Evidence map›Paper›PMID 41652416›Full record

SynthesisHealth and quality of life outcomes2026

Implementing electronic Patient-Reported Outcome Measures in Chronic Kidney Disease: a qualitative systematic review of barriers, enablers, and mechanisms.

Xutong Zheng, Yuhong Zhang, Liuxuan Xie, Yingshuo Liu, Qiuying Yu, Han Zhang, Yao Li, Aiping Wang

Abstract readSystematic Review
In one paragraph

Synthesis in Health and quality of life outcomes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Xutong ZhengDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.ORCID http://orcid.org/0000-0002-9236-1764
Yuhong ZhangDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Liuxuan XieDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Yingshuo LiuDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Qiuying YuDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Han ZhangDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Yao LiDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China.
Aiping WangDepartment of Public Service, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, China. apwang@cmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis systematic review investigates the barriers, enablers and mechanisms affecting ePROMs implementation in CKD (chronic kidney disease) management, with a focus on the perspectives of patients and healthcare providers.

methodsA qualitative systematic review was conducted using the UK Medical Research Council's Process Evaluation Framework to analyze studies on ePROM implementation in CKD care. We systematically searched databases for peer-reviewed qualitative studies published from inception to October 2025. Thematic analysis, guided by the Process Evaluation Framework, was used to synthesize the findings. Studies from PubMed, Embase, Scopus, CINAHL, and APA PsycINFO were included.

resultsResults Eleven studies met the inclusion criteria. The synthesis identified distinct barriers and mechanisms of impact. Key barriers included structural and technical obstacles: digital literacy gaps, cognitive overload in vulnerable populations, misalignment with clinical IT systems, interface usability issues, and inconsistent implementation protocols. Regarding Enablers and Mechanisms, the review revealed a paradox. While ePROMs acted as enablers for personalized treatment and improved symptom awareness, their effectiveness was mediated by complex relational mechanisms. Both patients and clinicians expressed skepticism regarding utility in routine care. Furthermore, relational tensions arose when patient input was perceived as overlooked, highlighting that patient empowerment is conditional on the quality of the therapeutic alliance.

conclusionePROMs have the potential to enhance CKD care by providing valuable insights into patient experiences. However, their adoption is hindered by digital literacy, technological issues, and inconsistent protocols. To optimize adoption, policymakers must prioritize IT integration and standardized protocols, while clinicians should actively incorporate results into consultations to validate patient input. Future research should focus on mixed-methods studies in diverse populations to ensure equitable and effective implementation.

Indexed as

Patient Reported Outcome MeasuresRenal Insufficiency, ChronicHealth LiteracyHumansQualitative ResearchChronic kidney diseaseePROMsHealthcare providersImplementation barriersPatient-centered careQualitative studySystematic review

Identifiers

PMID41652416
PMCPMC12973700

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.