|Year : 2020 | Volume
| Issue : 3 | Page : 362-370
The impact of antimicrobial stewardship programme on regulating the policy adherence and antimicrobial usage in selected intensive care units in a tertiary care center - A prospective interventional study
Sushmita Sana Chowdhury1, Apurba Sankar Sastry2, Sathasivam Sureshkumar3, Anusha Cherian4, Sujatha Sistla2, Deepashree Rajashekar2
1 Department of Microbiology, JIPMER, Dhanvantari Nagar; Department of Microbiology, JIPMER, Karaikal, Puducherry, India
2 Department of Microbiology, JIPMER, Dhanvantari Nagar, Puducherry, India
3 Department of Surgery, JIPMER, Dhanvantari Nagar, Puducherry, India
4 Department of Anaesthesiology, JIPMER, Dhanvantari Nagar, Puducherry, India
|Date of Submission||19-Jul-2020|
|Date of Decision||15-Aug-2020|
|Date of Acceptance||31-Aug-2020|
|Date of Web Publication||4-Nov-2020|
Dr. Apurba Sankar Sastry
Department of Microbiology, JIPMER, Dhanvantari Nagar - 605 006, Puducherry
Source of Support: None, Conflict of Interest: None
Purpose: Antimicrobial resistance (AMR) presents a significant threat to human health. The root cause for this global problem is irrational antimicrobial usage. Antimicrobial stewardship (AMS) emphasises on the appropriate use of antibiotics and ensures strict implementation of antimicrobial policy guidelines. This study was conducted to evaluate the impact of auditing of AMS programme on regulating the antimicrobial policy adherence and antimicrobial usage in hospital intensive care units. Materials and Methods: This was a prospective interventional study. It consisted of pre-implementation and implementation phases 6 months each. Two hundred and eighty patients were enrolled. Details of antibiotic consumption, surgical prophylaxis, culture/sensitivity patterns, de-escalation rates, etc., were collected in both phases. The implementation phase, in addition, included stewardship audit rounds. Results: In pre-implementation phase and implementation phases: policy adherence rates were 23.7% and 41.8%, respectively, de-escalation rates were 22.73% and 43.48%, respectively. Cultures were sent before the initiation of antimicrobials in 36.73% cases during the pre-implementation phase, which improved to 60.41% during the implementation phase. Defined daily dose (DDD) for the antibiotics was 98.66 DDD 100BD during the pre-implementation phase, which reduced to 91.62 DDD 100BD in the implementation phase. Total days of therapy (DOT) in the pre-implementation phase were 561 DOT1000BD, which reduced to 463 DOT1000BD during the implementation phase. Conclusions: Implementation of continuous monitoring of the AMS programme, therefore, has a definite role in reducing the antimicrobial consumption and improving the compliance to the policy guidelines. A more robust study for a prolonged period is, however, necessary to have a better analysis of the outcome.
