Role of telepharmacy in pharmacist counselling to coronavirus disease 2019 patients and medication dispensing errors

Abstract

Introduction

Remote pharmacist interventions have achieved much more attention during the coronavirus disease 2019 (COVID-19) outbreak, since they reduce the risk of transmission and can potentially increase the access of vulnerable populations, such as patients with COVID-19, to pharmaceutical care. This study aimed to examine differences in rates and types of pharmacist interventions related to COVID-19 and medication dispensing errors (MDEs) across community pharmacies with and without telepharmacy services.

Methods

This was a prospective, disguised, observational study conducted over four months (from March 2020 to July 2020) in 52 community pharmacies (26 with and 26 without telepharmacy) across all seven states of the United Arab Emirates using proportionate random sampling. A standardised data-collection form was developed to include information about patient status, pharmacist interventions and MDEs.

Results

The test (telepharmacy) group pharmacies provided pharmaceutical care to 19,974 patients, of whom 6371 (31.90%) and 1213 (6.07%) were probable and confirmed cases of COVID-19, respectively. The control group pharmacies provided care to 9151 patients, of whom 1074 (11.74%) and 33 (0.36%) were probable and confirmed cases of COVID-19, respectively. Rates of MDEs and their subcategories, prescription-related errors and pharmacist counselling errors across pharmacies with telepharmacy versus those without remote services were 15.81% versus 19.43% (p < 0.05), 5.38% versus 10.08% (p < 0.05) and 10.42% versus 9.35% (p > 0.05), respectively.

Discussion

This is one of the first studies to provide high-quality evidence of the impact of telepharmacy on COVID-19 patients’ access to pharmaceutical care and on medication dispensing safety.

Keywords

COVID-19 pandemic pharmacy safety teleconsulting telecare telehealth remote consultation

Introduction

The spread of coronavirus disease 2019 (COVID-19) has overwhelmed public-health and health-care systems worldwide.¹ Correspondingly, COVID-19 has posed new challenges for the health-care systems of both developed and developing countries.² In particular, many countries have combated the pandemic through adopting response strategies to flatten the contagion curve by implementation of restrictive measures, including early diagnoses, prompt isolation for suspected individuals and health quarantine for confirmed cases, and initiation of infection-control measures.³,⁴ In this context, telepharmacy falls under the umbrella of telemedicine, and refers to providing pharmaceutical services within the scope of a pharmacist’s responsibilities, with a temporal and spatial distance between patients as the consumers of health services and health-care providers.⁵,⁶ Rural community pharmacies across the USA have been using telepharmacy to increase access to pharmaceutical services.⁷ Brown et al.⁸ demonstrated the effectiveness of telepharmacy as a mean to maintain asthma control in a community setting. Schneider⁹ found that implementation of telepharmacy services in community hospitals can reduce the number of potential adverse drug events. In addition, the number of pharmacist interventions increased by 42% following implementation of telepharmacy services in a multi-hospital health system.¹⁰ The expanded application of telepharmacy can improve the provision of patient-focused consultation and patient access to pharmacy services as well.¹¹ Nevertheless, Friesner et al.¹² concluded that there is no significant difference in rates of medication dispensing errors (MDEs) between telepharmacy and traditional pharmacy.

In light of COVID-19, several countries, including the USA, Canada, the UK and Australia, have legally permitted the extension of the role of pharmacists to include virtual consultations with patients using social media websites, home delivery of medications and permission to compound antiseptic solutions.⁴,^13–15 In Italy, a limited diffusion of telemedicine/telehealth services among Italian pharmacies and a lack of support from health authorities have been reported.¹⁶

In the Middle East, health officials in the United Arab Emirates (UAE) have issued circulars regulating the delivery of telepharmacy services during the COVID-19 pandemic.¹⁷ These services include dispensing medications, medical products, herbal and food supplements, cosmetic products, formulary compliance, patient counselling, medicine therapy management, automated packaging and labelling systems.¹⁸ These legal permissions may enable community pharmacists utilising telepharmacy to identify differences between sessional flu and COVID-19 symptoms safely among patients, refer them to the appropriate health-care facility for testing and provide necessary information to reduce the spread of this virus in the community.⁶,¹⁹

Several studies have raised concerns regarding patient privacy.^20–22 More specifically, there have been concerns regarding the nature of the data, for instance an electronic medical record can hold more intimate details of an individual than any single document.²² Therefore, maximum protection of patient data must be ensured, not only by those who supply the device but also by all health professionals.²² Baldoni et al. concluded that legal implications make greater diffusion of telepharmacy difficult.²³

