Toward personalized care management of patients at risk

Neuvirth, Hani; Ozery-Flato, Michal; Hu, Jianying; Laserson, Jonathan; Köhn, Martin; Ebadollahi, Shahram; Rosen-Zvi, Michal

doi:10.1145/2020408.2020472

Cited by 39 publications

(42 citation statements)

References 12 publications

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“…With rare exceptions [264], existing clinical predictive models [38] use only patient predictors by assuming that a patient's outcome depends only on the patient's characteristics. In reality, a patient's outcome depends not only on the patient's characteristics but also on the treating physician's practice characteristics.…”

Section: Using Physician Practice Predictorsmentioning

confidence: 99%

A systematic review of predictive modeling for bronchiolitis

Luo

Nkoy

Gesteland

et al. 2014

International Journal of Medical Informatics

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Purpose: Bronchiolitis is the most common cause of illness leading to hospitalization in young children. At present, many bronchiolitis management decisions are made subjectively, leading to significant practice variation among hospitals and physicians caring for children with bronchiolitis. To standardize care for bronchiolitis, researchers have proposed various models to predict the disease course to help determine a proper management plan. This paper reviews the existing state of the art of predictive modeling for bronchiolitis. Predictive modeling for respiratory syncytial virus (RSV) infection is covered whenever appropriate, as RSV accounts for about 70% of bronchiolitis cases.Methods: A systematic review was conducted through a PubMed search up to April 25, 2014. The literature on predictive modeling for bronchiolitis was retrieved using a comprehensive search query, which was developed through an iterative process.Search results were limited to human subjects, the English language, and children (birth-18 years). Results:The literature search returned 2,312 references in total. After manual review, 168 of these references were determined to be relevant and are discussed in this paper. We identify several limitations and open problems in predictive modeling for bronchiolitis, and provide some preliminary thoughts on how to address them, with the hope to stimulate future research in this domain. Conclusions:Many problems remain open in predictive modeling for bronchiolitis. Future studies will need to address them to achieve optimal predictive models.

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Section: Using Physician Practice Predictorsmentioning

confidence: 99%

A systematic review of predictive modeling for bronchiolitis

Luo

Nkoy

Gesteland

et al. 2014

International Journal of Medical Informatics

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“…In the medical domain, Neuvirth et al [111] used this idea to predict the future health condition of each diabetic patient and identify the diabetic patients at high risk. For each physician, two sets of features are computed.…”

Section: Step 1: Building a Profile For Each Ihpmentioning

confidence: 99%

Open Issues in Intelligent Personal Health Record – An Updated Status Report for 2012

Luo

2013

J Med Syst

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To improve the capability and usability of the personal health record (PHR) as a tool to empower consumers in the management of their own health, we have proposed the concept of an intelligent PHR (iPHR) and built a prototype iPHR system with four functions. These four functions use various health knowledge and computer science techniques to automatically provide users with personalized healthcare information to facilitate their wellbeing. This paper discusses several open issues in iPHR, including two enhancements to an existing function and two potential new functions. The two enhancements are for automatically compiling relevant self-care activities for each health issue and automatically identifying contraindicated self-care activities, respectively. One potential new function is personalized search for individual healthcare providers. Another potential new function is personalized local search for health-related services to help maintain patients in their homes. We include some preliminary thoughts on how to address these open issues with the hope to stimulate future research work on iPHR.Keywords Personal health record  Self-care activity  Medical information extraction  Automatic contraindication identification  Personalized search for individual healthcare providers  Personalized local search for health-related services

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“…Our work will provide targeted monitoring based on patient self-reported data, patient monitoring data, and compliance monitoring and offer important recommendations as to the testing frequency that patients need to follow and necessary medication need to be provided to patients. Our work will build on that of Neuvirth et al [11] who conducted a study on recommendation based on two criteria: the need for emergency care services and the probability of the treatment producing a sub-optimal result, by exploiting data mining techniques. SIMS will assist clinicians in assessing risk of clinical deterioration through multiple domains.…”

Section: Limitations Of the Current Hf Servicesmentioning

confidence: 99%

SIMS: Self-adaptive Intelligent Monitoring System for Supporting Home-Based Heart Failure Patients

Wang

Zhang

Soar

et al. 2013

Inclusive Society: Health and Wellbeing in the Community, and Care at Home

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Abstract. This paper presents our research work to develop an advanced Selfadaptive Intelligent Monitoring System (SIMS) to help patients, families and clinicians manage chronic conditions associated with heart failure more effectively at home. SIMS takes advantages of a number of advanced technologies from software intelligence, data/knowledge retrieval, data mining and database. SIMS is able to provide a number of advanced functions. It can effectively prioritize patients, provide automatic recommendation for checking frequency and risk assessment, and carry out correlation analysis in order to pinpoint relationships between external factors and the development of patient's heart condition overtime. All these functions can significantly reduce patients' burden for checking, build up their self-confidence of health and enhance their general quality of life.

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Toward personalized care management of patients at risk

Cited by 39 publications

References 12 publications

A systematic review of predictive modeling for bronchiolitis

A systematic review of predictive modeling for bronchiolitis

Open Issues in Intelligent Personal Health Record – An Updated Status Report for 2012

SIMS: Self-adaptive Intelligent Monitoring System for Supporting Home-Based Heart Failure Patients

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