Drug prescribing and dispensing practices in regional and national referral hospitals of Eritrea: Evaluation with WHO/INRUD core drug use indicators.

Rational use of medicine (RUM) for all medical conditions is crucial in attaining quality of healthcare and medical care for patients and the community as a whole. However, the actual medicine use pattern is not consistent with that of the World Health Organization (WHO) guideline and is often irrational in many healthcare setting, particularly in developing countries. Thus, the aim of the study was to evaluate rational medicine use based on WHO/International Network of Rational Use of Drugs (INRUD) core drug use indicators in Eritrean National and Regional Referral hospitals. A descriptive and cross-sectional approach was used to conduct the study. A sample of 4800 (600 from each hospital) outpatient prescriptions from all disciplines were systematically reviewed to assess the prescribing indicators. A total of 1600 (200 from each hospital) randomly selected patients were observed for patient indicators and all pharmacy personnel were interviewed to obtain the required information for facility-specific indicators. Data were collected using retrospective and prospective structured observational checklist between September and January, 2018. Descriptive statistics, Welch's robust test of means and Duncan's post hoc test were performed using IBM SPSS (version 22). The average number of medicines per prescription was 1.78 (SD = 0.79). Prescriptions that contained antibiotic and injectable were 54.50% and 6.60%, respectively. Besides, the percentage of medicines prescribed by generic name and from an essential medicine list (EML) was 98.86% and 94.73%, respectively. The overall average consultation and dispensing time were 5.46 minutes (SD = 3.86) and 36.49 seconds (SD = 46.83), respectively. Moreover, 87.32% of the prescribed medicines were actually dispensed. Only 68.24% of prescriptions were adequately labelled and 78.85% patients knew about the dosage of the medicine(s) in their prescriptions. More than half (66.7%) of the key medicines were available in stock. All the hospitals used the national medicine list but none of them had their own medicine list or guideline. In conclusion, majority of WHO stated core drug use indicators were not fulfilled by the eight hospitals. The results of this study suggest that a mix of policies needs to be implemented to make medicines more accessible and used in a more rational way.

Introduction

Rational use of medicine (RUM) is an essential element in achieving quality of health care for patients and the community. The WHO defines rational use of medicine as providing the right medicine, for the right patient at the right dose, for the right duration and at the lowest possible cost to them and their community [1]. WHO estimates that more than half of all medicines are prescribed, dispensed or sold inappropriately, and that half of all patients fail to take them properly. The overuse, underuse or misuse of medicines results in wastage of scarce resources and widespread health hazards [2].

Irrational use of medicines is a global burden. A number of factors that lead to an irrational use of medicines are polypharmacy, inadequate dosage of antibiotics, use of antibiotics for viral infections, over-use of injections when oral medication can be more suitable [3, 4]. Most physicians would vouch for having observed this in their day-to-day practice but there is no dearth of hard evidence to reinforce this impression.

WHO in collaboration with the International Network of Rational Use of Drugs (INRUD) has developed a manual that defines a limited number of objective measures that can describe the medicine situation in a country, region or individual health facilities. Such measures or indicators will allow health planners, managers and researchers to make basic comparisons between situations in different areas or at different times. Drug use indicators can be used to identify general prescribing and quality of care problems at primary health care facilities thereby enhancing the rational use of medicines.

Eritrea, a developing country in the Horn of Africa, encountered with the challenges of irrational use of medicines in parallel with the rest of the world. Despite the commitment towards ensuring RUM is highlighted in the national drug policy of the Ministry of Health, numerous studies reported that irrational use of medicines still exists in the country [5-7]. This study assessed the rational use of medicines in all regional and national referral hospitals of the country.

Materials and methods

Study design and setting

A facility-based cross-sectional study with a quantitative approach was conducted in all the regional (zonal) and two national referral hospitals of Eritrea. The study was conducted from September 1, 2017 to January 31, 2018. Retrospective cross-sectional study was used to evaluate prescribing indicators while prospective cross-sectional study design was employed for patient care and facility indicators.

The provision of health services in Eritrea has been provided through a three tier or level system which include primary, secondary and tertiary level of services. The primary level services includes community-based health services, health station and health center. The secondary level includes a regional (zonal) referral hospital and a second contact hospital within a region (zoba). Moreover, a tertiary level comprises of a national referral hospital. Eritrea has a total of six regions (zobas) namely: Anseba, Debub, Debubawi Keih Bahri, Gash-Barka, Maekel, and Semenawi Keih Bahri. Each region (zoba) has its own referral hospital. Moreover, Eritrea has also four national referral hospitals. This study was conducted in two national referral hospitals namely: Orotta and Halibet and six regional referral hospitals: Barentu (Gash-Barka region), Mendefera (Debub region), Ghindae (Semenawi Keih Bahri region), Assab (Debubawi Keih Bahri region), Keren (Anseba region) and Hazhaz (Maekel region).

Study population

All outpatient prescriptions dispensed from January 1, 2017 to December 31, 2017 (prescribing indicators); patient attendants and their prescriptions in the outpatient departments (OPDs) of the selected hospitals from September 1 to November 30, 2018 (patient care indicators) and medicines under Eritrean essential medicine list (EML) of 2015 were included. Nevertheless, prescriptions that contain any item apart from a pharmaceutical and patient attendants outside the normal employment hours were not included in the study.

Sampling

As per the WHO recommendation, 600 prescribing encounters were taken from each hospital to assess the prescribing practices. As a result, a total of 4,800 prescriptions were investigated in the study. To minimize the sampling bias (seasonal alterations or supply cycle of medicines), the encounters per year were uniformly divided into four quarters and 150 prescriptions were randomly selected from each quarter, irrespective of acute or chronic illnesses, including a mixture of health conditions and a range of patient ages. Then, systematic random sampling was used once sampling frame had been developed by arranging the study population in chronological order of prescription.

Moreover, based on WHO criteria, at least 100 outpatient attendants (encounters) were recommended in individual health facility [8]. Therefore, to get a more reliable outcome 200 patients were assessed in each hospital after spreading them throughout the clinic hours [9]. The patient attendants with their prescriptions in OPDs were sampled by convenient sampling technique prospectively.

