Quality of social and emotional wellbeing services for families of young Indigenous children attending primary care centers; a cross sectional analysis
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R E S E A R C H A R T I C L E Open Access
Quality of social and emotional wellbeing
services for families of young Indigenous
children attending primary care centers; a
cross sectional analysis
Karen M. Edmond 1*
, Kimberley McAuley 1
, Daniel McAullay 1,2 , Veronica Matthews 3
, Natalie Strobel 1
,
Rhonda Marriott4 and Ross Bailie 3
Abstract
Background: The quality of social and emotional wellbeing services for Indigenous families of young children is
not known, in many settings especially services provided by primary care centers.
Methods: Our primary objective was to assess delivery of social and emotional wellbeing services to the families of
young (3–11 months) and older (12–59 months) Indigenous children attending primary care centers. Our secondary
objective was to assess if delivery differed by geographic location. Two thousand four hundred sixty-six client files
from 109 primary care centers across Australia from 2012 to 2014 were analysed using logistic regression and
generalised estimating equations.
Results: The proportion of families receiving social and emotional wellbeing services ranged from 10.6% (102)
(food security) to 74.7% (1216) (assessment of parent child interaction). Seventy one percent (71%, 126) of families
received follow up care. Families of children aged 3–11 months (39.5%, 225) were more likely to receive social and
emotional wellbeing services (advice about domestic environment, social support, housing condition, child stimulation)
than families of children aged 12–59 months (30.0%, 487) (adjusted odds ratio [aOR] 1.68 95% CI 1.33 to 2.13). Remote
area families (32.6%, 622) received similar services to rural (29.4%, 68) and urban families (44.0%, 22) (aOR 0.64 95% CI 0.
29, 1.44).
Conclusions: The families of young Indigenous children appear to receive priority for social and emotional wellbeing
care in Australian primary care centers, however many Indigenous families are not receiving services. Improvement in
resourcing and support of social and emotional wellbeing services in primary care centers is needed.
Keywords: Health services, Indigenous, Child health services, Quality improvement, Child welfare
Background
Primary care providers work at the first level of the
health system in clinics and health centers and include
nurses, doctors and community health workers.
Evidence is emerging about the potential for primary
care providers to improve social and emotional well-
being and long term neurodevelopmental outcomes in
disadvantaged children [1–4]. ‘Child health checks’ are a
core component of primary care for Aboriginal and
Torres Strait Islander (hereafter Indigenous) children
across Australia [5–7]. The governments in all Austra-
lian states and territories advise primary care providers
to administer at least one ‘child health check’ to each
Indigenous child every 12 months [5, 6, 8]. The checks
are standardised, based on best practice national guide-
lines, and include physical measurements such as weight
and height, assessment of oral health, assessment of
developmental milestones and discussion about social
and emotional needs including: parent child interaction,
physical and mental stimulation of the child, child
* Correspondence: karen.edmond@uwa.edu.au
1
School of Medicine, Division Paediatrics, The University of Western Australia,
35 Stirling Highway, Crawley, Western Australia 6009, Australia
Full list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Edmond et al. BMC Health Services Research (2018) 18:100
DOI 10.1186/s12913-018-2883-6
Quality of social and emotional wellbeing
services for families of young Indigenous
children attending primary care centers; a
cross sectional analysis
Karen M. Edmond 1*
, Kimberley McAuley 1
, Daniel McAullay 1,2 , Veronica Matthews 3
, Natalie Strobel 1
,
Rhonda Marriott4 and Ross Bailie 3
Abstract
Background: The quality of social and emotional wellbeing services for Indigenous families of young children is
not known, in many settings especially services provided by primary care centers.
Methods: Our primary objective was to assess delivery of social and emotional wellbeing services to the families of
young (3–11 months) and older (12–59 months) Indigenous children attending primary care centers. Our secondary
objective was to assess if delivery differed by geographic location. Two thousand four hundred sixty-six client files
from 109 primary care centers across Australia from 2012 to 2014 were analysed using logistic regression and
generalised estimating equations.
