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  • Research article
  • Open Access
  • Open Peer Review

Patient-centered medical home care access among adults with chronic conditions: National Estimates from the medical expenditure panel survey

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BMC Health Services Research201818:744

https://doi.org/10.1186/s12913-018-3554-3

  • Received: 4 May 2018
  • Accepted: 21 September 2018
  • Published:
Open Peer Review reports

Abstract

Background

The Patient-Centered Medical Home (PCMH) model is a coordinated-care model that has served as a means to improve several chronic disease outcomes and reduce management costs. However, access to PCMH has not been explored among adults suffering from chronic conditions in the United States. Therefore, the aim of this study was to describe the changes in receiving PCMH among adults suffering from chronic conditions that occurred from 2010 through 2015 and to identify predisposing, enabling, and need factors associated with receiving a PCMH.

Methods

A cross-sectional analysis was conducted for adults with chronic conditions, using data from the 2010–2015 Medical Expenditure Panel Surveys (MEPS). Most common chronic conditions in the United States were identified by using the most recent data published by the Agency for Healthcare Research and Quality (AHRQ). The definition established by the AHRQ was used as the basis to determine whether respondents had access to PCMH. Multivariate logistic regression analyses were conducted to detect the association between the different variables and access to PCMH care.

Results

A total of 20,403 patients with chronic conditions were identified, representing 213.7 million U.S. lives. Approximately 19.7% of the patients were categorized as the PCMH group at baseline who met all the PCMH criteria defined in this paper. Overall, the percentage of adults with chronic conditions who received a PCMH decreased from 22.3% in 2010 to 17.8% in 2015. The multivariate analyses revealed that several subgroups, including individuals aged 66 and older, separated, insured by public insurance or uninsured, from low-income families, residing in the South or the West, and with poor health, were less likely to have access to PCMH.

Conclusion

Our findings showed strong insufficiencies in access to a PCMH between 2010 and 2015, potentially driven by many factors. Thus, more resources and efforts need to be devoted to reducing the barriers to PCMH care which may improve the overall health of Americans with chronic conditions.

Keywords

  • PCMH
  • MEPS
  • Care access
  • Chronic conditions

Background

In the United States (U.S.), chronic conditions are among major causes of disability, mortality, and high medical costs [14]. It has been estimated that nearly half (50.9%) of U.S. adults live with at least one chronic condition, while 26% have two or more chronic conditions [5]. These conditions are responsible for 46% of all deaths among the U.S. population annually. Furthermore, the associated costs of these conditions are enormous and compromise the health of the U.S. [6] It was estimated that 86% of U.S. health care expenditures are correlated with the treatment of chronic conditions [7].

With the growing number of chronic conditions [8], the associated costs made by these conditions will continue to threaten the entire federal budget. Over the last three decades, several improvements have been implemented into U.S. law, but they all focused heavily on insurance reforms. These steps will not be adequate unless they are coupled with fundamental health care improvement efforts targeting the primary care practice [9]. To achieve this goal, more attention has been paid to replace the poorly coordinated, acute-focused, episodic primary care practice with a care that is continuous, comprehensive, patient-centered, coordinated, and accessible, and that provides communication and shared decision-making [10].

A recent, successful approach to improve the chronic care management is the patient-centered medical home (PCMH). The PCMH model is an innovative primary care delivery system that has served to improve the quality of care and to reduce medical costs. PCMH rearranges how primary care service is designed and delivered to the patients, with the prime focus on patient needs and preferences [11, 12]. Over the past few years, with the growing numbers of adults with chronic conditions, many healthcare stakeholders in the U.S. have adopted the PCMH to prevent or inhibit the progression of specific chronic conditions [12].

Several studies have demonstrated the ability of PCMH application in improving the primary care quality, safety, and efficiency across the U.S. Some studies, for example, have suggested that receiving PCMH care is associated with a decreased number of hospitalizations and emergency room visits [1318]. Others have also identified improvements in the quality of health care after implementing PCMH care [17, 19, 20].

Despite growing evidence in the literature that supports the effectiveness of the PCMH in improving health care outcomes and reducing costs, the extent of the PCMH’s adoption in treating Americans with chronic conditions remains unknown. Therefore, the objective of this study is to describe, at the national level, the changes in receiving PCMH among adults suffering from chronic conditions and to identify predisposing, enabling, and need factors associated with accessing PCMH care.