As for the assessment of the health facility indicators, key medicines were selected from each hospital as per WHO recommendation which is a minimum of 15 essential medicines in each health facility [8]. These key medicines being used for the management of the leading diseases of the respective hospitals were selected by communicating with prescribers and dispensers and reviewing national guideline [9]. All available pharmacy personnel were invited to participate in the study and the consented participants were interviewed to obtain the required information [8].

Data collection tools and approach

Data were collected using structured checklists for prescribing, patient care and health facility indicators. Data regarding prescribing indicators were taken from sampled prescription records retrospectively and filled in structured checklist accordingly by careful observation.

Patient prescriptions were used as a reference to check the patient knowledge on how to take the correct dosage of a medicine. A stop watch was used to determine the health care providers-patient interaction time (consultation and dispensing time). Data about patient care indicators were taken from patient attendants and their prescriptions in OPD during the period of data collection prospectively and were recorded in an observational checklist. Among patient care indicators, data of patient knowledge on how they take a correct dosage were collected through face to face interview and recorded as 1 or 0 for each patient. In addition, the availability of key/essential medicines, were evaluated in OPD, and was recorded in the facility indicator form.

Variable measurement

To evaluate the rational medicine use comprehensively, Index of Rational Drug Prescribing (IRDP), Index of Rational Patient- Care Drug Use (IRPCDU), and Index of Rational Facility- Specific Drug Use (IRFSDU) were developed by Zhang and Zhi for a comprehensive appraisal of medical care [4, 10]. For the calculation of non-polypharmacy, rational antibiotic use and injection safety indices, the following formula was used;

The optimal values for calculating the indices of non-polypharmacy, rational antibiotic use and injection safety were taken as 1.8, 26.8 and 24.1, respectively.

All other indices (index of generic prescribing, index of prescribing from an essential medicine list (EML), consultation time index, dispensing time index, index of medicines actually dispensed, index of labelling of medicines, index of patients’ knowledge, index of EML availability and index of key medicines availability in stock) was calculated by the following formula;

The optimal values for the calculation of indices for generic prescribing, medicine prescribed from EML, medicines actually dispensed, patient knowledge of correct doses, labelling of medicines and availability of key medicines were taken as 100. Besides, the optimal value for the calculation of indices for consultation and dispensing time were taken as 10 minutes and 90 seconds, respectively.

The Index of Rational Drug Prescribing (IRDP) was calculated for all hospitals by adding the index values of all the prescribing indicators. Similarly, the Index of Rational Patient-Care Drug Use (IRPCDU) and the Index of Rational Facility- Specific Drug Use (IRFSDU) were calculated. Based on the IRDP, IRPCDU and IRFSDU values, the hospitals were ranked from 1 to 8 within each category (rank 1 for the higher value and rank 8 for the lower value). The optimal index for all the indicators is one. As the value of the optimal index is closer to one, the more rational the medicine use indicator.

Finally, the Index of Rational Drug Use (IRDU) was calculated for all hospitals by adding up the total of IRDP, IRPCDU and IRFSDU. Moreover, a rank was assigned to each hospital based on the IRDU value.

The country performance indicator for drug prescribing, patient-care and facility-specific was calculated using the same approach with the above-mentioned formulas. For instance, the country performance indicator of generic prescribing was measured by dividing the observed value by the optimal value (100%). The observed value was taken as the average value of the generic prescribing across the eight hospitals. Table 1 displays the WHO optimal values of the core drug use indicators

Table 1

Core drug use indicators and their optimal values.

Core drug use indicators	WHO Optimal values [8, 11]	Optimal Index [10]
Prescribing Indicators
Average number of medicines prescribed per patient encounter	1.6–1.8	1
Percentage of medicines prescribed by generic name	100	1
Percentage of encounters with an antibiotic prescribed	20.0–26.8	1
Percentage of encounters with an injection prescribed	13.4–24.1	1
Percentage of medicines prescribed from essential medicines list or formulary	100	1
Patient-Care Indicators
Average consultation time (minutes)	≥10	1
Average dispensing time (seconds)	≥90	1
Percentage of medicines actually dispensed	100	1
Percentage of patients with knowledge of correct doses	100	1
Percentage of drugs adequately labelled	100	1
Facility-Specific Indicators
Availability of essential medicines list or formulary to practitioners	100	1
Availability of key essential medicines	100	1

Data quality

To ensure data consistency in results all data collectors were trained together and then allowed to practice together in Orotta National Referral Hospital and Hazhaz Regional Referral Hospital. This step provides an opportunity to identify and solve unforeseen problems. It also allowed to make realistic estimate of the time required for collecting data at each site.

Statistical analysis

Data entry and analyses were conducted using SPSS (Version 22.0). Mean (SD) or median (IQR) was used to make descriptive analysis for the continuous variables, while frequency (percent) was used for the qualitative ones. Welch’s robust test of means was used to assess the possible differences in mean consultation time and mean dispensing time across the health facilities. Subsequently, grouping of the health facilities that have similar mean consultation time and mean dispensing time was also performed using Duncan’s post-hoc analysis. IRDP, IRPCDU, IRFSDU, and IRDU indices were also computed appropriately and then ranks assigned to make comparisons among the health facilities. The statistical significant was determined by a p-value less than 0.05.

Ethical consideration

A formal written ethical approval form was obtained from Research Ethical Clearance Committee of Asmara College of Health Sciences with a reference number of 019/07/18 and Ministry of Health research ethics and protocol review committee with a reference number of 22/08/18.

Participant information sheet and a written informed consent form were filled by trained data collectors after explaining the purpose of the study to the individual respondents. Confidentiality was assured for all information collected.