Results: The proportion of families receiving social and emotional wellbeing services ranged from 10.6% (102)
(food security) to 74.7% (1216) (assessment of parent child interaction). Seventy one percent (71%, 126) of families
received follow up care. Families of children aged 3–11 months (39.5%, 225) were more likely to receive social and
emotional wellbeing services (advice about domestic environment, social support, housing condition, child stimulation)
than families of children aged 12–59 months (30.0%, 487) (adjusted odds ratio [aOR] 1.68 95% CI 1.33 to 2.13). Remote
area families (32.6%, 622) received similar services to rural (29.4%, 68) and urban families (44.0%, 22) (aOR 0.64 95% CI 0.
29, 1.44).
Conclusions: The families of young Indigenous children appear to receive priority for social and emotional wellbeing
care in Australian primary care centers, however many Indigenous families are not receiving services. Improvement in
resourcing and support of social and emotional wellbeing services in primary care centers is needed.
Keywords: Health services, Indigenous, Child health services, Quality improvement, Child welfare
Background
Primary care providers work at the first level of the
health system in clinics and health centers and include
nurses, doctors and community health workers.
Evidence is emerging about the potential for primary
care providers to improve social and emotional well-
being and long term neurodevelopmental outcomes in
disadvantaged children [1–4]. ‘Child health checks’ are a
core component of primary care for Aboriginal and
Torres Strait Islander (hereafter Indigenous) children
across Australia [5–7]. The governments in all Austra-
lian states and territories advise primary care providers
to administer at least one ‘child health check’ to each
Indigenous child every 12 months [5, 6, 8]. The checks
are standardised, based on best practice national guide-
lines, and include physical measurements such as weight
and height, assessment of oral health, assessment of
developmental milestones and discussion about social
and emotional needs including: parent child interaction,
physical and mental stimulation of the child, child
* Correspondence: karen.edmond@uwa.edu.au
1
School of Medicine, Division Paediatrics, The University of Western Australia,
35 Stirling Highway, Crawley, Western Australia 6009, Australia
Full list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Edmond et al. BMC Health Services Research (2018) 18:100
DOI 10.1186/s12913-018-2883-6
behaviour, optimal domestic and social environment,
housing and food security, and social and family support
services [8].
However, it is not clear how well social and emotional
wellbeing services are being implemented in busy pri-
mary care settings, and there is little information about
the implementation of social and emotional services for
the families of the youngest infants who require the
most support. Variation between urban, rural and
remote locations is also unclear.
The Audit and Best Practice for Chronic Disease
(ABCD) program is a continuous quality improvement
(CQI) program for the prevention and management of
chronic disease in Indigenous people in Australia [9, 10].
The program broadened its scope in 2007 to include
maternal and child health, mental health and health
promotion. By the end of 2014 ABCD and its service
support organisation (One21seventy [11]) had supported
over 270 primary care centers across Australia. There
are now data available from standardised audits of
almost 15,000 clinical files of Indigenous children who
attended primary care centers across Australia from
2007 to 2014.
The primary objective of this study was to use ABCD
data from 2012 to 2014 to assess the delivery of social
and emotional wellbeing services in Australian primary
care centers to the families of young (3–11 months) and
older (12–59 months) Indigenous children. The second-
ary objective was to assess if delivery differed by
geographic location.
Methods
Study setting and design
This was a cross sectional study of client files from the
109 remote, rural and urban Australian primary care
centers that participated in ABCD from 2012 to 2014.
Key characteristics are presented in Table 1.
Data collection
The ABCD program included annual audits of client
files in all participating primary care centers [9, 10]. The
audits were implemented by primary care center staff
who had received standardised training with ABCD
educators including assessment of interrater reliability
[9, 10]. The training program was based on national best
practice clinical guidelines and involved face to face
training sessions using a standardised manual and data
collection tool which are available online [10, 12]. Client
files were eligible if the following criteria were met: i)
child aged between 3 months and 14 years at the audit
date; ii) child resident in the community for at least
6 months (or half of the time since birth if aged under
6 months); and iii) child had no major health anomaly
such as heart defects or inherited disorders.
A random sample of at least 30 individual patient re-
cords were selected for audit from each health center.
The auditors read each client file (electronic and paper)
and recorded information in a standardised pre-coded
data collection tool. Child characteristics included: date
of birth, age, sex, Indigenous status, attendance at the
primary care center in the previous 12 months, reason
for the last attendance (acute care, health check, vaccin-
ation, other) and receipt of any child health checks in
the last 12 months (Australian Commonwealth funded
[Medicare 715] or other child health check). Health
center characteristics included governance (Aboriginal
community controlled health service or government op-
erated), location (urban, rural or remote), and number
of CQI audits the primary care center had completed.
