Evaluation of hospital readmissions for surgical site infections in Italy

Evaluation of hospital readmissions for surgical site infections in Italy Abstract Background The objectives of this investigation are to assess the prevalence of hospital readmissions for surgical site infections (SSIs) in patients aged ≥18 in Italy and to describe the clinical characteristics of these patients and evaluate the possible association with readmission for SSIs. Methods A retrospective epidemiological study was conducted between January and May 2015 considering a sample of patients aged ≥18 years admitted to the surgical wards of two hospitals in Naples and undergoing surgery in the year 2014. Results 3.8% of patients had been readmitted and 28.8% of them were readmitted to hospital due to SSIs. The multiple logistic regression model showed that readmissions for SSIs were significantly more common in smokers (odds ratio [OR] = 3.14; 95% confidence interval [CI] = 1.13–8.69), in patients with immunosuppression status (OR = 8.28; 95% CI = 1.76–38.87), in patients with low serum albumin (OR = 3.07; 95% CI = 1.05–9.01) and in patients who had undergone a surgical procedure classified as contaminated (OR = 10:44; 95% CI = 3.11–35.01) compared with those that had undergone a surgical procedure classified as clean. Conclusions The results point to the need that hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in health spending since almost one third of readmissions to the hospital in our study were due to SSIs. Introduction Surgical site infections (SSIs) are amongst the most frequent health care infections and represent a common complication for patients who undergo surgery.1 Indeed in Europe, previous prevalence studies have demonstrated that SSIs are the second most frequent cause of healthcare associated infections and occur in 1.3% of inpatients in acute care hospitals.2 In particular, in Italy, a prevalence of SSIs in 2.6% of surgical procedures in 2009–11 has been reported.3 It is well-known that SSIs depend on several factors involving patients, health care professionals and hospitals including patients’ health status, wound contamination class and the preventive measures to which the patient is subjected before, during and after the surgical procedures.4 Despite significant progress achieved in understanding of SSIs mainly regarding the main risk factors associated and their prevention and control measures, SSIs still continue to represent a relevant problem for the public health as they can determine an increase in mortality and a longer hospital stay with a considerable increase of expenditure of health care resources.5 Moreover, patients with SSIs can have prolonged antibiotic therapy and revision of surgical procedures and may be more likely to have a hospital readmission or intensive care treatment compared with those without infections.6 The readmissions for SSIs represent a minimal portion of SSI burden which may be investigated through in-hospital and post-discharge surveillance. However, although the prospective longitudinal surveillance is the ideal approach to understanding the weight of these infections, this surveillance system is very expensive and requires a challenging work of healthcare professionals. For this reason, the prevalence studies are the most commonly used for monitoring infections as they are able to provide information on the distribution of SSIs in a short time and with limited resources use. Moreover, it is well-established that SSIs are amongst the most common reasons for readmission in surgical patients7–10 and, since readmissions are increasingly used as a measure of the quality of hospital care, the understanding of the frequency of readmissions for SSIs represents for the hospital where they occur an opportunity to improve quality and the effectiveness of care in surgical patients and to expand the knowledge about the SSIs’ complications. Several investigations have been carried out to evaluate the frequency of SSIs11–17 and the associated factors, whilst to the best of our knowledge little data are available worldwide regarding the frequency of hospital readmissions for SSIs and in particular no data are available on this topic in Italy.18–20 Therefore, this retrospective epidemiological investigation has the following primary objectives. The first is to assess the frequency of hospital readmissions for SSIs in a sample of patients who underwent general and specialty surgery in Italy. The second aim is to evaluate the role of clinical history of the patients and the characteristics of the surgical procedures as determinants of readmission in hospital for SSIs. Methods Between January and May 2015 a retrospective study was conducted considering a sample of patients aged ≥18 years admitted to the surgical wards and undergoing surgery in the year 2014 in two hospitals in Naples, and in particular in an academic hospital with 382 and in a public acute care hospital with 168 beds. In particular, from the list of public hospitals in Naples, two hospitals were selected amongst those for which administrative data were available and all admissions in surgical wards of the selected hospitals were examined. Patients who died during hospitalization and who had undergone emergency procedures were excluded. Before starting the investigation, a letter was delivered to the medical director of the hospitals to describe the purpose of the study to ensure the confidentiality of patients’ data and to obtain approval. Following the approval, all admissions to the surgical wards were examined using administrative data. In particular, from the hospital administrative data it was possible to collect the following information for all surgical patients: gender, age, marital status, educational level, ward of admission, length of hospital stay, date of admission and discharge, date of admission and discharge, number of readmission in hospital. Subsequently, only the medical records of each patient readmitted after the first admission for the surgery were requested from the hospital for examination. The readmissions to hospital for SSIs have been defined as readmission of patients who had had SSI within thirty days after surgery or within one year for those who had an implant of prosthesis. The SSIs were defined according to the criteria of the European Centers for Disease Control and Prevention21 or based on the reasons for the hospitalization reported in the medical records or an ICD-9 diagnosis code indicating SSI. The information collected from the medical records was reviewed and summarized on a standardized case report form by two investigators not directly involved in patient care. The following characteristics were collected: age, gender, weight, height, ward type, admission diagnosis, date and day of the week, length of hospital stay, smoking