Results

Prescribing indicators

A total of 8555 drugs were prescribed from the 4800 prescriptions assessed. The average number of drugs per encounter was 1.78 (SD = 0.79). The mean drugs prescribed ranged from 1.62 (SD = 0.70) in Hazhaz regional referral hospital to 2.07 (SD = 0.80) in Keren regional referral hospital. Most of the drugs were prescribed by their generic names (94.86%). The range of percentage of generic prescribing varied from a minimum of 84.01% in Ghindae regional referral hospital, to as high as 98.08 in Barentu regional referral hospital. Generally, the percentage of drugs prescribed using generic name was above 94.72% except in one hospital. Overall, one or more antibiotics was prescribed in 54.5% of the encounters (n = 2617/4800). Hazhaz regional referral hospital showed the highest percentage of prescriptions with antibiotics (63.8%) followed by Keren (58.3%), Assab (57.0%), and Barentu (56.3%). There were 318 (6.6%) prescriptions that contained at least one injectable medications. Majority of the drugs (94.73%) were prescribed from the Eritrean National List of Medicines (ENLM) [Table 2].

Table 2

Prescribing indicators vis-à-vis WHO core standards.

Prescribing indicators	Name of Health facility
	ONRH M, SD (Md, IQR)	HNRH M, SD (Md, IQR)		HRRH M, SD (Md, IQR)	GRRH M, SD (Md, IQR)	ARRH M, SD (Md, IQR)	KRRH M, SD (Md, IQR)	MRRH M, SD (Md, IQR)	BRRH M, SD (Md, IQR)	Overall M, SD (Md, IQR)	WHO standard[8, 11]
Average number of drugs per encounter	1.92, 0.98 (2,1)		1.74, 0.70 (2,1)	1.62, 0.70 (2,1)	1.65, 0.67 (2,1)	1.82, 0.87 (2,1)	2.07, 0.80 (2,1)	1.72, 0.69 (2,1)	1.73, 0.75 (2,1)	1.78, 0.79 (2,1)	1.6–1.8
Percentage of encounter with antibiotic	53		44.3	63.8	53.5	57	58.3	49.8	56.3	54.5	20–26.8
Percentage of encounter with injection	6.8		7.2	8.2	7.7	7.8	3.8	6.8	4.7	6.6	13.4–24.1
Percentage of medicines prescribed by generic	97.04		94.72	95.88	84.01	95.41	95.34	97.58	98.08	94.86	100
Percentage of medicines from essential medicine list	97.04		90.01	95.37	83.4	95.05	99.76	97.38	98.08	94.73	100

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital, M = Mean, SD = Standard Deviation, Md = Median, IQR = Interquartile range.

Patient care indicators

Median consultation time was 4 (Q1 = 2 and Q3 = 8) minutes. Welch’s robust test of means showed that there was significant difference in consultation time among the health facilities (F = 89.79, p<0.0001). Duncan’s grouping has discovered Ghindae as group 1, Hazhaz and Mendefera as group 2, Halibet and Orotta as group 3, Keren as group 4, Assab as group 5, and Barentu as group 6 [Table 3].

Table 3

Grouping of hospitals as per their homogeneity with regards to the consultation time (minutes).

Health Facility	Group							F (df1, df2)	p-value
	1	2	3	4		5	6
GRRH	2.67 min							89.79 (7, 679.49)	<0.0001
HRRH		3.47 min
MRRH		3.9 min
HNRH			5.29 min
ONRH			5.7min
KRRH				6.45 min
ARRH					7.31 min
BRRH							8.9 min
p-value	1	0.2	0.22	1	1		1

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital, F = Fisher’s exact test, df = degree of freedom.

The median dispensing time of drugs in all the health facilities was 25 (Q1 = 14, Q3 = 45) seconds. Welch’s robust test of means showed that there was significant difference in dispensing time among the health facilities (F = 27.76, p<0.0001). Duncan’s grouping has discovered Barentu, Keren, Mendefera and Ghindae as group 1, Keren, Mendefera, Ghindae, Halibet, Hahzaz and Orotta as group 2, Assab as group 3 [Table 4].

Table 4

Grouping of hospitals as per their homogeneity with regards to the dispensing time (seconds).

Health Facility	Group			F (df1, df2)	p-value
	1	2	3
BRRH	20.77s			27.76 (7, 672.54)	<0.0001
KRRH	25.55s	25.55s
MRRH	25.69s	25.69s
GRRH	27.99s	27.99s
HNRH		31.7s
HRRH		31.76s
ONRH		32.57s
ARRH			95.94s
p-value	0.11	0.14	1.00

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital, F = Fisher’s exact test, df = degree of freedom, s = seconds (dispensing time).

Majority of the drugs prescribed (87.32%, n = 2623/3004) from the eight hospitals were actually dispensed. An adequate label includes at least the name and strength of the medicine and written instructions on how to take it. The overall median percent medicines adequately labelled was found to be 68.24%. Moreover, the average percent of patients who know how to take medicines was found to be 78.88% [Table 5].

Table 5

Patient care indicators vis-à-vis WHO core standards.

Prescribing indicators	Name of Health facility
	ONRH M, SD (Md, IQR)	HNRH M, SD (Md, IQR)	HRRH M, SD (Md, IQR)	GRRH M, SD (Md, IQR)	ARRH M, SD (Md, IQR)	KRRH M, SD (Md, IQR)	MRRH M, SD (Md, IQR)	BRRH M, SD (Md, IQR)	Overall M, SD (Md, IQR)	WHO standard [8, 11]
Average Consultation Time (minutes)	5.70, 3.72 (5,5)	5.29, 3.24 (4,4)	3.47, 2.68 (3,2)	2.67, 2.17 (2,1)	7.31, 3.79 (6,4)	6.45, 3.65 (6,4.75)	3.90, 3.25 (3,3)	8.90. 3.85 (8.5)	5.46, 3.86 (4,6)	>10
Average Dispensing Time (seconds)	32.57. 25.12 (27.50,30.75)	31.70, 53.91 (15,25)	31.76, 44.27 (25,25)	27.99, 16.30 (20,20.75)	95.94, 82.59 (72,71.75)	25.55, 21.96 (18.50,18)	25.69, 14.04 (22,19)	20.77, 13.59 (16,21)	36.49, 46.83 (25,31)	≥90
Percentage of drugs actually dispensed	92.56	91.03	87.95	81.21	90.99	94.09	97.00	63.16	87.32	100
Percentage of drugs adequately labelled	71.05	21.16	79.01	91.81	36.96	71.99	87.64	93.33	68.24	100
Percentage of patient knowledge about dosage of dispensed drugs	79.5	67	85.5	79	91.5	84	85	55.5	78.88	100

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital, M = Mean, SD = Standard Deviation, Md = Median, IQR = Interquartile range.

