Drug Related Problems in Type-2-Diabetes Mellitus with and Without Cardiovascular Diseases: A Systematic Review and Meta-Analysis
DeepthiEnumula1, Muhammed Rashid 2, Sushmitha Sharma 3, GirishThunga4, Shivashankar KN 5, Leelavathi D Acharya 6
1Research scholar, Department of Pharmacy Practice, Manipal college of Pharmaceutical sciences, Manipal Academy of Higher Education, Manipal-576104, Karnataka, India
2Research scholar, Department of Pharmacy Practice, Manipal college of Pharmaceutical sciences, Manipal Academy of Higher Education, Manipal-576104, Karnataka, India
3Pharm D Intern, Department of Pharmacy Practice, Manipal college of Pharmaceutical sciences, Manipal Academy of Higher Education, Manipal-576104, Karnataka, India
4Assistant Professor- selection grade, Department of Pharmacy Practice, Manipal college of Pharmaceutical sciences, Manipal Academy of Higher Education, Manipal-576104, Karnataka, India
5Department of Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal- 576104, Karnataka, India
6Associate Professor, Department of Pharmacy Practice, Manipal college of Pharmaceutical sciences, Manipal Academy of Higher Education, Manipal-576104, Karnataka, India
ABSTRACT
Background: Drug related problems (DRPs) are more prevalent among the type-2-diabetes mellitus (T2DM) patients especially because of related comorbidities and polypharmacy.
Objective: We aimed to quantify the prevalence of different types of DRPs among the T2DM patients with or without cardiovascular diseases (CVD) through a systematic review.
Methods: PubMed/MEDLINE, Scopus and the Cochrane Library were searched to identify the literature till September 2019 from inception. Reference list of all included studies were also searched for additional relevant studies. Studies which assessed the DRPs in T2DM patients with or without CVD published in English language were included in our review. Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields were used to check the risk of bias. Two authors were independently involved in study selection, data extraction and quality assessment of the studies and disagreements were resolved by reconciliation or by consulting a third reviewer.
Results: A total of 34 out of 407 studies considered for the review. The overall prevalence of untreated indications, treatment without indication, inadequate dose, over dose, ineffective treatment, drug interactions and adverse drug reactions was found to be 14.96% (95% Confidence Interval [CI]: 11.86-18.05; 25 studies);
8.54% (95% CI: 6.82-10.27; 23studies); 8.94% 95% CI: 7.11-10.78; 23 studies); 9.20% (95% CI: 3.03-15.37;
23 studies); 17.53% (95% CI: 12.92-22.14; 9 studies); 10.58% (95% CI: 8.66-12.50; 24 studies) and 12.68%
(95% CI: 10.52-14.83; 28 studies), respectively. Moreover, DRPs were higher among the T2DM patients with CVD than the patients with T2DM alone. The quality of the included studies appeared to be moderate to high.
Conclusion: Our findings indicate that DRPs were higher among the T2DM patients with CVD than the patients with T2DM alone. There is a need of multi-disciplinary treatment approach to control the prevalence of DRPs.
Prospero registration ID: CRD42020154376
1.Introduction
The latest data from International Diabetes Federation showed that the global prevalence of diabetes mellitus [DM] has reached to 463 million in 2019 and is still undergoing a rapid increase by 2045 to 700 million where in India the prevalence of diabetes was 88 million in 2019 and may increase up to 153 million by 2045[1]. DM is a chronic, progressive systemic metabolic disorder marked by hyperglycaemia. It is associated with abnormalities in carbohydrate, fat, and protein metabolism and results in chronic complications including microvascular [neuropathy, nephropathy, retinopathy] and macrovascular disorders [cardiovascular, cerebrovascular, peripheral vascular diseases] which leads to tissue and organ damage[2]. DM patients are often
accompanied by hypertension and this comorbid condition may lead to serious cardiovascular complications such as heart attack, stroke, and kidney failure[3]. The illness and its complexities experienced by DM patients requires polypharmacy [various medication treatment] which thus can tranquilize drug related problems [DRPs], for example, drug interactions, ADRs, medicine errors, which could lessen levels of prescription adherence[4,5]. A DRP can be defined as any event or circumstances involving the drug treatment, which potentially interferes with the desired health outcomes[3,6]. If DRP's are not solved it may increase Re-hospitalizations, length of hospital stays and expanded financial weight to the patients[6]. However, other factors that may increase the risk of DRPs among the hospitalized DM patients are poor lipid control, cardiovascular disease, renal impairment and the duration of hospital stay[7] . Several studies have been published on DRPs among T2DM with or without cardiovascular diseases [CVD]
globally. However, there are no systematic review and meta-analysis done so far, thus our study aims to identify the prevalence rate on types of DRPs in T2DM with or without CVD and tends to provide evidence based approach toreduce the number of DRPs while filling the prescription to the T2DM patients with comorbidities.