Therefore, this study aimed to test whether using telepharmacy can efficiently reduce the burden on the health-care system by providing services to probable and confirmed patients of COVID-19, and whether adopting telepharmacy leads to higher or lower medication dispensing error rates compared to community pharmacies that do not operate remote pharmacy services. Furthermore, the study investigated the nature of pharmacist recommendations related to COVID-19 and the types of errors induced during the dispensing of medications in community pharmacies both with and without telepharmacy services. If adopting telepharmacy results in the delivery of pharmacy services to more susceptible and confirmed patients of COVID-19 and lower MDE rates, then a case can be made for generalised implementation of the remote services in community pharmacy settings. This study examined the differences in frequency and types of patients, recommendations and interventions, and MDE rates across community pharmacies with and without remote services.

Methods

Study design

This was a cross-sectional, observational, comparative study conducted prospectively over four months (from March 2020 to July 2020) in community pharmacies across all seven states of the UAE during the COVID-19 outbreak. To avoid the Hawthorne effect, a disguised direct observation of the pharmacy dispensary team was conducted. Only the community pharmacy managers were informed about the purposes of our study and were asked to sign a written consent form, whereas the staff members were told that the research investigators would be examining the prescribing trends of physicians. This study was approved by the Ethics Committee at the University of Sharjah.

Sample size and sampling technique

The minimum recommended sample size was calculated using G*Power software²⁴ (power = 0.8, α ≤ 0.05, effect size = 0.8 (large)). The recommended sample size was 52 community pharmacies, of which 26 were operating telepharmacy services (test group) and 26 were operating traditional pharmacy services (control group). Pharmacies were divided based on three geographical regions using proportionate random sampling: the capital region (Abu Dhabi), the north region (Ajman, Fujairah, Ras al Khaimah, Sharjah and Umm al Quwain) and the central region (Dubai). These regions were further stratified into the residential areas of workers, in which the risk of acquiring and transmission of the infection is high, and of non-workers. The number of targeted pharmacies included from Abu Dhabi was 16 (30.8%) based on its proportion of community pharmacies from the total number of pharmacies in the UAE (30.5%; 802/2625). Using the same approach, 21 (40.4%) pharmacies were included from the north region, and 15 (28.8%) pharmacies were included from the central region. To achieve the targeted sample, we approached 103 pharmacies. Of these, 43 refused to participate, and eight dropped out. Reasons for dropping out included the place was not appropriate for performing research (light workload or small size), managers who work on a regular basis or telepharmacy services were operated partially.

Characteristics of the pharmacies

As shown in Figure 1, the community pharmacies included in this study were divided into intervention (with remote services) and control (without remote services) groups. A computerised physician order-entry system, electronic patient record and automated medication dispensing cabinets were not available in either of the groups. Pharmacies in the test group utilised the available information technology (IT) tools to deliver remote pharmaceutical services to patients, such as filling out prescriptions, medication reviews, patient counselling and home delivery of medications.²⁵ These pharmacies used videoconferencing software, phone calls and social media websites to deliver their services to patients, who were not interacting with the pharmacist face to face at any point.

Figure 1.

Characteristics of the included community pharmacies. √√: available; ××: not available.

Pharmacies were invited to participate in the intervention group if (a) they were working on a regular basis, (b) they were operating remote pharmacist interventions and (c) they had appropriate space to accommodate the inspectors and maintain social distancing. Pharmacies were excluded from the test group if (a) they partially operated remote pharmacist services, (b) the remote services were not authorised/licensed by the UAE health authorities or (c) the pharmacy manager was working as the pharmacist in charge.

MDEs

Based on previous studies,^26–28 a MDE was defined as ‘any unintended deviation from an interpretable written prescription or medication order. Both content and labeling errors are included. Any unintended deviation from professional or regulatory references, or guidelines affecting dispensing procedures, is also considered a dispensing error’. The operational definitions of errors were adopted from Cohen’s classification of MDEs²⁸ and tailored to our setting (Figure 2). The categorisation of MDEs into pharmacist counselling errors (PCEs) and prescription-related errors (PREs), and the techniques for observation were adopted from Abdel-Qader.²⁹

Figure 2.

Classification of medication dispensing errors.

