Impact of Clinical Pharmacist Interventions in Management of Diabetes in Primary Care in Saudi Arabia


King AbdulAziz Medical City, Riyadh, Saudi Arabia, +966 56 577 2757
Universiti Sains Malaysia, Penang, Malaysia
Vision Colleges, Riyadh, Saudi Arabia

Abstract

The study aimed to identify the impact and effectiveness of clinical pharmacist intervention on the management and overall quality of life of diabetic patients. Two cross-sectional studies using SF36 Health Survey, involving physicians and pharmacists at the Ambulatory Care Department in Riyadh, Saudi Arabia. Diabetic patients showed significant improvements in their QoL in terms of general health, energy and fatigue, pain scores, and social, emotional, and physical functions. Moreover, PC was found to have a significant impact on diabetes related QoL along with various outcome indicators, such as HbA1c, random blood sugar, and lipid profile in such patients. Additionally, satisfactory knowledge, good practice in identifying prescription errors were found among pharmacists. This study reveals that clinical pharmacists are valuable members of interdisciplinary primary care teams in ambulatory care. This can positively impact glycemic control in patients with type 2 diabetes and improve their quality of life. Also, the current study presented that a satisfactory extent of pharmaceutical care by an ambulatory clinical pharmacist was effective in improving HbA1c in patients with diabetes. A clinical pharmacist in ambulatory care was found to be eminent and of an added value to the patients, physicians, and healthcare team.

Keywords

Clinical Pharmacist, Diabetes, Primary Care, Intervention, Quality of Life, Pharmaceutical Care

Introduction

To evaluate the impact of the clinical pharmacist in an ambulatory care setting. Clinical pharmacists performed interventions on patients with chronic diseases: mainly diabetes, hypertension, and dyslipidemia. The current chapter presents the methodology of the interventions undertaken, results obtained, and discussion. Conclusions about the impact of clinical pharmacists in the management of diabetes and its complications are presented in the following chapters. The study aimed to evaluate if pharmaceutical care can improve disease knowledge, adherence to medications and rehabilitation, and quality of life (HRQOL) in patients with type 2 diabetes.

Ethics Approval

The study was approved by Institution Review Board (IRB) at National Guard Health Affairs, King Abdul Aziz Medical City, Riyadh, Saudi Arabia.

Methods

A trial was designed to evaluate the objective and was conducted in three outpatient centers of National Guard hospitals in Riyadh, Saudi Arabia. A longitudinal study follows individuals to see how things change over time. Hence, the study was a longitudinal prospective interventional study to evaluate the direct impacts of treatment or preventive measures on disease. A prevalence-based sample size determination was made. Previous literature has reported a varying prevalence. The prevalence of diabetes in Saudi Arabia is 25% (Aldossari et al., 2018). A target significance level of 5%, a confidence level of 95%, and a power of ≥ 80% were set. The Cochran equation allows calculating an ideal sample size provided a required level of precision, pet confidence level, and the expected proportion of the disease in the population. Hence, by applying Cochran’s equation, the minimum required sample size for the study. The sample size obtained was 287 and a 10% drop-out rate was added in the final count to yield 315 patients. This figure was considered as required sample size, who were recruited for intervention and control arms.

The study included atients attending KAAMC primary clinics, patients between the ages of 30 and 75 years, patients having uncontrolled hypertension, LDL equal to or more than 2.6 mmol/dL for diabetic patients, patients with HbA1c of 7.5% or above, patients taking oral antidiabetic drugs plus insulin. On the other hand, exclusion criteria were patients with a non-essential or secondary cause of hypertension, pregnancy, HIV, cancer patients, patients on insulin therapy (Type 1 diabetes), newly diagnosed diabetics, patients with controlled diabetes (HbA1c ≤7%).

The study was conducted in the Khasm Al-Aan primary care center, (Health Comprehensive Specialized Clinic, HCSC), and Umm Al-Hamam clinic (National Guard Comprehensive Specialized Clinic, NGCSC) where clinical pharmacists are present and practicing routine care along with family medicine physicians on daily basis. Patients from these two clinics were the target group for inclusion in the present study. For purpose of comparison, an equivalent number of patients in other NGHA family medicine centers were enrolled as control groups.

The study was carried out at three centers; two of them have clinical pharmacy services and one does not. The samples were divided into the Intervention arm: patients that would receive clinical pharmacist care and the Control arm: patients at an outpatient clinic that does not have a clinical pharmacy service, in which the patients would not receive care by a clinical pharmacist.

