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. 2025 Sep 4;15(9):e102044. doi: 10.1136/bmjopen-2025-102044

Quality of care for people with chronic kidney disease: a systematic review and meta-analysis

Daniel Bekele Ketema 1,2,3, Hannah Wallace 1,4,5, Workagegnehu Hailu 6, Sunil V Badve 1,2,7, Paul Ronksley 8, Brendon L Neuen 1,2,9,10, Roberto Pecoits-Filho 11,12, Martin Gallagher 1,13, Sradha Kotwal 1,14, Vlado Perkovic 1,2, Rohina Joshi 15,16, Min Jun 1,2,✉
PMCID: PMC12414227  PMID: 40908011

Abstract

Abstract

Objectives

Guideline-based strategies to prevent chronic kidney disease (CKD) progression and complications are available, yet their implementation in clinical practice is uncertain. We aimed to synthesise the available evidence on the concordance of CKD care with clinical guidelines to identify gaps and inform future CKD care.

Design

Systematic review and meta-analysis.

Data sources, participants, and outcomes

We systematically searched MEDLINE (OVID), EMBASE (OVID) and CINAHL (EBSCOhost) (to 18 July 2025) for observational studies of adults with CKD reporting data on the quality of CKD care. We assessed data on quality indicators of CKD care across domains that related to patient monitoring (glomerular filtration rate and albuminuria), medications use (ACE inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), statins) and treatment targets (blood pressure (BP) and HbA1c). Pooled estimates (95% CI) of the percentage of patients who met the quality indicators for CKD care were estimated using random effects model.

Results

59 studies across 24 countries, including a total of 3 003 641 patients with CKD, were included. Across studies, 81.3% (95% CI: 75% to 87.6%) of patients received eGFR monitoring, 47.4% (95% CI: 40.0% to 54.7%) had albuminuria testing, and 90% (95% CI: 84.3% to 95.9%) had BP measured. ACEIs/ARBs were prescribed among 56.7% (95% CI: 51.5% to 62%), and statins among 56.6% (95% CI: 48.9% to 64.3%) of patients. BP (systolic BP ≤140/90 mm Hg) and HbA1c (<7%) targets were achieved in 56.5% (95% CI: 48.5% to 64.6%) and 43.5% (95% CI: 39.4% to 47.6%) of patients, respectively. Subgroup analysis indicated higher rates of proteinuria testing among patients with diabetes (52.2%) compared with those without (31.3%).

Conclusions

Current evidence shows substantial variation in CKD care quality globally. Guideline-concordant care varied according to quality measures and across patient groups, with gaps in indicators like albuminuria testing. These findings underscore the need for effective quality improvement strategies to address gaps in CKD care, including increased albuminuria testing for risk stratification, together with systematic measures for monitoring care quality.

PROSPERO registration number

CRD42023391749.

Keywords: Systematic Review, Meta-Analysis, Quality Improvement , Chronic kidney disease

STRENGTHS AND LIMITATIONS OF THIS STUDY.

  • Comprehensive search strategy identified 59 studies involving over 3 million patients across 24 countries.

  • Multiple domains of chronic kidney disease care were systematically synthesised to assess concordance with clinical guidelines.

  • The data were derived from a relatively small number of jurisdictions, primarily in high-income countries, which may limit the generalisability of the findings to low-income settings.

  • Methodological heterogeneity and variation in indicator definitions limit the pooling of some outcomes.

