Drug-Related Problems and Clinical Pharmacist-Led Medication Therapy Management; Three-Year Survey in an Educational Pharmacotherapy Clinic

doi:10.21203/rs.3.rs-3812800/v1

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Research Article

Drug-Related Problems and Clinical Pharmacist-Led Medication Therapy Management; Three-Year Survey in an Educational Pharmacotherapy Clinic

https://doi.org/10.21203/rs.3.rs-3812800/v1

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Objectives

Drug-related problems (DRPs) are adverse events or circumstances that interfere with favorable health outcomes. Medication therapy management (MTM) was developed to detect and manage DRP. This study set out to identify DRP-associated factors and reporting of subsequent interventions in a university-affiliated educational pharmacy.

Methods

This study was conducted from January 2020 to December 2022 at Shahid Kazemi Pharmacy, a large referral community pharmacy in Tehran, Iran. After medication review and complete medical history collection, DRPs were identified classified, and necessary interventions were performed. Medication adherence and satisfaction were evaluated before and 2–4 weeks after providing the MTM services.

Results

Within 1432 admissions, 838 patients were included and received 1116 interventions. Among the 1116 DRPs detected, the most common were drug information (27.4%), difficulty using dosage forms (26.3%), and any toxicity, allergic reaction, or adverse effects related to medications (12.8%). A significant association was detected between the number of DRPs and the age, the number of medications, and underlying chronic diseases (P < 0.05). Adjusting the age association of the number of medications and the number of underlying chronic diseases remained significant. The use of medications related to the alimentary tract and metabolism, medications affecting the blood and hematopoietic organs, medications affecting the cardiovascular system, antineoplastic and immunomodulatory medications, and medications affecting the nervous system were significantly associated with a higher risk for the occurrence of DRPs (P < 0.05).

Conclusions

Community pharmacy-led MTM services have a significant impact on DRP detection, management, medication adherence, and pharmacotherapy satisfaction.

Pharmacists

Medication Therapy Management

Pharmaceutical Services

Drug-Related Problems

Medication Adherence

Community pharmacies are among the most accessible components of the healthcare system. Over the past 40 years, the role of pharmacists has shifted from dispensing medications to providing pharmaceutical care (1). In 1994, the World Health Organization submitted the Good Pharmacy Practice (GPP) standard to optimize pharmacists’ services. In this standard, medication therapy management (MTM) service, is introduced as one of the most important aspects of the pharmacist role, which is independent of, but can occur in conjunction with, the provision of patient’s medications (2).

MTM services have been developed to optimize medication adherence and treatment compliance to detect and manage DRPs. MTM is a promising service to proactively identify DRPs, support evidence-based medication use, and provide individualized counseling to at-risk patients. This includes identifying DRPs and recommending interventions (3). Clinical pharmacists provide this service as a face-to-face visit in a private setting (1, 4–7). Readapted clinical services provided by community pharmacists can improve patient health outcomes (8). Several studies have demonstrated pharmaceutical care's effectiveness in all settings (9–11). In particular, research shows that pharmacist medication review can positively impact adherence, improve prescription appropriateness, and potentially reduce emergency department visits.

Most of the pharmacists' missions assigned to them in the GPP standard are in the area of DRP prevention and management, such as prescribing medicines when 1) Proper dose regimens and dosage forms are performed, 2) Instructions for use are clear, 3) Interactions are prevented, 4) Known and predictable ADR, including allergies and other contraindications, are avoided, 5) Unnecessary treatments are minimized, 6) The cost of medicines is considered, assisting patients to understand the importance of taking medicines properly, 7) Monitoring treatment to verify the effectiveness and adverse medicine events.

DRPs are defined as "preventable or predictable events or circumstances that actually or potentially interfere with favorable health outcomes'' (12). They can lead to hospitalization and increase the length of hospital stays (13). Several systems have been developed to identify and classify the DRPs in a standard manner (1, 14). One of these systems was set and validated by the Pharmaceutical Society of Australia which classifies DRPs and subsequent interventions in detail (15).

Studies examining the predisposing factors for DRP occurrence have been performed mostly in hospitalized patients. Factors, such as co-occurrence of chronic diseases, advanced age, polypharmacy (16), and the use of high-risk medications, for instance, those with a narrow therapeutic index, are reported (17). Multimorbidity, or the simultaneous occurrence of several conditions, is a clinical and therapeutic challenge for health systems (18). In this case, because the patient is receiving some pharmacotherapy regimens from different physicians, they will need a service that aligns the different regimens to prevent and manage DRPs if they occur.

