Impact of remote biometric monitoring on cost and hospitalization outcomes in peritoneal dialysis.


Journal

Journal of telemedicine and telecare
ISSN: 1758-1109
Titre abrégé: J Telemed Telecare
Pays: England
ID NLM: 9506702

Informations de publication

Date de publication:
Dec 2019
Historique:
pubmed: 14 7 2018
medline: 11 2 2020
entrez: 14 7 2018
Statut: ppublish

Résumé

Peritoneal dialysis is a home-based therapy for individuals with end-stage renal disease. Telehealth, and in particular - remote monitoring, is making inroads in managing this cohort. We examined whether daily remote biometric monitoring (RBM) of blood pressure and weight among peritoneal dialysis patients was associated with changes in hospitalization rate and hospital length of stay, as well as outpatient, inpatient and overall cost of care. Outpatient visit claim payment amounts (in US dollars derived from CMS data) decreased post-intervention relative to pre-intervention for those at age 18-54 years. For certain subgroups, non- or nearly-significant changes were found among female and Black participants. There was no change in inpatient costs post-intervention relative to pre-intervention for females and while the overall visit claim payment amounts increased in the outpatient setting slightly (US$511.41 (1990.30) RBM offers a powerful opportunity to provide care to those receiving home therapies such as peritoneal dialysis. RBM may be associated with reduction in both inpatient and outpatient costs for specific sub-groups receiving peritoneal dialysis.

Identifiants

pubmed: 30001668
doi: 10.1177/1357633X18784417
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

581-586

Auteurs

Susie Q Lew (SQ)

Department of Medicine, George Washington University, Washington, USA.

Neal Sikka (N)

Department of Emergency Medicine, George Washington University, Washington, USA.

Clinton Thompson (C)

Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, USA.

Manya Magnus (M)

Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, USA.

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Classifications MeSH