The training of the pharmacists was conducted for four weeks with a total of 8 lectures of 1-hour duration starting at 9 am on weekdays, i.e., Sunday to Thursday. The training also encompassed briefing about the study protocol, questionnaires, and forms to be used as well as patient diaries. The training module and disease education literature were also provided to them for self-study at home. A lecture on pharmaceutical care and counseling skills for pharmacists was given. The training was based on the topics: diabetes disease information, pathophysiology, disease epidemiology, symptoms, risk factors, diagnosis and treatment, self-care and quality of life in DM, the importance of adherence to treatment goals, brief introduction about the role of pharmacists in self-care.

Physicians at the clinics received a referral form including the inclusion/exclusion criteria developed by the clinical pharmacist. The referral form requested them to refer these patients to the clinical pharmacist to follow up on their treatment. The clinical pharmacist would review medications, patient history, laboratory tests, and overall assessment and would then develop a medication therapy management plan and contact the physician to discuss. A joint plan would then be agreed upon between the clinical pharmacist and the physician. The clinical pharmacists would keep following up on the patients’ adherence, provide patient education, and report on drug therapy problems. Each session to follow up with the patients would take around 45–50 minutes. The clinical pharmacists would document their interventions and recommendations in a ‘clinical pharmacist intervention form’. The clinical pharmacist collected a basal metabolic profile of each patient upon their first visit. Also, a QoL questionnaire (SF36) was collected from each patient upon the first visit to compare it later with a similar questionnaire at the final visit. There was a period of one year between the first and final visits. During this duration, the patient was followed up every three months, i.e., four visits within the year. Baseline data was collected when the patient visited the physician for the first time. Baseline laboratory tests were also scheduled before the next visit; however, the management of BP began at the first visit. In the combined physician–pharmacist care group, the patient was referred to the clinical pharmacist who reviewed the patient’s chart in detail and made an assessment, and discussed medication adherence and therapy options with both the physician and the patient. Hypertension, dyslipidemia, and diabetes parameters of the control group were monitored (Table 2 and Table 3).

Table 1: Patients’ data at baseline

Patient information

Entire sample

(N = 301)

Frequency (%)

Intervention group (N = 150)

Frequency (%)

Control group

(N = 151)

Frequency (%)

P value

Gender

0.45*

Male

106 (38.2)

38 (25.2)

68 (45.3)

Female

195 (64.7)

112 (74.8)

83 (54.7)

Marital status

0.636*

Single

43

34

9

Married

206

83

123

Other

52 (17.3)

33

19

Education

0.486*

Educated

246 (81.7)

137 (92.4)

109 (72.18)

No formal education

55 (18.3)

13 (8.6)

42 (27.8)

Occupation

0.381*

Employed

133 (44.2)

51

82

Retired

54 (17.9)

34

20

Un-employed

114 (37.9)

49

65

Monthly Income

0.821*

2500 < 5000

120 (39.9)

62 (44.6)

58 (38.4)

5000 < 10,000

181 (60.1)

77 (55.4)

93 (61.5)

Table 2: Parameters of patients in control group during the study£ (n = 151)

Variables

Visit 1

Mean + SD

Visit 2

Mean + SD

Visit 3

Mean + SD

Visit 4

Mean + SD

P-value

Age (years)

60.5 ± 7.8

Weight (kg)

81.5 ± 14.4

81.9 ± 15.2

83.4 ± 14.2

82.1 ± 15.6

0.084

SBP (mm Hg)

150.6 ± 15.6

149.1 ± 21.2

147.8 ± 18.7

147.8 ± 19.5

0.002*

DBP (mm Hg)

87.1 ± 13.8

82.1 ± 14.1

82.8 ± 11.4

81.3 ± 12.2

<0.0001*

Pulse (per minute)

87.0 ± 12.6

83.0 ± 13.2

83.1 ± 14.5

80.9 ± 12.6

<0.0001*

Random BS (mmol/L)

12.0 ± 3.7

12.1 ± 3.7

11.7 ± 2.9

11.0 ± 2.9

0.009

HbA1c (%)

9.4 ± 1.2

9.4 ± 1.1

9.5 ± 1.2

9.4 ± 1.1

0.015*

T Cholesterol (mmol/L)

4.6 ± 0.8

4.3 ± 0.9

4.3 ± 0.8

4.2 ± 0.7

<0.0001*

Triglycerides (mmol/L)

1.5 ± 0.6

1.6 ± 0.6

1.6 ± 0.6

1.6 ± 0.5

0.087

HDL (mmol/L)

1.0 ± 0.2

0.9 ± 0.2

0.9 ± 0.2

0.9 ± 0.2

0.116

LDL (mmol/L)

3.0 ± 0.6

2.7 ± 0.8

2.6 ± 0.7

2.7 ± 0.6

<0.0001*

BUN@ (mmol/L)

6.1 ± 1.9

6.2 ± 1.8

6.7 ± 5.5

6.7 ± 4.7

0.225

Creatinine (μmol/L)

