| Literature DB >> 34148842 |
Yi Zhao, Kavon Diggs, David Ha, Hannah Fish, John Beckner, Salisa C Westrick.
Abstract
BACKGROUND: The COVID-19 pandemic highlights the critical role of pharmacists in pandemic response. To enhance pharmacist's involvement in future emergency situations, there is a critical need to understand pharmacists' knowledge, willingness and preparedness in response to various emergency situations.Entities:
Mesh:
Year: 2021 PMID: 34148842 PMCID: PMC8679573 DOI: 10.1016/j.japh.2021.05.011
Source DB: PubMed Journal: J Am Pharm Assoc (2003) ISSN: 1086-5802
Participant experience in actual participation in and training for emergency situations
| Participant experience | n (%) |
|---|---|
| Whether they are registered as an emergency preparedness volunteer (n = 285) | |
| Yes → Reported comfort with the following (check all that apply): | 44 (15.4) |
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| No → Whether they consider registering as a volunteer and being trained in emergency preparedness and response | 229 (80.4) |
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| Not sure | 12 (4.2) |
| Whether they have volunteered in an actual public health emergency in the past 5 years (N = 342) | |
| Yes → Type of emergency (check all that apply): | 40 (11.7) |
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| No | 294 (86.0) |
| Don’t remember or unsure | 8 (2.3) |
| Whether they participated in a training session or an emergency preparedness drill in the past 5 years (N = 336) | |
| Yes → Whether immunization topic was included in the training: | 108 (32.1) |
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| No | 216 (64.3) |
| Unsure | 12 (3.6) |
| Willingness to be trained in an emergency preparedness (N = 333) | |
| Not at all | 3 (0.9) |
| Somewhat | 155 (46.5) |
| Very | 175 (52.6) |
Individual and pharmacy preparedness and willingness to respond in emergency situations
| Preparedness and willingness | Emergency situations | Not at all | Somewhat | Very |
|---|---|---|---|---|
| Individual preparedness (N = 324) | Natural disasters | 34 (10.5) | 219 (67.6) | 71 (21.9) |
| Bioterrorism emergencies | 168 (51.9) | 136 (42.0) | 20 (6.2) | |
| Influenza pandemic | 9 (2.8) | 152 (46.9) | 163 (50.3) | |
| Noninfluenza respiratory virus pandemic | 22 (6.8) | 198 (61.1) | 104 (32.1) | |
| Pharmacy preparedness (N = 316) | Natural disasters | 43 (13.6) | 219 (69.3) | 54 (17.1) |
| Bioterrorism emergencies | 170 (53.8) | 131 (41.5) | 15 (4.7) | |
| Influenza pandemic | 13 (4.1) | 164 (51.9) | 139 (44.0) | |
| Noninfluenza respiratory virus pandemic | 23 (7.3) | 193 (61.1) | 100 (31.6) | |
| Individual willingness (N = 301) | Distribution of prophylactic medical countermeasures | 8 (2.7) | 104 (34.6) | 189 (62.8) |
| Distribution of treatment medical countermeasures | 7 (2.3) | 101 (33.6) | 193 (64.1) | |
| Vaccine administration | 13 (4.3) | 57 (18.9) | 231 (76.7) | |
| Diagnostic testing for suspected infection | 39 (13.0) | 135 (44.9) | 127 (42.2) | |
| Antibody testing for postinfectious | 35 (11.6) | 104 (34.6) | 162 (53.8) | |
| Pharmacy willingness (N = 290) | Distribution of prophylactic medical countermeasures | 6 (2.1) | 86 (29.7) | 198 (68.3) |
| Distribution of treatment medical countermeasures | 5 (1.7) | 88 (30.3) | 197 (67.9) | |
| Vaccine administration | 10 (3.4) | 62 (21.4) | 218 (75.2) | |
| Diagnostic testing for suspected infection | 41 (14.1) | 129 (44.5) | 120 (41.4) | |
| Antibody testing for postinfectious | 34 (11.7) | 101 (34.8) | 155 (53.4) |
Participants’ knowledge and awareness of an MOU and their pharmacies’ disaster preparedness plan
| Knowledge and awareness | n(%) |
|---|---|
| Whether pharmacy has an MOU with health departments (N = 289) | |
| Yes | 6 (9.0) |
| No | 177 (61.2) |
| Not sure | 86 (29.8) |
| Know what MOU is (N = 263) | |
| Yes | 46 (17.5) |
| No | 167 (63.5) |
| Unsure | 50 (19.0) |
| Know how to establish an MOU (N = 262) | |
| Yes | 13 (5.0) |
| No | 115 (43.9) |
| Unsure | 46 (17.6) |
| Don’t know what MOU is | 88 (33.6) |
| Willingness to develop an MOU (N = 262) | |
| Not at all | 2 (0.8) |
| Somewhat | 107 (41.2) |
| Very | 56 (21.5) |
| Don’t know what MOU is | 95 (36.5) |
| Familiarity with the pharmacy’s disaster preparedness plan (N=279) | |
| Yes → Whether the plan was adequate for the COVID pandemic: | 180 (64.5) |
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| No | 67 (24.0) |
| Unsure | 32 (11.5) |
| Whether they want to receive assistance to update a disaster preparedness plan (N = 276) | |
| Yes | 215 (77.9) |
| No | 27 (9.8) |
| Unsure | 34 (12.3) |
Abbreviations used: MOU, memorandum of understanding; COVID, coronavirus disease.