status, diabetes, systemic steroid use, poor nutritional status, chemotherapy/radiotherapy, transfusion of blood products, comorbidity Charlson index,22 surgical wound classification,23 type and length of the surgery (minutes), American Society of Anesthesiologists (ASA) Score, time interval between the date of surgical procedure and readmission, presence of SSI, antibiotic therapy for SSIs, microbiological culture test, surgery during the readmission and details of perioperative antibiotic prophylaxis. The antibiotic prophylaxis has been evaluated for each surgical procedure and was considered appropriate if the choice of antibiotic administration, when indicated, the timing, the doses and the length of administration were in according to the Italian national guidelines.24 The protocol of the study was approved by the Ethical Committee of the University of Campania ‘Luigi Vanvitelli’ of Naples. Statistical analysis The collected data were entered into a database in the form of numeric codes and a quality check of database was carried out before starting the statistical analysis. Statistical analyses were conducted in several stages. First, descriptive analyses were performed to describe and summarize the information available from administrative data for all surgical patients and then the characteristics of readmitted patients. Secondly, for the sample of readmitted patients, bivariate analysis was performed using chi-square test or Fischer exact test for all categorical variables and Student’s t-test for continuous variables. Following, a multivariate stepwise logistic regression analysis was performed to investigate the independent characteristics associated with the outcome of interest: profile of patients with a readmission for a SSI (readmission for other reasons = 0; readmission for SSI = 1). The significance levels for the exclusion and inclusion of variables in the model were 0.4 and 0.2, respectively. All inferential tests were performed through the execution of bilateral hypothesis test with statistical significance level of P values equal to or less than 0.05. The results of multivariate regression analyses were reported as odds ratios (ORs) and 95% confidence intervals (CIs). In the logistic regression model the following independent variables were included: age (continuous), sex (male = 0; female = 1), surgical ward of hospital stay (general = 0, specialties = 1), smoking status (no = 0, yes =1), immunosuppression status (no = 0, yes = 1), low serum albumin (no = 0, yes = 1), diabetes (no = 0, yes = 1), ASA score (ASA I = 0; ASA II, III and IV = 1), surgical wound classification (clean = 1, clean-contaminated = 2, contaminated = 3), length of hospital stay in days (continuous), length of surgery in minutes (continuous), endoscopic surgery (no = 0, yes = 1), the implant of prosthesis (no = 0, yes = 1), appropriateness of perioperative antibiotic prophylaxis (no = 0, yes = 1). The independent variables to include in the model were chosen based on the previous investigations in published literature and because they were considered as interesting predictors of the outcome. Statistical analyses were performed using Stata version 10.1 software.25 Results A total of 3815 surgical procedures performed in the year 2014 on patients ≥ 18 years of age admitted to the ordinary regime were included. More than half of the patients were female (60.2%), the average age was 53 years (range 18–107), more the half of patients were married (56.1%), 34.1% had at least a secondary school educational level, more than half of the procedures were performed in specialist surgery and the average length of hospital stay was 7 days (range 1–137). Table 1 shows the main characteristics of the patients who had had at least one readmission after the previous surgery and the main risk factors SSIs compared with those for patients who had had at least one readmission due to SSI. Overall, 145 patients had a readmission, 61.4% of them were female with an average age of 56 years (range 18–87) and 54.5% of the examined procedures were performed in general surgery wards. The average length of hospital stay for these patients was 9.6 days and the average time between the admission for surgical procedure and readmission was 15.6 days. Table 1 Main characteristics and risk factors of study population associated with the patients readmitted for SSI Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Surgical site infections (SSI). a Mean ± standard deviation (range). b Mean ± standard deviation (range) for readmitted patients without SSIs. Table 1 Main characteristics and risk factors of study population associated with the patients readmitted for SSI Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Surgical site infections (SSI). a Mean ± standard deviation (range). b Mean ± standard deviation (range) for readmitted patients without SSIs. With regard to the risk factors for SSIs, 33.8% of readmitted patients were smokers, 22.8% had diabetes, 10.3% had immunosuppression status and one in five had a poor nutritional status with a low serum albumin (22.1%). During the first admission for surgery, 39.3% of patients had undergone a surgical procedure classified as clean, 51.7% as clean-contaminated and only 14.5% had undergone a surgical procedure classified as contaminated. Moreover, 26.2% of patients had received an endoscopic approach, more than half (57.9%) had undergone surgery under general anaesthesia and in 75.2% of the examined procedures were administered antibiotics as surgical prophylaxis. Perioperative antibiotic prophylaxis was appropriate only for the 9.2% of procedures where the antibiotics were indicated, and considering all surgical procedures, only the 6.9% of the perioperative antibiotic prophylaxis was appropriate. In total, 1.1% (41 patients) of the sample had a readmission for SSIs and these representing the 28.3% of all readmitted patients. Other main reasons for hospital readmission were in order planned readmissions for surgical procedures (22.1%), progression/reoccurrence of diseases (15.2%), admission for diagnostic and therapeutic procedures (11.4%) and non-infectious surgical complications (7.6%). As shown in the bivariate analyses in table 1, a significantly higher frequency of patients who had a readmission for SSIs was observed amongst patients admitted to the general surgery ward (χ2=4.39; P = 0.036), amongst those with diabetes (χ2=6.21; P = 0.013), in patients with low serum albumin (χ2=9.55; P = 0.002), amongst those who had undergone a surgical procedures classified as contaminated (χ2=18.77; P < 0.001) and in those who had had a greater length of surgery (t=-2.49; P =0.014). The results of the multivariate regression were substantially similar to the bivariate associations and revealed that the readmissions for SSIs were significantly more likely in smokers (OR = 3.14; 95% CI = 1.13–8.69), in patients with immunosuppression status (OR = 8.28; 95% CI = 1.76–38.87), in patients with low serum albumin (OR = 3.07; 95% CI = 1.05–9.01) and in patients who had undergone surgical procedures classified as contaminated (OR = 10.44; 95% CI = 3.11–35.01) compared with those that had undergone a surgical procedure classified as clean (table 2). Table 2 Multivariate logistic regression model for potential predictors of the readmission for SSIs Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 a Reference category. Table 2 Multivariate logistic regression model for potential predictors of the readmission for SSIs Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 a Reference category. The types of SSIs that occurred were for 26.8% of cases superficial SSI, for 48.8% of cases deep SSIs and in 24.4% of cases involving organs or spaces. A microbiological culture test was performed only for 16 patients with SSIs (39%) and the more frequently isolated microorganisms were Staphiloccoccus aureus (seven cases) and Candida albicans (two cases). Considering all surgical procedures only 4.9% of perioperative antibiotic prophylaxis amongst readmitted patients for SSIs was appropriate. 88.2% of SSIs were treated with antibiotics. Discussion To the best of our knowledge, this is the first investigation conducted in Italy that has evaluated readmissions for SSIs of patients undergoing surgery in both general surgeries wards that specialty surgery and represent the first survey that has assessed which factors could be associated predictors to readmissions. As well as reported by other investigation, the results of this study show that SSIs are the most common reasons for readmission in surgical patients, given that 28.3% of patients readmitted after the first admission for surgery were readmitted to hospital due to SSIs. This is an interesting result because the readmission rates are increasingly seen as a gauge of the quality of care provided by the hospital. Indeed, since the readmissions for SSIs are potentially avoidable readmissions, understanding their impact on hospital care is useful for the hospital management to implement programs to decrease the number of these readmissions, reduce healthcare expenditures and improve quality of care and patients safety. Previous experience published on this topic in Italy had well-documented the prevalence of hospital readmissions and it is interesting to mark that in this study the potentially avoidable readmissions were significantly more likely amongst patients admitted in general surgery wards.26 Several studies worldwide have evaluated the readmission for SSIs for specific surgical procedures, but there is a dearth of literature that evaluated the frequency of readmission for the totality of surgical procedures performed in surgical wards after the first admission. Therefore, it is very difficult to compare to previous studies due to different objectives, sample and methodology. The readmission rate for SSIs in our sample is similar to values found in two studies conducted in the US amongst neurosurgery patients where SSIs were the most common reasons for readmissions.18,19 Moreover, SSIs was the cause of 22.1% of readmissions in a study conducted amongst general surgery patients.27 In other studies, the rates of readmission for SSIs were lower than those observed in our study. In particular, in a study conducted in Texas, amongst patients readmitted 8.6% had a SSI20 and SSI was the cause of 17.7% of readmissions in a study who evaluated the hospital readmission after total hip arthroplasty.28 Finally, in a retrospective cohort study that evaluated the readmission of orthopaedic surgical patients, 38% of the surgical readmissions were due to SSIs.29 An interesting finding of our study was that only 6.9% of perioperative antibiotics prophylaxis performed during the first admission for surgery was appropriate amongst those readmitted with SSIs, although at multivariate analysis the appropriateness of perioperative antibiotic prophylaxis was not associated with readmission for SSIs. A low value of appropriate antibiotics prophylaxis was found also in recent studies published in Italy regarding the appropriate use of surgical antibiotic prophylaxis.30–32 However, performing an appropriate antibiotic prophylaxis is essential not only to reduce the incidence of SSIs but above all to reduce the risk of anti-microbial resistance and other serious complications for patients. Moreover, this study results may have important implications for the development of quality-improvement programs within the hospital for the purpose of developing appropriate practices regarding the administration of antibiotics. Moreover, during the considered period, a clinical culture was carried out only for 39% of patients with a SSI. This result must raise awareness of healthcare workers of the need to demand timely cultural examinations in order to provide the etiologic diagnosis of the infectious disease. Indeed, the main purpose of the cultural examination is to recommend an appropriate antibiotic treatment and to identify adequate prevention strategies. The results of bivariate and multivariate logistic regression analysis also showed that several risk factors for SSIs are significant determinants for readmissions. For example, contaminated surgical wound, immunosuppression status, low serum albumin and diabetes were strongly associated factors. These results indicate that, whenever possible, greater efforts should be made during hospitalization and post-discharge surveillance to prevent and correct all those clinical conditions that represent risk factors for infections before they require readmission to the hospital. Then, although not all SSIs are avoidable, understanding which clinical characteristics have patients is important to determine how to prevent complications related also to surgery and thus these measures may result in reducing hospital readmissions and decrease consequently healthcare costs. This study has some limitations that must be considered for proper interpretation of the results. The first limit is that this is a retrospective investigation that, unlike the prospective longitudinal study, does not represent the ideal study for the evaluation of the frequency of SSIs and then of readmissions for SSIs. Secondly, the readmissions of patients have been evaluated only in two hospitals and thus the rate of readmissions may be underestimated because some patients could have been readmitted to other hospitals. The third limitation is that the readmission rate for SSIs may also be underestimated due to the lack of information in the medical records that did not allow us to clarify for all patients the reason for hospital readmission. Despite these limits, this investigation has a large sample size, the