Introduction

Chronic kidney disease (CKD) is a major global public health issue.1 2 Globally, an estimated 850 million people have CKD,3 accounting for 10% of the global population and expected to be the fifth-leading cause of death worldwide by 2040.4 5 Effective, evidence-based strategies such as controlling blood pressure (BP), reducing albuminuria and implementing screening and risk stratification6 are available to slow the progression of CKD and prevent complications. Optimising the implementation of these effective CKD management strategies is essential for achieving improvements in patient outcomes,6 7 which can also help to reduce healthcare costs by preventing complications and hospitalisations.8 9

However, several individual reports suggest substantial gaps between guideline-recommended CKD care and the care actually received.310,16 For instance, a study involving 14 618 patients in Switzerland found that only 18% had undergone proteinuria measurement,12 while a study in Canada showed that 30.5% of patients with CKD received ACE inhibitors or angiotensin receptor blockers (ACEIs/ARBs).15 These studies also indicate considerable variability in jurisdictional coverage, quality measures assessed and how these measures were defined, making it difficult to determine the full nature and extent of any practice gaps. We, therefore, performed a systematic review to synthesise the available evidence on the extent to which CKD care is consistent with clinical practice guidelines to identify any gaps in care and inform future strategies for improving CKD care.

Methods

Search strategy

We conducted a systematic review of the literature according to the Meta-analysis of Observational Studies in Epidemiology group consensus statement17 (PROSPERO registration: CRD42023391749). Relevant studies were identified through a systematic search of MEDLINE (OVID), EMBASE (OVID) and CINAHL (EBSCOhost) (inception to 18 July 2025, no language restrictions). The Coco Pop (Co=Condition, Co=Context, Pop=Population) framework18 was used to develop the search strategy using a combination of medical subject headings and text words related to CKD and quality of care. The search terms included “chronic kidney failure”, “renal insufficiency”, “quality of care,” “quality of CKD care” and “health care quality of care.” The complete search strategies for MEDLINE (OVID), EMBASE (OVID) and CINAHL(EBSCOhost) are provided in online supplemental table S1–S3, respectively. Reference lists of included studies were manually reviewed for any eligible studies.

Study selection

All observational studies on adults (≥18 years) and reporting data on the quality of CKD care were eligible for inclusion. CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or the presence of albuminuria lasting more than 3 months according to the Kidney Disease Improving Global Outcomes (KDIGO) Clinical Practice Guidelines19 (or as defined by authors). Two authors (DBK and HW) independently conducted the literature search including title and abstract screening performed using Covidence.20 Agreement between the two reviewers regarding the inclusion of eligible studies was calculated using the kappa statistic.21 Any disagreements in abstract screening were resolved through discussion involving a third reviewer (MJ). In the second step of screening, the full texts of the selected articles from step 1 were retrieved and independently assessed by two reviewers (DBK and HW) against the inclusion criteria. Any discrepancies were resolved through discussion and consensus, which was mediated by a third reviewer (MJ).

Data extraction and quality assessment

Two authors (DBK and HW) independently conducted data extraction using a standardised data extraction spreadsheet. Information sought included study characteristics (publication year, study design and size, geographical location, study duration and nature of the data source(s) used to assess quality of CKD care), patient characteristics (age, sex and comorbidities) and outcome data (definitions described below). The study quality was appraised independently by two reviewers (DBK and HW) using a modified Newcastle-Ottawa Quality Assessment Scale.22 Risk of bias was assessed across the domains of representativeness of the study sample (all patients with CKD vs subpopulations of CKD such as those with comorbid diabetes mellitus), study size (median study size: <7740 vs ≥7740 individuals), method of CKD status ascertainment (eGFR and/or urine albumin-creatinine ratio (UACR) based vs diagnosis codes), comparability (controlled for differences in patient characteristics vs no adjustments), outcomes ascertainment, study follow-up (<12 vs ≥12 months),23 and use of statistical testing, as per the Newcastle-Ottawa Scale (eg, appropriate reporting of statistical methods). For each study, 1 point was given for each domain when the criteria requirement was met (for a maximum of 7 points). Low, moderate and high risk of bias was defined as 6–7, 4–5 and 1–3 points, respectively.24 Any disagreement in abstracted data or quality assessment was resolved by a third reviewer (MJ).

