 5th and 95th percentile. SCV: Systematic Component of Variation.

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DENMARK ENGLAND

PORTUGAL SPAIN

Blue line represents the evolution of the average age-sex standardized rates Green dots represent the evolution .

of the Systematic Component of Variation.

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Larger areas, lesser variation

Tonsillectomy C-section Prostatectomy

Larger Smaller Larger Smaller Larger Smaller

RV5-95 4.3 8.4 7.18 10.4 2.34 2.55

RV25-75 2.1 2.4 1.8 2.2 1.5 1.6

CSV 0.40 0.54 0.95 0.97 0.11 0.11

EB 0.29 0.31 0.43 0.31 0.08 0.08