85.6 ± 24.6

92.8 ± 85.5

86.7 ± 24.4

86.9 ± 24.6

<0.0001*

Albumin (g/L)

47.4 ± 7.9

47.7 ± 6.9

47.9 ± 6.9

48.1 ± 6.9

0.103

* Significance level P < 0.05 (Repeated measures ANOVA-Wilks' Lambda test was used)

£ follow-up for one year, three months between each visit

@ BUN Blood Urea Nitrogen

Table 3: Laboratory parameters of intervention group on follow-up£ (n = 150)

Variables

Visit 1

Mean + SD

Visit 2

Mean + SD

Visit 3

Mean + SD

Visit 4

Mean + SD

P-value

Age (years)

54.1 ± 9.1

Weight (kg)

81.8 ± 13.5

82.5 ± 12.0

81.6 ± 14.2

81.5 ± 12.0

0.001*

Systolic BP (mmHg)

127.8 ± 16.0

125.2 ± 13.3

126.7 ± 10.9

126.1 ± 8.8

0.825

Diastolic BP (mmHg)

71.2 ± 10.0

69.2 ± 7.3

71.5 ± 7.9

72.2 ± 7.7

0.516

Pulse (per minute)

84.0 ± 9.6

82.4 ± 11.0

83.5 ± 9.3

81.4 ± 7.0

0.022*

Random BS (mmol/L)

13.2 ± 4.7

10.4 ± 3.9

9.7 ± 3.4

8.6 ± 2.4

<0.0001*

HbA1c (%)

9.9 ± 1.9

9.4 ± 1.7

9.0 ± 1.5

8.5 ± 1.6

<0.0001*

Cholesterol (mmol/L)

4.6 ± 0.9

4.3 ± 0.8

4.3 ± 0.8

4.2 ± 0.6

<0.0001*

Triglycerides (mmol/L)

1.7 ± 0.6

1.5 ± 0.5

1.5 ± 0.5

1.5 ± 0.5

<0.0001*

HDL (mmol/L)

1.0 ± 0.2

1.0 ± 0.2

1.0 ± 0.2

1.1 ± 0.3

0.116

LDL (mmol/L)

3.0 ± 0.8

2.5 ± 0.7

2.4 ± 0.6

2.3 ± 0.5

<0.0001*

BUN (mmol/L)

7.1 ± 7.9

7.0 ± 7.8

6.8 ± 7.7

7.0 ± 8.5

<0.0001*

Creatinine (μmol/L)

87.2 ± 20.6

86.1 ± 20.5

85.1 ± 20.7

84.4 ± 20.5

<0.0001*

Albumin (g/L)

47.4 ± 6.9

46.3 ± 6.9

45.5 ± 6.8

44.8 ± 6.7

<0.0001*

*Significance level P < 0.05 (Repeated measures ANOVA-Wilks' Lambda test was used)

£follow-up for one year, three months between each visit

There were two treatment groups, i.e., the control group (CG) and the intervention group (IG). Patients in the intervention group received usual care and consultation with pharmaceutical care provided by pharmacists while those in the control group received usual care and consultation without pharmaceutical care.

Table 4: Mean difference between first and final visit in the laboratory parameters of both groups

Variable

Cases

Control

P-value

M

SD

M

SD

Weight (kg)

0.40

7.29

1.06

7.23

0.549

Systolic BP (mm Hg)

–1.97

16.08

–2.87

20.94

0.676

Diastolic BP (mm Hg)

0.89

12.04

–5.43

14.87

<0.0001*

Pulse (per minute)

–2.85

10.71

–6.27

13.68

0.017*

Random BS (mmol/L)

–4.66

4.27

–1.04

4.25

<0.0001*

HbA1C (%)

–1.63

1.63

0.00

1.50

<0.0001*

Cholesterol (mmol/L)

–0.38

0.89

–0.35

1.08

0.787

Triglycerides (mmol/L)

–0.17

0.60

0.08

0.51

<0.0001*

HDL (mmol/L)

0.08

0.23

0.01

0.20

0.010*

LDL (mmol/L)

–0.63

0.75

–0.31

0.75

<0.0001*

BUN (mmol/L)

–0.11

11.41

0.62

5.01

0.475

Creatinine (μmol/L)

–2.74

26.26

1.24

3.30

0.067

Albumin (g/L)

–2.62

9.05

0.70

10.65

0.004*

*Significance level P < 0.05 (Non-parametric test used when needed)

The outcome variables were systolic blood pressure (SBP) and diastolic blood pressure (DBP), which were measured at each visit, and the laboratory data (HbA1c, post-prandial blood sugar level, lipid profiles, and kidney and liver function tests) were collected every three months for one year (a total of four times). SF-36 scores, indicating the bio-psycho-social parameters of included patients, were used to measure their QoL. Data were entered and analyzed using Statistical Package of Social Sciences (SPSS) software. A codebook with variables and their labels was created. Categorical variables were expressed as frequencies and percentages and summarized in tables. Associations between continuous variables were presented in graphs and expressed with the help of means and standard deviations. Significant differences between the control and intervention groups were determined based on the outcomes measured (continuous or categorical) using the t-test and/or Chi-square correlation test. A P-value of ≤ 0.05 was considered to be significant between the intervention and the control groups.