Outcomes

We collected data on quality indicators of CKD care across domains that related to patient monitoring (measurement of serum creatinine, eGFR, proteinuria (UACR, urine protein-creatinine ratio (UPCR); 24-hour urine protein excretion), HbA1c, BP and other laboratory tests), appropriate use of medications (ACEIs/ARBs, statins, not taking non-steroidal anti-inflammatory drugs (NSAIDs)) and achievement of treatment targets (BP ≤140/90 mm Hg or ≤130/80 mm Hg; HbA1c <7%). Quality measures for CKD care, including the timing of measurements related to patient monitoring, were based on management recommendations in international CKD clinical practice guidelines (KDIGO)19 and as defined by the included studies.

Data synthesis and analysis

The percentage of patients with CKD with 95% CIs) who met the definition for the quality indicators was calculated for each eligible study. Proportions were logit-transformed and pooled using random-effects meta-analysis with the DerSimonian and Laird method. The analysis was performed using the metaprop function from the meta package in R (V.8.1.0),25 applying the DerSimonian and Laird method.26 To assess the potential range of true effects in future studies, we computed a 95% prediction interval (PI), which accounts for the pooled proportion estimate, between-study variance (τ²) and the SE of the pooled estimate.27 To account for potential duplication of patient outcome data arising from the use of identical data sources or overlapping geographical and/or jurisdictional coverage across the included studies, we conducted two separate analyses. In the primary analysis, within each country of the included studies, data derived from nationally representative data sources or multiple jurisdictions (hereinafter referred to as ‘national level’ data) were prioritised where available. Specifically, if both national-level and data derived from single jurisdictions or sites (hereinafter referred to as ‘regional-level’ data) were available, the national-level data were included and the corresponding regional-level data were excluded in this analysis. In the absence of national-level data within each country, regional-level data were included where available. In sensitivity analysis, we repeated all analyses using regional-level data. In both the primary and sensitivity analyses, if there were multiple studies within the same jurisdiction reporting outcome data derived from the same data source, the most recent data were included (defined as the latest end date of the assessed study periods of the included studies). Where data could not be combined quantitatively using meta-analysis (due to substantial differences in data reporting including outcome definitions), a narrative synthesis approach was used to descriptively summarise the study findings.

To assess the percentage of variability across the included studies attributable to heterogeneity beyond chance for each of the quality indicators, I2 statistic was used.28 To explore potential sources of heterogeneity, subgroup analysis by diabetes status was conducted. Moreover, to assess the impact of major CKD guidelines released during the period covered by the included studies (2012 KDIGO Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease)19 on quality indicators of CKD care, we conducted subgroup analysis based on the timing of the studies relative to the release of the 2012 KDIGO guidelines (studies were categorised as pre-2012 or post-2012 based on the first year of the study cohort for each included study). Univariable meta-regression was also performed using the metafor package in R to examine the effect of study-level characteristics (including mean age, study period, cohort size and the proportion of patients with diabetes or hypertension) on pooled estimates. Moreover, a leave-one-out sensitivity analysis was conducted to assess the influence of individual studies. Potential for publication bias was assessed using the Egger’s test and graphically presented using funnel plots.

Funding

This work received no specific funding.

Patient and public involvement

None.

Results

Search results and characteristics of the studies

The literature search identified 3591 articles, of which 89 were selected for full-text review (figure 1). Among these, 59 studies met the inclusion criteria, including a total of 3 003 641 patients (median: 7740 patients) with CKD across 24 countries: 23 studies in the USA,1429,50 7 in Canada,1315 51,55 5 in the UK,56,60 3 in Italy,61,63 3 in Australia,64,66 3 in Taiwan,11 67 68 2 in Germany,69 70 2 in the Netherlands71 72 and 1 study each in Japan,73 Brazil,74 Singapore,75 Switzerland,12 Thailand,76 Israel77 and South Africa.78 In addition, four studies assessed data from multiple countries.10 16 79 80 The key characteristics of included studies are summarised in online supplemental table S4 and S5. Most studies (86%) were conducted in high-income countries (online supplemental figure S1).

Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart.