Keywords: Antimicrobial stewardship programme, days of therapy, de-escalation, defined daily dose, surgical antimicrobial prophylaxis
|How to cite this article:|
Chowdhury SS, Sastry AS, Sureshkumar S, Cherian A, Sistla S, Rajashekar D. The impact of antimicrobial stewardship programme on regulating the policy adherence and antimicrobial usage in selected intensive care units in a tertiary care center - A prospective interventional study. Indian J Med Microbiol 2020;38:362-70
|How to cite this URL:|
Chowdhury SS, Sastry AS, Sureshkumar S, Cherian A, Sistla S, Rajashekar D. The impact of antimicrobial stewardship programme on regulating the policy adherence and antimicrobial usage in selected intensive care units in a tertiary care center - A prospective interventional study. Indian J Med Microbiol [serial online] 2020 [cited 2020 Nov 24];38:362-70. Available from: https://www.ijmm.org/text.asp?2020/38/3/362/299834
| ~ Introduction|| |
The emergence of multidrug-resistant microorganisms is an alarming global health-care problem. Antimicrobial resistance (AMR) presents a significant threat to human health. The root cause for this global problem is irrational antimicrobial usage. Infection with resistant organisms prolongs hospital stay and increases patient mortality, morbidity and cost of healthcare.,,, Despite concerns about the irrational use of antibiotics, very little change has been noted in the prescription patterns over the last decade or so. Therefore, a good stewardship programme is essential for monitoring the use of antibiotics and checking the emergence and transmission of resistant organisms.,
Antimicrobial stewardship (AMS) emphasises on appropriate consumption of antibiotics by ensuring the selection of appropriate regimen, route, time and duration for the use of antibiotics. AMS also ensures strict implementation of antimicrobial policy guidelines along with time to time monitoring of the adherence to these guidelines.,,,
Over the last two decades, only a handful of new antimicrobials have been introduced into the market. Antimicrobials presently in the pipeline also belong to the already existing classes of drugs, and all have broad-spectrum activity. These newer drugs are expected to further worsen the problem of AMR rather than ameliorating it. In such a scenario, the introduction of an effective AMS programme in all hospitals is, therefore, very essential. The study was conducted in the surgery intensive care unit (SICU) and critical care unit (CCU) of a tertiary care hospital to evaluate the impact of auditing of AMS programme (AMSP) on regulating the policy adherence and antimicrobial usage. Restriction of irrational antimicrobial usage can prevent the emergence of AMR and further reduce the financial burden of our hospital.
| ~ Materials and Methods|| |
This study was a prospective interventional study.
Patients admitted in SICU and CCU in our hospital from January 2017 to December 2017.
Assuming alpha as 0.05, power as 0.80, baseline adherence as 21.8%, expected increase in adherence of at least 30% and 20% wastage, the sample size was calculated to be 120. However, we have included the antimicrobial prescription cards from all consecutive patients admitted in SICU and CCU during the study period (both pre-implementation and implementation phases), thereby, reaching a sample size of total 280. Patients shifted in the intensive care units (ICUs) for mere post-operative observation (usually for <12 h) were, however, not included.
The study period was 12 months.
The study protocol was approved by Institutional Ethics Committee (IEC), and it abides by the tenets of the declaration of Helsinki. We had obtained waiver of consent certificate from our institute ethics committee (JIP/IEC/2016/1032).
Study period was divided into the pre-implementation phase (January to June 2017) and implementation (July to December 2017) phase, 6 months each. Pre-implementation phase included only observation and documentation of various parameters in the ICUs. The implementation phase included audit rounds by the AMSP team in the ICUs, discussion with ICU personnel, and documentation of the parameters.
Common work done in both phases included:
- Documentation of antimicrobial prescription practice patterns in SICU and CCU
- Documentation of whether surgical antimicrobial prophylaxis (SAP) was given for patients undergoing surgery and comparison with the National Treatment guidelines for antimicrobial use in infectious diseases
- Calculation of antimicrobial monthly usage
- Documentation of details of culture specimens sent
- Documentation of whether blood culture was sent before starting antibiotics
- Documentation of AMR patterns of the isolates from both the ICUs from records in the department of microbiology
- Documentation of whether de-escalation of antibiotic was done based on the antimicrobial susceptibility testing (AST) report.
During both the phases, automated identification and sensitivity testing were carried out by using Phoenix AST Panel (Becton Dickinson BD Phoenix 100) so that the report could be generated early and the turnaround time could be reduced considerably.
Additional intervention done during the implementation phase included AMS audit rounds in both the ICUs. For SICU audit rounds, the external team comprised hospital infection control officer (microbiologist) and Anaesthesiologist. The surgeon from SICU was the internal member. In CCU audit rounds, the external expert team comprised Infection control officer and Surgeon while Anaesthesiologist in charge of CCU was the internal member. The external team in each ICU verified the antimicrobial prescription cards in detail and noted the various parameters such as de-escalation done on time or not, antimicrobials prescribed according to guidelines or not, whether the culture was sent before administration of antimicrobials or not. To improve the prevailing practice patterns in the ICUs noted during pre-implementation phase, the audit team deliberated with the ICU personnel and re-emphasised on the need for:
- Starting surgical prophylaxis whenever indicated
- Sending blood culture before starting antibiotics
- De-escalation of antibiotics based on the AST report.
