Evidence map›Paper›PMID 38756283›Full record

ReviewCureus2024

Navigating the Digital Landscape: Embracing Innovation, Addressing Challenges, and Prioritizing Patient-Centric Care.

Kanika Vats

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
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

1 author.

Kanika VatsDepartment of Management, School of Commerce and Management, Om Sterling Global University, Hisar, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the digital era, healthcare customer feedback plays a pivotal role in shaping the reputation of healthcare organizations. The study explores how digital advancements are integrated into modern healthcare, offering both transformative insights and addressing the challenges they present. It investigates how technologies such as artificial intelligence (AI), digital platforms, and patient feedback systems impact patient care, operational efficiency, and customer satisfaction in healthcare settings. The study emphasizes the importance of balancing both capitalizing on the opportunities presented by innovations and addressing the inherent difficulties associated with digitalization in healthcare, underlining the need for a comprehensive approach to navigating the opportunities and challenges in healthcare digitalization. AI is recognized for its role in reshaping value creation in healthcare, fostering collaboration among stakeholders, and improving patient care. Additionally, the study identifies key areas of research essential for effectively navigating the digital transformation in healthcare, including operational efficiency, patient-centric strategies, and organizational factors. However, along with the potential benefits come challenges, such as the need for regulatory frameworks to validate new technologies and address privacy concerns surrounding patient data. Managing reputation and customer relationships in the digital sphere also emerges as critical for healthcare organizations. In summary, the study underscores the importance of healthcare institutions prioritizing patient-centric care, adopting digital innovations, and adeptly navigating regulatory and ethical challenges. By doing so, they can enhance patient outcomes, and satisfaction, and drive innovation in today's dynamic healthcare landscape.

Indexed as

customer feedbackdigitalizationinnovationpatient centric carereputation

Identifiers

PMID38756283
PMCPMC11097284

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.