Pharmacist recommendations

To document access of COVID-19 probable and confirmed patients to pharmaceutical services, the study adopted the criteria for COVID-19 case classification based on the Centers for Disease Control and Prevention³⁰ and European Centre for Disease Prevention and Control.³¹ A person was considered matching the clinical criteria for COVID-19 if he/she had at least two of the following symptoms: fever (measured or subjective), chills, rigors, myalgia, headache, sore throat, new olfactory and taste disorders, or if they had at least one of the following symptoms: cough, shortness of breath or difficulty breathing, or if they had severe respiratory illness with clinical or radiographic evidence of pneumonia or acute respiratory distress syndrome. A person was considered matching the laboratory criteria for COVID-19 if he/she had been tested using a method approved or authorised by the UAE Ministry of Health and Prevention, and the result showed detection of severe acute respiratory syndrome coronavirus 2 ribonucleic acid (SARS-CoV-2 RNA) in a clinical specimen using a molecular amplification detection test. A person was considered matching the epidemiological criteria for COVID-19 if he/she had one or more of the following exposures in the 14 days before onset of symptoms: (a) close contact with a confirmed or probable case of COVID-19 disease, (b) travel to or residence in an area with sustained ongoing community transmission of SARS-CoV-2 and (c) member of a risk cohort as defined by the health authorities during an outbreak. A close contact was defined as being within six feet for a period of at least 10 minutes to 30 minutes or more, depending upon the exposure. A person was considered a probable case of COVID-19 if he/she had met the clinical criteria and epidemiological evidence with no confirmatory laboratory testing performed for COVID-19. A person was considered a confirmed case of COVID-19 if he/she met confirmatory laboratory evidence.

Data collection

A preliminary pilot study was conducted in four community pharmacies (two from each group) for five days to ensure the validity and practicality of the research methods. At the time of the research, community pharmacies in the UAE did not implement an electronic system linking physician orders directly to the pharmacy. Thus, types of errors related to this system, such as selection errors, were omitted from the data-collection form. After piloting, the period of the study was increased from two weeks per pharmacy to four weeks. To maintain patient privacy and reduce the spread of COVID-19, research pharmacists were instructed to have no interaction with patients unless absolutely necessary. The piloting study data were not included in the final data set.

Collection of data on MDEs

A standardised data-collection form was developed by the research team. The form included information about patient status, prescription details and types and causes of errors. Each research pharmacist prospectively collected data for a month (9:00am–5:00pm) at a designated pharmacy. For pharmacies with a high workload ( > 100 prescriptions a day), two research pharmacists were assigned for observation. At the end of each research day, the main investigator (O.M.I.) and the research assistant (A.Z.M.) reviewed and confirmed the detected errors and incidents against the eligibility criteria. Those not matching the criteria were removed.

Collection of data on pharmacist recommendations

Pharmacist recommendations were reported on a data-collection form by the research team. The research team consisted of 16 licensed pharmacists with more than two years of experience in pharmacy practice, who were recruited following an online assessment that tested their core knowledge about infectious diseases, attention to detail and IT skills. Unfortunately, one of the research pharmacists contracted the virus before data collection and was thus excluded from the research. To ensure infection-control measures were properly taken, the other research team members were tested for COVID-19 before and after data collection. The principal investigator (O.M.I.) used Zoom to deliver the training and to update the research team consistently regarding local regulations and measures related to COVID-19.

Data analysis

The data were entered and analysed with Microsoft Excel (Microsoft, Redmond, WA) and IBM SPSS Statistics for Windows v26 (IBM Corp., Armonk, NY). To examine differences in frequencies of patients who received pharmacy care, recommendations provided, pharmacist interventions on prescriptions and MDE rates, as well as types across test (with remote services) and control (without remote services) groups, chi-square or Fisher’s exact tests were used as appropriate. A Bonferroni correction was applied for more than two group comparisons. Descriptive results are presented as proportions (%) with 95% confidence intervals (CIs).

Results

COVID-19-related recommendations

As noted in Table 1, the proportions for probable and confirmed COVID-19 cases who received pharmaceutical services across pharmacies with remote services (test group) and pharmacies without remote services (control group) were 31.90% versus 11.74% and 6.07% versus 0.36% (p = 0.011), respectively. Compared to the control group, pharmacies with telepharmacy services had a significantly higher frequency of recommendations related to COVID-19 (test group: 63,714 vs. control group: 15,539). Recommendations for the use of face masks and gloves, frequent hand washing, maintaining social distancing, taking vitamin C and take paracetamol for fever across the test and control groups were 21.57% versus 44.48%, 13.13% versus 20.43%, 12.75% versus 10.57% and 10.67% versus 4.78% (p = 0.037), respectively. Prescriptions dispensed across the test and control groups were 6982 versus 2841, respectively. Results for pharmacies among the test group showed higher proportions of minor (51.54%) and moderate (36.87%) polypharmacy prescriptions rather than major polypharmacy (11.59%), and higher proportions of pharmacist interventions related to a change in medication due to potential drug–drug interactions or contraindications (20.36%) and removal of duplicate drugs (7.67%), followed by pharmacist interventions related to the addition of another medicine (5.47%) and modifying overdose (4.03%).

