JMIR Publications

ABSTRACT

Background:

Computerized clinical decision support systems (CDSS) have the potential to improve quality of care and efficiency in clinical practice. Postoperative delirium (POD) is a common and serious complication among older surgical patients and is associated with adverse outcomes and increased healthcare costs. Digi-POD is a CDSS designed to enhance guideline adherence in the prevention and management of POD. Despite increasing use of CDSS, evidence on their cost-effectiveness remains limited.

Objective:

This study aims to evaluate the cost-effectiveness of Digi-POD compared with standard care in older surgical patients in Germany, considering both short-term and long-term outcomes. Additionally, the study assesses potential productivity gains associated with Digi-POD implementation.

Methods:

This economic evaluation is conducted alongside a multicenter, prospective, non-randomized controlled before–after study in four German hospitals. Patients aged ≥70 years undergoing elective surgery are included. During the intervention phase - including the preoperative phase, the day of surgery, and the first five postoperative days - patients receive Digi-POD supported care. Digi-POD is a computerized clinical decision support system that provides real-time, evidence based recommendations for POD risk assessment, prevention, and management based on clinical guidelines. Patients in the control phase receive standard postoperative care without CDSS support. Co-primary outcomes are guideline adherence and proportion of POD-free days within the first five postoperative days. Costs are assessed from the statutory health insurance perspective, with a secondary analysis from the provider perspective. Incremental cost-effectiveness ratios (ICERs) will be estimated using regression-based approaches, specifically time-adjusted seemingly unrelated regression models accounting for confounding, study center effects, and temporal trends. Statistical uncertainty will be assessed using nonparametric bootstrapping, and sensitivity analyses will explore the robustness of results under alternative model specifications and assumptions. Long-term outcomes and productivity effects will be analyzed in secondary analyses using appropriate regression methods.

Results:

Patient recruitment has been completed, and follow-up data collection is ongoing. Data analysis is planned to begin in July 2026, with results expected in 2027.

Conclusions:

This study will provide real-world evidence on the cost-effectiveness and efficiency of a CDSS for POD prevention and inform decision-making on the implementation of digital health interventions in hospital care. Clinical Trial: ClinicalTrials.gov NCT06445153; http://clinicaltrials.gov/study/NCT06445153, (Date of registration: June 5, 2024)