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Section 13. Appendix G: Diabetes and asthma consumer surveys
Final Report
13.APPENDIX G: DIABETES AND ASTHMA
CONSUMER SURVEYS
Diabetes and asthma were selected as a focus to examine the effects of QCPP on
consumer health because a number of specific pharmacy-conducted activities have
been shown to improve outcomes for people with these conditions. Activities such as
patient counselling, patient education and information provision, medication review,
demonstration of the use of devices and working with other health professionals can
improve patient care for people with diabetes or asthma, and are all the subject of
QCPP standards.
13.1 DIABETES CONSUMER QUESTIONNAIRE
People with diabetes require specific services from community pharmacies. A survey
was developed to assess the characteristics of people with diabetes and their
experiences at their community pharmacy. Questions focused on information about
the person’s diabetes in general and upon the specific diabetes related services they
received from their pharmacy. The directive guidance items were modified to include
specific diabetes-related pharmacy activities and aspects covered by the SERVPERF
scale were modified to ask about consumer satisfaction focusing on diabetes related
services. The sampled pharmacies were asked to obtain patient consent and to
distribute the questionnaire to their consumers with diabetes.
13.1.1 RESPONSE TO SURVEY AND RESPONDENT CHARACTERISTICS
Consumer surveys were completed by 246 respondents with the following
characteristics:
58 had Type I Diabetes, one participant responded on behalf of their child with
Type I Diabetes and 180 participants had Type II Diabetes.
The majority of respondents to this survey (31%) were aged 65-74, with only 8.6%
of respondents under 44 and only 2.4% over 84 years of age.
Of the respondents, there were 135 males and 106 females (five participants failed
to record their gender).
In total, the 246 respondents visited 60 pharmacies (Mean = 4.1 responses per
pharmacy), with 227 respondents citing the pharmacy in question as their main
pharmacy. Since the questionnaire was distributed by the pharmacy staff, it is not
unexpected that the majority of respondents were regular consumers. It might be
argued that regular consumers would be more likely to have received diabetes-specific
pharmacy services than non-regular consumers (as indicated by directive guidance
score in the main consumer survey).
The characteristics of the pharmacies visited by participants, showed that 29 were
QCPP accredited (135 respondents) and 31 were not (111 respondents). When
analysed by business size, 22 pharmacies were classified as small, 28 as medium and
10 were classified as large. It was also noted that 50 pharmacies were in PhARIA
category one, seven in categories two to three and three pharmacies in PhARIA
categories four to six. The distribution of responses across the latter two pharmacy
characteristics was similar to the national pattern.
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13.1.2 PREPARATION OF SURVEY MEASURES
13.1.2.1 Diabetes directive guidance
The diabetes survey asked about participants’ experiences with their community
pharmacy in relation to the treatment and management of their diabetes. Data was
cleaned so that instances where participants answered ‘not applicable’ to any
questions were treated as missing for the purposes of analysis.
Responses to the diabetes modified directive guidance scale were analysed to
determine the frequency with which pharmacies provided specific diabetes related care
activities. These responses were aggregated using multidimensional scaling with the
two-dimensional Euclidian distance model. A solution was reached in 6 iterations and
two unique dimensions were identified. An examinations of the activities involved in
each dimension suggested that they related to the following two types of diabetes
directive guidance (Table 13.1 contains the full questions comprising each dimension):
1. Pharmacy care and advanced directive guidance: This dimension focused on care
outside of that which is normally offered by pharmacies and included pharmacists
providing substantial information regarding patients’ disease state (in this case
diabetes), as well as lifestyle and goal setting advice; and
2. Traditional pharmacy care and monitoring: This dimension related to traditional
pharmacy care and monitoring of patients’ disease condition.
Table 13.1
Components of directive guidance dimensions
Dimension 1 – Advanced pharmacy care and directive
guidance
Discussed the difference between Type I and
Type II diabetes
Discussed possible side effects or drug
interactions of diabetes medicines
Explained why it is important to take diabetes
medicines as directed by the doctor
Discussed lifestyle or other approaches to
reduce complications of diabetes e.g. stop
smoking, weight loss, exercise, lowering
cholesterol
Emphasised the need to monitor blood glucose
Checked whether or not you have an action
plan to deal with a low blood glucose situation
Given you any written information about how to
manage your diabetes
Assisted you in setting a goal related to taking
diabetes medicines correctly?
