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Bariatric Surgery can Lead to Net Cost Savings to Health Care Systems: Results from a Comprehensive European Decision Analytic Model.

Borisenko O, Adam D, Funch-Jensen P, Ahmed AR, Zhang R, Colpan Z, Hedenbro J - Obes Surg (2015)

Bottom Line: Clinical effectiveness and safety were based on the literature and data from the Scandinavian Obesity Surgery Registry.Gastric bypass, sleeve gastrectomy, and gastric banding were included in the analysis.Cost data were obtained from Swedish sources.

View Article: PubMed Central - PubMed

Affiliation: Synergus AB, Svardvagen 19, 182 33, Danderyd, Sweden, oleg.borisenko@synergus.com.

ABSTRACT

Background: The objective of the present study was to evaluate the cost-utility of bariatric surgery in a lifetime horizon from a Swedish health care payer perspective.

Methods: A decision analytic model using the Markov process was developed covering cardiovascular diseases, type 2 diabetes, and surgical complications. Clinical effectiveness and safety were based on the literature and data from the Scandinavian Obesity Surgery Registry. Gastric bypass, sleeve gastrectomy, and gastric banding were included in the analysis. Cost data were obtained from Swedish sources.

Results: Bariatric surgery was cost saving in comparison with conservative management. It also led to a substantial reduction in lifetime risk of events: from a 16 % reduction in the risk of transient ischaemic attacks to a 62 % reduction in the incidence of type 2 diabetes. Over a lifetime, surgery led to savings of euro 8408 and generated an additional 0.8 years of life and 4.1 quality-adjusted life years (QALYs) per patient, which translates into gains of 32,390 quality-adjusted person-years and savings of euro 66 million for the cohort, operated in 2012. Analysis of the consequences of a 3-year delay in surgery provision showed that the overall lifetime cost of treatment may be increased in patients with diabetes or a body mass index >40 kg/m(2). Delays in surgery may also lead to a loss of clinical benefits: up to 0.6 life years and 1.2 QALYs per patient over a lifetime.

Conclusion: Bariatric surgery, over a lifetime horizon, may lead to significant cost savings to health care systems in addition to the known clinical benefits.

No MeSH data available.


Related in: MedlinePlus

Structure of the Markov model. The figure presents the structure of the Markov model. Patients in the surgical arm enter the model through the “Initial surgery” state and, in the next cycle, move to either “Diabetes post-surgery” or “No Diabetes post-surgery” state depending on the presence or absence of diabetes at the start of the analysis. Patients may recover from diabetes or experience diabetes. From any of the post-surgery state, patients can experience angina pectoris, myocardial infarction, heart failure, transient ischaemic attack, stroke, peripheral arterial disease, complications of surgery, or undergo conversion surgery if weight loss was not achieved. Patients can also move from one negative health state to another (i.e., experience a stroke after being in a heart failure state). Patients may also die from any state. Patients in the medical management arm enter the model either through “Diabetes” or “No diabetes” state. They can experience the same negative events except for complications of surgery or conversion surgery
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Fig1: Structure of the Markov model. The figure presents the structure of the Markov model. Patients in the surgical arm enter the model through the “Initial surgery” state and, in the next cycle, move to either “Diabetes post-surgery” or “No Diabetes post-surgery” state depending on the presence or absence of diabetes at the start of the analysis. Patients may recover from diabetes or experience diabetes. From any of the post-surgery state, patients can experience angina pectoris, myocardial infarction, heart failure, transient ischaemic attack, stroke, peripheral arterial disease, complications of surgery, or undergo conversion surgery if weight loss was not achieved. Patients can also move from one negative health state to another (i.e., experience a stroke after being in a heart failure state). Patients may also die from any state. Patients in the medical management arm enter the model either through “Diabetes” or “No diabetes” state. They can experience the same negative events except for complications of surgery or conversion surgery

Mentions: Decision analytic modeling was employed to evaluate the cost-effectiveness of bariatric surgery. A Markov process [4] was developed covering surgery and post-surgery, post-surgery complications, type 2 diabetes, angina pectoris, myocardial infarction, stroke, transient ischaemic attack, heart failure, and peripheral arterial disease states. In the Markov model during each cycle, which is equal to 1 month, a patient may progress to another health state (e.g., healthy individual in post-surgery state may experience stroke) or remain in the previous state. Each state is associated with specific cost and utility (based on health-related quality of life). The flow of patients in the surgical arm is presented in Fig. 1. The flow of patients in the optimal medical management arm is the same with the exception of absence of initial surgery, conversion surgery, and surgical complications states. Cost-effectiveness was evaluated over a lifetime perspective. Additional information on methods is provided in section S1 of Supplemental Material.Fig. 1


Bariatric Surgery can Lead to Net Cost Savings to Health Care Systems: Results from a Comprehensive European Decision Analytic Model.

