| Literature DB >> 28775763 |
Massimo Sartelli1, Francesco M Labricciosa2, Pamela Barbadoro2, Leonardo Pagani3, Luca Ansaloni4, Adrian J Brink5,6, Jean Carlet7, Ashish Khanna8, Alain Chichom-Mefire9, Federico Coccolini10, Salomone Di Saverio11, Addison K May12, Pierluigi Viale13, Richard R Watkins14,15, Luigia Scudeller16, Lilian M Abbo17, Fikri M Abu-Zidan18, Abdulrashid K Adesunkanmi19, Sara Al-Dahir20, Majdi N Al-Hasan21, Halil Alis22, Carlos Alves23, André R Araujo da Silva24, Goran Augustin25, Miklosh Bala26, Philip S Barie27, Marcelo A Beltrán28, Aneel Bhangu29, Belefquih Bouchra30, Stephen M Brecher31,32, Miguel A Caínzos33, Adrian Camacho-Ortiz34, Marco Catani35, Sujith J Chandy36, Asri Che Jusoh37, Jill R Cherry-Bukowiec38, Osvaldo Chiara39, Elif Colak40, Oliver A Cornely41, Yunfeng Cui42, Zaza Demetrashvili43, Belinda De Simone44, Jan J De Waele45, Sameer Dhingra46,47, Francesco Di Marzo48, Agron Dogjani49, Gereltuya Dorj50, Laurent Dortet51, Therese M Duane52, Mutasim M Elmangory53, Mushira A Enani54, Paula Ferrada55, J Esteban Foianini56, Mahir Gachabayov57, Chinmay Gandhi58, Wagih Mommtaz Ghnnam59, Helen Giamarellou60, Georgios Gkiokas61, Harumi Gomi62, Tatjana Goranovic63, Ewen A Griffiths64, Rosio I Guerra Gronerth65, Julio C Haidamus Monteiro66, Timothy C Hardcastle67, Andreas Hecker68, Adrien M Hodonou69, Orestis Ioannidis70, Arda Isik71, Katia A Iskandar72, Hossein S Kafil73, Souha S Kanj74, Lewis J Kaplan75, Garima Kapoor76, Aleksandar R Karamarkovic77, Jakub Kenig78, Ivan Kerschaever79, Faryal Khamis80, Vladimir Khokha81, Ronald Kiguba82, Hong B Kim83, Wen-Chien Ko84, Kaoru Koike85, Iryna Kozlovska86, Anand Kumar87, Leonel Lagunes88, Rifat Latifi89, Jae G Lee90, Young R Lee91, Ari Leppäniemi92, Yousheng Li93, Stephen Y Liang94, Warren Lowman95, Gustavo M Machain96, Marc Maegele97, Piotr Major98, Sydney Malama99, Ramiro Manzano-Nunez100, Athanasios Marinis101, Isidro Martinez Casas102, Sanjay Marwah103, Emilio Maseda104, Michael E McFarlane105, Ziad Memish106, Dominik Mertz107, Cristian Mesina108, Shyam K Mishra109, Ernest E Moore110, Akutu Munyika111, Eleftherios Mylonakis112, Lena Napolitano113, Ionut Negoi114, Milica D Nestorovic115, David P Nicolau116, Abdelkarim H Omari117, Carlos A Ordonez118, José-Artur Paiva119, Narayan D Pant120, Jose G Parreira121, Michal Pędziwiatr122, Bruno M Pereira123, Alfredo Ponce-de-Leon124, Garyphallia Poulakou125, Jacobus Preller126, Céline Pulcini127, Guntars Pupelis128, Martha Quiodettis129, Timothy M Rawson130, Tarcisio Reis131, Miran Rems132, Sandro Rizoli133, Jason Roberts134, Nuno Rocha Pereira23, Jesús Rodríguez-Baño135, Boris Sakakushev136, James Sanders137, Natalia Santos138, Norio Sato139, Robert G Sawyer140, Sandro Scarpelini141, Loredana Scoccia142, Nusrat Shafiq143, Vishalkumar Shelat144, Costi D Sifri145, Boonying Siribumrungwong146, Kjetil Søreide147,148, Rodolfo Soto149, Hamilton P de Souza150, Peep Talving151, Ngo Tat Trung152, Jeffrey M Tessier153, Mario Tumbarello154, Jan Ulrych155, Selman Uranues156, Harry Van Goor157, Andras Vereczkei158, Florian Wagenlehner159, Yonghong Xiao160, Kuo-Ching Yuan161, Agnes Wechsler-Fördös162, Jean-Ralph Zahar163, Tanya L Zakrison164, Brian Zuckerbraun165, Wietse P Zuidema166, Fausto Catena167.