Despite the negative impact of DRPs on clinical and economic healthcare outcomes in the outpatient setting, few studies have examined the frequency of DRPs occurrence and identified the predisposing factors and subsequent interventions in this setting. Therefore, this study aims to identify DRPs and associated factors such as the occurrence, classification, and reporting of subsequent interventions by clinical pharmacists, and to follow the acceptance rate of physicians in an outpatient setting.

Study Design

This was performed at the MTM clinic of Shahid Kazemi Pharmacy affiliated with Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran from January 2020 to December 2022. Shahid Kazemi MTM clinic is an ambulatory academic pharmacy and has almost all drugs in the official Iranian drugs list (IDL), such as chemotherapy agents and medications for orphan and rare diseases. Hence, a wide range of patients refer to.

Ethical Consideration

The study protocol was approved by the Ethics Committee of SBMU with the registered code IR.SBMU.PHARMACY.REC.1399.054. The survey process thoroughly, performed in accordance with Helsinki declaration and patient-centered regulations and the details of recriutment, survey, dara extraction, and reporting were accepted by the Ethic Committee of SBMU. Patients were informed of the study's aims and were assured that their data would be kept confidential. Their participation in the study was voluntary and confirmed with the patients’ informed written consent.

Participants

Patients were enrolled in the MTM clinic at the pharmacist’s discretion in charge of the community pharmacy or their request for a pharmacotherapy visit. The inclusion criteria for this study included the participants' referral to the MTM clinic with at least one chronic condition. Chronic conditions were defined as those requiring ongoing medical care +/or associated with limitation of daily activities for at least one year. Patients who did not have sufficient information about their medical and medication history and patients who were unwilling to participate in the study were excluded.

Outcome Measurements & Data Collection

The primary outcome of this study was to identify the association between the incidence of DRPs the number of patients’ medicines, and the number of chronic conditions. The secondary outcome of this study was the effect of pharmacist-led MTM services on medication adherence and medication satisfaction. The third outcome was to evaluate the rate of agreement of physicians to the pharmacist's suggestion for DRP correction.

Medication Therapy Management (MTM) & Drug Related Problems (DRP) Identification

Patients were evaluated at the MTM clinic by a team consisting of a pharmacy intern and a clinical pharmacy resident under the supervision of a clinical pharmacist. Pharmacists in the MTM clinic received an education program, including how to conduct MTM services and prioritize DRPs to ensure the quality of the MTM services and detection of DRPs. Patient demographics, chief complaints, and medical histories were obtained either from the patients themselves or their caregivers.

DRP Classification

The WHO disease classification system was used to categorize the underlying chronic diseases (23). The Anatomical Therapeutic Chemical (ATC) classification system was also used for medication history (24). To categorize DRPs and subsequent interventions, we used the Pharmaceutical Society of Australia (PSA) (12). This classification consists of eight categories for DRPs (drug selection, over- or under-prescribing, compliance, under-treatment, monitoring, education or information, unclassifiable, and toxicity or adverse reaction) and five categories for interventions (change in therapy, referral required, provision of information, monitoring, and no recommendation required). In cases where patients needed to be followed up, patients were followed up by telephone or clinic.

Medication Adherence

Patients' adherence to the treatment regimen was the assessed by Persian language version of the Morisky medication adherence scale-8 (19), which includes eight questions. To quantify the adherence, questions 1 to 7 (excluding question 5) were given one point for each negative answer and zero points for each positive response. For the last question, 0.25, 0.5, 0.75, and 1 were equivalent to the options "All the time/Usually/Sometimes/Rarely/Never,” and the final score can be classified as those with high adherence ≥ 8, average adherence 6–8 and poor adherence ≤ 6.

Patient Satisfaction

All patients were assessed regarding their medication satisfaction based on a self-reporting question, “Taking all things into account, how satisfied or dissatisfied are you with this medication?” with a 7-point Likert scale consisting; of 1) Extremely dissatisfied, 2) Very dissatisfied, 3) Dissatisfied, 4) Somewhat satisfied, 5) Satisfied, 6) Very satisfied and 7) Extremely satisfied.

