| Literature DB >> 36011449 |
Anastasios Sepetis1, Paraskevi N Zaza2, Fotios Rizos3, Pantelis G Bagos2.
Abstract
The healthcare sector is an ever-growing industry which produces a vast amount of waste each year, and it is crucial for healthcare systems to have an effective and sustainable medical waste management system in order to protect public health. Greek public hospitals in 2018 produced 9500 tons of hazardous healthcare wastes, and it is expected to reach 18,200 tons in 2025 and exceed 18,800 tons in 2030. In this paper, we investigated the factors that affect healthcare wastes. We obtained data from all Greek public hospitals and conducted a regression analysis, with the management cost of waste and the kilos of waste as the dependent variables, and a number of variables reflecting the characteristics of each hospital and its output as the independent variables. We applied and compared several models. Our study shows that healthcare wastes are affected by several individual-hospital characteristics, such as the number of beds, the type of the hospital, the services the hospital provides, the number of annual inpatients, the days of stay, the total number of surgeries, the existence of special units, and the total number of employees. Finally, our study presents two prediction models concerning the management costs and quantities of infectious waste for Greece's public hospitals and proposes specific actions to reduce healthcare wastes and the respective costs, as well as to implement and adopt certain tools, in terms of sustainability.Entities:
Keywords: Greece; climate change; healthcare waste; medical waste; public health; sustainability in healthcare; waste management
Mesh:
Substances:
Year: 2022 PMID: 36011449 PMCID: PMC9408452 DOI: 10.3390/ijerph19169821
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Hospital distribution in Greece per health region and hospital type.
| Health District | Small Hospitals | General Hospitals | University Hospitals | Specialized Type I Hospitals | Specialized Type II Hospitals |
|---|---|---|---|---|---|
| 1st | 1 | 11 | 0 | 7 | 3 |
| 2nd | 6 | 9 | 2 | 2 | 2 |
| 3rd | 0 | 14 | 0 | 1 | 0 |
| 4th | 1 | 10 | 2 | 0 | 1 |
| 5th | 2 | 10 | 1 | 0 | 0 |
| 6th | 6 | 19 | 2 | 1 | 0 |
| 7th | 3 | 4 | 1 | 0 | 0 |
Figure 1Schematic representation of the research methodology and the process of analysis.
Figure 2Cost (€) of hazardous waste management in 2018, per Health District in total and as a percentage of their total annual operating cost.
Average annual costs of hazardous waste management in 2018 for Greece’s public hospitals (per bed) by Health District.
| Health District | Average Annual Cost of Hazardous Waste per Bed (€) | Total Average Waste Cost per Bed (€) |
|---|---|---|
| 1st | 718 | 571.3 |
| 2nd | 630 | |
| 3rd | 355 | |
| 4th | 395 | |
| 5th | 467 | |
| 6th | 449 | |
| 7th | 601 |
Average annual costs of hazardous waste management in 2018 for Greece’s public hospitals (per patient) by Health District.
| Health District | Average Cost of Hazardous Waste per Patient (€) | Total Average Waste Cost per Patient (€) |
|---|---|---|
| 1st | 10.6 | 7.6 |
| 2nd | 10.7 | |
| 3rd | 4.4 | |
| 4th | 5.3 | |
| 5th | 6.1 | |
| 6th | 8.2 | |
| 7th | 9.0 |
Average quantities in kilos of hazardous waste generated per bed and day of hospitalization in 2018 for public hospitals in Greece by hospital type.
| Hospital Type | Average Kilos of Hazardous Waste per Bed per Day | Total Average Kilos of Hazardous Waste per Bed per Day |
|---|---|---|
| Small Hospital | 0.33 | 0.84 |
| General Hospital | 0.75 | |
| University Hospital | 0.99 | |
| Specialized Hospital I | 0.34 | |
| Specialized Hospital II | 1.00 |
Figure 3Average cost (€) of hazardous waste management for public hospitals in Greece in 2018 per patient and by health region.
Correlation table for the pairs of the statistically significant variables. High evidence of interdependencies (coefficient correlation > 0.5).
| Pairwise Correlations | LogWaste Cost | LogWaste Kilos | Beds | Hospital Type | ICU | Inpatients | Days of Stay | Employees |
|---|---|---|---|---|---|---|---|---|
| LogWaste Cost | 1.0000 | |||||||
| LogWaste Kilos | 0.9492 | 1.0000 | ||||||
| Beds | 0.6084 | 0.6790 | 1 | |||||
| Hospital Type | 0.2557 | 0.3017 | 0.3784 | 1.0000 | ||||
| ICU | 0.7271 | 0.7326 | 0.5579 | 0.1627 | 1.0000 | |||
| Inpatients | 0.7544 | 0.7712 | 0.8005 | 0.3044 | 0.6509 | 1.0000 | ||
| Days of stay | 0.6586 | 0.6961 | 0.9078 | 0.3149 | 0.5753 | 0.899 | 1.0000 | |
| Employees | 0.7759 | 0.799 | 0.924 | 0.3154 | 0.6436 | 0.8798 | 0.9217 | 1.0000 |
Regression analysis results. Coefficient of determination, R2, and statistically significant variables from each regression method for estimating management costs and the amount of infectious waste generated in Greek public hospitals.
