Publications

BACKGROUND

Readmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction.

OBJECTIVE

To develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay").

DESIGN

Observational cohort study using stepwise-backward selection and cross-validation.

SUBJECTS

Consecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010.

MEASURES

All-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals.

RESULTS

Of 1463 patients, 13.6% were readmitted. The first-day pneumonia-specific model included sociodemographic factors, prior hospitalizations, thrombocytosis, and a modified pneumonia severity index; the full-stay model included disposition status, vital sign instabilities on discharge, and an updated pneumonia severity index calculated using values from the day of discharge as additional predictors. The full-stay pneumonia-specific model outperformed the first-day model (C statistic 0.731 vs 0.695; P = 0.02; net reclassification index = 0.08). Compared to a validated multi-condition readmission model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores, the full-stay pneumonia-specific model had better discrimination (C statistic range 0.604-0.681; P < 0.01 for all comparisons), predicted a broader range of risk, and better reclassified individuals by their true risk (net reclassification index range, 0.09-0.18).

CONCLUSIONS

EHR data collected from the entire hospitalization can accurately predict readmission risk among patients hospitalized for pneumonia. This approach outperforms a first-day pneumonia-specific model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores. Journal of Hospital Medicine 2017;12:209-216.

Objective

With the rapid rise in the adoption of patient portals, many patients are gaining access to their personal health information online for the first time. The objective of this study was to examine specific usability barriers to patient portal engagement among a diverse group of patients and caregivers.

Materials and Methods

We conducted interviews using performance testing and think-aloud methods with 23 patients and 2 caregivers as they first attempted to use features of a newly launched patient portal.

Results

In navigating the portal, participants experienced basic computer barriers (eg, difficulty using a mouse), routine computer barriers (eg, mistyping, navigation issues), reading/writing barriers, and medical content barriers. Compared to participants with adequate health literacy, participants with limited health literacy required 2 additional minutes to complete each task and were more likely to experience each type of navigational barrier. They also experienced more inaccuracies in interpreting a test result and finding a treatment plan within an after-visit summary.

Discussion

When using a patient portal for the first time, participants with limited health literacy completed fewer tasks unassisted, had a higher prevalence of encountering barriers, took longer to complete tasks, and had more problems accurately interpreting medical information.

Conclusion

Our findings suggest a strong need for tailored and accessible training and support to assist all vulnerable patients and/or caregivers with portal registration and use. Measuring the health literacy of a patient population might serve as a strong proxy for identifying patients who need the most support in using health technologies.