• Journal of Service Research and Studies
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• v.13 no.3
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• pp.147-159
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• 2023

This study is a study to develop a model for measurement and processing of experience data, which is emerging as a core value in quality management of medical services. In the theoretical background, a literature study was conducted on the importance of experience in medical service, measurement and processing of experience data, and realization of patient-centeredness. Based on these literature and theoretical background research results, operational definitions were performed for the following four research variables, and statistical tests were conducted. Hypothesis 1 is the effect of measuring experience data from the perspective of three factors on persona modeling, Hypothesis 2 is the effect of persona modeling on service blueprint visualization, Hypothesis 3 is the effect of service blueprint visualization on realization of patient-centeredness, and Hypothesis 4 is persona modeling This is the effect that modeling has on the realization of patient-centeredness. After data-based testing of factor analysis, reliability analysis, and correlation analysis, all four hypotheses were adopted as a result of verification using regression analysis. In conclusion, in an era where it is difficult to recognize the value of having only good medical staff and medical equipment in hospitals, it was possible to grasp the meaning that what kind of medical service experience is continuously obtained is more important to patients than the effectiveness of medical staff and medical equipment. In the era of the service economy, the core of hospital service competitiveness is providing attractive experiences, which is the real strength of hospitals, so the measurement and processing of experience data, which is the subject of this study, will have an important meaning in realizing patient-centeredness and realizing smart hospitals.

• Asian Oncology Nursing
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• v.12 no.2
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• pp.186-193
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• 2012

Purpose: The purpose of this narrative study was to understand how family caregivers interpreted themselves life during caring for dying patients with gliobalstoma, and how they integrated these experiences into their personal biographies. Methods: Three family caregivers were recruited for the study. Data were collected through a series of audio-taped unstructured interviews and conversations with participants. The interviews and observation were conducted between October and November, 2011. Data were analyzed using psychosocial analytical methods that combined case based, in-depth staged analysis of narratives. Results: The life experiences of the family caregivers with a dying family member were summarized as, in their own voices, 'the repetition of gliobalstoma,' 'a smart patient,' 'being obsessed with rehabilitation treatment,' 'the frustration from nothing but just looking at the suffering of the patient,' and 'a stubborn son'. Conclusion: Caregiving was characterised by various roles and life changes from the moment of diagnosis. Family caregivers of brain tumor reported experiences similar to those described by caregivers of people with other cancers. What differed for this group was the rapidity of change and the need for immediate information and support to assist with caring for a person with high-grade glioma.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.261-267
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• 2016

As IoT technology has gained the attention all around the world, the development for various services of healthcare, smart city, agriculture, and defense based on IoT is in progress. However, it is likely that healthcare services based on IoT have a problem of being leaked of patients' biological information by a third party and that risks patients' lives. In this paper, an IoT health care service managing model based on location sensor is proposed, which secures the biological information of a patient and simplifies the procedure to process the treatment and administration steps by using the data resources sensed. Even when an emergency occurs, this proposed model can respond quickly using the location information of the patient, which enables the staff in the hospital to locate the patient in real time. In addition, there is an advantage to minimize the time and the process of care, because the location of the equipment for necessary treatment is possible to be instantaneously located with attached sensors.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.145-150
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• 2021

Patients with Pressure injuries (PIs) may have pain and discomfort, which results in poorer patient outcomes and additional cost for treatment. This study was a part of larger research project that aimed at prediction modeling using a big data. The purpose of this study were to describe the characteristics of patients with PI in critical care; and to explore comorbidity and diagnostic and interventive procedures that have been done for patients in critical care. This is a secondary data analysis. Data were retrieved from a large clinical database, MIMIC-III Clinical database. The number of unique patients with PI was 2,286 in total. Approximately 60% were male and 68.4% were White. Among the patients, 9.9% were dead. In term of discharge disposition, 56.2% (33.9% Home, 22.3% Home Health Care) where as 32.3% were transferred to another institutions. The rest of them were hospice (0.8%), left against medical advice (0.7%), and others (0.2%). The top three most frequently co-existing kinds of diseases were Hypertension, not otherwise specified (NOS), congestive heart failure NOS, and Acute kidney failure NOS. The number of patients with PI who have one or more procedures was 2,169 (94.9%). The number of unique procedures was 981. The top three most frequent procedures were 'Venous catheterization, not elsewhere classified,' and 'Enteral infusion of concentrated nutritional substances.' Patient with a greater number of comorbid conditions were likely to have longer length of ICU stay (r=.452, p<.001). In addition, patient with a greater number of procedures that were performed during the admission were strongly tend to stay longer in hospital (r=.729, p<.001). Therefore, prospective studies focusing on comorbidity; and diagnostic and preventive procedures are needed in the prediction modeling of pressure injury development in ICU patients.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.434-442
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• 2023