The ABCD audit tool also included eleven pre-coded
items about social and emotional wellbeing services
(Table 2). The auditors scored ‘yes’ in the audit tool if
there had been any documentation in the client file in
the last 12 months of: (i) assessment of parent child
interaction (e.g. bonding, attachment, responsiveness);
(ii) advice about: childhood domestic or social environ-
ment (e.g. violence, substance use, gambling); social or
family support (e.g. other family members involved in
care of child, attendance at parent groups, social worker
involvement); finances (e.g. regular employment, social
service payments, food cards); housing condition (e.g.
overcrowding, water and sanitation); food security (e.g.
food consumed in the last 24 h and in the last week);
physical and mental stimulation (e.g. play, reading,
attendance at play groups); child behaviour (e.g. sleep,
crying, and temper tantrums); (iii) evidence of concern
about: domestic or social environment; social or family
support; housing condition; and food security; (iv) follow
up or referral regarding concern about domestic or
social environment; social or family support; housing
condition and food security. Items were recorded as ‘not
applicable’ if they were not specified in the national best
practice guidelines for children of that age [5–7]. The
items that were specified in the national best practice
guidelines for all families of children aged between 3 and
59 months were advice about: physical and mental
stimulation for children; domestic or social environment;
social or family support and advice about housing
condition.
Definitions
We defined a composite measure of social and emo-
tional wellbeing care for the four items required in the
national guidelines for all children aged 3–59 months i.e.
advice provided at least once in the last 12 months
about: domestic environment, social support, housing
condition and child stimulation. The composite measure
was scored as ‘yes’ if all four areas were documented in
Edmond et al. BMC Health Services Research (2018) 18:100 Page 2 of 11
housing and food security, and social and family support
services [8].
However, it is not clear how well social and emotional
wellbeing services are being implemented in busy pri-
mary care settings, and there is little information about
the implementation of social and emotional services for
the families of the youngest infants who require the
most support. Variation between urban, rural and
remote locations is also unclear.
The Audit and Best Practice for Chronic Disease
(ABCD) program is a continuous quality improvement
(CQI) program for the prevention and management of
chronic disease in Indigenous people in Australia [9, 10].
The program broadened its scope in 2007 to include
maternal and child health, mental health and health
promotion. By the end of 2014 ABCD and its service
support organisation (One21seventy [11]) had supported
over 270 primary care centers across Australia. There
are now data available from standardised audits of
almost 15,000 clinical files of Indigenous children who
attended primary care centers across Australia from
2007 to 2014.
The primary objective of this study was to use ABCD
data from 2012 to 2014 to assess the delivery of social
and emotional wellbeing services in Australian primary
care centers to the families of young (3–11 months) and
older (12–59 months) Indigenous children. The second-
ary objective was to assess if delivery differed by
geographic location.
Methods
Study setting and design
This was a cross sectional study of client files from the
109 remote, rural and urban Australian primary care
centers that participated in ABCD from 2012 to 2014.
Key characteristics are presented in Table 1.
Data collection
The ABCD program included annual audits of client
files in all participating primary care centers [9, 10]. The
audits were implemented by primary care center staff
who had received standardised training with ABCD
educators including assessment of interrater reliability
[9, 10]. The training program was based on national best
practice clinical guidelines and involved face to face
training sessions using a standardised manual and data
collection tool which are available online [10, 12]. Client
files were eligible if the following criteria were met: i)
child aged between 3 months and 14 years at the audit
date; ii) child resident in the community for at least
6 months (or half of the time since birth if aged under
6 months); and iii) child had no major health anomaly
such as heart defects or inherited disorders.
A random sample of at least 30 individual patient re-
cords were selected for audit from each health center.
The auditors read each client file (electronic and paper)
and recorded information in a standardised pre-coded
data collection tool. Child characteristics included: date
of birth, age, sex, Indigenous status, attendance at the
primary care center in the previous 12 months, reason
for the last attendance (acute care, health check, vaccin-
ation, other) and receipt of any child health checks in
the last 12 months (Australian Commonwealth funded
[Medicare 715] or other child health check). Health
center characteristics included governance (Aboriginal
community controlled health service or government op-
erated), location (urban, rural or remote), and number
of CQI audits the primary care center had completed.