Follow-ups

In this study, the participants were evaluated at least two times before the intervention, and two to four weeks after the MTM services.

Sample Size

to calculate the minimum sample size required to establish a relationship between the variables in the study, a pilot study was conducted with 50 patients. The result of the pilot study showed a significant association between the number of medicines and the number of DRPs (Pearson coefficient: 0.125, P = 0.041) and chronic conditions (Pearson coefficient: 0.143, P = 0.038). With an alpha coefficient of 0.05, a power of 80%, and a correlation coefficient of 0.125, the calculated sample size was 826.

Data Analysis

The Kolmogorov-Smirnov test was used to test the normality assumption of the variables. Parametric variables were presented using mean ± standard deviation (SD); we used median and interquartile range (IQR) for nonparametric variables. One-way analysis of variance (ANOVA) was used to compare the number of DRPs between groups. An independent sample T-test was performed to compare the frequency of drug classes across the number of DRPs. In addition, the linear regression model was used to evaluate the association between the number of DRPs and the number of underlying chronic diseases or medications taken. Finally, a multivariable regression model was constructed and adjusted for age. All analyses were performed in IBM SPSS statistics for Windows (version 22.0 IBM, Armonk. NY). The statement of strengthening the reporting of observational studies in epidemiology (STROBE) was followed in reporting (20).

Participant Characteristics

Sampling was performed over three years to reach the sample size required to achieve the study objective; during this period, 1432 admissions were recorded in the MTM clinic, among whom 359 cases did not meet the inclusion criteria, 143 cases had exclusion criteria, and 19 cases declined to participate in the study; finally, 911 patients meet the requirements of participation. Awhom 73 did not complete all questionnaires and feedback per protocol. Eventually, the results of 838 patients were included in this study. The mean age of participants was 50.2 ± 12.4. Among the participants, 49 were ≤ 14 years old, and 235 were ≥ 65, and the age of 33% of patients were in the range of 24–65 years, and 51.4% of the study population were females. A summary of patients' demographic and clinical data is available in Table 1.

Table 1

Demographic and clinical characteristics of the study population.
Variables Total number of participants: 838		Descriptive statistics (n, %) (mean ± SD*)
Gender	Female	431 (51.4%)
Gender	Male	407 (48.6%)
Source of information	Patient	582 (69.5%)
Source of information	Patients caregiver	256 (30.5%)
Age range (y)	45–64	282 (33.7%)
	25–44	253 (30.2%)
	> 65	235 (28.0%)
Duration of consultation		13.05 ± 6.32
Number of baseline chronic condition		1.14 ± 0.75
Number of DRP		1.33 ± 0.68
Number of medication		1.26 ± 1.41
Number of interventions		1.33 ± 0.84
*: absolute frequency
**: standard deviation

The first three common diseases among the participants were endocrine, nutritional, and metabolic diseases (25.2%), neoplasms (10.7%), and musculoskeletal or connective tissue diseases (10.4%). Figure 1 illustrates the frequency of the underlying chronic conditions in detail.

In addition, the first three categories of medications taken by the patients were nutritional and metabolic agents (32.5%), antineoplastic and immunomodulatory agents (31.1%), and musculoskeletal (12.9%) (Fig. 2). The most common chief complaints of the patients were related to drug administration (32.7%), requests for drug information (21.5%), and complications of adverse effects (12.6%) (Fig. 3).

Outcome Reports

Description of DRPs: We identified 1116 (median: 1; IQR 1st, third: 1,2) DRPs in the study population. The most common DRPs were patients' requests for information about their medications (27.4%), difficulty using dosage forms (26.3%), and any toxicity, allergic reaction, or adverse effects related to medications (12.8%). Table 3 shows the frequency of major categories and subcategories of DRPs in detail. Only 11 (1.3%) patients did not experience any DRP.

Pharmacists performed 1118 interventions during the study period (median: 1; IQR 1st, 3rd: 1,1). Patient education and counseling were the most common interventions (67.9%), followed by referral to a physician (16.7%) and recommendation for dose administration (11%). The detailed distribution of interventions is shown in Fig. 4.

Among the admitted patients, 628 were identified as requiring more follow-ups and were contacted by telephone, and in 334 cases, the patient identified as requiring face-to-face follow-up.

