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Record W4380987273 · doi:10.5334/ijic.6952

Patients, Caregivers, and Healthcare Providers’ Experiences with COVID Care and Recovery across the Care Continuum: A Qualitative Study

2023· article· en· W4380987273 on OpenAlexaff
Marina B. Wasilewski, Zara Szigeti, Christine Sheppard, Jacqueline Minezes, Sander L. Hitzig, Amanda L. Mayo, Lawrence R. Robinson, Maria Lung, Robert Simpson

Bibliographic record

VenueInternational Journal of Integrated Care · 2023
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoWellesley InstituteHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsRehabilitationAcute careHealth careMedicineNursingQualitative researchPandemicPatient experienceCoronavirus disease 2019 (COVID-19)Medical emergencyPhysical therapyDisease

Abstract

fetched live from OpenAlex

Introduction: During the COVID-19 pandemic, discharge timelines were accelerated and patients were moved across the continuum of care, from acute to post-acute care, to relieve the strain in health system capacity. This study aimed to investigate the COVID-19 care pathway from the perspective of patients, caregivers, and healthcare providers to understand their experiences with care and recovery within and across care settings. Methods: A qualitative descriptive study. Patients and their families from an inpatient COVID-19 unit and healthcare providers from an acute or rehabilitation COVID-19 unit were interviewed. Results: A total of 27 participants were interviewed. Three major themes were identified: 1) The perceived quality and pace of COVID-19 care improved from acute care to inpatient rehabilitation; 2) Care transitions were especially distressing; and 3) Recovery from COVID-19 stagnated in the community. Conclusion: Inpatient rehabilitation was viewed as higher quality due to the slower paced care. Care transitions were distressing for stakeholders and enhanced integration between acute and rehabilitation care were suggested to improve patient handover. A lack of rehabilitation access led to recovery stagnating for patients discharged to the community. Telerehab may improve the transition to home and ensure access to adequate rehabilitation and support in the community.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.352
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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