The relationship between acute kidney injury (AKI) prediction and nephrotoxic drugs, or drugs that adversely affect kidney function, is one that has yet to be explored in the critical care setting. One contributing factor to this gap in research is the limited investigation of drug modalities in the intensive care unit (ICU) context, due to the challenges of processing prescription data into the corresponding drug representations and a lack in the comprehensive understanding of these drug representations. This study addresses this gap by proposing a novel approach that leverages patient prescription data as a modality to improve existing models for AKI prediction. We base our research on Electronic Health Record (EHR) data, extracting the relevant patient prescription information and converting it into the selected drug representation for our research, the extended-connectivity fingerprint (ECFP). Furthermore, we adopt a unique multimodal approach, developing machine learning models and 1D Convolutional Neural Networks (CNN) applied to clinical drug representations, establishing a procedure which has not been used by any previous studies predicting AKI. The findings showcase a notable improvement in AKI prediction through the integration of drug embeddings and other patient cohort features. By using drug features represented as ECFP molecular fingerprints along with common cohort features such as demographics and lab test values, we achieved a considerable improvement in model performance for the AKI prediction task over the baseline model which does not include the drug representations as features, indicating that our distinct approach enhances existing baseline techniques and highlights the relevance of drug data in predicting AKI in the ICU setting.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.67-75
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• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.

• International Journal of Contents
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• v.9 no.1
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• pp.11-17
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• 2013

Recently, online real-time web accessible mobile devices such as smartphones, tablet PCs and application services have been developing rapidly. Hospitals also need to adopt an efficient information system that can provide decent medical services under mobile computing environments to complete future medical services. This study proposes a system in which a doctor can examine a patient and make out a prescription in a ward on a real-time based on the current Order Communication Systems (OCSs) through mobile interfaces. The proposed system implements mobile web pages using HTML5, instead of a mobile app. Web processing speed can be enhanced using the web socket and web storage functions of HTML5.

• The Journal of the Korean dental association
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• v.54 no.2
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• pp.123-133
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• 2016

Currently increasing use of implants, especially in anterior implant esthetics has become a major concern for both the patient and dentist. In the case of thin biotype if the thickness of the gingival soft tissue is less than 2mm, human eye can detect differences of colors depends on underlying materials. The zirconia abutment can be use not only for better esthetics but also for the hygienic because it is less attractive for the plaque deposition when it compare to the metals. Zirconia itself has many advantages as a biomaterial but also has frequent mechanical problems when it use for abutment of internal connection implant. For prevention or reduction of mechanical failures, use of titanium-link with zirconia super-structure which part that connects directly into the implant can be a good alternative. In this literature, I would like to review the clinical considerations of use of titanium link - CAD/CAM zirconia abutment for dental implant in esthetically important areas.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.47-50
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• 2016

Big Data is coming rapidly in recent times and keep the vast amount of data was utilized them. These data are utilized in many fields in particular, based on the patient data in the medical field to increase the therapeutic effect, as well as re-incidence to better treatment, lowering the readmission rates increased the quality of life. In this paper it is practiced to report basis of the analysis and verification of data using python. And it can be analyzed the data through a simple formula, from Select reason of Python to how it used; by Press analysis of Agriculture, Forestry and Fisheries research. In this process, a simple formula can be used that expression for analyzing the actual data so it taking advantage of the use of functions in real life.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.10-14
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• 2016

Among the methods of treating tinnitus, the transcutaneous clectrical nerve stimulation (TENS) method of treating by electrical stimulation is common. However, there is a problem that surgical operation is required to stimulate the vagus nerve (VN) main trunk near most of the bronchus. Alternatively, we found that the same effect could be achieved by electrically stimulating the vagus nerve VN branch (Arnold's nerve) distributed in the outer ear. The TENS system for stimulation of vagus nerve has been developed, but it has not been able to implement to stimulate as a parameter optimized for the patient by simultaneously playing the sound of eliminating the tinnitus frequency. Therefore, in this paper, it is important to develop a safe and practical TENS device for tinnitus treatment based on a 32-bit microprocessor that simultaneously applies non-invasive and notched sounds and to develop optimal treatment methods for treating tinnitus.