2. Materials And Methods 2.1 Protocol registration and reporting
The protocol for this study was already registered in PROSPERO, The International Prospective Register of Systematic Reviews with a registration Number: CRD42020154376 [8]. This review was reported based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses [PRISMA] guidelines for evidence synthesis[9].
2.2 Criteria for inclusion of studies
The analytical studies [interventional and observational] which addressed the DRPs among T2DM patients with or without CVD published in English language studies were considered for our review. Any descriptive studies, reviews, commentaries, editorials, news and conference proceedings were excluded.
2.3 Data sources and search strategy
The literature search was carried out using the following keywords: drug-related problem, DRP, type 2 Diabetes mellitus, type 2 Diabetes with cardiovascular diseases. These keywords were used to search databases, including MEDLINE/PubMed, The Cochrane Library and Scopus for the published studies from inception to September 2019. Any additional published or unpublished studies were searched by checking the references of the included studies. Moreover, Google Scholar, Open Grey and ProQuest were also searched for the grey literature.
2.4 Study selection and data extraction 2.4.1 Study Selection
Title and abstract screening followed by full-text screening of all the retrieved studies was done by two independent reviews [DE and SS] against the pre-defined criteria. Any disagreements in
the study selection were resolved by the discussion among the reviewers or by the third reviewer [MR].
2.4.2 Data extraction
Data extraction was performed using a pre-framed data extraction sheet by two independent researchers [DE and SS]. The following variables was extracted from the included studies which includes participants’ demographic characteristics, study design, setting, and duration, study population, author/year of publication/ country of study origin, methods of analysing T2DM with or without CVD, characteristics of DRP [prevalence, types and most common drug classes], DRP risk factors, and DRP Classification system used. Any disagreements during the data extraction was settled through consensus or the discussion with a third reviewer [MR].
2.5 Risk of Bias and Quality Assessment
Methodological quality of each included study were assessed by 2 independent reviewers [DE and SS] using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields [10] , a 14-item measurement tool used to assess the methodological quality of the studies included in a systematic review. Each item/question was scored as 2 [if the response was ‘yes’], 1 [if the response was ‘partial’], or 0 [if the response was ‘no’]. Questions that were not applicable to a particular study were marked as ‘n/a’ and were excluded from the calculation of the summary score, which was calculated for each paper by summing the total score obtained for all items and dividing it by the total possible score. A higher summary score indicated a lower risk of bias and better study quality. Disagreements were resolved by the discussion with a third reviewer [MR/GT].
2.6 Strategy for data synthesis
All the extracted information pertaining to the study and DRP characters and was synthesised qualitatively and presented in a narrative manner. The meta-analysis was performed in Review Manager Software[11] if there is enough quantitative data. The prevalence was extracted as number with percentage and pooled result was presented in the form of percentage along with its 95% confidence interval [CI]. I2 statistics was used to assess the measure of inconsistency. The random effect model was applied as there was significant heterogeneity [I2>50%]. A subgroup analysis depends on the presence or absence of CVD with T2DM. No other subgroup analysis was possible because of insufficient data. Publication bias was detected using funnel plot and statistical significance was assessed using the Egger’s and Begg’s test.
3. Results 3.1 Search and study selection process
A total of 407 studies were identified in the search and 328 non-duplicate studies of them were subjected for initial screening. Among those 247 records were excluded based on the title and abstracts and 81 full-text articles were assessed for the inclusion. Finally, a total of 34 eligible studies were comprising of 17983 participants were considered for the synthesis and analysis. A detailed process of study selection was described in Figure 1.
3.2 Data Summary of included studies
The overall duration of included studies ranged from 3 days[12] to 28 months[13] with study participants of T2DM. The cardiovascular comorbidities along with T2DM reported in our studies were hypertension, angina pectoris, Ischemic heart disease, dyslipidaemia, heart failure.
All the included studies have varied study designs such as prospective, interventional, randomized controlled trail, retrospective and cross-sectional. The commonly used classifying system was PCNE [Pharmaceutical care network Europe of varied versions] among the included studies. The detailed information on study characteristics is represented in Table 1.
Table 1: Characteristics of included studies
3.3 Quality evaluation of included studies
The quality evaluation of 34 studies scores ranged from 80% to 100%, Twenty studies had the maximum score of 100 [4,7,20–28,12–19]. Overall, the quality of the included studies was satisfactory. The quality scores of each study are presented in Table 2.
Table 2: Quality evaluation of included studies
3.4 Meta-analysis of Prevalence rate on types of DRPs among included studies 3.4.1 Untreated indication
A total of 25 studies addressed the untreated indication, the overall prevalence of untreated indication appeared to be 14.9% [95% CI: 11.86-18.05; I2=99%]. There was a substantial heterogeneity among the studies. However, heterogeneity was not reduced by subgroup analysis.