Parameters collected during both the phases were finally compared and analysed to determine the impact of the stewardship audit rounds.
The outcome parameters studied were divided into primary and secondary.
Primary outcome assessment
Policy adherence outcome indicators - SAP adherence rate, de-escalation adherence rate and percentage of culture sent before administration of antimicrobials.
- SAP adherence rate = number of times antimicrobials prescribed according to policy/total number of antimicrobial prescriptions given in the same period ×100
- De-escalation adherence rate = number of times de-escalation done after the culture sensitivity report/number of possible de-escalations indicated in the same period ×100
- Percentage of culture sent before administration of antimicrobials = number of times blood culture sent before the administration of antimicrobials/total number of blood culture sent in the same period ×100.
Secondary outcome assessment
Antimicrobial usage outcome indicators
This was calculated based on defined daily dose (DDD) and days of therapy (DOT).
- Number of DDD - It is the average maintenance dose per day for a drug used for its main indication in adults. This is the best indicator to calculate antimicrobial consumption. The WHO assigned DDDs were used for calculating the DDDs as shown in [Table 1].
Number of DDDs = therapeutic dose (number of tablets used × g per tablet)/WHO defined DDD of the antimicrobial
DDDs per 100 patient bed days = number of DDDs used in an ICU in a period/total patient days of the ICU in the same period (sum of occupied beds daily) ×100
- Days of therapy (DOT per 1000 patient bed days)-Data on DOT were collected by verifying the dose of administration of antimicrobials on the patient's case sheet. Then, the DOT per 1000 patient days was calculated as follows.
DOT per 1000 patient bed days = Total DOT of an antimicrobial in an ICU in a period/total patient days of the ICU in the same period (sum of occupied beds daily) × 1000.
Antimicrobial resistance outcome indicator
AMR surveillance - This data were taken from the records of department of microbiology.
Record-based financial measures indicators
Antibiotic cost per admission - Antibiotics used in the ICU in a given period × cost of the antibiotics/number of admissions in the same ICU during the period × 100.
| ~ Results|| |
During the study period of 12 months, a total of 280 cases were enrolled. 140 cases were included in the pre-implementation phase (95 males and 45 females) and 140 cases in the implementation phase (108 males and 32 females). Mean age for all the patients enrolled in the study was 47.61 ± 14.54 years with a range of 17–82 years.
In the pre-implementation phase, a total of 251 samples were sent from 91 patients -40 of these patients had undergone surgery. In the implementation phase, a total of 243 samples were sent from 97 patients -35 of these patients had undergone surgery. Samples sent during the entire study period included blood (37.2%), pus (9.1%), tissue bits (8.3%), wound swab (8.5%), tracheal aspirate (8.5%) and others such as bile, sputum, cerebrospinal fluid, bleb fluid, peritoneal fluid, pleural fluid and stool. Positive culture was found in 49% of samples (123/251) in the pre-implementation phase and 39% (100/243 samples) in the implementation phase. Commonly isolated organisms from the specimens sent in the pre-implementation phase were Escherichia coli (32.2%), Acinetobacter baumannii (18.1%), Pseudomonas aeruginosa (12.9%), etc., and in the implementation phase were E. coli (29.8%), A. baumannii (17.6%), P. aeruginosa (7.6%), etc.
