Enhancing Web-Based Kidney Disease Prevention Messages for Hispanics Using Targeting and Tailoring

BACKGROUND Supporting patients to self-manage their chronic kidney disease (CKD) has been identified as a research priority by patients with CKD and those that care for them. Self-management has been shown to slow CKD progression and improve the quality of life for individuals living with the disease. Previous work has identified a need for a person-centered, theory-informed web-based tool for CKD self-management that can be individualized to a patient’s unique situation, priorities, and preferences. We addressed this gap using an Integrated Knowledge Translation method and patient engagement principles. OBJECTIVE The aim of this study was to implement the systematic co-design and usability testing of a web-based self-management prototype for adults with CKD (non-dialysis, non-transplant) and their caregivers to enhance self-management support. METHODS A multi-step, iterative system development cycle was used to co-design and test My Kidneys My Health prototype. The 3-step process included: (1) creating website features and content using two sequential focus groups with patients with CKD and caregivers; (2) heuristic testing using Nielsen’s 10 heuristic principles; (3) usability testing through in-person 60-minute interviews with patients with CKD and a caregiver. Patients with CKD, caregivers, clinicians, researchers, software developers, graphic designers, and policy makers were involved in all steps of this study. RESULTS In step 1, 18 participants (14 patients and 4 caregivers) attended one of the two sequential focus groups. The participants provided specific suggestions for simplifying navigation, as well as suggestions to incorporate video, text, audio, interactive components, and visuals to convey information. Five reviewers completed the heuristic analysis (step 2), identifying items mainly related to navigation and functionality. Five participants completed usability testing (step 3) and provided feedback on video production, navigation, features and functionality, and branding. Participants reported visiting the website repeatedly for the following features: personalized food tool, my health care provider question list, symptom guidance based on CKD severity, and medication advice. Usability was high, with a mean System Usability Score of 90 out of 100. CONCLUSIONS My Kidneys My Health prototype is a systematically developed, multi-faceted CKD self-management web-based support tool guided by theory and preferences of patients with CKD and their caregivers. The website is user-friendly and provides features that improve the user experience by tailoring the content and resources to their needs. A feasibility study will provide insight into the acceptability of and engagement with the prototype, and identify preliminary patient reported outcomes (e.g., self-efficacy), as well as potential factors related to implementation. This work is relevant given the shift to virtual care during a pandemic era, providing patients with support when in-person care is restricted. CLINICALTRIAL

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Sistem Pakar Diagnosa Awal Penyakit Ginjal Berbasis Web Menggunakan PHP DAN MYSQL

Jurnal Ilmiah Betrik ◽

10.36050/betrik.v8i03.72 ◽

2017 ◽

Vol 8 (03) ◽

pp. 115-122

Author(s):

Buhori Muslim ◽

Yadi ◽

Madi Harta

Keyword(s):

Expert System ◽

Kidney Disease ◽

Data Collection ◽

Programming Language ◽

System Development ◽

Health Centers ◽

Extreme Programming ◽

Consultation Process ◽

Web Based ◽

Research Interviews

The design of expert systems for diagnosis of kidney disease is to build an expert system to diagnose kidney disease that provides information on diseases of the kidney through diagnosis of symptoms felt by sufferers with Web-based programming. Currently, if people want to diagnose with doctors to hospital or other health centers and have to wait their turn or queue to consult with doctors, to facilitate the consultation process needs a system that allows people to consult quickly, precisely and accurately. In designing this system using PHP and mysql programming language. The type of data collection obtained from the place of research, interviews with an expert, books and other literature. The method used in system development is Extreme Programming method which consists of Planning, Design, Coding, Test and Release. And the results of this design is to produce a system that provides information about kidney disease and help diagnose the disease through symptoms experienced.

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A Novel Evidence-Based Predictor Tool for Hospitalization and Length of Stay: Insights from COVID19 Patients in New York City

10.1101/2021.04.24.21256042 ◽

2021 ◽

Author(s):

Maan El Halabi ◽

James Feghali ◽

Paulino Tallon de Lara ◽

Bharat Narasimhan ◽

Kam Ho ◽

...

Keyword(s):

Chronic Kidney Disease ◽

New York ◽

New York City ◽

Kidney Disease ◽

Length Of Stay ◽

Oxygen Saturation ◽

Predictive Models ◽

York City ◽

Maximum Temperature ◽

Web Based

Background: Coronavirus disease 2019 (COVID-19) has evolved into a true global pandemic infecting more than 30 million people worldwide. Predictive models for key outcomes have the potential to optimize resource utilization and patient outcome as outbreaks continue to occur worldwide. We aimed to design and internally validate a web-based calculator predictive of hospitalization and length of stay (LOS) in a large cohort of COVID-19 positive patients presenting to the Emergency Department (ED) in a New York City health system. Methods The study cohort consisted of consecutive adult (>18 years) patients presenting to the ED of one of the Mount Sinai Health System hospitals between March, 2020 and April, 2020 who were diagnosed with COVID-19. Logistic regression was utilized to construct predictive models for hospitalization and prolonged (>3 days) LOS. Discrimination was evaluated using area under the receiver operating curve (AUC). Internal validation with bootstrapping was performed, and a web-based calculator was implemented. Results The cohort consisted of 5859 patients with a hospitalization rate of 65% and a prolonged LOS rate of 75% among hospitalized patients. Independent predictors of hospitalization included older age (OR=6.29; 95% CI [1.83-2.63], >65 vs. 18-44), male sex (OR=1.35 [1.17-1.55]), chronic obstructive pulmonary disease (OR=1.74; [1.00-3.03]), hypertension (OR=1.39; [1.13-1.70]), diabetes (OR=1.45; [1.16-1.81]), chronic kidney disease (OR=1.69; [1.23-2.32]), elevated maximum temperature (OR=4.98; [4.28-5.79]), and low minimum oxygen saturation (OR=13.40; [10.59-16.96]). Predictors of extended LOS included older age (OR=1.03 [1.02-1.04], per year), chronic kidney disease (OR=1.91 [1.35-2.71]), elevated maximum temperature (OR=2.91 [2.40-3.53]), and low minimum percent oxygen saturation (OR=3.89 [3.16-4.79]). AUCs of 0.881 and 0.770 were achieved for hospitalization and LOS, respectively. A calculator was made available under the following URL: https://covid19-outcome-prediction.shinyapps.io/COVID19_Hospitalization_Calculator/ Conclusion The prediction tool derived from this study can be used to optimize resource allocation, guide quality of care, and assist in designing future studies on the triage and management of patients with COVID-19.

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