Borisenko O, Adam D, Funch-Jensen P, Ahmed AR, Zhang R, Colpan Z, Hedenbro J - Obes Surg (2015)

Structure of the Markov model. The figure presents the structure of the Markov model. Patients in the surgical arm enter the model through the “Initial surgery” state and, in the next cycle, move to either “Diabetes post-surgery” or “No Diabetes post-surgery” state depending on the presence or absence of diabetes at the start of the analysis. Patients may recover from diabetes or experience diabetes. From any of the post-surgery state, patients can experience angina pectoris, myocardial infarction, heart failure, transient ischaemic attack, stroke, peripheral arterial disease, complications of surgery, or undergo conversion surgery if weight loss was not achieved. Patients can also move from one negative health state to another (i.e., experience a stroke after being in a heart failure state). Patients may also die from any state. Patients in the medical management arm enter the model either through “Diabetes” or “No diabetes” state. They can experience the same negative events except for complications of surgery or conversion surgery
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4522026&req=5

Fig1: Structure of the Markov model. The figure presents the structure of the Markov model. Patients in the surgical arm enter the model through the “Initial surgery” state and, in the next cycle, move to either “Diabetes post-surgery” or “No Diabetes post-surgery” state depending on the presence or absence of diabetes at the start of the analysis. Patients may recover from diabetes or experience diabetes. From any of the post-surgery state, patients can experience angina pectoris, myocardial infarction, heart failure, transient ischaemic attack, stroke, peripheral arterial disease, complications of surgery, or undergo conversion surgery if weight loss was not achieved. Patients can also move from one negative health state to another (i.e., experience a stroke after being in a heart failure state). Patients may also die from any state. Patients in the medical management arm enter the model either through “Diabetes” or “No diabetes” state. They can experience the same negative events except for complications of surgery or conversion surgery
Mentions: Decision analytic modeling was employed to evaluate the cost-effectiveness of bariatric surgery. A Markov process [4] was developed covering surgery and post-surgery, post-surgery complications, type 2 diabetes, angina pectoris, myocardial infarction, stroke, transient ischaemic attack, heart failure, and peripheral arterial disease states. In the Markov model during each cycle, which is equal to 1 month, a patient may progress to another health state (e.g., healthy individual in post-surgery state may experience stroke) or remain in the previous state. Each state is associated with specific cost and utility (based on health-related quality of life). The flow of patients in the surgical arm is presented in Fig. 1. The flow of patients in the optimal medical management arm is the same with the exception of absence of initial surgery, conversion surgery, and surgical complications states. Cost-effectiveness was evaluated over a lifetime perspective. Additional information on methods is provided in section S1 of Supplemental Material.Fig. 1

Bottom Line: Clinical effectiveness and safety were based on the literature and data from the Scandinavian Obesity Surgery Registry.Gastric bypass, sleeve gastrectomy, and gastric banding were included in the analysis.Cost data were obtained from Swedish sources.

View Article: PubMed Central - PubMed

Affiliation: Synergus AB, Svardvagen 19, 182 33, Danderyd, Sweden, oleg.borisenko@synergus.com.

ABSTRACT

Background: The objective of the present study was to evaluate the cost-utility of bariatric surgery in a lifetime horizon from a Swedish health care payer perspective.

Methods: A decision analytic model using the Markov process was developed covering cardiovascular diseases, type 2 diabetes, and surgical complications. Clinical effectiveness and safety were based on the literature and data from the Scandinavian Obesity Surgery Registry. Gastric bypass, sleeve gastrectomy, and gastric banding were included in the analysis. Cost data were obtained from Swedish sources.

Results: Bariatric surgery was cost saving in comparison with conservative management. It also led to a substantial reduction in lifetime risk of events: from a 16 % reduction in the risk of transient ischaemic attacks to a 62 % reduction in the incidence of type 2 diabetes. Over a lifetime, surgery led to savings of euro 8408 and generated an additional 0.8 years of life and 4.1 quality-adjusted life years (QALYs) per patient, which translates into gains of 32,390 quality-adjusted person-years and savings of euro 66 million for the cohort, operated in 2012. Analysis of the consequences of a 3-year delay in surgery provision showed that the overall lifetime cost of treatment may be increased in patients with diabetes or a body mass index >40 kg/m(2). Delays in surgery may also lead to a loss of clinical benefits: up to 0.6 life years and 1.2 QALYs per patient over a lifetime.

Conclusion: Bariatric surgery, over a lifetime horizon, may lead to significant cost savings to health care systems in addition to the known clinical benefits.

No MeSH data available.


Related in: MedlinePlus