| Literature DB >> 31554837 |
Yonas Getaye Tefera1, Begashaw Melaku Gebresillassie2, Asnakew Achaw Ayele2, Yared Belete Belay3, Yohannes Kelifa Emiru4.
Abstract
The types of drug-related information request from patients and health professionals, the extent of inquiry and capability of existing drug information centers are seldom studied in Ethiopia. This study aimed to identify the types and potential areas of drug information inquiry at the Drug Information Center (DIC) of Gondar University specialized Hospital (GUSH), Ethiopia. An observational study was employed. The drug information query was collected by distributing the drug information queries in different hospital units through two batches of graduating undergraduate pharmacy students. Descriptive statistics used to describe, characterize and classify drug related queries. Binary logistic regression test was employed to identify predictor variables to type of drug information query. A total of 781 drug related queries were collected and 697 were included in the final analysis. Near to half (45.3%) of queries comes from the pharmacists followed by general practitioners (11.3%) and nurses (10.2%). Slightly greater than half of the queries (51.9%) were focused on therapeutic information. 39.6% of drug related queries related to infectious disease case scenarios, followed by cardiovascular cases in 21.3% of queries. More than half of (53.9%) and nearly one in five (19.4%) of the queries took 5 to 30 minutes and 30 minutes to 1 hour of literature searching to answer, respectively. Pharmacists (with odds ratio of 2.474(95% CI (1.373-4.458)) and patients (with odds ratio of 4.121(1.403-12.105)) ask patient-specific questions in their drug related queries higher than other group of health professionals. Pharmacists are the primary drug information users and frequent drug related information inquirers at the DIC. Most of the queries targeted therapeutic indications, adverse drug events, infectious or cardiovascular disease related requests. This is imperative that drug information services can assist the growing role of pharmacists in addressing the patient specific drug related needs.Entities:
Mesh:
Year: 2019 PMID: 31554837 PMCID: PMC6761201 DOI: 10.1038/s41598-019-50204-1
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Socio demographic characteristics of drug information requestors at Gondar University Specialized Hospital, 2018 (N = 697).
| Variables | Frequency (%) |
|---|---|
| Qualification of the requestor | |
| General Practitioner | 79(11.3%) |
| Specialist Physician | 39(5.6%) |
| Pharmacist | 316(45.3%) |
| Nurse | 71(10.2%) |
| Health officer | 47(6.7%) |
| Patient | 23(3.3%) |
| Caregiver | 9(1.3%) |
| Intern | 55(7.9%) |
| Druggist | 4(0.6%) |
| Other | 54(7.7%) |
|
| |
| Visit | 668(95.8%) |
| Phone | 25(3.6%) |
| 4(0.6%) | |
|
| |
| Oral | 579(83.1%) |
| Written | 91(13.1%) |
| Literature supplied | 13(1.8%) |
| Referred | 14(2.0%) |
|
| |
| Therapy | 362(51.9%) |
| Pregnancy | 18(2.6%) |
| ADR | 77(11.0%) |
| Interaction | 41(5.9%) |
| Quality | 2(0.3%) |
| Pharmaceutical | 3(0.4%) |
| Pharmacology | 61(8.8%) |
| Pharmacokinetics | 19(2.7%) |
| Local/foreign equivalence | 3(0.4%) |
| Availability | 14(2.0%) |
| Price | 2(0.3%) |
| Dose | 41(5.9%) |
| Administration | 21(3.0%) |
| Other | 33(4.7%) |
Query Characteristics in the drug information request at Gondar University Specialized Hospital; 2018 (N = 697).
| Variables | Frequency (%) |
|---|---|
|
| |
| Male | 187(26.8%) |
| Female | 173(24.8%) |
| Not specified | 337(48.4%) |
|
| |
| Yes | 502(72%) |
| No | 195(28%) |
|
| |
| Reference books | 146(20.9%) |
| Journals | 32(4.6%) |
| In-house database | 284(40.7%) |
| Peer reviewer | 3.9% |
| Internet sources | 170(24.4%) |
| Packaging inserts | 4(0.6%) |
| Other drug information services | 17(2.4%) |
|
| |
| 0–5 mins | 103(14.8%) |
| 5–30 mins | 375(53.8%) |
| 30 mins – 1 hour | 135(19.4%) |
| 1–4 hours | 60(8.6%) |
| 4–8 hours | 23(3.3%) |
|
| |
| Patient specific Questions | 370(53.1%) |
| General type Questions | 327(46.9%) |
|
| |
| 2016 | 451(64.7%) |
| 2017 | 246(35.3%) |
Figure 1Query classification by the patient diagnosis requested at GUSH DIC, 2018.
