scholarly journals A Study of Management of Health Care System Using Optical Cards Stored Personal Health Data

1990 ◽  
Vol 17 (2) ◽  
pp. 204-204
Keyword(s):  
Health Care ◽  
Health Care System ◽  
Health Data ◽  
Personal Health ◽  
Care System

scholarly journals From Information Seekers to Innovators: Qualitative Analysis Describing Experiences of the Second Generation of E-Patients

10.2196/13022 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e13022 ◽  
Author(s):  
Therese Scott Duncan ◽  
Sara Riggare ◽  
Sabine Koch ◽  
Lena Sharp ◽  
Maria Hägglund
Keyword(s):  
Health Care ◽  
Health Care System ◽  
Chronic Conditions ◽  
First Generation ◽  
Second Generation ◽  
Informal Caregivers ◽  
Self Care ◽  
Health Data ◽  
Web Based ◽  
Care System

Background Current health care systems are rarely designed to meet the needs of people living with chronic conditions. However, some patients and informal caregivers are not waiting for the health care system to redesign itself. These individuals are sometimes referred to as e-patients. The first generation of e-patients used the internet for finding information and for communicating with peers. Compared with the first generation, the second generation of e-patients collects their own health data and appears to be more innovative. Objective The aim of this study was to describe the second generation of e-patients through exploration of their active engagement in their self-care and health care. Methods Semistructured interviews were conducted with 10 patients with chronic conditions and 5 informal caregivers. They were all recruited through a Web-based advertisement. Data were analyzed according to the framework analysis approach, using the 3 concepts of the self-determination theory—autonomy, relatedness, and competence—at the outset. Results Study participants were actively engaged in influencing their self-care and the health care system to improve their own health, as well as the health of others. This occurred at different levels, such as using their own experience when giving presentations and lectures to health care professionals and medical students, working as professional peers in clinical settings, performing self-tracking, contributing with innovations, and being active on social media. When interaction with health care providers was perceived as being insufficient, the participants sought support through their peers, which showed strong relatedness. Competence increased through the use of technology and learning experiences with peers. Their autonomy was important but was sometimes described as involuntary and to give up was not an option for them. Conclusions Like the first generation of e-patients, the participants frequently searched for Web-based information. However, the second generation of e-patients also produce their own health data, which they learn from and share. They also engage in the innovation of digital tools to meet health-related needs. Utilizing technological developments comes naturally to the second generation of e-patients, even if the health care system is not prepared to support them under these new circumstances.

scholarly journals Mobile Personal Health Care System for Noninvasive, Pervasive, and Continuous Blood Pressure Monitoring: Development and Usability Study

10.2196/18012 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e18012
Author(s):  
Luis J Mena ◽  
Vanessa G Félix ◽  
Rodolfo Ostos ◽  
Armando J González ◽  
Rafael Martínez-Peláez ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Health Care ◽  
Health Care System ◽  
Blood Pressure Monitoring ◽  
Cost Effective ◽  
Machine Learning Techniques ◽  
Personal Health ◽  
Usability Study ◽  
British Hypertension Society ◽  
Care System

Background Smartphone-based blood pressure (BP) monitoring using photoplethysmography (PPG) technology has emerged as a promising approach to empower users with self-monitoring for effective diagnosis and control of hypertension. Objective This study aimed to develop a mobile personal health care system for noninvasive, pervasive, and continuous estimation of BP level and variability, which is user friendly for elderly people. Methods The proposed approach was integrated by a self-designed cuffless, calibration-free, wireless, and wearable PPG-only sensor and a native purposely designed smartphone app using multilayer perceptron machine learning techniques from raw signals. We performed a development and usability study with three older adults (mean age 61.3 years, SD 1.5 years; 66% women) to test the usability and accuracy of the smartphone-based BP monitor. Results The employed artificial neural network model had good average accuracy (>90%) and very strong correlation (>0.90) (P<.001) for predicting the reference BP values of our validation sample (n=150). Bland-Altman plots showed that most of the errors for BP prediction were less than 10 mmHg. However, according to the Association for the Advancement of Medical Instrumentation and British Hypertension Society standards, only diastolic blood pressure prediction met the clinically accepted accuracy thresholds. Conclusions With further development and validation, the proposed system could provide a cost-effective strategy to improve the quality and coverage of health care, particularly in rural zones, areas lacking physicians, and areas with solitary elderly populations.

