On All Accounts: Cost-Effectiveness Analysis of Limited Preoperative Optimization Efforts Before Colon Cancer Surgery.
Aged
Colonic Neoplasms
/ pathology
Comorbidity
Cost-Benefit Analysis
/ methods
Decision Support Techniques
Health Care Costs
/ statistics & numerical data
Humans
Neoplasm Staging
/ methods
Patient Simulation
Postoperative Complications
/ economics
Postoperative Period
Preoperative Care
/ economics
Preoperative Exercise
/ physiology
Quality-Adjusted Life Years
Sensitivity and Specificity
Journal
Diseases of the colon and rectum
ISSN: 1530-0358
Titre abrégé: Dis Colon Rectum
Pays: United States
ID NLM: 0372764
Informations de publication
Date de publication:
01 06 2021
01 06 2021
Historique:
entrez:
6
5
2021
pubmed:
7
5
2021
medline:
8
10
2021
Statut:
ppublish
Résumé
Reports suggest that preoperative optimization of a patient's serious comorbidities is associated with a reduction in postoperative complications. The purpose of this study was to assess the cost and benefits of preoperative optimization, accounting for total costs associated with postoperative morbidity. This study is a decision tree cost-effectiveness analysis with probabilistic sensitivity analysis (10,000 iterations). This is a hypothetical scenario of stage II colon cancer surgery. The simulated 65-year-old patient has left-sided, stage II colon cancer. Focused preoperative optimization targets high-risk comorbidities. Total discounted (3%) economic costs (US $2018), effectiveness (quality-adjusted life-years), incremental cost-effectiveness ratio (incremental cost-effectiveness ratio, cost/quality-adjusted life-years gained), and net monetary benefit. We calculated the per individual expected health care sector total cost of preoperative optimization and sequelae to be $12,395 versus $15,638 in those not optimized (net monetary benefit: $1.04 million versus $1.05 million). A nonoptimized patient attained an average 0.02 quality-adjusted life-years less than one optimized. Thus, preoperative optimization was the dominant strategy (lower total costs; higher quality-adjusted life-years). Probabilistic sensitivity analysis demonstrated 100% of simulations favoring preoperative optimization. The breakeven cost of optimization to remain cost-effective was $6421 per patient. Generalizability must account for the lack of standardization among existing preoperative optimization efforts, and decision analysis methodology provides guidance for the average patient or general population, and is not patient-specific. Although currently not comprehensively reimbursed, focused preoperative optimization may reduce total costs of care while also reducing complications from colon cancer surgery. See Video Abstract at http://links.lww.com/DCR/B494. ANTECEDENTES:Los informes sugieren que la optimización preoperatoria de las comorbilidades graves de un paciente se asocia con una reducción de las complicaciones postoperatorias.OBJETIVO:El propósito de este estudio fue evaluar el costo y los beneficios de la optimización preoperatoria, teniendo en cuenta los costos totales asociados con la morbilidad postoperatoria.DISEÑO:Análisis de costo-efectividad de árbol de decisión con análisis de sensibilidad probabilístico (10,000 iteraciones).AJUSTE ENTORNO CLINICO:Escenario hipotético Cirugía de cáncer de colon en estadio II.PACIENTE:Paciente simulado de 65 años con cáncer de colon en estadio II del lado izquierdo.INTERVENCIÓN:Optimización preoperatoria enfocada dirigida a comorbilidades de alto riesgo.RESULTADOS:Costos económicos totales descontados (3%) (US $ 2018), efectividad (años de vida ajustados por calidad [AVAC]), relación costo-efectividad incremental (ICER, costo / AVAC ganado) y beneficio monetario neto (NMB).RESULTADOS:Calculamos que el costo total esperado por sector de atención médica individual de la optimización preoperatoria y las secuelas es de $ 12,395 versus $ 15,638 en aquellos no optimizados (NMB: $ 1.04 millones versus $ 1.05 millones, respectivamente). Un paciente no optimizado alcanzó un promedio de 0.02 AVAC menos que uno optimizado. Por lo tanto, la optimización preoperatoria fue la estrategia dominante (menores costos totales; mayores AVAC). El análisis de sensibilidad probabilístico demostró que el 100% de las simulaciones favorecían la optimización preoperatoria. El costo de equilibrio de la optimización para seguir siendo rentable fue de $ 6,421 por paciente.LIMITACIONES:La generalización debe tener en cuenta la falta de estandarización entre los esfuerzos de optimización preoperatorios existentes y esa metodología de análisis de decisiones proporciona una guía para el paciente promedio o la población general, no específica del paciente.CONCLUSIONES:Si bien actualmente no se reembolsa de manera integral, la optimización preoperatoria enfocada puede reducir los costos totales de la atención y al mismo tiempo reducir las complicaciones de la cirugía de cáncer de colon. Consulte Video Resumen en http://links.lww.com/DCR/B494.