Methods

Data source

We conducted an observational cross-sectional analysis of the 2010–2015 Medical Expenditure Panel Survey (MEPS). MEPS has been conducted by the Agency for Healthcare Research and Quality (AHRQ) since 1996. MEPS is a nationally representative population-based survey of health care utilization and expenditures of the U.S. civilian noninstitutionalized population. The MEPS utilizes an overlapping panel design in which participant data are collected over a series of five rounds of interviews spaced about five months apart. The collected data include patient demographics, access to health care, use of health services, health conditions, health status, and other data as well. Information regarding the data and a description of its survey design have been published previously [21].

Study population

Individuals aged 18 years and older who were diagnosed with at least one of the most common chronic conditions (i.e., hypertension, hyperlipidemia, mood disorders, diabetes, anxiety disorders, upper respiratory conditions, arthritis, asthma, or coronary artery disease) were identified. These conditions were considered to be chronic because they are long-lasting, cause diminished physical and/or mental capacity, or require long-term monitoring and medical interventions [22]. The prevalence of these conditions has been confirmed by the most recent data published by the Agency for Healthcare Research and Quality (AHRQ) [23]. According to MEPS documentation, patients in each year may be used as independent observations since each year in MEPS data is intended to be nationally representative [24].

Primary outcome

The primary outcome of our analysis was determining whether the individual was receiving care consistent with PCMH principles. PCMH care was defined using the provider-related questionnaires in MEPS. AHRQ’s definition classifying PCMH care was used to determine whether respondents had a PCMH [25]. The respondent was considered to be receiving PCMH if the patient received comprehensive, patient-centered, and accessible care. Table 1 shows the survey items used to define PCMH features based on AHRQ’s criteria. Similar questions had been used in high-quality research to detect access to PCMH care using the same data [2629].
Table 1

MEPS survey items used to define PCMH care

PCMH criteria

Survey items used

Comprehensive care

 

Does the provider usually ask about medications and treatments prescribed by other doctors

 

Does the provider provide care for new health problems

 

Does the provider provide preventive healthcare

 

Does the provider provide referrals to other health professionals

 

Does the provider provide care for ongoing health problems

Patient-centered care

 

Does the provider show respect for the medical, traditional, and alternative treatments other doctors may give

 

Does the provider explain all healthcare options to participant

 

Does the provider ask participant to help decide treatment choice

Accessible care

 

Is it difficult to contact the provider by phone about a health problem during regular office hours

 

Does the provider offer night and weekend office hours

 

Does the provider speak the participant’s language or provide translation services

We determined that the care received by an individual was comprehensive care if the provider did all of the following: 1) usually asked about any medications prescribed by other doctors; 2) provided care for new health problems; 3) provided preventive care; 4) offered referrals to other health professionals; and 5) provided care for ongoing health problems. We considered the individual to have received patient-centered care if the provider 1) showed respect for the medical, traditional, and alternative treatments other doctors may give; 2) explained all healthcare options to the individual; and 3) asked the individual to help decide on treatment. We considered care to be accessible if the provider 1) was easy to contact by phone about a health problem during regular office hours; 2) offered night and weekend office hours; and 3) spoke the participant’s language or provided translation services. Participants with responses of don’t know, refused, or not ascertained to any question were excluded from the final dataset.

Independent variables

By using the Andersen Behavioral Model [30] in the current analysis, we examined the effects of person-specific predisposing, enabling, and need factors on having a PCMH. Predisposing factors investigated in this study included age, sex, race, marital status, and education years. Enabling factors consisted of health insurance, employment status, family income, and census region. (Appendix A contains a list of states composing each region with demographic data.) [31] Our assessments of health needs were based on self-rated health status variables (good/excellent or poor/fair).

Data analysis

Descriptive statistics were used to characterize and evaluate changes in annual percentage for individuals who had PCMH over the six-year pooled dataset. The number of those individuals and their weighted percentage were calculated. Rao–Scott chi-square (a design-adjusted Pearson chi-square test) [32] analyses were performed to examine significant subgroup differences across strata for the two groups (having PCMH and having no PCMH). Adjusted multiple logistic regression analyses were then conducted to assess predictors associated with having a PCMH. In all analyses, we control for age, sex, race, marital status, education years, health insurance type, employment status, family income, chronic conditions, and calendar year. The c-statistic was calculated for each model to assess the model’s practical ability for correctly discriminating an individual outcome (PCMH/ No PCMH). A model demonstrates a good discrimination when the c-statistic is > 0.7 and outstanding when > 0.9.

