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Epidemiology and Predictors of Drug Therapy Problems among Type 2 Diabetic Patients at Wolaita Soddo University Teaching Hospital, Southern Ethiopia

Hailu Chare Koyra*, Seble Bancha Tuka, Efrata Girma Tufa

Department of Pharmacy, School of Medicine, Wolaita Soddo University, Soddo, Ethiopia

Abstract: Background: Diabetic patients have a significant number of co-morbidities which increases number of medications and complexity of treatment that can finally result in drug therapy problems among these populations. Despite its serious negative impact on health outcomes, there is lack of research evidence on drug therapy problem in the country. Therefore, current study aims to assess epidemiology and predictors of drug therapy problems among adult type 2 diabetic patients at Wolaita Soddo University teaching hospital. Method: Institution-based cross-sectional study was conducted from January to March, 2015, among 243 adult type2 diabetes patients attending their ambulatory care in Wolaita University teaching hospital. Medical record reviews and interviewer-administered questionnaire was used for data collection. Drug therapy problems were identified by using Cipolle’s method which was adapted to diabetic patients and further refined by panel of experts. Bivariate and multivariate logistic regressions were used to identify predictors of drug therapy problems. Results: Out of 243 adult type 2 diabetic patients included, the prevalence of drug therapy problems was 83.1%. Need additional drug, 137(56.37%) and non-compliance 126(51.9%) were the most common types of drug therapy problems. Age ≥ 65 (AOR=9.079; 95% CI: 2.213, 37.241), comorbidity (AOR=7.004; 95% CI: 1.285, 18.194), polypharmacy (AOR =3.311; 95% CI: 1.366, 30.329), and history of hospitalization (AOR=0.403; 95%CI: 0.176, 0.925) were independent predictors of the drug therapy problems. Conclusion: the study showed that drug related problems especially need additional drug or unmet conditions and non-compliance were major challenges for optimal management of type 2 diabetes in the hospital. Hence, the hospital should optimize utilization of statins and antiplatelet for cardiovascular prevention with due emphasis to increase medication adherence of the diabetic patients.

Keywords: drug therapy, diabetes, Wolaita Soddo, Ethiopia

Citation: Hailu Chare Koyra, Seble Bancha Tuka, Efrata Girma Tufa, Epidemiology and Predictors of Drug Therapy Problems among Type 2 Diabetic Patients at Wolaita Soddo University Teaching Hospital, Southern Ethiopia. American Journal of Pharmacological Sciences, 5 (2). 40-48. January 2017. doi:10.12691/ajps-5-2-4

1. Introduction

A drug-therapy problem (DTPs) is as ‘an event or circumstance involving drug therapy that actually or potentially interferes with desired health outcomes. According to Cipolle, DTPs are classified into seven categories including: patients with unmet condition (need additional drug therapy), unnecessary drug therapy, and dose too low, dose too high, adverse drug reaction, ineffective drug therapy and non-compliance. Patients with type 2 diabetes receive a wide range of pharmacotherapeutic agents and are therefore at higher risk to experience DTPs that are associated with negative effects on patient outcomes and have the potential to increase the cost of care [1,2].

Type 2 diabetes which previously is referred to as “noninsulin-dependent diabetes” or “adult onset diabetes,” is a chronic disorder characterized by hyperglycemia and glycosuria. It is the most common type of diabetes affecting 90 to 95% of sufferers and encompasses individuals who have insulin resistance and usually relative insulin deficiency [3].

In recent years, diabetes has evolved to become one of the most serious health concerns in both the developed and developing world. The global increase in prevalence of diabetes has been rapid and alarming. IDF Atlas 6th edition 2013 shows that 382 million people worldwide, or 8.3% of adults, are estimated to have diabetes of which 80% lives in low- and middle-income countries. If this tendency continues without rigorous action to prevent the disease, by 2035, 592 million people, or one adult in 10, will have diabetes. The largest increases will take place in the regions where developing economies are predominant [4].