Pooled prevalence of untreated indication found to be 12.34% [95% CI: 5.90-18.78 I2 =99%; 10 studies] among patients with T2DM only and 16.84% [95% CI: 11.69-21.99 I2=99%, 15 studies]
among those with T2DM and CVD which is represented in Figure 2.
3.4.2 Ineffective provided drug
Pooled analysis of 9 studies estimated that, pooled prevalence of ineffective drug used was 17.53% [95% CI: 12.92-22.14, I2=99%] with a substantial heterogeneity. The overall prevalence of ineffective drug use was 17.21% [95% CI: 0.04-34.39; I2 =98%; 3 studies] and 18.90% [95%
CI: 12.76-25.04, I2=99%; 6 studies] among the patients with T2DM only and T2DM with CVD, respectively which is represented in Figure 3.
3.4.3 Inadequate dose
Meta-analysis of 23 studies demonstrated an overall prevalence of inadequate dose was 8.94%
[95% CI: 7.11-10.78; I2=97%], which was almost similar among the T2DM patients [8.23%;
95% CI: 5.48-10.97, I2=95%; 10 studies] and T2DM with CVD [9.45%; 95% CI: 6.81-12.10, I2=97%; 13 studies] which is represented in Figure 4.
3.4.4 Adverse drug reactions
Summary of 28 studies estimated an overall ADR prevalence of 12.68%; [95% CI: 10.52-14.83;
I2=97%], which was comparable in case of patients with T2DM [11.86%; 95% CI: 8.82-14.91,
I2=91%; 12 studies] and T2DM with CVD [13.25%; 95% CI: 10.32-16.19, I2=98%; 16 studies]
patientswhich is represented in Figure 5.
3.4.5 Drug interactions
An estimation of 24 studies addressed the drug interactions, which yielded an overall prevalence of 10.58; [95% CI: 8.66-12.50; I2=99%], which was lesser among the T2DM [8.91%; 95% CI:
6.67-11.16; I2=98%; 13 studies] and higher T2DM with CVD [11.87%; 95%CI: 7.82-15.61, I2=99%; 11 studies], respectively which is represented in Figure 6.
3.4.6 Overdose
The overall prevalence of high dose was observed to be 9.20 [95% CI: 3.03-15.37; I2=100%; 23 studies], which was higher than the T2DM patients [5.73%; 95% CI: 3.03-8.44, I2=97%; 8 studies] and lower than the T2DM with CVD patients [10.93%; 95% CI: 0.94-20.92; I2=100%;
15 studies] which is represented in Figure 7.
3.4.7 Unnecessary drug treatment
Pooled analysis of 23 studies demonstrated 8.54% [95% CI]: 6.82-10.27; I2=98%] of unnecessary drug treatment, which was higher among the patients with T2DM [10.45%; 95% CI: 7.05-13.85, I2=99%; 9 studies] and lower among the T2DM with CVD [7.77%; 95% CI: 5.24-10.31; I2=98%;
14 studies] patients, which is represented in Figure 8.
3.5 Publication bias
An obvious asymmetry was observed with the visual inspection of funnel plot as represented in Figure 9. However, it was not significant by statistical analysis through Egger’s [P=0.793] and Begg’s [P=0.186] test.
4. Discussion
The overall mean age of the included studies in this review ranged from 40-75 years. A total of 36 studies with type 2 diabetes with or without cardiovascular diseases comprising of 18,190 participants were included in this study. Among 36 studies, 34 studies with 17,983 participants data was pooled for metanalysis on prevalence rate of different types of drug related problems like untreated indication, ineffective provided drug, inadequate dose, adverse drug reactions, drug interactions, high dose and unnecessary drug treatment. A total of 63,637 DRPs were reported from the included studies. Type 2 diabetic patients were commonly accompanied with hypertension comorbidity which increases the risk of other cardiovascular and cerebrovascular diseases [3] where multiple drugs are to be prescribed for the patients which results in one or the other drug related problems leading to increased hospital stay and economic burden to the patients. Polypharmacy was closely linked with drug related problems which was proved in one of the studies done Malaysia in 2013 emphasizing on significant relationship between polypharmacy and drug interactions [18].