Query characterization encompassing on different medication classification at the DIC of GUSH, 2018. (N = 697).
| Query by Medication categories (n = 544, 78%) | Frequency | Percentage from total query | Percentage from medication related query |
|---|---|---|---|
| Antibiotics | 128 | 18.4% | 23.5% |
| Antiretrovirals | 23 | 3.3% | 4.2% |
| Antimalarials | 18 | 2.6% | 3.3% |
| Antihelminth | 14 | 2.0% | 2.6% |
| Anti TB | 19 | 2.7% | 3.5% |
| B-blockers | 16 | 2.3% | 2.9% |
| Diuretics | 19 | 2.7% | 3.5% |
| ACE inhibitors | 13 | 1.9% | 2.4% |
| CCB | 10 | 1.4% | 1.8% |
| Hypoglycemic agents | 25 | 3.6% | 4.6% |
| Analgesics (opioids and NSAIDS) | 45 | 6.5% | 8.3% |
| Steroids | 43 | 6.2% | 7.9% |
| Anticoagulants + antiplatelets | 24 | 3.4% | 4.4% |
| PPIs and acid suppressants | 20 | 2.9% | 3.7% |
| Antidepressants | 8 | 1.1% | 1.5% |
| Chemotherapy | 13 | 1.9% | 2.4% |
| Vitamins and supplements | 20 | 2.9% | 3.7% |
| Others group of Medications | 86 | 12.3% | 15.8% |
|
|
|
|
|
| Other than drug related Queries | 153 | 22.0% | |
|
|
|
|
TB- Tuberculosis, B-Blocker -Beta blocker, CCB- Calcium Channel Blockers.
NSAIDS- Non-Steroidal Anti-Inflammatory Drugs.
Reference category and specific drug information resources consulted to respond drug related queries at GUSH DIC, 2018 (N = 697).
| Reference category | Type of references used to reply queries | Frequency | Percentage (%) |
|---|---|---|---|
Tertiary Resources (n = 575, 82.5%) | Leaflet/package inserts | 4 | 0.57% |
| Good man and Gilman’s pharmacology, 12th edition | 7 | 1% | |
| Katzung pharmacology, 10th edition | 10 | 1.43% | |
| Nelson text book of pediatrics, 19th edition | 10 | 1.43% | |
| Standard treatment guideline of Ethiopia, 2014 edition | 11 | 1.57% | |
| Harrison Principle of Internal medicine, 19th edition | 20 | 2.87% | |
| Kodak -Kimble & young’s applied therapeutics, 10th edition | 30 | 4.3% | |
| Dipiro Pathophysiologic approach of Pharmacotherapy, 8th edition | 33 | 4.73% | |
| Unspecified Internet sites | 82 | 11.76% | |
| Medscape | 84 | 12.05% | |
| Up-to-date version 21.2 | 284 | 40.7% | |
| Primary resources (n = 24, 3.4%) | Original articles | 24 | 3.4% |
| Secondary resource (n = 5, 0.7%) | PubMed | 5 | 0.7% |
| Peer review and Asking | 27 | 3.9% | |
| Reference specifically not mentioned | 66 | 9.5% | |
| Total | 697 | 100% |
Binary logistic regression test (crude odds ratio) for qualification of the requester predicted type of question asked either Patient specific and general type questions.
| Question Type | B | S.E. | Wald | df | Sig. | Exp(B) | 95% CI. for EXP(B) | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Patient specific (n = 370) | General (n = 327) | Lower | Upper | |||||||
|
| 37.113 | 9 | ||||||||
| General Practitioner | 35 | 44 | 0.146 | 0.358 | 0.166 | 1 | 0.684 | 1.157 | 0.574 | 2.333 |
| Specialist Physician | 15 | 24 | −0.095 | 0.430 | 0.049 | 1 | 0.825 | 0.909 | 0.391 | 2.112 |
| Pharmacist | 199 | 117 | 0.906 | 0.300 | 9.089 | 1 | 2.474 | 1.373 | 4.458 | |
| Nurse | 26 | 45 | −0.174 | 0.371 | 0.220 | 1 | 0.639 | 0.840 | 0.406 | 1.738 |
| Health officer | 18 | 29 | −0.102 | 0.408 | 0.063 | 1 | 0.902 | 0.903 | 0.406 | 2.010 |
| Patient | 17 | 6 | 1.416 | 0.550 | 6.636 | 1 | 4.121 | 1.403 | 12.105 | |
| Caregiver | 5 | 4 | 0.598 | 0.726 | 0.679 | 1 | 0.410 | 1.818 | 0.438 | 7.540 |
| Intern | 30 | 25 | 0.557 | 0.387 | 2.068 | 1 | 0.150 | 1.745 | 0.817 | 3.729 |
| druggist | 3 | 1 | 1.473 | 1.187 | 1.539 | 1 | 0.215 | 4.364 | 0.426 | 44.731 |
| Constant | 22 | 32 | −0.375 | 0.277 | 1.830 | 1 | 0.176 | 0.687 | ||
CI – Confidence Interval.