Demographical characteristics between early and late responders
| Early Responders (15%) | Late Responders (15%) | P-value | |
|---|---|---|---|
| Mean (SD) | Mean (SD) | ||
| Age | 49.76 (12.36) | 48.54 (10.57) | 0.093 |
| N (%) | N (%) | ||
| Male | 22 (57.9) | 21 (55.3) | 0.817 |
| Female | 16 (42.1) | 17 (44.7) | |
| White | 37 (100.0) | 30 (78.9) | 0.011 |
| Other | 0 | 8 (21.1) | |
| Not Hispanic or Latino | 37 (100) | 35 (100) | -- |
| Pharmacist pharmacy owner/partner/manager | 32 (84.2) | 28 (73.7) | 0.260 |
| Other | 6 (15.8) | 10 (26.3) | |
| PharmD | 20 (52.6) | 20 (52.6) | 1.000 |
| Other | 18 (47.4) | 18 (47.4) |
Potential difference between early respondents and late respondents were investigated by using t-test for respondents’ age, Fisher’s Exact text for race and Chi-square test for respondents’ gender, title and education.
Significant difference is defined as P-value < 0.05.
Pharmacy characteristics between early and late responders
| Early Responders (15%) | Late Responders (15%) | P-value | |
|---|---|---|---|
| 1.000 | |||
| Stand-alone independent pharmacy | 32 (84.2) | 32 (84.2) | |
| Other | 6 (15.8) | 6 (15.8) | |
| 0.345 | |||
| Yes, no change | 6 (17.6) | 9 (27.3) | |
| Yes, with some modifications or No | 28 (82.4) | 24 (72.7) | |
| 0.105 | |||
| Yes, no change or with some modifications | 28 (82.4) | 32 (97.0) | |
| No | 6 (17.6) | 1 (3.0) | |
| 0.803 | |||
| Yes | 12 (31.6) | 11 (28.9) | |
| No | 26 (68.4) | 27 (71.1) | |
| 1.000 | |||
| Yes | 36 (94.7) | 36 (94.7) | |
| No | 2 (5.3) | 2 (5.3) |
Potential difference between early respondents and late respondents were investigated by using Chi-square test. Significant difference is defined as P-value < 0.05.
Participant and pharmacy characteristics (N = 255)
| Participant and pharmacy characteristics | Mean/n(%) |
|---|---|
| Age (N = 255) | 49.2 (12.0) |
| Sex (N = 254) | |
| Male | 153 (60.2) |
| Race (N = 251) | |
| White | 224 (89.2) |
| Asian | 10 (4.0) |
| Black | 1 (0.4) |
| American Indian or Alaska Native | 1 (0.4) |
| Other | 15 (6.0) |
| Ethnicity (N = 248) | |
| Hispanic or Latino | 2 (0.8) |
| Not Hispanic or Latino | 246 (99.2) |
| Title | |
| Pharmacist pharmacy owner/partner/manager | 206 (80.8) |
| Staff pharmacist | 35 (13.7) |
| Nonpharmacist pharmacy owner/partner/manager | 13 (5.1) |
| Pharmacy technician or clerk | 8 (3.1) |
| Student pharmacist | 4 (1.6) |
| Other | 6 (2.4) |
| Education/Training | |
| B.S. Pharmacy | 121 (47.5) |
| PharmD | 113 (44.3) |
| Residency in Pharmacy | 15 (5.9) |
| Pharmacy Technician Certification | 11 (4.3) |
| Master of Pharmacy | 2 (0.8) |
| Other | 24 (9.4) |
| Pharmacy type | |
| Stand-alone independent pharmacy | 213 (60.2) |
| Pharmacy within a grocery or retail store | 21 (39.8) |
| Pharmacy embedded within a medical clinic or a hospital | 16 (6.3) |
| Other | 9 (3.5) |
| Geographic regions (N = 246) | |
| Southeast | 77 (31.3) |
| Midwest | 72 (29.3) |
| Northeast | 46 (18.7) |
| Southwest | 28 (11.4) |
| West | 23 (9.3) |
| Rurality | |
| Urban | 142 (57.7) |
| Rural | 61 (24.8) |
| Suburban | 43 (17.5) |
| Prescription volume per day (N = 249) | 240.88 (170.9) |
| Full-time equivalents, 40 hr/wk (N = 253) | 3.4 (7.3) |
More than one option can be selected
Degree of rurality was classified on the basis of 2010 rural-urban commuting area codes. Codes 1 to 3 were defined as urban areas, 4 to 6 as suburban areas, and 7 to 10 as rural areas.