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Record W4362692219 · doi:10.2196/41950

How Older Persons and Health Care Professionals Co-designed a Medication Plan Prototype Remotely to Promote Patient Safety: Case Study

2023· article· en· W4362692219 on OpenAlexvenueno aff
Malin Holmqvist, Axel Ros, Bertil Lindenfalk, Johan Thor, Linda Johansson

Bibliographic record

VenueJMIR Aging · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
FundersFuturum - Akademin för Hälsa och Vård, Region Jönköpings läns
KeywordsThematic analysisPatient safetyPsychological interventionHealth careMedicineNursingQualitative propertyResearch designHarmQualitative researchMedical educationMedical emergencyPsychologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Harm from medications is a major patient safety challenge. Most adverse drug events arise when a medication is prescribed or reevaluated. Therefore, interventions in this area may improve patient safety. A medication plan, that is, a plan for continued treatment with medications, may support patient safety. Participation of patients in the design of health care products or services may improve patient safety. Co-design, as in the Double Diamond framework from the Design Council, England, can emphasize patient involvement. As the COVID-19 pandemic brought restrictions to face-to-face co-design approaches, interest in remote approaches increased. However, it is uncertain how best to perform remote co-design. Therefore, we explored a remote approach, which brought together older persons and health care professionals to co-design a medication plan prototype in the electronic health record, aiming to support patient safety. OBJECTIVE: This study aimed to describe how remote co-design was applied to create a medication plan prototype and to explore participants' experiences with this approach. METHODS: Within a case study design, we explored the experiences of a remote co-design initiative with 14 participants in a regional health care system in southern Sweden. Using descriptive statistics, quantitative data from questionnaires and web-based workshop timestamps were analyzed. A thematic analysis of the qualitative data gathered from workshops, interviews, and free-text responses to the survey questions was performed. Qualitative and quantitative data were compared side by side in the discussion. RESULTS: The analysis of the questionnaires revealed that the participants rated the experiences of the co-design initiative very high. In addition, the balance between how much involved persons expressed their wishes and were listened to was considered very good. Marked timestamps from audio recordings showed that the workshops proceeded according to the plan. The thematic analysis yielded the following main themes: Everyone's perspective matters, Learning by sharing, and Mastering a digital space. The themes encompassed what helped to establish a permissive environment that allowed the participants to be involved and share viewpoints. There was a dynamic process of learning and understanding, realizing that despite different backgrounds, there was consensus about the requirements for a medication plan. The remote co-design process seemed appealing, by balancing opportunities and challenges and building an inviting, creative, and tolerant environment. CONCLUSIONS: Participants experienced that the remote co-design initiative was inclusive of their perspectives and facilitated learning by sharing experiences. The Double Diamond framework was applicable in a digital context and supported the co-design process of the medication plan prototype. Remote co-design is still novel, but with attentiveness to power relations between all involved, this approach may increase opportunities for older persons and health care professionals to collaboratively design products or services that can improve patient safety.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.203
GPT teacher head0.481
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 teacher head, not a consensus.

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

Citations16
Published2023
Admission routes1
Has abstractyes

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