retrospective data were collected carefully for a one-year period and therefore we are confident that the results of this study are valid. In conclusion, the results point to the need for the hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in healthcare spending given that almost one third of readmissions to the hospitals in our study were due to SSIs. Acknowledgements The authors gratefully acknowledge the staff of the hospitals without whom this study would not have been possible. Members of the Collaborative Working Group are: Maurizio di Mauro (University Hospital University of Campania ‘Luigi Vanvitelli’, Naples) and Vito Rago (Hospital San Giovanni Bosco, Naples). Funding This study was supported by the Department of Experimental Medicine, University of Campania ‘Luigi Vanvitelli’. Conflicts of interest: None declared. Key points This is the first investigation conducted in Italy that evaluates readmissions for SSIs of patients undergoing surgery and represents the first survey that has assessed which factors could be associated predictors to readmissions. The results of this study show that the 28.3% of patients readmitted within 365 days from the first admission for surgery were readmitted to hospital due to SSIs. The results point to the need that hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in healthcare spending given that almost one third of readmissions to the hospitals in our study were due to SSIs. References 1 European Centre for Disease Prevention and Control . Annual Epidemiological Report 2016 – Surgical site infections. Stockholm: ECDC; 2016. Available at: http://ecdc.europa.eu/en/healthtopics/healthcare-associated_infections/surgical-siteinfections/pages/annual-epidemiological-report-for-2014.aspx (20 June 2017, date last accessed). 2 European Centre for Disease Prevention and Control . Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals. Stockholm: ECDC; 2013. Available at: http://ecdc.europa.eu/en/publications/Publications/healthcare-associated-infections-antimicrobial-use-PPS.pdf (20 June 2017, date last accessed). 3 Marchi M , Pan A , Gagliotti C , et al. The Italian national surgical site infection surveillance programme and its positive impact, 2009 to 2011 . Euro Surveill 2014 ; 19 : 4 European Centre for Disease Prevention and Control . Surveillance of surgical site infections in Europe 2010–2011. Stockholm: ECDC; 2013. Available at: http://ecdc.europa.eu/en/publications/Publications/SSI-in-europe-2010-2011.pdf (20 June 2017, date last accessed). 5 World Health Organization (WHO) . Report on the burden of endemic health care-associated infection worldwide. Geneva: WHO; 2011 . Available at: http://apps.who.int/iris/bitstream/10665/80135/1/9789241501507_eng.pdf (20 June 2017, date last accessed). 6 Badia JM , Casey AL , Petrosillo N , et al. Impact of surgical site infection on healthcare costs and patient outcomes: a systematic review in six European countries . J Hosp Infect 2017 ; 96 : 1 – 15 . Google Scholar CrossRef Search ADS PubMed 7 Osborn HA , Rathi VK , Tjoa T , et al. Risk factors for thirty-day readmission following flap reconstruction of oncologic defects of the head and neck . Laryngoscope 2017 . doi: 10.1002/lary.26726. 8 Puvanesarajah V , Nourbakhsh A , Hassanzadeh H , et al. Readmission rates, reasons, and risk factors in elderly patients treated with lumbar fusion for degenerative pathology . Spine (Phila Pa 1976) 2016 ; 41 : 1933 – 8 . Google Scholar CrossRef Search ADS PubMed 9 Akamnonu C , Cheriyan T , Goldstein JA , et al. Unplanned hospital readmission after surgical treatment of common lumbar pathologies: rates and causes . Spine (Phila Pa 1976) 2015 ; 40 : 423 – 8 . Google Scholar CrossRef Search ADS PubMed 10 Chow I , Hanwright PJ , Hansen NM , et al. Predictors of 30-day readmission after mastectomy: a multi-institutional analysis of 21,271 patients . Breast Dis 2015 ; 35 : 221 – 31 . Google Scholar CrossRef Search ADS PubMed 11 Cato KD , Liu J , Cohen B , Larson E . Electronic surveillance of surgical site infections . Surg Infect (Larchmt) 2017 ; 18 : 498 – 502 . Google Scholar CrossRef Search ADS PubMed 12 Legesse Laloto T , Hiko Gemeda D , Abdella SH . Incidence and predictors of surgical site infection in Ethiopia: prospective cohort . BMC Infect Dis 2017 ; 17 : 119 . Google Scholar CrossRef Search ADS PubMed 13 Morikane K . Epidemiology and risk factors associated with surgical site infection after different types of hepatobiliary and pancreatic surgery . Surg Today 2017 . doi: 10.1007/s00595-017-1503-0. 14 Pakzad R , Safiri S . Incidence and risk factors for surgical site infection posthysterectomy in a tertiary care center: methodologic issues . Am J Infect Control 2017 ; 45 : 580 – 1 . Google Scholar CrossRef Search ADS PubMed 15 Pop-Vicas A , Musuuza JS , Schmitz M , et al. Incidence and risk factors for surgical site infection post-hysterectomy in a tertiary care center . Am J Infect Control 2017 ; 45 : 284 – 7 . Google Scholar CrossRef Search ADS PubMed 16 Magill SS , Edwards JR , Bamberg W , et al. Multistate point-prevalence survey of health care-associated infections . N Engl J Med 2014 ; 370 : 1198 – 208 . Google Scholar CrossRef Search ADS PubMed 17 Zarb P , Coignard B , Griskeviciene J , et al. The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use . Euro Surveill 2012 ; 17 :pii 20316. 18 Karhade AV , Vasudeva VS , Dasenbrock HH , et al. Thirty-day readmission and reoperation after surgery for spinal tumors: a National Surgical Quality Improvement Program analysis . Neurosurg Focus 2016 ; 41 : E5 . Google Scholar CrossRef Search ADS PubMed 19 Webb ML , Nelson SJ , Save A , et al. Of 20, 376 lumbar discectomies, 2.6% of patients readmitted within 30 days: surgical site infection, pain, and thromboembolic events are the most common reasons for readmission . Spine (Phila Pa 1976) 2017 ; 42 : 1267 – 73 . Google Scholar CrossRef Search ADS PubMed 20 Sreeramoju P , Montie B , Ramirez AM , Ayeni A . Healthcare-associated infection: a significant cause of hospital readmission . Infect Control Hosp Epidemiol 2010 ; 31 : 1195 – 7 . Google Scholar CrossRef Search ADS PubMed 21 European Centre for Disease Prevention and Control . Surveillance of surgical site infections and prevention indicators in European hospitals – HAISSI protocol. Stockholm: ECDC; 2017 . Available at: http://ecdc.europa.eu/en/publications/_layouts/forms/Publication_DispForm.aspx? List=4f55ad51-4aed-4d32-b960-af70113dbb90&ID=1695 (20 June 2017, date last accessed). 22 Charlson ME , Pompei P , Ales KL , MacKenzie CR . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation . J Chronic Dis 1987 ; 40 : 373 – 83 . Google Scholar CrossRef Search ADS PubMed 23 Surgical Site Infection (SSI) Event: Center for Disease Control. 2010 . Available at: https://www.cdc.gov/nhsn/pdfs/pscmanual/9pscssicurrent.pdf (25 September 2017, date last accessed). 