1. A managerial use of the volume-outcome association
Elisabetta Listorti, PhD Student Politecnico di Torino
volume-outcome association
hospital dimensioning
mortality
health policy
health quality
Key words

2. The volume-outcome association
Piano Nazionale Valutazione Esiti, 2011
Relevance of managerial tools within healthcare, but with a strategical approach and clinical objectives
30-day adjusted mortality rates
Volume=
Planning
Volume by facility
The volume-outcome association
Managerial and clinical perspective
Recurring trend that associates higher volume of activity to better results, which in turn means better patients’ health conditions
Why?
Existence of learning curves
Outcomes=
Quality
More prepared medical staff
Commitment for the uneven distribution of outcome quality levels within national contexts
Better structural organization
in high-volume hospitals

3. The operational research model
Objective function
Commissioner
Objective: improving population health conditions
Perspective
Costs
Constraints
Demand
Outcome depends only on volume
Omit external constraints
No actors interactions
Assumptions
Capacity
Under/Overtreatment
Expressed through
the volume-outcome association
Solution:
Volume of activity
of operation j
performed in hospital i
Number of interventions to be allocated to hospitals,
optimal in terms of patients health conditions

4. Objective functions analysis
Improving patients health conditions was translated as:
Drawing to different solutions:
Minimize total mortality
Minimize the average mortality rate
Minimize the mortality rates variance
Minimize the mortality rates average range
Unbalanced solution extremely high number of interventions in one facility, very low volumes in the remaining hospitals
Priority:
Quality
Balanced solution: total volume equally divided by hospitals
Priority:
Equity

5. Case studies Geographical distribution Specialization threshold
Hospitals performance
Which consequences has a threshold imposition,
In terms of outcome?
Mortality curve
Real outcomes
Volume
Negative consequences in terms of outcomes
Differences in outcomes, volumes being equal
Actual configuration
(bladder cancer interventions, 2013, PNE data):
We can track hospitals performance and adjust the allocation based on their competences
What if we entered the model constraints on catchment area coverage?
Minimum volume of activity imposed to hospitals

6. On-going and future research
xij  xij +1
Patients answer
Uncertainty
Model application
Volume of activity
Patient choice
Which factors affect patients hospital choice?
Stochastic surgery demand and mortality rates
Territorial configurations robust to uncertainty
Enriching the model of data information:
Costs
Capacity: Human resources and structural resources
Network of wards, including oncology ones