30. Huybrechts KF, Caro JJ, London GM. Modeling the implications of changes || 40.

|| 40. An WS, Kim SE, Kim KH et al. Associations between oxidized LDL to LDL
in vascular calcification in patients on hemodialysis. Kidney Int 2005; 67: || ratio, HDL and vascular calcification in the feet of hemodialysis patients. J
1532–1538 || Korean Med Sci 2009; 24 (Suppl): S115–S120
31. Block GA, Raggi P, Bellasi A et al. Mortality effect of coronary calcification || 41. Sun L, Zou L, Chen M et al. Meta-analysis of statin therapy in maintenance
and phosphate binder choice in incident hemodialysis patients. Kidney Int
|| dialysis patients. Ren Fail 2015; 37: 1149–1156
||
2007; 71: 438–441 || 42. M€arz W, Genser B, Drechsler C et al. Atorvastatin and low-density lipopro-
32. Schwarz U, Buzello M, Ritz E et al. Morphology of coronary atherosclerotic || tein cholesterol in type 2 diabetes mellitus patients on hemodialysis. Clin J
lesions in patients with end-stage renal failure. Nephrol Dial Transplant || Am Soc Nephrol 2011; 6: 1316–1325
2000; 15: 218–223
|| 43. Yazbek DC, de Carvalho AB, Barros CS et al. Cardiovascular disease in early
||
33. Floege J, Kim J, Ireland E et al. Serum iPTH, calcium and phosphate, and || kidney transplantation: comparison between living and deceased donor
the risk of mortality in a European haemodialysis population. Nephrol Dial || recipients. Transplant Proc 2012; 44: 3001–3006
Transplant 2011; 26: 1948–1955 || 44. Kim HG, Song SW, Kim TY et al. Risk factors for progression of aortic arch
34. Floege J, Gillespie IA, Kronenberg F et al. Development and validation of a
|| calcification in patients on maintenance hemodialysis and peritoneal dialy-
||
predictive mortality risk score from a European hemodialysis cohort. || sis. Hemodial Int 2011; 15: 460–467
Kidney Int 2015; 87: 996–1008 || 45. Roberts WC, Taylor MA, Shirani J. Cardiac findings at necropsy in patients
35. Palmer SC, Craig JC, Navaneethan SD et al. Benefits and harms of statin || with chronic kidney disease maintained on chronic hemodialysis. Medicine
||
therapy for persons with chronic kidney disease: a systematic review and || 2012; 91: 165–178
meta-analysis. Ann Intern Med 2012; 157: 263–275 || 46. Pruijm M, Schmidtko J, Aho A et al. High prevalence of anti-
36. Steinberg D. The LDL modification hypothesis of atherogenesis: an update. || apolipoprotein/A-1 autoantibodies in maintenance hemodialysis and associ-
J Lipid Res 2009; 50 (Suppl): S376–S381
|| ation with dialysis vintage. Ther Apher Dial 2012; 16: 588–594
||
37. Samouilidou EC, Karpouza AP, Kostopoulos V et al. Lipid abnormalities || 47. Herrington W, Haynes R, Staplin N et al. Evidence for the prevention and
and oxidized LDL in chronic kidney disease patients on hemodialysis and || treatment of stroke in dialysis patients. Semin Dial 2015; 28: 35–47
peritoneal dialysis. Ren Fail 2012; 34: 160–164 || 48. Findlay MD, Thomson PC, Fulton RL et al. Risk factors of ischemic stroke
38. Johnson-Davis KL, Fernelius C, Eliason NB et al. Blood enzymes and oxida-
|| and subsequent outcome in patients receiving hemodialysis. Stroke 2015; 46:
||
tive stress in chronic kidney disease: a cross sectional study. Ann Clin Lab || 2477–2481
Sci 2011; 41: 331–339 ||
39. Pawlak K, Mysliwiec M, Pawlak D. Oxidized low-density lipoprotein || Received: 1.3.2016; Editorial decision: 6.9.2016
(oxLDL) plasma levels and oxLDL to LDL ratio—are they real oxidative
||
||
stress markers in dialyzed patients? Life Sci 2013; 92: 253–258 ||
||

Nephrol Dial Transplant (2018) 33: 112–121

doi: 10.1093/ndt/gfw359
Advance Access publication 23 January 2017

Chronic disease management interventions for people with

chronic kidney disease in primary care: a systematic review and
meta-analysis
Lauren Galbraith1,2, Casey Jacobs3, Brenda R. Hemmelgarn1,2,4, Maoliosa Donald1,2, Braden J. Manns1,2,4
and Min Jun1,2
1
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada, 2Interdisciplinary Chronic Disease Collaboration,
Calgary, Alberta, Canada, 3Faculty of Veterinary Medicine, Department of Production Animal Health, University of Calgary, Calgary, Alberta,
Canada and 4Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

Correspondence and offprint requests to: Min Jun; E-mail: mjun@ucalgary.ca

interventions used by primary care providers managing patients

ABSTRACT || with CKD.
|| Methods. The Medline, Embase and Cochrane Central data-
Background. Primary care providers manage the majority of ||
|| bases were systematically searched (inception to November
patients with chronic kidney disease (CKD), although the most || 2014) for randomized controlled trials (RCTs) assessing
effective chronic disease management (CDM) strategies for ||
|| education-based and computer-assisted CDM interventions tar-
these patients are unknown. We assessed the efficacy of CDM || geting primary care providers managing patients with CKD in
||

