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Mauliņa I, Darbiniece K, Miķelsone-Jansone L, Erts R, Bandere D, Krūmiņa A. Experience of Vancomycin Therapeutic Drug Monitoring in Two Multidisciplinary Hospitals in Latvia. Medicina (Kaunas) 2022; 58. [PMID: 35334546 DOI: 10.3390/medicina58030370] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 02/10/2022] [Accepted: 02/25/2022] [Indexed: 01/23/2023]
Abstract
Background and Objectives: Management of infectious diseases is a huge burden to every healthcare system worldwide. Antimicrobial resistance, including antibacterial resistance, is an increasing problem worldwide; therefore, more new antibiotics are necessary to be discovered. Meanwhile, “old” antibacterial agents are still administered to fight infectious diseases caused by resistant bacteria. One of these antibacterial agents is vancomycin, which is effective in treating serious systemic infections caused by gram-positive bacteria. Thus, it is necessary to perform vancomycin concentration measurements in plasma due to its narrow therapeutic index. Various approaches are implemented for more precise therapy, including therapeutic drug monitoring (TDM) of vancomycin and with a supervision of a clinical pharmacist. The purpose of the study was to investigate if the TDM practice is improved with a local vancomycin TDM protocol applied in a hospital. The results of TDM in two multidisciplinary hospitals, one with a local TDM protocol implemented and applied and the other with no local TDM protocol implemented and applied, were compared. Materials and Methods: A retrospective study was performed in two multidisciplinary hospitals in Latvia. The data were collected for a time period of 4 years (2016−2020) in a hospital without a local TDM protocol and for a time period of 2 years (2018−2020) in a hospital with a local TDM protocol, starting with a period of time when the vancomycin TDM protocol was developed. The data about the patients included in the study were analyzed based on gender, age, body weight, and renal function. Vancomycin therapy was analyzed based on dosing schemes (vancomycin dose and dosing interval), data about loading and maintenance doses, vancomycin concentration, and details about vancomycin concentration (sampling time and concentration level). Results: Differences between the hospitals were found in terms of the initiation of vancomycin administration and concentration sampling. In the hospital with a TDM protocol compared with the hospital without a TDM protocol, more accurate initiation was found, alongside adaption of therapy (97.22% vs. 18.95%, p < 0.001), better performance of administration of a loading dose (22.73% vs. 1.29%, p < 0.01), and reaching of target concentration (55.56% vs. 35.29%, p < 0.01). Concentration sampling in the correct timeframe before the vancomycin dose and vancomycin administration did not show statistically better results in either of the hospitals (4.60% vs. 6.29%, p = 0.786). Conclusions: Better results of adequate adjustments of vancomycin therapy were achieved in the hospital with a TDM protocol. In the long term, sustainable results and regular medical professionals’ training is necessary.
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Gallegos PJ, Mistry B, Freshwater D, Mullen C. Continued professional development: A comparison of online vs. in-person workshops. Curr Pharm Teach Learn 2021; 13:770-775. [PMID: 34074505 DOI: 10.1016/j.cptl.2021.03.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 12/23/2020] [Accepted: 03/25/2021] [Indexed: 06/12/2023]
Abstract
INTRODUCTION Pharmacy practice continues to change and therefore requires lifelong health professions education. These practice changes require academics and leaders in pharmacy to identify how to best teach and train pharmacists to manage patient care services. This study assessed whether an online training module is as effective as an in-person workshop to train pharmacists to apply dosing and therapeutic monitoring of vancomycin. METHODS The primary endpoint measured the difference in average assessment score change between pre- and post-training between intervention groups. All pharmacists completed: (1) a baseline pretest, (2) Session 1 online, (3) Session 2 (an online training module or in-person workshop), (4) a posttest, and (5) a voluntary survey of perceptions on training. RESULTS A total of 56 pharmacists completed the training, 43% online and 57% in-person. The multiple linear regression included pretest, training method, and pharmacists' role on posttest (R2 = 0.1041 and P = .34). A voluntary anonymous survey about perceptions on the training was completed by 20 participants. On average, perceptions were agreeable on an eight-item Likert scale between groups (Cronbach's alpha = 0.77). The total scores for the Likert scale were 27 ± 3.3 vs. 23 ± 1.6, P = .001, in the online and in-person sessions, respectively. More participants in the online group agreed that they had enough time to comprehend and apply the material, 4 vs. 3 (on the Likert scale). CONCLUSIONS An online training module is as effective as an in-person workshop at training pharmacists to apply vancomycin dosing and monitoring.
