This study was conducted during the period from July 2021 through January 2022 in the cardiology center of GGH in AlGurayat, which is a small city residing in the north of Saudi Arabia with a population size of 167,080 as of 2022. GGH is a 220-bed hospital. The cardiology center was established in May 2018. A catheterization laboratory is available, while clinical pharmacy service has not yet been established.

This study included patients aged ≥18 years who were admitted to GGH with an acute presentation of MI during the study period. Patients who died after admission for acute MI were excluded.

In this interventional study, we assessed the impact of the clinical pharmacist services on the primary outcome measure of adherence to the clinical PMs and QMs for adults with STEMI and NSTEMI according to the 2017 ACC/AHA report (Jneid et al. 2017). Besides, the role of the clinical pharmacist in the secondary outcome measure of the identification and prevention of other TRPs in the study population was also assessed. The acceptance rate of clinical pharmacist recommendations by the physicians was also assessed. The study protocol was approved by the local research ethics committee in AlGurayat Health Affairs (IRB no. 076/2021), and the study was performed in accordance with relevant guidelines and regulations. The data obtained was considered confidential, and patients’ names were not collected.

The minimum required sample size for this study was estimated to be 20 using power calculations as previously described (Charan and Biswas 2013). The following equation was used:

$\mathrm{N}=\frac{2{\left(Z_{\frac{\alpha }{2}}+Z_{\beta }\right)}^{2}P(1-P)}{(p1-p2{)}^2}$

where N is the sample size; Z_α/2 = 1.96 at type 1 error of 5%; Z_β = 0.842 at 80% power; p1−p2 = difference in proportion of events in two groups; P = pooled prevalence = [prevalence in case group (p1) + prevalence in control group (p2)]/2. The values of p1 and p2 were estimated based on the results of a previous report, which demonstrated that clinical pharmacist intervention significantly increased the optimal prescribing of five guideline-direct medical therapies in patients with ACS from 35% (p2) of the patients in the observation phase into 80% (p1) of the patients in the intervention phase (Jabri et al. 2020).The target sample size was inflated to 50 in each cohort to account for any possible dropouts.

The researcher who collected the data was a clinical pharmacist who holds a Master’s degree in clinical pharmacy and has obtained training on the field of critical care, including the coronary care unit. The data was collected from the patient records through the hospital information system and from the patients or their caregivers after obtaining informed consent. In addition, the relevant physician was also consulted throughout the process of data collection in cases of discrepancies and to ensure the reliability and completeness of the obtained data. The data collection process was continuously monitored and verified for accuracy by members of our research team.

A four-part data collection sheet was structured based on previous reports (AbuRuz et al. 2006; Jneid et al. 2017) and was face-validated by several colleagues in the field of clinical pharmacy. Piloting was also conducted, and the data obtained were not included in the final analysis. The first two parts of the collection sheet included patients’ demographics and medical histories. The third part included the 17 PMs and the 6 QMs as described in the 2017 ACC/AHA report (Jneid et al. 2017). The PMs and QMs were selected based on their applicability within the hospital setting and healthcare system in GGH. Therefore, of the 17 PMs, PM-10 and PM-11 could not be assessed due to the difficulty in assessing the relevant time intervals that are related to first medical contact (FMC) for patients referred from non-percutaneous coronary intervention (PCI)-capable facilities into GGH. In addition, QM-6 could not be assessed as prasugrel was not available in GGH during the study interval. The last part included a modified TRP assessment tool (AbuRuz et al. 2006) for the identification of treatment and drug therapy problems related to unnecessary drug therapy, untreated conditions, drug efficacy, drug safety, miscellaneous, and treatment-related problems on discharge medications.

This study is a controlled before-and-after quasi-experimental interventional study (Fig. 1). Two cohorts of patients were included: the historical retrospective (control) and the prospective (intervention) cohorts. This study design is justifiable when there are ethical concerns in recruiting patients for the control arm in life-threatening diseases such as AMI (Harris et al. 2006; Ghadessi et al. 2020). In addition, this study design ensures the blindness of physicians and the avoidance of any reflective interference from the intervention group on the control group. The historical control group included the eligible patients who had been admitted to the hospital from August 2020 to June 2021 and received standard-of-care treatment. For the intervention cohort, eligible patients who were admitted during the period of July 2021 to January 2022 were included. The medical records of patients in both groups were reviewed by the researcher clinical pharmacist and assessed for adherence to the 2017 ACC/AHA clinical performance and quality measures and for the presence of other TRPs. However, the management plan of the patients in the intervention cohort-but not the control cohort- was then discussed with the relevant cardiologist before setting recommendations. Physicians’ acceptance rate of clinical pharmacist recommendations was recorded.

Figure 1. 

Workflow for the study.

The proportion of patients whose management plan included the application of the different individual PMs or QMs was calculated and compared between the two cohorts. The total frequencies of the PMs or the QMs applied in either group were determined and compared. The total number of TRPs identified during hospitalization was calculated for each group. The total number of TRPs left without resolution at discharge was calculated and compared between the two groups.

Statistical analysis was performed using SPSS version 26.0 (SPSS Inc., Chicago, IL). Descriptive statistics of frequencies and percentages were used to describe the categorical variables, while mean and SD were used to describe continuous variables. Bivariate analyses were used to find between-group differences. Normality testing was performed using the Kolmogorov-Smilnorv and Shapiro-Wilk tests. An independent sample t-test was used to compare the means of normally distributed continuous variables. For non-normally distributed continuous variables, the Mann-Whitney U test was employed. For categorical variables, the chi-square test was applied. Fisher’s exact test replaced the Chi-square test when counts were less than 5. Valid percentages were used to account for missing data. A P value < 0.05 was considered statistically significant.