Most commonly used antibiotics reported in the study were metronidazole (pre-implementation 32.7% of cases, implementation 34.0% of cases), ceftriaxone (27.4% of cases in pre-implementation, 24.7% cases in implementation), cefoperazone/sulbactam (10.4% cases in pre-implementation, 12.2% of cases in implementation phase) piperacillin-tazobactam (7.2% of cases in pre-implementation, 8.3% of cases implementation). Organisms isolated from the specimens sent and antibiotics most commonly used in the study period are shown in [Table 2].
|Table 2: Organisms isolated from the specimens sent and antibiotics used in the study period|
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Policy adherence outcome indicators calculated during both the phases were as below:
Surgical antimicrobial prophylaxis adherence rate
In the pre-implementation phase, 59 cases admitted in both the ICUs underwent surgery and had SAP documentation, of which only 14 were in accordance with SAP guidelines (policy adherence rate = 23.7%). During the implementation phase, SAP was documented in 55 cases admitted in both the ICUs who underwent surgery, of which 23 cases followed the SAP guidelines (policy adherence rate = 41.8%). The difference was statistically significant (P value = 0.013). [Figure 1] and [Table 3] depict details of SAP followed during the study period.
|Figure 1: Surgical antimicrobial policy adherence during both the phases|
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|Table 3: Surgical antimicrobial prophylaxis and blood sample collection details|
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De-escalation adherence rate
Total indications for de-escalation in the pre-implementation and implementation phases were 65 and 45 cases, respectively. De-escalation following culture reports was done in 15/65 (22.73%) and 21/45 (43.48%) cases during their ICU stay in pre-implementation and implementation phases, respectively. The difference was statistically significant, with a P value of 0.044.
Month-wise de-escalation rates during both phases are depicted in [Figure 2].
|Figure 2: Month-wise de-escalation adherence rates during both the phases|
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Blood sample sent before starting of antibiotics
The total number of blood samples sent for culture during the 12 months period of our study was 184. During the pre-implementation phase, a total of 104 blood samples were sent from 49 patients. Out of 49 patients, only in 18 (36.73%) patients, blood culture was sent before starting antibiotics. In the implementation phase, a total of 80 blood samples were sent from 48 patients. Out of 48 patients, blood culture was sent before starting antibiotics in 29 (60.41%) patients [Figure 3] and [Table 3]. The difference was statistically significant, with a P = 0.034.
|Figure 3: Blood culture sent prior to and after starting antimicrobials in both the phases|
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Defined daily dose
Total DDD per 100 patient bed days for all the antimicrobials was 98.66 DDD 100BD during the pre-implementation phase and 91.62 DDD 100BD in the implementation phase. The difference was, however, statistically not significant (P = 0.749). Month-wise DDD100BD during both phases are depicted in [Figure 4].
|Figure 4: Month-wise defined daily dose per 100 patient bed days during both the phases|
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Days of therapy
Total DOT per 1000 patient bed days for all the antimicrobials used during the pre-implementation phase was 561 DOT1000BD and 463 DOT1000BD during the implementation phase. The difference was not statistically (P = 0.337). Month-wise DOT per 1000-bed days during both the phases are shown in [Figure 5].
|Figure 5: Month-wise days of therapy 1000 patient bed days during both the phases|
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Cost of antibiotics
Antibiotic cost per ICU admission was calculated for both the pre-implementation and implementation phase, as shown in [Figure 6]. The antibiotic cost per ICU admission in the pre-implementation phase was Rs. 404.05 and in the implementation phase was Rs. 375.61, P = 0.631. Although the difference was not statistically significant, we could observe a reduction in the average monthly antibiotic cost.
|Figure 6: Antibiotic consumption per intensive care unit admission during the 12 months study period|
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Antimicrobial resistance surveillance
AMR patterns were calculated for the most common organisms- E. coli, Klebsiella pneumoniae, A. baumannii and P. aeruginosa isolated from blood, tissue bits, pus and wound swabs, etc., Other organisms were excluded as the number of isolates was less in number. The resistance pattern for each organism is shown in [Table 4]. Since the study period is short, therefore, AMR change seen in both the phases cannot be commented upon.