Table 1.

Frequency and categorisation of patients, prescriptions, recommendations and pharmaceutical care interventions at pharmacies with or without remote services.

Item	Pharmacies with remote services	Pharmacies without remote services	Total (%)	p-Value^a
1. Patients received pharmaceutical care				0.011
COVID-19 probable cases	6371 (31.90%)	1074 (11.74%)	7445 (25.56%)
COVID-19 confirmed cases	1213 (6.07%)	33 (0.36%)	1241 (4.26%)
Patients with no sufficient information about status	12,390 (62.03%)	8044 (87.90%)	20,439 (70.18%)
Subtotal	19,974 (100%)	9151 (100%)	29,125 (100%)
2. COVID-19-related recommendations				0.037
Use face mask and gloves, and wash hands frequently	13,744 (21.57%)	6911 (44.48%)	20,655 (26.06%)
Maintain social distancing	8367 (13.13%)	3174 (20.43%)	11,541(14.56%)
Take vitamin C	8121 (12.75%)	1642 (10.57%)	9763 (12.32%)
Take paracetamol for fever	6799 (10.67%)	742 (4.78%)	7541(9.52%)
Maintain home quarantine	6581 (10.33%)	436 (2.81%)	7017 (8.85%)
Avoid non-essential travel	5941 (9.32%)	1422 (9.15%)	7363 (9.29%)
Eat healthy food	4297(6.74%)	299 (1.92%)	4596 (5.80%)
Contact the nearest testing centre	3997 (6.27%)	197 (1.27%)	4194 (5.29%)
Stop smoking	3125 (4.90%)	577 (3.71%)	3702 (4.67%)
Self-isolate	1113 (1.75%)	25 (0.16%)	1138 (1.44%)
Contact the nearest medical centre	975 (1.53%)	113 (0.73%)	1088 (1.37%)
Call emergency services	654 (1.03%)	1 (0.01%)	655 (0.83%)
Subtotal	63,714 (100%)	15,539 (100%)	79,253 (100%)
3. Prescriptions				0.672^b
Minor polypharmacy	3599(51.54%)	1369 (48.19%)	4968 (50.58%)
Moderate polypharmacy	2574 (36.87%)	968 (34.07%)	3542 (36.06%)
Major polypharmacy	809 (11.59%)	504(17.74%)	1313 (13.36%)
Subtotal	6982 (100%)	2841 (100%)	9823 (100%)
4. Interventions on prescriptions				0.027
Clarifying instructions for medicine use	2961(40.27%)	1321 (42.67%)	4282 (40.98%)
Changing medication order due to potential DDI or contraindication (potential allergy, pregnancy, etc.)	1497 (20.36%)	507 (16.38%)	2004 (19.18%)
Calling physician for clarification	1079 (14.67%)	766 (24.74%)	1845 (17.66%)
Removing duplicate drugs	564 (7.67%)	91 (2.94%)	655 (6.27%)
Addition of another medicine	402 (5.47%)	103 (3.33%)	505 (4.83%)
Optimising overdose	296 (4.03%)	66 (2.13%)	362 (3.46%)
Changing dosage form	265 (3.60%)	174 (5.62%)	439 (4.20%)
Optimising sub-therapeutic dose or duration	166 (2.26%)	41 (1.32%)	207 (1.98%)
Clarifying instructions inhaler use	123 (1.67%)	27 (0.87%)	150 (1.44%)
Subtotal	7353 (100%)	3096 (100%)	10,449 (100%)

Data shown as n (%). p<0.05 was considered significant.

^aUnivariate association of each of the four item levels across the two groups of pharmacy status were studied using chi-square tests for differences of association between the categorical variables. All p-values <0.05 were significant. A Bonferroni correction was applied for more than two group comparisons. Minor polypharmacy: 2–4 medication orders; moderate polypharmacy: 4–5 medication orders; major polypharmacy: ≥5 medication orders.⁵⁰

DDI: drug–drug interaction; COVID-19: coronavirus disease 2019.

MDEs

As shown in Table 2, 7908 MDEs were detected in the remote telepharmacy group (50,026 dispensed items), and 4563 were reported in the control group (23,481 dispensed items). These numbers resulted in overall MDE rates of 15.81% for the remote telepharmacy group and 19.43% for the control group. Results for MDE incidence based on prescriptions and MDE rate based on pharmacist counselling across the test and control groups were 5.38% versus 10.08% and 10.42% versus 9.35%, respectively.