One hundred eligible patients with symptoms of STEMI and NSTEMI were included in this study, with 50 cases in each of the control and intervention groups. As presented in Table 1, there were no statistically significant differences between the control and the intervention groups in terms of age, gender, smoking, or the presence of previous comorbidities. This indicates that the population in both groups was homogenous. Both groups showed similarities in the proportion of comorbidities presented at the time of admission. Sixty percent of the control group and 76% of the intervention group had at least one comorbidity documented in the medical file. The most commonly encountered medical conditions were diabetes mellitus, hypertension, heart failure, and ischemic heart disease. However, the specific type of ACS (STEMI, NSTEMI, or unstable angina) was not clearly documented in the patient’s medical file.

Of the 17 PMs described by the 2017 ACC/AHA report, PMs 1-6, 8, 9, 13, and 16 were applicable and could be evaluated (Table 2). Analysis of the application of the individual PMs revealed that of the 9 PMs evaluated, only PM-4 was applied at a significantly higher frequency in the intervention group as compared to the control group. High-intensity statin prescription at discharge was significantly higher in the intervention group (n= 41, 82%) as compared to the control group (n=29, 58%) (P-value = 0.009). Interestingly, the total number of PMs applied to all patients in the intervention group was significantly higher than that in the control group (P-value = 0.006).

The measures were generally applied at an overall higher frequency in the intervention group as compared to the control group, with the measures PM-1, PM-2, and PM-16 being applied to 100% of the patients in that group. PM-3, 4, 5, and 6 were not applied to some of the patients in the intervention group due to physician opinion or the presence of contraindications. PM-8 was applied to only 60% of the patients in the intervention group, which means GGH should develop an emergency protocol to handle ACS cases in a timely manner. PM-9 was applied to 92% (n = 46) of the intervention group, where PCI was performed on all patients with a presentation of ACS admitted to GGH regardless of being STEMI or NSTEMI, while the remaining patients (n = 4; 8%) were transferred to another hospital for coronary artery bypass grafting (CABG). PM-13 was applied to all patients in the intervention group with the exception of one, as the patient was transferred to another hospital to pursue his management.

PM-7, PM-10, PM-11, PM-12, PM-14, PM-15, and PM-17 were not collected in this study due to the reasons presented in Table 3. None of the patients in this study received fibrinolytic therapy, and therefore PM-7 was not evaluated. Among the patients referred from other hospitals, there was not an accurate approach to determining neither the door-in-door-out time (PM-10) nor the FMC to PCI time (PM-11) in a PCI-capable hospital. Cardiac rehabilitation services are not available in GGH; therefore, none of the patients were transferred to such services prior to discharge (PM-12). None of the patients were resuscitated out of the hospital, so PM-14 could not be evaluated for this group of patients. PM-15 could not be addressed as all the patients were managed with invasive angiography rather than a conservative strategy. Regarding PM-17, the GGH does not participate in the national registry for AMI.

Of the seven quality measures provided in the 2017 ACC/AHA report, only QM-4 was applicable and evaluated in the current study (Table 4). About 60% (n = 8) of those patients who are eligible for aldosterone antagonist treatment in the control group and 28.5% (n = 4) of those eligible in the intervention group had actually received aldosterone antagonist treatment. This difference was not statistically significant (P-value = 0.222).

None of the patients included in this study was eligible for QM-1, QM-2, QM-3, QM-5, QM-6, or QM-7. For QM-1 and QM-2, all the patients went to immediate and early invasive strategies, and no risk stratification score (TIMI or GRACE scores) was calculated. For QM-3, none of the patients in either group was comatose with out-of-hospital cardiac arrest. For QM-5, none of the patients in either of the groups were prescribed NSAIDs during hospitalization. Prasugrel was not prescribed during the study period to any of the patients as this drug was not available in GGH (QM-6). Finally, the inappropriate prescription of a high-dose aspirin (>100 mg) with Ticagrelor at discharge was not assessed due to the unavailability of a high-dose aspirin dosage in GGH, where all patients were prescribed 81 mg of aspirin at discharge (QM-7).

As presented in Table 5, the clinical pharmacist identified 136 TRPs in both groups. Sixty-one TRPs were identified in the control group, while 75 TRPs were identified in the intervention group. A total of 82 TRPs were related to QMs and PMs in both groups. There was no statistically significant difference between the groups in terms of the number of TRPs identified, neither individual TRP classes nor the overall number of TRPs (Table 5). However, the clinical pharmacist provided recommendations in relation to all TRPs in the intervention group, and 60 out of the 75 recommendations were accepted and implemented by a physician. Consequently, the number of TRPs in the intervention group was reduced to 15 TRPs on discharge. This was significantly lower than the number of TRPs left on discharge for the patients in the control group (61 TRPs) (p < 0.001). Therefore, the clinical pharmacist service significantly reduced the number of TRPs on discharge of the patients in the intervention group as compared to the control group, with an acceptance rate of 80%.

Although the current study provides interesting findings regarding the need for and the vital role of clinical pharmacists in the cardiology center in GGH, it still has several limitations. The current study was conducted in only one hospital in Saudi Arabia, and that limits the generalizability of our findings. In addition, exact differentiation in the diagnosis of either STEMI or NSTEMI was not clearly identified where all patients with angina pain were treated with PCI. This study used a historical retrospective control rather than a concurrent control group. This is attributed to ethical concerns, as it is not ethical to deny patients in the control group the proper quality of care provided by the clinical pharmacist. Furthermore, the use of a historical control guarantees the blindness of physicians and the avoidance of applying the recommendations provided by clinical pharmacists regarding the intervention group to the control groups if both groups were run concurrently. This allowed a valid comparison of PMs and QMs applied before and after clinical pharmacist intervention.