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Affiliation(s)
- Patrick J Gallegos
- Department of Pharmacy, Cleveland Clinic Akron General, United States; Northeastern Ohio Medical University, United States.
| | - Bhavin Mistry
- Department of Pharmacy, Cleveland Clinic Akron General, United States; Northeastern Ohio Medical University, United States
| | - Dustin Freshwater
- Department of Pharmacy, Cleveland Clinic Akron General, United States
| | - Chanda Mullen
- Northeastern Ohio Medical University, United States; Department of Research, Cleveland Clinic Akron General, United States
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Nguyen-Thi HY, Nguyen DA, Huynh PT, Le NDT. Impact of Antimicrobial Stewardship Program on Vancomycin Usage: Costs and Outcomes at Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam. Risk Manag Healthc Policy 2021; 14:2637-2646. [PMID: 34188574 PMCID: PMC8235933 DOI: 10.2147/rmhp.s307744] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 05/27/2021] [Indexed: 11/30/2022] Open
Abstract
Background Nowadays, with the emergence of vancomycin-resistant strains, the clinical use of vancomycin has been followed closely by applying the antimicrobial stewardship program (ASP) to enhance effectiveness in treatment and reduce cost burden for patients. Methods A descriptive cross-sectional study at the Hospital for Tropical Diseases was conducted to assess the inpatient status assigned to intravenous vancomycin and factors associated with the cost of treatment during two periods of implementing ASP, which were i) from April 1, 2016 to March 31, 2018 (previous ASP-pASP) and ii) from June 1, 2018 to March 31, 2020 (new ASP-nASP). Results Among 1375 patients who met the sampling criteria, there were 601 and 774 patients in pASP and nASP, respectively. The rate of no improvement/mortality in the pASP was higher than that in nASP (37.10% vs 25.98%, p <0.05). The proportion of patients with two or more infection episodes in nASP is lower than that in pASP (9.83% vs 18.64%, p<0.05). Besides, nASP has higher length of therapy (LOT) and higher day of therapy (DOT). The average treatment cost in the pASP is higher than that in the nASP, 1891.22 (95% CI, 1713.46–2068.98) USD vs 1775.55 (95% CI, 1576.22–1974.88) USD. There are seven factors (p<0.05) that associate with the total cost of treatment (age, number of infection episodes, length of stay, discharge status, clinical department, LOT, DOT) in pASP. On the other hand, the nASP has five factors (p<0.001), in which the log(LOT) and age are not as statistically significant (p=0.5127 and 0.3852, respectively) as in the pASP model. Conclusion The implementation and improvement of the ASP at the Hospital for Tropical Diseases have initially shown benefits for patients using intravenous vancomycin. Specifically, the ASP helps to reduce treatment costs, improve patient outcomes, reduce length of stay and decrease the average daily dose of vancomycin.
