Literature DB >> 31802915

An Evaluation Of Antibiotics Prescribing Patterns In The Emergency Department Of A Tertiary Care Hospital In Saudi Arabia.

Menyfah Q Alanazi1,2,3, Mahmoud Salam2,3,4, Fulwah Y Alqahtani5, Anwar E Ahmed2,3, Abdullah Q Alenaze6, Majed Al-Jeraisy2,3,7, Majed Al Salamah8, Fadilah S Aleanizy5, Daham Al Daham2,3, Saad Al Obaidy7, Fatma Al-Shareef9, Abdulaziz H Alsaggabi1, Mohammed H Al-Assiri2,3.   

Abstract

BACKGROUND: Antibiotic prescriptions at emergency departments (ED) could be a primary contributing factor to the overuse of antimicrobial agents and subsequently antimicrobial resistance. The aim of this study was to describe the pattern of antibiotic prescriptions at an emergency department of a tertiary care hospital in Saudi Arabia.
METHODS: A cross-sectional study, based on a review of antibiotic prescriptions was conducted. All cases who visited the emergency department over a three-month period with a complaint of infection were analyzed in terms of patient characteristics (age, sex, infection type, and number of visits) and prescription characteristics (antibiotic category, spectrum, course and costs). The World Health Organization and International Network of Rational Use of Drugs prescribing indicators were presented. Descriptive and analytic statistics were applied.
RESULTS: A total of 36,069 ED visits were recorded during the study period, of which 45,770 drug prescriptions were prescribed, including 6,354 antibiotics. The average number of drugs per encounter was 1.26, while the percentage of encounters with a prescribed antibiotic was 17.6%. Among antibiotic prescriptions, the percentage of encounters with injection antibiotics was 15.2%. Almost 77% of antibiotics were prescribed by their generic names, and the percentage of antibiotics prescribed from the essential list was 100%.
CONCLUSION: The average number of drugs per encounter in general and antibiotics per encounter in specific at this setting was lower than the standard value. However, the percentage of antibiotics prescribed by its generic name was less than optimal.
© 2019 Alanazi et al.

Entities:  

Keywords:  antibiotic; emergency; errors; predictors; prescription; prevalence

Year:  2019        PMID: 31802915      PMCID: PMC6801487          DOI: 10.2147/IDR.S211673

Source DB:  PubMed          Journal:  Infect Drug Resist        ISSN: 1178-6973            Impact factor:   4.003


Background

Antibiotics are among the most commonly prescribed medications in emergency departments (ED).1 Recently, an uncontrolled rise in infections caused by antimicrobial-resistant pathogens has been reported, resulting in an increase in morbidity, mortality, and healthcare costs.2 Therefore, there has been a growing worldwide concern with regards to the clinical and economic impact of antimicrobial resistance. Prevention of inappropriate antimicrobial usage is considered to be the most important preventable cause of drug resistance in both hospital and community settings.3–7 EDs play an important role in delivering health services, yet over usage of antibiotics at EDs is a big concern in clinical practice.8 Almost half of ED visits require antibiotic prescriptions,9 most of which are not compliant with evidence-based guidelines10,11 or witness an over usage of broad-spectrum antibiotics.12,13 In addition, numerous ED visits result in adverse reactions associated with systemic usage of antibiotics.14 Unfortunately, there is a limited insight into the antibiotic prescription patterns at EDs in Saudi Arabia. Reports stated that 4.4% of the Saudi Arabian population have visited its healthcare facilities as outpatients, and 11.5% were admitted in 2014.15 A review of the literature revealed that only three studies have addressed antibiotic-prescribing patterns and its appropriateness at EDs in Saudi Arabia.16–18 One of these studies that was conducted in Central Saudi Arabia investigated the antibiotic prescriptions at a pediatric emergency setting and showed that 18.5% of prescriptions were antibiotics.16 A second study concluded that the duration of treatment was the most common inappropriate pattern in antibiotic prescriptions.17 In Western Saudi Arabia, almost half (47%) of ED prescriptions contained at least one systemic antibiotic.18 The aim of this study was to describe the pattern of antibiotic prescriptions at an emergency department of a tertiary care hospital in Saudi Arabia.

