Objective To identify independent risk factors for in-hospital all-cause mortality in patients with sepsis and to integrate them into the quick Sequential Organ Failure Assessment (qSOFA) score to construct modified models, thereby improving the ability of the original qSOFA to predict mortality risk. Methods This retrospective study included adult patients who met the Sepsis-3 criteria for sepsis and were admitted to the Intensive Care Unit or Emergency Intensive Care Unit of Zigong Fourth People’ s Hospital between January 2018 and December 2023. Demographic characteristics, vital signs, comorbidities, and laboratory parameters were collected, and the Sequential Organ Failure Assessment (SOFA) and qSOFA scores were calculated. Multivariable logistic regression analysis was used to identify independent predictors of in-hospital mortality. Independent predictors were dichotomized according to cut-off values derived from receiver operating characteristic (ROC) curves and combined with qSOFA to construct new models. The ROC analysis with bootstrap validation was used to assess predictive performance, and comparative performance was further evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results A total of 218 patients were included. Multivariable logistic regression analysis identified blood urea nitrogen (BUN) [odds ratio (OR)=1.100, 95% confidence interval (CI) (1.040, 1.170)] and qSOFA [OR=2.610, 95%CI (1.450, 4.920)] as independent risk factors for in-hospital mortality, whereas high-density lipoprotein cholesterol (HDL-C) was an independent protective factor [OR=0.250, 95%CI (0.065, 0.841)]. After dichotomization by ROC-derived cut-off values, BUN and HDL-C were incorporated into qSOFA to generate B-qSOFA, H-qSOFA, and BH-qSOFA. Bootstrap ROC analysis showed that BH-qSOFA exhibited the highest discriminatory ability compared with all combined models as well as the conventional SOFA and qSOFA scores [area under the curve=0.803, 95%CI (0.735, 0.863)]. NRI and IDI analyses demonstrated that BH-qSOFA provided incremental prognostic improvement over qSOFA (NRI=0.969, IDI=0.165), B-qSOFA (NRI=0.644, IDI=0.054), and H-qSOFA (NRI=0.804, IDI=0.091) (all P<0.05). Conclusions Elevated BUN and qSOFA and decreased HDL-C are independent predictors of in-hospital mortality in sepsis. The BH-qSOFA model is simple and clinically practical, exhibits superior predictive performance over the original qSOFA. It may serve as a useful early instrument for prognostic risk stratification in patients with sepsis.