The top most DRPs from included studies were Untreated indication and no optimal therapy reported by Ayele et al[29], Hartuti et al reports that in their study the most common DRPs were
drug interactions and inadequate dose [30], need for additional drug therapy as reported by Ali et al[26], ineffective provided drug and need of additional drug as reported by Yimama et al[31], drug dose too low as reported by Yschung et al[32], unnecessary use of drugs and improper drug selection are the top most DRPs as reported by Shareef et al [15], drug choice problems and drug interactions were the top most DRPs as reported by Gangwar et al[33], Ahmad et al reports that untreated indication and unnecessary use of drugs were most prominent DRPs[16], potential drug -drug interactions were predominantly reported in the study conducted by Huri et al [17], drug dosing and drug interactions [18], potential drug interactions as reported by Eichenberger et al[34], Adverse drug reactions and wrong dose prescribed were commonly DRPs reported by Granas et al [35], therapy failure and drug choice problems as reported by Roozendaal et al [19], inappropriate use of medicines by the patients was the top most DRPs reported by the study conducted by Haugbolle et al [20], ineffective provided drug and unnecessary use of drugs were the most common DRPs reported by Setter et al[36], drug interactions as reported by Hussein et al [37], untreated indication and drug interactions were top most DRPs reported by Blanc et al [21], unnecessary use of drugs and high dose were DRPs reported in a study done by Benson et al [22], Kovacevic et al reported that ineffective provided drug is the most predominant DRPs in their study[23], additional drug therapy and unnecessary use of drugs were the highest DRPs reported by Westberg et al [24] , untreated indication and drug interactions were the top most DRPs reported in a study conducted by Zazuli et al [3], Steele et al reported that medication under use and unnecessary use of drugs were the commonest DRPs in their study[25], adverse drug reactions and inadequate dose were the most top most DRPs reported by Mendonca et al[13], need for additional drugs and untreated conditions were the commonest DRPs reported by Al-Azzam et al [12], in a study conducted by Ali et al drug interactions were predominant DRPs in their study [26] , untreated indication are top most DRPs reported by Stewart et al [38], the top most DRPs like ineffective provided drug and adverse drug reactions as reported by Kempen et al [27], adverse drug reactions and untreated conditions were the top most DRPs reported by Chua et al [39], Touchette et al reports that adverse drug reactions are the top most DRPs in their study [28], need for additional drug therapy was the commonest DRPs reported in a study conducted by Hall et al[40], high dose and adverse drug reactions were the top most DRPs reported by Scott et al[41], need for additional drug and adverse drug reactions were the most common DRPs reported by Kassam et al[4], Hence, multiple drugs in varied comorbid condition leads to increase risk of DRPs.
The overall pooled analysis on prevalence rate of different types of drug related problems in this study ranged from 8.54% [unnecessary use of drugs] to 17.53% [ineffective provided drug].
5. Conclusions
Polypharmacy results in increased risk of DRPs resulting in inappropriate clinical outcomes therefore regular monitoring and optimizing the drug therapy is needed if patients are with multiple diseases. Our findings indicate that DRPs were higher among the T2DM patients with CVD than the patients with T2DM only. Still, it can be reduced with multi-disciplinary treatment approach
6. Abbreviations
T2DM, type 2 diabetes; CVD, cardiovascular diseases; DRPs, drug related problems; PRISMA,
preferred reporting items for systematic reviews and meta-analyses; EMBASE, excerptamedica database; MEDLINE, medical literature analysis and retrieval system online; CI, confidence interval.
7. Acknowledgements:
Authors would like to thank the staff of department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, MAHE for giving timely suggestions and support for conducting this review.
CONFLICTS OF INTEREST: None of the authors declares conflicts of interest References
[1] IDF Atlas 9th edition and other resources [Internet]. [cited 2020 May 5]. Available from:
https://www.diabetesatlas.org/en/resources/?gclid=EAIaIQobChMI1pqKjPeb6QIVmQ VyCh3y5wbREAAYASAAEgLa2vD_BwE
[2] Type 2 Diabetes - Symptoms, Causes, Treatment [Internet]. [cited 2020 May 5].
Available from: https://www.diabetes.org/diabetes/type-2
[3] ZulfanZazuli, AzmiRohaya IKA. Drug‑related problems in Type 2 diabetic patients with hypertension in Cimahi, West Java, Indonesia: A prospective study. Int J Green Pharm. 2017;11(2).
[4] Kassam R, Meneilly GS. Role of the Pharmacist on a Multidisciplinary Diabetes Team.
Can J Diabetes [Internet]. 2007;31(3):215–22. Available from:
http://dx.doi.org/10.1016/S1499-2671(07)13008-2
[5] Gudi SK, Kashyap A, Chhabra M, Rashid M, Tiwari KK. Impact of pharmacist-led home medicines review services on drug-related problems among the elderly population: a systematic review. Epidemiol Health. 2019;41:e2019020.
[6] Hepler CD, Strand LM. Opportunities and responsibilities in pharmaceutical care. Am J Hosp Pharm. 1990;47:533–43.
[7] Al-Taani GM, Al-Azzam SI, Alzoubi KH, Elhajji FWD, Scott MG, Alfahel H, et al.
Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach. Drug Healthc Patient Saf. 2017;9:65–70.
[8] Enumula D, Rashid M, Acharya LD, Thunga G, N SSK, Enumula D, et al.
International prospective register of systematic reviews Drug-related problems in type 2 diabetes mellitus with or without cardiovascular diseases : a systematic review protocol Citation Review question Participants / population Intervention ( s ), exposu.
2020;2–5.
[9] Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ. 2009;339(7716):332–6.
[10] . Kmet LM, Lee RC CL. Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Edmonton. 2004.
[11] RevMan | Cochrane Training [Internet]. [cited 2020 May 21]. Available from:
https://training.cochrane.org/online-learning/core-software-cochrane-reviews/revman [12] Al-azzam SI, Alzoubi KH, Alefan Q, Alzayadeen RN. Evaluation of the types and
frequency of drug-related problems and the association with gender in patients with chronic diseases attending a primary health care center in Jordan. Int Health. 2016;1–4.
[13] Mendonça S de AM, Melo2 AC, Pereira2 GCC, Santos3 DM de SS dos, Grossi2 EB, Boas M do CV, et al. Clinical outcomes of medication therapy management services in primary health care. Brazilian J Pharm Sci. 2016;52(3):365–73.
[14] sayeri al-azzam, Karem h alzoubi ,salahabuRuz Q alefan. Drug-related problems in a sample of outpatients with chronic diseases : a cross-sectional study from Jordan.
TherClin Risk Manag. 2016;12:233–9.
[15] Shareef J, Fernandes J, Samaga L. Assessment of clinical pharmacist interventions in drug therapy in patients with diabetes mellitus in a tertiary care teaching hospital.
Diabetes MetabSyndrClin Res Rev [Internet]. 2016;10(2):82–7. Available from:
http://dx.doi.org/10.1016/j.dsx.2015.09.017
[16] Ahmad A, Mast MR, Hugtenburg JG. Identification of drug-related problems of elderly patients discharged from hospital. Patient Prefer Adherence. 2014;8:155–65.
[17] Huri HZ, Ling LC. Drug-related problems in type 2 diabetes mellitus patients with dyslipidemia. BMC Public Health. 2013;13(1192):1–13.
[18] Huri HZ, Wee HF. Drug related problems in type 2 diabetes patients with hypertension : a cross-sectional retrospective study. BMC EndocrDisord [Internet].
2013;13(2):1–12. Available from: BMC Endocrine Disorders
[19] Van Roozendaal BW, Krass I. Development of an evidence-based checklist for the detection of drug related problems in type 2 diabetes. Pharm World Sci.
2009;31(5):580–95.
[20] Stig L, Ellen HÆ, Sørensen W. Drug-related problems in patients with angina pectoris , type 2 diabetes and asthma – interviewing patients at home. Pharm World Sci.
2006;28:239–47.
[21] A.L.Blanc, B.Guignard, A D, O. Grosgurin CM, C.Samer, P.Bonnabry. Prevention of potentially inappropriate medication in internal medicine patients : A prospective study using the electronic application PIM- - Check. J Clin Pharm Ther. 2018;(March):1–7.
[22] Benson H, Lucas C, Kmet W, Benrimoj SI, Williams K. Pharmacists in general practice : a focus on drug ‑ related problems. Int J Clin Pharm [Internet].
2018;(0123456789). Available from: https://doi.org/10.1007/s11096-018-0617-9 [23] Kovačević SV, BranislavaMiljković MĆ, Milena Kovačević , BojanaGolubović ,
MarijaJovanović Katarina Vučićević JJ de G. Evaluation of drug ‐ related problems in older polypharmacy primary care patients. J EvalClinPract. 2017;(February):1–6.
[24] Westberg SM, Derr SK, Weinhandl ED, Adam TJ, Brummel AR, Lahti J, et al. Drug Therapy Problems Identified by Pharmacists Through Comprehensive Medication Management Following Hospital Discharge. J Pharm Technol 2017. 2017;33(3):96–
107.
[25] Steele KM, Ruisinger JF, Bates J, Prohaska S, Melton BL, Hipp S. Research and
Reports. Consult Pharm. 2016;31(10):598–605.
[26] Ali I, Khan JZ, Khan AU, Ullah I, Ahmad F. Pharmacotherapy evaluation of diabetic patients in ward of general medicine, Northwest General Hospital & research centre, a case study from Khyber Pakhtunkhwa, Pakistan. Pharmacologyonline.
2015;1(April):104–8.
[27] Kempen TGH, Hoogland P, Liu Y, Bouvy ML. Large scale implementation of clinical medication reviews in Dutch community pharmacies : drug-related problems and interventions. Int J Clin Pharm. 2014;36:630–5.