Methods

Study Design And Setting

This was a cross-sectional study, during which antibiotic prescriptions were revised over a period of 3 months at the ED of a major tertiary care facility in Riyadh, Saudi Arabia. King Abdulaziz Medical City (KAMC) is a distinguished Joint Commission International (JCI) accredited health care provider established since 1983 and under the umbrella of the Ministry of National Guard Health Affairs (MNG-HA). It has a total bed capacity exceeding 1,200 beds among which 90 beds are allocated within two adult and pediatric emergency wards. A team of more than 80 emergency consultants (specialists,  associates, and assistants), staff physicians, fellows, and residents provide services at this facility.

Study Population And Sampling Technique

Consecutive sampling was done by screening all visits to the targeted ED during a 3-month period. Eligible participants were of all age groups (6 months to 65 years), registered at KAMC with a medical record number and received at least one antibiotic during each visit or encounter. ATB prescriptions that were either incomplete (e.g., missing ATB dosage or frequency) or had illegible handwriting were dropped out. Infants with weight less than 5 kg were excluded. At KAMC, prescriptions are generally cashed from an in-hospital pharmacy free of charge. This study was approved by the Institution Review Board of the Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia (RR08/005).

Methods Of Measurement

Three certified and well-trained research coordinators collected the data. Training was performed by the study investigators on how to access, screen, and select eligible study cases from the medical records and document the findings on a controlled research form. The antibiotic prescriptions were written by medical residents, fellows, and consultants at the ED. All prescriptions were revised by the pharmacy staff through a computerized pharmacy data system (Legacy). The pattern of antibiotic prescription for each case was evaluated by two certified pharmacists with extensive research and clinical experience. Cases that lacked consensus during the evaluation were dropped out. The data collection form was composed of patient characteristics (age, sex, number of visits, type of infection, cultures obtained) and prescription characteristics (antibiotic category, spectrum, number of courses and associated costs). The World Health Organization (WHO) and International Network of Rational Use of Drugs (INRUD) antibiotic-prescribing indicators at EDs were used in this study.19 The average number of drugs per encounter was calculated by dividing the total number of drugs prescribed at the ED over the total number of visits during the study period. The percentage of encounters with a prescribed antibiotic was calculated by dividing the number of prescribed antibiotics over the total number of ED visits multiplied by 100. The percentage of encounters with injection antibiotics was calculated by dividing the number of injection antibiotics over the total number of prescribed antibiotics multiplied by 100. The number of antibiotic prescriptions by generic name was divided over the total number of antibiotics to determine the percentage of antibiotics prescribed by generic name. As per the WHO Essential Medicine List for optimal use,20 the percentage of antibiotics prescribed from the essential list (classified as Access or Watch) was divided over the total number of prescriptions multiplied by 100.

Statistical Analysis

Data were analyzed using SPSS (version 25.0, IBM SPSS Inc., NY, USA). Descriptive statistics such as mean ± standard deviation (mean ± SD) were used to describe the quantitative variables. Frequencies (n) and percentages (%) were used to describe categorical variables. Bar charts were generated to display the most common types and classes of antibiotics prescribed according to age groups and common diseases treated with antibiotics. Pearson’s chi-squared tests were used to assess for age group differences across various exposures. Independent two-sample Mann–Whitney U-test was used to assess the difference in the cost of the antibiotic prescription according to age groups. A P-value ≤0.05 was considered to indicate statistical significance.

Results

During the study period, there were 36,069 ED visits, resulting in 45,770 drug prescriptions, of which 6,354 were antibiotic prescriptions. The prevalence of prescribed oral antibiotics was 13.9%, whereas others (86.1%) were injections. Of the antibiotic prescriptions, 2,335 (36.7%) were prescribed for children (<18 years), while 4,019 (63.3%) were prescribed for adults. Significantly, more oral antibiotics (26.5%) were prescribed for adults than children (P = 0.001). Similar sex distribution was observed. Patients were treated mainly for upper respiratory tract infections (URTIs) and urinary tract infections (UTIs) (31.8% and 22.5%, respectively). Other types of infections were observed at lower rates, including otitis media (OM) (10.2%), and skin infections (6.3%). Cultures were obtained from 18.6% of patients only. The most frequent cultures were for samples of urine (51.2%), blood (21.1%), and throat swabs (11.3%). Only 27.9% of patients had positive cultures. The average cost of antibiotics prescribed was equivalent to US$17.8, with maximum costs up to $139.2 (Table 1).
Table 1