Physician Approval Rate

To inform the patient's physician about the actions taken by the clinic for DRP management, or to request a decision, 641 correspondences were made, of which 354 (55.2%) correspondences were made for the physician's information, in 287 (44.7%) cases a change in the patient's medication was suggested, of which 276 (96.1%) physicians agreed with the proposal, in 11 other cases the physician suggested another management to the detected DRP.

Medication Adherence

The average total adherence to the treatment regimen before the intervention was 4.21 ± 1.22, and it improved to 7.53 ± 0.30 (P < 0.0001). Table 2 illustrates the results in more detail. There is a significant difference between the before and after intervention results in all cases except question 5. Also, the results showed that before the intervention, 775 (92.48%) patients were in the poor adherence level, and only 63 (7.51%) were patients are an average level, while after the intervention, the adherence score of all (100%) patients were in the middle range (P < 0.0001). Analysis of the mean difference in the score obtained from the medication adherence score showed that patients’ average score has increased by 3.31 ± 1.26.

Table 2

Adherence to treatment regimen and patient satisfaction before and after the MTM services
Item		Answer	Patients’ Responses # (%)
Item		Answer	Before	After	P-Value
Medication Adherence	Question 1	No	301 (63.96)	385 (45.94)	0.003
	Question 2	No	511 (60.98)	720 (85.92)	0.001
	Question 3	No	544 (64.92)	731 (87.23)	< 0.0001
	Question 4	No	419 (64.92)	636 (87.23)	< 0.0001
	Question 5	Yes	804 (95.94)	833 (99.40)	0.181
	Question 6	No	604 (72.08)	804 (95.94)	< 0.0001
	Question 7	No	343 (40.93)	502 (59.90)	< 0.0001
	Question 8	Never	160 (19.09)	178 (21.24)	< 0.0001
		Rarely	192 (22.91)	486 (58.00)
		Sometimes	453 (54.06)	166 (19.81)
		Usually	33 (3.94)	8 (0.95)
		All the time	0 (0)	0 (0)
Patient Satisfaction		Extremely Dissatisfied	58 (6.92)	0 (0)	< 0.0001
		Very Dissatisfied	182 (21.72)	0 (0)
		Dissatisfied	323 (38.54)	61 (7.28)
		Somewhat Satisfied	210 (25.06)	158 (18.85)
		Satisfied	59 (7.04)	202 (24.11)
		Very Satisfied	6 (0.72)	234 (27.92)
		Extremely Satisfied	0 (0)	183 (21.84)

Table 3

Frequency of categories and subcategories of DRPs
Categories of DRPs	Drug selection (n, %) (69, 6.2%)	Compliance (n, %) (366, 32.8%)	Over or underdose-prescribed (n, %) (34, 3.0%)	Undertreated (n, %) (38, 3.4%)	Monitoring (n, %) (31, 2.8%)	Education or information (n, %) (401, 35.9%)
Subcategories of DRPs	Wrong drug (18, 1.6%)	Difficulty using the dosage form (294, 26.3%)	The prescribed dose too low (11, 1.0%)	Condition undertreated (15, 1.3%)	Laboratory monitoring (22, 2.0%)	The patient requests drug information (306, 27.4%)
	Drug interaction (14, 1.2%)	Under-use by patient (20, 1.8%)	Prescribed dose is too high (6, 0.5%)	Condition untreated (11, 1.0%)	Non-laboratory monitoring (6, 0.5%)	The patient requests disease management advice (95, 8.5%)
	No indication apparent (13, 1.2%)	Erratic use of medications (20, 1.8%)	Incorrect or unclear dosing instruction (15, 1.3%)	Preventive therapy required (12, 1.1%)	Other monitoring problem (3, 0.25%)	Other educational information problem (0, 0%)
	Contraindication apparent (9, 0.8%)	Other compliance problem (15, 1.3%)	Other dose problem (2, 0.2%)	Other undertreated indication problem (0, 0%)
	Duplication (7, 0.6%)	Over-use by patient (15, 1.3%)
	Other drug selection problem (7, 0.6%)	Intentional drug misuse (2, 0.2%)
	Inappropriate dosage form (1, 0.1%)
	Incorrect strength (0, 0%)

Medication Satisfaction

The results of patient satisfaction with their treatment regimen showed that before providing the MTM services, 275 (32.82%) patients were satisfied with their treatment regimen, while after providing services, 777 (92.72%) patients were satisfied (P < 0.0001). Table 2 presents the results in more detail.