[28] Touchette DR, Masica AL, Dolor RJ, Schumock GT, Choi YK, Kim Y, et al. Safety- focused medication therapy management: A randomized controlled trial. J Am Pharm
Assoc [Internet]. 2012;52(5):603–12. Available from:
http://dx.doi.org/10.1331/JAPhA.2012.12036
[29] Ayele Y, Melaku K, Dechasa M, Ayalew MB, Horsa BA. Assessment of drug related problems among type 2 diabetes mellitus patients with hypertension in HiwotFana Specialized University Hospital ,Harar , Eastern Ethiopia. BMC Res Notes [Internet].
2018;11(728):1–5. Available from: https://doi.org/10.1186/s13104-018-3838-z
[30] Hartuti S, Nasution A, Syafril S. The Effect of Drug-Related Problems on Blood Glucose Level in the Treatment of Patients with Type 2 Diabetes Mellitus.
2019;7(11):1798–802.
[31] Yimama M, Jarso H, Desse TA. Determinants of drug ‑ related problems among ambulatory type 2 diabetes patients with hypertension comorbidity in Southwest Ethiopia : a prospective cross sectional study. BMC Res Notes [Internet].
2018;11(679):1–6. Available from: https://doi.org/10.1186/s13104-018-3785-8
[32] Chung AYS, Anand S, Wong ICK, Tan KCB, Wong CFF, Chui WCM, et al.
Improving medication safety and diabetes management in hongkong: A multidisciplinary approach. Hong Kong Med J. 2017;23(2):158–67.
[33] Gangwar SS, Monisha N, Nachiya J, Parimalakrishnan S, Narasingarao K, Singh SP.
Impact of medication and psychological behaviour assessment by community pharmacists in type 2 diabetes mellitus patients after hospital stay. Afr Health Sci.
2014;14(3):539–50.
[34] Eichenberger PM, Haschke M, Lampert ML, Hersberger KE. Drug-related problems in diabetes and transplant patients : an observational study with home visits. Int J Clin Pharm. 2011;33:815–23.
[35] Granas AG, Berg C, Hjellvik V, Haukereid C, Kronstad A, Blix HS, et al. Evaluating categorisation and clinical relevance of drug-related problems in medication reviews.
Pharm World Sci. 2010;32(3):394–403.
[36] Setter SM, Corbett CF, Cook D, Johnson SB. Exploring the clinical pharmacist’s role in improving home care for patients with diabetes. Home Care Provid. 2000;5(5):185–
92.
[37] Hussein Rand Nidal, Ibrahim OM. Assessment of treatment-related problems and associated factors among hospitalized patients in the United Arab Emirates : a
retrospective study. J Pharm Heal Serv Res. 2018;1–6.
[38] Stewart AL, Snodgrass J, Schontz M, Parekh M. A student pharmacist-led medication reconciliation service and its impact on the identi fi cation of drug-related problems in an ambulatory clinic. Curr Pharm Teach Learn [Internet]. 2015;1–9. Available from:
http://dx.doi.org/10.1016/j.cptl.2015.06.020
[39] Chua SS, Kok LC, Yusof FA, Tang GH, Wen S, Lee H, et al. Pharmaceutical care issues identified by pharmacists in patients with diabetes , hypertension or hyperlipidaemia in primary care settings. BMC Health Serv Res. 2012;12(388):1–10.
[40] Hall DL, Pater KS. Original Article Implementation of a Medication Therapy Management Program in a Hospital-Based Outpatient Pharmacy. Hosp Pharm.
2011;46(July):512–8.
[41] Scott DM, Dewey MW, Johnson TA, Kessler ML, Friesner DL. Preliminary Evaluation of Medication Therapy Management Services in Assisted Living. Consult Pharm. 2010;25(5):305–19.
[42] Abu RK, Mukattash TL. Drug-related problems and health-related quality of life in outpatients with type 2 diabetes : a cross-sectional study from Jordan. 2019;
Table 1: Characteristics of included studies
S . n o
Author, year, Country Study design Study Period
Samp le size
Mean age Study participants
Total no. of DRPS
DRP Classification used
Re f
1
Harthuti, 2019, Indonesia Prospective Observational study
4 months 81 51-60 T2DM 68 Cipolle
classification
[3 0]
2 Ayele, 2018, Harar city Retrospective cross sectional
4months 203 40-60 T2DM+HTN 364 PCNE V8.02 [2
9]
3 Yimama, 2018, Ethiopia Prospective cross - sectional study
2 months 300 54.44 ± 11.68
T2DM+HTN 494 Cipolle classification
[3 1]
4 Chung ,2017, Hong Kong
ProspectiveObservational study
17 months 522 75.2 ± 5.4 T2DM 417 PCNE V5.01 [3
2]
5 Al-Azzam, 2016, Jordan Prospective Cross- sectional study
15 months 2898 56.59±13.