Results

Impact of clinical pharmacist interventions on clinical outcomes

For the sake of this research, patients in the intervention group will be referred to as cases. Table 1 shows the baseline characteristics of the study population.

All the cases were asked to complete a questionnaire to assess their existing QoL, using form SF36. Table 4 and Table 5 show the responses given by the cases for each item. When asked about their overall general health, many of them, i.e., 45.7% said that it was not bad, while one-third of them, i.e., 33.1% declared it as bad and only 21.2% were having a good QoL. When the health status of these cases was compared at the one-year follow-up, the vast majority said that their health status had become worse or much worse, 23.2% found it the same, and only 4% said that their health was better than in the previous year.

Study participants were also asked about their QoL after the intervention had been provided to them. The changes in their life and their capabilities of performing their routine daily work after they had received PC in addition to the conventional care was also noted, and form SF36 was completed by the same cases who had been recruited pre-intervention. Table 4, Table 5 and Table 6 below demonstrates the responses given by the participants post-intervention.

The Table 7 show the pre and post-intervention comparison in cases using SF36 questionnaires. Significant differences were found between pain scores, social function, general health, emotional wellness, energy and fatigue, physical function, and limitation in physical and emotional roles of the study participants after provision of the intervention.

Discussion

The role of the clinical pharmacist is still being investigated in many countries. In Saudi Arabia, the role of the clinical pharmacist in an inpatient setting is becoming increasingly important. However, it is very uncommon for clinical pharmacists to work in an outpatient setting. The current study aimed at shedding light on the impact of clinical pharmacists in outpatient clinics by investigating their role in improving diabetes management, its complications, and the QoL of diabetic patients. By reviewing the patients’ profiles, treatment plan, discussions with the physician, patient education, improved drug adherence, and vigorous follow-up, the current study was able to report positive impacts of the clinical pharmacists. Compared to inpatients, (Davis, Clifford, Davis, & Batty, 2005) reported PC to be a useful adjunct to conventional management of diabetes in primary care, because monitoring of drug therapy can prevent problems associated with adverse drug reactions and polypharmacy. It can also minimize prescription errors and can ensure compliance (Al-Quteimat & Amer, 2016). After participating in the educational sessions, pharmacists reported that good communication skills, collaboration with other healthcare providers, and an empathic attitude towards patients can sustain such goals. In line with the study findings, (Merks, Swieczkowski, & Jaguszewski, 2016) also suggested that the practice of PC by pharmacists can be effective in improving not only clinical outcomes but also the QoL of diabetes patients. Specifically, the implementation of PC results in enhanced glycaemic control and a lower risk score in Type II DM patients (Al-Mazroui et al., 2009). (Vlcek, Malý, & Dosedel, 2009) also found acceptable knowledge in their study of pharmacists. The study by (Alhabib, Aldraimly, & Alfarhan, 2016) showed a promising attitude, an interest in improving their knowledge, and a recognition of the importance of PC in the practice of their profession. The authors also concluded that those individuals who received the PC had a statistically significant drop in blood pressure, HbA1c, lipid profile, and ultimately CHD and an improvement in their QoL, all of which are consistent with the findings of the study. The clinical pharmacists started to follow up with diabetes patients where they showed high HbA1c levels. As the study progressed and upon following visits, HbA1c levels decreased, whereas the patients in the control group did not experience any improvement in HbA1c. As HbA1c is considered as one of the most important markers for diabetes control, this study reflects that the input of clinical pharmacists was valuable in diabetes control. In conjunction with the current study, the Fremantle study (Clifford, Davis, Batty, & Davis, 2005) demonstrated a decrease in the glycaemic levels and systolic as well as diastolic BPs of the participants receiving PC, and HbA1c reduced

Table 5: Responses to questionnaire by intervention patients before intervention; n = 151

Questions

Responses (%)

Very bad

Bad

Not bad

Good

Very good

Excellent

General health

0

50 (33.1)

69 (45.7)

32 (21.2)

0

0

Much worse

Worse

Same

Better

Health compared to last year

27 (17.9)

83 (55)

35 (23.2)

6 (4)

Does your health limit your:

Never

Less

More

Vigorous activities

10 (6.6)