Since in low and middle income countries, 29% of diabetes deaths occurs among people under the age of 50, compared to 13% in high income countries, it is a great burden for the quality of life of affected individuals, their families and for the country’s socioeconomic structure at large. Compared to the western world, the burden in the developing world, particularly in Africa, is even worse due to late diagnosis and poor access to diabetic care [5]. The cost of management of diabetes mellitus is complex and multidisciplinary, therefore expensive in poor resource countries where majority of the population live below a dollar per day [6].

In most hospitals of Ethiopia, the cost for patient attendance rates and medical admissions are rising for diabetic management. Access to diabetes care in the country also does not meet the increments in the incidences and complications of the disease. Furthermore, studies show that blood glucose levels of diabetic patients still remain high despite the treatment they receive indicating that there is a problem with management of these patients [7,8].Therefore, it is unequivocal that drug therapy problems (DTPs) may account the lion share of the problems in diabetes management in the country. Hence, early identification of types of DTPs and factors associated to them is essential for optimization of diabetes management and can also enable the practitioner in collaboration with the patient to construct a better care plan. Furthermore, resolving as well as preventing the occurrence of DTPs among T2DM patients has tremendous positive impact on improving clinical, humanistic and economic outcomes of the patients. Despite its serious negative impact on health outcomes, there is lack of research evidence on this problem in the country. Therefore, this study aims to assess epidemiology and predictors of drug therapy problems among adult type 2 diabetic patients.

Figure 1. Conceptual frame work of the study

2. Methods

2.1. Study Setting and Period

The study was carried out among patients with type 2 diabetic patients at Wolaita Soddo University Teaching hospital. The Hospital is located 380 km away from the national capital Addis Ababa and 170 km far from the regional capital Hawassa. The teaching hospital was established in 1923 and serving people in catchment area of above 2 million. It is one of the two teaching referral hospitals in the region and it has the total capacity of about 195 inpatient beds. The hospital provides its service to about 1836, 1452 patients per year [14]. Currently there are about 520 type two diabetic patients on their chronic care. The study was conducted from February to April, 2016.

Study design: Institutional based retrospective cross–sectional study was conducted.

Study participants: The study participants were adult type2 diabetes patients who were attending their follow up care in the hospital during the study period.

Inclusion criteria: Type2 diabetes patients who had received at least one ant diabetic medication and on follow up for at least 3 months with their FBS measurements available before data collection were included in the study.

Exclusion criteria: Unwilling patients, age <18 years, critically ill, those with documented psychiatric problems and with gestational diabetes were excluded from the study.

Sample size determination and sampling procedures: A sample size of 243 was calculated using single proportion formula assuming 50% proportion of DTPs (due to absence of similar study in the country) at a 95% confidence limit and 5% margin of error with addition of 10% contingency for nonresponse rate. All type2 diabetes patients coming to the hospital during data collection period and who fulfill the inclusion criteria were consecutively included in the study.

Data collection: Patient medical record review was used to obtain pertinent medical and past and present medication history including subsequent glycemic levels, BP levels, and organ function tests, history of ADR (hypoglycemia), allergy, and presence of comorbidity, duration of diabetes, type, dose and number of drugs used. Structured questionnaire which was translated to the local language for patient interview was used to collect information on medication adherence, socio-demographic, socio-economic and social drug use. The data collection involved six pharmacists and one General practitioner for supervision.

DRPs Identification and classification: The Cipolle’s method of identification and classification was used to identify and assess DTPs in this study [1,2]. The method was refined based on literature review and standard treatment guidelines with further revision, and endorsement by panel of experts including Internists and Clinical Pharmacy Specialists. Information on drugs, such as recommended dosages, frequency, drug interactions and side-effects, was based on the standard text books and guidelines [9,10,11,12]. DTPs due to patient non-compliance was identified by using validated Morisky Medication Adherence Scale (MMAS) which consists of 8 items with a dichotomous response (yes/no) with questions asking the patient to respond “yes” or “no” to items 1–7 and a 5 point Likert response for the last item. A positive response indicates a problem with adherence. Therefore, higher scores indicate that a patient is least-adherent to medications. The total score for each patient is the summation of the scores in each item [13]. Finally, the identified DTPs were classified as unnecessary drug therapy, needs additional drug therapy, ineffective drug, dosage too low, adverse drug reaction, dosage too high and noncompliance.