Figure 1

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47 studies (79%) were longitudinal, while the rest were cross-sectional. Most studies (82.7%) were published between 2010 and 2022. Overall, 52% of patients were women and the mean age of the included patient populations ranged between 51.2 and 75.9 years. The proportion of patients with comorbid diabetes (median (interquartile interval (IQI): 36.8% (27.1%–68.3%)) and hypertension (median (IQI): 80% (63%–90%)) varied widely across the studies (online supplemental table S4).

Quality assessment

Of the 59 included studies, 31 (54%) had a low risk of bias, 21 (35%) had a moderate risk of bias and 7 (12%) had a considerable risk of bias. The most common areas where studies performed poorly were related to representativeness, ascertainment of exposure and follow-up (online supplemental table S6).

Quality of CKD care

Patient monitoring

eGFR and albuminuria/proteinuria measurement

A total of 11 studies11 12 15 30 31 38 42 55 66 70 72 reported data on the proportion of patients who received eGFR monitoring, of which 9 (n=98 414 patients) were included in the meta-analysis. The frequency of eGFR monitoring was defined variably across the included studies (up to 24 months following the last measurement). Overall, the pooled percentage of patients with CKD who had their eGFR monitored was 81.3% (95% CI: 75% to 87.6%; figure 2), which varied significantly across these studies (I2=99%; 95% PI=58% to 100%; online supplemental figure S2).

Figure 2. Forest plot summarising the proportion of patients meeting the monitoring, medication use and treatment target quality indicators of CKD management. SCr, serum creatinine; ACEIs, ACE inhibitors; ARBs, angiotensin receptor blockers; BP, blood pressure; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; NSAIDs, non-steroidal anti-inflammatory drugs; PTH, parathyroid hormone; HbA1c, hemoglobin A1c.

Figure 2

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A total of 33 studies11,1629 reported data on albuminuria testing. Of these, 17 studies reported on UACR and/or UPCR measurement. Other studies included various combinations of 24-hour UACR, UPCR, spot urine proteinuria and dipstick testing. Definitions of the frequency of albuminuria testing varied (up to 24 months following the last measurement). From 33 studies, 12 (n=1 903 286) were included in the meta-analysis. Overall, the pooled percentage of patients who received albuminuria testing was 47.4% (95% CI: 40% to 54.7%; figure 2), which varied widely across the studies (I2=99%; 95% PI: 15% to 79%; online supplemental figure S3). Subgroup analysis showed that albuminuria testing was higher among patients with comorbid diabetes (figure 3; I2=99%; online supplemental figure S4 and S5).

Figure 3. Forest plot of the proportion of patients with CKD meeting albuminuria monitoring and ACEIs/ARBs use criteria, stratified by diabetes status. ACEIs, ACE inhibitors; ARBs, angiotensin receptor blockers; CKD, chronic kidney disease.

Figure 3

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HbA1c assessment

11 studies11 14 15 29 38 40 42 58 60 76 77 reported the proportion of patients with CKD with diabetes who had hemoglobin A1c (HbA1c) monitored over a period of up to 2 years. Of these, seven studies (n=317 510 patients) were included in the meta-analysis. HbA1c testing rates varied widely (I²=99%; 95% PI: 0% to 100%; online supplemental figure S6) with a pooled percentage of 61.7% (95% CI: 43.3% to 80.1%; figure 2).

Other laboratory assessments

A total of 14 studies1115 29 31 37,39 42 50 58 70 reported data on parathyroid hormone (PTH) testing in patients with CKD for the assessment of mineral and bone health and 10 studies (n=74 468) were included in the meta-analysis. The overall pooled percentage of CKD patients who received serum PTH testing was 16.9% (95% CI: 11.8% to 22.1%; I2=99%; 95% PI: 0% to 36% figure 2; online supplemental figure S7). In addition, a population-based study (n=1778) conducted in Germany reported that serum calcium and phosphate were assessed in 19.5% and 3.7% of patients with CKD, respectively.60

