| Literature DB >> 31367344 |
J Keizer1, L M A Braakman-Jansen1, S Kampmeier2, R Köck2,3,4, N Al Naiemi5,6, R Te Riet-Warning5, N Beerlage-De Jong1, K Becker3, J E W C Van Gemert-Pijnen1.
Abstract
Background: Cross-border healthcare may promote the spread of multidrug-resistant microorganisms (MDRO) and is challenging due to heterogeneous antimicrobial resistance (AMR) prevention measures (APM). The aim of this article is to compare healthcare workers (HCW) from Germany (DE) and The Netherlands (NL) on how they perceive and experience AMR and APM, which is important for safe patient exchange and effective cross-border APM cooperation.Entities:
Keywords: Antimicrobial resistance (AMR); Cross-border; Euroregion; Germany; Healthcare worker; Infection control; Multidrug-resistant microorganisms; Netherlands; Prevention
Mesh:
Year: 2019 PMID: 31367344 PMCID: PMC6647090 DOI: 10.1186/s13756-019-0577-4
Source DB: PubMed Journal: Antimicrob Resist Infect Control ISSN: 2047-2994 Impact factor: 4.887
Survey respondents’ characteristics
| Variable & levels | Total | All respondents | Diff. DE/NL | Physicians | Diff. P DE/NL | Nurses | Diff. N DE/NL | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| n (%) | DE | NL | Test | DE | NL | Test | DE | NL | Test | ||
| # | n (%) | 574 (100) | 305 (53) | 269 (47) | – | 128 (22) | 49 (9) | – | 177 (31) | 220 (38) | – |
| Sex | Male | 181 (32) | 131 (43) | 50 (19) | Chi2 (≤0.001) | 86 (67) | 32 (65) | Chi2 (0.812) | 45 (25) | 18 (8) | Chi2 (≤0.001) |
| Female | 393 (68) | 174 (57) | 219 (81) | 42 (33) | 17 (35) | 132 (75) | 202 (92) | ||||
| Age | < 25 years | 30 (5) | 20 (7) | 11 (4) | Chi2 (≤0.001) | 0 (0) | 0 (0) | Fisher’s exact (≤0.001) | 20 (11) | 10 (5) | Chi2 (0.002) |
| 25–35 years | 182 (32) | 121 (40) | 61 (23) | 58 (45) | 8 (16) | 63 (36) | 53 (24) | ||||
| 36–45 years | 157 (27) | 78 (26) | 78 (29) | 45 (35) | 19 (39) | 33 (19) | 60 (27) | ||||
| 46–55 years | 129 (22) | 60 (20) | 67 (25) | 17 (13) | 10 (20) | 43 (24) | 59 (27) | ||||
| 56–65 years | 74 (13) | 25 (8) | 51 (19) | 7 (5) | 11 (22) | 18 (10) | 38 (17) | ||||
| > 65 years | 2 (0) | 1 (0) | 1 (0) | 1 (1) | 1 (2) | 0 (0) | 0 (0) | ||||
| Hospital | 1 (general) | 223 (39) | – | 223 (83) | – | – | 41 (84) | – | – | 182 (83) | – |
| 2 (academic) | 252 (44) | 251 (82) | – | 96 (75) | – | 156 (88) | – | ||||
| 3 (academic) | 46 (8) | – | 46 (17) | – | 8 (16) | – | 38 (17) | ||||
| 4 (university) | 23 (4) | 23 (8) | – | 11 (9) | – | 12 (7) | – | ||||
| 5 (university) | 13 (2) | 14 (5) | – | 9 (7) | – | 4 (2) | – | ||||
| 6 (university) | 12 (2) | 12 (4) | – | 8 (6) | – | 4 (2) | – | ||||
| Otherb | 5 (1) | 5 (2) | – | 4 (3) | – | 1 (1) | – | ||||
| Departmentsa | Anaesthesiology | 80 (11) | 72 (17) | 8 (3) | – | 34 (19) | 5 (10) | – | 38 (16) | 3 (1) | – |
| Intensive Care | 79 (11) | 63 (15) | 17 (6) | 25 (14) | 4 (2) | 38 (16) | 13 (5) | ||||
| Paediatrics | 77 (11) | 42 (10) | 35 (11) | 14 (8) | 1 (1) | 28 (12) | 34 (13) | ||||
| Surgery | 72 (10) | 25 (6) | 47 (15) | 8 (4) | 3 (2) | 17 (7) | 44 (17) | ||||
| Obstetrics/Gynaecology | 44 (6) | 11 (3) | 34 (11) | 4 (2) | 5 (3) | 7 (3) | 29 (11) | ||||
| Internal medicine | 36 (5) | 20 (5) | 16 (5) | 15 (8) | 1 (1) | 5 (2) | 15 (6) | ||||
| Oncology | 33 (5) | 24 (6) | 11 (4) | 9 (5) | 0 (0) | 15 (6) | 11 (4) | ||||
| Orthopaedics | 33 (5) | 17 (4) | 17 (6) | 8 (4) | 7 (4) | 9 (4) | 10 (4) | ||||
| Emergency Department | 30 (4) | 17 (4) | 13 (4) | 9 (5) | 3 (2) | 8 (3) | 10 (4) | ||||
| Other | 235 (33) | 124 (30) | 111 (36) | 52 (29) | 20 (11) | 72 (30) | 91 (35) | ||||
| Hospital experience | < 1 year | 25 (4) | 15 (5) | 10 (4) | Chi2 (≤0.001) | 6 (5) | 4 (8) | Chi2 (0.333) | 9 (5) | 6 (3) | Chi2 (0.005) |
| ≥1 year, < 5 years | 116 (20) | 84 (28) | 32 (12) | 49 (38) | 12 (24) | 35 (20) | 20 (9) | ||||
