Evidence map›Paper›PMID 39281041›Full record

ArticleDigital health

Identification of required capabilities of digital health ecosystems when preventing and managing non-communicable diseases.

Minna Pikkarainen, Marika Iivari, Julius F Gomes, Jouni Kaartinen, Yueqiang Xu, He Hong-Gu, Parisa Gazerani

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

7 authors.

Minna PikkarainenDepartment of Rehabilitation and Health Technology and Product Design, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0003-4516-6584
Marika IivariMartti Ahtisaari Institute, Oulu Business School, University of Oulu, Oulu, Finland.ORCID https://orcid.org/0000-0002-5954-2133
Julius F GomesMartti Ahtisaari Institute, Oulu Business School, University of Oulu, Oulu, Finland.
Jouni KaartinenHealth data analytics, VTT Technical Research Centre of Finland, Espoo, Finland.
Yueqiang XuMartti Ahtisaari Institute, Oulu Business School, University of Oulu, Oulu, Finland.
He Hong-GuAlice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0001-8545-1123
Parisa GazeraniDepartment of Life Sciences and Health, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0003-0109-3600

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Non-communicable diseases cause annual mortality for 41 million people worldwide. These diseases include coronary heart disease, cancer, stroke, diabetes, and musculoskeletal as well as mental disorders. Innovation ecosystems in healthcare are multifactor networks in which different stakeholders interact together to create socio-economic (patient and cost) value via research, co-creation, and traditional market activities. Although there is much evidence about the impact of digital health interventions and the capabilities needed to support individual actors and specific diseases in non-communicable disease prevention and management, the current understanding of the concept of innovation ecosystems associated with theories is not well understood. There is also a lack of research about innovation ecosystems in the healthcare context. Or understanding of the holistic perspective of the capabilities needed in innovation ecosystems to support future digital health. The objective of this study was to answer this research gap by identifying what capabilities are needed in future digital health ecosystems related to people with non-communicable diseases or at risk of non-communicable diseases. By doing this, the study will help different organisations and policies address this very challenging situation. Methods: To answer this objective, a qualitative interview-based study including 34 semi-structured interviews was conducted in Finland. Complex adaptive systems theory was used as a theoretical lens to analyse empirical data. Results and conclusion: Several new capabilities were identified for digital health innovation ecosystems to make organisation managers and policymakers aware of how to deal with future health system demands. From the organisational perspective, capabilities are needed to use non-medical and heterogeneous data to support better treatments and clinical decision-making and provide better and safer data access. From the management perspective, hospitals need capabilities to allow critical experts to participate in innovation work, and overall, all ecosystem actors need capabilities to orchestrate research and innovation actions in the area of digital health.

Indexed as

capabilitychronic diseasescomplex systems theoryDigital healthinnovativepreventive

Identifiers

PMID39281041
PMCPMC11402099

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.