Evidence map›Paper›PMID 38435072›Full record

ArticleKidney medicine2024

A CKD Clinical Decision Support System: A Cluster Randomized Clinical Trial in Primary Care Clinics.

JoAnn Sperl-Hillen, A Lauren Crain, James B Wetmore, Lilian N Chumba, Patrick J O'Connor

Registry-linked trialAbstract read
In one paragraph

Article in Kidney medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03890588 (A Technology-Driven Intervention to Improve Identification and Management of Chronic Kidney Disease in Primary Care), which is not on this map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03890588 nacompletednot on this map

A Technology-Driven Intervention to Improve Identification and Management of Chronic Kidney Disease in Primary Care

TypeinterventionalSponsorHealthPartners InstituteRan2019 to 2021Enrolled6,295ConditionsChronic Kidney Diseases, Hypertension, DiabetesArmsCKD enhanced clinical decision support
3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

JoAnn Sperl-HillenHealthPartners Institute, Minneapolis, Minnesota.
A Lauren CrainHealthPartners Institute, Minneapolis, Minnesota.
James B WetmoreDivision of Nephrology, Hennepin Healthcare; Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, MN.
Lilian N ChumbaHealthPartners Institute, Minneapolis, Minnesota.
Patrick J O'ConnorHealthPartners Institute, Minneapolis, Minnesota.

Funding

A Technology-Driven Intervention to Improve Identification and Management of Chronic Kidney Disease in Primary CareR18DK118463 · NIDDK · HEALTHPARTNERS INSTITUTE · PI SPERL-HILLEN, JOANN M · 2018 to 2020
$1.5M
NIDDK NIH HHS R18 DK118463
6 · The paper itself

Abstract

Rationale & Objective: The study aimed to develop, implement, and evaluate a clinical decision support (CDS) system for chronic kidney disease (CKD) in a primary care setting, with the goal of improving CKD care in adults. Study Design: This was a cluster randomized trial. Setting & Participants: A total of 32 Midwestern primary care clinics were randomly assigned to either receive usual care or CKD-CDS intervention. Between April 2019 and March 2020, we enrolled 6,420 patients aged 18-75 years with laboratory-defined glomerular filtration rate categories of CKD Stage G3 and G4, and 1 or more of 6 CKD care gaps: absence of a CKD diagnosis, suboptimal blood pressure or glycated hemoglobin levels, indication for angiotensin-converting enzyme inhibitor or angiotensin receptor blocker but not prescribed, a nonsteroidal anti-inflammatory agent on the active medication list, or indication for a nephrology referral. Intervention: The CKD-CDS provided personalized suggestions for CKD care improvement opportunities directed to both patients and clinicians at primary care encounters. Outcomes: We assessed the proportion of patients meeting each of 6 CKD-CDS quality metrics representing care gap resolution after 18 months. Results: The adjusted proportions of patients meeting quality metrics in CKD-CDS versus usual care were as follows: CKD diagnosis documented (26.6% vs 21.8%; risk ratio [RR], 1.17; 95% CI, 0.91-1.51); angiotensin-converting enzyme inhibitor or angiotensin receptor blocker prescribed (15.9% vs 16.1%; RR, 0.95; 95% CI, 0.76-1.18); blood pressure control (20.4% vs 20.2%; RR, 0.98; 95% CI, 0.84-1.15); glycated hemoglobin level control (21.4% vs 22.1%; RR, 1.00; 95% CI, 0.80-1.24); nonsteroidal anti-inflammatory agent not on the active medication list (51.5% vs 50.4%; RR, 1.03; 95% CI, 0.90-1.17); and referral or visit to a nephrologist (38.7% vs 36.1%; RR, 1.02; 95% CI, 0.79-1.32). Limitations: We encountered an overall reduction in expected primary care encounters and obstacles to point-of-care CKD-CDS utilization because of the coronavirus disease 2019 pandemic. Conclusions: The CKD-CDS intervention did not lead to a significant improvement in CKD quality metrics. The challenges to CDS use during the coronavirus disease 2019 pandemic likely influenced these results. Funding: National Institute of Diabetes and Digestive and Kidney Diseases (R18DK118463). Trial Registration: clinicaltrials.gov Identifier: NCT03890588.

Indexed as

Chronic kidney diseasesclinical decision support systemsCOVID-19 challengesprimary carequality of health carerandomized controlled trials

Identifiers

PMID38435072
PMCPMC10906435

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.