Privacy protection laws and public perception of data privacy

2018 ◽  
Vol 25 (6) ◽  
pp. 1883-1902 ◽  
Author(s):  
Jawahitha Sarabdeen ◽  
Immanuel Azaad Moonesar
Keyword(s):  
Health Care ◽  
Content Analysis ◽  
Health Care System ◽  
Data Protection ◽  
Privacy Protection ◽  
Data Privacy ◽  
Health Data ◽  
Content Type ◽  
Care System ◽  
Laws And Regulations

Purpose The move toward e-health care in various countries is envisaged to reduce the cost of provision of health care, improve the quality of care and reduce medical errors. The most significant problem is the protection of patients’ data privacy. If the patients are reluctant or refuse to participate in health care system due to lack of privacy laws and regulations, the benefit of the full-fledged e-health care system cannot be materialized. The purpose of this paper is to investigate the available e-health data privacy protection laws and the perception of the people using the e-health care facilities. Design/methodology/approach The researchers used content analysis to analyze the availability and comprehensive nature of the laws and regulations. The researchers also used survey method. Participants in the study comprised of health care professionals (n=46) and health care users (n=187) who are based in the Dubai, United Arab Emirates. The researchers applied descriptive statistics mechanisms and correlational analysis to analyze the data in the survey. Findings The content analysis revealed that the available health data protection laws are limited in scope. The survey results, however, showed that the respondents felt that they could trust the e-health services systems offered in the UAE as the data collected is protected, the rights are not violated. The research also revealed that there was no significance difference between the nationality and the privacy data statements. All the nationality agreed that there is protection in place for the protection of e-health data. There was no significance difference between the demographic data sets and the many data protection principles. Originality/value The findings on the users’ perception could help to evaluate the success in realizing current strategies and an action plan of benchmarking could be introduced.

scholarly journals From Information Seekers to Innovators: Qualitative Analysis Describing Experiences of the Second Generation of E-Patients (Preprint)

2019 ◽  
Author(s):  
Therese Scott Duncan ◽  
Sara Riggare ◽  
Sabine Koch ◽  
Lena Sharp ◽  
Maria Hägglund
Keyword(s):  
Health Care ◽  
Health Care System ◽  
Chronic Conditions ◽  
First Generation ◽  
Second Generation ◽  
Informal Caregivers ◽  
Self Care ◽  
Health Data ◽  
Web Based ◽  
Care System

BACKGROUND Current health care systems are rarely designed to meet the needs of people living with chronic conditions. However, some patients and informal caregivers are not waiting for the health care system to redesign itself. These individuals are sometimes referred to as e-patients. The first generation of e-patients used the internet for finding information and for communicating with peers. Compared with the first generation, the second generation of e-patients collects their own health data and appears to be more innovative. OBJECTIVE The aim of this study was to describe the second generation of e-patients through exploration of their active engagement in their self-care and health care. METHODS Semistructured interviews were conducted with 10 patients with chronic conditions and 5 informal caregivers. They were all recruited through a Web-based advertisement. Data were analyzed according to the framework analysis approach, using the 3 concepts of the self-determination theory—autonomy, relatedness, and competence—at the outset. RESULTS Study participants were actively engaged in influencing their self-care and the health care system to improve their own health, as well as the health of others. This occurred at different levels, such as using their own experience when giving presentations and lectures to health care professionals and medical students, working as professional peers in clinical settings, performing self-tracking, contributing with innovations, and being active on social media. When interaction with health care providers was perceived as being insufficient, the participants sought support through their peers, which showed strong relatedness. Competence increased through the use of technology and learning experiences with peers. Their autonomy was important but was sometimes described as involuntary and to give up was not an option for them. CONCLUSIONS Like the first generation of e-patients, the participants frequently searched for Web-based information. However, the second generation of e-patients also produce their own health data, which they learn from and share. They also engage in the innovation of digital tools to meet health-related needs. Utilizing technological developments comes naturally to the second generation of e-patients, even if the health care system is not prepared to support them under these new circumstances.