Factors Associated with DRP Occurrence

A significant association was found between the number of DRPs and the age (P = 0.003, Pearson correlation coefficient = 0.103) the number of medications (P < 0.001, Pearson correlation coefficient = 0.206) and the number of underlying chronic diseases (P < 0.001, Pearson correlation coefficient = 0.225). Adjusting the age in the multivariable linear regression model showed that both the number of medications and the number of underlying chronic diseases remained significant (unstandardized B = 0.055 and 0.140, P = 0.006 and < 0.001, respectively). Some chronic diseases resulted in a significantly higher number of DRPs. Table 4. illustrates in detail the discrepancies in DRP frequency among all diseases.

Table 4

Distribution of DRP frequency in different disease categories.
Disorders		N	Number of DRPS Mean ± SD	P-Value
Endocrine, Nutritional or Metabolic Diseases	With	211	1.43 ± 0.82	0.019*
Endocrine, Nutritional or Metabolic Diseases	Without	627	1.30 ± 0.62	0.019*
Neoplasms	With	90	1.35 ± 0.66	0.724
Neoplasms	Without	748	1.33 ± 0.68	0.724
Disease of the Musculoskeletal System or Connective Tissue	With	87	1.22 ± 0.56	0.138
Disease of the Musculoskeletal System or Connective Tissue	Without	751	1.34 ± 0.69	0.138
Diseases of the Nervous System	With	81	1.28 ± 0.57	0.504
Diseases of the Nervous System	Without	757	1.34 ± 0.68	0.504
Disease of the Circulatory System	With	81	1.51 ± 085	0.015*
Disease of the Circulatory System	Without	757	1.31 ± 0.65	0.015*
Diseases of the Digestive System	With	68	1.41 ± 0.67	0.310
Diseases of the Digestive System	Without	770	1.32 ± 0.68	0.310
Disease of the Genitourinary System	With	61	1.36 ± 0.75	0.729
Disease of the Genitourinary System	Without	777	1.33 ± 0.67	0.729
Factors Influencing Health Status or Contact with Health Services	With	54	1.68 ± 0.99	0.000*
	Without	784	1.31 ± 0.64	0.000*
Diseases of Blood or Blood-forming Organs	With	47	1.30 ± 0.59	0.724
Diseases of Blood or Blood-forming Organs	Without	791	1.33 ± 0.68	0.724
Disease of the Respiratory	With	31	1.45 ± 0.67	0.315
Disease of the Respiratory	Without	807	1.32 ± 0.68	0.315
Mental & Behavioral or Neurodevelopmental Disorders	With	27	1.59 ± 0.75	0.042*
Mental & Behavioral or Neurodevelopmental Disorders	Without	811	1.32 ± 0.67	0.042*
Disease of the Visual System	With	4	2.00 ± 1.15	0.048*
Disease of the Visual System	Without	834	1.33 ± 0.67	0.048*
Diseases of the Skin	With	21	1.43 ± 0.67	0.507
Diseases of the Skin	Without	817	1.33 ± 0.68	0.507
Certain Infectious or Parasitic Diseases	With	7	1.00 ± 0.00	0.193
Certain Infectious or Parasitic Diseases	Without	831	1.33 ± 0.68	0.193
Symptoms, Signs or Clinical Findings, Not Elsewhere Classified	With	7	1.43 ± 0.53	0.704
	Without	831	1.33 ± 0.68	0.704
Conditions Related to Sexual Health	With	6	1.33 ± 0.52	0.995
Conditions Related to Sexual Health	Without	832	1.33 ± 0.68	0.995
Sleep-wake Disorders	With	5	1.60 ± 1.34	0.375
Sleep-wake Disorders	Without	833	1.33 ± 0.67	0.375
Disease of the Immune System	With	3	0.67 ± 0.58	0.088
Disease of the Immune System	Without	835	1.33 ± 0.68	0.088
Injury, Poisoning, or Certain other Consequences of External Causes	With	3	1.33 ± 0.58	0.997
	Without	835	1.33 ± 0.68	0.997
Disease of the Ear or Mastoid Process	With	1	1.00	0.624
Disease of the Ear or Mastoid Process	Without	837	1.33 ± 0.68	0.624
* With significant difference

Among the drug categories in the multivariable regression model, alimentary tract and metabolism (standardized coefficient B = 0.219; P < 0.001), blood and hematopoietic organs (standardized coefficient B = 0.075; P < 0.038), cardiovascular system (standardized coefficient B = 0.076; P < 0.039), antineoplastic and immunomodulatory agents (standardized coefficient B = 0.084; P < 0.025), and nervous system (standardized coefficient B = 0.084; P < 0.016) remained significant in the final model and showed a positive correlation with the number of DRPs.