Characteristics Of Patients Who Received Antibiotics

Characteristicsn%
Females325751.3
Children (<18 years)233536.7
DiagnosisUpper RTI202031.8
UTI143222.5
OM65110.2
Lower RTI116118.3
Skin infection3966.3
Others69410.9
Culture availableYes118318.6
Culture resultsNegative85672.1
Positive33227.9
If culture available, type of cultureBlood25121.1
Urine60851.2
Throat13411.3
Others19516.4
Number of visits to EDOne353255.6
Two146223.0
Three or more136021.4
Antibiotic categoryCephalosporin192430.3
Macrolide132720.9
Penicillin225935.5
Quinolone64610.2
Others1983.1
Antibiotic spectrumBroad489477.0
Narrow146023.0
Antibiotic coursesOne course494188.5
Two courses5419.7
Three courses or more1001.8
Cost (US$) (range 0.82–139.2), mean ± SD17.8±11.6

Abbreviations: ED, emergency department; RTI, respiratory tract infection; UTI, urinary tract infection; SD, standard division; OM, otitis media.

Characteristics Of Patients Who Received Antibiotics Abbreviations: ED, emergency department; RTI, respiratory tract infection; UTI, urinary tract infection; SD, standard division; OM, otitis media. Male children were more likely to be prescribed an antibiotic than male adults (56.9% vs 44.0%), while female adults were more likely to be prescribed an antibiotic than female children (56% vs 43.1%). The frequency of RTIs was significantly higher in children (42.9%) than adults (25.4%) (P = 0.001) and UTIs were observed in 29% of the adults and 11.5% of the pediatric patients. A significantly higher proportion of adult patients had positive culture results compared with the pediatric patients (30.2% vs 24.9%). The number of antibiotic courses was significantly associated with age groups (P = 0.001). A significantly higher proportion of children received a single course of antibiotics compared with the adult patients (90.7% vs 87.3%). In contrast, a significantly higher proportion of adult patients received two courses of antibiotics compared with children (10.4% vs 8.3%). The price of prescribed antibiotics was significantly higher among children compared to adults ($19.9 ± 12.5 vs $14.1±8.7, P = 0.001) (Table 2).
Table 2

Association Between Age Groups And Other Sample Characteristics

Children2335 (36.7%)Adults4019 (63.3%)P-value
n%n%
SexMale132856.9176944.00.001*
Female100743.1225056.0
DiagnosisUpper RTI100142.9101925.40.001*
UTI26811.5116429.0
OM43218.52195.4
Lower RTI42318.173818.4
Skin infection1014.32957.3
Others1104.758414.5
VisitOne122252.4231057.50.001*
Two57524.688722.1
Three or more53823.082220.4
Type of cultureBlood13827.511316.50.001*
Urine16232.344665.0
Throat11723.3172.5
Others8516.911016.0
Culture resultsNegative37775.147969.80.045*
Positive12524.920730.2
Spectrum of antibioticBroad172774.0316778.80.001*
Narrow60826.085221.2
Antibiotic categoryCephalosporin77933.3114528.50.001*
Macrolide43218.689522.3
Penicillin108146.4117829.3
Quinolone150.563115.7
Others281.21704.2
Antibiotic coursesOne191890.7302987.30.001*
Two1768.336210.4
Three or more211.0792.3
Cost (US$), mean ± SD19.9±12.514.1±8.70.001#

Notes: *Pearson Chi-squared test significant at α = 0.05. #Mann–Whitney U-test significant at α = 0.05.

Abbreviations: RTI, respiratory tract infection; UTI, urinary tract infection; SD, standard division; OM, otitis media.