Health facility indicators

Eritrean National List of Medicines (ENLM) and National formulary was available in all the hospitals. Furthermore, 80.1% of the key essential medicines were in stock during the study period [Table 6].

Table 6

Percentage distribution on availability of key essential drugs.

Health Facility	Percent
Orotta	80
Halibet	79
Hazhaz	81.5
Ghindae	81.2
Assab	79.7
Keren	80
Mendefera	79.9
Barentu	79.8
Overall	80.1

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital.

Indices of performance indicators

Relatively better IRDP value was observed in Mendefera regional referral hospital (IRDP = 4.488) in comparison to the other health facilities. Similarly, the IRPCDU values indicated that Assab regional referral hospital (IRPCDU = 3.926) showed better results compared with the other health facilities. Hazhaz regional referral hospital (IRFSDU = 1.815) showed better index with regard to facility-specific drug use indicators. Overall, Assab regional referral hospital (IRDU = 10.086) was the best performing hospital in terms of core drug indicators [Table 7].

Table 7

Index of rational medicine use in Eritrean zonal and national referral hospitals.

Performance Indicators	Health Facilities
	ONRH	HNRH	HRRH	GRRH	ARRH	KRRH	MRRH	BRRH
Drug Prescribing Indicators
Non polypharmacy index	1.000	1.000	1.000	1.000	0.989	0.870	1.000	1.000
Generic name index	0.970	0.947	0.959	0.840	0.954	0.953	0.976	0.981
Rational Antibiotic index	0.506	0.605	0.420	0.501	0.470	0.460	0.538	0.476
Rational Injection Safety Index	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000
Essential drugs list index	0.970	0.900	0.954	0.834	0.950	0.998	0.974	0.981
IRDP	4.446	4.452	4.333	4.175	4.364	4.280	4.488	4.438
Rank	3	2	6	8	5	7	1	4
Patient-Care Indicators
Consultation time index	0.570	0.529	0.347	0.267	0.731	0.645	0.390	0.890
Dispensing time index	0.362	0.352	0.353	0.311	1.000	0.284	0.285	0.231
Dispensed medicine index	0.926	0.910	0.880	0.812	0.910	0.941	0.970	0.632
Labelled medicine index	0.711	0.212	0.790	0.918	0.370	0.720	0.876	0.933
Patient’s knowledge index	0.795	0.670	0.855	0.790	0.915	0.840	0.850	0.555
IRPCDU	3.363	2.673	3.224	3.098	3.926	3.430	3.372	3.241
Rank	4	8	6	7	1	2	3	5
Facility Specific Indicators
Index of EML	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000
Index of key drugs in stock	0.800	0.790	0.815	0.812	0.797	0.800	0.799	0.798
IRFSDU	1.800	1.790	1.815	1.812	1.797	1.800	1.799	1.798
Rank	3	8	1	2	7	3	5	6
Grand Total
IRDU	9.609	8.915	9.372	9.085	10.086	9.510	9.659	9.476
Rank	3	8	6	7	1	4	2	5

Note: ONRH = Orotta National Referral Hospital, HNRH = Halibet National Referral Hospital, HRRH = Hazhaz Regional Referral Hospital, GRRH = Ghindae Regional Referral Hospital, ARRH = Assab Regional Referral Hospital, KRRH = Keren Regional Referral Hospital, MRRH = Mendefera Regional Referral Hospital, BRRH = Barentu Regional Referral Hospital, EML = Essential Medicine List, IRDP = Index of Rational Drug Prescribing, IRPCDU = Index of Rational Patient- Care Drug Use, IRFSDU = Index of Rational Facility- Specific Drug Use, IRDU = Index of Rational Drug Use.

Eritrea as a country scored 1 in the indices of non polypharmacy and rational injection safety. Nearly similar scores in generic name index (0.949) and essential drugs list (0.947) were scored in all the health facilities. However, lesser index in rational antibiotic index (0.492) was scored. Combined Index of Rational Drug Prescribing (IRDP) score was 4.388. Score of Index of Rational Patient-Care Drug Use (IRPCDU) was 3.296 which is low compared to the optimal value of 5 [Table 8].

Table 8

Country performance indicators.

Performance Indicators		Country Score
Drug Prescribing Indicators
	Non polypharmacy index	1.000
	Generic name index	0.949
	Rational Antibiotic index	0.492
	Rational Injection Safety Index	1.000
	Essential drugs list index	0.947
	IRDP	4.388
Patient-Care Indicators
	Consultation time index	0.546
	Dispensing time index	0.405
	Dispensed medicine index	0.873
	Labelled medicine index	0.682
	Patient’s knowledge index	0.789
	IRPCDU	3.296
Facility Specific Indicators
	Index of EML	1.000
	Index of key medicine in stock	0.801
	IRFSDU	1.801
Grand Total
	IRDU	9.484

Note: EML = Essential Medicine List, IRDP = Index of Rational Drug Prescribing, IRPCDU = Index of Rational Patient- Care Drug Use, IRFSDU = Index of Rational Facility- Specific Drug Use, IRDU = Index of Rational Drug Use.

Discussion

The average number of medicines per encounter was found to be 1.78. This value in general falls within the frame of WHO standard (1.6–1.8) in outpatient settings [8]. Even though the overall average number of medicines per encounter falls within the WHO standard, 15.2% of the prescriptions enclosed three or more drugs. In a previous study conducted in community-chain pharmacies in Asmara, Eritrea; the average number of drugs per encounter was 1.76 which is exactly the same with the current finding [5]. The figure was consistent with studies conducted in different parts of Ethiopia [12-14]. However, it was lower than 4.8 reported from Sri Lanka [15], 2.9 reported from Kenya [16], 2.9 from Kuwait [17], 2.4 from Saudi Arabia [18] and 2.04 from China [19]. This difference in the number of drugs prescribed per patient could be due to the variation in the study sites and prescribing habits among various medical disciplines. Even though, polypharmacy was not a problem in our country; prescribers should prescribe the lowest possible number of drugs to treat diseases while avoiding symptomatic treatments as polypharmacy was seen in some prescriptions assessed.

