patient portal readmission rates pubmed

Can patient portals reduce hospital readmissions?

Decreasing 30-day readmission rates. Decreasing 30-day readmission rates. Decreasing 30-day readmission rates Am J Nurs. 2011 Nov;111(11):65-9. doi: 10.1097/01.NAJ.0000407308.53587.02. ... Nurse-Patient Relations* Nursing Assessment / methods* Outcome and Process Assessment, Health Care ...

Are 2011 readmission rates lower at academic medical centers?

Of those who used the portal, active users had a higher odds of being readmitted within 30 days. Health care systems should consider strategies to: (1) increase overall use of patient portals and (2) target patients with the highest comorbidity scores to reduce hospital readmissions.

What is the readmission rate for AMI patients?

Feb 26, 2021 · However, recent research by Sharma and colleagues and Lin et al. found that patient portal access is still underused, [12,47] suggesting there remains a need for policymakers and other stakeholders to intervene and incentivize portal adoption and use in order to realize greater reduction in readmission risk. Given the positive correlation among ...

What drives readmissions within 30 days of hospitalization?

Jun 06, 2016 · Of 2,975 eligible patients, 83.4% were non-users; 8.6% were light users; and 8.0% were active users of My UNC Chart. The messaging feature was used most often. For patients who were active users, the odds of being readmitted within 30 days was 66% greater than patients who were non-users (p<0.05).

How does health information technology reduce readmission risk?

Health information technology (IT) is often proposed as a solution to fragmentation of care , and has been hypothesized to reduce read mission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.#N#To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.#N#This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.#N#A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = −0.086; 95% Confidence Interval, −0.162 to −0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.#N#These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial – perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.

How much money does the US government give to improve health information technology?

Through the Health Information Technology for Economic and Clinical Health Act, the United States (US) government has provided more than $27 billion to subsidize the adoption of health Information Technology (IT) capabilities, under the premise that improved information capture and transfer across various care settings will improve patient outcomes. [1–3]

How many items are in the AHA IT supplement survey?

From the AHA IT supplement survey, we identified 55 survey items, also referred to as indicators, to conduct the exploratory and confirmatory factor analyses (EFA and CFA) in order to derive and validate specific factors representing hospital health IT capabilities that were plausibly clinically important to reducing readmissions. These items were selected from various sections of the AHA IT supplement survey, including meaningful use functionalities (topic 2, 19 items), health information exchange functionalities (topic 3, 24 items), and patient engagement functionalities (topics 7 and 8, 8 and 4 items, respectively).

How many hospitals were there in 2013?

As displayed in Figure 1, there were 3,283 hospitals in the 2013 AHA annual survey IT supplement dataset. Of these hospitals, 62 were federal hospitals and were excluded. Among the 3,221 non-federal hospitals remaining, 37% were in rural areas; 28% were teaching hospitals; 50% were relatively small hospitals with less than 100 beds (including 23% critical access hospitals), 14% were relatively large hospitals with more than 400 beds, and the rest (36%) were medium-sized hospitals. Means and standard deviations (SD) are reported in Figure 1 because non-normality is not an issue for the distributions of data across the 1000 pairs of randomly-split samples, as confirmed by the results of the Shapiro–Wilk test ( P = .73). After excluding those without hospital Medicare Provider IDs and RSRRs, a mean of 1,335 hospitals (SD = 27.4) were linked to the CMS Hospital Compare database, representing our final analytic dataset.

How many derivation sets were used for EFA?

The 1000 derivation sets were used to conduct the EFA. The estimation of the tetrachoric correlation matrix converged for 619 of them. For the factor structure, we reported medians and IQRs because the Shapiro-Wilk test revealed P values of <.05 for more than half of the variables that loaded on the seven factors, demonstrating non-normality. On the basis of the median loading values and IQRs for the factor structure suggested by EFA (see Appendix A, http://links.lww.com/MD/F672 ), and the loading frequencies (see Appendix B, http://links.lww.com/MD/F673 ), we retained 54 survey items with high loadings, and deleted the one with low median factor loading and frequency.

Abstract

Background: The impact of web-based patient portals on patient outcomes—specifically hospital readmissions in patients with atrial fibrillation (AF)—remains understudied.

INTRODUCTION

Atrial fibrillation (AF), one of the most commonly encountered arrhythmias, is known to cause frequent hospitalizations, readmissions, and increased mortality among patients in the United States.

METHODS

The Baylor Scott and White Research Institute Institutional Review Board approved this retrospective cohort study. Informed consent of participants was not required, as this was a retrospective, minimal-risk study.

RESULTS

Data were collected for 11,334 patients with individual hospital admissions with either a primary or secondary diagnosis of AF during the study period. Baseline demographics are detailed in Table 1.

DISCUSSION

Web-based patient portals are commonly believed to be an advance in patient care, but the implications of using this patient-provider link are difficult to ascertain and have yet to be fully comprehended.

CONCLUSION

The results of this study demonstrate higher rates of hospital readmissions in patients with AF who were users of the online patient portal MyChart vs nonusers. Online patient portals provide patients unique access to their providers that may potentially have unintended consequences such as increased readmissions.

ACKNOWLEDGMENTS

The authors have no financial or proprietary interest in the subject matter of this article.