C The Author 2017. Published by Oxford University Press

V 112
on behalf of ERA-EDTA. All rights reserved.
the community. The efficacy of CDM interventions was || key stakeholders have limited guidance for CKD management
assessed using quality indicators [use of angiotensin-converting
|| programs.
|| Several studies have attempted to determine how interven-
enzyme inhibitor (ACEI) or angiotensin receptor blocker ||
(ARB), proteinuria measurement and achievement of blood
|| tions targeting primary care providers affect the management of
|| patients with CKD, but these found considerable variability in
pressure (BP) targets] and clinical outcomes (change in BP and ||
|| efficacy on patient outcomes and processes of care [13, 14].
glomerular filtration rate). Two independent reviewers eval- ||
uated studies for inclusion, quality and extracted data. Random || Furthermore, a recent systematic review found that despite the
|| emphasis on early management of CKD, a substantial evi-
effects models were used to estimate pooled odds ratios (ORs) ||
and weighted mean differences for outcomes of interest. || dence–practice gap persists regarding the most effective strat-
|| egies for managing patients with CKD in the community [15].
Results. Five studies (188 clinics; 494 physicians; 42 852 patients ||
with CKD) were included. Two studies compared computer- || We therefore conducted a systematic review and meta-
|| analysis of randomized controlled trials (RCTs) to evaluate the
assisted intervention strategies with usual care, two studies com- ||
pared education-based intervention strategies with computer- || efficacy of primary care physician-targeted CDM interventions
|| meant to improve outcomes and processes of care for people
assisted intervention strategies and one study compared both ||
these intervention strategies with usual care. || with CKD compared with usual care.
||
Compared with usual care, computer-assisted CDM interven- ||
tions did not increase the likelihood of ACEI/ARB use among ||
|| MATERIALS AND METHODS
patients with CKD fpooled OR 1.00 [95% confidence interval ||
(CI) 0.83–1.21]; I2 ¼ 0.0%g. Similarly, education-related CDM ||
|| Data sources and searches
interventions did not increase the likelihood of ACEI/ARB use |||
compared with computer-assisted CDM interventions [pooled || We performed a systematic review and meta-analysis
OR 1.12 (95% CI 0.77–1.64); I2 ¼ 0.0%]. Inconsistencies in || according to the Preferred Reporting Items for Systematic
||
reporting methods limited further pooling of data. || Reviews and Meta-analyses for the conduct of meta-analyses of
Conclusions. To date, there have been very few randomized tri- || RCTs [16]. Medline via OVID (1946–November 2014), Embase
||
als testing CDM interventions targeting primary care providers || via OVID (1947–November 2014) and the Cochrane Central
with the goal of improving care of people with CKD. Those con- || Registry of Controlled Trials (CENTRAL; no date restriction)
||
ducted to date have shown minimal impact, suggesting that || were systematically searched (Supplementary data, Table S1)
other strategies, or multifaceted interventions, may be required
||
|| for relevant RCTs. Relevant text words and subject headings
to enhance care for patients with CKD in the community. || were used to capture computer-assisted and education-based
||
Keywords: chronic disease management, chronic kidney dis- || interventions including electronic prompts, computer decision
|| support systems, audit and feedback, academic detailing and
ease, computer-assisted, education-assisted, nephrology, pri- ||
mary care || guideline education. The search was not limited by language.
|| Two reviewers (L.G. and C.J.) manually searched reference lists
||
|| of all included articles, systematic reviews and meta-analyses for
|| additional eligible articles. Finally, experts in the field were con-
INTRODUCTION
||
|| tacted to obtain information about additional ongoing or
|| unpublished studies.
Chronic kidney disease [CKD; defined as a glomerular filtration ||
||
rate (GFR) <60 mL/min/1.73 m2] is a significant public health ||
problem [1] affecting an estimated 2.9 million Canadian adults || Study selection
||
[2] and increases the risk of cardiovascular disease and all-cause || We included cluster RCTs of adult patients with CKD man-
mortality [3]. Clinical practice guidelines recommend early rec- || aged by primary care providers in the community. We focused
||
ognition of CKD, modification of risk factors associated with || on cluster RCTs since health services interventions related to
CKD progression (e.g. hypertension, diabetes and proteinuria) || the assessment of delivery of care modes such as computer-
||
and management of CKD-related complications (e.g. cardiovas- || assisted and education-based decision support systems are often
cular disease, anemia and bone disease) [4–8]. However, trans- || tested at the level of the practice rather than the individual
||
lating guidelines into practice has been challenging [9, 10]. Data || patient [17]. We limited the CDM interventions to physician-
suggest that chronic disease management (CDM) strategies || targeted interventions only (computer-assisted and education-
||
(defined as ongoing and proactive follow-up of patients) are || based), as we were interested in the impact of interventions tar-
effective in improving care for patients with diabetes and thus
|| geting primary care providers on patient outcomes. Usual care
||
may prove helpful in addressing the evidence-to-practice gap in || (defined as the typical care received consisting of assessments
CKD care [11]. However, evidence to date has shown that CDM
||
|| and treatments considered necessary by the family doctor) was
strategies are not equally effective for improving patient care || the comparator of interest. Studies were restricted to trials that
among various chronic conditions [12]. Although current CKD
||
|| measured quality indicators or clinical or process of care out-
practice guidelines recommend the development of disease || comes. Studies that included patients with end-stage renal dis-
||
management programs that optimize community management || ease (those treated with renal replacement therapy or kidney
of CKD, they do not provide a consensus on the optimal strat- || transplant) were excluded. A third reviewer (M.J.) was con-
||
egy for CKD management [4]. As such, decision makers and sulted in cases where discrepancies existed between reviewers.

