Health Care Professionals’ Experiences With Using Information and Communication Technologies in Patient Care During the COVID-19 Pandemic: Qualitative Study (Preprint)
Bibliographic record
Abstract
BACKGROUND The COVID-19 pandemic acted as a catalyst for the use of information and communication technology (ICT) in inpatient and outpatient health care settings. Digital tools were used to connect patients, families, and providers amid visitor restrictions, while web-based platforms were used to continue care amid COVID-19 lockdowns. What we have yet to learn is the experiences of health care providers (HCPs) regarding the use of ICT that supported changes to clinical care during the COVID-19 pandemic. OBJECTIVE The aim of this paper was to describe the experiences of HCPs in using ICT to support clinical care changes during the COVID-19 pandemic. This paper is reporting on a subset of a larger body of data that examined changes to models of care during the pandemic. METHODS This study used a qualitative, descriptive study design. In total, 30 HCPs were recruited from 3 hospitals in Canada. One-on-one semistructured interviews were conducted between December 2022 and June 2023. Qualitative data were analyzed using an inductive thematic approach to identify themes across participants. RESULTS A total of 30 interviews with HCPs revealed 3 themes related to their experiences using ICT to support changes to clinical care during the COVID-19 pandemic. These included the use of ICT (1) to support in-person communication with patients, (2) to facilitate connection between provider to patient and patient to family, and (3) to provide continuity of care. CONCLUSIONS HCP narratives revealed the benefits of digital tools to support in-person communication between patient and provider, the need for thoughtful consideration for the use of ICT at end-of-life care, and the decision-making that is needed when choosing service delivery modality (eg, web based or in person). Moving forward, organizations are encouraged to provide education and training on how to support patient-provider communication, find ways to meet patient and family wishes at end-of-life care, and continue to give autonomy to HCPs in their clinical decision-making regarding service delivery modality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".