Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jul 29, 2022
Date Accepted: Apr 7, 2023

The final, peer-reviewed published version of this preprint can be found here:

Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review

Konopik J, Blunck D

Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review

J Med Internet Res 2023;25:e41512

DOI: 10.2196/41512

PMID: 37289482

PMCID: 10288351

Development of an Evidence-Based Conceptual Model of the Healthcare-Sector under Digital Transformation: Integrative Review

  • Jens Konopik; 
  • Dominik Blunck

ABSTRACT

Background:

The digital transformation is one of the most dominant trends of our time. It is fundamentally changing consumers’ expectations and behaviors, challenging traditional firms, and disrupting numerous markets. Recent discussions in the healthcare-sector tend to assess the influence of technological implications but neglect other factors, needed for a holistic view on the digital transformation. This calls for a reevaluation of the current state of digital transformation in healthcare. Consequently, the need for a holistic view on the complex interdependencies of digital transformation in the healthcare-sector emerges.

Objective:

This study aims to examine the effects of digital transformation on the healthcare-sector. This is done by providing a conceptual model of the healthcare-sector under digital transformation.

Methods:

First, the most essential stakeholders in the healthcare-sector were identified by a scoping review and grounded theory approach. Second, the effects on these stakeholders were assessed. Based on an integrative review and grounded theory-methodology, the relevant academic literature was systematized and quantitatively and qualitatively analyzed to evaluate the impact on the value creation of, and the relationships among the stakeholders. Third, the findings were synthesized into a conceptual model of the healthcare-sector under digital transformation.

Results:

The results revealed that providers of medical treatments, patients, governing institutions, and payers are the most essential stakeholders in the healthcare-sector. As for the individual stakeholders, patients are experiencing a technology-enabled growth of influence in the sector. Providers become increasingly dependent on intermediaries for essential parts of the value creation and patient interaction. Payers are expected to try to increase their influence on intermediaries to exploit the enormous amounts of data whilst seeing their business models to be challenged by emerging technologies. Governing institutions regulating the healthcare-sector are increasingly facing challenges from new entrants in the sector. Intermediaries increasingly interconnect all these stakeholders, which in turn drives new ways of value creation. These collaboration efforts lead to the establishment of a virtually integrated healthcare ecosystem.

Conclusions:

The conceptual model provides a novel and evidence-based perspective on the interrelations among actors in the healthcare-sector indicating that individual stakeholders need to recognize their individual role in the system. The model can be the basis of further evaluations of strategic actions of actors and their effects on other actors or the healthcare ecosystem itself.


 Citation

Please cite as:

Konopik J, Blunck D

Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review

J Med Internet Res 2023;25:e41512

DOI: 10.2196/41512

PMID: 37289482

PMCID: 10288351

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.