Checked back with you about how you (or your
child) were going with the medicines
Suggested you visit the doctor about your (or
your child’s) diabetes
Checked whether you had received diabetes
information, education or training from another
health professional
Given you feedback on how you were doing
managing diabetes
Dimension 2 - Traditional pharmacy care
and monitoring
Explained how to use a blood
glucose monitor correctly
Discussed how to prepare insulin
doses or to use insulin injection
devices
Advised on the storage of insulin
Given you written information about
diabetes medicines
Explained to you what happens in the
body as a result of diabetes
Explained the importance of foot care
Emphasised the necessity for yearly
eye checks
Checked back with you about your
(or your child’s) recent blood glucose
readings
The number of times a consumer indicated that they had experienced a particular
activity in each dimension was calculated as the dimension score. The distributions of
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the dimension scores were positively skewed (Figure 13.1) showing a substantial floor
effect in both dimensions 1 and 2, with 31.5% and 36.7% of participants respectively,
reporting a score of zero on a dimension (none of the directive guidance items were
experienced). The median score for dimension 1 was 1 and the dimension 2 median
was 1. Thus pharmacy consumers with diabetes generally reported a low level of
receipt of disease management value-added services, even though the majority of
respondents were regular consumers of the pharmacies sampled.
50
30
40
20
30
Frequency
20
Frequency
10
10
Std. Dev = 3.84
Mean = 3.8
N = 124.00
0
0
2
4
6
8
10
12
0
0
1
2
3
4
5
6
7
8
Dimension 2 Traditional
pharmacy care and monitoring
Dimension 1 Advanced pharmacy
care and directive guidance
Figure 13.1
Std. Dev = 2.67
Mean = 2.3
N = 60.00
Distributions of diabetes directive guidance dimensions
After square root transformation of the dimension scores, the distribution more closely
approximated the normal distribution although there was still a floor effect.
50
30
40
20
30
10
Std. Dev = 1.21
Mean = 1.51
N = 124
0
0
0.5 1
1.5 2
2.5 3
Frequency
Frequency
20
10
3.5
0
Square root transformed Dimension 1 Advanced pharmacy care and directive
guidance
Figure 13.2
Std. Dev = 1.02
Mean = 1.12
N = 60
0
0.5 1
1.5 2
2.5 3
Square root transformed Dimension 2 Traditional pharmacy care and
monitoring
Distributions of transformed diabetes directive guidance dimensions
13.1.2.2 Diabetes modified SERVPERF
Factor analysis of the diabetes modified SERVPERF questions extracted a single
factor using all 12 items. Cronbach’s alpha reliability analysis showed a high level of
internal consistency (α = 0.96), with no item deletions able to improve that level. These
findings suggest that the diabetes modified SERVPERF scale is reliability assessing
the intended frame of reference. Since reliability was high, the scores on each item
were summed. Again, this functional quality score was skewed with consumers
reporting high levels of satisfaction with diabetes related services (Figure 13.3). The
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median score was 76 out of a maximum of 84; 27% of respondents had this top score.
Using a logit transformation, the modified SERVPERF scale was transformed so that it
approximated a normal distribution.
70
60
60
50
50
40
40
30
20
20
Std. Dev = 14.64
Mean = 70.9
N = 207
10
0
20 30 40 50 60 70 80
25 35 45 55 65 75 85
Figure 13.3
Frequency
Frequency
30
Std. Dev = 1.60
Mean = -2.34
0
N = 207
-4.5 -3.5 -2.5 -1.5 -0.5 0.5 1.5
-4 -3 -2 -1 0 1
10
Distributions of diabetes modified SERVPERF score and logit transformed
score
13.1.3 IMPACT OF ACCREDITATION STATUS ON DIABETES DIRECTIVE GUIDANCE
Diabetes directive guidance scores were not significantly different between accredited
and non-accredited pharmacies, nor by adopter group (early, mid, late and last
adopters) (Table 13.2).
