Evidence map›Paper›PMID 37256664›Full record

ArticleJMIR formative research2023

A Smart System for Remote Monitoring of Patients in Palliative Care (HumanITcare Platform): Mixed Methods Study.

Manuel Ramón Castillo Padrós, Nuria Pastor, Júlia Altarriba Paracolls, Marcelino Mosquera Peña, Denise Pergolizzi, Àngels Salvador Vergès

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 11% 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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
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

6 authors at 2 institutions in 1 country.

Manuel Ramón Castillo PadrósUniversity Hospital Nuestra Señora de la Candelaria, Santa Cruz de Tenerife, Spain.ORCID https://orcid.org/0000-0003-4872-4983
Nuria PastorHumanITcare, Barcelona, Spain.ORCID https://orcid.org/0000-0003-3172-7459
Júlia Altarriba ParacollsHumanITcare, Barcelona, Spain.ORCID https://orcid.org/0000-0002-1386-839X
Marcelino Mosquera PeñaUniversity Hospital Complex of Ferrol, A Coruña, Spain.ORCID https://orcid.org/0000-0002-2960-0953
Denise PergolizziUniversitat Internacional de Catalunya, Campus Sant Cugat, Barcelona, Spain.ORCID https://orcid.org/0000-0002-8357-9462
Àngels Salvador VergèsInnohealth Academy, Barcelona, Spain.ORCID https://orcid.org/0000-0001-5110-8423
Universitat Internacional de Catalunya · ESHospital Universitario Nuestra Señora de Candelaria · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the complexities of advanced illnesses and their treatments, it can be difficult for patients in palliative care to maintain their quality of life. Telemedicine interventions in chronic disease management engage patients in their care, provide continuous follow-up by their health care providers, identify symptoms earlier, and allow a quick response to illness-related decline.

objectiveWe aimed to detail and reflect on the design of an app and evaluate its feasibility to monitor the clinical situation of patients with advanced illnesses.

methodsThis study used a mixed methods design using qualitative methods to inform app development and design and quantitative methods for data collection and analysis of patient evaluations. Palliative care units in 2 Spanish university hospitals (Nuestra Señora de la Candelaria in Santa Cruz de Tenerife and University Hospital Complex of Ferrol in A Coruña) carried out a literature review, designed the study protocol, and obtained approval from the Ethics Committee from June to December 2020. In addition, focus group meetings were held, and the design and technical development of the app were elaborated on and subsequently presented in the participating palliative care units. From January to March 2021, the app was made public on the App Store and Play Store, and a pilot study with patients was carried out in April to September 2021.

resultsSix focus group meetings were held that included doctors, nurses, app developers, technology consultants, and sponsors. In addition, the technology consultants presented their results 3 times in the participating palliative care units to obtain feedback. After the app's final design, it was possible to publish it on the usual servers and begin its evaluation in patients (n=60, median age 72 years). Sixty percent (n=36) of the participants were women and 40% (n=24) were men. The most prevalent advanced pathology was cancer (n=46, 76%), followed by other diseases (n=7, 12%) and amyotrophic lateral sclerosis (n=5, 8%). Seventy percent (n=42) of the patients were already in follow-up prior to the start of the study, while 30% (n=18) were included at the start of their follow-up. The information in the app was collected and entered by relatives or caregivers in 60% (n=36) of the cases. The median follow-up was 52 (IQR 14-104) days. In all, 69% (n=41) had a follow-up >30 days (10 were deceased and 9 were missing data). The use of the different sections of the app ranged from 37% (n=22) for the glycemic record to 90% (n=54) for the constipation scale). Patients and caregivers were delighted with its ease of use and usefulness.

conclusionsIncorporating an intelligent remote patient monitoring system in clinical practice for patients in palliative care can improve access to health services and provide more information to professionals.

Indexed as

advanced illnesseHealthmHealthpalliative careremote monitoringtelemedicine

Identifiers

PMID37256664
PMCPMC10267781
OpenAlexW4378781651

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.