Table 2.

MDEs across pharmacies with or without remote services.

Code	Characteristics	Pharmacies with remote services	Pharmacies without remote services	p-Value^a^,b
A	Number of patients	19,974	9151
B	Number of medications dispensed based on prescriptions	23,938	9814
C	Number of medications dispensed based on pharmacist counselling	26,088	13,667
D	Total number of dispensed medications	50,026	23,481
E	MDEs (based on prescriptions)	2691	2366
F	MDEs (based on pharmacist counselling)	5217	2197
G	Total number of MDEs	7908	4563	0.03
H	MDEs per patient(H = G/A)	0.4	0.5	0.63^b
J	Overall MDE incidence (J = G/D×100)	15.81%	19.43%	0.01
K	MDE incidence based on prescriptions (K = E/D×100)	5.38%	10.08%	0.002
L	MDE incidence based on pharmacist counselling (L = F/D×100)	10.42%	9.35%	0.1^b

Statistically significant values are shown in bold.

^aDifferences in characteristics across pharmacies with or without remote services were examined using the chi-square test (p<0.05 was considered significant).

^bp-Value not significant.

MDEs: medication dispensing errors.

Table 3 compares the types of MDEs, on both total MDEs across the two groups of pharmacies and as a proportion of the total. The chi-square test demonstrated a statistically significant difference in the distribution of MDEs between test (with remote services) and control groups (p < 0.05). The most common types of errors detected in test group pharmacies were wrong patient (37.36%), followed by wrong drug (20.25%) and wrong quantity (16.46%) errors. However, wrong drug (40.85%), wrong quantity (20.69%) and wrong strength (9.27%) accounted for the most frequent types of errors detected in pharmacies without remote services.

Table 3.

Differences in type of MDEs across pharmacies with or without remote services.

	Pharmacies with remote services		Pharmacies without remote services			p-Value^a^,b
Type	PCEs (N = 5217)	PREs (N = 2691)	PCEs (N = 2197)	PREs (N = 2366)	Total (%)	0.01
Wrong drug	1011	590	1096	768	3465 (27.78%)
Wrong strength	350	226	107	316	999 (8.01%)
Wrong dosage form	235	406	67	268	976 (7.83%)
Wrong quantity	514	788	381	563	2246 (18.01%)
Omission	22	79	17	62	180 (1.44%)
Wrong preparation	67	31	40	83	221 (1.77%)
Deteriorated drug	146	52	51	27	276 (2.21%)
Wrong instruction for drug usage	105	72	47	68	292 (2.34%)
Wrong label instruction	187	72	56	147	462 (3.70%)
Wrong patient	2580	375	335	64	3354 (26.89%)
Subtotal	7908		4563		12,471 (100%)

^aDifference in the distribution of MDE types between test and comparison groups were examined using the chi-square test (p=0.01 is considered significant).

^bp-Value not significant.

PCEs: pharmacist counselling errors; PREs: prescription-related errors.

Discussion

To our knowledge, the present study is one of only a few to investigate the effectiveness of telepharmacy services in increasing access to pharmaceutical care and improving medication dispensing practice across community pharmacy settings during the COVID-19 era.

In response to the health crisis caused by the COVID-19 pandemic, hospital pharmacy services in Spain adapted their outpatient consultation services and drug dispensing to telepharmacy in order to optimise clinical outcomes and to reduce the risk of contagion.³² However, this procedure implied some limitations on the level of coordination with primary care and community pharmacists.

Before the COVID-19 outbreak, rural community pharmacies and rural hospitals across the USA⁷,³³,³⁴ and Australia³⁵,³⁶ used varied models of telepharmacy services. In Spain, home delivery of medications was offered to specific patient groups.³⁷ An similar service was adopted in Denmark.³⁸ This included remote pharmacist counselling for patients who obtained medicines via the Internet or received them at home. This counselling was provided mainly via telephone or video calls by community pharmacists.³⁸ Both experiences achieved the goals of guaranteeing the adequate treatment of patients³⁷,³⁸ and patient satisfaction,³⁸ as well as saving time.³⁷ Telepharmacy models were also established to increase Egyptian pharmacists’ education on paediatric oncology³⁹ and to educate patients suffering from pulmonary diseases, namely asthma⁸,⁴⁰ and chronic obstructive pulmonary disease,⁴¹ to improve medication safety.

