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Record W4390957044 · doi:10.5334/ijic.icic23270

Pandemic Patient Engagement Success: Maintaining Family Presence Through Partnership

2023· article· en· W4390957044 on OpenAlexaff
Anne O’Riordan, Angela Morin

Bibliographic record

VenueInternational Journal of Integrated Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsGeneral partnershipGovernment (linguistics)Public relationsVisitor patternHealth carePandemicNursingMedicineBusinessPolitical scienceCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

This presentation is relevant for patients of hospitals and residents of long-term care facilities, their loved ones and essential partners in care, and staff and leadership of healthcare facilities. A painful pandemic challenge for patients, families and staff in hospitals was the absence of loved ones or essential care partners through Family Presence/Visitor Policy restrictions. Leadership at Kingston Health Sciences Centre (KHSC) worked proactively with the Patient and Family Advisory Council and a small, diverse group of Patient Experience Advisors to plan for possible restrictions and consider how best to approach ongoing changes and challenges to the policy expected in the face of the pandemic. The group continues to work together at this time of uncertainty. An initial meeting of eight advisors and leaders took place prior to the World Health Organization’s official announcement of the pandemic. Due to growing concern about hospital infections, the meeting venue was a local coffee shop, hence the group became known throughout the hospital as The Balzac’s Group. Synchronous virtual meetings and asynchronous communication were employed by the group to address concerns and create family presence opportunities on a rapid response basis. Group collaboration remains evident as new concerns arise with the ongoing ebb and flow of COVID-19 hospitalizations, staff shortages and less restrictive family presence policies. This partnership has been pivotal to the organization’s pandemic planning and response, enabling family presence while respecting government directives, organizational challenges, and patient/family priorities. This collaboration informed several new and sustained initiatives including: a virtual visits process, ePostcards, a Care Partner Program, expanded cell phone use in restricted areas, resources for loved ones traveling distances, careful and measured increases in family presence and a family presence policy Exceptions Committee. An unexpected outcome was an increased level of respect and strengthened patient engagement. Factors influencing this success were transparency and trust in sharing sensitive or confidential information, mutual decision-making, frank and honest sharing of both personal and professional perspectives, and active listening. Many KHSC advisors increased their patient partnership activities during the pandemic and felt an enhanced sense of agency in their efforts to improve the patient experience in healthcare. This initiative may be a source of new ideas, inspiration, and encouragement for patient partners and hospital leaders to actively partner in co-design and delivery of compassionate person-centred policies and care, especially during times of crisis. The group continues to be the “go-to” group for family presence policy questions. The strengthened relationship with Patient Advisors has had a spillover effect more broadly into other hospital initiatives and increased awareness of the value of their input. We hope to continue to share this success story broadly to encourage other healthcare facilities to partner with the precious resource of patients, families, and patient advisors, at all levels of health care. We are considering a Patient Advisor led publication in the future.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0140.005
Scholarly communication0.0110.010
Open science0.0020.024
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0290.006

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 head0.154
GPT teacher head0.432
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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