24 SNLG – Antibioticoprofilassi perioperatoria nell’adulto – Linea Guida . 2011 . Available at: http://www.snlg-iss.it/cms/files/LG_AntibioticoP_Unico_2008.pdf (20 June 2017, date last accessed). 25 Stata Corporation : Stata Reference Manual Release 10.1 . College Station, TX, USA ; 2007 . Available at: www.stata.com (18 November 2017, date last accessed). 26 Bianco A , Molè A , Nobile CG , et al. Hospital readmission prevalence and analysis of those potentially avoidable in southern Italy . PLoS ONE 2012 ; 7 : e48263 . Google Scholar CrossRef Search ADS PubMed 27 Kassin MT , Owen RM , Perez SD , et al. Risk factors for 30-day hospital readmission among general surgery patients . J Am Coll Surg 2012 ; 215 : 322 – 30 . Google Scholar CrossRef Search ADS PubMed 28 Schairer WW , Sing DC , Vail TP , Bozic KJ . Causes and frequency of unplanned hospital readmission after total hip arthroplasty . Clin Orthop Relat Res 2014 ; 472 : 464 – 70 . Google Scholar CrossRef Search ADS PubMed 29 Bernatz JT , Tueting JL , Hetzel S , Anderson PA . What are the 30-day readmission rates across orthopaedic subspecialties? Clin Orthop Relat Res 2016 ; 474 : 838 – 47 . Google Scholar CrossRef Search ADS PubMed 30 Giordano M , Squillace L , Pavia M . Appropriateness of surgical antibiotic prophylaxis in pediatric patients in Italy . Infect Control Hosp Epidemiol 2017 ; 38 : 823 – 31 . Google Scholar CrossRef Search ADS PubMed 31 Bianco A , Larosa E , Pileggi C , et al. Appropriateness of intrapartum antibiotic prophylaxis to prevent neonatal group B streptococcus disease . PLoS ONE 2016 ; 11 : e0166179 . Google Scholar CrossRef Search ADS PubMed 32 Napolitano F , Izzo MT , Di Giuseppe G , et al. Evaluation of the appropriate perioperative antibiotic prophylaxis in Italy . PLoS ONE 2013 ; 8 : e79532 . Google Scholar CrossRef Search ADS PubMed © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Evaluation of hospital readmissions for surgical site infections in Italy

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Oxford University Press
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© The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
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1101-1262
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1464-360X
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10.1093/eurpub/ckx205
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Abstract

Abstract Background The objectives of this investigation are to assess the prevalence of hospital readmissions for surgical site infections (SSIs) in patients aged ≥18 in Italy and to describe the clinical characteristics of these patients and evaluate the possible association with readmission for SSIs. Methods A retrospective epidemiological study was conducted between January and May 2015 considering a sample of patients aged ≥18 years admitted to the surgical wards of two hospitals in Naples and undergoing surgery in the year 2014. Results 3.8% of patients had been readmitted and 28.8% of them were readmitted to hospital due to SSIs. The multiple logistic regression model showed that readmissions for SSIs were significantly more common in smokers (odds ratio [OR] = 3.14; 95% confidence interval [CI] = 1.13–8.69), in patients with immunosuppression status (OR = 8.28; 95% CI = 1.76–38.87), in patients with low serum albumin (OR = 3.07; 95% CI = 1.05–9.01) and in patients who had undergone a surgical procedure classified as contaminated (OR = 10:44; 95% CI = 3.11–35.01) compared with those that had undergone a surgical procedure classified as clean. Conclusions The results point to the need that hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in health spending since almost one third of readmissions to the hospital in our study were due to SSIs. Introduction Surgical site infections (SSIs) are amongst the most frequent health care infections and represent a common complication for patients who undergo surgery.1 Indeed in Europe, previous prevalence studies have demonstrated that SSIs are the second most frequent cause of healthcare associated infections and occur in 1.3% of inpatients in acute care hospitals.2 In particular, in Italy, a prevalence of SSIs in 2.6% of surgical procedures in 2009–11 has been reported.3 It is well-known that SSIs depend on several factors involving patients, health care professionals and hospitals including patients’ health status, wound contamination class and the preventive measures to which the patient is subjected before, during and after the surgical procedures.4 Despite significant progress achieved in understanding of SSIs mainly regarding the main risk factors associated and their prevention and control measures, SSIs still continue to represent a relevant problem for the public health as they can determine an increase in mortality and a longer hospital stay with a considerable increase of expenditure of health care resources.5 Moreover, patients with SSIs can have prolonged antibiotic therapy and revision of surgical procedures and may be more likely to have a hospital readmission or intensive care treatment compared with those without infections.6 The readmissions for SSIs represent a minimal portion of SSI burden which may be investigated through in-hospital and post-discharge surveillance. However, although the prospective longitudinal surveillance is the ideal approach to understanding the weight of these infections, this surveillance system is very expensive and requires a challenging work of healthcare professionals. For this reason, the prevalence studies are the most commonly used for monitoring infections as they are able to provide information on the distribution of SSIs in a short time and with limited resources use. Moreover, it is well-established that SSIs are amongst the most common reasons for readmission in surgical patients7–10 and, since readmissions are increasingly used as a measure of the quality of hospital care, the understanding of the frequency of readmissions for SSIs represents for the hospital where they occur an opportunity to improve quality and the effectiveness of care in surgical patients and to expand the knowledge about the SSIs’ complications. Several investigations have been carried out to evaluate the frequency of SSIs11–17 and the associated factors, whilst to the best of our knowledge little data are available worldwide regarding the frequency of hospital readmissions for SSIs and in particular no data are available on this topic in Italy.18–20 Therefore, this retrospective epidemiological investigation has the following primary objectives. The first is to assess the frequency of hospital readmissions for SSIs in a sample of patients who underwent general and specialty surgery in Italy. The second aim is to evaluate the role of clinical history of the patients