To adjust for the complex multistage survey design and nonresponse, the estimates that are calculated from the data sample were multiplied by person-specific sampling weights provided within the original datasets of MEPS. All analyses were conducted with the use of SAS 9.4 software (SAS, Cary, NC).

Results

A total of 20,403 patients with chronic conditions were identified, representing 213.7 million U.S. lives between 2010 and 2015. Approximately 19.7% of the patients were categorized as the PCMH group at baseline who met all the PCMH criteria defined in this study. The proportion of adults with chronic conditions who received a PCMH decreased from 22.3% in 2010 to 17.8% in 2015. However, in 2012 there was an increase in the number to 23.31% (Table 2).
Table 2

Annual changes in individuals with chronic conditionsa

Year

N

N, weighted, in million

No PCMH, % (95% CI)

PCMH, % (95% CI)

2010

1458

15.6

77.69 (74.73–80.64)

22.31 (19.35–25.26)

2011

2935

31.8

81.21 (78.91–83.51)

18.78 (16.48–21.26)

2012

3725

37.3

76.68 (74.42–78.94)

23.31 (21.05–25.57)

2013

3313

33.7

81.31 (79.05–83.57)

18.68 (16.42–20.94)

2014

3112

33.7

80.13 (77.91–82.35)

19.86 (17.64–22.08)

2015

5860

61.3

82.17 (80.37–83.97)

17.82 (16.02–19.62)

Abbreviations: CI, confidence interval

aSample size (N) is unweighted; Percentage weighted using weights provided with 2010–2015 MEPS

Table 3 presents the results of the study population’s descriptive characteristics. Individuals aged between 41 and 65 were most likely to report that they had at least one chronic condition (49.5%). The overall sample was predominantly female (57.1%), white (79.5%), married (57.8%), educated beyond high school (59.6%), insured by private insurance (70.1%), employed (58.1%), from a family with a high level of income (42.1%), from the southern U.S. geographical region (38.2%), and in excellent/good perceived health (79.7%). Hypertension, arthritis, and hyperlipidemia were the most prevalent chronic conditions among the study sample, 47.4%, 44.9%, and 37.8%, respectively.
Table 3

Baseline characteristics of individuals with chronic conditions, by PCMH access

Characteristic

  

Has a PCMH

P

Total

 

No

Yes

N

Weighted %

N

Weighted %

N

Weighted %

(N = 20,403; Weighted

N = 213,733,954)

(N = 16,443; Weighted

N = 171,600,510)

(N = 3960; Weighted

N = 42,133,444)

Predisposing

Age (Years)

      

0.001

 19 to 40

5423

26.3

4299

25.9

1124

28.3

 

 41 to 65

10,227

49.5

8213

49.2

2014

50.5

 

 66 and older

4753

24.1

3931

24.8

822

21.2

 

Sex

      

0.012

 Female

12,196

57.1

9926

57.6

2270

55.2

 

 Male

8207

42.8

6517

42.4

1690

44.7

 

Race

      

0.8

 Non-white

6834

20.4

5485

20.5

1349

20.3

 

 White

13,569

79.5

10,958

79.5

2611

79.6

 

Marital Status

      

<.0001

 Married

10,810

57.8

8508

56.7

2302

62.1

 

 Never Married

4272

18.4

3465

18.5

807

18.3

 

 Separated

5321

23.6

4470

24.7

851

19.5

 

Education Years

      

0.001

  < 12 Years

3505

14.1

2980

14.7

525

11.8

 

 12 Years

4764

26.2

3833

26.3

931

25.5

 

  > 12 Years

8876

59.6

6956

58.9

1920

62.6

 

Enabling

Health Insurance

      

<.0001

 Any Private

12,422

70.1

9708

68.5

2714

76.6

 

 Public Only

6301

23.7

5319

25.04

982

18.2

 

 Uninsured

1680

6.2

1416

6.4

264

5.2

 

Employment Status

      

<.0001

 Employed

11,006

58.1

8656

57.01

2350

62.7

 

 Not employed

9336

41.8

7734

42.9

1602

37.2

 

Family Income Categorical

      

<.0001

 High

6515

42.2

5001

40.8

1514

47.6

 

 Middle

5913

28.4

4747

28.3

1166

28.8

 