Previous studies have evaluated the impact of remote pharmaceutical services by tracking MDE rates,⁴²,⁴³ by reporting the number of orders reviewed, modified or discontinued by remote pharmacists,³⁴ by documenting pharmacist interventions based on a conceptual framework,³³ by describing the 24-hour pharmacy staffing coverage given⁴⁴ or by showing the time saved and freeing up pharmacists for quality-enhancing initiatives.⁴⁵,⁴⁶

Our findings yielded two major conclusions. First, the study found that telepharmacy services increased patient access to pharmaceutical care. Hence, remote pharmacy services enabled community pharmacies to deliver their care efficiently to more COVID-19 probable and confirmed patients compared to pharmacies without telepharmacy service. This finding supports the discussion of Adunlin et al.⁶ about the potential role of community pharmacists in the response to the COVID-19 outbreak. Second, the findings indicated a lower incidence of MDEs in pharmacies with remote services compared to control pharmacies. This is consistent with the conclusion of Casey et al.⁴² in which they indicated a lower MDE rate following the implementation of a telepharmacy service. However, MDE rates were consistent across central and remote community telepharmacies.⁴³ Looking for meaningful interpretation, we subdivided MDEs into PCEs and PREs. The incidence of PCEs was considerably higher in pharmacies operating remote services compared to the control group pharmacies. This conclusion implies (but in no way proves) that IT tools could empower pharmacists to act as independent prescribers, but their readiness is still questionable, as pharmacists in the Middle East tend to provide pharmaceutical care, raising their profits by independently prescribing medications to patients. In the Arabic region, few studies have been conducted to assess the role of the pharmacist in monitoring medication safety.²⁹,⁴⁷,⁴⁸ However, these studies did not address using IT as a tool to facilitate pharmacist interventions.

Recent studies have discussed the importance of pharmacist interventions to optimise monitoring and the correct use of drugs.⁴⁹ They have suggested that standardisation of pharmacies is imperative in order to have a complete on-board pharmacy that would allow any situation of health danger to be prevented and counteracted.⁴⁹ In this regard, our work discussed how IT tools could reduce drug-related problems and improve the patient access to the care they needed, thus reducing the burden of the pandemic on the health-care system and improving medication dispensing safety by reducing MDE rates.

Limitations

Several limitations could have affected the study findings. First, because the study was conducted on several community pharmacies operating different trends of remote services, the major outcomes of the study would have been affected by this variation. Second, avoiding close contact with staff and patients and the absence of electronic patient records may have made the research pharmacists only report considerable pharmacist interventions, leading to the study results being underestimated. This was also due to a lack of time, as it was difficult to allow enough time to document every single pharmacist intervention that a pharmacist conducted during the course of his/her duties or changes to the service provision. Third, the effect of missing information related to patient status on documented pharmacist interventions and errors were beyond the scope of this study’s aims. Fourth, COVID-19-related recommendations were documented up to and including the point at which the medication was handed over to the patient. We were unable to corroborate whether these recommendations were accepted and applied by the patients, as this was beyond the scope of the study. Finally, cost-effectiveness, clinical impact, error severity and causes and the delivery channels (phone, fax, etc.) of the remote pharmacist interventions were beyond the scope of this study. However, these limitations could be a basis for future research. Furthermore, the present study adopted holistic and valid operational definitions of MDEs, and used disguised direct observation of errors, enhancing the validity of the findings. The study also added a new and previously unexplored perspective to the literature, investigating all MDEs types, including those based on pharmacist counselling and independent prescribing (PCEs) – a common yet little researched practice in community pharmacies across the UAE and the Middle East.

Therefore, the current study results would be of interest to policymakers, stakeholders and providers in fixing and generalising implementation of remote pharmacist interventions in the community setting. This is important, given the disastrous impact of COVID-19 on health-care systems, as well as on the global economy.

Conclusion

The current findings suggest that adopting telepharmacy service could increase patient access, particularly COVID-19 probable and confirmed cases, to pharmacy care and could also reduce dispensing errors. Health authorities in the UAE were the first in the region to implement, regulate and monitor remote pharmaceutical services.

Footnotes

Acknowledgements

We thank the University of Sharjah for facilitating our research. Our thanks go to the community pharmacists for their efforts and cooperation.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Ahmad Z Al Meslamani

References

Smith

Thomas

Snoswell

, et al. Telehealth for global emergencies: implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare 2020; 26: 309–313.

Anderson

Heesterbeek

Klinkenberg

, et al. How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet 2020; 395: 931–934.

Cadogan

Hughes

CM.

