1.Social Media in Clinical Practice.
Healthcare Informatics Research 2015;21(2):138-140
No abstract available.
Social Media*
2.Development of Individual Survival Estimating Program for Cancer Patients' Management.
Healthcare Informatics Research 2015;21(2):134-137
OBJECTIVES: The goal of this report is to present an individual patient's survival estimation curve using the each institution's survival data after Cox proportional hazard analysis. METHODS: The program was developed in three parts: input of basic data from Cox proportional hazard analysis, input of individual patient's covariates, and presentation of individual patient's survival curve. In the first part, the average survival rates with each survival time were entered as the means of covariates using the results of Cox proportional hazard analysis. In the second part, the individual patient's values of each covariate were entered for the calculation of survival estimation. In the third part, the survival curve was displayed according to the input data. RESULTS: The data of 2,652 breast cancer patients were analyzed. Cox regression analysis was conducted using the covariates of age, tumor size, N stage, and M stage. The individual patient's survival curve was presented using the basic data and covariate factors. In the breast cancer patients, the program presented survival curves according to each patient's age, tumor size, N stage, and M stage. The data of 251 thyroid cancer patients were analyzed by a similar method. CONCLUSIONS: We developed a program to present individual survival curves of cancer patients. This program will be useful for clinicians to assist their decision-making and discussion with patients.
Breast Neoplasms
;
Humans
;
Prognosis
;
Survival Rate
;
Thyroid Neoplasms
3.Effects of Mobile Phone-Based App Learning Compared to Computer-Based Web Learning on Nursing Students: Pilot Randomized Controlled Trial.
Healthcare Informatics Research 2015;21(2):125-133
OBJECTIVES: This study aimed to determine the effect of mobile-based discussion versus computer-based discussion on self-directed learning readiness, academic motivation, learner-interface interaction, and flow state. METHODS: This randomized controlled trial was conducted at one university. Eighty-six nursing students who were able to use a computer, had home Internet access, and used a mobile phone were recruited. Participants were randomly assigned to either the mobile phone app-based discussion group (n = 45) or a computer web-based discussion group (n = 41). The effect was measured at before and after an online discussion via self-reported surveys that addressed academic motivation, self-directed learning readiness, time distortion, learner-learner interaction, learner-interface interaction, and flow state. RESULTS: The change in extrinsic motivation on identified regulation in the academic motivation (p = 0.011) as well as independence and ability to use basic study (p = 0.047) and positive orientation to the future in self-directed learning readiness (p = 0.021) from pre-intervention to post-intervention was significantly more positive in the mobile phone app-based group compared to the computer web-based discussion group. Interaction between learner and interface (p = 0.002), having clear goals (p = 0.012), and giving and receiving unambiguous feedback (p = 0.049) in flow state was significantly higher in the mobile phone app-based discussion group than it was in the computer web-based discussion group at post-test. CONCLUSIONS: The mobile phone might offer more valuable learning opportunities for discussion teaching and learning methods in terms of self-directed learning readiness, academic motivation, learner-interface interaction, and the flow state of the learning process compared to the computer.
Cellular Phone
;
Humans
;
Internet
;
Learning*
;
Mobile Applications
;
Motivation
;
Students, Nursing*
4.Effects of Health Information Technology on Malpractice Insurance Premiums.
Healthcare Informatics Research 2015;21(2):118-124
OBJECTIVES: The widespread adoption of health information technology (IT) will help contain health care costs by decreasing inefficiencies in healthcare delivery. Theoretically, health IT could lower hospitals' malpractice insurance premiums (MIPs) and improve the quality of care by reducing the number and size of malpractice. This study examines the relationship between health IT investment and MIP using California hospital data from 2006 to 2007. METHODS: To examine the effect of hospital IT on malpractice insurance expense, a generalized estimating equation (GEE) was employed. RESULTS: It was found that health IT investment was not negatively associated with MIP. Health IT was reported to reduce medical error and improve efficiency. Thus, it may reduce malpractice claims from patients, which will reduce malpractice insurance expenses for hospitals. However, health IT adoption could lead to increases in MIPs. For example, we expect increases in MIPs of about 1.2% and 1.5%, respectively, when health IT and labor increase by 10%. CONCLUSIONS: This study examined the effect of health IT investment on MIPs controlling other hospital and market, and volume characteristics. Against our expectation, we found that health IT investment was not negatively associated with MIP. There may be some possible reasons that the real effect of health IT on MIPs was not observed; barriers including communication problems among health ITs, shorter sample period, lower IT investment, and lack of a quality of care measure as a moderating variable.
California
;
Delivery of Health Care
;
Electronic Health Records
;
Health Care Costs
;
Health Information Systems
;
Humans
;
Insurance*
;
Investments
;
Malpractice*
;
Medical Errors
;
Medical Informatics*
5.Wave Detection in Acceleration Plethysmogram.
Healthcare Informatics Research 2015;21(2):111-117
OBJECTIVES: Acceleration plethysmogram (APG) obtained from the second derivative of photoplethysmography (PPG) is used to predict risk factors for atherosclerosis with age. This technique is promising for early screening of atherosclerotic pathologies. However, extraction of the wave indices of APG signals measured from the fingertip is challenging. In this paper, the development of a wave detection algorithm including a preamplifier based on a microcontroller that can detect the a, b, c, and d wave indices is proposed. METHODS: The 4th order derivative of a PPG under real measurements of an APG waveform was introduced to clearly separate the components of the waveform, and to improve the rate of successful wave detection. A preamplifier with a Sallen-Key low pass filter and a wave detection algorithm with programmable gain control, mathematical differentials, and a digital IIR notch filter were designed. RESULTS: The frequency response of the digital IIR filter was evaluated, and a pulse train consisting of a specific area in which the wave indices existed was generated. The programmable gain control maintained a constant APG amplitude at the output for varying PPG amplitudes. For 164 subjects, the mean values and standard deviation of the a wave index corresponding to the magnitude of the APG signal were 1,106.45 and +/-47.75, respectively. CONCLUSIONS: We conclude that the proposed algorithm and preamplifier designed to extract the wave indices of an APG in real-time are useful for evaluating vascular aging in the cardiovascular system in a simple healthcare device.
