Improving hospital safety for patients with chronic kidney disease: a mixed methods study
Bibliographic record
Abstract
BACKGROUND: People living with chronic kidney disease (CKD) require complex medical management and may be frequently hospitalized. Patient safety incidents during hospitalization can result in serious complications which may negatively affect health outcomes. There has been limited examination of how these patients perceive their own safety. OBJECTIVES: This study compared the safety perceptions of patients hospitalized with CKD using two approaches: (a) the Patient Measure of Safety (PMOS) questionnaire and (b) qualitative interviews. The study objectives were to: (1) assess concordance between qualitative and quantitative data on safety perceptions and (2) better understand safety as perceived by study participants. METHODS: A cross-sectional convergent mixed methods design was used. Integration at the reporting level occurred by weaving together patient narratives and survey domains through the use of a joint display. Interview data were merged with results of the PMOS on a case-by-case basis for analysis to assess for concordance or discordance between these approaches to safety data collection. RESULTS: Of the 30 inpatients with CKD, almost one quarter (23.3 %) of participants reported low levels of perceived safety in hospitals. Four major themes emerged from the interviews: receiving safe care; expecting to be taken care of; expecting to be cared for; and reporting safety concerns. Suboptimal communication, delays in care and concerns about technical aspects of care were common to both forms of data collection. Concordance was noted between qualitative and quantitative data with respect to communication/teamwork, respect and dignity, staff roles, and ward type/lay-out. While interviews allowed for participants to share specific concerns related to safety about quality of interpersonal interactions, use of the questionnaire alone did not capture this concern. CONCLUSIONS: Safety issues are a concern for in-patients with CKD. Both quantitative and qualitative approaches provided important and complementary insights into these issues. Narratives were mostly concordant with questionnaire scores. Findings from this mixed methods study suggest that communication, interpersonal interactions, and delays in care were more concerning for participants than technical aspects of care. Eliciting the concerns of people with CKD in a systematic fashion, either through interviews or a survey, ensures that hospital safety improvement efforts focus on issues important to patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".