Dataset Information

Would patients undergo postoperative follow-up by using a smartphone application?

ABSTRACT:

Background

eHealth applications have been proposed as an alternative to monitor patients in frequent intervals or over long distances. The aim of this study was to assess whether patients would accept an application on their smartphone to be monitored by their physicians.

Methods

During September 2017 and December 2017 a survey amongst smartphone users was conducted via paper and web-based questionnaires.

Results

More than half of the 962 participants (54%) were older than 55 years of age. The majority of the participants (68.7%) would accept a follow-up by a smartphone application obtaining personal healthcare data. 72.6% of all patients older than 55 years of age would use the application. The most prevalent reason against installing the application was data protection. Patients being currently treated in an orthopaedic practice and pedestrians were more eager to accept a follow-up by a mobile app than participants from social media.

Conclusion

The majority of participants would accept a mobile application, collecting personal health-related data for postoperative follow-up, and saw a direct benefit for the patient in such an application.

SUBMITTER: Scherer J

PROVIDER: S-EPMC7542718 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Would patients undergo postoperative follow-up by using a smartphone application?

Scherer Julian J Keller Frank F Pape Hans-Christoph HC Osterhoff Georg G

BMC surgery 20201007 1

<h4>Background</h4>eHealth applications have been proposed as an alternative to monitor patients in frequent intervals or over long distances. The aim of this study was to assess whether patients would accept an application on their smartphone to be monitored by their physicians.<h4>Methods</h4>During September 2017 and December 2017 a survey amongst smartphone users was conducted via paper and web-based questionnaires.<h4>Results</h4>More than half of the 962 participants (54%) were older than ...[more]

PMID: 33028309

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Project description:ImportanceThe Centers for Medicare and Medicaid Services have implemented penalties for hospitals with above-average readmission rates under the Hospital Readmissions Reductions Program. These changes will likely be extended to affect postoperative readmissions in the future.ObjectivesTo identify variables that place patients at risk for readmission, develop a predictive nomogram, and validate this nomogram.Design, setting, and participantsRetrospective review and prospective validation of a predictive nomogram. A predictive nomogram was developed with the linear predictor method using the American College of Surgeons National Surgical Quality Improvement Program database paired with institutional billing data for patients who underwent nonemergent inpatient general surgery procedures. The nomogram was developed from August 1, 2006, through December 31, 2011, in 2799 patients and prospectively validated from November 1, 2013, through December 19, 2013, in 255 patients at a single academic institution. Area under the curve and positive and negative predictive values were calculated.Main outcomes and measuresThe outcome of interest was readmission within 30 days of discharge following an index hospitalization for a surgical procedure.ResultsBleeding disorder (odds ratio, 2.549; 95% CI, 1.464-4.440), long operative time (odds ratio, 1.601; 95% CI, 1.186-2.160), in-hospital complications (odds ratio, 16.273; 95% CI, 12.028-22.016), dependent functional status, and the need for a higher level of care at discharge (odds ratio, 1.937; 95% CI, 1.176-3.190) were independently associated with readmission. The nomogram accurately predicted readmission (C statistic = 0.756) in a prospective evaluation. The negative predictive value was 97.9% in the prospective validation, while the positive predictive value was 11.1%.Conclusions and relevanceDevelopment of an online calculator using this predictive model will allow us to identify patients who are at high risk for readmission at the time of discharge. Patients with increased risk may benefit from more intensive postoperative follow-up in the outpatient setting.

Dataset Information

Would patients undergo postoperative follow-up by using a smartphone application?

Background

Methods

Results

Conclusion

Publications

Would patients undergo postoperative follow-up by using a smartphone application?

Similar Datasets

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