|Table 4: Antimicrobial resistance pattern for organism in both the phases|
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| ~ Discussion|| |
AMR is a significant health-care problem in terms of morbidity, mortality and associated economic repercussions. AMR is a serious concern in India as well. Although guidelines for control of infections do exist in many health-care facilities, however, expertise and infrastructure for implementation of the guidelines are still lacking in most of these facilities. To tackle these issues, Indian Council of Medical Research and National Centre for Disease Control have initiated various programmes like Antibiotic Stewardship, Prevention of Infection and Control, AMR Surveillance Research Network, National Programme on the Containment of AMR, etc., Surgical site infection (SSI) is an important factor causing AMR emergence through irrational and/or prolonged antimicrobial use, contributing to around 10%–30% of overall nosocomial infections. One study in India has shown SSI rate of ~2% for minor surgeries and ~ 16% in major surgeries. SSI rate reported from a prior study in our hospital was 3.5%. SSI leads to delay in wound healing, increased patient morbidity, prolonged stay in the hospital, increased antimicrobial consumption, and, therefore, increased risk of AMR, and higher hospital expenditures. Strict compliance with SAP guidelines is, therefore, very essential to prevent SSI.
In this study, we monitored antimicrobial usage along with adherence to the guidelines for 12 months. Our study included patients from SICU and CCU. One hundred and fourteen patients (40.7%) out of a total of 280 cases during the entire study period had undergone surgery - 59 patients in the pre-implementation phase and 55 patients in the implementation phase underwent surgery. Hence, monitoring adherence to SAP and the effect of AMSP on the adherence rate was an important component of our study. Apart from this, various outcome and process measures were also monitored and analysed in our study, which are discussed below.
Policy adherence outcome indicators
Surgical antimicrobial prophylaxis adherence rate
In this study, we analysed adherence to surgical antimicrobial prophylactic guidelines among patients who had undergone surgery and were admitted to CCU or SICU. Compliance to antibiotic policy in our study was 23.7% (14/59 cases) in the pre-implementation phase and 41.8% (23/55 cases) in the implementation phase. Although there is a statistically significant improvement (P = 0.013) in the adherence rate to SAP guidelines during the implementation phase, we should target for a further increase in the adherence rate. One possible reason for low rates of adherence to antimicrobial policy can be non-uniformity in protocols followed at the time of admission between emergency services, outpatient department (OPD) services and ICUs. We, therefore, recommend to follow uniform SAP guidelines across all services in the hospital.
In concordance to our study, Schmitt et al., in their study, monitored the compliance rate with SAP in neurosurgery services across institutions. Compliance rate was, however, found to be as low as10%.
De-escalation adherence rate
De–escalation rate in our study was 23.08% (15/65 cases) during the pre-implementation phase and 46.67% (21/45 cases) during the implementation phase. The difference was significant statistically (P = 0.044). De-escalation rate in our study is comparable to and in fact, better than similar studies discussed below. However, we can still aim for higher de-escalation rates through constant auditing and feedback to the concerned physicians through future AMS activities. In a study by Madaras-Kelly et al., the de-escalation rate in 9319, patients with health-care-associated pneumonia was found to be 28.3%. Variables associated with de-escalation were initial therapy with broad-spectrum antimicrobials, respiratory tract cultures and care in higher complexity facilities. In the study by Shah et al., antibiotic escalation was done in 12.67% (19 prescriptions), and de-escalation was done in only 2.67% (4 prescriptions) out of a total 150 prescriptions. In a similar study by Malacarne et al., antimicrobial regimen escalation was done in 37.6% of cases, while de-escalation was done in 24% of cases in ICU.