The ABCD audit tool also included eleven pre-coded
items about social and emotional wellbeing services
(Table 2). The auditors scored ‘yes’ in the audit tool if
there had been any documentation in the client file in
the last 12 months of: (i) assessment of parent child
interaction (e.g. bonding, attachment, responsiveness);
(ii) advice about: childhood domestic or social environ-
ment (e.g. violence, substance use, gambling); social or
family support (e.g. other family members involved in
care of child, attendance at parent groups, social worker
involvement); finances (e.g. regular employment, social
service payments, food cards); housing condition (e.g.
overcrowding, water and sanitation); food security (e.g.
food consumed in the last 24 h and in the last week);
physical and mental stimulation (e.g. play, reading,
attendance at play groups); child behaviour (e.g. sleep,
crying, and temper tantrums); (iii) evidence of concern
about: domestic or social environment; social or family
support; housing condition; and food security; (iv) follow
up or referral regarding concern about domestic or
social environment; social or family support; housing
condition and food security. Items were recorded as ‘not
applicable’ if they were not specified in the national best
practice guidelines for children of that age [5–7]. The
items that were specified in the national best practice
guidelines for all families of children aged between 3 and
59 months were advice about: physical and mental
stimulation for children; domestic or social environment;
social or family support and advice about housing
condition.
Definitions
We defined a composite measure of social and emo-
tional wellbeing care for the four items required in the
national guidelines for all children aged 3–59 months i.e.
advice provided at least once in the last 12 months
about: domestic environment, social support, housing
condition and child stimulation. The composite measure
was scored as ‘yes’ if all four areas were documented in
Edmond et al. BMC Health Services Research (2018) 18:100 Page 2 of 11
Table 1 Key characteristics of client files by geographic location, age and CQI participation in Indigenous children aged 3–59 months
Geographic location Age (months) CQI participation (number
of audits completed)
Total Remote Rural Urban 3–11 12–23 24–59 1 2 > = 3
Total 2466 2010
(81.51%)
371
(15.0%)
85
(3.5%)
609
(24.7%)
532
(21.6%)
1325
(53.7%)
410
(16.6%)
569
(23.1%)
1487
(60.3%)
Health service characteristics
Governance
Aboriginal community
controlled
573
(23.2%)
319
(15.9%)
224
(60.4%)
30
(35.3%)
133
(21.8%)
118
(22.2%)
322
(24.3%)
77
(18.8%)
182
(32.0%)
314
(21.1%)
Government 1893
(76.8%)
1691
(84.1%)
147
(39.6%)
55
(64.7%)
476
(78.2%)
414
(77.8%)
1003
(75.7%)
333
(81.2%)
387
(68.0%)
1173
(78.9%)
Health service provider who first saw the child
Indigenous health worker 338
(13.7%)
220
(10.9%)
94
(25.3%)