56 (37.1)

85 (56.3)

Moderate activities

19 (12.6)

86 (57)

46 (30.5)

Lifting/carrying groceries

35 (23.2)

82 (54.3)

34 (22.5)

Climbing several flights of stairs

13 (8.6)

45 (29.8)

93 (61.6)

Climbing one flight of stairs

34 (22.5)

80 (53)

37 (24.5)

Bending, kneeling, stooping

108 (71.5)

21 (13.9)

22 (14.6)

Walking >1 mile

32 (21.2)

80 (53)

39 (25.8)

Walking several blocks

68 (45)

70 (46.4)

13 (8.6)

Walking one block

85 (56.3)

60 (39.7)

6 (4)

Bathing or dressing yourself

137 (90.7)

8 (5.3)

6 (4)

In last 4 weeks: (physical health)

No

Yes

Cut down amount of time

10 (6.6)

141 (93.4)

Accomplished less

16 (10.6)

135 (89.4)

Limited kind of work

21 (13.9)

130 (86.1)

Difficulty in performing work

18 (11.9)

133 (88.1)

In last 4 weeks: (emotional problems)

No

Yes

Cut down amount of time

10 (6.6)

141 (93.4)

Accomplished less

18 (11.9)

133 (88.1)

Did not work carefully as usual

12 (7.9)

139 (92.1)

Never

Low

Moderate

High

Severe

Problems interfered with work (past 4 weeks)

1 (.7)

10 (6.6)

69 (45.7)

64 (42.4)

7 (4.6)

No pain

Very low

Low pain

Moderate

Too much

Severe pain

Bodily pain (past 4 weeks)

2 (1.3)

16 (10.6)

51 (33.8)

73 (48.3)

9 (6)

Never

Low

Moderate

High

Severe

Pain interfered with work (past 4 weeks)

12 (7.9)

76 (50.3)

58 (38.4)

5 (3.3)

In past 4 weeks:

Never

Rarely

Sometimes

Mostly

Always

All time

Did you feel full of pep?

18 (11.9)

79 (52.3)

49 (32.5)

4 (2.6)

1 (.7)

Have you been a nervous person?

9 (6)

37 (24.5)

31 (20.5)

59 (39.1)

15 (9.9)

Felt so down that nothing could cheer you

5 (3.3)

34 (22.5)

63 (41.7)

25 (16.6)

23 (15.2)

1 (.7)

Felt calm and peaceful

3 (2)

46 (30.5)

67 (44.4)

27 (17.9)

8 (5.3)

0

Have a lot of energy

26 (17.2)

84 (55.6)

31 (20.5)

6 (4)

4 (2.6)

0

Felt downhearted and blue

108 (71.5)

25 (16.6)

14 (9.3)

2 (1.3)

2 (1.3)

0

Felt worn out

3 (2)

6 (4)

25(16.6)

32 (21.2)

56 (37.1)

29 (19.2)

Have you been a happy person?

0

43 (28.5)

78 (51.7)

19 (12.6)

11 (7.3)

0

Feel tired?

0

10 (6.6)

23 (15.2)

18 (11.9)

41 (27.2)

59 (39.1)

Never

Infrequently

Sometimes

Mostly

All time

Interference in social activity

1 (.7)

46 (30.7)

83 (55.3)

19 (12.7)

1 (.7)

Mostly wrong

Wrong

Don’t know

True

Mostly true

Get sick a little earlier than others

57 (37.7)

2 (1.3)

16 (10.6)

3 (2)

73 (48.3)

As healthy as anybody else

63 (41.7)

0

50 (33.1)

0

38 (25.2)

Expect health to get worse

10 (6.6)

0

126 (83.4)

0

15 (9.9)

Health is excellent

46 (30.5)

0

81 (53.6)

0

24 (15.9)

Table 6: Responses to questionnaire by patients after intervention (N = 151)

Questions

Responses

Very bad

Bad

Not bad

Good

Very good

Excellent

General health

0

0

0

3 (2)

96 (63.6)

52 (34.4)

Much worse

Worse

Same

Better

Much better

Health compared to last year

0

0

2 (1.3)

63 (41.7)

86 (57)

Does your health limit your:

Never

Less

More

Vigorous activities

42 (27.8)

101 (66.9)

8 (5.3)

Moderate activities

75 (49.7)

73 (48.3)

3 (2)

Lifting/carrying groceries

116 (76.8)

32 (21.2)

3 (2)

Climbing several flights of stairs

57 (37.7)

93 (61.6)

1 (.3)

Climbing one flight of stairs

147 (97.4)

4 (2.6)

0

Bending, kneeling, stooping

149 (98.7)

2 (1.3)

0

Walking >1 mile

130 (86.1)

21 (13.9)