Table 13.2
Accreditation status comparisons of dimensions 1 and 2
Test Variable
QCPP
accreditation
status
QCPP
adopter
group
Dimension 1 Findings
Med
IQR
P*
Accredited
2.00
0.00-7.00
Not Accredited
3.00
0.25-6.00
Early
Mid
Late
Last
3.00
0.00
1.50
4.00
0.00-7.00
0.00-7.00
0.00-6.00
1.00-7.00
p=
0.776
p=
0.258
Dimension 2 Findings
Med
IQR
P*
1.00
0.00-4.00
1.00
0.00-4.00
1.00
0.00
1.00
2.00
0.00-4.00
0.00-4.00
0.00-3.50
0.75-5.25
p=
0.430
p=
0.553
Med. = Median IQR = Inter-quartile Range; *untransformed value tested
13.1.3.1 Identifying potential covariates
Analysis of the transformed variables was undertaken to determine whether scores on
Dimensions 1 and 2 varied based on participant or pharmacy variables. Using
independent t-tests, non-significant results were recorded for analyses based on
participant age, gender, health status and length of time the participant had been
visiting the pharmacy. The findings of each analysis can be seen in Table 13.3. Both
dimensions differed significantly across business size categories. Tukey’s HSD
method post hoc testing, showed that for Dimension 1, ‘small’ pharmacies recorded a
higher mean directive guidance score than ‘medium’ and large pharmacies. For
Dimension 2, ‘small’ pharmacies recorded a higher mean directive guidance score than
‘medium’ pharmacies, but were not significantly different to ‘large’ pharmacies. This
finding is consistent with the pattern from the general consumer survey.
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Table 13.3
Final Report
Results of Dimension 1 and 2 covariate analyses
Test Variable
Dimension 1 Findings
Med
IQR
p
Participant age
Participant gender
Participant health status
Length of time visiting pharmacy
Diabetes Type
Business size
Small
Medium
Large
2.12
1.57
0
2.96
2.6
1.4
p = 0.63
p = 0.08
p = 0.31
p = 0.12
p = 0.69
p = 0.003
Dimension 2 Findings
Med
IQR
p
1.41
1
1
2.2
2
1.57
p = 0.83
p = 0.23
p = 0.93
p = 0.42
p = 0.17
p = 0.02
Med. = Median IQR = Inter-quartile Range
Participant age, gender, length of time visiting the pharmacy, health status and
diabetes type did not differ by accreditation status.
13.1.3.2 Impact of accreditation status adjusting for covariates
Since business size also differed across accredited and non-accredited pharmacies in
the census, this was included in a multivariate analysis (using SPSS General Linear
Model procedure) where each transformed dimension score was the dependent
variable.
For advanced pharmacy care (dimension 1), after adjusting for business size, there
was no significant difference between consumers of accredited and non-accredited
pharmacies (p=0.823). Nor was there a significant difference for dimension 2
(p=0.870). Similarly, no difference was seen across adopter groups (dimension 1
p=0.201, dimension 2 p=0.681).
13.1.4 IMPACT OF ACCREDITATION STATUS ON DIABETES FUNCTIONAL QUALITY
Diabetes functional quality scores were not significantly different between accredited
and non-accredited pharmacies, nor by adopter group (early, mid, late and last
adopters) (Table 13.4).
Table 13.4
Accreditation status comparisons of functional quality
Test Variable
QCPP accreditation
status
QCPP adopter group
Diabetes SERVPERF Score
Med
IQR
p
Accredited
Not Accredited
Early
Mid
Late
Last
75
78.5
76
74
75
80
60-83
63.25-84
62-82
53.25-84
55-83.5
71-84
p = 0.216 MW
p = 0.122 KW
Med. = Median IQR = Inter-quartile Range MW=Mann Whitney U test KW= Kruskal Wallis test
13.1.4.1 Identifying potential covariates
Analysis was then conducted on the transformed SERVPERF variable using a variety
of participant and pharmacy measures. No significant differences were found for any
of the participant variables. These included age, gender, health status and the length
of time the participant had been visiting the pharmacy. Non-significant results were
also recorded for business size (small, medium and large) (Table 13.5).
