The aim of this study was to estimate OC from a hospital perspective to determine the potential for infection prevention interventions in hospitals. Three main findings were reported. First, patients with NI stayed in the hospital significantly longer than patients without NI. Second, the daily revenue for patients with NI was significantly lower than that for patients without NI; third, the resulting OCs for patients with NI are high and pose a substantial economic burden from a hospital perspective. Therefore, we see strong economic incentives for hospitals to implement appropriate infection prevention measures.
Our findings are in line with those of previous studies. An article from Germany considering only CDAD estimated the opportunity cost to be €5,263 [8]. The same applies to the additional LOS in patients with NI. The published literature reports an excess LOS of approximately 10 days for patients with SSI [9, 22].
We found that comorbidities had a significant effect on the LOS. Previous studies have shown that comorbidities contribute to a longer LOS [23, 24]. For patients with multiple comorbidities, there might also be a greater risk of developing (more) complications and being less independent than for patients with fewer comorbidities. Both aspects lead to longer hospital stays, which then increase the risk of NI [21]. For example, Karaoui et al. [25] identified previous hospitalization and comorbidities as significant risk factors for NI. A similar observation applies when looking at the number of operations. Obviously, the more frequently a patient undergoes surgery, the longer the LOS and the greater the risk that this patient will acquire an NI. Longer hospital stays can lead to colonization of patients with pathogenic microorganisms, increasing the likelihood of infection with NI [21, 26, 27]. Similarly, we found that both comorbidity and the number of operations were statistically significant predictors (p < 0.001) of prolonged LOS in our multivariate regression model.
In addition to prolonging the LOS, NIs impose a significant economic burden on hospitals because they result in a loss in daily revenues. The multivariate regression underscores that age serves as a statistically significant predictor of the loss in daily hospital revenues. The estimated coefficient implies that each additional 10 life-years reduced daily revenue by approximately €70. This finding aligns with the observations of Lange et al. [28], who found that the main cost drivers for high-cost insureds in the German hospital sector were cerebral infarction, heart failure, atherosclerosis, fracture of the femur, and acute myocardial infarction. These diseases, which are more common in older people, may explain the significant effect of age on daily revenues.
Our analysis aims to shed light on the economic incentives for preventing NIs from a hospital’s perspective. The results indicate that individuals with NIs are associated with a daily revenue decline surpassing €400 per patient. Given our robust estimate of an additional 10-day LOS due to NI, the estimated daily revenue loss translates to an approximate revenue loss of €4,000 per NI patient. Our estimate is in line with the assessment of revenue loss for CDAD in Germany by Grube et al. [29], who calculated losses of €3,442 for secondary diagnoses and €4,194 for recurrent diagnoses in 2011. Overall, our findings suggest that hospitals can maintain profitability by effectively managing NIs, as they have the potential to replace each NI patient with 2 non-NI patients, thereby increasing overall hospital gross revenues [30]. Assuming that most of a hospital´s costs are fixed (e.g., staff costs), this also means higher profits for the hospital.
The multivariate analysis underscores the substantial impact of comorbidity and the number of operations on the hospital's OC. Specifically, patients with baseline comorbidities experience prolonged hospital stays, leading to a notable increase in forgone revenue and, consequently, OC. These findings align with those of Karaoui et al. [25], who highlighted the significance of prior comorbidity scores as primary predictors in their cohort study. Additionally, the number of operations has emerged as a pivotal factor influencing OC for patients with NI. From a hospital perspective, managing and minimising comorbidities and optimising surgical procedures can significantly contribute to reducing the OC associated with treating NI patients.
At the same time, given an average OCR of 81.6% for Germany in 2016, the estimates of LOS and daily revenue suggest that preventing a single NI case would lead to the release of 10 blocked hospital beds per NI patient, potentially allowing 2 additional admissions of non-NI patients (median LOS). Since the NI patient pays €700 (median DRG for NI patients) and the non-NI patients each pay €1,000, preventing a single NI would be equivalent to an increase in gross daily revenues for the hospital of €1,300. Since 30–50% of NIs are preventable [31], these estimates imply that hospital revenue increases by approximately €390 to €650 per NI patient prevented per day. If the hospital has no extra non-NI patient to fill the newly freed beds, the loss of revenue often leads to changes in resource allocation and/or staffing [30].
Strength & limitations
This study analysed the economic burden of NIs on a surgical and orthopedic unit of a German hospital from 2018 to 2019 using data provided by routine accounting department data. While our study provides valuable insights into the economic evaluation of NIs, it is important to acknowledge certain limitations. We lacked information on some sociodemographic variables, such as patients' education and income levels. Therefore, our multivariate regression estimates may be biased due to unobserved and unadjusted covariates via channels related to healthcare practices and access to treatments.
Furthermore, the type of infection was not evenly distributed across the sample, and SSI was the most common infection, as the data were collected from a sample of patients treated at an orthopedic or surgical unit. As a result, we were unable to analyse the revenue loss, LOS and OC per infection type. However, our results have a high transferability for similar units in other hospitals. Nevertheless, to the best of our knowledge, this is the first study estimating opportunity costs in Germany considering different types of NI. The applied matching method enabled us to generate a good balanced sample and thus estimate robust outcomes. Therefore, the findings of this study could provide valuable input for future economic assessments.
Conclusion and Implications
NIs are associated with high opportunity costs for hospitals. Therefore, it can be concluded that the economic benefits of preventing NI are high. Hospitals have strong incentives to implement comprehensive infection control measures and interventions. Currently, there is evidence supporting the effectiveness of various measures for preventing NI. These measures include implementing a complex infection prevention bundle by a prevention link physician [32], introducing an infection control link nurse [33], surveilling the NI [34], improving adherence to hand hygiene [32, 35] and changing dressing. A next step should be to evaluate the cost-effectiveness of these interventions in Germany.