Acceleration*
;
Aging
;
Atherosclerosis
;
Cardiovascular System
;
Delivery of Health Care
;
Mass Screening
;
Pathology
;
Photoplethysmography
;
Risk Factors
;
Vascular Stiffness
6.Impact of Doctors' Resistance on Success of Drug Utilization Review System.
Jong Soo CHOI ; Seong Hyeon YUN ; Dongsoo KIM ; Seung Woo PARK
Healthcare Informatics Research 2014;20(2):99-108
OBJECTIVES: The drug utilization review (DUR) system, which checks any conflict event of medications, contributes to improve patient safety. One of the important barriers in its adoption is doctors' resistance. This study aimed to analyze the impacts of doctors' resistance on the success of the DUR system. METHODS: This study adopted an augmented the DeLone and McLean Information System (D&M IS) Success Model (2003), which used doctors' resistance as a socio-technological measure. This study framework is the same as that of the D&M IS Success Model in that it is based on qualities, such as system, information, and services. The major difference is that this study excluded the variable 'use' because it was not statistically significant for mandatory systems. A survey of doctors who used computers to enter prescriptions was conducted at a Korean tertiary hospital in February 2012. RESULTS: This study is very meaningful in that it is the first study to explore the success factors of the DUR system associated with doctors' resistance. Doctors' resistance to the DUR system was not statistically associated with user usefulness, whereas it affected user satisfaction. CONCLUSIONS: The results indicate that doctors still complain of discomfort in using the DUR system in the outpatient clinical setting, even though they admit that it contributes to patient safety. To mitigate doctors' resistance and raise user satisfaction, more opinions from doctors regarding the DUR system have to be considered and have to be reflected in the system.
Drug Utilization Review*
;
Humans
;
Information Systems
;
Medicare Assignment
;
Outpatients
;
Patient Safety
;
Prescriptions
;
Tertiary Care Centers
7.Development of Health Information Search Engine Based on Metadata and Ontology.
Tae Min SONG ; Hyeoun Ae PARK ; Dal Lae JIN
Healthcare Informatics Research 2014;20(2):88-98
OBJECTIVES: The aim of the study was to develop a metadata and ontology-based health information search engine ensuring semantic interoperability to collect and provide health information using different application programs. METHODS: Health information metadata ontology was developed using a distributed semantic Web content publishing model based on vocabularies used to index the contents generated by the information producers as well as those used to search the contents by the users. Vocabulary for health information ontology was mapped to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and a list of about 1,500 terms was proposed. The metadata schema used in this study was developed by adding an element describing the target audience to the Dublin Core Metadata Element Set. RESULTS: A metadata schema and an ontology ensuring interoperability of health information available on the internet were developed. The metadata and ontology-based health information search engine developed in this study produced a better search result compared to existing search engines. CONCLUSIONS: Health information search engine based on metadata and ontology will provide reliable health information to both information producer and information consumers.
Consumer Health Information
;
Information Systems
;
Internet
;
Search Engine*
;
Semantics
;
Systematized Nomenclature of Medicine
;
Vocabulary
8.Massive Open Online Course for Health Informatics Education.
Healthcare Informatics Research 2014;20(2):81-87
OBJECTIVES: This paper outlines a new method of teaching health informatics to large numbers of students from around the world through a Massive Open Online Course (MOOC). METHODS: The Health Informatics Forum is one of examples of MOOCs through a social networking site for educating health informatics students and professionals. It is running a MOOC for students from around the world that uses creative commons licenced content funded by the US government and developed by five US universities. The content is delivered through narrated lectures with slides that can be viewed online with discussion threads on the forum for class interactions. Students can maintain a professional profile, upload photos and files, write their own blog posts and post discussion threads on the forum. RESULTS: The Health Informatics Forum MOOC has been accessed by 11,316 unique users from 127 countries from August 2, 2012 to January 24, 2014. Most users accessed the MOOC via a desktop computer, followed by tablets and mobile devices and 55% of users were female. Over 400,000 unique users have now accessed the wider Health Informatics Forum since it was established in 2008. CONCLUSIONS: Advances in health informatics and educational technology have both created a demand for online learning material in health informatics and a solution for providing it. By using a MOOC delivered through a social networking platform it is hoped that high quality health informatics education will be able to be delivered to a large global audience of future health informaticians without cost.
Blogging
;
Computer-Assisted Instruction
;
Education*
;
Education, Distance
;
Education, Professional
;
Educational Technology
;
Female
;
Financial Management
;
Hope
;
Humans
;
Informatics*
;
Learning
;
Lectures
;
Medical Informatics
;
Running
;
Social Media
;
Tablets
9.Recent Movement on Education and Training in Health Informatics.
Healthcare Informatics Research 2014;20(2):79-80
No abstract available.
Education*
;
Informatics*
10.Book Review: Spatial Analysis in Epidemiology.
Healthcare Informatics Research 2013;19(2):148-149
No abstract available.
Spatial Analysis