2.2. Operational Definitions and Definition of Terms

Adverse drug reaction: if drug causes an undesirable reaction that is not dose-related, a drug interaction causes an undesirable reaction that is not dose-related, and the drug causes an allergic reaction, is contraindicated due to risk factors [1,2] or any single episode of hypoglycemia

Comorbidity:-any documented chronic disease which coexists with diabetes.

CVD risks: HTN, smoking, dyslipidemia, albuminuria and family history of CVD [3].

Drug therapy problem: is any undesirable event experienced by a patient which involves, or is suspected to involve, drug therapy, and that interferes with achieving the desired goals of therapy [1,2]

Dosage too low: when drug interaction reduces the amount of active drug available, the duration of drug therapy is too short to produce the desired response, the dosage interval is too infrequent to produce the desired response [1,2].

Dosage too high: if dose is too high, the dosing frequency is too short, the duration of drug therapy is too long, a drug interaction occurs resulting in a toxic reaction to the drug product, the dose of the drug was administered too rapidly [1,2]

Glycemic control: good when the average FBS is 70-130mg/dl whereas >130mg/dl is poor [3].

Ineffective drug: Use of drugs reducing effectiveness of the medications (by worsening the disease condition), the medical condition is refractory to the drug product [1,2].

Noncompliance: if the patient scores >3 in Morisky scale due to the reasons like; the patient does not understand the instructions, the patient prefers not to take the medication, the drug product is too expensive for the patient, the patient cannot swallow or self-administer the drug product appropriately, and the drug product is not available for the patient [1,2].

Need for additional drug therapy: if a medical condition requires the initiation of drug therapy, preventive drug therapy is required to reduce the risk of developing a new condition, a medical condition requires additional pharmacotherapy to attain synergistic effects [1,2].

Polypharmacy: if greater or equal to five chronic medications for at least one month [15].

Unnecessary drug therapy: when there is no valid medical indication for the drug therapy at this time, multiple drug products are being used for a condition that requires single drug therapy, the medical condition is more appropriately treated with nondrug therapy, Drug therapy is being taken to treat an avoidable adverse reaction associated with another medication[1,2].

2.3. Data Analysis

Completeness of the data was checked every day and entered and cleaned using EPI-data version 3.1 and exported to SPSS version 21.0 for analysis. Descriptive analysis was computed as frequency, mean and standard deviation (SD) for continuous variables and for categorical data. To examine the influences of different variables on DTPs and controlling for potential confounders, both binary and multiple logistic analyses were performed.

Independent variables having p-value <0.25 in the bivariate logistic regression analysis were entered into multivariable logistic regression analysis in order to control confounding effect. P-value of <0.05% was considered significant in the final model. Model diagnostics and goodness of fit test were done and was found fit. Multicollinearity was checked to test correlation among predictor variables and none was collinear.

2.4. Ethical Considerations

Ethical clearance was obtained from Research and Graduate Studies College of Health Sciences Ethical Review Board of Jimma University. Permission letter from all offices and written consent from each study participants were also taken to get his/her medical information. Patients were assured that lack of willingness to involve in the study will not affect the service they get from the hospital. Pertinent drug information inquiry from patients regarding the concerns about his/her medications was provided to the patient during the data collection. To ensure patient confidentiality, name and address of the patient was not recorded in the data collection format. The patients were also clearly informed that that his/her medical information would not be disclosed to any external subjects/media.