Association Between Age Groups And Other Sample Characteristics Notes: *Pearson Chi-squared test significant at α = 0.05. #Mann–Whitney U-test significant at α = 0.05. Abbreviations: RTI, respiratory tract infection; UTI, urinary tract infection; SD, standard division; OM, otitis media. As shown in Figure 1, Augmentin was the most frequently prescribed antibiotic (22.1%; 25.3% in children vs 20.2% in adults), followed by cefuroxime (16.9%; 3.5% in children vs 24.8% in adults), and amoxicillin (13.1%; 20.7% in children vs 8.7% in adults). Penicillin was the most frequently prescribed class of antibiotics (35.5%; 46.3% in children vs 29.3% in adults), followed by cephalosporin (30.3%; 33.4% in children vs 28.5% in adults), and macrolides (20.9%; 18.5% in children vs 22.3% in adults). Figure 2 shows that the most common classes of antibiotics prescribed to URTI cases were penicillin (45%), including amoxicillin (24.1%) and Augmentin (21%), followed by macrolides (35.1%), including azithromycin (17.1%) and clarithromycin (18%), and cephalosporin (20%), including cefuroxime (10%), cefprozil (8.1%), and cephalexin (1.6%). The most common classes of antibiotics prescribed for UTI cases were cephalosporin (39.2%; mainly cefuroxime 33%), followed by penicillin (26.5%), including amoxicillin (9%) and Augmentin (17.4%), and quinolones (23%; mainly norfloxacillin 21%). In OM, the most common classes of antibiotics prescribed were penicillin (62%), including amoxicillin (16%) and Augmentin (46%), followed by cephalosporin (30%; mainly cefprozil 25%).
Figure 1

The most frequently prescribed antibiotics by age group.

Figure 2

The most frequently prescribed classes of antibiotics by disease.

The most frequently prescribed antibiotics by age group. The most frequently prescribed classes of antibiotics by disease. The average number of drugs per encounter was 1.26, while the percentage of encounters with a prescribed antibiotic was 17.6%. Among antibiotic prescriptions, the percentage of encounters with injection antibiotics was 15.2%. Almost 77% of antibiotics were prescribed by their generic names, and the percentage of antibiotics prescribed from the essential list was 100%. The indicators were tabulated and compared to the standard values of WHO/INRUD prescribing indicators at EDs in Table 3.
Table 3

WHO/INRUD Prescribing Indicators At EDs

IndicatorValue (SD)Standard Value
Average number of drugs per encounter (n=45,770)1.261.6–1.8
Percentage of encounters with a prescribed antibiotic (n=6354)17.6 (0.4)20.0–26.8%
Percentage of encounters with an injection antibiotics (n=5470)15.2 (0.4)13.4–24.1%
Percentage of antibiotic prescribed by generic name (n=4881)77 (1.1)100%
Percentage of antibiotic prescribed from the essential lista (n=6354)100100%

Note: aAccess and Watch classified antibiotics.

Abbreviations: WHO, World Health Organization; INURD, International Network of Rational Use of Drugs.

WHO/INRUD Prescribing Indicators At EDs Note: aAccess and Watch classified antibiotics. Abbreviations: WHO, World Health Organization; INURD, International Network of Rational Use of Drugs.