24
(28.2%)
69
(11.3%)
67
(12.6%)
202
(15.2%)
21
(5.1%)
88
(15.5%)
229
(15.4%)
Nurse 1723
(69.9%)
1505
(74.9%)
176
(47.4%)
42
(49.4%)
460
(75.5%)
381
(71.6%)
882
(66.6%)
286
(69.8%)
430
(75.6%)
1007
(67.7%)
General practitioner 271
(11.0%)
163
(8.1%)
90
(24.3%)
18
(21.2%)
62
(10.2%)
60
(11.3%)
149
(11.2%)
81
(19.8%)
27
(4.7%)
163
(11.0%)
Other 117 (4.7%) 106 (5.3%) 10 (2.7%) 1 (1.2%) 16 (2.6%) 20
(3.8%)
81 (6.1%) 21
(5.1%)
24
(4.2%)
72 (4.8%)
Missing 17 (0.7%) 16 (0.8%) 1 (0.3%) 0 (0.0%) 2 (0.3%) 4 (0.8%) 11 (0.8%) 1 (0.2%) 0 (0.0%) 16 (1.1%)
Year of data collection
2012 488
(19.8%)
319
(15.9%)
148
(39.9%)
21
(24.7%)
127
(20.9%)
107
(20.1%)
254
(19.2%)
196
(47.8%)
84
(14.8%)
208
(14.0%)
2013 1334
(54.1%)
1163
(57.9%)
171
(46.1%)
0
(0.0%)
313
(51.4%)
276
(51.9%)
745
(56.2%)
155
(37.8%)
274
(48.2%)
905
(60.9%)
2014 644
(26.1%)
528
(26.3%)
52
(14.0%)
64
(75.3%)
169
(27.8%)
149
(28.0%)
326
(24.6%)
59
(14.4%)
211
(37.1%)
374
(25.2%)
Population size
< 500 848
(34.4%)
831
(41.3%)
17
(4.6%)
0
(0.0%)
137
(22.5%)
196
(36.8%)
515
(38.9%)
101
(24.6%)
175
(30.8%)
572
(38.5%)
500–999 499
(20.2%)
448
(22.3%)
41
(11.1%)
10
(11.8%)
114
(18.7%)
101
(19.0%)
284
(21.4%)
104
(25.4%)
92
(16.2%)
303
(20.4%)
> =1000 1119
(45.4%)
731
(36.4%)
313
(84.4%)
75
(88.2%)
358
(58.8%)
235
(44.2%)
526
(39.7%)
205
(50.0%)
302
(53.1%)
612
(41.2%)
Child characteristics
Sex of child
Male 1249
(50.6%)
1017
(50.6%)
189
(50.9%)
43
(50.6%)
310
(50.9%)
272
(51.1%)
667
(50.3%)
202
(49.3%)
283
(49.7%)
764
(51.4%)
Female 1217
(49.4%)
993
(49.4%)
182
(49.1%)
42
(49.4%)
299
(49.1%)
260
(48.9%)
658
(49.7%)
208
(50.7%)
286
(50.3%)
723
(48.6%)
Type of child health check completed in the last 12 months
Medical benefits schedule
(MBS) 715
999
(40.5%)
847
(42.1%)
122
(32.9%)
30
(35.3%)
246
(40.4%)
229
(43.0%)
524
(39.5%)
115
(28.0%)
212
(37.3%)
672
(45.2%)
Other child health check 648
(26.3%)
507
(25.2%)
124
(33.4%)
17
(20.0%)
181
(29.7%)
147
(27.6%)
320
(24.2%)
144
(35.1%)
88
(15.5%)
416
(28.0%)
Not known /
not recorded
819
(33.2%)
656
(32.6%)
125
(33.7%)
38
(44.7%)
182
(29.9%)
156
(29.3%)
481
(36.3%)
151
(36.8%)
269
(47.3%)
399
(26.8%)
Reason for last clinic attendance
Acute care 1200
(48.7%)
990
(49.3%)
171
(46.1%)
39
(45.9%)
265
(43.5%)
271
(50.9%)
664
(50.1%)
161
(39.3%)
284
(49.9%)
755
(50.8%)
Vaccination
Edmond et al. BMC Health Services Research (2018) 18:100 Page 3 of 11
Geographic location Age (months) CQI participation (number
of audits completed)
Total Remote Rural Urban 3–11 12–23 24–59 1 2 > = 3
Total 2466 2010
(81.51%)
371
(15.0%)
85
(3.5%)
609
(24.7%)
532
(21.6%)
1325
(53.7%)
410
(16.6%)
569
(23.1%)
1487
(60.3%)
Health service characteristics
Governance
Aboriginal community
controlled
573
(23.2%)
319
(15.9%)
224
(60.4%)
30
(35.3%)
133
(21.8%)
118
(22.2%)
322
(24.3%)
77
(18.8%)
182
(32.0%)
314
(21.1%)
Government 1893
(76.8%)
1691
(84.1%)
147
(39.6%)
55
(64.7%)
476
(78.2%)
414
(77.8%)
