The State of Data in Healthcare: Path Towards Standardization

Feldman, Keith; Johnson, Reid A.; Chawla, Nitesh V.

doi:10.1007/s41666-018-0019-8

Cited by 19 publications

(15 citation statements)

References 92 publications

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“…The model indicates that big data analytics enabled by wearable technology products can transform the key dynamic capabilities of a health insurance firm into distinct service and knowledge A study of health insurance firms advantages resulting in superior firm performance. Further, it provides significant support to the paradigm shift that wearable technology can bring to the field of healthcare delivery through a better understanding of the complex nature of health data (Feldman et al, 2018). The unique nature of health insurance and its difference from other forms of insurance can be summed up in the remarks from a private sector CXO:…”

Section: Jsit 212mentioning

confidence: 95%

Integrating wearable technology products and big data analytics in business strategy

Nayak

Bhattacharyya

Krishnamoorthy

2019

JSIT

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Purpose This study aims to explore the impact of the adoption of wearable technology products for Indian health insurance firms. It identifies the key dynamic capabilities that health insurance firms should build to manage big data generated by wearable technology so as to attain a competitive advantage. Design/methodology/approach A qualitative exploratory study using in-depth personal interviews with 53 Indian health insurance experts was conducted with a semi-structured questionnaire. The data were coded using holistic and pattern codes and then analyzed using the content analysis technique. The findings were based on the thematic and relational intensity analysis of the codes. Findings An empirical model was established where all the propositions were strongly established except for the moderate relationship between wearable technology adoption and product innovation. The study established the nature of the interaction of variables on technology policy, organizational culture, strategic philosophy, product innovation, knowledge management and customer service quality with wearable technology adoption and also ascertained its influence on firm performance and competitive advantage. Research limitations/implications From a dynamic capabilities perspective, this study deliberates on wearable technology adoption in the health insurance context. It also explicates the relationship between the variables on technology policy, organizational culture, strategic philosophy, product innovation, knowledge management and customer service quality with wearable technology adoption on firm performance. Originality/value This study is one of the first studies to add the context of wearable technology and health insurance to the existing body of knowledge on dynamic capabilities and sustainable competitive advantage for the service sector. It would help existing and prospective players in adopting or setting up appropriate business models.

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Section: Jsit 212mentioning

confidence: 95%

Integrating wearable technology products and big data analytics in business strategy

Nayak

Bhattacharyya

Krishnamoorthy

2019

JSIT

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“…As the volume of public health data expands and data are more interconnected, a broad range of data is being used to support research and inform global health policies and practice. We expand on an existing framework ( 21 ) to provide a classification of data into four broad archetypes (1) patient data, (2) health systems data, (3) routine public health data, and (4) health research data. It should be noted that this categorization is used to describe how these data are generated and not necessarily their application or use.…”

Section: Data Archetypesmentioning

confidence: 99%

Data Sharing and Global Public Health: Defining What We Mean by Data

Schwalbe¹,

Wahl²,

Song³

et al. 2020

Front. Digit. Health

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“…[30]. Given the introduction of IT technology and the various needs associated with patient information, standardization of patient data is under progress [31,32]. Furthermore, the collected patient data is developed such that it can be checked anytime and anywhere through the entire network of medical institutions.…”

Section: Vital Sign Sensing Device Trend and Data Transmissionmentioning

confidence: 99%

Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

Bae

Kwon

Kim

2020

Sensors

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An important function in the future healthcare system involves measuring a patient’s vital signs, transmitting the measured vital signs to a smart device or a management server, analyzing it in real-time, and informing the patient or medical staff. Internet of Medical Things (IoMT) incorporates information technology (IT) into patient monitoring device (PMD) and is developing traditional measurement devices into healthcare information systems. In the study, a portable ubiquitous-Vital (u-Vital) system is developed and consists of a Vital Block (VB), a small PMD, and Vital Sign Server (VSS), which stores and manages measured vital signs. Specifically, VBs collect a patient’s electrocardiogram (ECG), blood oxygen saturation (SpO2), non-invasive blood pressure (NiBP), body temperature (BT) in real-time, and the collected vital signs are transmitted to a VSS via wireless protocols such as WiFi and Bluetooth. Additionally, an efficient R-point detection algorithm was also proposed for real-time processing and long-term ECG analysis. Experiments demonstrated the effectiveness of measurement, transmission, and analysis of vital signs in the proposed portable u-Vital system.

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The State of Data in Healthcare: Path Towards Standardization

Cited by 19 publications

References 92 publications

Integrating wearable technology products and big data analytics in business strategy

Integrating wearable technology products and big data analytics in business strategy

Data Sharing and Global Public Health: Defining What We Mean by Data

Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

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