On the frontline against COVID-19: Community pharmacists’ contribution during a public health crisis. Res Soc Adm Pharm. Epub ahead of print 31 March 2020. DOI: 10.1016/j.sapharm.2020.03.015

Merks

Jakubowska

Drelich

, et al. The legal extension of the role of pharmacists in light of the COVID-19 global pandemic. Res Soc Adm Pharm. Epub ahead of print 12 June 2020. DOI: 10.1016/j.sapharm.2020.05.033

Toscani

Colaizzi

Telepharmacy: a new paradigm for our profession. J Pharm Pract 2020; 33: 176–182.

Adunlin

Murphy

Manis

COVID-19: how can rural community pharmacies respond to the outbreak? J Rural Health. Epub ahead of print 30 May 2020. DOI: 10.1111/jrh.12439

Kimber

Peterson

GM.

Telepharmacy – enabling technology to provide quality pharmacy services in rural and remote communities. J Pharm Pract Res 2006; 36: 128–133.

Brown

Scott

Friesner

, et al. Impact of telepharmacy services as a way to increase access to asthma care. J Asthma 2017; 54: 961–967.

Schneider

PJ.

Evaluating the impact of telepharmacy. Am J Heal Pharm 2013; 70: 2130–2135.

10.

Garrelts

Gagnon

Eisenberg

, et al. Impact of telepharmacy in a multihospital health system. Am J Heal Pharm 2010; 67: 1456–1462.

11.

Lam

Rose

Telepharmacy services in an urban community health clinic system. J Am Pharm Assoc 2009; 49: 652–659.

12.

Friesner

Scott

Rathke

, et al. Do remote community telepharmacies have higher medication error rates than traditional community pharmacies? Evidence from the North Dakota Telepharmacy Project. J Am Pharm Assoc 2011; 51: 580–590.

13.

Gross

MacDougall

Roles of the clinical pharmacist during the COVID-19 pandemic. J Am Coll Clin Pharm 2020; 3: 564–566.

14.

Zheng

S-Q

Yang

Zhou

P-X

, et al. Recommendations and guidance for providing pharmaceutical care services during COVID-19 pandemic: a China perspective. Res Social Adm Pharm. Epub ahead of print 26 March 2020. DOI: 10.1016/j.sapharm.2020.03.012

15.

General Pharmaceutical Council. Update on new legislation relating to controlled drugs during the COVID-19 pandemic, https://www.pharmacyregulation.org/news/update-new-legislation-relating-controlled-drugs-during-covid-19-pandemicast (2020, accessed 29 September 2020).

16.

Baldoni

Pallotta

Traini

, et al. A survey on feasibility of telehealth services among young Italian pharmacists. Pharm Pract (Granada) 2020; 18: 1926.

17.

Department of Health AD. Remote Healthcare Platform, https://doh.gov.ae/en/covid-19/Remote-Healthcare-Platform (2020, accessed 29 September 2020).

18.

Dubai Health Authority. Standards for Telehealth Services, https://services.dha.gov.ae/sheryan/wps/portal/home/circular-details?circularRefNo=CIR-2019-00000368&isPublicCircular=1&fromHome=true (2020, accessed 29 September 2020).

19.

Collins

Moles

RJ.

Management of respiratory disorders and the pharmacist’s role: cough, colds, and sore throats and allergies (including eyes). Encyclopedia of pharmacy practice and clinical pharmacy. Cambridge, MA: Elsevier Academic Press, 2019, pp.282–291.

20.

Botrugno

Telemedicine in daily practice: addressing legal challenges while waiting for an EU regulatory framework.

Health Policy Technol 2018; 7: 131–136.

21.

Comer

Furr

Cooper-Vince

, et al. Rationale and considerations for the Internet-based delivery of parent–child interaction therapy. Cogn Behav Pract 2015; 22: 302–316.

22.

Crico

Renzi

Graf

, et al. mHealth and telemedicine apps: in search of a common regulation. Ecancermedicalscience 2018; 12: 853.

23.

Baldoni

Amenta

Ricci

Telepharmacy services: present status and future perspectives: a review.

Medicina (Kaunas) 2019; 55: 327.

24.

Raoul Bell Nils Brandenburg Axel Buchner

JH.

G*Power: Statistical Power Analyses for Windows and Mac, https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html (2007).

25.

Poudel

Nissen

LM.

Telepharmacy: a pharmacist’s perspective on the clinical benefits and challenges. Integr Pharm Res Pract 2016; 5: 75–82.

26.

Ashcroft

Quinlan

Blenkinsopp

Prospective study of the incidence, nature and causes of dispensing errors in community pharmacies. Pharmacoepidemiol Drug Saf 2005; 14: 327–332.

27.

Franklin

O’Grady

Dispensing errors in community pharmacy: frequency, clinical significance and potential impact of authentication at the point of dispensing. Int J Pharm Pract 2007; 15: 273–281.