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Table 13.5
Final Report
Results of Dimension 1 and 2 covariate analyses
Test Variable
Transformed Diabetes SERVPERF
Med
IQR
p
p = 0.13
p = 0.75
p = 0.09
p = 0.09
p = 0.85
-2.41
3.12
p = 0.17
-2.26
3.41
-1.42
3.26
Participant age
Participant gender
Participant health status
Length of time visiting pharmacy
Diabetes Type
Business Size
Small
Medium
Large
Med. = Median IQR = Inter-quartile Range
Since there were no significant covariates for the diabetes SERVPERF score, no
adjustment for covariates was necessary to further examine effects of accreditation
status.
13.1.5 CONCLUSION
Overall, these findings suggest that QCPP accreditation status does not affect either
the technical or functional diabetes related service performance of pharmacies.
Additionally, as evidenced by the significant ceiling effect in the untransformed diabetes
modified SERVPERF variable (Figure 13.3), consumers perceive that pharmacies are
performing commendably in their diabetes related service performance. This high level
of satisfaction was expressed in the face of low technical quality Despite the finding
that between 31.5% and 36.2% of participants received no directive guidance from
their pharmacy, no participants recorded a SERVPERF score of 12 (the minimum
possible score). Clearly this indicates that participants ratings of service performance
does not match the actual technical quality of the service provided to them (a finding
previously noted for pharmacy services generally). Brown and Green (Brown et al.
2002) have previously noted that patients with diabetes had a low expectation for
pharmaceutical care activities in a community pharmacy setting. Low service
expectations are certainly being met and so may well account for the high satisfaction
levels.
A number of diabetes-specific services have shown are associated with improved
outcomes in studies (Baran et al. 1999; Fincham & Lofholm 1998;Berringer et al.
1999;Nau & Ponte 2002). Since these services were performed at low level by both
accredited and non-accredited pharmacies (as captured by the diabetes directive
guidance scores), it is unlikely that any health outcome difference will be related to
QCPP accreditation at this stage.
13.2 ASTHMA CONSUMER QUESTIONNAIRE
People with asthma require specific services from community pharmacies. A survey
was developed to assess the experiences of asthma sufferers with their community
pharmacy. The survey focused on questions about participants’ asthma in general, its
affects on their lifestyle and the asthma related services they receive from their
pharmacy. The directive guidance items were modified to include specific asthmarelated pharmacy activities and aspects covered by the SERVPERF scale were
modified to ask about consumer satisfaction focusing on asthma related services. The
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sampled pharmacies were asked to obtain patient consent and to distribute the
questionnaire to their consumers with asthma.
13.2.1 RESPONSE TO SURVEY AND RESPONDENT CHARACTERISTICS
Consumer surveys were completed by 101 respondents with the following
characteristics:
83 of these had asthma, 11 responded on behalf of a child with asthma and five
responded that both they and their child had asthma.
Of the respondents, 53 were female and 45 were male.
The majority of participants (52.5%) were aged between 5 and 54 years, with
47.5% of participants aged over 55 years.
In total the 101 respondents visited 41 pharmacies. The characteristics of the
pharmacies visited by participants showed that 22 were QCPP accredited (58
respondents) and 19 were not (43 respondents). When analysed by business size, 12
pharmacies were classified as small, 25 as medium and four as large. It was also
noted that 33 pharmacies were in PhARIA category one, two pharmacies in categories
two to three and six pharmacies in categories four to six. Small businesses were
under-represented and PhARIA categories 4 to 6 were over-represented in the sample
of pharmacies about whom responses were received compared to the national pattern.
13.2.2 PREPARATION OF SURVEY MEASURES
13.2.2.1 Asthma directive guidance
The asthma survey asked about participants’ experiences with their community
pharmacy in relation to the treatment and management of their diabetes. Data was
cleaned so that instances were participants answered ‘not applicable’ to any questions
were treated as missing for the purposes of analysis.