| 5–10 years | 132 (23) | 73 (24) | 60 (22) | 35 (27) | 15 (31) | 38 (21) | 44 (20) | ||||
| > 10 years | 301 (52) | 133 (44) | 167 (62) | 38 (30) | 18 (37) | 95 (54) | 150 (68) | ||||
Note. Differences between nationalities are calculated with Chi-square tests of homogeneity (Asymptotic Significance (2-sided) shown) or Fisher’s exact tests (Exact Sig. (2-sided) shown)
aOnly departments with > 30 respondents in total (DE + NL) are shown. Respondents could select multiple departments (23% of the German and 9% of the Dutch HCW indicated to work at various departments)
bSnowball-sampling included five respondents from two other hospitals, both located within the EUREGIO
AMR statement responses of (i) all respondents, (ii) German/Dutch physicians, and (iii) German/Dutch nurses, including p-values of differences between nationalities
|
| All respondents (n = 574) | Physicians (n = 177) | Nurses (n = 397) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| DE | NL | P-value | DE ( | NL | P-value | DE | NL | P-value | ||
| Mean | Mean | Mean | Mean | Mean | Mean | |||||
| AMR is a problem for … | the general population. | 4.2 |
|
| 4.3 |
|
| 4.1 |
|
|
| nursing homes. | 4.3 | 4.4 | 0.968 | 4.4 | 4.4 | 0.851 | 4.3 | 4.4 | 0.859 | |
| our hospital. | 4.4 |
|
| 4.3 | 4.6 | 0.180 | 4.4 | 4.6 | 0.262 | |
| my patients. | 4.2 |
|
| 4.2 | 4.3 | 0.281 | 4.3 |
|
| |
| One of the leading causes of AMR is … | the use of antibiotics in farming animals. |
| 3.6 |
|
| 4.0 |
|
| 3.5 |
|
| the use of antibiotics by patients. | 3.4 |
|
| 3.2 |
|
| 3.5 | 3.6 | 0.379 | |
| the admission of nursing home patients. |
| 2.4 |
| 2.6 | 2.5 | 0.254 |
| 2.4 |
| |
| I believe that … | antibiotics are prescribed at the request of patients. |
| 2.4 |
|
| 2.4 |
|
| 2.3 |
|
| antibiotic prescriptions should be based on lab results. |
| 3.9 |
|
| 3.9 |
|
| 3.9 |
| |
| I am sufficiently informed about the diagnostic policy. |
| 3.4 |
| 3.6 | 3.8 | 0.791 |
| 3.3 |
| |
| broad spectrum antibiotics should be provided when there is doubt of an infection. | 1.7 |
|
| 1.5 |
|
| 1.9 |
|
| |
| I can contribute sufficiently to limit AMR. |
| 2.8 |
|
| 4.3 |
|
| 2.6 |
| |
Note. When there is a statistically significant difference between nationalities, the nationality with the highest mean is shown in bold. DE Germany, NL The Netherlands
APM responses of (i) all respondents, (ii) German/Dutch physicians, and (iii) German/Dutch nurses, including p-values of differences between nationalities
|
| All respondents ( | Physicians ( | Nurses ( | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| DE | NL | DE ( | NL | DE | NL | |||||
| Mean | Mean | Mean | Mean | Mean | Mean | |||||
| Screening diagnostics | Importance |
| 4.5 |
|
| 4.4 |
|
| 4.6 |
|
| Feeling sufficiently equippeda |
| 3.3 |
| 3.7 | 3.6 | 0.075 | 3.5 | 3.3 | 0.166 | |
| Infection diagnosis | Importance |
| 4.5 |
|
| 4.4 |
| 4.6 | 4.5 | 0.134 |
| Feeling sufficiently equippeda |
| 3.3 |
| 4.3 | 4.2 | 0.197 | 3.2 | 3.1 | 0.335 | |
| Treatment | Importance |
| 4.5 |
|
| 4.5 |
|
| 4.4 |
|
| Feeling sufficiently equippeda |
| 2.8 |
| 4.0 | 4.1 | 0.746 |
| 2.5 |
| |
| Infection control | Importance |
| 4.5 |
|
| 4.3 |
|
| 4.5 |
|
| Feeling sufficiently equippeda | 4.0 | 3.9 | 0.230 | 3.9 | 3.8 | 0.534 | 4.0 | 3.9 | 0.114 | |
Note. When there is a statistically significant difference between nationalities, the nationality with the highest mean is shown in bold. DE = Germany, NL = The Netherlands
aCronbach’s alphas for the “Feeling sufficiently equipped”-scales were between 0.69 and 0.83 for all respondents of this study
Fig. 1Antimicrobial resistance (AMR) and AMR prevention measures (APM): similarities and differences between German and Dutch respondents