Percentage of culture sent before administration of antimicrobials
Following the admission of the patient, antimicrobial prescribing decisions should be reviewed within 48 h. This may help to decrease overall antimicrobial consumption by eliminating unnecessary antibiotics from the treatment regime, particularly broad-spectrum antibiotics. Blood culture reports may aid in making the decision on continuing, altering, or stopping parenteral antibiotics after 48 h. In our study, percentage of blood culture sent before initiation of any antibiotics following the admission of the patient in the ICUs was relatively low. Blood culture was sent in only 36.73% (18/49) cases in the pre-implementation phase. This, although improved to 60.41% (29/48 cases) (P = 0.034) during the implementation phase, there is still further scope for improvement. Continuous emphasis on the importance of sending blood culture before starting antimicrobial course and regular audit with feedback to the ICU residents/physicians by the stewardship team may be helpful in this regard. Referrals to tertiary hospitals from the peripheral centres often occur only after antibiotics have already been started. In such a scenario, blood culture sensitivity reports may not be very relevant for the physician in the tertiary hospital. This could be a possible reason for not sending pre-antibiotic course culture sensitivity test in the referral centre. In a study by Madaras-Kelly et al. blood cultures were sent on admission in 82.1% cases. In a study by Shallcross et al., 6% of patients attending the emergency services and up to 20% of the admitted patients were prescribed a parenteral antibiotic. However, blood cultures were obtained in only less than one-third of these patients who were treated with a parenteral antibiotic.
Antimicrobial usage outcome indicators
Defined daily dose and days of therapy
In our study, DDD was 98.66 DDD 100 BD in the pre-implementation phase and 91.62 DDD 100 BD in the implementation phase. DOT in the pre-implementation phase was 561 DOT 1000 BD and 463 DOT 1000 BD in the implementation phase. Although the differences were not statistically significant (P = 0.749 for DDD and 0.337 for DOT), we could notice a decreasing trend during the implementation phase. The reasons for insignificant statistical results can be explained as follows. Non-uniform protocol or guidelines are followed in each ICU (SICU and CCU in this study in our hospital). This was found to be an important drawback in our study. The protocols may vary in terms of choice of antibiotics, dose, frequency of dosing, duration of therapy, indications for de-escalation or cessation of therapy, etc., Compiling data from two different ICUs, analyzing and comparing them in terms of drug consumption and duration of therapy may, therefore, be not an ideal option in such a scenario. We should, therefore, advocate for uniform guidelines across all ICUs, wards, OPD, and emergency services. A similar trend in reduction in DDD has been seen in the following studies discussed below.
A study by Thursky et al. on implementation of AMSP through a computerised decision support tool on antibiotic use in an ICU setting has shown a 10.5% reduction in total antibiotic consumption (166–149 DDDs/100 ICU bed days). Meyer et al., in their study evaluated the impact of the implementation of revised guidelines for the use of antibiotics in nosocomial pneumonia in a neurosurgical ICU. Duration of antibiotic therapy for nosocomial pneumonia reduced from 14 to 7 days and for community-acquired pneumonia from 10 to 5 days. This was also associated with decrease in total antibiotic consumption from 949.8 to 626.7 DDD/1000 patient days. Further subgroup analysis revealed reduced consumption of cephalosporins (−100.6 DDD/1000 pd), imidazoles (−100.3 DDD/1000 pd), carbapenems (−33.3 DDD/1000 pd), etc., It was also accompanied by a significant decrease in antibiotic costs after the intervention.
Financial outcome measures
Antibiotic cost per admission
Antibiotic costs per ICU admission in the pre-implementation phase of our study was Rs. 404.05 while in the implementation phase, it was Rs. 375.61. Although we could observe a declining trend in in antibiotic costs during the implementation phase, the difference in cost per ICU admission between the two phases was, however, statistically not significant (P = 0.631). This declining trend of expenditures on antibiotics during the 6 months of implementation phase was consistent with similar trend seen in drug consumption in terms of DDD and DOT. Similar trend of hospital cost savings was noted following implementation of various stewardship strategies in studies as discussed below.
