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Record W2607422284 · doi:10.23889/ijpds.v1i1.87

Discharge Communication and Patient Involvement are Associated with Unplanned Hospital Readmissions: Results from a Validated Hospital Experience Survey

2017· article· en· W2607422284 on OpenAlexaffabout
Kyle Kemp, Maria Santana, Rachel Jolley, Danielle A. Southern, Hude Quan

Bibliographic record

VenueInternational Journal for Population Data Science · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineConfidence intervalLogistic regressionHealth careOdds ratioHospital dischargeOddsEmergency medicineTelephone surveyTelephone interviewCohortAcute careMedical emergencyFamily medicineIntensive care medicineInternal medicine

Abstract

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ABSTRACTObjectivesUnplanned hospital readmissions are an indicator of quality of care, and are associated with significant costs to healthcare systems. Previous research has shown that poor communication and discharge experiences are associated with higher readmission rates. This, however, has only been examined in the short-term, and in many instances, at the hospital-level. The purpose of the study was to examine the relationship between aspects of inpatient communication and discharge instructions and unplanned readmissions at the individual-level up to one-year post-discharge. ApproachThe Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) telephone survey was completed by patients within 6 weeks of hospital discharge in Alberta, Canada. Survey data were linked to corresponding inpatient records using personal health number, discharge date, and facility codes. Unplanned readmissions (yes vs. no; all causes) from 43 to 365 days post-hospital discharge comprised the outcome variable. Independent variables included selected demographic characteristics, clinical variables, and five survey questions: a) patient involvement in their care decisions, b) receiving written information at discharge, c) understanding the purpose of taking medications, d) understanding responsibility for one’s health, and e) discussing help needed when returning home. Multivariate logistic regression was used to examine each question in the presence of the other predictors. Odds ratios and 95% confidence intervals were calculated. ResultsFrom April 2011 to March 2014, 24,868 patients completed a survey which was successfully linked to the corresponding inpatient record. The cohort had a mean age of 52.8±19.8 years of age (range=18-100), and was predominantly female (65.4%). 18.6% of patients (n=4,620) experienced an unplanned hospital readmission within 43 to 365 days post-discharge. Patients who felt that they were not involved in their care decisions were more likely to be readmitted (OR=1.79; 95%CI: 1.59-2.01), as were patients who did not receive written information at discharge (OR=1.96; 95%CI: 1.83-2.11). Odds of unplanned readmissions did not differ according to understanding of medications (OR=1.08; 95%CI: 0.90-1.30), understanding responsibility for one’s health (OR=1.02; 95%CI: 0.86-1.20), or discussion of help needed when returning home (OR=1.03; 95%CI: 0.93-1.14). ConclusionOur results demonstrate that a lack of patient involvement in their care and not receiving written information at discharge is associated with increased unplanned readmission rate up to one-year post-discharge. This present study provides an example of how patient-reported measures may be linked to individual-level administrative data to drive healthcare improvements. Future research examining patient-reported hospital experience and other health system measures is warranted.

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)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.004
Open science0.0020.001
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 head0.210
GPT teacher head0.482
Teacher spread0.272 · 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 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

Citations4
Published2017
Admission routes2
Has abstractyes

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