Implementation of Digital Monitoring Services During the COVID-19 Pandemic for Patients With Chronic Diseases: Design Science Approach

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Abstract

Background

The COVID-19 pandemic is straining health systems and disrupting the delivery of health care services, in particular, for older adults and people with chronic conditions, who are particularly vulnerable to COVID-19 infection.

Objective

The aim of this project was to support primary health care provision with a digital health platform that will allow primary care physicians and nurses to remotely manage the care of patients with chronic diseases or COVID-19 infections.

Methods

For the rapid design and implementation of a digital platform to support primary health care services, we followed the Design Science implementation framework: (1) problem identification and motivation, (2) definition of the objectives aligned with goal-oriented care, (3) artefact design and development based on Scrum, (4) solution demonstration, (5) evaluation, and (6) communication.

Results

The digital platform was developed for the specific objectives of the project and successfully piloted in 3 primary health care centers in the Lisbon Health Region. Health professionals (n=53) were able to remotely manage their first patients safely and thoroughly, with high degrees of satisfaction.

Conclusions

Although still in the first steps of implementation, its positive uptake, by both health care providers and patients, is a promising result. There were several limitations including the low number of participating health care units. Further research is planned to deploy the platform to many more primary health care centers and evaluate the impact on patient’s health related outcomes.

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Most cited references 26

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Comorbidity and its Impact on Patients with COVID-19

Adekunle O Sanyaolu, Chuku Okorie, Aleksandra Marinkovic … (2020)

A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan, China, in December 2019. Since then, the virus has made its way across the globe to affect over 180 countries. SARS-CoV-2 has infected humans in all age groups, of all ethnicities, both males and females while spreading through communities at an alarming rate. Given the nature of this virus, there is much still to be learned; however, we know that the clinical manifestations range from a common cold to more severe diseases such as bronchitis, pneumonia, severe acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. It is believed that COVID-19, in those with underlying health conditions or comorbidities, has an increasingly rapid and severe progression, often leading to death. This paper examined the comorbid conditions, the progression of the disease, and mortality rates in patients of all ages, infected with the ongoing COVID-19 disease. An electronic literature review search was performed, and applicable data was then collected from peer-reviewed articles published from January to April 20, 2020. From what is known at the moment, patients with COVID-19 disease who have comorbidities, such as hypertension or diabetes mellitus, are more likely to develop a more severe course and progression of the disease. Furthermore, older patients, especially those 65 years old and above who have comorbidities and are infected, have an increased admission rate into the intensive care unit (ICU) and mortality from the COVID-19 disease. Patients with comorbidities should take all necessary precautions to avoid getting infected with SARS CoV-2, as they usually have the worst prognosis.

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Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Andrew Clark, Mark Jit, Charlotte Warren-Gash … (2020)

Summary Background The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from 66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research.

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A Design Science Research Methodology for Information Systems Research

Ken Peffers, Tuure Tuunanen, Marcus A. Rothenberger … (2007)

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Author and article information

Contributors

Luís Velez Lapão:

ORCID: https://orcid.org/0000-0003-0506-1294

Global Health and Tropical MedicineInstituto de Higiene e Medicina TropicalUniversidade Nova de LisboaRua da Junqueira, 100Lisbon, 1349-008Portugal351 213652600luis.lapao@ihmt.unl.pt

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: August 2021

Publication date (Electronic): 26 August 2021

Publication date PMC-release: 26 August 2021

Volume: 23

Issue: 8

Electronic Location Identifier: e24181

Affiliations

[1 ] Global Health and Tropical Medicine Instituto de Higiene e Medicina Tropical Universidade Nova de Lisboa Lisbon Portugal

[2 ] Comprehensive Health Research Center NOVA Medical School Universidade Nova de Lisboa Lisbon Portugal

[3 ] Research and Development Unit in Mechanical and Industrial Engineering (UNIDEMI) NOVA School of Science and Technology Universidade Nova de Lisboa Caparica Portugal

[4 ] NOVA School of Science and Technology Universidade Nova de Lisboa Caparica Portugal

[5 ] NOVA School of Social Sciences and Humanities Universidade Nova de Lisboa Lisbon Portugal

[6 ] Research Center for Biosciences and Health Technologies Universidade Lusófona de Humanidades e Tecnologias Lisbon Portugal

[7 ] Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

[8 ] Unit of Patient Education, Division of Endocrinology, Diabetology, Nutrition and Patient Education Department of Medicine Geneva University Hospitals and University of Geneva Geneva Switzerland

Author notes

Corresponding Author: Luís Velez Lapão luis.lapao@ 123456ihmt.unl.pt

Author information

Luís Velez Lapão https://orcid.org/0000-0003-0506-1294

Mariana Peyroteo https://orcid.org/0000-0003-4976-2826

Melanie Maia https://orcid.org/0000-0003-3695-0537

Jorge Seixas https://orcid.org/0000-0002-3110-6583

João Gregório https://orcid.org/0000-0002-6130-9453

Miguel Mira da Silva https://orcid.org/0000-0002-0489-4465

Bruno Heleno https://orcid.org/0000-0002-3943-1858

Jorge César Correia https://orcid.org/0000-0002-7020-0695

Article

Publisher ID: v23i8e24181

DOI: 10.2196/24181

PMC ID: 8396539

PubMed ID: 34313591

SO-VID: 93cef64e-63b2-4dc7-a7fb-8c905b476644

Copyright © ©Luís Velez Lapão, Mariana Peyroteo, Melanie Maia, Jorge Seixas, João Gregório, Miguel Mira da Silva, Bruno Heleno, Jorge César Correia. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.08.2021.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 7 September 2020

Date revision requested : 2 November 2020

Date revision received : 14 January 2021

Date accepted : 2 July 2021

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