Managing CKD in primary care 113

 Data extraction and quality assessment || identify those for full-text review (Figure 1). Of the 15 studies
Information from articles selected for inclusion in the system- || reviewed in full, 5 RCTs were eligible for inclusion [14, 21–24].
|| Four studies [14, 21, 22, 24] provided data appropriate for
atic review and meta-analysis was extracted into an Excel spread- ||
sheet (Microsoft, Redmond, WA, USA) independently by two
|| meta-analysis while one study [23] was described qualitatively
|| due to differences in reporting methods. A total of 23 unique
reviewers (L.G. and C.J.). Data abstracted included the study set- ||
ting (country, primary care or community setting, cluster design),
|| patient and processes of care outcomes were reported in the
|| four trials included in the meta-analysis. However, only five
intervention details (computer-assisted or education-based, ||
description, duration), comparator(s), participant demographics
|| outcomes (ACEI/ARB use, achieving target BP, proteinuria
||
(number of clinics, physicians and patients; mean patient age; sex || measurement, mean SBP and mean eGFR) were reported in
|| two or more studies.
proportions; comorbidities) and outcome events as described ||
below. Risk of bias of all eligible articles was independently || We observed substantial variability in the components of the
|| CDM interventions assessed across the included studies. Of the
assessed using the Cochrane Collaboration Tool for Assessing ||
Risk of Bias [18]. Each study was assigned a risk of bias score from || four studies eligible for inclusion in the meta-analysis, one study
|| compared the use of two 15-min education sessions combined
low to high based on sequence generation, allocation concealment, ||
blinding, incomplete outcome data, selective outcome reporting || with real-time automated electronic medical record (EMR)
|| alerts for patients with eGFR <45 mL/min/1.73 m2 (computer-
and other potential threats to validity as outlined in the tool. ||
|| ized prompt intervention) with the use of only two 15-min edu-
|| cation sessions (education-based intervention) [24]. The second
Outcomes ||
|| study compared an education intervention consisting of a lec-
Data were collected on (i) the proportion of patients using || ture on CKD guidelines with a computer-assisted intervention
angiotensin-converting enzyme inhibitors (ACEIs) or angioten- ||| (access to a web-based CKD registry combined with a lecture of
sin receptor blockers (ARBs), (ii) the proportion of patients ||
|| CKD guidelines) [22]. A third study compared an enhanced
who reached a prespecified blood pressure (BP) target, the || management-based laboratory eGFR prompt with usual care
mean systolic blood pressure (SBP), the proportion of patients ||
|| (standard eGFR laboratory prompt) [14]. The final study com-
who had a measurement of proteinuria and the mean estimated || pared an education-based intervention consisting of audit-
glomerular filtration rate (eGFR) at the end of the study. ||
|| based education, including feedback and training at data quality
|| workshops, printed aids and target patient lists compared with
||
Data synthesis and analysis || usual care. In addition, this study compared a computer-
|| assisted intervention (academic detailing, printed information
For binary outcomes, individual study outcomes were ||
expressed as odds ratios (ORs) with 95% confidence intervals || including CKD guidelines, and access to an information web-
|| site) with usual care [21].
(CIs) calculated from the event numbers extracted from each ||
trial. In the case where event numbers were not provided, the || The study characteristics, interventions and outcomes of the
|| five studies included in the qualitative synthesis are summarized
reported OR was extracted. ORs were calculated with the pro- ||
portion of events as the numerator and proportion of nonevents || in Table 1. Overall, study size ranged from 94 to 504 207
|| patients and between 30 and 354 physicians from up to 93 clinic
as the denominator. Continuous outcomes were expressed as ||
weighted mean differences calculated using end-of-trial mean || settings. Mean patient age ranged from 62 to 78 years. Males
|| represented the minority in four of the five studies (range 34–
values, standard deviations and treatment arm size. To account ||
for relative variability within and between randomized clusters, || 45%) [14, 21, 23, 24] and one study reported 95% of patients
||
appropriate adjustments were made using the intraclass correla- || being male [22]. Studies were conducted in the USA, Canada,
tion coefficient [19] prior to pooling. A random effects model || the UK and Mexico and were published between 2008 and
||
was used to calculate summary estimate ORs or weighted mean || 2013. All studies identified were published in English.
differences of the outcomes of interest. Heterogeneity was || Study quality of included studies was assessed and is pre-
||
assessed with the I2 statistic, expressed as the percentage of vari- || sented in Table 2. Allocation concealment is of concern in clus-
ability across studies attributable to heterogeneity beyond || ter randomized trials, as all clusters are typically randomized at
||
chance. Publication bias was assessed using the Begg’s test with || once [19]; however, this was included as a key indicator within
graphical representation using funnel plots of the natural loga- || the Cochrane Collaboration tool for assessing risk of bias. One
||
rithm of the OR against its standard error. A two-sided P-value || study [14] did not contain any components with a high risk of
<0.05 was considered statistically significant. All analyses were || bias. There was one study each with a high risk of bias in one,
||
performed using STATA, version 13 (StataCorp, College || two or three of the key indicators. De Lusignana et al. [21] was
Station, TX, USA)[20].
|| assessed with the highest risk of bias in three indicators: incom-
||
|| plete outcome data, selective outcome reporting and other sour-
|| ces of bias. Cortes-Sanabria et al. [23] was rated with low or
||
|| uncertain risk of bias in all components but was excluded from
RESULTS || meta-analysis and Table 2 as previously mentioned.
||
||
Search results and characteristics of included studies || Patient clinical outcomes and processes of care
||
The literature search yielded 1405 articles, which were || ACEI/ARB use. Two studies provided sufficient information
||
screened by reviewers with 98.4% agreement (j ¼ 0.51) to to compare the effects of computer-assisted interventions with