Sections du résumé
BACKGROUND
Reports suggest that preoperative optimization of a patient's serious comorbidities is associated with a reduction in postoperative complications.
OBJECTIVE
The purpose of this study was to assess the cost and benefits of preoperative optimization, accounting for total costs associated with postoperative morbidity.
DESIGN
This study is a decision tree cost-effectiveness analysis with probabilistic sensitivity analysis (10,000 iterations).
SETTING
This is a hypothetical scenario of stage II colon cancer surgery.
PATIENT
The simulated 65-year-old patient has left-sided, stage II colon cancer.
INTERVENTION
Focused preoperative optimization targets high-risk comorbidities.
OUTCOMES
Total discounted (3%) economic costs (US $2018), effectiveness (quality-adjusted life-years), incremental cost-effectiveness ratio (incremental cost-effectiveness ratio, cost/quality-adjusted life-years gained), and net monetary benefit.
RESULTS
We calculated the per individual expected health care sector total cost of preoperative optimization and sequelae to be $12,395 versus $15,638 in those not optimized (net monetary benefit: $1.04 million versus $1.05 million). A nonoptimized patient attained an average 0.02 quality-adjusted life-years less than one optimized. Thus, preoperative optimization was the dominant strategy (lower total costs; higher quality-adjusted life-years). Probabilistic sensitivity analysis demonstrated 100% of simulations favoring preoperative optimization. The breakeven cost of optimization to remain cost-effective was $6421 per patient.
LIMITATIONS
Generalizability must account for the lack of standardization among existing preoperative optimization efforts, and decision analysis methodology provides guidance for the average patient or general population, and is not patient-specific.
CONCLUSIONS
Although currently not comprehensively reimbursed, focused preoperative optimization may reduce total costs of care while also reducing complications from colon cancer surgery. See Video Abstract at http://links.lww.com/DCR/B494.
EN TODO CASO ANLISIS DE RENTABILIDAD DE LOS ESFUERZOS LIMITADOS DE OPTIMIZACIN PREOPERATORIA ANTES DE LA CIRUGA DE CNCER DE COLON
ANTECEDENTES:Los informes sugieren que la optimización preoperatoria de las comorbilidades graves de un paciente se asocia con una reducción de las complicaciones postoperatorias.OBJETIVO:El propósito de este estudio fue evaluar el costo y los beneficios de la optimización preoperatoria, teniendo en cuenta los costos totales asociados con la morbilidad postoperatoria.DISEÑO:Análisis de costo-efectividad de árbol de decisión con análisis de sensibilidad probabilístico (10,000 iteraciones).AJUSTE ENTORNO CLINICO:Escenario hipotético Cirugía de cáncer de colon en estadio II.PACIENTE:Paciente simulado de 65 años con cáncer de colon en estadio II del lado izquierdo.INTERVENCIÓN:Optimización preoperatoria enfocada dirigida a comorbilidades de alto riesgo.RESULTADOS:Costos económicos totales descontados (3%) (US $ 2018), efectividad (años de vida ajustados por calidad [AVAC]), relación costo-efectividad incremental (ICER, costo / AVAC ganado) y beneficio monetario neto (NMB).RESULTADOS:Calculamos que el costo total esperado por sector de atención médica individual de la optimización preoperatoria y las secuelas es de $ 12,395 versus $ 15,638 en aquellos no optimizados (NMB: $ 1.04 millones versus $ 1.05 millones, respectivamente). Un paciente no optimizado alcanzó un promedio de 0.02 AVAC menos que uno optimizado. Por lo tanto, la optimización preoperatoria fue la estrategia dominante (menores costos totales; mayores AVAC). El análisis de sensibilidad probabilístico demostró que el 100% de las simulaciones favorecían la optimización preoperatoria. El costo de equilibrio de la optimización para seguir siendo rentable fue de $ 6,421 por paciente.LIMITACIONES:La generalización debe tener en cuenta la falta de estandarización entre los esfuerzos de optimización preoperatorios existentes y esa metodología de análisis de decisiones proporciona una guía para el paciente promedio o la población general, no específica del paciente.CONCLUSIONES:Si bien actualmente no se reembolsa de manera integral, la optimización preoperatoria enfocada puede reducir los costos totales de la atención y al mismo tiempo reducir las complicaciones de la cirugía de cáncer de colon. Consulte Video Resumen en http://links.lww.com/DCR/B494.
Identifiants
pubmed: 33955409
doi: 10.1097/DCR.0000000000001926
pii: 00003453-202106000-00014
pmc: PMC8835996
mid: NIHMS1773979
doi:
Types de publication
Journal Article
Video-Audio Media
Langues
eng
Sous-ensembles de citation
IM
Pagination
744-753Subventions
Organisme : AHRQ HHS
ID : K08 HS024736
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA126607
Pays : United States
Informations de copyright
Copyright © The ASCRS 2021.
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