0

Walking several blocks

149 (98.7)

2 (1.3)

0

Walking one block

151 (100)

0

0

Bathing or dressing yourself

151 (100)

0

0

In last 4 weeks: (physical health)

No

Yes

Cut down amount of time

138 (91.4)

13 (8.6)

Accomplished less

129 (85.4)

22 (14.6)

Limited kind of work

96 (63.6)

55 (36.4)

Difficulty in performing work

141 (93.4)

10 (6.6)

In last 4 weeks: (emotional problems)

No

Yes

Cut down amount of time

137 (90.7)

14 (9.3)

Accomplished less

137 (90.7)

14 (9.3)

Did not work as carefully as usual

125 (82.8)

26 (17.2)

Never

Low

Moderate

High

Severe

Problems interfered with work (past 4 weeks)

48 (31.8)

95 (62.9)

6 (4)

1 (.7)

1 (.7)

No pain

Very low

Low pain

Moderate

Too much

Severe pain

Bodily pain (past 4 weeks)

57 (37.7)

85 (56.3)

5 (3.3)

2 (1.3)

0

2 (1.3)

Never

Low

Moderate

High

Severe

Pain interfered with work (past 4 weeks)

98 (64.9)

49 (32.5)

2 (1.3)

0

2 (1.3)

In past 4 weeks:

Never

Rarely

Some-times

Mostly

Always

All the time

Did you feel full of pep?

0

0

5 (3.3)

36 (23.8)

103 (68.2)

7 (4.6)

Have you been a nervous person?

7 (4.6)

132 (87.4)

11 (7.3)

0

1 (.7)

0

Felt so down that nothing could cheer you

115 (76.2)

31 (20.5)

5 (3.3)

0

0

0

Felt calm and peaceful

4 (2.6)

2 (1.3)

1 (.7)

40 (26.5)

92 (60.9)

12 (7.9)

Have a lot of energy

1 (.7)

2 (1.3)

13 (8.6)

54 (35.8)

77 (51)

4 (2.6)

Felt downhearted and blue

142 (94)

7 (4.6)

1 (.7)

0

1 (.7)

0

Felt worn out

7 (4.6)

120 (79.5)

21 (13.9)

0

3 (2)

0

Have you been a happy person?

0

4 (2.6)

19 (12.6)

123 (81.5)

5 (3.3)

Feel tired?

5 (3.3)

138 (91.4)

7 (4.6)

0

1 (.7)

0

Never

Infrequently

Some-times

Mostly

Always

All time

Interference in social activity

85 (57.8)

55 (37.4)

3 (2)

2 (1.4)

0

2 (1.4)

Mostly wrong

Wrong

Don’t know

True

Mostly true

Get sick a little earlier than others

129 (86.6)

16 (10.7)

2 (1.3)

0

2 (1.3)

As healthy as anybody else

2 (1.3)

0

3 (2)

16 (10.7)

128 (85.9)

Expect health to get worse

94 (63.5)

10 (6.8)

43 (29.1)

0

1 (.7)

Health is excellent

4 (2.6)

0

4 (2.6)

12 (8.1)

129 (86.6)

Table 7: Pre-Post comparison of changes in SF36 of patients (N = 151)

Theme

Mean Pre

Mean Post

Mean Diff.