BP measurement

10 studies12 15 16 34 50 60 66 69 72 77 provided data on BP measurements in patients with CKD. The overall pooled percentage of patients who had ≥1 BP measurement was 90.1% (95% CI: 84.3% to 95.9%; 7 studies, 103 747 patients; figure 2; I2=99%; 95% PI: 68% to 100%; online supplemental figure S8). Furthermore, three studies (n=60 405) indicated that BP assessment was more commonly performed in patients with comorbid diabetes or hypertension.15 60 72

Appropriate use of medications

ACEIs/ARBs use

A total of 47 studies provided information on patterns of ACEIs/ARBs use, with 18 studies (n=562 148) included in the meta-analysis. The overall pooled percentage of ACEIs/ARBs prescription among patients with CKD was 56.7% (95% CI: 51.6% to 62.0%, figure 2) but varied widely (I2=99%; 95% PI: 29% to 85%; online supplemental figure S9). In subgroup analysis, ACEIs/ARBs prescription rate in patients with comorbid diabetes did not significantly differ when compared with those without diabetes (diabetes vs no diabetes: 51.6% (95% CI: 37.8% to 65.3%) and 56% (95% CI: 41% to 71.1%), respectively; figure 3, online supplemental figure S10 and S11).

Two studies (n=17 985) reported data on the trends in ACEIs/ARBs use over time. A cohort study in Taiwan reported that the ACEIs/ARBs use increased from 51.1% in 1997 to 65% in 2003.11 Another study (n=10 245) conducted in Singapore75 showed increases in ACEIs/ARBs use from 78% in 2007 to 84% in 2011. On the other hand, a cross-sectional study of 159 357 patients conducted in the USA on trends in CKD care delivery by race and ethnicity from 2012 to 2019 showed there was a decrease in ACEI/ARBs use.48

Statin use

29 studies reported statin use, with 15 studies (n=837 885) included in the meta-analysis. The pooled statin use rate was 56.6% (95% CI: 48.9% to 64.4%; figure 2), varying widely across studies (I²=99%; 95% PI: 19% to 94%; online supplemental figure S12). A retrospective cohort study in Singapore (n=10 245)75 reported an increasing trend in statin prescription rates, rising from 81% in 2007 to 87.1% in 2011.

Not taking NSAIDs

14 studies (n=1 887 984)1229 31 33 47,49 51 55 57 60 72 73 78 provided evidence regarding the avoidance of long-term NSAIDs use in patients with CKD, of which eight studies (n=1 222 585) were included in the meta-analysis. The pooled percentage of patients who were not taking NSAIDs was 82.1% (95% CI: 77.4% to 86.7%; figure 2, I²=99%; 95% PI: 65% to 99%; online supplemental figure S13).

Treatment target achievement

BP control

31 studies provided data on the BP management among patients with CKD1012 14,16 30 31 35 40 42 and 11 studies (n=744 781)12 15 16 40 48 59 61 63 65 67 69 72 were included in the meta-analysis for the BP target of ≤140/90 mm Hg, and 14 (n=485 753) for the target of ≤130/80 mm Hg. The pooled percentage of patients who achieved a BP target of ≤140/90 mm Hg was 56.6% (95% CI: 48.5% to 64.6%) and varied widely among studies (I2=99%; 95% PI: 22% to 91%; online supplemental figure S14). The pooled percentage of those who met a BP target of ≤130/80 mm Hg was 35.2% (95% CI: 29.9% to 40.5%; figure 2; I2=99%; 95% PI: 8% to 62%; online supplemental figure S15). An international Network CKD study (17 cohorts, n=34 602) showed that the percentage of patients who achieved BP ≤140/90 mm Hg and ≤130/80 mm Hg ranged between 39% and 72% and 16%–46%,80 respectively.

Glycaemic control

A total of 12 studies1031 44 48 51 58 61 67 71 75,77 reported data on the proportion of patients with an HbA1c target <7%. Overall, the pooled percentage of patients with CKD who achieved the HbA1c target of <7% was 43.5% (95% CI: 39.5% to 47.6%; 11 studies, n=130 847; figure 2; I2=99%; 95% PI: 25% to 62%; online supplemental figure S16). A study conducted in Germany69 reported a mean HbA1c value of 6.5%±1%, while a study conducted in the USA45 found that 50% of patients with CKD with diabetes had HbA1c below 7%.