5
T2DM 32348 Nil [1
4]
6 Shareef, 2015, Mangalore
Prospective Interventional 10 months 151 61-70 T2DM 189 Hepler and strand
[1 5]
7 Gangwar,2014, Kanpur, Prospective randomized controlled intervention
12 months 723 20-75 T2DM 723 PCNE [3
3]
8 Ahmad, 2014 ProspectiveObservational 24 months 340 60-95 T2DM 992 PCNE [1
Netherlands, study 6]
9 ZamanHuri, 2013, Malaysia
Retrospective cross- sectional
23 months 208 61±13.3 T2DM+DYS 406 PCNE [1
7]
1 0
ZamanHuri ,2013, Malaysia
Retrospective cross- sectional
23 months 200 62.3±12.7 T2DM+HTN 387 PCNE V5.01 [1 8]
1 1
Eichenberg, 2011, Switzerland
Prospective cross- sectional, observational
24 months 76 71.4 ± 8.1 T2DM WITH RENAL TRANSPAL NT
54 PCNE V5.01 [3
4]
1 2
Granas, 2010, Norway, Prospective interventional study
Not mentioned
73 62 years T2DM 88 PCNE V5.01 [3
5]
1 3
Roozendaal,2009, Australia
Retrospective Cross - sectional study
-- 148 61.4±11.8 T2DM 682 PCNE [1
9]
1 4
Haugbolle, 2006, Denmark
Qualitative interview based
-- 155 51-70 T2DM 635 Nil [2
0]
1 5
Setter, 2000, Washington Descriptive survey design -- 105 62 T2DM 105 Nil [3
6]
1 6
Husseina,2018, Egypt
Retrospective Observational study
7 months 278 66.19±
12.90
T2DM+HTN +DYS
1762 PCNE V5.01 [3
7]
1 7
Abu Farha, 2019, Jordan Retrospective cross- sectional study
3 months 91 61.1 T2DM 571 PCNE [4
2]
1 8
Blanc, 2018, Switzerland
Prospective interventional study
2 months 297 67±16 T2DM 909 Nil [2
1]
1 9
Benson,2018, Western Sydney
Multi centric Prospective observational study
6 months 493 67.7 years T2DM+Astha ma
1124 The Second Granada Consensus DRP Classification
[2 2]
2 0
Kovacevic,2017, Serbia
Prospective observational study
4 months 388 72.1±6.3 T2DM+HTN +DYS+
AP+ CA+
Asthma
964 Nil [2
3]
2 1
Al-Taani, 2017, Jordan Multi-centre, cross- sectional
15 months 1494 58.4 T2DM 1494 Hepler and
strand
[7]
2 2
Westberg,2017, Minnesota
Retrospective observational study
24 months 408 67.7 ± 13.8
T2DM+HTN +
1033 Nil [2
4]
COPD+CKD +CA 2
3
Zazuli,2017, Indonesia Prospective Cross- sectional
3 months 90 57.73 years
T2DM+HTN 261 PCNE V5.01 [3]
2 4
Steele, 2016, Kansas City Pre-/post intervention study
5 months 25 76-92 T2DM+HTN
+DYS
85 Nil [2
5]
2 5
Mendonca, 2016, Brazil Retrospective descriptive study
28 months 92 63.0 years T2DM+HTN +DYS
316 Cipolle, Strand and Morley
[1 3]
2 6
Azzam, 2016, Jordan Non-randomized controlled trial
3 days 258 54.4±12.1 T2DM+HTN +DYS
258 Nil [1
2]
2 7
Ali, 2015, Pakistan Prospective observational 3 months 15 54 years T2DM 33 PCNE V6.2 [2 6]
2 8
Stewart, 2015, Putts burg Prospective observational study
12 months 1842 41.5 years T2DM+HTN +Asthama+C OPD+CVD+
Osteoporosis
673 Nil [3
8]
2 9
Kempen, 2013, Netherlands
Retrospective cohort study 9 months 4,579 75.6
±10.9
T2DM+CVD +Osteoporosis
13366 Nil [2
7]
3 0
Chua, 2012, Malaysia Multi centric trail 6 months 477 47.9 years T2DM+DYS 706 PCNE V5.01 [3 9]
3 1
Touchette, 2012, Chicago Randomized controlled clinical trial
25 months 637 74.5 ± 6.6 T2DM+HTN +DYS+HF
1083 PCNE V5.01 [2
8]
3 2
Hall ,2011, Pittsburgh Random screening 18 months 68 57 years T2DM+HTN +DYS+HF+A sthama
170 Nil [4
0]
3 3
Scott, 2010, Minnesota Prospective Cross- sectional, pilot study
11 months 130 86 years T2DM+HTN +CVD+Hyper lipidemia
304 Cipolle and Strand
[4 1]
3 4
Kassam, 2007, Canada Retrospective cohort study 24 months 138 79.6±4.9 T2DM 276 Nil [4]
T2DM: type2 diabetes mellitus, HTN: hypertension, DYS: dyslipidaemia, HF: heart failure, CKD: chronic kidney disease, CA: cardiac arrhythmias, COPD: chronic obstructive pulmonary disease
Table 2: Quality evaluation of included studies
S . N o
Ques tion/
objec tive suffic iently descr ibed?