The percentage of encounters with antibiotic(s) prescribed was found to be 54.5% which is twice that of the WHO optimal (20–26.8%) [8]. The highest percentage of encounters with antibiotic was recorded in Hazhaz regional referral hospital (63.8%) and none of the hospitals was within the range of WHOs optimal value [8]. This was similar with previous study conducted in Asmara city (Eritrea), which was 53% [5]. However, it was much higher than studies conducted in UAE 9.8% [20], Sri Lanka [15] and Nepal 28.3% [21]. It was lower than studies conducted in Sudan 63% [22], Uganda 56% [23], Ethiopia 58.1% [12] and Kenya 84.8% [16]. Irrational and overuse of antibiotics may lead to adverse drug reactions, antimicrobial resistance and unnecessary hospital admissions [24, 25]. Such high figure could be due to a number of reasons such as inappropriate prescribing of antibiotics, high prevalence of infectious disease in developing countries resulted in increased number of antibiotics prescription, patient pressure on prescribers and allowing lower health cadres to prescribe medicines. In Eritrea, one physician serves 18,041 patients, to deal with this shortage lower health cadres are allowed to prescribe medicines [5, 25]. This mandates policy makers and program managers to draft and implement strategies that decrease the irrational use of antibiotics.

The percentage of injection prescribed hospitals of Eritrea in the present study was 6.6%, lower than the WHO optimal value (≤10%). This figure was lower than the previous study in Eritrea (7.8%) [5], but higher than a study conducted in India 5.7% [26]. On the other hand, it was much lower than the studies in China (22.9%) [19], Bangladesh (38.1%) [27], Kenya (24.9%) [16] and Sri Lanka (30.1%) [15]. This lower value could be due to high preference of oral route by prescribers as injectable preparations are associated with higher risks of disease transmission, incompliance by patients and are expensive [8].

The WHO clearly mentions prescribing drugs by its generic name as generic prescribing is a safety precaution for patients to adhere to their medications and it eases the communication between healthcare providers and patients. Moreover, generic drugs are less expensive than brand drugs. The average percentage of generic prescribing in the present study was found to be 94.6% with the lowest value seen in Ghindae regional referral hospitals (84.01%). This value was higher than the previous study conducted in Eritrea (83.14%) [5]. Caution should be exercised during result comparison as the previous Eritrean study was conducted in community-chain pharmacies of Asmara city. Moreover, lower results were reported from studies conducted in China (69.2%) [19], KSA (61.2%) [18], Sudan (43.2%) [22], South India (42.9%) [28] and Kenya (27.7%) [16]. However, higher results to the present study were reported in researches done in countries like South Ethiopia (98.7%) [12] and Mozambique (99%). Brand prescribing is associated with unnecessary treatment costs, difficulty of remembering the medication name, accessibility and bioequivalence problems [8]. Therefore, more effort is to be devoted to effectively adhere to generic prescribing in order to promote safe, cost effective and accessible generic drugs.

Most of the drugs (94.73%) were prescribed from the Eritrean National List of Medicines (ENLM). This was much similar with a study conducted in Eritrea [5] which was 98.83%. However, it was much higher than 42.3% reported by Nepal [21], 53% by India [26] and 81.5% by Pakistan [11]. Moreover, this finding was lower that studies conducted in North-West Ethiopia (100%) [29] and North-East Ethiopia (100%) [30]. Such high adherence and availability could be due to the centralized medicine procurement system and the regulation that prohibits the procurement of drugs outside the ENLM.

The average consulting time in this study was 5.46 minutes (standard: greater than 10 minutes). The average consultation time varied from 2.67 minutes in Ghindae to 8.90 minutes in Barentu. This result was similar to a study conducted in Sri Lanka (5.4) [15], but lower than studies conducted in KSA (7.3) [18] and Egypt (7.1) [4]. Moreover, it was higher than 4.61 reported from Eastern Ethiopia [9], 4.1 reported from Kenya [16] and 4.7 reported from North-East Ethiopia [30]. In general, longer consultation time is necessary to assess the patient, give appropriate heath education and increases the level of physician-patient interaction thereby improves patient satisfaction towards the healthcare system [8]. The reason behind shorter consultation time compared to the WHO optimal could be increased workload of health staff and/or not understanding communication as an important aspect of their work role.

Average dispensing time reported in this study was 36.49 seconds which was much lower compared to what the WHO recommends (greater than 90 seconds). Assab regional referral hospital is the only hospital to reach the recommended time (95.94 seconds). This lower figure was similar to the dispensing time reported in Sri Lanka (40.2 seconds) [15], Egypt (47.4 seconds) [4] and Kuwait (54.6 seconds) [17]. However it was greater than those reported in Nigeria (12.5 seconds) [31] and Brazil (17 seconds) [32]. Moreover, results from, southern Ethiopia (96.1 seconds) [12], KSA (100 seconds) [18], Zimbabwe (150 seconds) [33], Nigeria (201 seconds) [31], and India (340 seconds) [28] showed better results probably because of adequate patient to health worker ratio and good dispensing setting. Prolonged dispensing time is necessary in improving patient care as short dispensing time (less than 90 seconds) is not enough to explain every information to the patient and it’s clear that patient adherence and compliance is directly proportional to dispensing time [8]. In this current study, the observed short dispensing time could be due to various reasons. First, the layout of most of the dispensaries does not allow for private pharmacist-patient interactions. Second, dispensers do not have sufficient time to explain medications to patient as they have too much workload. Furthermore, patients do not understand about the dispenser’s role and they also do not expect to learn more from dispensers about drugs.

The percentage of drugs actually dispensed was 87%. This indicator was lower than the ideal WHO standard (100%). This value was similar from study done in southern Ethiopia (86.3%) [12]. However, it was lower than studies reported in Egypt (95.9%) [4], Kuwait (97.6%) [17], and KSA (99.6%) [18]. The result might be due to inadequate medicine supply and leads to unnecessary medication charge by the patients from private drug retail outlets.