Subgroup analysis and meta-regression

Studies in the post-2012 group, compared with those in the pre-2012 group, showed numerically higher proportions of patients achieving target BP (BP ≤140/90: 60% (95% CI: 52% to 67%) vs 48% (95% CI: 16% to 81%), respectively) and receiving ACEi (61% (95% CI: 56% to 66%) vs 51% (95% CI: 40% to 63%), respectively) and statins (57% (95% CI: 45% to 64%) vs 52% (95% CI: 38% to 67%), respectively). However, these differences were not statistically significant (online supplemental figure S17–S20). In the univariable meta regression, study and patient level characteristics such as the proportion of patients with hypertension, diabetes and study sample size were significantly associated with several indicators (online supplemental table S7).

Sensitivity analysis

The overall findings remained unchanged when analyses were repeated using regional-level data (online supplemental figure S21–S32). In addition, in the leave-one-out analysis, the overall results remained stable across iterations for most of the outcomes (online supplemental figure S33–S38)

Publication bias

There was evidence of publication bias (p<0.05) for the quality indicators of albuminuria testing (online supplemental figure S39), ACEIs/ARBs use (online supplemental figure S40), statin prescribing (online supplemental figure S41) and BP targets (online supplemental figure S42). Overall findings remained similar after adjustment for publication bias using the trim-and-fill method.81

Discussion

Findings from this systematic review indicate substantial variation in guideline-concordant care across different quality measures, CKD patient profiles and healthcare settings. For instance, most patients with CKD received eGFR and BP monitoring, while albuminuria assessment was substantially lower. Approximately half of patients with CKD were prescribed ACEIs/ARBs, half received statins and NSAIDs were withheld in most patients. Overall, a BP target of ≤140/90 mm Hg was achieved in approximately half of patients with CKD, while 43% of patients with comorbid diabetes achieved the HbA1c target <7%.

Individual reports of evidence-practice gaps in CKD care to date have mostly focused on specific care domains (eg, ACEIs/ARBs use) or jurisdictions. Our findings, based on a holistic assessment of the quality of CKD care across multiple domains of clinical management and geographical regions, provide important insights into the contemporary state of CKD care and priority areas of focus for improving the quality of CKD care globally. First, our findings identify substantial variation in the concordance of CKD care with guideline recommendations, which is most evident in albuminuria testing for monitoring disease progression. Guidelines recommend annual UACR testing in patients with type 2 diabetes, and more frequent assessments in higher risk patient groups including those with moderate-to-advanced stages of CKD.6 82 However, we observed that even among patients with comorbid CKD and diabetes, albuminuria testing was lacking in >40% of patients. Absence of UACR testing, especially among high-risk groups, has significant prognostic implications given that decisions to initiate or intensify relevant guideline-recommended treatment options are contingent on optimal albuminuria testing. Indeed, a recent study showed that lack of UACR testing is associated with lower odds of ACEIs/ARBs and sodium-glucose cotransporter-2 inhibitors (SGLT2i) use.83 A recent Global Kidney Atlas report highlighted that lack of reimbursement remains an important barrier to CKD care, even in developed countries.7 Prioritising initiatives that strengthen reimbursement may help to increase routine UACR testing.

