Data mining and electronic devices applied to quality of life related to health data

Big data analytics has been introduced as a set of scalable, distributed algorithms optimized for analysis of massive data in parallel. There are many prospective applications of data mining in healthcare. In this chapter, the authors investigate whether health data exhibits characteristics of big data, and accordingly, whether big data analytics can leverage the data mining applications in healthcare. To answer this interesting question, potential applications are divided into four categories, and each category into sub-categories in a tree structure. The available types of health data are specified, with a discussion of the applicable dimensions of big data for each sub-category. The authors conclude that big data analytics can provide more advantages for the quality of analysis in particular categories of applications of data mining in healthcare, while having less efficacy for other categories.

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Identification of publicly available data sources to inform the conduct of Health Technology Assessment in India

F1000Research ◽

10.12688/f1000research.14041.1 ◽

2018 ◽

Vol 7 ◽

pp. 245 ◽

Cited By ~ 7

Author(s):

Laura Downey ◽

Neethi Rao ◽

Lorna Guinness ◽

Miqdad Asaria ◽

Shankar Prinja ◽

...

Keyword(s):

Quality Of Life ◽

Health Technology Assessment ◽

Technology Assessment ◽

Service Use ◽

Health Technology ◽

Health Data ◽

Data Sources ◽

Quality Data ◽

Epidemiological Information

Background: Health technology assessment (HTA) provides a globally-accepted and structured approach to synthesising evidence for cost and clinical effectiveness alongside ethical and equity considerations to inform evidence-based priorities. India is one of the most recent countries to formally commit to institutionalising HTA as an integral component of the heath resource allocation decision-making process. The effective conduct of HTA depends on the availability of reliable data. Methods: We draw from our experience of collecting, synthesizing, and analysing health-related datasets in India and internationally, to highlight the complex requirements for undertaking HTA, and explore the availability of such data in India. We first outlined each of the core data components required for the conduct of HTA, and their availability in India, drawing attention to where data can be accessed, and different ways in which researchers can overcome the challenges of missing or low quality data. Results: We grouped data into the following categories: clinical efficacy; cost; epidemiology; quality of life; service use/consumption; and equity. We identified numerous large local data sources containing epidemiological information. There was a marked absence of other locally-collected data necessary for informing HTA, particularly data relating to cost, service use, and quality of life. Conclusions: The introduction of HTA into the health policy space in India provides an opportunity to comprehensively assess the availability and quality of health data capture across the country. While epidemiological information is routinely collected across India, other data inputs necessary for HTA are not readily available. This poses a significant bottleneck to the efficient generation and deployment of HTA into the health decision space. Overcoming these data gaps by strengthening the routine collection of comprehensive and verifiable health data will have important implications not only for embedding economic analyses into the priority setting process, but for strengthening the health system as a whole.

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Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology (Preprint)

10.2196/preprints.7952 ◽

2017 ◽

Author(s):

Rachel R.J. Kalf ◽

Amr Makady ◽

Renske M.T. ten Ham ◽

Kim Meijboom ◽

Wim G. Goettsch ◽

...

Keyword(s):

Quality Of Life ◽

Social Media ◽

Adverse Events ◽

Real World ◽

Relative Effectiveness ◽

Health Data ◽

Real World Data ◽

World Data ◽

Effectiveness Assessment

BACKGROUND An element of health technology assessment constitutes assessing the clinical effectiveness of drugs, generally called relative effectiveness assessment. Little real-world evidence is available directly after market access, therefore randomized controlled trials are used to obtain information for relative effectiveness assessment. However, there is growing interest in using real-world data for relative effectiveness assessment. Social media may provide a source of real-world data. OBJECTIVE We assessed the extent to which social media-generated health data has provided insights for relative effectiveness assessment. METHODS An explorative literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify examples in oncology where health data were collected using social media. Scientific and grey literature published between January 2010 and June 2016 was identified by four reviewers, who independently screened studies for eligibility and extracted data. A descriptive qualitative analysis was performed. RESULTS Of 1032 articles identified, eight were included: four articles identified adverse events in response to cancer treatment, three articles disseminated quality of life surveys, and one study assessed the occurrence of disease-specific symptoms. Several strengths of social media-generated health data were highlighted in the articles, such as efficient collection of patient experiences and recruiting patients with rare diseases. Conversely, limitations included validation of authenticity and presence of information and selection bias. CONCLUSIONS Social media may provide a potential source of real-world data for relative effectiveness assessment, particularly on aspects such as adverse events, symptom occurrence, quality of life, and adherence behavior. This potential has not yet been fully realized and the degree of usefulness for relative effectiveness assessment should be further explored.

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