and the characteristics of the surgical procedures as determinants of readmission in hospital for SSIs. Methods Between January and May 2015 a retrospective study was conducted considering a sample of patients aged ≥18 years admitted to the surgical wards and undergoing surgery in the year 2014 in two hospitals in Naples, and in particular in an academic hospital with 382 and in a public acute care hospital with 168 beds. In particular, from the list of public hospitals in Naples, two hospitals were selected amongst those for which administrative data were available and all admissions in surgical wards of the selected hospitals were examined. Patients who died during hospitalization and who had undergone emergency procedures were excluded. Before starting the investigation, a letter was delivered to the medical director of the hospitals to describe the purpose of the study to ensure the confidentiality of patients’ data and to obtain approval. Following the approval, all admissions to the surgical wards were examined using administrative data. In particular, from the hospital administrative data it was possible to collect the following information for all surgical patients: gender, age, marital status, educational level, ward of admission, length of hospital stay, date of admission and discharge, date of admission and discharge, number of readmission in hospital. Subsequently, only the medical records of each patient readmitted after the first admission for the surgery were requested from the hospital for examination. The readmissions to hospital for SSIs have been defined as readmission of patients who had had SSI within thirty days after surgery or within one year for those who had an implant of prosthesis. The SSIs were defined according to the criteria of the European Centers for Disease Control and Prevention21 or based on the reasons for the hospitalization reported in the medical records or an ICD-9 diagnosis code indicating SSI. The information collected from the medical records was reviewed and summarized on a standardized case report form by two investigators not directly involved in patient care. The following characteristics were collected: age, gender, weight, height, ward type, admission diagnosis, date and day of the week, length of hospital stay, smoking status, diabetes, systemic steroid use, poor nutritional status, chemotherapy/radiotherapy, transfusion of blood products, comorbidity Charlson index,22 surgical wound classification,23 type and length of the surgery (minutes), American Society of Anesthesiologists (ASA) Score, time interval between the date of surgical procedure and readmission, presence of SSI, antibiotic therapy for SSIs, microbiological culture test, surgery during the readmission and details of perioperative antibiotic prophylaxis. The antibiotic prophylaxis has been evaluated for each surgical procedure and was considered appropriate if the choice of antibiotic administration, when indicated, the timing, the doses and the length of administration were in according to the Italian national guidelines.24 The protocol of the study was approved by the Ethical Committee of the University of Campania ‘Luigi Vanvitelli’ of Naples. Statistical analysis The collected data were entered into a database in the form of numeric codes and a quality check of database was carried out before starting the statistical analysis. Statistical analyses were conducted in several stages. First, descriptive analyses were performed to describe and summarize the information available from administrative data for all surgical patients and then the characteristics of readmitted patients. Secondly, for the sample of readmitted patients, bivariate analysis was performed using chi-square test or Fischer exact test for all categorical variables and Student’s t-test for continuous variables. Following, a multivariate stepwise logistic regression analysis was performed to investigate the independent characteristics associated with the outcome of interest: profile of patients with a readmission for a SSI (readmission for other reasons = 0; readmission for SSI = 1). The significance levels for the exclusion and inclusion of variables in the model were 0.4 and 0.2, respectively. All inferential tests were performed through the execution of bilateral hypothesis test with statistical significance level of P values equal to or less than 0.05. The results of multivariate regression analyses were reported as odds ratios (ORs) and 95% confidence intervals (CIs). In the logistic regression model the following independent variables were included: age (continuous), sex (male = 0; female = 1), surgical ward of hospital stay (general = 0, specialties = 1), smoking status (no = 0, yes =1), immunosuppression status (no = 0, yes = 1), low serum albumin (no = 0, yes = 1), diabetes (no = 0, yes = 1), ASA score (ASA I = 0; ASA II, III and IV = 1), surgical wound classification (clean = 1, clean-contaminated = 2, contaminated = 3), length of hospital stay in days (continuous), length of surgery in minutes (continuous), endoscopic surgery (no = 0, yes = 1), the implant of prosthesis (no = 0, yes = 1), appropriateness of perioperative antibiotic prophylaxis (no = 0, yes = 1). The independent variables to include in the model were chosen based on the previous investigations in published literature and because they were considered as interesting predictors of the outcome. Statistical analyses were performed using Stata version 10.1 software.25 Results A total of 3815 surgical procedures performed in the year 2014 on patients ≥ 18 years of age admitted to the ordinary regime were included. More than half of the patients were female (60.2%), the average age was 53 years (range 18–107), more the half of patients were married (56.1%), 34.1% had at least a secondary school educational level, more than half of the procedures were performed in specialist surgery and the average length of hospital stay was 7 days (range 1–137). Table 1 shows the main characteristics of the patients who had had at least one readmission after the previous surgery and the main risk factors SSIs compared with those for patients who had had at least one readmission due to SSI. Overall, 145 patients had a readmission, 61.4% of them were female with an average age of 56 years (range 18–87) and 54.5% of the examined procedures were performed in general surgery wards. The average length of hospital stay for these patients was 9.6 days and the average time between the admission for surgical procedure and readmission was 15.6 days. Table 1 Main characteristics and risk factors of study population associated with the patients readmitted for SSI Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Surgical site infections (SSI). a Mean ± standard deviation (range). b Mean ± standard deviation (range) for readmitted patients