Stud y desig n evide nt and appr opria te?
Met hod of subj ect/
com pari son gro up sele ctio n or sou rce of info rma tion /inp ut vari able s desc ribe d and app rop riat e?
Subjec t [and compa rison group, if applica ble]
charac teristic s sufficie ntly describ ed?
If interv ention al and rando m alloca tion was possib le, was it descri bed?
If inte rve ntio nal and blin din g of inve stig ator s was poss ible, was it rep orte d?
If inter venti onal and blind ing of subje cts was possi ble, was it repor ted?
Outco me and [if applica ble]
exposu re measur e[s]
well defined and robust to measur ement / misclas sificati on bias?
Means of assess ment reporte d?
S a m pl e si ze a p p ro p ri at e?
An aly tic me th od s de scr ibe d/j ust ifie d an d ap pr op ria te?
Is som e esti mat e of vari anc e is rep orte d for the mai n resu lts?
Co ntr oll ed for co nf ou nd ing
? Re su lts re po rt ed in su ffi cie nt de tai l?
Concl usion suppo rted by the result s?
M a xi m u m p oi nt s
T ot al p oi nt s
Summary of score [Percentage]
R ef
1. 2 2 2 2 N/A N/A N/A 2 2 2 0 N/
A
2 2 2
0 1 8
90% [3 0]
2. 2 2 2 2 N/A N/A N/A 2 2 2 1 0 2 2 2 0
1 8
90% [2 9]
3. 2 2 2 2 N/A N/A N/A 2 2 2 1 N/
A
2 2 2
0 1 9
95% [3 1]
4. 2 2 2 2 N/A N/A N/A 2 2 2 1 N/
A
2 2 2
0 1 9
95% [3 2]
5. 2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 4]
6. 2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 5]
7. 2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 1 2
0 1 9
95% [3 3]
8. 2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 6]
9. 2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 7]
1 0.
2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 8]
1 1.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 1 9
95% [3 4]
1 2.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 1 8
90% [3 5]
1 3.
2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 9]
1 4.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 0]
1 5.
1 2 1 2 N/A N/A N/A 1 0 1 1 N/
A
2 2 2
0 1 3
65% [3 6]
1 6.
2 2 2 2 N/A N/A N/A 2 2 1 2 N/
A
2 2 2
0 1 9
95% [3 7]
1 7.
2 2 2 2 N/A N/A N/A 2 1 2 2 N/
A
2 2 2
0 1 9
95% [4 2]
1 8.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 1]
1 9.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 2]
2 0.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 3]
2 1.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [7
] 2
2.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 4]
2 3.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [3
] 2
4.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 5]
2 5.
2 0 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [1 3]
2 6.
2 1 1 2 N/A N/A N/A 2 1 2 2 N/
A
2 2 2
0 2 0
100
% [1 2]
2 7.
2 0 1 2 N/A N/A N/A 2 1 2 2 N/
A
2 2 2
0 1 8
100
% [2 6]
2 8.
2 1 1 1 N/A N/A N/A 2 1 2 2 N/
A
2 2 2
0 1 6
80% [3 8]
2 9.
2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 7]
3 0.
2 2 2 2 N/A N/A N/A 1 2 2 2 N/
A
2 2 2
0 1 9
95% [3 9]
3 1.
2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [2 8]
3 2.
2 0 2 2 N/A N/A N/A 2 1 2 2 N/
A
2 2 2
0 1 7
85% [4 0]
3 3.
2 1 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 1 9
95% [4 1]
3 4.
2 2 2 2 N/A N/A N/A 2 2 2 2 N/
A
2 2 2
0 2 0
100
% [4
]
0, if the response is ‘no’; 1, if the response is ‘partial’; 2, if the response is ‘yes’; N/A, not applicable
Figure 1. Prisma flowchart of included studies
Figure 2. Metanalysis of Untreated indication
Figure 3. Metanalysis of Ineffective provided drug
Figure 4. Metanalysis of Inadequate dose
Figure 5. Metanalysis of Adverse drug reactions
Figure 6. Metanalysis of Drug interactions
Figure 7. Metanalysis of Overdose
Figure 8. Metanalysis of Unnecessary drug treatment
Figure 9. Funnel plot