SD

t-test

P-value

Pain Q21–22

87.6

35.7

51.9

17.2

37.2

<0.001

Social function Q 20, 32

42.2

48.1

5.9

17.8

4.1

<0.001

General health Q 1, 33–36

23.9

57.9

34

14.1

29.7

<0.001

Emotional wellness Q 24–26, 28, 30

15.6

47.8

32.2

14.4

27.4

<0.001

Energy fatigue Q 23, 27, 29, 31

25.1

73.7

48.7

19.3

31

<0.001

Physical function Q 3–12

11.8

44.7

32.8

19.2

21

<0.001

Physical role limitation Q 13–16

16.5

89.2

72.7

28.9

30.9

<0.001

Emotional role limitation Q 17–19

11.9

91.2

79.2

31

31.4

<0.001

*Q2 was not included in any thematic analysis as per reference

by an average of 0.5% over the 12-month follow-up period from a baseline of 7.5%, even though there was no change in the control group. Moreover, the decreasing trend in HbA1c was also found in RBS in both genders of diabetic patients who received PC as compared to controls, who showed an initial decrease with a dip and then a gradual increase, in contrast to a consistent downward trend observed in the cases. Likewise, Farsaei et al. from Iran revealed a significant decrease in HbA1c (Farsaei, Sabzghabaee, Zargarzadeh, & Amini, 2011), and Suppapitiporn et al. also reported improved efficacy of glycaemic control in each consultation visit with a pharmacist (Suppapitiporn, Chindavijak, & Onsanit, 2005). Taken together, such inferences suggest the success of PC towards reducing mean glycaemic values. An RCT found a significant reduction in SBP, in addition to blood glucose and HbA1c levels in the intervention group in comparison to the control group after a period of 12 months. Other community-based studies (Barber, Wilson, & Willson, 1999) have demonstrated a greater reduction, i.e., 2% over a shorter period (3–4 months) but from a higher baseline mean HbA1c (11%) in an outpatient clinic setting. Another study reported a mean reduction of 0.4%, i.e., from 7.5% to 7.1% in HbA1c over four years. Yet, six-monthly follow-ups did not show any advantage of PC over routine care in terms of improvement in HbA1c (Clifford et al., 2011). Likewise, a prospective study that was conducted to investigate the impact of PC on QoL in T2DM patients in a private tertiary hospital in South India found it effective in modifying outcome indicators in an eight-month follow-up period. Mean values of HbA1c decreased from 8.44% to 6.73% (P < 0.01) and fasting blood glucose from 195.57 to 107.25 mg/dl between the baseline and end-line interviews in the PC group. Treatment satisfaction score also improved in a similar pattern. Improvement in the intervention group was particularly noted in reductions concerning worries, the future and the living condition domains of the patients. The age range of the participants in both the groups was between 32 and 85 years old with an approximately equal male-to-female ratio, which was also similar to the current study (Sriram et al., 2011). Also, a few other studies with a similar one-year follow-up period to the present research have pointed out that overall changes for the better in the lifestyle of diabetic patients were observed. (Correr, Melchiors, Fernandez-Llimos, & Pontarolo, 2011) reported that the intervention group in their study presented a noteworthy improvement, i.e., 8.6% in health-related QoL compared to the control group (1.6%) in terms of impact and satisfaction domains after 12 months of follow-up. (Korcegez, Sancar, & Demirkan, 2017) at the end of their 12-month study period in Northern Cyprus also observed a significant reduction in HbA1c, from 8.29% to 7.55%, and in fasting blood glucose in its intervention arm that was given PC. No significant differences were found between the groups in HDL, LDL, triglycerides, and total cholesterol levels (P = 0.063, 0.331, 0.896 and 0.04, respectively). This was in contrast to the findings of the present study, as a consistent fall was noticed in LDL, total cholesterol and triglycerides, whereas an increase in HDL was observed when compared to baseline across both the genders. Although DBP, BMI and triglycerides were lower in the intervention group, it was not significant. Total cholesterol, LDL and HDL were significantly higher in the intervention group than in the control group, which is in contrast to current study, where LDL, cholesterol and triglycerides were lower and HDL was higher in cases compared to controls in the post-intervention period (Ali et al., 2012). In the Asheville Project, Cranor and Christensen also reported significant improvements in glycaemic control, LDL and blood pressure (Cranor & Christensen, 2003). Similar to the present study findings, other studies have also revealed the beneficial effect of pharmacist intervention on lipid profiles. For instance, Bellary et al. showed a significant decline in total cholesterol (Bellary et al., 2008). The conclusions obtained from the findings of the present study indicate that PC has a noticeable impact on certain laboratory parameters including glycaemic levels (HbA1c and RBS) and lipid profile (cholesterol, LDL, HDL and triglycerides) in diabetic patients, along with improvements in the general health of the cases. A positive association was also seen between high education and the presence of higher levels of HDL, and lower levels of LDL, RBS and HbA1c. PC was hence found to be valuable and helpful in supporting diabetic patients in dealing with their disease with regard to improvements in their clinical and biochemical profile, to prevent complications and to promote good health and wellbeing. Clinically significant differences were obtained in terms of post-prandial blood glucose (PPBG) levels (7.4 ± 1.7 vs. 10.4 ± 2.0 mmol/L) between intervention and control groups, respectively. The increase in the percentage of the intervention group that reached target PPBG was from 12.0 to 54.0% (P = 0.001), while those that reached the target HbA1c increased from 52.0% from 10.5% initially. HbA1c values were improved for the intervention group compared to the control group (7.8 ± 1.9% vs. 9.5 ± 2%; P = 0.001), respectively. Input from pharmacists resulted in a greater proportion of the intervention group participants attaining comprehensive clinical outcomes for diabetes in comparison to the control group (Ahmad et al., 2015).

As the patients were still in primary care, they did not develop severe complications and the cases did not deteriorate. This was obvious from the results reported, especially from the renal function tests, so the renal marker did not show any differences. If any of these complications do arise, the patient goes to inpatient or specialized care, and is no longer under primary or FP care. Hence, the involvement of the clinical pharmacist in early intervention decreases the burden of the disease in terms of minimizing hospital admissions and complications and, in turn, the costs of disease management.