Participants’ responses to the asthma modified directive guidance scale were analysed
to determine the frequency with which pharmacies provided specific asthma related
care activities. These responses were aggregated using multidimensional scaling with
the two-dimensional Euclidian distance model. A solution was reached in 5 iterations
and two unique dimensions were identified. An examinations of the activities involved
in each dimension suggested that they related to the following two types of asthma
directive guidance (Table 1.1 contains a full list of questions comprising each
dimension):
1. Traditional pharmacy care and monitoring: This dimension related to traditional
pharmacy care, such as provision of medication information and the monitoring of
patients’ condition(s).
2. Pharmacy care and advanced directive guidance: This dimension focused on care
provided by the pharmacy in the form on information about the patients’ disease
and information regarding the management of the disease; and
The number of times a consumer indicated that they had experienced a particular
activity in each dimension was calculated as the dimension score. The distributions of
the dimension scores were skewed (Figure 13.4) but were approximately normal.
There was a floor effect in both dimensions 1 and 2, with 35.1% and 33.8% of
participants respectively, reporting a score of zero on a dimension (none of the
directive guidance items were experienced). The median score for dimension 1 was 1
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and the dimension 2 median was 1. Thus pharmacy consumers with asthma generally
reported a low level of receipt of disease management value-added services, even
though the majority of respondents were regular consumers of the pharmacies
sampled.
Table 13.6
Components of asthma directive guidance dimensions
Dimension 1 – Traditional pharmacy care and
monitoring
Dimension 2 - Advanced pharmacy care and
directive guidance
Given you written information about asthma
medicines
Discussed situations or medicines that
might trigger asthma and how to avoid
them
Given you any written information about
how to manage asthma
Assisted you in setting a goal related to
taking asthma medicines correctly
Given advice about using a spacer with
inhalers
Discussed the use a peak flow meter to
monitor asthma symptoms
Talked about overuse of reliever medicines
Checked back with you about use of
preventer medicines
Checked whether you had received asthma
information, education or training from
another health professional e.g. a GP, a
specialist, a nurse or a physiotherapist
30
30
20
20
10
10
0
0
1
2
3
4
5
6
7
8
Std. Dev = 2.77
Mean = 2.7
N = 74
Std. Dev = 3.45
Frequency
Frequency
Explained how to use the inhalers
correctly
Explained the difference between
preventer and reliever asthma
medicines
Discussed the possible side effects of
asthma medicines
Explained to you what happens in the
lungs in asthma
Emphasised the need to use preventer
medicines even when asthma
symptoms are under control
Checked whether or not you have an
asthma action plan
Checked that inhalers were being used
correctly
Suggested you visit the doctor about
your (or your child’s) asthma
Given you feedback on how you were
doing managing asthma
0
Dimension 1
Figure 13.4
Mean = 3.5
N = 74
0
2
4
6
8
10
Dimension 2
Distributions of directive guidance Dimensions 1 and 2
13.2.2.2 Asthma modified SERVPERF
Factor analysis of the asthma modified SERVPERF questions extracted a single factor
using all 11 items. Cronbach’s alpha reliability analysis showed a high level of internal
consistency (α = 0.98), with no item deletions able to improve that level. These
findings suggest that the asthma modified SERVPERF scale is reliability assessing the
intended frame of reference. Since reliability was high, the scores on each item were
summed. Again, this functional quality score was skewed with consumers reporting
high levels of satisfaction with asthma related services (Figure 13.5). The median score
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was 71 out of a maximum of 77; 38.2% of respondents had this top score. It was not
possible to transform this skew so that it approximated a normal distribution, for this
reason non-parametric tests were used when analysing SERVPERF scores.