Discussion

The prescribing indicators at this setting were compared to the standard benchmark as well as figures published in the literature. The average number of drugs per encounter in general and antibiotics in specific at this setting was lower than the standard values. This can be attributed to the general Saudi Arabian population’s prevalence of infections compared to other Asian countries. For instance, The Saudi Commission for Health Specialties in Saudi Arabia has stated that lower respiratory infections ranked 5th on the top 10 list for mortality.21 In countries like Yemen, Mongolia, Uzbekistan, Philippines, Pakistan and India, lower respiratory infections, as well as diarrheal diseases and tuberculosis, have been reported as the worst-ranked countries in Asia in terms of these infections.22 This justifies why the percentage of antibiotic encounters was less in Saudi Arabia compared to others. The percentage of encounters with a prescribed antibiotic could be influenced by some factors. For instance, these figures might be inflated due to the lack of compliance of ED physicians with the standards of practice, or deficient hospital resources to confirm infections by ordering cultures.17 In Saudi Arabia, the health care industry is highly supported and funded by the government, courtesy to the high economic revenues generated by the oil industry. Therefore, ED physicians at this setting were probably more conservative in antibiotic selection. They were capable of ordering laboratory cultures and confirming any suspected microbe prior to antibiotic prescriptions. However, the percentage of antibiotics prescribed by their generic name was less than optimal, compared to other studies.19,23 In this setting, the most common antibiotic used by its brand name was Augmentin. WHO recommend prescribing drugs by their generic name (rational prescribing) since it has been shown to be cost-effective and provides flexibility in its purchase from drug stores. It is noteworthy that this policy is applicable to both the public and private healthcare settings, yet at this setting, this lack of compliance had trivial effects as antibiotics are cashed from the in-hospital pharmacy and monitored by licensed pharmacists, free of charge to the patients. Antibiotics accounted for 17.6% of all prescribed medications in this study. This figure was found to be rational, as it falls below the WHO index that stated antibiotic prescriptions range between 20.0% and 26.8% of the total prescriptions in EDs.24 The ED at this facility is continuously implementing updated policies and guidelines to monitor the usage of antibiotics. A variety of training programs are performed annually to educate clinicians on the proper usage of antibiotics. It has been reported that staff education is the most useful option in improving such outcomes.25 These initiatives are more likely to contribute to the rational use of oral antibiotics recorded at this setting, although further studies are required to explore the impact of these guidelines and training programs. Augmentin was the most common antibiotic prescribed at this ED which was not consistent with a Saudi Arabian study reported by Oqal et al.18 In this setting, the most frequently prescribed antibiotics were penicillin, cephalosporin, and macrolides, which was comparable to findings reported by previous local studies.16,18 Similar to previous studies,18,26–30 this study showed that URTIs and UTIs were the leading types of infection for which antibiotics are prescribed in EDs. For patients who complained of URTIs, broad-spectrum antibiotics, predominantly Augmentin and macrolides were prescribed more often than narrow-spectrum antibiotics. This pattern of prescription was similar to previous reports that cautioned about the phenomenon of Augmentin18,31 or macrolides27,32 over-prescription in the treatment of URTIs. Apparently, such an increase in the selection of broad-spectrum antibiotics by ED clinicians is expected because of uncertainty regarding the patients’ diagnoses.33 The present study has some limitations. First, the study was conducted in EDs only; thus, our findings may not be generalized to other types of healthcare settings or populations. Second, the study period was short (3 months) and retrospective in nature; therefore, some prescriptions might have been missed. Authors were unable to collect other important information as our study was based mainly on chart review. Regardless of these limitations, this study provides important information on the prescribing pattern in a major healthcare facility in Saudi Arabia.

Conclusions

This study described the pattern of antibiotic prescriptions at an ED. Evaluation of antibiotic prescription patterns is crucial to improve the rational usage of antimicrobial agents. The pattern of antibiotic prescription at this setting appears to be rational, as it fell within the standard WHO prescribing indexes. It is noteworthy that the variations in prescription indicators across countries might be attributed to the differences in the spread of infections and availability of resources to conduct confirmatory laboratory tests. Continuous surveillance on the implementation of guidelines is important to improve prescribing practices and reduce the misuse of antibiotics.
  25 in total

1.  Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship.

Authors:  Timothy H Dellit; Robert C Owens; John E McGowan; Dale N Gerding; Robert A Weinstein; John P Burke; W Charles Huskins; David L Paterson; Neil O Fishman; Christopher F Carpenter; P J Brennan; Marianne Billeter; Thomas M Hooton
Journal:  Clin Infect Dis       Date:  2006-12-13       Impact factor: 9.079

2.  Antibiotic resistance-the need for global solutions.

Authors:  Ramanan Laxminarayan; Adriano Duse; Chand Wattal; Anita K M Zaidi; Heiman F L Wertheim; Nithima Sumpradit; Erika Vlieghe; Gabriel Levy Hara; Ian M Gould; Herman Goossens; Christina Greko; Anthony D So; Maryam Bigdeli; Göran Tomson; Will Woodhouse; Eva Ombaka; Arturo Quizhpe Peralta; Farah Naz Qamar; Fatima Mir; Sam Kariuki; Zulfiqar A Bhutta; Anthony Coates; Richard Bergstrom; Gerard D Wright; Eric D Brown; Otto Cars
Journal:  Lancet Infect Dis       Date:  2013-11-17       Impact factor: 25.071

3.  Practice patterns and management strategies for purulent skin and soft-tissue infections in an urban academic ED.

Authors:  Larissa May; Katherine Harter; Kabir Yadav; Ryan Strauss; Jameel Abualenain; Amy Keim; Gillian Schmitz
Journal:  Am J Emerg Med       Date:  2011-01-28       Impact factor: 2.469

4.  Understanding variation in quality of antibiotic use for community-acquired pneumonia: effect of patient, professional and hospital factors.