 Poor/ Low

7975

29.4

6695

30.8

1280

23.6

 

Census Region

      

<.0001

 Midwest

4073

21.8

3175

20.9

898

25.5

 

 Northeast

3355

17.8

2538

16.7

817

21.9

 

 South

7872

38.2

6583

39.8

1289

31.8

 

 West

5103

22.2

4147

22.5

956

20.8

 

Healthcare Need

Self-Reported Health

      

<.0001

 Excellent/Good

15,144

79.7

1,1957

78.4

3187

85.03

 

 Fair/Poor

4872

20.3

4157

21.6

715

14.9

 

Chronic Conditions

 Hypertension

10,207

47.4

8350

48.1

1857

44.4

0.001

 Hyperlipidemia

7732

37.8

6359

38.6

1373

34.5

0.0001

 Mood Disorders

3902

20.4

3259

21.3

643

17.05

<.0001

 Diabetes Mellitus

4474

19.1

3673

19.4

801

17.9

0.06

 Anxiety Disorders

3589

19.4

2976

19.9

613

17.1

0.002

 Upper Respiratory Conditions

7405

38.8

5888

38.03

1517

42.1

0.0005

 Arthritis

9250

44.9

7682

46.3

1568

39.3

<.0001

 Asthma

2557

12.2

2071

12.3

486

11.8

0.4

 Coronary Artery Disease

2197

10.8

1787

11.05

410

9.8

0.04

PCMH indicates Patient-Centered Medical Home

Compared to those who did not receive a PCMH, those who received PCMH were more likely to be younger, male individuals (44.7% vs. 42.4%), married individuals (62.1% vs. 56.7%), employed (62.7% vs. 57.01%), from families with higher income levels (47.6% vs. 40.8%), covered by private insurance (76.6% vs. 68.5%), and in excellent/good perceived health status (85.03% vs. 78.4%). They were also more likely to have achieved a higher level of education (had more than 12 years of education, 62.6% vs. 58.9%), and less likely to be from the southern U.S. geographical region (31.8% vs. 39.8%).

In Table 4, we found that the odds ratios (ORs) for individuals 66 years and older of having access to PCMH were 0.8 (confidence interval [CI]: 0.67–0.95). Compared with married individuals, those who were separated had significantly lower odds of having access to PCMH (OR = 0.78; CI: 0.67–0.91). Compared with individuals who completed fewer than 12 years of education, those who had more than 12 years of education had significantly higher odds of having a PCMH (OR = 1.25; CI:1.05–1.48).
Table 4

Adjusted odds ratios of having access to PCMH care among adults with chronic conditions, 2010–2015a

Independent Variable

Has a PCMH

OR b

95% CI

P

 

No

Yes

   

Predisposing

N

N

   

Age (Years)

    

19 to 40

4299

1124

1.00

   

41 to 65

8213

2014

0.93

0.82

1.06

0.3

66 and older

3931

822

0.80

0.67

0.95

0.01

Sex

 Female

9926

2270

1.00

   

 Male

6517

1690

1.08

0.99

1.18

0.05

Race

 Non-white

5485

1349

1.00

   

 White

10,958

2611

1.003

0.88

1.13

0.9

Marital Status

 Married

8508

2302

1.00

   

 Never Married

3465

807

0.87

0.75

1.01

0.06

 Separated

4470

851

0.78

0.67

0.91

0.001

Education Years

  < 12 Years

2980

525

1.00

   

 12 Years

3833

931

1.17

0.99

1.37

0.05

  > 12 Years

6956

1920

1.25

1.05

1.48

0.01

Enabling

Health Insurance

 Any Private

9708

2714

1.00

   

 Public Only

5319

982

0.71

0.63

0.81

<.0001

 Uninsured

1416

264

0.73

0.59

0.91

0.005

Employment Status

 Employed

8656

2350

1.00

   

 Not employed

7734

1602

0.83

0.74

0.93

0.001

Family Income Categorical

 High

5001

1514

1.00

   

 Middle

4747

1166

0.89

0.77

1.03

0.1

 Poor/ Low

6695

1280

0.67

0.57

0.78

<.0001

Census Region

 Midwest

3175

898

1.00

   

 Northeast

2538

817

1.11

0.89

1.39

0.3

 South

6583

1289

0.64

0.52

0.78

<.0001

 West

4147

956

0.76

0.61

0.96

0.02

Healthcare Need

Self-Reported Health

 Excellent/Good

1,1957

3187

1.00

   