50
40
30
Frequency
20
10
Std. Dev = 16.78
Mean = 63.7
N = 89
0
15
Figure 13.5
20
25
30
35
40
45
50
55
60
65
70
75
Distribution of the summed asthma modified SERVPERF score
13.2.2.3 Mini asthma quality of life questionnaire score
A score on the mini asthma quality of life instrument (Juniper et al. 1999) was
calculated as the mean of participants’ responses to the frequency with which they had
experienced asthma related symptoms in the past two weeks. Scores for each of 11
symptoms were recorded on a seven point Likert type scale, with a score of one
indicating that the patient experienced asthma symptoms ‘all of the time’ and a score of
seven indicating that the patient had asthma symptoms ‘none of the time’. It was found
that the overall health score variable was normally distributed (Figure 13.6).
20
Frequency
10
Std. Dev = 1.36
Mean = 4.33
N = 100
0
1.5
Figure 13.6
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
Distribution of participant overall health score
13.2.3 IMPACT OF ACCREDITATION STATUS ON ASTHMA DIRECTIVE GUIDANCE SCORES
Asthma directive guidance scores were not significantly different between accredited
and non-accredited pharmacies, nor by adopter group (early, mid, late and last
adopters) (Table 13.7).
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Table 13.7
Final Report
Accreditation status comparisons of dimensions 1 and 2
Test Variable
QCPP
accreditation
status
QCPP
adopter
group
Accredited
Dimension 1 Findings
Med
IQR
p
p
=
0.63
2.00 0.00-6.00
Not Accredited
4.00
0.00-7.00
Early
Mid
Late
Last
2.00
5.00
3.00
4.00
0.00-6.00
1.00-9.50
0.00-5.75
1.00-9.00
p = 0.21
Dimension 2 Findings
Med
IQR
p
p
=
0.55
2.00 0.00-4.75
1.50
0.00-5.25
1.00
4.00
2.00
1.00
0.00-4.50
0.00-5.00
0.00-5.50
0.00-6.00
p = 0.66
13.2.3.1 Identifying potential covariates
Analysis of the transformed variables was undertaken to determine whether scores on
Dimensions 1 and 2 varied based on participant or pharmacy variables. Using
independent t-tests, non-significant results were recorded for analyses based on
participant age, gender, health status and length of time the participant had been
visiting the pharmacy. The findings of each analysis can be seen in Table 13.8. Both
dimensions differed significantly across business size categories. Tukey’s HSD
method post hoc testing showed that for Dimension 1, ‘small’ pharmacies recorded a
higher mean directive guidance score than ‘medium’ and large pharmacies. For
Dimension 2, ‘small’ pharmacies recorded a higher mean directive guidance score than
‘medium’ pharmacies and ‘large’ pharmacies. This finding is consistent with the pattern
from the general consumer survey.
Table 13.8
Results of Dimension 1 and 2 covariate analyses
Test Variable
Participant age
Participant gender
Participant health status
Length of time visiting pharmacy
QCPP
Accredited
accreditation
Not Accredited
status
QCPP adopter
Early
group
Mid
Late
Last
Business Size
Small
Medium
Large
Dimension 1 Findings
Med
IQR
p
p = 0.63
p = 0.3
p = 0.18
p = 0.27
2
6
p = 0.63
Dimension 2 Findings
Med
IQR
p
p = 0.83
p = 0.39
p = 0.18
p = 0.81
2
4.75
p = 0.55
3
7.5
1
5
2
5
2
4
5
1
0
6
8
6
8
4
6
1.5
1
4
1
1
4
1
-
4.5
5
5
6
4
4
-
p = 0.21
p = 0.02
p = 0.66
p = 0.02
Med. = Median IQR = Inter-quartile Range
13.2.3.2 Impact of accreditation status adjusting for covariates
Since business size also differed across accredited and non-accredited pharmacies in
the census, this was included in a multivariate analysis (using SPSS General Linear
Model procedure) where each transformed dimension score was the dependent
variable. Since participant overall health score and gender tended to different with
accreditation status, these variables were also included in the model.
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For traditional pharmacy care (dimension 1), after adjusting for covariates, there was
no significant difference between consumers of accredited and non-accredited
pharmacies (p=0.396). Nor was there a significant difference for dimension 2
(p=0.459). Similarly, no difference was seen across adopter groups (dimension 1
p=0.0.097, dimension 2 p=0.593).
