Dataset Information

Predictors for patients understanding reason for hospitalization.

ABSTRACT:

Objective

To examine predictors for understanding reason for hospitalization.

Methods

This was a retrospective analysis of a prospective, observational cohort study of patients 65 years or older admitted for acute coronary syndrome, heart failure, or pneumonia and discharged home. Primary outcome was complete understanding of diagnosis, based on post-discharge patient interview. Predictors assessed were the following: jargon on discharge instructions, type of medical team, whether outpatient provider knew if the patient was admitted, and whether the patient reported more than one day notice before discharge.

Results

Among 377 patients, 59.8% of patients completely understood their diagnosis. Bivariate analyses demonstrated that outpatient provider being aware of admission and having more than a day notice prior to discharge were not associated with patient understanding diagnosis. Presence of jargon was not associated with increased likelihood of understanding in a multivariable analysis. Patients on housestaff and cardiology teams were more likely to understand diagnosis compared to non-teaching teams (OR 2.45, 95% CI 1.30-4.61, p<0.01 and OR 3.83, 95% CI 1.92-7.63, p<0.01, respectively).

Conclusions

Non-teaching team patients were less likely to understand their diagnosis. Further investigation of how provider-patient interaction differs among teams may aid in development of tools to improve hospital to community transitions.

SUBMITTER: Weerahandi H

PROVIDER: S-EPMC5922555 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Predictors for patients understanding reason for hospitalization.

Weerahandi Himali H Ziaeian Boback B Fogerty Robert L RL Jenq Grace Y GY Horwitz Leora I LI

PloS one 20180427 4

<h4>Objective</h4>To examine predictors for understanding reason for hospitalization.<h4>Methods</h4>This was a retrospective analysis of a prospective, observational cohort study of patients 65 years or older admitted for acute coronary syndrome, heart failure, or pneumonia and discharged home. Primary outcome was complete understanding of diagnosis, based on post-discharge patient interview. Predictors assessed were the following: jargon on discharge instructions, type of medical team, whether ...[more]

PMID: 29702676

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Project description:IntroductionSevere hyperkalemia, with potassium (K+) levels ? 6.5 mEq/L, is a potentially life-threatening electrolyte imbalance. For prompt and effective treatment, it is important to know its risk factors, clinical manifestations, and predictors of mortality.MethodsAn observational cohort study was performed at 2 medical centers. A total of 923 consecutive Korean patients were analyzed. All were 19 years of age or older and were hospitalized with severe hyperkalemia between August 2007 and July 2010; the diagnosis of severe hyperkalemia was made either at the time of admission to the hospital or during the period of hospitalization. Demographic and baseline clinical characteristics at the time of hyperkalemia diagnosis were assessed, and clinical outcomes such as in-hospital mortality were reviewed, using the institutions' electronic medical record systems.ResultsChronic kidney disease (CKD) was the most common underlying medical condition, and the most common precipitating factor of hyperkalemia was metabolic acidosis. Emergent admission was indicated in 68.6% of patients, 36.7% had electrocardiogram findings typical of hyperkalemia, 24.5% had multi-organ failure (MOF) at the time of hyperkalemia diagnosis, and 20.3% were diagnosed with severe hyperkalemia at the time of cardiac arrest. The in-hospital mortality rate was 30.7%; the rate was strongly correlated with the difference between serum K+ levels at admission and at their highest point, and with severe medical conditions such as malignancy, infection, and bleeding. Furthermore, a higher in-hospital mortality rate was significantly associated with the presence of cardiac arrest and/or MOF at the time of diagnosis, emergent admission, and intensive care unit treatment during hospitalization. More importantly, acute kidney injury (AKI) in patients with normal baseline renal function was a strong predictor of mortality, compared with AKI superimposed on CKD.ConclusionsSevere hyperkalemia occurs in various medical conditions; the precipitating factors are similarly diverse. The mortality rate is especially high in patients with severe underlying disease, coexisting medical conditions, and those with normal baseline renal function.

Dataset Information

Predictors for patients understanding reason for hospitalization.

Objective

Methods

Results

Conclusions

Publications

Predictors for patients understanding reason for hospitalization.

Similar Datasets

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