28.

Hansen

LB.

Medication errors.

Am J Pharm Educ 2007; 71: 59.

29.

Abdel-Qader

Al Meslamani

Lewis

, et al. Incidence, nature, severity, and causes of dispensing errors in community pharmacies in Jordan. Int J Clin Pharm. Epub ahead of print 17 August 2020. DOI: 10.1007/s11096-020-01126-w.

30.

Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19) 2020 interim case definition, https://wwwn.cdc.gov/nndss/conditions/coronavirus-disease-2019-covid-19/case-definition/2020/ (2020, accessed 29 September 2020).

31.

European Centre for Disease Prevention and Control. Case definition for coronavirus disease 2019 (COVID-19), https://www.ecdc.europa.eu/en/covid-19/surveillance/case-definition (2020).

32.

Margusino-Framiñán

Illarro-Uranga

Lorenzo-Lorenzo

, et al. Pharmaceutical care to hospital outpatients during the COVID-19 pandemic. Telepharmacy. Farm Hosp 2020; 44: 61–65.

33.

Sankaranarayanan

Murante

Moffett

LM.

A retrospective evaluation of remote pharmacist interventions in a telepharmacy service model using a conceptual framework. Telemed J E Health 2014; 20: 893–901.

34.

Wakefield

Ward

Loes

, et al. Implementation of a telepharmacy service to provide round-the-clock medication order review by pharmacists. Am J Heal Pharm 2010; 67: 2052–2057.

35.

McFarland

Telepharmacy for remote hospital inpatients in north-west Queensland. J Telemed Telecare 2017; 23: 861–865.

36.

Poulson

Nissen

Coombes

Pharmaceutical review using telemedicine–a before and after feasibility study. J Telemed Telecare 2010; 16: 95–99.

37.

Margusino-Framiñán

Cid-Silva

Castro-Iglesias

, et al. Teleconsultation for the pharmaceutical care of HIV outpatients in receipt of home antiretrovirals delivery: clinical, economic, and patient-perceived quality analysis. Telemed J E Health 2019; 25: 399–406.

38.

Nielsen

Jacobsgaard

, et al. Chat-based telepharmacy in Denmark: design and early results. Int J Pharm Pract 2015; 23: 61–66.

39.

Alfaar

Kamal

Abouelnaga

, et al. International telepharmacy education: another venue to improve cancer care in the developing world. Telemed J E Health 2012; 18: 470–474.

40.

Young

Havican

Griesbach

, et al. Patient And phaRmacist Telephonic Encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study. Telemed J E Health 2012; 18: 427–433.

41.

Margolis

Young

Lis

, et al. A telepharmacy intervention to improve inhaler adherence in veterans with chronic obstructive pulmonary disease. Am J Health Syst Pharm 2013; 70: 1875–1876.

42.

Casey

Sorensen

Elias

, et al. Current practices and state regulations regarding telepharmacy in rural hospitals. Am J Heal Pharm 2010; 67: 1085–1092.

43.

Scott

Friesner

Rathke

, et al. Differences in medication errors between central and remote site telepharmacies. J Am Pharm Assoc (2003) 2012; 52: e97–104.

44.

Young

Telepharmacy project aids North Dakota’s rural communities. Am J Health Syst Pharm 2006; 63: 1779–1780.

45.

Woodall

SC.

Remote order entry and video verification: reducing after-hours medication errors in a rural hospital. Jt Comm J Qual Saf 2004; 30: 442–447.

46.

Boon

AD.

Telepharmacy at a critical access hospital. Am J Health Syst Pharm 2007; 64: 242–244.

47.

Abdel-Qader

Al Meslamani

El-Shara’

, et al. Investigating prescribing errors in the emergency department of a large governmental hospital in Jordan. J Pharm Heal Serv Res Epub ahead of print 4 August 2020. DOI: 10.1111/jphs.12376

48.

Abdel-Qader

Ismael

Al Meslamani

, et al. The role of clinical pharmacy in preventing prescribing errors in the emergency department of a governmental hospital in Jordan: a pre–post study. Hosp Pharm Epub ahead of print 25 July 2020. DOI: 10.1177/0018578720942231

49.

Nittari

Pallotta

Pirillo

, et al. Evaluation of medical prescriptions and off-label use on board ships to improve healthcare quality. Eur Rev Med Pharmacol Sci 2018; 22: 4392–4400.

50.

Masnoon

Shakib

Kalisch-Ellett

, et al. What is polypharmacy? A systematic review of definitions. BMC Geriatr 2017; 17: 230.