OBJECTIVE: Sepsis occurs in a heterogeneous population. A prospective nationwide surveillance study found that populations stratified by infection type had significant differences in the incidence of sepsis syndrome, rate of complications and mortality. The objective of this study was to explore whether successful identification of population-specific risk factors for disease-associated morbidity and mortality may allow for more accurate assessment of the cost effectiveness of treatment strategies. DESIGN: A decision analytic model was developed using outcomes data on incidence and resolution of major complications in sepsis syndrome. Healthcare resource utilisation data were based on length of hospital stay, intensive care unit stay versus hospital ward stay, and cost of treating sepsis-related complications. SETTING: This modelling study, conducted from the perspective of the healthcare institution, used actual outcomes data on 2 infection-specific patient populations. PATIENTS AND PARTICIPANTS: The 2 populations studied were patients with nosocomial respiratory tract infection or community-acquired urinary tract infection who subsequently developed sepsis syndrome. INTERVENTIONS: Treatment options modelled were standard therapy plus biotechnology therapy versus standard therapy alone in the treatment of gram-negative sepsis complications. MAIN OUTCOME MEASURES AND RESULTS: The incremental cost-effectiveness ratios differed between the 2 study populations, due to differences in the incidence and rate of resolution of major sepsis-associated complications. The use of biotechnology therapy is always more cost effective in the respiratory tract infection population. CONCLUSIONS: Cost-effectiveness results for a therapy may change when the epidemiology of the disease state is known and incorporated into the decision analytic model. An infection-specific approach is important in the treatment of sepsis.
OBJECTIVE:Sepsis occurs in a heterogeneous population. A prospective nationwide surveillance study found that populations stratified by infection type had significant differences in the incidence of sepsis syndrome, rate of complications and mortality. The objective of this study was to explore whether successful identification of population-specific risk factors for disease-associated morbidity and mortality may allow for more accurate assessment of the cost effectiveness of treatment strategies. DESIGN: A decision analytic model was developed using outcomes data on incidence and resolution of major complications in sepsis syndrome. Healthcare resource utilisation data were based on length of hospital stay, intensive care unit stay versus hospital ward stay, and cost of treating sepsis-related complications. SETTING: This modelling study, conducted from the perspective of the healthcare institution, used actual outcomes data on 2 infection-specific patient populations. PATIENTS AND PARTICIPANTS: The 2 populations studied were patients with nosocomial respiratory tract infection or community-acquired urinary tract infection who subsequently developed sepsis syndrome. INTERVENTIONS: Treatment options modelled were standard therapy plus biotechnology therapy versus standard therapy alone in the treatment of gram-negative sepsis complications. MAIN OUTCOME MEASURES AND RESULTS: The incremental cost-effectiveness ratios differed between the 2 study populations, due to differences in the incidence and rate of resolution of major sepsis-associated complications. The use of biotechnology therapy is always more cost effective in the respiratory tract infection population. CONCLUSIONS: Cost-effectiveness results for a therapy may change when the epidemiology of the disease state is known and incorporated into the decision analytic model. An infection-specific approach is important in the treatment of sepsis.
Authors: R L Greenman; R M Schein; M A Martin; R P Wenzel; N R MacIntyre; G Emmanuel; H Chmel; R B Kohler; M McCarthy; J Plouffe Journal: JAMA Date: 1991-08-28 Impact factor: 56.272
Authors: R C Bone; R A Balk; A M Fein; T M Perl; R P Wenzel; H D Reines; R W Quenzer; T J Iberti; N Macintyre; R M Schein Journal: Crit Care Med Date: 1995-06 Impact factor: 7.598