The current study implemented Short Form 36 (SF-36) questionnaire. SF-36 is the most widely used general health status tool. The questionnaire consists of eight items that cover the aspects of: [1] physical functioning; [2] role-physical; [3] pain; [4] general health; [5] vitality; [6] social functioning; [7] role-emotional; and [8] mental health (Ware & Sherbourne, 1992). Changes in fewer than four SF-36 scores are considered as small, four to 10 as moderate, and more than 10 as large (Contopoulos-Ioannidis, Karvouni, Kouri, & Ioannidis, 2009). In the current study, around seven parameters were seen to have improved in the post-intervention phase of the study. The results provided some preliminary evidence that PC can have a positive impact on HRQoL in diabetics, with the evidence pointing towards a larger effect on mental health than on physical health; however, the findings are inconclusive, as different scales were used to assess the QoL and so it is difficult to compare the studies (Krass & Dhippayom, 2013).

A study using the SF36 questionnaire focused on the change in the QoL of participants after PC was given to them. QoL is well accepted and is one of the most important outcomes and goals in the treatment of diabetes. Improvements were seen in the domains of general health, physical aspects, functional capacity, pain, vitality, and mental health. Such improvements in the QoL of patients may be partly attributed to their increased contact with the clinical pharmacist because of their uncontrolled diabetes, but it is also possibly associated with appropriate adherence to lifestyle changes following counseling.

In practical terms, among additional benefits was the contribution by the qualified pharmacist having prior exposure to diabetes-specific medication issues with formal education, who could implement the present PC model after the patients were selected as cases. Hence, the pharmaceutical care process was meant to complement formal diabetes education. It was found that pharmacists developed good relationships with individual patients and other allied health personnel during the study; another factor that might have contributed to improved outcomes. Our PC model was flexible and can be adapted to a variety of settings. The pharmacist in this study was working relatively independently, but the program could be easily and conveniently implemented by diabetes educators, physicians, pharmacists, and other health professionals in an outpatient or inpatient setting. In this regard, the data from this study, as well as from others, argue that the pharmacist can be beneficial in addition to the integrated care for patients with T2D (Irons et al., 2002; Krass et al., 2011; Wagner et al., 2001).

The study established the favorable impact of clinical pharmacists in accomplishing a primary therapeutic goal for overall diabetes control in patients with diabetes mellitus, in addition to the routine care provided by the physician in ambulatory care set up in Saudi Arabia. The improved QoL indicates the advantages of pharmacist-driven education and the significance of consultations with a pharmacist in an ambulatory setting, as physicians are usually not able to deliver prolonged counseling and hours of consultation; their follow-ups are not frequent, and hence many of the patients’ questions remain unanswered. On the other hand, pharmacists’ follow-ups led the patients to air their queries and to clarify their perceptions, as they understood well the importance of maintaining a healthy lifestyle by managing their diabetes.

Conclusion

Pharmaceutical Care was found to have a positive impact on diabetes-related QoL, along with various other outcome indicators, such as HbA1c, RBS, and lipid profile, for T2DM patients. Inferences achieved also recognized the favorable influence of the clinical pharmacist in practicing PC to attain therapeutic goals, in addition to the overall control of their patients’ diabetes, along with the routine care offered by the physician. Such improvements noticeably indicate the need to incorporate the input from clinical pharmacists with routine care in the hospital as well as in outpatient settings to maximize the benefits for diabetic patients. Moreover, these strategies can also be applied to various chronic illnesses so that the maximum number of patients can experience beneficial effects in controlling and managing their respective illnesses. The study established the favorable impact of clinical pharmacists in accomplishing a primary therapeutic goal in patients having diabetes mellitus for overall diabetes control; in addition to the routine care provided by the physician. The improved QoL indicated the advantages of pharmacist-driven education and the significance of consultations with a pharmacist in a hospital setting as physicians are usually not able to deliver prolong counseling and hours of consultation, their follow-ups are not frequent and hence many of the patients’ questions remain unanswered. On the other hand, pharmacists’ follow-up led the patients to take out their queries and clarify their perceptions as well as they understood the importance of maintaining a healthy lifestyle by managing their diabetes. Hence, the study can reimburse that an ambulatory care clinical pharmacist is effective in identifying drug therapy problems. Though in terms of monetary value, the study did not tap into these factors and whether the involvement of clinical pharmacists resulting in significant cost savings to the institution or not.

Acknowledgement

The authors acknowledge the healthcare staff in King Abdulaziz Medical City for their help to accomplish the current study, in terms of documents provision, clean environment, and any direct or indirect help from their side.

Funding Support

The study was not sponsored by any funding.

Conflicts of Interest

The authors do not have conflicts of interest to declare.