In the present study, DRPs and subsequent interventions were evaluated at the MTM clinic of a community pharmacy over three years. The significant impact of clinical pharmacy-based MTM services on identifying DRPs and recommendations of interventions was evident. Of all the 838 patients, 1116 DRPs were identified, with difficulty using dosage forms, desire for more information about medications, and any toxicity, allergic reaction, or adverse effect related to medications topping the list. The most common interventions included education and counseling, referral to the prescriber, and dosage recommendation. Interestingly, higher numbers of medications and underlying chronic conditions were associated with more DRPs. Finally, a specific category of diseases contributed to a higher number of DRPs. The results showed that only 11 (1.3%) patients had no DRPs. However, even these patients benefited from MTM services provided by clinical pharmacists, such as education. Additionally, both medication adherence and satisfaction regimens improved after MTM services.

Several studies have previously examined DRPs in hospitalized patients (11, 21–23); however, few data are available from regular community pharmacies (24). While we found our most common DRPs, studies with predominantly inpatient settings have shown that DRPs such as the need for a new medication or dose increase (9), suboptimal drug effect (22), and lack of therapy (25) are significant problems in inpatients. On the other hand, the most common DRPs in community pharmacies included information problems, therapeutic errors (26), drug interactions, contraindications (27), need for additional therapy, unnecessary drug therapy, and poor adherence (28). The different outcomes may be due to differences in the healthcare system, deficiencies in data documentation, and a lack of appropriate infrastructure. The finding that "seeking more information about medications" is the most common DRP indicates that many patients are not informed about their medications and treatment, underscoring the importance of pharmacists' MTM services.

Regarding the drug classes associated with the occurrence of DRPs, the results of previous studies conducted in the outpatient setting are similar. For example, the results for the alimentary tract and metabolism (29, 30), blood and hematopoietic organs, cardiovascular system, nervous system (29), and antineoplastic and immunomodulatory agents were the same. In the inpatient setting, in chronic kidney disease (CKD) clinics, cardiovascular drugs, gastrointestinal agents, and analgesics are more likely to be responsible for DRPs. In an intensive care unit, systemic antimicrobial agents are more likely to be accountable for DRPs (7, 12, 31).

Both the number of drugs and underlying chronic diseases were critical factors contributing to the rate of DRPs. Previous studies have shown that the number of medications in both outpatient and inpatient settings could significantly determine the incidence of DRPs (32). In this regard, polypharmacy is a critical factor leading to a higher risk of DRPs, necessitating a move away from the classic thresholds of 4 + or 5 + medications to a realistic linear approach (29). To address this issue and reduce the rate of preventable adverse drug events, studies have suggested the use of advanced computerized drug prescribing systems (33).

In addition, the current study results showed that the presence of some diseases was significantly related to the increased risk of DRPs, which is discussed below. In the category of endocrine disorders, more patients had diabetes mellitus who used insulin pens. They had difficulty in using their medication due to inadequate education. A prospective study showed that patients with circulatory diseases were taking more than five medications, which is a risk predictor for developing DRPs. The number of chronic diseases per patient was almost four, indicating obvious multiple morbidities (33). Visual impairment may also affect patients' taking prescribed medications (34). This is mainly because they have difficulty reading prescription labels, recognizing expiration dates, understanding the name of the drug, and keeping their medications. Of the group factors affecting health status or contact with health services for illness, most patients were those who had undergone organ transplantation. It seems that these patients are more prone to DRPs due to their polypharmacy and use of immunosuppressive drugs (35). Patients with severe mental illnesses are less likely to receive standard treatment for their comorbidities, making them more susceptible to DRPs (36).