An adequate label includes at least the name of the medicine, name and strength of the medicine and written instructions on how to take the medicine. The median percent medicines adequately labelled was found to be 68.24%. Lower results were observed in North-East Ethiopia (0%) [30], KSA (10%) [18], Eastern Ethiopia (20%) [9], and Kuwait (66.9%) [17]. However, Egypt (95.9%) [4] and India (100%) [26] are almost consistent with the WHO optimal value. Labelling is one of the key indicators of good dispensing practice, adequate labelling eventually promotes patient awareness about the regimen the patient takes and hence increases treatment adherence [8]. This difference could be attributed to dispenser’s adequacy of training in how drugs are to be packaged and labelled. Likewise, the workload of the dispensers could also explain the inadequate labelling.

Patient’s knowledge of correct dosage in this study was found to be 78.88% (optimal value: 100%). This current study reported higher patient knowledge than Kuwait (26.9) [17], India (46%) [28], Eastern Ethiopia (61.88%) [9] and KSA (79.3%) [18] but lower than the study conducted in Egypt (94%) [4]. Even though the interview was done immediately after dispensing and might not be concluded that this knowledge persists throughout the course of therapy, patient knowledge definitely improves patient care and prevents any harm related to the medication and avoids medicine overuse and abuse.

The results for the facility indicators showed that all health facilities included (100%) had a copy of Eritrean National List of Medicine (ENLM). This value was higher than the study conducted at KSA (90%) [18], Egypt (80%) [4] and Kenya (20%) [16]. WHO recommends adherence of physicians to the medicines listed in the EML/formulary when prescribing medications in order to ensure effective health care for all [8].

Majority (80.1%) of the selected key essential medicines were in stock during the study period. This figure was higher than studies conducted at KSA (59.2%) [18], Eastern Ethiopia (66.7%) [9], and almost similar with studies conducted in Egypt (78.3%) [4] and Nigeria (83.3%) [34]. This variation could be due to the difference in study sites and inventory management. A shortage of supplies of essential medicines that treat common health problems is harmful to health status of patients, in that doctors may not be able to prescribe the correct essential medicine or they are limited to prescribing out-of-stock medicines which may pose extra financial burden on the patients’ “through out of pocket” expense [8]. This requires an immediate attention from the policy makers in that essential medicines should be fully accessible without any inconsistency in their supply.

This study revealed that the overall IRDP was 4.388. It was lower than the optimal value of five. Moreover, it was also lower than 4.43 reported from North-East Ethiopia [30]. However, it was higher than a study conducted in Sri Lanka (3.67) [15]. The overall IRPCDU and IRFSDU were 3.296 (out of 5.0) and 1.801 (out of 2.0), respectively. The overall IRPCDU and IRFSDU were much higher than a study conducted in North-East Ethiopia (2.51 and 0.64, respectively) [30]. This finding necessitates the policy makers and program managers to find a quick solution to improve the rational use of medicines in all areas.

Limitations of the study

This indicator highlights general prescribing and dispensing problems at each facility. These results indicate where the problem exists but could not reveal reasons that lead to irrational use of medicines. These indicators do not show whether the prescribed medicines in the study is in compliance with the diagnosis. Besides, our findings could not be generalized to the whole of Eritrea. The authors therefore recommended further studies that explore the reasons that lead to irrational use of medicines.

Conclusion

The overall rationality of medicine use was found sub-optimal as some of important components were missed. Three of the five prescribing indicators (percentage of encounter with antibiotic, percentage of medicines prescribed by generic and percentage of medicines from EML) and all the patient care indicators were less than the optimal value. Average number of medicines per prescription and percentage of encounters with injection prescribed falls within the window of WHO criteria. Moreover, inappropriate use of antibiotics was highly noticeable. The overall results of medicines use studies showed that there is highly appreciable practice with generic name prescribing and a high adherence to the Eritrean National List of Medicines.

Recommendations

Considering such irrational medicine use, further in-depth investigation is warranted to dig out the underlying problem hence interventional strategies can be designed to redirect the current drug use pattern. Besides, proper utilization of standard treatment guidelines, essential medicine lists by healthcare professionals, establishment of medicines and therapeutic committee and targeted educational programs are highly recommended to enhance the rational use of medicines.

Prescribing indicator recording form.

(PDF)

Click here for additional data file.

Patient-care indicator recording form.

(PDF)

Click here for additional data file.

Facility indicator recording form.

(PDF)

Click here for additional data file.

9 Nov 2021

Drug Prescribing and Dispensing Practices in Regional and National Referral Hospitals of Eritrea: Evaluation with WHO/INRUD Core Drug Use Indicators

PLOS ONE

Dear Dr. Abdu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. In particular, the implications of the findings of the study need to be further explored and included in the discussion. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Few comments related to study methods/ discussion are

1. How was non-polypharmacy defined in the study? it is mentioned that two or less drugs were defined as non-polypharmacy. Usually polypharmacy is defined as five or more drugs in a prescription. "Index of non-polypharmacy was measured by dividing average number of drugs by 1.8." Why 1.8? and On page 7, line 136 the formula mentions observed value in the denominator.

2. What is the source of WHO standard as mentioned in the tables? The term optimal value is also used at several places in the text. What is the difference between - WHO standard and optimal values? It is worthwhile to give a table mentioning the optimal values used in the study and their references.

3. The naming of healthcare facilities needs to be uniform in the manuscript text especially tables.

4. The methods section doesn't mention about the country performance indicators. How was the value of 1 calculated for indices of non-polypharmacy and rational injection use?

5. The implications of the study findings need to be discussed in greater details for all stakeholders especially policy makers.

6. There are some language errors and some discrepancies in the numbers mentioned in the text and table.

Please submit your revised manuscript by Dec 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Ashish Kakkar, MD DM

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please update your Methods section to clarify if the participants gave verbal consent for the information to be used in the study --  did the trained data collectors specifically ask the patients if they consent? Also, please explain why written consent was not used.

3. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

4. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

5. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

- http://pharmamedix.in/journals/IJPPR/article/download/107/pdf_28

- https://www.sciencedirect.com/science/article/pii/S1658361213000498?via%3Dihub

- https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-017-2097-3

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Good day

Statistical Analysis: Kindly develop adjusted result

Ethical Approval sound appropriate. Please detail ethical approval body with address. Add Reference number of approval letter.

Please separate Conclusion and Recommendation.

Your key message in a BOX.

Please try to use recent reference add or replace more than 5 years old.

Reviewer #2: Overall

1) Correction of grammar, spellings and punctuations to improve readability.

2) I notice that the term drug and medicine are used inter-changeably, suggest sticking to the term medicine. Of course you will have to use Drug when referring to INRUD. But in other place make it uniform.

Abstract

1) Were the prescriptions collected from in-patients or out-patients or both? its not clear in the abstract

2) Which disciplines were included? coz prescribing patterns will be different. Was it all? Medicine, Surgery, Gyn & Obs, Paediatrics, etc. Again not clear in abstract.

3) In abstract SD is not reported for some parameters

4) Since most of these are likely to be skewed by outlier values, its best to report median and range as well.

Introduction

1) Would benefit from a description regarding current practices in the country and a small introduction about its health care system (public vs. private, etc, etc)

Methods

1) How big are these hospitals. An indicator about bed strength or an appropriate reference will be helpful for the reader.

2) I now see that this is mainly OPD prescriptions. However, is it all specialties?

3) How many data collectors were involved?

Results

1) As mentioned above mean may not be the best way to report. At least mention median and range within brackets

Discussion

1) The implications of the study findings are not sufficiently discussed with appropriate references. For example, use of antibiotics

2) Whats the impact of having a mixed group of patients from different specialities

3) Limitations of the study not described adequately.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Mainul Haque

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

1 Dec 2021

Author response to Reviewer’s comments

We would like to thank our academic editor and reviewers for their invaluable inputs and constructive comments that are helpful to massively improve the quality of the manuscript. After careful consideration of the points raised by academic editor and reviewers, a point-by-point response are as follows:

Academic editor

1. How was non-polypharmacy defined in the study? It is mentioned that two or less were defined as non-polypharmacy. Usually polypharmacy is defined as five or more drugs in a prescription. “Index of non-polypharmacy was measured by dividing average number of drugs by 1.8”. Why 1.8? And on page 7, line 136 the formula mentions observed value in the denominator.

Response: It is well noted. The definition of polypharmacy in the manuscript was inappropriate and therefore omitted from the text. Besides, the statement “Index of non-polypharmacy was measured by dividing average number of drugs by 1.8” was a typing error and therefore removed from the text. Furthermore, in the result section of the study the concept of “Index of non-polypharmacy was measured by dividing the optimal value (taken as 1.8) by the average number of drugs”. The index of non-polypharmacy was expressed in terms of the average number of drugs per prescription.

2. What is the source of WHO standard as mentioned in the tables? The term optimal value is also used at several places in the text. What is the difference between- WHO standard and optimal values? It is worthwhile to give a table mentioning the optimal values in the study and their references.

Response: The reference for the optimal values was cited. There is no difference between the WHO standard and optimal values (used interchangeably). Moreover, an additional table (1) that mentions the WHO standard (optimal values) for all the three indicators alongside their references is added in the method section.

3. The naming of healthcare facilities needs to be uniform in the manuscript especially tables.

Response: Accepted

4. The methods section doesn’t mention about the country performance indicators. How was the value of 1 calculated for indices of non-polypharmacy and rational injection use?

Response: The country performance indicators for indices of non-polypharmacy and rational injection use was calculated by the concept (optimal value/observed value). The optimal value for non-polypharmacy was taken as 1.8, whereas the optimal value for rational injection use was taken as 24.1. Moreover, the observed value was taken as the overall (average) of the hospitals in each item within the indicators. Optimal index that yielded more than one was taken as one as the maximum value of the optimal index is one. The above-mentioned calculation approach for the country performance indicators was included in the ‘method’ section within the revised manuscript.

5. The implications of the study findings need to be discussed in greater details for all stakeholders especially policy makers.

Response: Accepted. The implications of the study findings are discussed in greater details for all stakeholders. The discussion section is modified in the revised manuscript.

6. There are some language errors and some discrepancies in the numbers mentioned in the text and tables.

Response: Accepted. A massive editing is made on the manuscript. We have made 320 insertions, 236 deletions, 2 moves and 13 formatting in the revised section. Accordingly, the reference section is fully revised. Please refer the ‘revised manuscript with track changes’.

Reviewer 1

-Statistical analysis: kindly develop adjusted result

Response: Adjusted result could not be obtained as there is only one independent variable namely, hospital. All the other variable such as average number of medicines per prescription, average consultation and dispensing time and so on are assessed on their potential difference across the hospitals.

-Ethical approval sound appropriate. Please detail ethical approval body with address. Add Reference number of approval letter.

Response: Accepted

-Please separate conclusion and recommendation.

Response: Accepted.

-Your key message in a box.

Response: The key message is already included in the separated recommendation section.

-Please try to use recent references add or replace more than 5 years old.

Response: This is a very important comment. Our paper has been prepared before 2 years. Hence, your comment is valuable and we included recent available studies in the introduction and discussion sections, while removing too old references. Besides, for WHO and other guidelines that were prepared a long time ago and which were used as a source material for the methodology we preferred to keep them in the references.

Reviewer 2

1. Correction of grammar, spellings and punctuations to improve readability.

Response: Accepted. A massive editing is made on the manuscript. We have made 320 insertions, 236 deletions, 2 moves and 13 formatting in the revised section. Accordingly, the reference section is fully revised. Please refer the ‘revised manuscript with track changes’.

2. I notice that the term drug and medicine are used interchangeably, suggest sticking to the term medicine. Of course you will have to use Drug when referring to INRUD. But in other place make it uniform.

Response: Accepted. Where appropriate, the term ‘drug’ is replaced with the term ‘medicine’.