114 L. Galbraith et al.

FIGURE 1: Flow diagram of studies that were considered for inclusion.

usual care on the proportion of patients using ACEI/ARBs [14, || BP target. Three studies [21, 22, 24] reported the proportion
21]. The proportion of patients using ACEI/ARBs did not differ || of patients achieving a prespecified BP target (130/80 or 140/80
between computer-assisted interventions and usual care
|| mmHg). The proportion was similar for education-based com-
||
[pooled OR 1.00 (95% CI 0.83–1.21)] (Figure 2) (I2 ¼ 0.0%, P- || pared with computer-assisted interventions [pooled OR 1.11
value ¼ 0.60). Three studies [21, 22, 24] provided data sufficient
|| (95% CI 0.90–1.37)] (Figure 3), with no evidence of heterogene-
||
to compare ACEI/ARB use between education-based and || ity across studies included (I2 ¼ 0.0%, P ¼ 0.86).
||
computer-assisted interventions; similarly, the proportion of ||
patients using ACEI/ARBs did not differ [pooled OR 1.12 (95% || Proteinuria assessment. Two [22, 24] studies provided suf-
||
CI 0.77–1.64)] (Figure 2) with no evidence of heterogeneity in || ficient information to compare the effects of education-based
the magnitude of effect across the included studies (I2 ¼ 0.0%, P || interventions with computer-assisted interventions on the pro-
||
¼ 0.87). portion of patients having a proteinuria measurement (binary

Managing CKD in primary care 115

 Table 1. Characteristics of included studies

116
Author (year) Country Inclusion criteria Intervention (category) Comparator Unit of Total no. Mean Patient Outcomes reported Timeline
of origin randomization of patients patient gender
(no. of age (% male)
clusters) (years)
Cortés-Sanabria Mexico Primary health care 6-months education based on Usual care Clinic 94 (2) 62.0 43.5 Clinical competence of 6-months intervention;
et al. (2008) units, patients with type theory-practice model physicians; BP; BMI; smok- outcomes assessed at
2 diabetes and CKD ing cessation; alcohol cessa- enrollment, 6- and
tion; glucose; cholesterol; 12-month time points
albuminuria; eGFR; use of
antihypertensives, antidia-
betics, statins, NSAID use
Abdel-Kader USA CKD patients (eGFR Two 15-min education Two 15-min Physician 248 (30) 65.3 37.7 EMR order for nephrology 12-month interven-
et al. (2011) <45 mL/min/1.73 m2) sessions (education related) þ education sessions practice consultation; Albuminuria tion; outcomes
in the 12 months prior real-time automated EMR (education related) or proteinuria; ACEI/ARB, assessed 1 year before
to their visit and had alerts (EMR related) for NSAID use; documentation and 1 year after
never been evaluated by patients with eGFR of CKD; achievement of (exceptions ACEI/
a nephrologist <45 mL/min/1.73 m2 target BP; BP; eGFR; Hb; ARB assessed at onset
bicarbonate; calcium; and after
phosphorus; PTH
Drawz et al. USA Primary care clinics, Access to web-based CKD Lecture on CKD Patients 781 (N/A) 71.0 95.2 PTH measurement; 12-month interven-
(2012) CKD patients (eGFR registry (EMR related) þ guidelines achievement of target BP; tion; outcomes
<60 mL/min/1.73 m2 lecture on CKD guidelines (education related) phosphorous; proteinuria; assessed 1 year before
based on two readings (education related) Hb measurement; use of and 1 year after
between 90–730 days ACEI/ARB, diuretica
previous
Manns et al. Canada Primary care practices, Enhanced eGFR laboratory Standard eGFR Clinic 5444 (90) 78.1 44.8 ACEI/ARB prescription; 12-month interven-
(2012) elderly (>66 years old) prompt (EMR related) laboratory prompt cholesterol lowering medi- tion; outcomes
CKD patients defined (usual care) cation; new class antihyper- assessed within 1 year
by eGFR <60 mL/min/ tensive medication; of first prompt
1.73 m2 with diabetes or nephrologist consultation;
proteinuria albuminuria measurement;
Lipid measurement; Hb
A1C measurement
de Lusignana UK Primary care clinics, Audit-based education Usual care Clinic 504 207 (93) 75.0 33.9 Reduction in SBP over time; 2-year intervention;
et al. (2013) CKD patients (eGFR (education related) involved incident cases of cardiovas- outcomes assessed
<60/mL/min/1.73 m2) feedback and training at data cular disease; eGFR between earliest and
based on two readings quality workshops, printed latest measurements
at least 90 days apart aids, target patient lists.
Guidelines and prompts
(EMR related) involved
academic detailing, printed
information including CKD
guidelines, and access to an
information website
Outcomes reported in studies included continuous variables, expressed as means, and categorical variables, expressed as numbers or proportions.
KDOQI, Kidney Disease Outcomes Quality Initiative; N/A, not applicable; BP, blood pressure; Hb, hemoglobin; TG, triglyceride; SCr, serum creatinine; SBP, systolic blood pressure; PTH, parathyroid hormone; ACEI/ARB, angiotensin-converting
enzyme inhibitor or angiotensin receptor blocker; EMR, electronic medical record; NSAID, nonsteroidal anti-inflammatory drug; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate.
a
Outcomes reported as ORs.