3. Results

3.1. Socio-demographic Characteristics of the Study Population

A total of 243 adult type 2 diabetic patients were included, of these 129(53.1%) were males. Majority, 105(43.2%) were within the age range of 45-54 years followed by 55-64 years old 82(33.7%). The mean age of patients was 53(SD=±8.36 years) ranging from 26 to 88 years old. The highest percent of patients were married (70.8%), having primary education (45.3%) and merchants (29.6%). Most of patients (96.7%) did not use tobacco, did not chew chat (90.9%), while 18.5% drink alcohol and 22.6% had family history of DM [Table 1].

Table 1. Socio-demographic characteristics of type 2diabetic patients at WSU teaching hospital

3.2. Disease Related Variables of Study Patients

Majority, 79% (192) of the patients had duration of T2DM of ≤ 10 years with the mean duration of 6.74± 5.02 years ranging from 7 months to 25 years. The average fasting plasma glycemic level calculated from at least three consecutive values showed that 59.2% (144) of patients had poor glycemic control with the mean value of 130.06 ± 10.895 mg/dl ranging from 82 to 147mg/dl [Table 2].

More than half of patients, 56.0% (137) were with comorbidity of which hypertension contributed to the highest percentage (61.8%) followed by peptic ulcer disease (13.4%). Majority 71% (97) of patients had one comorbidity with the mean number of comorbidities per patient was 2.54 ± 1.385 [Table 2].

Table 2. Diseases related variables among T2DM patients at WSU teaching hospital

3.3. Medication Related Variables of Study Patients

Majority, 76 (31.3%) of patients were taking three medications daily and 48 (19.8%) had polypharmacy. The mean number of medications was 3.34 ± 1.383 ranging from one to seven medications. Majority (65.8%) of the medications were taken twice per day. The most commonly prescribed anti-diabetic medication type was a combination of Glibenclamide with metformin 116(47.7%) followed by monotherapy with Glibenclamide (25.9%) while monotherapy with ACEIs 39(46%) and a combination of ACEIs with calcium channel blockers 27(32%) were the most frequently prescribed antihypertensive medications. About quarter (26.7%) of patients were prescribed with lipid lowering medication of which almost all (91.67%) received simvastatin while 18.1% were prescribed with antiplatelet agent, aspirin. Among concurrently used medications other than anti-diabetics, antihypertensive, statins and antiplatelet, acid lowering drugs 32 (48.5%) and antibiotics 14 (21.2) were the most frequently prescribed medications [Table 3].

Table 3. Medication related variables among T2DM patients at WSU teaching hospital

3.4. Epidemiology of Drug Therapy Problems

A total of 202(83.1%) patients had at least one drug therapy problem. The mean number of DTPs was 1.8 ± 0.751 with a total of 378 DTPs identified. The maximum number of DTPs was four but most of the patients 85 (42%) had two DTPs [Figure 2]. Of the seven categories of DTPs identified, need additional drug therapy and noncompliance were found to be the most frequent 137(67.8%) type [Table 4].

Table 4. Types of DTPs among T2DM patients at WSU teaching hospital

Figure 2. Number of DTPs among type 2 diabetes patients in WSU teaching hospital

3.5. Common Causes of Drug Therapy Problems

It was found that requirement of preventive drug therapy for cardiovascular risk, 126(92%) was the most common reason for occurrence of need additional drug therapy. A total of 67(49%) and 26(18.9%) patients were not receiving statins and antiplatelet therapy respectively although they were at increased CV risk. According to Validated Morisky Medication Adherence Scale (MMAS), 127 (52.3%) number of patients were not adhering to their medication giving non-compliance as the second most frequent type of DTPs. Majority 64(50.4%) of non- adherent patients reported that forgetting to take their medication followed by fear of side effects 36(28.3%) were the common reasons for their non-adherence [Table 5].

Table 5. Common causes of each DTP identified among T2DM patients in WSU teaching hospital, from February to April, 2016(N=202)

3.6. Drugs Commonly Involved in Drug Therapy Problems

Among drug classes commonly used by type two diabetes patients in the hospital, anti-diabetic medications 78(38.6%) followed by statins 74(36.6%) were found to be the most frequently involved drugs in overall occurrence of DTPs. Of patients requiring drug therapy for cardiovascular prevention, the lion share was due to underutilization of lipid lowering drugs (statins) 67(49%) followed by antiplatelet 26(18.9%). Whereas Enalapril 42(64.6%) and metformin 21(32.4%) were common drugs involved in dosage too low type of DTPs [Table 6].