Authors:  Jeroen A Schouten; Marlies E Hulscher; Bart-Jan Kullberg; Anton Cox; Inge C Gyssens; Jos W van der Meer; Richard P Grol
Journal:  J Antimicrob Chemother       Date:  2005-07-27       Impact factor: 5.790

5.  Antibiotic prescribing for adults in ambulatory care in the USA, 2007-09.

Authors:  Daniel J Shapiro; Lauri A Hicks; Andrew T Pavia; Adam L Hersh
Journal:  J Antimicrob Chemother       Date:  2013-07-25       Impact factor: 5.790

6.  Antibiotic Prescribing Patterns in Outpatient Emergency Clinics at Queen Rania Al Abdullah II Children's Hospital, Jordan, 2013.

Authors:  Sahar I Al-Niemat; Tareq M Aljbouri; Lana S Goussous; Rania A Efaishat; Rehab K Salah
Journal:  Oman Med J       Date:  2014-07

7.  Classifying antibiotics in the WHO Essential Medicines List for optimal use-be AWaRe.

Authors:  Mike Sharland; Celine Pulcini; Stephan Harbarth; Mei Zeng; Sumanth Gandra; Shrey Mathur; Nicola Magrini
Journal:  Lancet Infect Dis       Date:  2017-12-20       Impact factor: 25.071

8.  WHO/INRUD prescribing indicators and prescribing trends of antibiotics in the Accident and Emergency Department of Bahawal Victoria Hospital, Pakistan.

Authors:  Muhammad Atif; Muhammad Azeem; Muhammad Rehan Sarwar; Samia Shahid; Sidra Javaid; Huria Ikram; Uzma Baig; Shane Scahill
Journal:  Springerplus       Date:  2016-11-08

9.  An evaluation of E. coli in urinary tract infection in emergency department at KAMC in Riyadh, Saudi Arabia: retrospective study.

Authors:  Menyfah Q Alanazi; Fulwah Y Alqahtani; Fadilah S Aleanizy
Journal:  Ann Clin Microbiol Antimicrob       Date:  2018-02-09       Impact factor: 3.944

10.  An evaluation of community-acquired urinary tract infection and appropriateness of treatment in an emergency department in Saudi Arabia.

Authors:  Menyfah Q Alanazi
Journal:  Ther Clin Risk Manag       Date:  2018-12-05       Impact factor: 2.423

View more
  6 in total

1.  Evaluation of Health-Related Quality of Life in Women with Community-Acquired Urinary Tract Infections Using the EQ-5D-3L in Saudi Arabia.

Authors:  Menyfah Q Alanazi
Journal:  Patient Prefer Adherence       Date:  2020-12-04       Impact factor: 2.711

2.  Evaluation of Adult Outpatient Antibiotics Use at Jimma Medical Center (with Defined Daily Doses for Usage Metrics).

Authors:  Tsegaye Melaku; Mulatu Gashaw; Legese Chelkeba; Melkamu Berhane; Sisay Bekele; Gemechu Lemi; Tekle Wakjira; Getnet Tesfaw; Zeleke Mekonnen; Solomon Ali; Arne Kroidl; Andreas Wieser; Guenter Froeschl; Esayas Kebede Gudina
Journal:  Infect Drug Resist       Date:  2021-04-28       Impact factor: 4.003

3.  Characteristics of patients infected with Clostridioides difficile at a Saudi Tertiary Academic Medical Center and assessment of antibiotic duration.

Authors:  Khadijah M Alammari; Abrar K Thabit
Journal:  Gut Pathog       Date:  2021-02-17       Impact factor: 4.181

4.  Clinical Efficacy and Cost Analysis of Antibiotics for Treatment of Uncomplicated Urinary Tract Infections in the Emergency Department of a Tertiary Hospital in Saudi Arabia.

Authors:  Menyfah Q Alanazi
Journal:  Ther Clin Risk Manag       Date:  2021-11-21       Impact factor: 2.423

5.  Management of acute diarrhea in the emergency department of a tertiary care university medical center.

Authors:  Suha J Jabak; Lamees Kawam; Ali El Mokahal; Ala I Sharara
Journal:  J Int Med Res       Date:  2022-08       Impact factor: 1.573

6.  The magnitude of prescribing medicines by brand names in a tertiary hospital, Mwanza, Tanzania.

Authors:  Stanley Mwita; Brigitte Mchau; Winfrida Minja; Deogratias Katabalo; Kayo Hamasaki; Karol Marwa
Journal:  J Med Access       Date:  2022-05-15
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.