ArticleClinical nephrology2013
Electronic health records: a new tool to combat chronic kidney disease?
Article in Clinical nephrology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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.
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.
Who cites it
20 citing papers in PubMed.
- Validation of ICD-10-CM algorithms for repeated eGFR-defined chronic kidney disease in the TriNetX network.BMJ health & care informatics · 2026Article
- Identifying and Characterising a Chronic Kidney Disease Electronic-Phenotype Using Electronic Health Record-Derived Data: A Narrative Review of Strategies and Applications.Nephrology (Carlton, Vic.) · 2025Review
- Population Health Management for Improving Kidney Health Outcomes.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025Article
- Identifying a cohort of hospitalized chronic kidney disease patients using electronic health records: lessons learnt and implications for future research and clinical practice guidelines.Clinical kidney journal · 2025Article
- Optimizing use of an electronic medical record system for quality improvement initiatives in hemodialysis: Review of a single center experience.Hemodialysis international. International Symposium on Home Hemodialysis · 2025Review
- Early renal function trajectories, cytomegalovirus serostatus and long-term graft outcomes in kidney transplant recipients.BMC nephrology · 2021Article
- Rationale and design of a multicenter Chronic Kidney Disease (CKD) and at-risk for CKD electronic health records-based registry: CURE-CKD.BMC nephrology · 2019Article
- Primary Care Physicians' Perceived Barriers to Nephrology Referral and Co-management of Patients with CKD: a Qualitative Study.Journal of general internal medicine · 2019Article
- Putting patients at the center of kidney care transitions: PREPARE NOW, a cluster randomized controlled trial.Contemporary clinical trials · 2018Article
- Associations of dysnatremias with mortality in chronic kidney disease.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2017Article
- Multi-Trajectory Models of Chronic Kidney Disease Progression.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Disparities in Electronic Health Record Patient Portal Use in Nephrology Clinics.Clinical journal of the American Society of Nephrology : CJASN · 2015Article
- CKD as a Model for Improving Chronic Disease Care through Electronic Health Records.Clinical journal of the American Society of Nephrology : CJASN · 2015Article
- Drug induced diseases (DID): Need for more awareness & research.The Indian journal of medical research · 2015Article
- Development of a chronic kidney disease patient navigator program.BMC nephrology · 2015Article
- Patients with chronic kidney disease and their intent to use electronic personal health records.Canadian journal of kidney health and disease · 2015Article
- Chronic kidney disease in an electronic health record problem list: quality of care, ESRD, and mortality.American journal of nephrology · 2014Article
- Strategies for handling missing data in electronic health record derived data.EGEMS (Washington, DC) · 2013Article
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Electronic health records (EHRs) were first developed in the 1960s as clinical information systems for document storage and retrieval. Adoption of EHRs has increased in the developed world and is increasing in developing countries. Studies have shown that quality of patient care is improved among health centers with EHRs. In this article, we review the structure and function of EHRs along with an examination of its potential application in CKD care and research. Well-designed patient registries using EHRs data allow for improved aggregation of patient data for quality improvement and to facilitate clinical research. Preliminary data from the United States and other countries have demonstrated that CKD care might improve with use of EHRs-based programs. We recently developed a CKD registry derived from EHRs data at our institution and complimented the registry with other patient details from the United States Renal Data System and the Social Security Death Index. This registry allows us to conduct a EHRs-based clinical trial that examines whether empowering patients with a personal health record or patient navigators improves CKD care, along with identifying participants for other clinical trials and conducting health services research. EHRs use have shown promising results in some settings, but not in others, perhaps attributed to the differences in EHRs adoption rates and varying functionality. Thus, future studies should explore the optimal methods of using EHRs to improve CKD care and research at the individual patient level, health system and population levels.
Indexed as
Identifiers
What OpenQuestion holds
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.