Evidence map›Paper›PMID 28031020›Full record

ArticleBMC health services research2016

Assessing key cost drivers associated with caring for chronic kidney disease patients.

Paul Damien, Holly J Lanham, Murali Parthasarathy, Nikhil L Shah

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.9field-weighted citation impact, top 7% of its field
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

14 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Chronic kidney disease and transvenous cardiac implantable electronic device infection-is there an impact on healthcare utilization, costs, disease progression, and mortality?Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
    Article
  6. Article
  7. Review
  8. Article
  9. Age-related difference in health care use and costs of patients with chronic kidney disease and matched controls: analysis of Dutch health care claims data.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2020
    Article
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  12. Observational
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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

4 authors at 2 institutions in 1 country.

Paul DamienMcCombs School of Business, University of Texas in Austin, Austin, USA.
Holly J LanhamMcCombs School of Business, University of Texas in Austin, Austin, USA. lanham@uthscsa.com.
Murali ParthasarathySaaraa Medical Solutions, Whitehouse Station, NJ, USA.
Nikhil L ShahPiedmont Clinic, Atlanta, GA, USA.
The University of Texas at Austin · USGeorgia Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo examine key factors influencing chronic kidney disease (CKD) patients' total expenditure and offer recommendations on how to reduce total cost of CKD care without compromising quality.

methodsUsing the 2002-2011 Medical Expenditure Panel Survey (MEPS) data, our cross-sectional study analyzed 197 patient records-79 patients with one record and 59 with two entries per patient (138 unique patients). We used three patient groups, based on international statistical classification of diseases version 9 code for condition (ICD9CODX) classification, to focus inference from the analysis: (a) non-dialysis dependent CKD, (b) dialysis and (c) transplant. Covariate information included region, demographic, co-morbid conditions and types of services. We used descriptive methods and multivariate generalized linear models to understand the impact of cost drivers. We compared actual and predicted CKD cost of care data using a hold-out sample of nine, randomly selected patients to validate the models.

resultsTotal costs were significantly affected by treatment type, with dialysis being significantly higher than non-dialysis and transplant groups. Costs were highest in the West region of the U.S. Average costs for patients with public insurance were significantly higher than patients with private insurance (p < .0743), and likewise, for patients with co-morbid conditions over those without co-morbid conditions (p < .001).

conclusionsManaging CKD patients both before and after the onset of dialysis treatment and managing co-morbid conditions in individuals with CKD are potential sources of substantial cost savings in the care of CKD patients. Comparing total costs pre and post the United States Affordable Care Act could provide invaluable insights into managing the cost-quality tradeoff in CKD care.

Indexed as

ComorbidityCosts and Cost AnalysisCross-Sectional StudiesHealth ExpendituresHumansMedicareMultivariate AnalysisRenal DialysisRenal Insufficiency, ChronicUnited StatesChronic kidney diseaseCo-morbid conditionsTotal costs drivers

Identifiers

PMID28031020
PMCPMC5192586
OpenAlexW2567071500

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.