13.2.4 IMPACT OF ACCREDITATION STATUS ON ASTHMA FUNCTIONAL QUALITY
Diabetes functional quality scores were not significantly different between accredited
and non-accredited pharmacies, nor by adopter group (early, mid, late and last
adopters) (Table 13.4).
Table 13.9
Accreditation status comparisons of functional quality
Test Variable
Accredited
SERVPERF Findings
IQR
p
p
=
0.34
71.50 58.25-77.00
Not Accredited
69.00
48.00-77.00
Early
Mid
Late
Last
70.00
77.00
69.00
64.50
55.50-77.00
62.00-77.00
50.00-77.00
47.25-77.00
Med
QCPP accreditation status
QCPP adopter group
p = 0.44
13.2.4.1 Identifying potential covariates
Analysis was then conducted on the SERVPERF variable using Spearmen’s
correlations and the Mann-Whitney and Kruskal-Wallis tests on a variety of participant
and pharmacy measures. No significant differences were found for the participant
variables age, gender and health status (Table 13.10). The length of time the
participant had been visiting the pharmacy and pharmacy business size did influence
asthma SERVPERF scores. Participants who had been visiting their pharmacy for two
or more years recorded significantly higher SERVPERF scores that participants who
had been visiting their pharmacy for less than two years. Pharmacies categorized as
‘small’ and ‘medium’ were scored significantly higher on the asthma modified
SERVPERF scale than ‘large’ pharmacies.
Table 13.10
Results of asthma SERVPERF covariate analyses
Test Variable
Med
Participant age
Participant gender
Participant health status
Length of time visiting
pharmacy
Business Size
Less than 2 years
2 or more years
Small
Medium
Large
63.5
73
76
69
45
SERVPERF Findings
IQR
p
p = 0.38
p = 0.87
p = 0.95
29
p = .02
19
12.75
p = 0.001
27.25
26
Med. = Median IQR = Inter-quartile Range
Consortium: ACPPM, QMC, UQTRU
463
February 2005
An evaluation of the Quality Care Pharmacy Program
Section 13. Appendix G: Diabetes and asthma consumer surveys
Final Report
13.2.4.2 Impact of accreditation status adjusting for covariates
Logistic regression with accreditation status as a dependent variable was used to
adjust for the effects of covariates health status, length of time visiting the pharmacy,
business size and gender on the asthma modified SERVPERF score. In this model,
the functional quality score did not differ significantly between consumers of accredited
and non-accredited pharmacies (p=0.338). The same covariates were used in a
multinominal logistic regression of adopter status. In this model, the functional quality
score did not differ significantly between consumers of early, mid, late or last adopters
of QCPP (p=0.414).
13.2.5 CONCLUSION
Overall, these findings suggest that QCPP accreditation status does not affect either
the technical or functional asthma related service performance of pharmacies.
Additionally, as evidenced by the significant ceiling effect in the untransformed asthma
modified SERVPERF variable (Figure 13.5), consumers perceive that pharmacies are
performing commendably in their asthma related service performance. This high level
of satisfaction was expressed in the face of low technical quality.
Despite the finding that between 35.1% and 33.8% of participants received no directive
guidance from their pharmacy, no participants recorded a SERVPERF score of 11 (the
minimum possible score). Clearly this indicates that participants ratings of service
performance does not match the actual technical quality of the service provided to
them (a finding previously noted for pharmacy services generally). Others have also
noted a that low asthma service provision did not mean low satisfaction with the
pharmacy service (Liu et al. 1999;Kradjan et al. 1999).
Since the asthma services that studies have been shown to be associated with
improved outcomes (Herborg et al. 2001a; Herborg et al. 2001b; Naerhi et al. 2002;
Schulz et al. 2001) were performed at an equally low level by accredited and nonaccredited pharmacies (as captured by the asthma directive guidance scores), it is
unlikely that any health outcome difference will be related to QCPP accreditation at this
stage.
Consortium: ACPPM, QMC, UQTRU
464
February 2005