Abstract
BACKGROUND: Antimicrobial Stewardship Programs (ASPs) have been promoted to optimize antimicrobial usage and patient outcomes, and to reduce the emergence of antimicrobial-resistant organisms. However, the best strategies for an ASP are not definitively established and are likely to vary based on local culture, policy, and routine clinical practice, and probably limited resources in middle-income countries. The aim of this study is to evaluate structures and resources of antimicrobial stewardship teams (ASTs) in surgical departments from different regions of the world.Entities:
Keywords: Antibiotics; Antimicrobial stewardship; Infections; Surgery
Mesh:
Substances:
Year: 2017 PMID: 28775763 PMCID: PMC5540347 DOI: 10.1186/s13017-017-0145-2
Source DB: PubMed Journal: World J Emerg Surg ISSN: 1749-7922 Impact factor: 5.469
Participants’ working settings and professional profiles
| Characteristics | African region | Eastern- Mediterranean region | European region | Region of Americas | South-East Asia region | Western Pacific region | Total |
|---|---|---|---|---|---|---|---|
| Type of hospital, n (%) | |||||||
| - University hospital | 5 (62.5) | 6 (46.1) | 50 (74.6) | 35 (74.5) | 6 (75.0) | 12 (80.0) | 114 (72.1) |
| - Community teaching hospital | 2 (25.0) | 3 (23.1) | 14 (20.9) | 9 (19.1) | 1 (12.5) | 1 (6.7) | 30 (19.0) |
| - Community hospital | 0 | 2 (15.4) | 3 (4.5) | 1 (2.1) | 1 (12.5) | 2 (13.3) | 9 (5.7) |
| - Other | 1 (12.5) | 2 (15.4) | 0 | 2 (4.3) | 0 | 0 | 5 (3.2) |
| Hospital setting, n (%) | |||||||
| - Urban | 5 (62.5) | 10 (76.9) | 65 (97.0) | 44 (93.6) | 6 (75.0) | 14 (93.3) | 144 (91.1) |
| - Suburban | 3 (37.5) | 3 (23.1) | 2 (3.0) | 1 (2.1) | 2 (25.0) | 0 | 11 (7.0) |
| - Rural | 0 | 0 | 0 | 2 (4.3) | 0 | 1 (6.7) | 3 (1.9) |
| Hospital inpatient beds, n (%) | |||||||
| - ≤100 | 0 | 2 (15.4) | 3 (4.5) | 1 (2.1) | 0 | 0 | 6 (3.8) |
| - 101–500 | 3 (37.5) | 5 (38.5) | 15 (22.4) | 10 (21.3) | 2 (25.0) | 3 (20.0) | 38 (24.1) |
| - 501–1000 | 3 (37.5) | 5 (38.5) | 27 (40.3) | 28 (59.6) | 3 (37.5) | 1 (6.7) | 67 (42.4) |
| - ≥ 1000 | 2 (25.0) | 1 (7.7) | 22 (32.8) | 8 (17.0) | 3 (37.5) | 11 (73.3) | 47 (29.7) |
| Profession, n (%) | |||||||
| Epidemiologist | 1 (12.5) | 0 | 2 (3.0) | 1 (2.1) | 0 | 0 | 4 (2.5) |
| Hospital administrator | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Clinical pharmacologist | 0 | 1 (7.7) | 0 | 4 (8.5) | 1(12.5) | 1 (6.7) | 7 (4.4) |
| Hospital pharmacist | 0 | 0 | 1 (1.5) | 1 (2.1) | 1 (12.5) | 1 (6.7) | 4 (2.5) |
| Infection control specialist | 0 | 0 | 1 (1.5) | 1 (2.1) | 0 | 0 | 2 (1.3) |
| Infectious diseases specialist | 0 | 4 (30.8) | 10 (14.9) | 10 (21.3) | 0 | 5 (33.3) | 29 (18.4) |
| Intensivist | 1 (12.5) | 0 | 5 (7.5) | 2 (4.3) | 0 | 1 (6.7) | 9 (5.7) |
| Microbiologist | 3 (37.5) | 3 (23.1) | 1 (1.5) | 1 (2.1) | 3 (37.5) | 0 | 11 (7.0) |
| Surgeon | 3 (37.5) | 5 (38.5) | 44 (65.7) | 24 (51.1) | 3 (37.5) | 6 (40.0) | 85 (53.8) |
| Other | 0 | 0 | 3 (4.5) | 3 (6.4) | 0 | 1 (6.7) | 7 (4.4) |
Characteristics of the team in 156 hospitals
| Characteristics |