Table 6. Common drugs involved in each category of DTPs among T2DM patients in WSU teaching hospital, from February to April, 2016

3.7. Predictors of DTPs in Study Patients

Age, presence of comorbidity, polypharmacy, and history of hospitalization were found to be independent predictors of drug related problems. It was found that the likely hood of having DTPs increases as age of respondents increases. Patients with in the age range of 45-54 years were 4.8 times more likely to have DTPs [AOR=4.851;95%CI:(1.129,20.853)] whereas those above 65 years old were nine times more likely to have DTPs compared to those less than 45 years old [AOR=9.079; 95%CI:(2.213,37.241)] (p-value <0.001). It was also found that patients who were taking more than or equal to five medications per day were about three times more likely to have DTPs [AOR=3.311; 95% CI: (1.366, 30.329)] compared to those who were taking less than five medications per day (p-value <0.025). Similarly, patients with comorbidity were seven times more likely to experience DTPs than patients without comorbidity [AOR=7.004; 95% CI: (1.285, 18.194)]. However, patients with history of hospitalization while on treatment were less likely to have DTPs [AOR=0.403; 95%CI: (0.176, 0.925)] compared to those who did not [Table 7].

Table 7. Multivariate analysis of variables predicting DTPs among T2DM patients in WSU teaching hospital, from February to April, 2016(N=243)

4. Discussion

The current study showed that 83.1 % of type 2 diabetic patients had at least one DTP with the mean number of 1.8 ± 0.751DTPs. This is consistent with a study in in Denmark (81%) [16], Minnesota (84%) [17], and in Nigeria (2.1± 1.4 DTPs) [18]. But the prevalence of DTPs in this study is lower than the DTPs study by Van Roosendaal et al in Australia which showed an average number of 4.6 ± 1.7 DTPs [19] and by Eichenberger et al in Switzerland which found that all study patients (100%) had at least one DTP with the mean of 7.5 ± 2.5DTP [20]. The discrepancy with the previous studies could be due to use of different DTPs identification methods and socio-demographics of study patients. Previous studies used PCNE classification of DTPs, and they identified concurrent use of ACEIs and sulfonylureas as potential DTPs in the study. But, this was not identified as DTP in our study because the interaction was not found to be clinically significant. Furthermore, Eichenberger et al used inclusion of patients of age above 60 years and intake of at least four prescribed drugs which could possibly contribute to the higher prevalence of DTPs in the study.

The most common type of DTPs identified was needs additional drug therapy 137(56.37%). This is in line with a study by Van Roosendaal et al in Australia [19] and Cipolle et al in Minnesota [17]. The cause for its high prevalence is absence of statins and antiplatelet for cardiovascular prevention which accounted 49% and 18.9% respectively. This is still in concordance with the finding from Australia which showed that 60.8% and 48.0% of patients were not receiving anti-platelet and statin therapy respectively although they were at increased cardio-vascular risk (19). In current study, ineffective drug therapy which accounted and ADR were the least frequent DTPs of all categories. Even though this finding is in line with a study by Cipolle [17], ADR was found to be among the frequent types of DTPs in Van Roosendaal et al study in Australia [19]. The difference could be due to consideration of concurrent use of ACEIs and sulfonylureas or insulin as potential drug interaction resulting in ADR in the previous and absence of causality assessment in current study.