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Affiliation(s)
- Hai-Yen Nguyen-Thi
- Department of Pharmaceutical Administration, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Duy-Anh Nguyen
- Department of Pharmaceutical Administration, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Phuong-Thao Huynh
- Department of Pharmacy, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Nguyen Dang Tu Le
- Department of Pharmaceutical Administration, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
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Stocker SL, Carland JE, Reuter SE, Stacy AE, Schaffer AL, Stefani M, Lau C, Kirubakaran R, Yang JJ, Shen CFJ, Roberts DM, Marriott DJE, Day RO, Brett J. Evaluation of a Pilot Vancomycin Precision Dosing Advisory Service on Target Exposure Attainment Using an Interrupted Time Series Analysis. Clin Pharmacol Ther 2020; 109:212-221. [PMID: 33190285 DOI: 10.1002/cpt.2113] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 11/10/2020] [Indexed: 12/30/2022]
Abstract
This study evaluated the ability of a pilot therapeutic drug monitoring (TDM) Advisory Service to facilitate vancomycin therapeutic target attainment within a real-world clinical setting. The Service provided area under the concentration-time curve (AUC)-guided vancomycin dose recommendations, using Bayesian forecasting software and clinical expertise, to prescribers at an Australian hospital. A retrospective audit of intravenous vancomycin therapy (> 48 hours) in adults (≥ 18 years old) was undertaken over a 54-month period to evaluate attainment of established vancomycin pharmacokinetic/pharmacodynamic targets (AUC over 24 hours / minimum inhibitory concentration: 400-600) before (36-month period) and after (18-month period) Service implementation. Interrupted time series analysis was employed to evaluate monthly measures of the median proportion of therapy spent within the target range. Indices of time to target attainment were also assessed before and after Service implementation. The final cohort comprised 1,142 courses of vancomycin (816 patients); 835 courses (596 patients) and 307 courses (220 patients) administered before and after Service implementation, respectively. Prior to piloting the Service, the median proportion of time in the target range was 40.1% (95% CI, 34.3-46.0%); this increased by 10.4% (95% CI, 1.2-19.6%, P = 0.03) after the Service, and was sustained throughout the post-Service evaluation period. Post-Service target attainment at 48-72 hours after initiation of therapy was increased (7.8%, 95% CI, 1.3-14.3%, P = 0.02). The findings of this study provide evidence that a consultative TDM Service can facilitate attainment of vancomycin therapeutic targets; however, optimization of the Service may further improve the use of vancomycin.
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Affiliation(s)
- Sophie L Stocker
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia.,Sydney Pharmacy School, Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Jane E Carland
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Stephanie E Reuter
- UniSA Clinical & Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Alexandra E Stacy
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,School of Medicine, The University of Notre Dame Australia, Sydney, New South Wales, Australia
| | - Andrea L Schaffer
- Centre for Big Data Research in Health, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Maurizio Stefani
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Cindy Lau
- Sydney Pharmacy School, Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.,Pharmacy Department, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Ranita Kirubakaran
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Jennifer J Yang
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Catriona F J Shen
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Darren M Roberts
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Deborah J E Marriott
- St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia.,Department of Clinical Microbiology & Infectious Diseases, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Richard O Day
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Jonathan Brett
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
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Carland JE, Elhage T, Baysari MT, Stocker SL, Marriott DJE, Taylor N, Day RO. Would they trust it? An exploration of psychosocial and environmental factors affecting prescriber acceptance of computerised dose-recommendation software. Br J Clin Pharmacol 2020; 87:1215-1233. [PMID: 32691902 DOI: 10.1111/bcp.14496] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 06/14/2020] [Accepted: 07/09/2020] [Indexed: 02/06/2023] Open
Abstract
AIMS Dose-prediction software can optimise vancomycin therapy, improving therapeutic drug monitoring processes and reducing drug toxicity. Success of software in hospitals may be dependent on prescriber uptake of software recommendations. This study aimed to identify the perceived psychosocial and environmental barriers and facilitators to prescriber acceptance of dose-prediction software. METHODS Semi-structured interviews, incorporating prescribing scenarios, were undertaken with 17 prescribers. Participants were asked to prescribe the next maintenance dose of vancomycin for a scenario(s) and then asked if they would accept a recommendation provided by a dose-prediction software. Interviews further explored opinions of dose-prediction software. Interview transcripts were analysed using an inductive approach to identify themes and the Theoretical Domains Framework was used to synthesise barriers and facilitators to software acceptance. RESULTS When presented with software recommendations, half of the participants were comfortable with accepting the recommendation. Key barriers to acceptance of software recommendations aligned with 2 Theoretical Domains Framework domains: Knowledge (uncertainty of software capability) and Beliefs about Consequences (perceived impact of software on clinical outcomes and workload). Key facilitators aligned with 2 domains: Beliefs about Consequences (improved efficiency) and Social Influences (influence of peers). A novel domain, Trust, was identified as influential. CONCLUSION Prescribers reported barriers to acceptance of dose-prediction software aligned with limited understanding of, and scepticism about, software capabilities, as well as concerns about clinical outcomes. Identification of key barriers and facilitators to acceptance provides essential information to design of implementation strategies to support the introduction of this intervention into the workplace.