1003
(75.7%)
333
(81.2%)
387
(68.0%)
1173
(78.9%)
Health service provider who first saw the child
Indigenous health worker 338
(13.7%)
220
(10.9%)
94
(25.3%)
24
(28.2%)
69
(11.3%)
67
(12.6%)
202
(15.2%)
21
(5.1%)
88
(15.5%)
229
(15.4%)
Nurse 1723
(69.9%)
1505
(74.9%)
176
(47.4%)
42
(49.4%)
460
(75.5%)
381
(71.6%)
882
(66.6%)
286
(69.8%)
430
(75.6%)
1007
(67.7%)
General practitioner 271
(11.0%)
163
(8.1%)
90
(24.3%)
18
(21.2%)
62
(10.2%)
60
(11.3%)
149
(11.2%)
81
(19.8%)
27
(4.7%)
163
(11.0%)
Other 117 (4.7%) 106 (5.3%) 10 (2.7%) 1 (1.2%) 16 (2.6%) 20
(3.8%)
81 (6.1%) 21
(5.1%)
24
(4.2%)
72 (4.8%)
Missing 17 (0.7%) 16 (0.8%) 1 (0.3%) 0 (0.0%) 2 (0.3%) 4 (0.8%) 11 (0.8%) 1 (0.2%) 0 (0.0%) 16 (1.1%)
Year of data collection
2012 488
(19.8%)
319
(15.9%)
148
(39.9%)
21
(24.7%)
127
(20.9%)
107
(20.1%)
254
(19.2%)
196
(47.8%)
84
(14.8%)
208
(14.0%)
2013 1334
(54.1%)
1163
(57.9%)
171
(46.1%)
0
(0.0%)
313
(51.4%)
276
(51.9%)
745
(56.2%)
155
(37.8%)
274
(48.2%)
905
(60.9%)
2014 644
(26.1%)
528
(26.3%)
52
(14.0%)
64
(75.3%)
169
(27.8%)
149
(28.0%)
326
(24.6%)
59
(14.4%)
211
(37.1%)
374
(25.2%)
Population size
< 500 848
(34.4%)
831
(41.3%)
17
(4.6%)
0
(0.0%)
137
(22.5%)
196
(36.8%)
515
(38.9%)
101
(24.6%)
175
(30.8%)
572
(38.5%)
500–999 499
(20.2%)
448
(22.3%)
41
(11.1%)
10
(11.8%)
114
(18.7%)
101
(19.0%)
284
(21.4%)
104
(25.4%)
92
(16.2%)
303
(20.4%)
> =1000 1119
(45.4%)
731
(36.4%)
313
(84.4%)
75
(88.2%)
358
(58.8%)
235
(44.2%)
526
(39.7%)
205
(50.0%)
302
(53.1%)
612
(41.2%)
Child characteristics
Sex of child
Male 1249
(50.6%)
1017
(50.6%)
189
(50.9%)
43
(50.6%)
310
(50.9%)
272
(51.1%)
667
(50.3%)
202
(49.3%)
283
(49.7%)
764
(51.4%)
Female 1217
(49.4%)
993
(49.4%)
182
(49.1%)
42
(49.4%)
299
(49.1%)
260
(48.9%)
658
(49.7%)
208
(50.7%)
286
(50.3%)
723
(48.6%)
Type of child health check completed in the last 12 months
Medical benefits schedule
(MBS) 715
999
(40.5%)
847
(42.1%)
122
(32.9%)
30
(35.3%)
246
(40.4%)
229
(43.0%)
524
(39.5%)
115
(28.0%)
212
(37.3%)
672
(45.2%)
Other child health check 648
(26.3%)
507
(25.2%)
124
(33.4%)
17
(20.0%)
181
(29.7%)
147
(27.6%)
320
(24.2%)
144
(35.1%)
88
(15.5%)
416
(28.0%)
Not known /
not recorded
819
(33.2%)
656
(32.6%)
125
(33.7%)
38
(44.7%)
182
(29.9%)
156
(29.3%)
481
(36.3%)
151
(36.8%)
269
(47.3%)
399
(26.8%)
Reason for last clinic attendance
Acute care 1200
(48.7%)
990
(49.3%)
171
(46.1%)
39
(45.9%)
265
(43.5%)
271
(50.9%)
664
(50.1%)
161
(39.3%)
284
(49.9%)
755
(50.8%)
Vaccination
Edmond et al. BMC Health Services Research (2018) 18:100 Page 3 of 11
the client file. We explicitly planned to only include
items in the composite score that were required for all
families of children under 5 years. The auditors read
each client file (electronic and paper) and recorded in-
formation in a standardised pre-coded data collection
tool for all (100%) of health centres which included the
item in their best practice guidelines.