|
|---|---|
| Components | |
| - Epidemiologist | 64 (41.0) |
| - Hospital administrator | 73 (46.8) |
| - Clinical pharmacologist | 8 (5.1) |
| - Hospital pharmacist | 95 (60.9) |
| - Infection control specialist | 106 (67.9) |
| - Infectious disease specialist | 125 (80.1) |
| - Intensivist | 76 (48.7) |
| - Microbiologist | 119 (76.3) |
| - Surgeon | 92 (59.0) |
| - Other | 11 (7.1) |
| - Infectious disease specialist AND hospital pharmacologist/pharmacist | 87 (55.8) |
| Frequency of meetings | |
| - More than once a week | 15 (9.6) |
| - Once a week | 26 (16.7) |
| - Twice a month | 13 (8.3) |
| - Once a month | 58 (37.2) |
| - Less than once a month | 27 (17.3) |
| - Only as necessary | 17 (10.9) |
Implementation of protocols and monitoring systems in 158 hospitals
| Implementation of protocols and monitoring systems | All hospital wards | Some hospital wards, including surgical wards | Some hospital wards, not including surgical wards | No hospital wards | |
|---|---|---|---|---|---|
| Every surgical wards | Some surgical wards | ||||
| - SAP protocol | NA | 124 (78.5) | 28 (17.7) | NA | 6 (3.8) |
| - TIS protocol | NA | 70 (44.3) | 60 (38.0) | NA | 28 (17.7) |
| - UAMS | 84 (53.2) | 45 (28.5) | 9 (5.7) | 20 (12.7) | |
| - RDSR | 104 (65.8) | 26 (16.5) | 7 (4.4) | 21 (13.3) | |
SAP Surgical antimicrobial prophylaxis, TIS therapy for infections in surgery, UAMS used antimicrobial monitoring system, RDSR resistance data systematic report
Difference in type of ASPs and related implemented types of interventions in surgical departments and non-surgical departments
| Characteristics | Surgical departments, | Other departments, |
| Total, |
|---|---|---|---|---|
| Type of ASPs | ||||
| - Persuasive interventions | 23 (16.9) | 7 (36.8) | 0.06a | 30 (19.4) |
| - Restrictive interventions | 14 (10.3) | 3 (15.8) | 0.44a | 17 (11.0) |
| - Both | 99 (72.8) | 9 (47.4) | <0.05 | 108 (69.7) |
| Type of interventions | ||||
| - Dissemination of educational materials | 85 (62.5) | 8 (42.1) | 0.15 | 93 (60.0) |
| - Reminders | 56 (41.2) | 8 (42.1) | 1.00 | 64 (41.3) |
| - Audit and feedback | 75 (55.1) | 4 (21.1) | <0.05 | 79 (51.0) |
| - Educational outreach | 73 (53.7) | 10 (52.6) | 1.00 | 83 (53.6) |
| - Other persuasive interventions | 23 (16.9) | 3 (15.8) | 1.00a | 26 (16.8) |
| - Compulsory order form | 70 (51.5) | 7 (36.8) | 0.34 | 77 (49.7) |
| - Expert approval | 83 (61.0) | 5 (26.3) | <0.05 | 88 (56.8) |
| - Restriction by removal | 41 (30.1) | 2 (10.5) | 0.13 | 43 (27.7) |
| - Review and make changes | 36 (26.5) | 1 (5.3) | <0.05a | 37 (23.9) |
| - Other restrictive interventions | 10 (7.4) | 3 (15.8) | 0.20a | 13 (8.4) |
All p values were calculated using two-sided chi-square test unless otherwise noted
ASP antimicrobial stewardship program
aCalculated using two-sided Fisher’s exact test
Implementation of protocols, monitoring systems and ASPs interventions in surgical departments related to working setting and team components