scholarly journals De-Identified Personal Health Care System Using Hadoop

2015 ◽  
Vol 5 (6) ◽  
pp. 1492 ◽  
Author(s):  
Dasari Madhavi ◽  
B.V. Ramana
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Information ◽  
Health Care System ◽  
Demographic Data ◽  
Data File ◽  
Personal Health Information ◽  
Map Reduce ◽  
Personal Health ◽  
Care System

Hadoop technology plays a vital role in improving the quality of healthcare by delivering right information to right people at right time and reduces its cost and time. Most properly health care functions like admission, discharge, and transfer patient data maintained in Computer based Patient Records (CPR), Personal Health Information (PHI), and Electronic Health Records (EHR). The use of medical Big Data is increasingly popular in health care services and clinical research. The biggest challenges in health care centers are the huge amount of data flows into the systems daily. Crunching this Big Data and de-identifying it in a traditional data mining tools had problems. Therefore to provide solution to the de-identifying personal health information, Map Reduce application uses jar files which contain a combination of MR code and PIG queries. This application also uses advanced mechanism of using UDF (User Data File) which is used to protect the health care dataset. De-identified personal health care system is using Map Reduce, Pig Queries which are needed to be executed on the health care dataset. The application input dataset that contains the information of patients and de-identifies their personal health care.  De-identification using Hadoop is also suitable for social and demographic data.

scholarly journals Health Data Processes: A Framework for Analyzing and Discussing Efficient Use and Reuse of Health Data With a Focus on Patient-Reported Outcome Measures (Preprint)

2018 ◽  
Author(s):  
Niels Henrik Ingvar Hjollund ◽  
José Maria Valderas ◽  
Derek Kyte ◽  
Melanie Jane Calvert
Keyword(s):  
Health Care ◽  
Data Collection ◽  
Health Care System ◽  
Personal Data ◽  
Patient Reported Outcome ◽  
Health Data ◽  
Data Availability ◽  
Data Process ◽  
Patient Reported ◽  
Care System

UNSTRUCTURED The collection and use of patient health data are central to any kind of activity in the health care system. These data may be produced during routine clinical processes or obtained directly from the patient using patient-reported outcome (PRO) measures. Although efficiency and other reasons justify data availability for a range of potentially relevant uses, these data are nearly always collected for a single specific purpose. The health care literature reflects this narrow scope, and there is limited literature on the joint use of health data for daily clinical use, clinical research, surveillance, and administrative purposes. The aim of this paper is to provide a framework for discussing the efficient use of health data with a specific focus on the role of PRO measures. PRO data may be used at an individual patient level to inform patient care or shared decision making and to tailor care to individual needs or group-level needs as a complement to health record data, such as that on mortality and readmission, in order to inform service delivery and measure the real-world effectiveness of treatment. PRO measures may be used either for their own sake, to provide valuable information from the patient perspective, or as a proxy for clinical data that would otherwise not be feasible to collect. We introduce a framework to analyze any health care activity that involves health data. The framework consists of four data processes (patient identification, data collection, data aggregation and data use), further structured into two dichotomous dimensions in each data process (level: group vs patient; timeframe: ad hoc vs systematic). This framework is used to analyze various health activities with respect to joint use of data, considering the technical, legal, organizational, and logistical challenges that characterize each data process. Finally, we propose a model for joint use of health data with data collected during follow-up as a base. Demands for health data will continue to increase, which will further add to the need for the concerted use and reuse of PRO data for parallel purposes. Repeated and uncoordinated PRO data collection for the same patient for different purposes results in misuse of resources for the patient and the health care system as well as reduced response rates owing to questionnaire fatigue. PRO data can be routinely collected both at the hospital (from inpatients as well as outpatients) and outside of hospital settings; in primary or social care settings; or in the patient’s home, provided the health informatics infrastructure is in place. In the future, clinical settings are likely to be a prominent source of PRO data; however, we are also likely to see increased remote collection of PRO data by patients in their own home (telePRO). Data collection for research and quality surveillance will have to adapt to this circumstance and adopt complementary data capture methods that take advantage of the utility of PRO data collected during daily clinical practice. The European Union’s regulation with respect to the protection of personal data—General Data Protection Regulation—imposes severe restrictions on the use of health data for parallel purposes, and steps should be taken to alleviate the consequences while still protecting personal data against misuse.

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