without SSIs. Table 1 Main characteristics and risk factors of study population associated with the patients readmitted for SSI Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Readmitted patients n = 145 Readmitted patients with surgical site infection n = 41 n % n % Gender Male 56 38.6 18 43.9 Female 89 61.4 23 56.1 χ2 = 0.67; 1df; P = 0.412 Age (years) 55.9 ± 16.8(18–87)a 58.1 ± 18.8(18–87)a; 55 ± 15.9(18–87)b t = -1.04; 143df; P = 0.299 Ward of admission General Surgery 79 54.5 28 68.3 Surgical Specialties 66 45.5 13 31.7 χ2 = 4.39; 1df; P = 0.036 Smoking status Yes 49 33.8 16 39.1 No 96 66.2 25 60.9 χ2 = 0.9; 1df; P = 0.341 Diabetes Yes 33 22.8 15 36.6 No 112 77.2 26 63.4 χ2 = 6.21; 1df; P = 0.013 Immunosuppression status Yes 15 10.3 9 21.9 No 130 89.7 32 78.1 χ2 = 8.3; 1df; P = 0.004 Low serum albumin Si 32 22.1 16 39.1 No 113 77.9 25 60.9 χ2 = 9.55; 1df; P = 0.002 ASA score I 32 22.1 5 12.2 II 75 51.7 24 58.5 III 34 23.4 11 26.8 IV 4 2.8 1 2.5 χ2 = 3.24; 1df; P = 0.072 Surgical wound classification Clean 57 39.3 10 24.4 Clean-contaminated 67 46.2 17 41.5 Contaminated 21 14.5 14 34.1 χ2 = 18.77; 1df; P < 0.0001 Length of hospital stay, days 9.6 ± 9.9(1–56)a 13 ± 11.7(1–56)a; 8.3 ± 8.8(1–53)b t = -2.64; 145df; P = 0.009 Length of surgery, minutes 107.1 ± 96.3(10–420)a 136.9 ± 117.7(20–420)a; 87.8 ± 83.3(10–400)b t = -2.49; 126df; P = 0.014 Days in hospital before surgery 3.2 ± 5.2(0–34)a 5.5 ± 8.6(0–34)a; 3.2 ± 5.5(0–34)b χ2 = 3.47; 1df; P = 0.062 Appropriateness of perioperative antibiotic prophylaxis Yes 10 6.9 2 4.9 No 135 93.1 39 95.1 χ2 = 0.36; 1df; P = 0.547 Classification of SSIs Superficial incisional SSI – – 11 26.8 Deep incisional SSI – – 20 48.8 Organ/space SSI – – 10 24.4 Antibiotic use for SSI Yes – – 15 36.6 No – – 26 63.4 Surgical site infections (SSI). a Mean ± standard deviation (range). b Mean ± standard deviation (range) for readmitted patients without SSIs. With regard to the risk factors for SSIs, 33.8% of readmitted patients were smokers, 22.8% had diabetes, 10.3% had immunosuppression status and one in five had a poor nutritional status with a low serum albumin (22.1%). During the first admission for surgery, 39.3% of patients had undergone a surgical procedure classified as clean, 51.7% as clean-contaminated and only 14.5% had undergone a surgical procedure classified as contaminated. Moreover, 26.2% of patients had received an endoscopic approach, more than half (57.9%) had undergone surgery under general anaesthesia and in 75.2% of the examined procedures were administered antibiotics as surgical prophylaxis. Perioperative antibiotic prophylaxis was appropriate only for the 9.2% of procedures where the antibiotics were indicated, and considering all surgical procedures, only the 6.9% of the perioperative antibiotic prophylaxis was appropriate. In total, 1.1% (41 patients) of the sample had a readmission for SSIs and these representing the 28.3% of all readmitted patients. Other main reasons for hospital readmission were in order planned readmissions for surgical procedures (22.1%), progression/reoccurrence of diseases (15.2%), admission for diagnostic and therapeutic procedures (11.4%) and non-infectious surgical complications (7.6%). As shown in the bivariate analyses in table 1, a significantly higher frequency of patients who had a readmission for SSIs was observed amongst patients admitted to the general surgery ward (χ2=4.39; P = 0.036), amongst those with diabetes (χ2=6.21; P = 0.013), in patients with low serum albumin (χ2=9.55; P = 0.002), amongst those who had undergone a surgical procedures classified as contaminated (χ2=18.77; P < 0.001) and in those who had had a greater length of surgery (t=-2.49; P =0.014). The results of the multivariate regression were substantially similar to the bivariate associations and revealed that the readmissions for SSIs were significantly more likely in smokers (OR = 3.14; 95% CI = 1.13–8.69), in patients with immunosuppression status (OR = 8.28; 95% CI = 1.76–38.87), in patients with low serum albumin (OR = 3.07; 95% CI = 1.05–9.01) and in patients who had undergone surgical procedures classified as contaminated (OR = 10.44; 95% CI = 3.11–35.01) compared with those that had undergone a surgical procedure classified as clean (table 2). Table 2 Multivariate logistic regression model for potential predictors of the readmission for SSIs Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 a Reference category. Table 2 Multivariate logistic regression model for potential predictors of the readmission for SSIs Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 Variable OR SE 95% CI p-Value Profile of patients with readmission for SSIs (sample size = 145) Log likelihood = -55.31, χ2 = 43.30 (128df), P < 0.0001 Surgical wound classification     Clean 1a – – –     Contaminated 10.44 6.44 3.11–35.01 <0.0001 Immunosuppression status 8.28 6.53 1.76–38.87 0.007 Smoking status 3.14 1.63 1.13–8.69 0.028 Low serum albumin 3.07 1.69 1.05–9–01 0.041 ASA score 0.33 0.23 0.08–1.32 0.116 Length of surgery 1.01 0.01 0.99–1.01 0.142 Diabetes 2.16 1.26 0.69–6.77 0.184 a Reference category. The types of SSIs that occurred were for 26.8% of cases superficial SSI, for 48.8% of cases deep SSIs and in 24.4% of cases involving organs or spaces. A microbiological culture test was performed only for 16 patients with SSIs (39%) and the more frequently isolated microorganisms were Staphiloccoccus aureus (seven cases) and Candida albicans (two cases). Considering all surgical procedures only 4.9% of perioperative antibiotic prophylaxis amongst readmitted patients for SSIs was appropriate. 88.2% of SSIs were treated with antibiotics. Discussion To the best of our knowledge, this is the first investigation conducted in Italy that has evaluated readmissions for SSIs of patients undergoing surgery in both general surgeries wards that specialty surgery and represent the first survey that has assessed which factors could be associated predictors to readmissions. As well as reported by other investigation, the results of this study show that SSIs are the most common reasons for readmission in surgical patients, given that 28.3% of patients readmitted after the first admission for surgery were readmitted to hospital due to SSIs. This is an interesting result because the readmission rates are increasingly seen as a gauge of the quality of care provided by the hospital. Indeed, since the readmissions for SSIs are potentially avoidable readmissions, understanding their impact on hospital care is useful for the hospital management to implement programs to decrease the number of these readmissions, reduce healthcare expenditures and improve quality of care and patients safety. Previous experience published on this topic in Italy had well-documented the prevalence of hospital readmissions and it is interesting to mark that in