L. Galbraith et al.
Table 2. Risk of bias assessment of included trials using the Cochrane Collaboration Tool for Assessing Risk of Bias

Sequence Allocation Blinding Incomplete Selective outcome Other potential

generation concealment outcome data reporting biases
Abdel-Kadar et al. [24] Low ? High Low Low ?
Drawz et al. [22] High High Low Low Low ?
Manns et al. [14] Low Low ? Low Low Low
De Lusignana et al. [21] Low ? Low High High High

FIGURE 2: Forest plot of studies reporting the odds of ACEI/ARB use in CKD patients between computer-assisted CDM interventions and
usual care and education-based and computer-assisted CDM interventions using random effects analysis.

measure). The proportion of patients with a proteinuria assess- intervention types [WMD 0.32 mL/min/ 1.73 m2 (95% CI
||
ment did not differ [pooled OR 0.87 (95% CI 0.41–1.84)] || 2.37–1.73)], with no evidence of heterogeneity (I2 ¼ 0.0%, P
(Figure 3), with moderate heterogeneity across the included || ¼ 0.89) (Figure 4).
||
studies (I2 ¼ 63.7%, P ¼ 0.09). ||
||
|| Publication bias. Publication bias could not be assessed due
Mean change in SBP. The mean difference in SBP postinter- || to inconsistency of data reporting in the included studies.
||
vention between the education-based and computer-assisted ||
interventions was included as an outcome in two [21, 24] stud- ||
||
ies identified. The mean difference in SBP did not differ ||
|| DISCUSSION
[weighted mean difference (WMD) 0.59 mmHg (95% CI
||
2.80–1.61)] across the interventions, with no evidence of het- || Our systematic review assessing CDM interventions targeting
erogeneity across the included studies (I2 ¼ 0.0%, P ¼ 0.76) ||
|| primary care providers who care for CKD patients in the com-
(Figure 4). || munity identified a critical lack of studies, with only five rele-
||
|| vant RCTs and with only four eligible for inclusion in the meta-
Mean change in eGFR. Two studies [21, 24] reported the || analysis. When compared with usual care, computer-assisted
||
mean change in eGFR for patients within the education-based || interventions had no effect on ACEI/ARB use among CKD
interventions compared with computer-assisted interventions. || patients. A head-to-head comparison of education-based versus
||
There was no difference in the mean eGFR between the computer-assisted CDM interventions also found no effect on

Managing CKD in primary care 117

FIGURE 3: Forest plot of studies comparing education-based to computer-assisted CDM interventions on the odds of CKD patients reaching a
specified BP target and having a proteinuria assessment using random effects analysis.

FIGURE 4: Forest plot of studies comparing education-based to computer-assisted CDM interventions on the mean weighted difference of
SBP and eGFR in CKD patients using random effects analysis.

any of the patient outcomes or processes of care. However, these assessment and care for these patients. Unfortunately, evi-
||
findings are limited by the considerable lack of evidence for all || dence suggests that many physicians are unfamiliar with the
CDM intervention types targeting primary care providers man- || CKD guidelines, resulting in a significant barrier to uptake
||
aging patients with CKD. || in practice [25–27]. Moreover, dissemination and implemen-
The Kidney Disease: Improving Global Outcomes || tation of guidelines into practice alone is insufficient to
||
(KDIGO) clinical practice guidelines for evaluation and || overcome the challenges of daily management of CKD [9],
management of CKD patients were developed to standardize || as patients with CKD often have numerous comorbid
||