| Dependent Variables | YEAR 2018 | |||||
|---|---|---|---|---|---|---|
| Seemingly Unrelated Regression | Multivariate Regression | Linear Regression | ||||
| Number of Obs = 121 | Number of Obs = 121 | Number of Obs = 121 | ||||
| R2 | Independent Variables | R2 | Independent Variables | R2 | Independent Variables | |
| Cost of hazardous waste | 0.8522 | Beds, Hosptype, Beds#Hosptype Icu, Inpatients, Days, Employees | 0.8603 | Beds, Hosptype, Beds#Hosptype Icu, Inpatients, Days, Employees | 0.8522 | Beds, Hosptype, Beds#Hosptype Icu, Inpatients, Days, Employees |
| Kilos of hazardous waste | 0.8594 | Beds, Hosptype, Beds#Hosptype Icu, Inpatients, Days, Employees, S.Surgeries | 0.8642 | Beds, Hosptype, Beds#Hosptype Icu, Inpatients, Days, Employees | 0.8471 | Beds, Hosptype, Beds#Hosptype Inpatients, Days, Employees |
Statistically significant variables (coefficients and their standard errors) with seemingly unrelated regression for prediction of cost for hazardous waste management in Greek public hospitals.
| Seemingly Unrelated Regression for the Cost of Hazardous Waste Management | R2 = 0.8522 | ||
|---|---|---|---|
| Number of Obs = 121 | |||
| Coefficient | (SE) | ||
| Constant | b0 | 8.013451 | (0.2663484) |
| Number of Beds | b1 | 0.0246254 | (0.0053255) |
| Hospital Type | |||
| General Hospital | b2 | 2.118334 | (0.2903447) |
| University Hospital | 5.640858 | (1.147168) | |
| Specialized Hospital Type I | 1.613669 | (0.3829162) | |
| Specialized Hospital Type II | 1.867596 | (0.6772875) | |
| Hospital Type # Beds | |||
| General Hospital | b3 | −0.0287761 | (0.0052831) |
| University Hospital | −0.0352248 | (0.0055343) | |
| Specialized Hospital Type I | −0.0278102 | (0.005303) | |
| Specialized Hospital Type II | −0.0276302 | (0.0057483) | |
| Intensive Care Unit | b4 | 0.4388912 | (0.1553799) |
| Total Internal Patients | b5 | 0.0000265 | (6.85 × 10−6) |
| Days of Stay | b6 | −0.00000633 | (2.83 × 10−6) |
| Total Number of Employees | b7 | 0.0030473 | (0.0003703) |
Statistically significant variables (coefficients and their standard errors) with seemingly unrelated regression for prediction of quantities of hazardous waste generated in Greek public hospitals.
| Seemingly Unrelated Regression for the Kilos of Hazardous Waste | R2 = 0.8594 | ||
|---|---|---|---|
| Number of Obs = 121 | |||
| Coefficient | (SE) | ||
| Constant | b0 | 6.711418 | (0.293857) |
| Number of Beds | b1 | 0.0268199 | (0.0058768) |
| Hospital Type | |||
| General Hospital | b2 | 2.482767 | (0.3203334) |
| University Hospital | 5.751815 | (1.26892) | |
| Specialized Hospital Type I | 1.803676 | (0.4244299) | |
| Specialized Hospital Type II | 2.805956 | (0.7482615) | |
| Hospital Type # Beds | |||
| General Hospital | b3 | −0.027856 | (0.0058301) |
| University Hospital | −0.0341217 | (0.0061111) | |
| Specialized Hospital Type I | −0.027567 | (0.0058515) | |
| Specialized Hospital Type II | −0.0285752 | (0.006342) | |
| Intensive Care Unit | b4 | 0.3689101 | (0.1717678) |
| Total Internal Patients | b5 | 0.0000337 | (7.68 × 10−6) |
| Days of Stay | b6 | −0.0000106 | (3.19 × 10−6) |
| Total Number of Employees | b7 | 0.0024858 | (0.0004086) |
| Scheduled Surgeries | b8 | −0.0000331 | (0.293857) |
Values of model A’s coefficients b2 and b3 for each hospital type.
| Hospital Type | b2 | b3 |
|---|---|---|
| Small Hospital/Health Center | 0 | 0 |
| General Hospital | 2.118334 | −0.0287761 |
| University Hospital | 5.640858 | −0.0352248 |
| Specialized Hospital Type I | 1.613669 | −0.0278102 |
| Specialized Hospital Type II | 1.867596 | −0.0276302 |
b4 = 1 when there is an ICU and 0 when there is not one.
Values of model B’s coefficients b2 and b3 for each hospital type.
| Hospital Type | b2 | b3 |
|---|---|---|
| Small Hospital/ Health Center | 0 | 0 |
| General Hospital | 2.482767 | −0.027856 |
| University Hospital | 5.751815 | −0.0341217 |
| Specialized Hospital I | 1.803676 | −0.027567 |
| Specialized Hospital II | 2.805956 | −0.0285752 |
b4 = 1 when there is an ICU and 0 when there is not one.
Figure 4Adjusted predictions of waste management cost for different hospital types and for different number of beds based on model A, if all other variables remain constant. Please note that the adjusted predictions of general hospitals coincide with the adjusted predictions of specialized hospitals type II.
Figure 5Average cost (€) of hazardous waste management for public hospitals in Greece per bed and per hospital type in 2018.
Figure 6Adjusted predictions of waste quantities generated (kilos) for different hospital types and for different number of beds based on model B, if all other variables remain constant.
Figure 7Predicted cost (logarithms) of waste management based on model A (y-axis) vs. observed values (logarithms) of cost for 2018.