Abstract

1. Were the prescriptions collected from in-patients or out-patients or both? It’s not clear in the abstract.

Response: It was from out-patients.

2. Which disciplines were included? Coz prescribing patterns will be different. Was it all? Medicine, Surgery, Gyn & Obs, Paediatrics, etc. Again not clear in the abstract.

Response: All medical specialties (disciplines) were included.

3. In abstract SD is not reported for some parameters.

Response: Accepted. Standard deviation is reported for all parameters expressed as M (SD).

4. Since most of these are likely to be skewed by outlier values, its best to report median and range as well.

Response: Accepted. We reported it as mean for ease of comparison of the values with that of the WHO standard. Besides, at times median value is important we reported it. For instance, average consultation and dispensing time.

Introduction

1. Would benefit from a description regarding current practices in the country and a small introduction about its healthcare system (public vs. private, etc, etc)

Response: Accepted. The current practices in the country is included in the introduction. Moreover, a small introduction about the Eritrean healthcare system is given in the method section (study design and setting sub-section).

Methods

1. How big are these hospitals? An indicator about bed strength or an appropriate reference will be helpful for the reader.

Response: All the study sites (hospitals) are one of the biggest hospitals in the country. Orotta and Halibet hospitals are national referral hospitals that serves patients from all around the country. They are situated in the capital city of Eritrea (Asmara) and considered as a tertiary level services that provides lots of services such as out-patient, in-patient, maternity, paediatrics, and surgery and so on. Furthermore, the rest six hospitals are regional referral hospitals that serves patients referred or self-referred within the region they locate. They are considered as secondary level of service and are bigger in nature.

2. I now see that this is mainly OPD prescriptions. However, is it all specialties?

Response: Yes, it was from all specialties.

3. How many data collectors were involved?

Response: A total of 20 data collectors were involved in the study.

Results

1. As mentioned above mean may not be the best way to report. At least mention median and range within brackets.

Response: Accepted. At times Md (IQR) is important we reported it in some parameters like average number of medicines per prescription, average consultation and dispensing time.

Discussion

1. The implications of the study findings are not sufficiently discussed with appropriate references. For example, use of antibiotics.

Response: Accepted. The implications of the study findings are expressed in detail in the revised manuscript.

2. What is the impact of having a mixed group of patients from different specialties?

Response: It helps to get a complete picture of the rational use of medicines within a hospital.

3. Limitations of the study not described adequately.

Response: Accepted. We explored the possible limitations we have in the study and added in the revised manuscript.

Kind regards

Nuru Abdu (BPharm)

On behalf of the authors

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

22 Jun 2022

25 Jun 2022

Author response to editor’s and reviewer’s comments

We would like to thank our academic editor and reviewers for their invaluable inputs and constructive comments that are helpful to massively improve the quality of the manuscript. After careful consideration of the points raised by academic editor and reviewers, a point-by-point response are as follows:

Academic editor

1. The tables should include SD wherever mean is mentioned. Either of them (Mean SD/Median IQR) be reported for each variable depending upon distribution of data values.

Response: Thank you for this comment. SD is included wherever mean is mentioned. Besides, the authors preferred to report both the mean (SD) and median (IQR). Mean (SD) is used for ease of comparison with the WHO standard values and median (IQR) is included as some variables have outliers.

2. Table 1 has typo. Percent of drugs adequately labelled!

Response: Thank you for pointing out this issue. The typos error in table 1 is corrected in the revised manuscript.

3. There is discrepancy in the average number of drugs per encounter mentioned in the abstract, main results, discussion and the table 2. Needs to be rechecked.

Response: Comment is addressed in the revised manuscript.

4. Several statements in the discussion lack appropriate references viz. irrational and overuse of antibiotics……., injectable preparations………..

Response: Thank you for the great comment. The discussion section is revised and where necessary citations are added. Besides, some statements used as implications are the authors’ own ideas.

5. Limitations need to include implications of having a mixed group of patients from various specialties.

Response: Thank you for this comment. The study sites are regional and national referral hospitals having various specialties (disciplines). Thus, the study involved a mixed group of patients. So, the authors do not see the importance of adding it in the limitation section.

6. Discussion needs to be rechecked for consistency and appropriate references.

Response: Comment well noted. Necessary changes are made in the revised manuscript.

Reviewer 1

-Accept. As comments are addressed, I would like to recommend they should be accepted and published in PLOS ONE.

Response: Thank you for your review.

Reviewer 2

-Introduction: Line 72 must be ‘ensuring’

Response: Thank you for your comment. It was corrected in the revised manuscript.

-Methods: Line 80- ‘September 1 to January 31, 2018’ year for September to be mentioned.

Response: Comment well taken. Addressed in the revised manuscript.

-Tables 2, 5: The abbreviations M, Md, IQR to be expanded in foot note.

Response: Comment well taken. Addressed in the revised manuscript.

-Column headings could be made appropriate for all the values described in table. Values in Table 4 represent time, but the column heading does not mention time.

Response: Thank you for your suggestion. For ease of understanding, the authors added ‘minute’ and ‘second’ alongside the values for the consultation and dispensing time, respectively.

-Many are incomplete, example – Ref 1 is incomplete. Web pages are without a URL.

Response: Thank you for pointing out this issue. References are updated in the revised version.

Kind regards

Nuru Abdu (BPharm)

On behalf of the authors

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

1 Aug 2022

Drug Prescribing and Dispensing Practices in Regional and National Referral Hospitals of Eritrea: Evaluation with WHO/INRUD Core Drug Use Indicators

PONE-D-21-11930R2

Dear Dr. Abdu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ashish Kakkar, MD DM

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The authors need to correct a minor typo in Table 1 that was mentioned in the comments - "Percent of drugs "actually" labelled. - It should be "adequately" labelled.

Reviewers' comments:

10 Aug 2022

PONE-D-21-11930R2

Drug Prescribing and Dispensing Practices in Regional and National Referral Hospitals of Eritrea: Evaluation with WHO/INRUD Core Drug Use Indicators

Dear Dr. Abdu:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ashish Kakkar

Academic Editor

PLOS ONE