118 L. Galbraith et al.

conditions, making their comprehensive management excep- || strategies in diabetes may be adaptable to CKD disease
tionally challenging [10]. CDM strategies may provide a sol- || management. The complexity of care for CKD patients,
ution to this evidence-practice gap by designing an
|| similar to diabetes patients, may require a standardized
||
intervention to improve patient care. CDM interventions || multidisciplinary approach [12]. Indeed, observational stud-
can be categorized into 11 unique strategies [28] (audit and
|| ies assessing the effectiveness of CDM interventions have
||
feedback, case management, team changes, electronic patient || shown promising results, suggesting favorable effects with
registry, clinician education, clinician reminders, facilitated
|| CDM interventions on improving outcomes among patients
||
relay of clinical information to clinicians, patient education, || with CKD [32–34], congestive heart failure [35, 36], chronic
||
promotion of self-management, patient reminder systems || obstructive pulmonary disease [37] and other chronic dis-
and continuous quality improvement), with each strategy || eases [38, 39]. The development of standardized definitions
||
varying in resource intensity [12]. Compared with usual || for CDM interventions and standardized reporting of uni-
care, CDM interventions aim to streamline these assess- || versally clinically relevant patient outcomes and processes of
||
ments and treatments. However, CDM interventions can be || care would significantly improve the relevance and impact
arduous and the different strategies require careful consider- || of future knowledge in this field.
||
ation of barriers to optimal care, differential effectiveness, || The results of our systematic review should be inter-
resource intensity and ease of implementation prior to || preted in light of the study limitations. We are primarily
||
choosing a CDM strategy [12]. These challenges may con- || limited by the paucity of evidence in the field to date.
tribute to the lack of effect of the interventions reported in || Additionally, this review found considerable heterogeneity in
||
our meta-analysis. || the definitions of CDM intervention within the computer-
There are a number of potential reasons why these || assisted and education-based CDM categories, which was
CDM interventions did not show an effect. Relevant CDM ||| compounded by the inconsistencies in CKD definitions and
||
interventions are required to target patients in earlier stages || outcomes reporting across the five trials. It should be noted
of CKD; however, this may be challenging, as less than 1/ || that while we have reported on the effects of CDM inter-
||
10 of individuals with moderately decreased kidney function || ventions on ACEI/ARB use, the most frequently reported
(stage 3 CKD) report awareness of their CKD [29]. || study outcome across the included studies, this outcome
||
Additionally, in the case of computer-assisted interventions || may have limited relevance in certain patient groups,
(alerts and prompts), primary care providers may have been || including patients without proteinuria, or more generally in
||
overwhelmed, or experienced alert fatigue, by the number || the elderly, in whom ACEI/ARB use is not indicated. Study
of patients receiving a prompt, as identified by two of the || outcomes with broader utility across the wider CKD popu-
||
studies in our review [14, 24]. Importantly, three features || lation are needed.
have been shown to be associated with effective clinical || In summary, the limited evidence to date suggests that
||
decision support: routine guidance as part of clinician work- || computer-assisted CDM interventions targeting primary care
flow, providing recommendations rather than assessments,
|| providers managing patients with CKD in the community
||
and provision of guidance at the time and location of deci- || have no effect on patient outcomes and processes of care when
sion making [30]. Only two [14, 24] of the four included
|| compared with usual care. A similar result was found in
||
studies appear to have considered these features in the || head-to-head comparisons with education-based CDM inter-
development and execution of their CDM interventions. We
|| ventions. Future research is required to further inform this
||
hypothesize that the systematic inclusion of these three fea- || question due to the current lack of evidence and considerable
||
tures would improve the efficacy of CDM interventions for || heterogeneity in the definition of CDM interventions included
primary care providers managing CKD patients. || in this review.
||
Although this review found no effect of CDM interven- ||
tions on patient outcomes and processes of care for CKD ||
||
patients, several systematic reviews of CDM interventions in || AUTHORS’ CONTRIBUTIONS
other settings have demonstrated efficacy, including in dia- ||
||
betic patients, where CDM interventions improved glycemic || All authors contributed to critical revision of this article.
control [11, 28, 31]. Many of the trials included in the || L.G., C.J., B.H. and M.J. contributed to study design and
||
review of people with diabetes used multidisciplinary inter- || data interpretation. L.G. and C.J. were responsible for data
ventions, where different disease management strategies || collection, analysis and manuscript preparation. L.G. and
||
were combined. Regardless of CDM type, all three prior || C.J. are graduate students, M.D. is a senior research associ-
systematic reviews noted that the effectiveness of the CDM || ate, M.J. is a postdoctoral fellow and B.H. and B.M. are
||
strategies was largely determined by two key components: || clinician scientists.
the ability for case managers to adjust treatment and medi- ||
||
cations autonomously (without prior physician approval), as ||
well as regular and high frequency of patient contact [11, ||
|| SUPPLEMENTARY DATA
28, 31]. Given that diabetes and CKD are both chronic ||
conditions and patient characteristics are very similar across || Supplementary data are available online at http://ndt.oxfordjour
||
the two patient groups, components of successful CDM || nals.org.
||