We divided geographic location into three categories
based on the Accessibility/ Remoteness Index of
Australia (ARIA) [13]. ARIA data are split into five
categories from least remote (1) (major cities) to most
remote (5) (remote area communities). We defined
‘urban’ as ARIA category one, ‘rural’ as ARIA categories
two to four and ‘remote’ as ARIA category five. The
urban category was very small (Table 1) so we combined
rural and urban into a ‘non-remote’ category for all
statistical analyses.
‘Any CQI participation’ was defined as the completion
of at least one ABCD audit. ‘High CQI participation’ was
defined as completing three or more ABCD audits.
Statistical analysis
We only included the last audit conducted by each
health centre between 2012 and 2014, so each health
centre was only represented once within the time period
and each client record was included only once in the
analysis. All other records were excluded.
The primary outcome measure was the proportion of
families which had received the composite measure of
social and emotional wellbeing care. We calculated that
our dataset of almost 2500 client files would provide
90% power to detect at least a 10% difference in quality
of care for families of children aged 3–11 months and
families of children aged 12–59 months. We assumed a
5% significance level, a baseline level of quality of care of
50% in families children aged 3–11 months and that the
ratio between families of children aged 3–11 months
and 12–59 months would be approximately 1:4 [14].
The items assessed in this study are services pro-
vided for the whole client population of both well
and unwell children. The denominator is the client
population and the numerator is whether a problem
is detected or not as a dichotomous variable. Crude
and adjusted logistic generalised estimating equations
(GEE) were used to examine the effect of age (3–11,
12–59 months) on the delivery of social and
emotional wellbeing care and to account for loss of
independence due to clustering. GEEs are a standard
method widely recommended to account for loss of
independence in regression models due to clustering
[15–17]. Odds ratios (ORs) and 95% confidence inter-
vals (95% CI) were calculated. Multilevel binomial
models with an exchangeable correlation structure
and robust standard errors were used with primary
care center as the clustering variable. Multivariable
regression models were constructed a priori to adjust
for the effect of important explanatory variables: age,
sex of child, geographic location, governance struc-
ture, CQI participation andk year of data collection.
Similar methods were used to assess if effects differed
by geographic location. Data analyses were conducted
using STATA 13.1.
Ethical approval
Ethical approval was obtained from all Human Research
Ethics Committees (HRECs) in the states and territories
involved: the Human Research Ethics Committee
(HREC) of the Northern Territory Department of Health
and Menzies School of Health Research (HREC-
EC00153); Central Australian HREC (HREC-12-53);
Queensland HREC Darling Downs Health Services Dis-
trict (HREC/11/QTDD/47); South Australian Indigenous
Health Research Ethics Committee (04–10-319); Curtin
University HREC (HR140/2008); Western Australian
Country Health Services Research Ethics Committee
(2011/27); Western Australian Aboriginal Health Ethics
Committee (111–8/05); and University of Western
Australia HREC (RA/4/1/5051).
Results
There were 2466 client files of Indigenous children
aged between 3 and 59 months from 109 primary
Table 1 Key characteristics of client files by geographic location, age and CQI participation in Indigenous children aged 3–59 months
(Continued)
Geographic location Age (months) CQI participation (number
of audits completed)
Total Remote Rural Urban 3–11 12–23 24–59 1 2 > = 3
366
(14.8%)
268
(13.3%)
78
(21.0%)
20
(23.5%)
122
(20.0%)
87
(16.4%)
157
(11.8%)
64
(15.6%)
89
(15.6%)
213
(14.3%)
Child health check 577
(23.4%)
467
(23.2%)
92
(24.8%)
18
(21.2%)
155
(25.5%)
112
(21.1%)
310
(23.4%)
105
(25.6%)
117
(20.6%)
355
(23.9%)
Other 323
(13.1%)
285
(14.2%)
30
(8.1%)
8
(9.4%)
67
(11.0%)
62
(11.7%)
194
(14.6%)
80
(19.5%)
79
(13.9%)
164
(11.0%)
CQI Continuous quality improvement
Edmond et al. BMC Health Services Research (2018) 18:100 Page 4 of 11
items in the composite score that were required for all
families of children under 5 years. The auditors read
each client file (electronic and paper) and recorded in-
formation in a standardised pre-coded data collection
tool for all (100%) of health centres which included the
item in their best practice guidelines.