Studies using formulary restrictions have shown to result in annual hospital savings in the range of around 8 lakh dollars. In another study, implementing use of education and order forms resulted in cost savings of around 9.1 lakh dollars. In a study by So et al., expenditure on antibiotic consumption reduced following AMSP implementation from $154.60 per patient day to $128.90 per patient day (P = 0.03). In a study by Nowak et al., expenses on antibiotics increased at a rate of 14.4% yearly prior to AMSP implementation. However, following the intervention of AMSP, expenses on antibiotics reduced at a rate of 9.7% yearly. This resulted in total hospital savings of around 1.6 million dollars.
However, in our study, we did not take into account the bias of the severity of the cases admitted in the ICUs and infections encountered while comparing between the two phases. Antibiotic cost per ICU admission may have been impacted by this as well.
Antimicrobial resistance surveillance
In this study, commonly isolated organisms were E. coli, K. pneumoniae, P. aeruginosa and A. baumannii. Resistance to the 3rd generation cephalosporins and carbapenems in E. coli isolates was noted to be 84% and 22%, respectively, in the pre-implementation phase, and 88% and 5%, respectively, in the implementation phase. K. pneumoniae in the pre-implementation was resistant to the 3rd generation cephalosporins in 77% of cases and carbapenems in 33% of cases, and 50% and 25%, respectively, in the implementation phase. Among the A. baumannii isolates, 66% and 50% were resistant to the 3rd generation cephalosporins and carbapenems, respectively, in the first 6 months and 100% and 33% in the next 6 months, respectively. The next common isolate P. aeruginosa showed the following resistance pattern -50% were resistant to 3rd generation cephalosporins and 38% were resistant to carbapenems in the pre-implementation phase and 25% and 13%, respectively, in the implementation phase. Due to the short study duration, it is difficult to comment on the resistance and susceptibility profile. However, we noted a high rate of resistance in all the isolates against 3rd generation cephalosporins in both the phases. Hence, we can plan future studies with implementing restrictive formula for 3rd generation cephalosporin use. In the study by Banerjee et al., MRSA was isolated from 36.3% nasal samples from ICU patients and VRE from 55.5% of the stool sample. In the study by Ramsamy et al., 19% of E. coli were positive for extended-spectrum β-lactamases (ESBL) and 62% ESBL negative. 25% of K. pneumoniae isolates were positive for ESBL, while 50% were negative.
| ~ Conclusions|| |
The present work is the first study conducted in our hospital, aiming to find out the impact of auditing of AMS programme on policy adherence and antimicrobial usage. We found that continuous monitoring of the AMS programme has a definite role in reducing antimicrobial consumption and improving compliance with the policy. Monitoring was done in terms of policy adherence-SAP, de-escalation rate, blood sample sent for culture and sensitivity before antibiotics treatment, and antimicrobial usage- DDD, DOT and financial outcome. There was a significant improvement in the parameters such as SAP, de-escalation rate, and blood culture request before antimicrobials in our study. However, the impact on antimicrobial usage and cost reduction was not significant because of the shorter duration of the study period. A more robust study for a prolonged period is, therefore, necessary to have a better analysis of the outcome of these parameters. Implementing policies in the ICU setting and subsequent auditing and feedback may help to improve trends of antibiotic consumption in ICUs alone. However, to improve overall hospital parameters, policies, and guidelines should be formulated and implemented in all settings of the hospital, including emergency services, general wards, pediatric wards, ICUs, etc., We can direct future studies with the goal of covering the entire hospital under the same antimicrobial policy. Such a policy will help to contain the emergence of AMR in a more effective manner as compared to restricting the policy to ICUs alone.
We would like to thank Dr. Amit Kumar Deb, Department of Ophthalmology, JIPMER, Puducherry-06.
Dr. Swapan Chowdhury, Department of Paediatrics, Melaka-Manipal Medical College, Malaysia. for specific scientific contribution
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2], [Table 3], [Table 4]