 Fair/Poor

4157

715

0.65

0.56

0.76

<.0001

Chronic Conditions (Yes vs No)

 Hypertension

8350

1857

0.90

0.80

1.01

0.09

 Hyperlipidemia

6359

1373

0.88

0.79

0.98

0.02

 Mood Disorders

3259

643

0.79

0.69

0.90

0.0006

 Diabetes Mellitus

3673

801

0.95

0.83

1.07

0.4

 Anxiety Disorders

2976

613

0.81

0.707

0.93

0.002

 Upper Respiratory Conditions

5888

1517

1.14

1.01

1.28

0.02

 Arthritis

7682

1568

0.78

0.70

0.87

<.0001

 Asthma

2071

486

0.93

0.80

1.06

0.3

 Coronary Artery Disease

1787

410

0.96

0.82

1.11

0.5

Abbreviations: PCMH indicates Patient-Centered Medical Home; CI, confidence interval

aSample size (N) is unweighted; Percentage weighted using weights provided with 2010–2015 MEPS

bAdjusted Odds Ratio

The result shows that the most important driver of having a PCMH was health insurance status. Compared with individuals covered by private insurance, those with public insurance were 71% as likely to have access to PCMH, while the uninsured were 73% as likely to have access to PCMH. There was also a significant difference in the employment status. Unemployed individuals were less likely to have access to PCMH compared to employed individuals (OR = 0.83; CI: 0.74–0.93).

Significant differences in the family income were observed in relation to having PCMH access. Individuals who were living in a poor or low-income family were about 33% less likely to have a PCMH compared to those living with a family with a high income (OR = 0.67; CI: 0.57–0.78). Individuals living in the South and West were the most likely to not have access to PCMH compared to individuals living in the Midwest (South: OR = 0.64; CI: 0.52–0.78; West: OR = 0.76; CI: 0.61–0.96). The analyses also showed that individuals who reported having fair or poor health were negatively associated with having a PCMH compared to those who reported excellent or good general health (OR = 0.65; CI: 0.57–0.76). In this population, individuals with the chronic conditions hyperlipidemia, mood disorders, anxiety disorders, and arthritis were significantly associated with limited access to PCMH. However, individuals diagnosed with upper respiratory conditions were positively associated with having access to a PCMH. The c-statistics associated with these adjusted logistic models ranged between 0.71 and 0.86.

Discussion

As the first national study to present the extent of access to PCMH among adults with chronic conditions and to identify potential drivers for its trends, this study attempts to address this gap in the literature. In this research, we examined the prevalence of adult patients with chronic conditions who accessed PCMH care over the six-year period in the U.S.

This study found only a small percentage of patients with chronic conditions had access to PCMH care with a decreasing trend during the study period. This may raise concerns as this vulnerable population typically requires comprehensive and continuous care by primary care providers to manage their chronic physical problems, especially when the number and complexity of care needs increase as the number of chronic conditions a patient has increases [33]. In terms of medical services, the average numbers of ambulatory and emergency department visits, inpatient stays, and number of prescribed medications were much higher among individuals who suffered from two or more chronic conditions compared to those with no chronic condition [34].

To better understand the characteristics and drivers of that observed trend in this population, we analyzed many factors and found several factors were associated with access to PCMH. A change in one of these factors can cause a change in the PCMH trend. The older adults (66 and older) were less likely than comparable younger adults [19 to 40] to have access to PCMH care. This finding is consistent with what has been reported by prior studies that older patients were less likely to have PCMH access [35]. This can be explained by the dynamic health status of such individuals who often use more than one healthcare provider with no one provider responsible for all care. Older patients with chronic conditions are usually heterogeneous in terms of number and severity of chronic conditions, health status, and risk of adverse events [36]. Thus, policy leaders should promote access to PCMH care among older patients with chronic conditions because it may help coordinate their complex medical needs, which would improve quality and health outcomes. This was confirmed in a prospective before-and-after study among seniors receiving a PCMH. That study reported that seniors who experienced PCMH care made fewer and less costly emergency department visits and had fewer hospitalizations [37].