We divided geographic location into three categories
based on the Accessibility/ Remoteness Index of
Australia (ARIA) [13]. ARIA data are split into five
categories from least remote (1) (major cities) to most
remote (5) (remote area communities). We defined
‘urban’ as ARIA category one, ‘rural’ as ARIA categories
two to four and ‘remote’ as ARIA category five. The
urban category was very small (Table 1) so we combined
rural and urban into a ‘non-remote’ category for all
statistical analyses.
‘Any CQI participation’ was defined as the completion
of at least one ABCD audit. ‘High CQI participation’ was
defined as completing three or more ABCD audits.
Statistical analysis
We only included the last audit conducted by each
health centre between 2012 and 2014, so each health
centre was only represented once within the time period
and each client record was included only once in the
analysis. All other records were excluded.
The primary outcome measure was the proportion of
families which had received the composite measure of
social and emotional wellbeing care. We calculated that
our dataset of almost 2500 client files would provide
90% power to detect at least a 10% difference in quality
of care for families of children aged 3–11 months and
families of children aged 12–59 months. We assumed a
5% significance level, a baseline level of quality of care of
50% in families children aged 3–11 months and that the
ratio between families of children aged 3–11 months
and 12–59 months would be approximately 1:4 [14].
The items assessed in this study are services pro-
vided for the whole client population of both well
and unwell children. The denominator is the client
population and the numerator is whether a problem
is detected or not as a dichotomous variable. Crude
and adjusted logistic generalised estimating equations
(GEE) were used to examine the effect of age (3–11,
12–59 months) on the delivery of social and
emotional wellbeing care and to account for loss of
independence due to clustering. GEEs are a standard
method widely recommended to account for loss of
independence in regression models due to clustering
[15–17]. Odds ratios (ORs) and 95% confidence inter-
vals (95% CI) were calculated. Multilevel binomial
models with an exchangeable correlation structure
and robust standard errors were used with primary
care center as the clustering variable. Multivariable
regression models were constructed a priori to adjust
for the effect of important explanatory variables: age,
sex of child, geographic location, governance struc-
ture, CQI participation andk year of data collection.
Similar methods were used to assess if effects differed
by geographic location. Data analyses were conducted
using STATA 13.1.
Ethical approval
Ethical approval was obtained from all Human Research
Ethics Committees (HRECs) in the states and territories
involved: the Human Research Ethics Committee
(HREC) of the Northern Territory Department of Health
and Menzies School of Health Research (HREC-
EC00153); Central Australian HREC (HREC-12-53);
Queensland HREC Darling Downs Health Services Dis-
trict (HREC/11/QTDD/47); South Australian Indigenous
Health Research Ethics Committee (04–10-319); Curtin
University HREC (HR140/2008); Western Australian
Country Health Services Research Ethics Committee
(2011/27); Western Australian Aboriginal Health Ethics
Committee (111–8/05); and University of Western
Australia HREC (RA/4/1/5051).
Results
There were 2466 client files of Indigenous children
aged between 3 and 59 months from 109 primary
Table 1 Key characteristics of client files by geographic location, age and CQI participation in Indigenous children aged 3–59 months
(Continued)
Geographic location Age (months) CQI participation (number
of audits completed)
Total Remote Rural Urban 3–11 12–23 24–59 1 2 > = 3
366
(14.8%)
268
(13.3%)
78
(21.0%)
20
(23.5%)
122
(20.0%)
87
(16.4%)
157
(11.8%)
64
(15.6%)
89
(15.6%)
213
(14.3%)
Child health check 577
(23.4%)
467
(23.2%)
92
(24.8%)
18
(21.2%)
155
(25.5%)
112
(21.1%)
310
(23.4%)
105
(25.6%)
117
(20.6%)
355
(23.9%)
Other 323
(13.1%)
285
(14.2%)
30
(8.1%)
8
(9.4%)
67
(11.0%)
62
(11.7%)
194
(14.6%)
80
(19.5%)
79
(13.9%)
164
(11.0%)
CQI Continuous quality improvement
Edmond et al. BMC Health Services Research (2018) 18:100 Page 4 of 11
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