As we showed that pharmacist-led MTM services could improve patient adherence to the treatment regimen, Daniel A. Ercu et al. also demonstrated that MTM services provided by pharmacists markedly increased medication adherence in patients with type 2 diabetes mellitus by 9.2% at baseline to 61% at six months in a prospective randomized controlled study (37). This may be because patients with chronic conditions like diabetes mellitus have complex treatment regimens, so educating and clarifying the treatment regimen can make them more adherent.

This study found that patients were more satisfied with their treatment regimen after MTM services than before. In a study conducted in a large, integrated healthcare system, 95.3% of patients agreed or strongly agreed that their overall health and well-being had improved due to pharmacist-led MTM services (8). This may be because pharmacists assume responsibility for patients’ medication therapy outcomes and collaborate with other healthcare providers to facilitate high-quality patient care (38).

This study has some limitations. First, as the data were not collected longitudinally, it does not allow us to identify causal relationships. Second, our results may differ from those of other geographic areas with different healthcare characteristics, particularly concerning domestic pharmaceutical care. Third, the diversity of patients referred to the pharmacy of the study site was high. Although this diversity was an advantage, this amount of variety in patients may not be seen in the usual community pharmacies and affect the generalizability of our results. The following limitation of the study is the non-detection of DRP by the pharmacist, especially in the case of uncommon DRPs that are also related to the pharmacist's professional experience. A standard validated DRP classification system was used in this study to minimize this.

This study suggests that MTM services lead to the detection and resolution of many DRPs with appropriate interventions and improvement in medication adherence and satisfaction. The mean probability of DRP detection in included patients was 1.33, and the most common were drug information and difficulty using dosage forms. The use of medications related to the alimentary tract and metabolism, medications affecting the blood and hematopoietic organs, medications affecting the cardiovascular system, antineoplastic and immunomodulatory medications, and medications affecting the nervous system were significantly associated with a higher risk for the occurrence of DRPs. A significant association was detected between the number of drug-related problems and the age, number of medications, and underlying chronic diseases. This study represents a promising approach to MTM services in community pharmacies delivered by clinical pharmacists, which could have significant health implications. The findings will be used for developing evidence-based eligibility criteria for MTM services in community pharmacies.

Conflict of interest: There is no conflict of interest of any of the authors with the results of this study.

Data availability statement: The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Acknowledgments

We thank and appreciate the efforts of Dr. Roozbeh Pourziaei Manesh, the director of Shahid Kazemi Pharmacy, and Professor Jamshid Salamzadeh, the head of SBMU pharmacies, who played a significant role in conducting this research. We appreciate the efforts of Morisky Medication Adherence Research group for giving us the license to use the MMAS scale (Certificate Number: 7799-8371-5354-4091-1040).

Ethical approval and consent: The study protocol was approved by the Ethics Committee of SBMU with the registered code IR.SBMU.PHARMACY.REC.1399.054. The survey process thoroughly, performed in accordance with Helsinki declaration and patient-centered regulations and the details of recriutment, survey, dara extraction, and reporting were accepted by the Ethic Committee of SBMU. Patients were informed of the study's aims and were assured that their data would be kept confidential. Informed written consent was obtained from all subjects.

Consent for publication: N.A

Declaration of Interest: The authors declare there is no conflict of interest in this study.

Funding: This work was supported by the Medical Research Council of SBMU [Grant NO: 22527].

Data Availability Statement: The data supporting this study’s findings are available from the corresponding author on request.

Author Contribution: H.E. and S.R. developed the idea and clinical gap, H.E. and G.M. designed the study, N.V. and A.F. extracted the epidemiologic data, H.E. and M.S. conducted the data analyses and interpretation, N.V. wrote the initial manuscript and edited by H.E., M.S., and N.V.. All authors reviewed the manuscript and consented to the submission.

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No competing interests reported.

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Drug-Related Problems and Clinical Pharmacist-Led Medication Therapy Management; Three-Year Survey in an Educational Pharmacotherapy Clinic

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Abstract

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Introduction

Methods

Study Design

Ethical Consideration

Participants

Outcome Measurements & Data Collection

Medication Therapy Management (MTM) & Drug Related Problems (DRP) Identification

DRP Classification

Medication Adherence

Patient Satisfaction

Follow-ups

Sample Size

Data Analysis

Results

Participant Characteristics

Outcome Reports

Discussion

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