Managing CKD in primary care 119

 15. Black C, Sharma P, Scotland G et al. Early referral strategies for manage-
||
ACKNOWLEDGEMENTS || ment of people with markers of renal disease: a systematic review of the evi-
|| dence of clinical effectiveness, cost-effectiveness and economic analysis.
L.G. was supported by the Strategic Training Initiative in || Health Technol Assess (Rockv) 2010; 14: 1–184
Health Research (STIHR) program, M.J. was supported by || 16. Moher D, Liberati A, Tetzlaff J et al. Preferred reporting items for systematic
||
postdoctoral fellowships from the Canadian Institutes of || reviews and meta-analyses: the PRISMA statement. Br Med J 2009; 339:
Health Research (CIHR), Alberta Innovates Health Solutions || b2535
|| 17. Cochrane Consumers and Communication Review Group: cluster rando-
(AIHS) and an early career fellowship from the National || mised controlled trials. http://cccrg.cochrane.org/. Accessed October 13, 2015
Health and Medical Research Council of Australia ||
|| 18. Higgins JP, Altman DG, Gotzsche PC et al. The Cochrane Collaboration’s
(NHMRC). B.H. is the recipient of the Roy and Vi Baay Chair || tool for assessing risk of bias in randomised trials. Br Med J 2011; 343:
in Kidney Research. The Interdisciplinary Chronic Disease || d5928
|| 19. Higgins JPT GS, ed. Cochrane Handbook for Systematic Reviews of
Collaboration is funded by the Alberta Innovates Health ||
Solutions—CRIO Team Grants Program. This study was not || Interventions. Cochrane Collaboration, 2011. Version 5.1.0
|| 20. Stata Statistical Software: Release 13 [computer program]. College Station,
supported by external funding. || TX: StataCorp, 2013
|| 21. Lusignan S, Gallagher H, Jones S et al. Audit-based education lowers systolic
||
|| blood pressure in chronic kidney disease: the Quality Improvement in CKD
|| (QICKD) trial results. Kidney Int 2013; 84: 609–620
CONFLICT OF INTEREST STATEMENT || 22. Drawz PE, Miller RT, Singh S et al. Impact of a chronic kidney disease regis-
|| try and provider education on guideline adherence – a cluster randomized
None declared.
||
|| controlled trial. BMC Med Inform Decis Mak 2012; 12: 62
|| 23. Cortes-Sanabria L, Cabrera-Pivaral CE, Cueto-Manzano AM et al.
|| Improving care of patients with diabetes and CKD: a pilot study for a
||| cluster-randomized trial. Am J Kidney Dis 2008; 51: 777–788
REFERENCES || 24. Abdel-Kader K, Fischer GS, Li J et al. Automated clinical reminders for pri-
||
1. Levey AS, Atkins R, Coresh J et al. Chronic kidney disease as a global || mary care providers in the care of CKD: a small cluster-randomized con-
public health problem: approaches and initiatives – a position statement || trolled trial. Am J Kidney Dis 2011; 58: 894–902
from Kidney Disease Improving Global Outcomes. Kidney Int 2007; 72:
|| 25. Abdel-Kader K, Greer RC, Boulware LE et al. Primary care physicians’
|| familiarity, beliefs, and perceived barriers to practice guidelines in nondia-
247–259 ||
2. Arora P, Vasa P, Brenner D et al. Prevalence estimates of chronic kidney dis- || betic CKD: a survey study. BMC Nephrol 2014; 15: 64
ease in Canada: results of a nationally representative survey. CMAJ 2013; || 26. Fox CH, Brooks A, Zayas LE et al. Primary care physicians’ knowledge and
185: E417–E423
|| practice patterns in the treatment of chronic kidney disease: an Upstate New
|| York Practice-based Research Network (UNYNET) study. J Am Board Fam
3. Tonelli M, Wiebe N, Culleton B et al. Chronic kidney disease and mortality ||
risk: a systematic review. J Am Soc Nephrol 2006; 17: 2034–2047 || Med 2006; 19: 54–61
4. Group KDIGOKCW. KDIGO 2012 clinical practice guideline for the evalua- || 27. Boulware LE, Troll MU, Jaar BG et al. Identification and referral of patients
tion and management of chronic kidney disease. Kidney Int Suppl 2013; 3:
|| with progressive CKD: a national study. Am J Kidney Dis 2006; 48: 192–204
|| 28. Shojania KG, Ranji SR, McDonald KM et al. Effects of quality improvement
1–150 ||
5. Group KDIGOKLW. KDIGO clinical practice guideline for lipid manage- || strategies for type 2 diabetes on glycemic control: a meta-regression analysis.
ment in chronic kidney disease. Kidney Int Suppl 2013; 3: 259–305 || JAMA 2006; 296: 427–440
6. Group KDIGOKBPW. KDIGO clinical practice guideline for the manage-
|| 29. Coresh J, Byrd-Holt D, Astor BC et al. Chronic kidney disease awareness,
||
ment of blood pressure in chronic kidney disease. Kidney Int Suppl 2012; 2: || prevalence, and trends among US adults, 1999 to 2000. J Am Soc Nephrol
337–414 || 2005; 16: 180–188
7. Group KDIGOKC-MW. KDIGO clinical practice guideline for the || 30. Kawamoto K, Houlihan CA, Balas EA et al. Improving clinical practice
|| using clinical decision support systems: a systematic review of trials to iden-
diagnosis, evaluation, prevention, and treatment of chronic kidney disease- ||
mineral and bone disorder (CKD-MBD). Kidney Int 2009; 76(Suppl 113): || tify features critical to success. BMJ 2005; 330: 765
S1–S130 || 31. Renders CM, Valk GD, Griffin S et al. Interventions to improve the manage-
8. Group KDIGOKAW. KDIGO clinical practice guideline for anemia in
|| ment of diabetes mellitus in primary care, outpatient and community set-
|| tings. Cochrane Database Syst Rev 2001: CD001481
chronic kidney disease. Kidney Int Suppl 2012; 2: 279–335 ||
9. Arenas MD, Alvarez-Ude F, Torregrosa V et al. Consequences of the imple- || 32. Fox CH, Swanson A, Kahn LS et al. Improving chronic kidney disease
mentation of K/DOQI clinical practice guidelines for bone metabolism and || care in primary care practices: an upstate New York practice-based
disease in chronic kidney disease in a population of patients on chronic
|| research network (UNYNET) study. J Am Board Fam Med 2008; 21:
|| 522–530
hemodialysis. J Nephrol 2007; 20: 453–461 ||
10. US Renal Data System. USRDS 2010 annual data report: atlas of chronic || 33. Humphreys J, Harvey G, Coleiro M et al. A collaborative project to improve
kidney disease and end-stage renal disease in the United States. Am J Kidney || identification and management of patients with chronic kidney disease in a
Dis 2011; 57: e1–e526
|| primary care setting in Greater Manchester. BMJ Qual Saf 2012; 21:
|| 700–708
11. Pimouguet C, Le Goff M, Thiebaut R et al. Effectiveness of disease- ||
management programs for improving diabetes care: a meta-analysis. CMAJ || 34. Richards N, Harris K, Whitfield M et al. Primary care-based disease man-
2011; 183: E115–E127 || agement of chronic kidney disease (CKD), based on estimated glomerular
12. Ronksley PE, Hemmelgarn BR. Optimizing care for patients with CKD. Am
|| filtration rate (eGFR) reporting, improves patient outcomes. Nephrol Dial
||
J Kidney Dis 2012; 60: 133–138 || Transplant 2008; 23: 549–555
13. Wentworth AL, Fox CH, Kahn LS et al. Two years after a quality improve- || 35. Rich MW, Beckham V, Wittenberg C et al. A multidisciplinary intervention
ment intervention for chronic kidney disease care in a primary care office. || to prevent the readmission of elderly patients with congestive heart failure.
|| N Engl J Med 1995; 333: 1190–1195
Am J Med Qual 2011; 26: 200–205 ||
14. Manns B, Tonelli M, Culleton B et al. A cluster randomized trial of an || 36. Rich MW, Vinson JM, Sperry JC et al. Prevention of readmission in elderly
enhanced eGFR prompt in chronic kidney disease. Clin J Am Soc Nephrol || patients with congestive heart failure: results of a prospective, randomized
2012; 7: 565–572
|| pilot study. J Gen Intern Med 1993; 8: 585–590
||
||
||