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Affiliation(s)
- Jane E Carland
- Department of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Darlinghurst, NSW, Australia.,St Vincent's Clinical School, University of NSW, Kensington, NSW, Australia
| | - Tania Elhage
- Department of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Darlinghurst, NSW, Australia.,School of Medical Sciences, University of NSW, Kensington, NSW, Australia
| | - Melissa T Baysari
- Sydney School of Health Sciences, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
| | - Sophie L Stocker
- Department of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Darlinghurst, NSW, Australia.,St Vincent's Clinical School, University of NSW, Kensington, NSW, Australia
| | - Deborah J E Marriott
- St Vincent's Clinical School, University of NSW, Kensington, NSW, Australia.,Department of Clinical Microbiology and Infectious Diseases, St Vincent's Hospital, Darlinghurst, NSW, Australia
| | - Natalie Taylor
- Sydney School of Health Sciences, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, NSW, Australia.,Cancer Council NSW, Woolloomooloo, NSW, Australia
| | - Richard O Day
- Department of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Darlinghurst, NSW, Australia.,St Vincent's Clinical School, University of NSW, Kensington, NSW, Australia.,School of Medical Sciences, University of NSW, Kensington, NSW, Australia
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Phillips CJ, Wisdom AJ, McKinnon RA, Woodman RJ, Gordon DL. Interventions targeting the prescribing and monitoring of vancomycin for hospitalized patients: a systematic review with meta-analysis. Infect Drug Resist 2018; 11:2081-2094. [PMID: 30464551 PMCID: PMC6219104 DOI: 10.2147/idr.s176519] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Purpose Vancomycin prescribing requires individualized dosing and monitoring to ensure efficacy, limit toxicity, and minimize resistance. Although there are nationally endorsed guidelines from several countries addressing the complexities of vancomycin dosing and monitoring, there is limited consideration of how to implement these recommendations effectively. Methods We conducted a systematic search of multiple databases to identify relevant comparative studies describing the impact of interventions of educational meetings, implementation of guidelines, and dissemination of educational material on vancomycin dosing, monitoring, and nephrotoxicity. Effect size was assessed using ORs and pooled data analyzed using forest plots to provide overall effect measures. Results Six studies were included. All studies included educational meetings. Two studies used implementation of guidance, educational meetings, and dissemination of educational materials, one used guidance and educational meetings, one educational meetings and dissemination of educational materials, and two used educational meetings solely. Effect sizes for individual studies were more likely to be significant for multifaceted interventions. In meta-analysis, the overall effect of interventions on outcome measures of vancomycin dosing was OR 2.50 (95% CI 1.29–4.84); P< 0.01. A higher proportion of sampling at steady-state concentration was seen following intervention (OR 1.95, 95% CI 1.26–3.02; P<0.01). Interventions had no effect on appropriate timing of trough sample (OR 2.02, 95% CI 0.72–5.72; P=0.18), attaining target concentration in patients (OR 1.50, 95% CI 0.49–4.63; P=0.48, or nephrotoxicity (OR 0.75, 95% CI 0.42–1.34; P=0.33). Conclusion Multifaceted interventions are effective overall in improving the complex task of dosing vancomycin, as well as some vancomycin-monitoring outcome measures. However, the resulting impact of these interventions on efficacy and toxicity requires further investigation. These findings may be helpful to those charged with designing implementation strategies for vancomycin guidelines or complex prescribing processes in hospitals.
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Affiliation(s)
- Cameron J Phillips
- SA Pharmacy, Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia, .,College of Medicine and Public Health, Flinders University, Adelaide, SA 5000, Australia, .,School of Pharmacy and Medical Sciences, Division of Health Sciences, University of South Australia, Adelaide, SA 5000, Australia, .,Infectious Diseases and Immunity, Department of Medicine, Imperial College, London W12 0NN, UK,
| | - Alice J Wisdom
- SA Pharmacy, Lyell McEwin Hospital, Elizabeth Vale, Adelaide, SA 5112, Australia
| | - Ross A McKinnon
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5000, Australia, .,School of Pharmacy and Medical Sciences, Division of Health Sciences, University of South Australia, Adelaide, SA 5000, Australia, .,Flinders Centre for Innovation in Cancer, Flinders University, Adelaide, SA 5000, Australia
| | - Richard J Woodman
- Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, SA 5000, Australia
| | - David L Gordon
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5000, Australia, .,SA Pathology, Department of Microbiology and Infectious Diseases, Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia.,Division of Medicine, Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia
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