Financial Cost of Lung Surgery
Alessandro Brunelli
Consultant Thoracic Surgeon
Honorary Clinical Associate Professor
St. James’s University Hospital, Leeds, UK
Cost variability
of Lung Cancer surgery
Identification of factors associated
with cost variability
Routine data
PLICS and Institutional clinical database
Patient Level Information and Costing System
• PLICS categorises Trust’s costs as direct, indirect
or as overhead to patient care in accordance with
NHS Clinical Costing Standards.
• Using pt activity PLICS allocates these costs to
each patient in the most appropriate and
granular method.
Thoracic Surgery Clinical Database
112 variables
11 Patient Basic Demographics variables
43 Pre Surgery Data variables
22 Surgery Data variables
36 Post Surgery Data variables
236 VATS lobectomy patients
15 months period
TOTAL COST
€ 11,368 (7,000-63,000)
INTRAOPERATIVE
POSTOPERATIVE
€ 8,226 (5,600-13,300)
€ 3,029 (500-51,000)
Results of the multivariable regression analysis on total costs
In a patient with COPD and DLCO<60% the expected cost
of VATS lobectomy is 4270€ higher than in a patient
without COPD and with higher DLCO
250 anatomic lung resection performed in one fiscal year
(2014-2015) in Leeds
210 without major postoperative complications
Most of the cost variability is explained by prolonged
length of stay in patients with one or more risk factors:
CAD + 1.5 days
DLCO<60% +1.7 days
Thoracotomy +0.9 days
The postoperative cost of an uncomplicated patient
with all 3 risk factors would be +2627 Euro compared to
one without risk factors
503 consecutive patients submitted to lung
resection for lung cancer (April 2014-March
2016)
Comparison of postop costs (USD) between patients with
major complications vs. no or minor complications,
p<0.0001
14000
12000
10000
8000
6000
11918
4000
2000
4022
0
Minor complications
Major complications
Linear regression revealed:
pts with major complications
PLOS (>14 days) +9,120$
Unexpected ICU admission +10,082$
pts without complications
PLOS (>14 days) +2,970$
Risk adjusted postoperative costs
A multivariable regression model was constructed to adjust costs
for patient and procedure related characteristics, p<0.0001
18000
15984
16000
14000
12591
12000
10000
8000
6455
6000
4000
3797
4908
4921
TMM 1
TMM 2
2000
0
TMM 0
TMM 3
TMM 4
death
Conclusions
•Risk adjusted analysis of cost variability is crucial to
identify areas of practice improvement and cost saving
•Tariff regulators need to account for cost variability
associated with each procedure when defining bundle
payments in order not to penalize hospitals caring for
sicker patients
•Future analyses will be needed to explore the financial
burden of lung cancer survivorship (costs of readmission,
outpatient visits, primary care, social costs)