this study the potentially avoidable readmissions were significantly more likely amongst patients admitted in general surgery wards.26 Several studies worldwide have evaluated the readmission for SSIs for specific surgical procedures, but there is a dearth of literature that evaluated the frequency of readmission for the totality of surgical procedures performed in surgical wards after the first admission. Therefore, it is very difficult to compare to previous studies due to different objectives, sample and methodology. The readmission rate for SSIs in our sample is similar to values found in two studies conducted in the US amongst neurosurgery patients where SSIs were the most common reasons for readmissions.18,19 Moreover, SSIs was the cause of 22.1% of readmissions in a study conducted amongst general surgery patients.27 In other studies, the rates of readmission for SSIs were lower than those observed in our study. In particular, in a study conducted in Texas, amongst patients readmitted 8.6% had a SSI20 and SSI was the cause of 17.7% of readmissions in a study who evaluated the hospital readmission after total hip arthroplasty.28 Finally, in a retrospective cohort study that evaluated the readmission of orthopaedic surgical patients, 38% of the surgical readmissions were due to SSIs.29 An interesting finding of our study was that only 6.9% of perioperative antibiotics prophylaxis performed during the first admission for surgery was appropriate amongst those readmitted with SSIs, although at multivariate analysis the appropriateness of perioperative antibiotic prophylaxis was not associated with readmission for SSIs. A low value of appropriate antibiotics prophylaxis was found also in recent studies published in Italy regarding the appropriate use of surgical antibiotic prophylaxis.30–32 However, performing an appropriate antibiotic prophylaxis is essential not only to reduce the incidence of SSIs but above all to reduce the risk of anti-microbial resistance and other serious complications for patients. Moreover, this study results may have important implications for the development of quality-improvement programs within the hospital for the purpose of developing appropriate practices regarding the administration of antibiotics. Moreover, during the considered period, a clinical culture was carried out only for 39% of patients with a SSI. This result must raise awareness of healthcare workers of the need to demand timely cultural examinations in order to provide the etiologic diagnosis of the infectious disease. Indeed, the main purpose of the cultural examination is to recommend an appropriate antibiotic treatment and to identify adequate prevention strategies. The results of bivariate and multivariate logistic regression analysis also showed that several risk factors for SSIs are significant determinants for readmissions. For example, contaminated surgical wound, immunosuppression status, low serum albumin and diabetes were strongly associated factors. These results indicate that, whenever possible, greater efforts should be made during hospitalization and post-discharge surveillance to prevent and correct all those clinical conditions that represent risk factors for infections before they require readmission to the hospital. Then, although not all SSIs are avoidable, understanding which clinical characteristics have patients is important to determine how to prevent complications related also to surgery and thus these measures may result in reducing hospital readmissions and decrease consequently healthcare costs. This study has some limitations that must be considered for proper interpretation of the results. The first limit is that this is a retrospective investigation that, unlike the prospective longitudinal study, does not represent the ideal study for the evaluation of the frequency of SSIs and then of readmissions for SSIs. Secondly, the readmissions of patients have been evaluated only in two hospitals and thus the rate of readmissions may be underestimated because some patients could have been readmitted to other hospitals. The third limitation is that the readmission rate for SSIs may also be underestimated due to the lack of information in the medical records that did not allow us to clarify for all patients the reason for hospital readmission. Despite these limits, this investigation has a large sample size, the retrospective data were collected carefully for a one-year period and therefore we are confident that the results of this study are valid. In conclusion, the results point to the need for the hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in healthcare spending given that almost one third of readmissions to the hospitals in our study were due to SSIs. Acknowledgements The authors gratefully acknowledge the staff of the hospitals without whom this study would not have been possible. Members of the Collaborative Working Group are: Maurizio di Mauro (University Hospital University of Campania ‘Luigi Vanvitelli’, Naples) and Vito Rago (Hospital San Giovanni Bosco, Naples). Funding This study was supported by the Department of Experimental Medicine, University of Campania ‘Luigi Vanvitelli’. Conflicts of interest: None declared. Key points This is the first investigation conducted in Italy that evaluates readmissions for SSIs of patients undergoing surgery and represents the first survey that has assessed which factors could be associated predictors to readmissions. The results of this study show that the 28.3% of patients readmitted within 365 days from the first admission for surgery were readmitted to hospital due to SSIs. The results point to the need that hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in healthcare spending given that almost one third of readmissions to the hospitals in our study were due to SSIs. References 1 European Centre for Disease Prevention and Control . Annual Epidemiological Report 2016 – Surgical site infections. Stockholm: ECDC; 2016. Available at: http://ecdc.europa.eu/en/healthtopics/healthcare-associated_infections/surgical-siteinfections/pages/annual-epidemiological-report-for-2014.aspx (20 June 2017, date last accessed). 2 European Centre for Disease Prevention and Control . Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals. Stockholm: ECDC; 2013. Available at: http://ecdc.europa.eu/en/publications/Publications/healthcare-associated-infections-antimicrobial-use-PPS.pdf (20 June 2017, date last accessed). 3 Marchi M , Pan A , Gagliotti C , et al. 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Google Scholar CrossRef Search ADS PubMed © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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The European Journal of Public HealthOxford University Press

Published: Nov 30, 2017

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