120 L. Galbraith et al.

37. Rea H, McAuley S, Stewart A et al. A chronic disease management pro- || 39. Lorig KR, Sobel DS, Stewart AL et al. Evidence suggesting that a chronic dis-
gramme can reduce days in hospital for patients with chronic obstructive || ease self-management program can improve health status while reducing
pulmonary disease. Intern Med J 2004; 34: 608–614 || hospitalization—a randomized trial. Med Care 1999; 37: 5–14
38. Lorig KR, Ritter P, Stewart AL et al. Chronic disease self-management pro- ||
gram—2-year health status and health care utilization outcomes. Med Care
||
|| Received: 7.2.2016; Editorial decision: 8.9.2016
2001; 39: 1217–1223 ||
||
|

Nephrol Dial Transplant (2018) 33: 121–128

doi: 10.1093/ndt/gfw366
Advance Access publication 27 October 2016

eMAP:CKD: electronic diagnosis and management assistance

to primary care in chronic kidney disease
Aspasia Pefanis1, Roslin Botlero2,3, Robyn G. Langham4 and Craig L. Nelson1,3,5,6
1
Department of Nephrology, Western Health, Melbourne, VIC, Australia, 2School of Public Health, Department of Medicine, Monash
University, Clayton, VIC, Australia, 3North West Academic Centre, The University of Melbourne, Melbourne, VIC, Australia, 4Monash Rural
Health, Monash University, Clayton, VIC, Australia, 5Sunshine Hospital, 176 Furlong Road, St Albans, VIC, Australia and 6Western Chronic
Disease Alliance, Sunshine Hospital, 176 Furlong Road, St Albans, VIC, Australia

Correspondence and offprint requests to: Craig L. Nelson; E-mail: craig.nelson@wh.org.au

Conclusion. The eMAP:CKD program has shown an improve-

ABSTRACT || ment in identification of patients at risk of CKD, appropriate
||
|| testing and management of these patients, as well as increased
Background. The increasing burden of chronic kidney disease || documentation of CKD diagnosis entered into the EHRs. We
(CKD) underpins the importance for improved early detection ||
|| have demonstrated efficacy in overcoming the verified gap
and management programs in primary care to delay disease || between current and best practice in primary care. The success
progression and reduce mortality rates. eMAP:CKD is a pilot ||
|| of the pilot program has encouraging implications for use across
program for primary care aimed at addressing the gap between || the primary care community as a whole.
current and best practice care for CKD. ||
||
Methods. Customized software programs were developed to || Keywords: chronic kidney disease, e-health, electronic health
integrate with primary care electronic health records (EHRs), || record, primary care, technology
||
allowing real-time prompting for CKD risk factor identification, ||
testing, diagnosis and management according to Kidney Health ||
||
Australia’s (KHA) best practice recommendations. Primary || INTRODUCTION
care practices also received support from a visiting CKD nurse
||
||
and education modules. Patient data were analyzed at baseline || The incidence and prevalence of chronic kidney disease (CKD)
(150 910 patients) and at 15 months (175 917 patients) follow-
|| is a growing public health concern [1]. It is reported that 1.7
||
ing the implementation of the program across 21 primary care || million (10%) Australian adults have indicators of CKD, with
practices.
|| only 103 700 (0.61%) Australians self-reported as having CKD,
||
Results. There was improvement in CKD risk factor recogni- || indicating a poor awareness of CKD [2]. One in three
|| Australian individuals has a risk factor for CKD and 16% of the
tion (29.40 versus 33.84%; P < 0.001) and more complete kid- ||
ney health tests were performed (3.20 versus 4.30%; P < 0.001). || Australian population have indicators of kidney damage [3].
||
There were more CKD diagnoses entered into the EHR (0.48 || The incidence of CKD in Australia is higher than that of diabe-
versus 1.55%; P < 0.001) and more patients achieved KHA’s || tes (5.1%) [2], with CKD being a stronger predictor of cardio-
||
recommended management targets (P < 0.001). || vascular disease (CVD) [4]. The high prevalence of CKD is
||
||
||
C The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA.
||
V
This is an Open Access article distributed under the terms of the Creative Commons
|
Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/
4.0/), which permits non-commercial re-use, distribution, and reproduction in any
medium, provided the original work is properly cited. For commercial re-use, please 121
contact journals.permissions@oup.com