Introduction: It is currently unknown which data sources from the clinical history, or combination thereof, should be evaluated to achieve the most complete calculation of postoperative complications (PC). The objectives of this study were: to analyze the morbidity and mortality of 200 consecutive patients undergoing major surgery, to determine which data sources or combination collect the maximum morbidity, and to determine the accuracy of the morbidity reflected in the discharge report.
Methods: Observational and prospective cohort study. The sum of all PC found in the combined review of medical notes, nursing notes, and a specific form was considered the gold standard. PC were classified according to the Clavien Dindo Classification and the Comprehensive Complication Index (CCI).
Results: The percentage of patients who presented PC according to the gold standard, medical notes, nursing notes and form were: 43.5%, 37.5%, 35% and 18.7% respectively. The combination of sources improved CCI agreement by 8%-40% in the overall series and 39.1-89.7 % in patients with PC. The correct recording of PC was inversely proportional to the complexity of the surgery, and the combination of sources increased the degree of agreement with the gold standard by 35 %-67.5% in operations of greater complexity. The CDC and CCI of the discharge report coincided with the gold-standard values in patients with PC by 46.8% and 18.2%, respectively.
Conclusions: The combination of data sources, particularly medical and nursing notes, considerably increases the quantification of PC in general, most notably in complex interventions.
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http://dx.doi.org/10.1016/j.cireng.2024.05.001 | DOI Listing |
JMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
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View Article and Find Full Text PDFJMIR Hum Factors
January 2025
Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Cheras Kuala Lumpur, Malaysia.
Background: Evaluating digital health service delivery in primary health care requires a validated questionnaire to comprehensively assess users' ability to implement tasks customized to the program's needs.
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Methods: A cross-sectional study was conducted in 2 phases.
JMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
View Article and Find Full Text PDFJMIR Form Res
January 2025
School of Psychology, Ulster University, Coleraine, United Kingdom.
Background: Psychologists have developed frameworks to understand many constructs, which have subsequently informed the design of digital mental health interventions (DMHIs) aimed at improving mental health outcomes. The science of happiness is one such domain that holds significant applied importance due to its links to well-being and evidence that happiness can be cultivated through interventions. However, as with many constructs, the unique ways in which individuals experience happiness present major challenges for designing personalized DMHIs.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background: Lifestyle interventions have been acknowledged as effective strategies for preventing type 2 diabetes mellitus (T2DM). However, the accessibility of conventional face-to-face interventions is often limited. Digital health intervention has been suggested as a potential solution to overcome the limitation.
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