| Variables | PAP protocol implemented | TIS protocol implemented | Monitoring system of used antimicrobials | Resistance data systematic reports | ASP implemented | Structural intervention |
|---|---|---|---|---|---|---|
| Number of bed | ||||||
| Less than 100, | 5 (83.3) 1.00a | 4 (66.7) 0.29a | 4 (66.7) 0.30a | 4 (66.7) 0.29a | 3 (50.0) 0.58a | 3 (50.0) 0.10a |
| 101–500, | 37 (97.4) 1.00a | 32 (84.2) 0.57 | 29 (76.3) 0.80 | 30 (78.9) 1.00 | 32 (84.2) 0.75 | 22 (57.9) <0.05a |
| 501–1000, | 62 (92.5) 0.08a | 53 (79.1) 0.49 | 53 (79.1) 0.62 | 56 (83.6) 0.87 | 56 (83.6) 0.75 | 58 (86.6) <0.05a |
| More than 1000, | 47 (100.0) 0.18a | 40 (85.1) 0.71 | 42 (89.4) 0.16 | 39 (83.0) 1.00 | 39 (83.0) 1.00 | 41 (87.2) 0.16 |
| Hospital setting | ||||||
| Urban, | 140 (97.2) 0.09 | 118 (81.9) 1.00a | 119 (82.6) 0.29a | 122 (84.7) <0.05a | 120 (83.3) 0.40a | 97 (67.4) 0.17a |
| Suburban and rural, | 12 (85.7) 0.09 | 12 (85.7) 1.00a | 11 (78.6) 0.29a | 9 (64.3) <0.05a | 10 (71.4) 0.40a | 9 (64.3) 0.17a |
| Type of hospital | ||||||
| University hospital, | 110 (96.5) 0.67a | 92 (80.7) 0.55 | 94 (82.5) 0.84 | 98 (86.0) 0.08 | 92 (80.7) 0.84 | 95 (83.3) <0.05 |
| Community teaching hospital, | 29 (96.7) 1.00a | 27 (90.0) 0.33 | 27 (90.0) 0.60 | 24 (80.0) 0.92 | 26 (86.7) 0.77a | 22 (73.3) 0.54 |
| Community hospital, | 8 (88.9) 0.30a | 8 (88.9) 1.00a | 7 (77.8) 0.67a | 5 (55.6) 0.05a | 9 (100.0) 1.00a | 3 (33.3) <0.05a |
| Other, | 5 (100.0) 1.00a | 3 (60.0) 0.21a | 3 (60.0) <0.05a | 4 (80.0) 0.21a | 4 (80.0) 0.52a | 4 (80.0) 1.00a |
| Components of the team | ||||||
| Epidemiologist, | 62 (96.9) 1.00a | 53 (82.8) 1.00 | 52 (81.3) 1.00 | 59 (92.2) <0.05 | 52 (81.3) 1.00 | 53 (82.8) 0.46 |
| Infection control specialist, | 103 (97.2) 0.40a | 90 (84.9) 0.31 | 91 (85.8) 0.08 | 89 (84.0) 0.57 | 89 (84.0) 1.00 | 82 (77.4) 0.79 |
| Hospital administrator, | 71 (97.3) 0.69a | 65 (89.0) 0.06 | 61 (83.6) 0.71 | 61 (83.6) 0.86 | 63 (86.3) 0.29 | 59 (80.8) 0.49 |
| Hospital pharmacologist, | 94 (98.9) <0.05a | 80 (84.2) 0.57 | 80 (84.2) 0.42 | 82 (86.3) 0.16 | 83 (87.4) 0.29 | 79 (83.2) 0.08 |
| Hospital pharmacist, | 7 (87.5) 0.27a | 6 (75.0) 0.43a | 7 (87.5) 0.55a | 5 (62.5) 0.15a | 7 (87.5) 0.36a | 3 (37.5) <0.05a |
| Infectious diseases specialist, | 120 (96.0) 1.00a | 100 (80.0) v0.23 | 104 (83.2) 0.47 | 103 (82.4) 1.00 | 107 (85.6) 0.15a | 95 (76.0) 0.50 |
| Intensivist, | 74 (97.4) 0.68a | 65 (85.5) 0.41 | 66 (86.8) 0.16 | 63 (82.9) 1.00 | 66 (86.8) 0.80 | 60 (78.9) 1.00 |
| Microbiologist, | 119 (100.0) 0.64a | 98 (82.4) 1.00 | 96 (80.7) 0.75 | 100 (84.0) 0.44 | 98 (82.4) 0.82 | 91 (76.5) 0.46 |
| Surgeon, | 88 (95.7) 1.00a | 80 (87.0) 0.11 | 77 (83.7) 0.56 | 77 (83.7) 0.73 | 76 (82.6) 0.70 | 70 (76.1) 0.61 |
| Other, | 11 (100.0) 1.00a | 9 (81.8) 1.00a | 11 (100.0) 0.22a | 10 (90.9) 0.69a | 10 (90.9) 1.00a | 8 (72.7) 0.70a |
All p values were calculated using two-sided chi-square test unless otherwise noted
PAP pre-operative antimicrobial prophylaxis, TIS therapy for infections in surgery, ASP antimicrobial stewardship program
aCalculated using two-sided Fisher’s exact test. ASP antimicrobial stewardship program