Patients found within age range of 45-54 years were 4.8 times more likely to develop DTPs than those below 44years old whereas the factor increased to nine times for elderly patients at p-value of <0.003. Association of advanced age with DTPs has prone scientific ground as it results in multiple disease conditions requiring multiple medications. This finding is consistent with a study in Jordan [21], in Nigeria [18] and a DTPs study in Ethiopia [22]. But a study done among T2DM patients with hypertension in Malaysia showed no significant association of older age with DRPs [23]. The discordance could be due to difference in study patients and presence of standard geriatric drug guidelines like Beers criteria in the hospital might possibly reduce DTPs in geriatric population in previous study. It was also found that almost all patients (97.8%) with polypharmacy had DRPs and they were 3.3 times more likely to have DRPs than who did not [AOR=3.311; 95%CI: 1.366, 30.329)]. This finding is in agreement with myriad of studies on DTPs which showed that patients with multiple drug classes have a complex drug schedule which may contribute to the poor medication adherence problem, potential drug-drug interactions and side-effects of drugs and finally increased risk of DTPs [15,17,18,23,24].

Similarly, presence of comorbidity was also an independent predictor of DTPs in present study (P<0.001) which can be corroborated by previous studies on DTPs that identified comorbid conditions as major predictors of DTPs [15,17,25,26]. This might be due to increase in number of medications(polypharmacy), complex drug taking schedule which contributes to high rate of non-compliance, increase in drug-drug interaction, adverse effects and cardiovascular risk that necessitates need of additional therapy which collectively result in increased likely hood of experiencing DTPs in the study patients.

It was found that patients having history of hospitalization while on treatment were less likely to experience DTPs compared to those who had not. We could not get such finding in previously conducted DTPs studies among ambulatory patients with chronic illness but the reason might be partly explained as further investigation and assessment of patient’s condition by physicians, increased awareness about medication adherence and change in attitude they got from health professionals at the time of hospitalization could result in lower prevalence of DTPs in this patients.

5. Limitations of the Study

Even though the study has strengths such as use of DTPs identification criteria which is evaluated and accepted by experts, determining association between different categories of DTPs and glycaemic control which has not been adequately addressed by many studies either globally or locally, it has the following limitations: chance of recall bias in adherence assessment as it was based on respondents self-report, absence of causality assessment for ADR, chart review may result in missing of some data, absence of HbA1C monitoring for glycaemic level, lack of adequate organ function tests like RFT, LFT and lipid profiles.

6. Conclusions

The overall prevalence of DTPs among type 2 DM patients in WSU teaching hospital was 83.1%. Of these, the common DTPs identified were need additional drug therapy due to underutilization of statins and antiplatelet for cardiovascular prevention, non-compliance and dose too low. Age of respondents, presence of comorbidity, polypharmacy, and history of hospitalization were found to be independent predictors of occurrence of drug therapy problems in this study. Based on the findings, we recommend that the hospital should improve management of type 2 DM with special emphasis on optimizing utilization of statins and antiplatelet and, also increasing medication adherence to reduce drug problems among these patients.

Competing Interests

The authors declare that there are no competing interests.

Authors’ Contributions

HC- conceived and designed the study, analyzed the data, and drafted the manuscript. SB and EG-analyzed the data and participated in manuscript preparation.

Acknowledgements

I thank W/ro Birtukan Ermias, Blen Hailu, Grace Hailu, Dr Legesse Chelkeba, Dr Ashebir Tesfaye and Dr Getnet Gara for their unreserved support throughout the study.

Wolaita Soddo University teaching hospital staffs and the study participants are also acknowledged for their cooperation during data collection.

Abbreviations

ADA (American Diabetes Association), ACEIs (Angiotensin Converting Enzyme Inhibitors), ADR (Adverse Drug Reaction), CHF (Congestive Heart Failure), CVD (Cardiovascular disease), DM (Diabetes Mellitus), DTP (Drug therapy problems), FBS (Fasting blood sugar), IDF (International Diabetes Federation), JUSH (Jimma University Specialized Hospital), MMAS (Morisky Medication Adherence Scale), PCNE (Pharmaceutical Care Network Europe), PUD (Peptic Ulcer Disease), T2 DM (Type 2 Diabetes Mellitus), WHO (World health organization), WSU( Wolaita Soddo University).

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