On the other hand, we observed reassuring findings including high rates of BP and eGFR monitoring (and to a lesser extent HbA1c monitoring) in patients with CKD, and that most patients were not prescribed NSAIDs for extended use. However, our findings also show a disconnect between monitoring of clinical parameters and indicators of treatment including use of guideline-recommended medications, such that overall, 43% of patients were not prescribed ACEIs/ARBs, while 43% and 56% did not achieve BP and HbA1c treatment targets. Of note, there was significant variability in the prescribing of ACEIs/ARBs and statins, as well as the extent to which BP targets were achieved across the studies. Indeed, our overall assessment of the use of ACEIs/ARBs and statins did not identify any consistent trends in the prescribing of these medications over time, with some data showing conflicting findings. For example, studies in Taiwan11 and Singapore show increases in ACEIs/ARBs use, while in the USA, data indicate a decreasing trend.75 Such differences may be attributed to variations in a range of patient, clinician and health system-level barriers including awareness of CKD and clinical practice guidelines,84 suboptimal medication adherence and fragmentation of health services relevant to the care of complex patient populations.16 84 Our subgroup analysis based on the timing of studies relative to release of KDIGO 2012 did not identify evidence of significant improvements in BP control and use of recommended medications including ACEIs/ARBs following the publication of the guidelines. Taken together, these findings suggest that the aforementioned barriers continue to persist in contemporary settings of CKD care.

With the emergence of newer effective guideline-recommended agents such as SGLT2i and glucagon-like peptide-1 receptor agonists, understanding and addressing these barriers will be particularly important so that these effective strategies are optimally implemented. Of note, of all the studies we reviewed, only four of them reported information on SGLT2i use.34 44 49 67 These studies revealed that SGLT2i usage was more prevalent among diabetic CKD patients compared with the overall CKD patient population, ranging from <1.5%34 49 to 20%.44 67 However, because most studies predated the period when SGLT2i use was recommended, it is difficult to draw conclusions on the extent of their use in routine clinical practice in this review. Further investigations on SGLT2 use and other newer agents in patients with CKD will be important.

Another key finding from our study is the variation in the reporting of data on the quality of CKD care in terms of the quality indicators considered and geographical coverage. In particular, we observed considerable evidence gaps in the patterns of CKD management in low-income and middle-income countries. Standardised approaches for assessing and monitoring CKD care across broad clinical and geographical settings (including low-income and middle-income countries) are needed to inform the development of quality improvement strategies.

To the best of our knowledge, this systematic review is the first study to comprehensively consolidate evidence on the extent to which current CKD care is concordant with clinical guidelines. However, our review has limitations, mostly because of the availability of data (with limited data on some care domains including lifestyle modifications) and the variability in the nature of the included studies (including differences in the patient populations assessed and reported quality indicators and their definitions). We sought to summarise findings of studies on the quality of care of patients with established CKD, and most of the included studies assessed individuals with moderate-to-advanced CKD. As such, we are unable to assess the concordance of CKD care with clinical guidelines relative to the detection of CKD or patients with early-stage CKD. While the review encompasses data from >3 million patients with CKD across 24 countries, much of the data were derived from a relatively small number of jurisdictions mostly from high-income countries, the quality of CKD care in regions where data are lacking remains uncertain.

Conclusions

In conclusion, currently available evidence indicates substantial variation in the reporting and quality of CKD care. Care quality varied according to quality measures and across different patient groups, with opportunities for considerable improvement in several indicators, especially albuminuria testing. These findings underscore the need for effective quality improvement strategies to address gaps in CKD care, including increased albuminuria testing for risk stratification, together with systematic measures for monitoring care quality.

Supplementary material

online supplemental file 1
bmjopen-15-9-s001.pdf (3.6MB, pdf)
DOI: 10.1136/bmjopen-2025-102044

Acknowledgements

DBK was supported by Tuition Fee Scholarship from UNSW Sydney. MJ is supported by the Scientia Programme at the Faculty of Medicine and Health, UNSW Sydney, Australia.

Footnotes

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-102044).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Map disclaimer: The depiction of boundaries on this map does not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. This map is provided without any warranty of any kind, either express or implied.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Presented at: Key findings from this research were presented as an abstract at the American Society of Nephrology Kidney Week 2024 international conference, San Diego, California, USA.

Ethics approval: This study is a systematic review and meta-analysis of previously published data. Therefore, this work was not reviewed by an ethics committee.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

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    Supplementary Materials

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    DOI: 10.1136/bmjopen-2025-102044

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