Cargando…

Population measurement for health systems

How can health systems make good use of digital medicine? For healthcare infrastructure, the answer is population measurement, monitoring people to compute status for clustering cohorts. In chronic care, most effective is measuring all the time, to track health status as it gradually changes. Passiv...

Descripción completa

Detalles Bibliográficos
Autor principal: R. Schatz, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550166/
https://www.ncbi.nlm.nih.gov/pubmed/31304348
http://dx.doi.org/10.1038/s41746-017-0004-2
_version_ 1783424141937868800
author R. Schatz, Bruce
author_facet R. Schatz, Bruce
author_sort R. Schatz, Bruce
collection PubMed
description How can health systems make good use of digital medicine? For healthcare infrastructure, the answer is population measurement, monitoring people to compute status for clustering cohorts. In chronic care, most effective is measuring all the time, to track health status as it gradually changes. Passive monitors run in the background, without additional tasks to activate monitors, especially on mobile phones. At its core, a health system is a “sorting problem”. Each patient entering the system must be effectively sorted into treatment cohorts. Health systems have three primary problems: Case Finding (which persons have which diagnoses), Risk Stratification (which persons are which status), and Care Routing (which persons need which treatments). The issue is then which measures can be continuously monitored at appropriate periodicity. The solutions of population measurement measure vital signs with passive monitors. These are input to predictive analytics to detect clinical values for providing care within health systems. For chronic care, complex vitals must be measured for overall status, such as oxygen saturation or gait speed. This enables healthcare infrastructure to support stratification, with persons placed into current levels of health status. Practical considerations for health systems influence implementation of new infrastructure. Case finding is more likely to be useful in urban settings, with barriers to entry based upon lower incomes. Care routing is more likely to be useful in rural settings, with barriers to entry based upon isolated geographies. Viable healthcare at acceptable quality and affordable cost is now possible for the range of geographies and incomes.
format Online
Article
Text
id pubmed-6550166
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-65501662019-07-12 Population measurement for health systems R. Schatz, Bruce NPJ Digit Med Perspective How can health systems make good use of digital medicine? For healthcare infrastructure, the answer is population measurement, monitoring people to compute status for clustering cohorts. In chronic care, most effective is measuring all the time, to track health status as it gradually changes. Passive monitors run in the background, without additional tasks to activate monitors, especially on mobile phones. At its core, a health system is a “sorting problem”. Each patient entering the system must be effectively sorted into treatment cohorts. Health systems have three primary problems: Case Finding (which persons have which diagnoses), Risk Stratification (which persons are which status), and Care Routing (which persons need which treatments). The issue is then which measures can be continuously monitored at appropriate periodicity. The solutions of population measurement measure vital signs with passive monitors. These are input to predictive analytics to detect clinical values for providing care within health systems. For chronic care, complex vitals must be measured for overall status, such as oxygen saturation or gait speed. This enables healthcare infrastructure to support stratification, with persons placed into current levels of health status. Practical considerations for health systems influence implementation of new infrastructure. Case finding is more likely to be useful in urban settings, with barriers to entry based upon lower incomes. Care routing is more likely to be useful in rural settings, with barriers to entry based upon isolated geographies. Viable healthcare at acceptable quality and affordable cost is now possible for the range of geographies and incomes. Nature Publishing Group UK 2018-01-15 /pmc/articles/PMC6550166/ /pubmed/31304348 http://dx.doi.org/10.1038/s41746-017-0004-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Perspective
R. Schatz, Bruce
Population measurement for health systems
title Population measurement for health systems
title_full Population measurement for health systems
title_fullStr Population measurement for health systems
title_full_unstemmed Population measurement for health systems
title_short Population measurement for health systems
title_sort population measurement for health systems
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550166/
https://www.ncbi.nlm.nih.gov/pubmed/31304348
http://dx.doi.org/10.1038/s41746-017-0004-2
work_keys_str_mv AT rschatzbruce populationmeasurementforhealthsystems