Evidence map›Paper›PMID 38855044›Full record

ReviewRisk management and healthcare policy2024

The Impact of Pandemic-Driven Care Redesign on Hospital Efficiency.

Mihajlo Jakovljevic, Yuriy Timofeyev, Tatyana Zhuravleva

Abstract readReview
In one paragraph

Review in Risk management and healthcare policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

3 authors.

Mihajlo JakovljevicUNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.ORCID 0000-0002-9160-6846
Yuriy TimofeyevGraduate School of Business, HSE University, Moscow, Russia.ORCID 0000-0002-0197-8495
Tatyana ZhuravlevaInternational Laboratory for Experimental and Behavioural Economics, HSE University, Moscow, Russia.ORCID 0000-0002-8858-7170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to identify medical care transformations during the COVID-19 pandemic and to assess the economic efficiency of these care transformations. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviewing and Meta-Analysis (PRISMA) guidelines. The databases used in the search protocol included PubMed, RSCI, and Google Scholar. Results: Ten eligible studies in English and one publication in Russian were identified. In general, the following changes in organization of health care processes since 2020 are observed: hospital at home, telemedicine (physician-to-patient), and the adoption of new information communication technologies within physician-to-physician and physician-to-nurse communication. Earlier trends, such as (a) wider use of electronic devices, (b) adoption of Lean techniques, (c) the incorporation of patient and other customer experience feedback, and (d) the implementation of clinical decision support systems and automation of workflow, tend to be preserved. Conclusion: The most common changes in hospital care organization and the respective impacts of workflow changes (ie, workflow interventions, redesign, and transformations) on the efficiency of hospital care were summarized and avenues for future research and policy implications were discussed. The pandemic demonstrated a need for building more resilient and adaptive healthcare systems, enhancing crisis preparedness along with rapid and effective responses.

Indexed as

care redesigncare transformationefficiencyhospital careworkflow improvementsworkflow redesign

Identifiers

PMID38855044
PMCPMC11162215

What OpenQuestion holds

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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.