Evidence map›Paper›PMID 33300882›Full record

ArticleJMIR public health and surveillance2020

Barriers to Creating Scalable Business Models for Digital Health Innovation in Public Systems: Qualitative Case Study.

Leah Taylor Kelley, Jamie Fujioka, Kyle Liang, Madeline Cooper, Trevor Jamieson, Laura Desveaux

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  6. Patient and Staff Insights on Digital Care Pathways for Patients With Low Back Pain in the Emergency Department: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2024
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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.

Leah Taylor KelleyInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-3236-4250
Jamie FujiokaInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-4942-6112
Kyle LiangInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0001-8459-531X
Madeline CooperInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0003-3381-5049
Trevor JamiesonUnity Health, Toronto, ON, Canada.ORCID 0000-0002-1050-3918
Laura DesveauxInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0003-3429-1865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth systems are increasingly looking toward the private sector to provide digital solutions to address health care demands. Innovation in digital health is largely driven by small- and medium-sized enterprises (SMEs), yet these companies experience significant barriers to entry, especially in public health systems. Complex and fragmented care models, alongside a myriad of relevant stakeholders (eg, purchasers, providers, and producers of health care products), make developing value propositions for digital solutions highly challenging.

objectiveThis study aims to identify areas for health system improvement to promote the integration of innovative digital health technologies developed by SMEs.

methodsThis paper qualitatively analyzes a series of case studies to identify health system barriers faced by SMEs developing digital health technologies in Canada and proposed solutions to encourage a more innovative ecosystem. The Women's College Hospital Institute for Health System Solutions and Virtual Care established a consultation program for SMEs to help them increase their innovation capacity and take their ideas to market. The consultation involved the SME filling out an onboarding form and review of this information by an expert advisory committee using guided considerations, leading to a recommendation report provided to the SME. This paper reports on the characteristics of 25 SMEs who completed the program and qualitatively analyzed their recommendation reports to identify common barriers to digital health innovation.

resultsA total of 2 central themes were identified, each with 3 subthemes. First, a common barrier to system integration was the lack of formal evaluation, with SMEs having limited resources and opportunities to conduct such an evaluation. Second, the health system's current structure does not create incentives for clinicians to use digital technologies, which threatens the sustainability of SMEs' business models. SMEs faced significant challenges in engaging users and payers from the public system due to perverse economic incentives. Physicians are compensated by in-person visits, which actively works against the goals of many digital health solutions of keeping patients out of clinics and hospitals.

conclusionsThere is a significant disconnect between the economic incentives that drive clinical behaviors and the use of digital technologies that would benefit patients' well-being. To encourage the use of digital health technologies, publicly funded health systems need to dedicate funding for the evaluation of digital solutions and streamlined pathways for clinical integration.

Indexed as

Diffusion of InnovationModels, TheoreticalCanadaCase-Control StudiesHumansPublic SectorQualitative Researchdigital technologiesevaluation studyhealth policyincentiveinnovation diffusionmobile phonereimbursementtelemedicine

Identifiers

PMID33300882
PMCPMC7759439

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.