Our findings also revealed that marital status is an important factor associated with access to PCMH. Being separated had the effect of decreasing the likelihood of having access to PCMH versus being married. Similar to previously published studies, this study showed that the separated patients were less likely to receive PCMH care, although the number was not significant [38]. Our findings showed a positive association between a higher level of education and having access to PCMH care. A possible explanation of this finding is that better-educated individuals typically have a higher impact on changing their economic barriers to have full access to PCMH care [39].

All enabling factors were significantly associated with the probability of having PCMH access. Individuals with private insurance, employed, and living in a high-income family were found to report better access to PCMH. These findings are consistent with the literature in that access to PCMH is limited due to financial barriers [40]. Therefore, policy makers and health care providers should pay special attention to these barriers as they may negatively affect health-related outcomes, and the effect is substantial, especially among individuals with chronic diseases. Our findings suggest that expanding health insurance coverage is not an adequate approach to increase access to such care, but policy makers should also improve the provided public health insurance coverage for this population to have better access to PCMH care [41].

Clearly, census region is also important. Individuals who resided in the South or the West were less likely to have access to PCMH. This is not surprising because of the considerable difference in socioeconomic status of the majority of people who live in the South or the West compared to those in other regions. For example, a higher proportion of the population in the South and the West are racially Hispanic and Black [42]. There is evidence in many studies that these groups tend to not seek care for their chronic conditions [4346]. Furthermore, compared to those in other regions, people in the South or the West are more likely to be uninsured, hence, less likely to have access to PCMH [47].

By looking closely at the chronic conditions, we identified a lack of uniform access to PCMH care across chronic conditions. We found that hyperlipidemia, mood disorders, anxiety disorders, and arthritis were significantly associated with limited access to PCMH, yet patients with upper respiratory conditions had better access to the care. A possible explanation is that upper respiratory conditions are minor and very common [48, 49]; thus, patients often seek the primary care provider’s help instead of the emergency department’s help, which results in a lower cost in managing their conditions.

Despite the uniqueness of the information provided by MEPS on individuals’ socioeconomics, access to care, and others in the U.S., there are limitations to the interpretation of the results of this study. First, as noted above, MEPS data provide information on the civilian, noninstitutionalized population, and hence exclude individuals living in institutions, such as individuals in nursing homes and long-term care hospitals who live with broad arrays of chronic conditions. Second, the definition of PCMH used in this study was based on patient responses, which might be subject to recall bias; thus, our estimates may underrepresent actual PCMH use. Despite the limitations, this study provides an important overview of the access to PCMH in a nationally representative general population sample of the U.S.

More effort is needed to facilitate access to PCMH among those with chronic conditions. In the PCMH care model, the primary care health professionals provide labor-intensive work behind the scenes, and it should be compensated accordingly because the total PCMH care fees ultimately demanded by physicians exceed the avoided expense for chronic conditions. This will increase access to PCMH, improve the quality of care, and reduce the overall cost associated with chronic conditions considerably [50, 51].

Conclusion

Despite general agreement about the importance of PCMH, our findings showed strong deficiencies in access to PCMH between 2010 and 2015 to be potentially driven by many factors. These findings serve as a sign for more general problems with access to appropriate care. Moreover, reduced access to comprehensive and continuous services such as PCMH care may exacerbate chronic conditions, leading to more emergency department visits and hospitalizations that might have been preventable, as was reported in the literature. Thus, more resources and efforts need to be devoted to reduce barriers to PCMH care across the U.S., which may improve the overall health of Americans with chronic conditions.

Declarations

Acknowledgments

The authors would like to thank the Saudi Association for Scientific Research (SASR) for providing logistical support throughout the duration of the project.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the AHRQ RDC, [https://meps.ahrq.gov/mepsweb/data_stats/onsite_datacenter.jsp].

Authors’ contributions

ZA carried out the literature review, statistical analyses, manuscript drafting, manuscript editing, and manuscript revision. NK and IA carried out the study design, statistical analyses, and manuscript revision. RA and AM participated in data collection, statistical analyses, and manuscript editing. NA and TA participated in manuscript editing and manuscript revision. EA and SA participated in study design and data collection, manuscript editing, manuscript revision, and coordination. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Riyadh, Saudi Arabia
(2)
Department of Clinical Pharmacy, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia
(3)
College of Pharmacy, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
(4)
Department of Pharmaceutical Science, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia
(5)
Department of Clinical Pharmacy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
(6)
Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Riyadh, Saudi Arabia
(7)
College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Riyadh, Saudi Arabia

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© The Author(s). 2018

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