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심부전환자를 위한 퇴원간호서비스모델 개발

Other Titles
 Development of discharge nursing service model for heart failure patients 
Authors
 박성혜 
College
 College of Nursing (간호대학) 
Department
 Others (기타) 
Degree
박사
Issue Date
2021-08
Abstract
의료기관의 의료비용 효율 강조는 병상회전율 향상을 위한 재원일수 단축과 조기퇴원 정책을 활성화시켰다. 이와 연관된 재입원 관리는 의료기관의 시스템 효율성, 제공된 의료서비스 질, 의료비용 측면에서 중요한 이슈가 되었다. 최근 10년 동안 우리나라 상급종합병원에서 가장 높은 재입원을 보이는 질환군은 심부전으로 확인되었다. 초고령화 사회로의 변화는 만성질환 관리, 특히 재입원율이 높은 심부전환자의 적절한 퇴원 후 관리가 필요하게 되었다. 이에 본 연구에서는 재입원율이 높은 심부전환자의 고위험지표, 퇴원전담간호사의 역할, 퇴원간호과정의 전반적 내용을 포함한 퇴원간호서비스모델을 개발하고 임상적 타당성을 확인하고자 한다. 본 연구는 방법론적 연구로 1단계 심부전환자를 위한 퇴원간호서비스모델 초안 개발은 체계적 문헌고찰과 전자의무기록 분석을 통한 심부전 재입원환자의 고위험지표 도출, 심부전환자에게 퇴원간호서비스를 제공할 퇴원전담간호사의 직무표준 개발, 심부전환자의 재입원 감소를 위한 퇴원간호과정으로 구성되어있다. 2단계는 심부전환자를 위해 개발된 퇴원간호서비스모델 초안의 타당도 평가로 전문가 집단의 델파이 기법을 통하여 평가가 진행되었다. 마지막 3단계에서는 최종 심부전환자를 위한 퇴원간호서비스모델 개발이 완성되었다. 연구 결과 문헌고찰을 통해 도출된 심부전환자의 재입원 고위험지표는 최근 3년간 일 상급종합병원에 심부전 진단 하 입원 후 퇴원한 환자의 전자의무기록 자료 분석을 통하여 그 타당성을 확인하였다. 심부전 퇴원환자 1,857명 중 재입원 환자는 총 267명(14.4%)이었으며 나이(p=0.048), 입원 시 최초 체중(p=0.031), 입원기간 동안 체중변화(p=0.009), 입원 이전 6개월 동안의 입원과 응급실 내원 여부(p<0.001), 맥박수(p=0.010), 퇴원약의 개수(p<0.001), 입원 시 Hg (p<0.001), Hct (p<0.001), BUN (p=0.002), Na (p<0.001) 수치, 퇴원 시 Hg (p<0.001), Hct (p<0.001), BUN (p=0.041), Na (p<0.001), CRP (p=0.043) 수치, 응급실 내원 시 주진단명(p<0.001), ACEI/ARB약물의 퇴원약 처방(p=0.025) 등이 재입원과 유의한 연관성이 있는 것으로 나타났다. 전자의무기록 자료 분석을 통하여 재입원 고위험지표의 타당성 확인 후 재입원군과 재입원이 발생하지 않은 군간 p값이 0.05 미만인 설명변수들로 다변량 로지스틱 회귀분석을 시행한 결과 퇴원약의 개수가 1개 증가할 때마다 재입원 오즈비가 1.030배, 즉 재입원이 약 3.0% 증가하는 것으로 나타났다(p<0.001). 입원 시 Na 수치가 증가할 때마다 재입원은 5.4% 감소(OR=0.946, p=0.021), 퇴원 시 Na 수치가 증가할 때마다 재입원은 6.6% 감소(OR=0.934, p=0.028), CRP 수치가 증가할 때마다 재입원은 1.1% 감소(OR=0.989, p=0.049)하는 것으로 나타났으며 AUC는 0.735였다. 선행연구와 문헌을 기반으로 퇴원전담간호사의 업무는 9개 핵심역량인 전문적 간호실무, 교육, 상담, 자문, 윤리적 의사결정, 연구, 협동, 근거기반 실무, 리더십에 따른 28개의 업무활동으로 구성하였다. 퇴원전담간호사의 직무표준(안)은 규명된 업무를 중심으로 9개의 표준(안), 15개의 기준(안), 42개의 지표(안)으로 개발되었다. 개발된 직무표준(안)은 두 차례에 걸쳐 진행된 델파이 기법으로 내용타당도를 검증, 평균 CVI는 0.94로 확인되었다. 심부전환자의 퇴원간호과정은 체계적 문헌고찰을 통하여 입원 시부터 퇴원 후 30일까지 심부전환자에게 필요한 퇴원간호중재 내용을 시기별로 분석, 통합하였다. 퇴원간호과정은 시기별로 입원 시부터 퇴원 전 단계, 퇴원 시, 퇴원 후 단계(전화상담과 가정방문), 외래진료 및 퇴원간호서비스 종료의 총 5단계로 분류되며 총 25개 항목의 퇴원간호과정으로 구성되었다. 개발된 퇴원간호과정 역시 두 차례에 걸쳐 진행된 전문가집단의 델파이 기법으로 내용타당도를 검증, 평균 CVI는 0.92로 확인되었다. 본 연구에서 심부전환자를 위한 퇴원간호서비스모델은 재입원 고위험지표와 퇴원전담간호사의 직무표준이라는 구조를 바탕으로 퇴원간호과정을 거쳐 심부전환자의 자가간호 행위 이행도와 퇴원 후 30일 이내 재입원이라는 결과를 평가할 수 있도록 개발되었다. 의료의 질 관리 측면에서 재입원은 중요한 지표이며 동시에 환자진료의 결과이자 의료비 증가의 주요 원인으로, 이를 감소시킬 수 있는 효율적인 시스템 또는 서비스의 개발이 필요하다. 본 연구를 통해 개발된 퇴원간호서비스모델은 지속적인 수정과 보완 작업을 거쳐 퇴원전담간호사의 업무지침서 작성 및 평가, 교육과정 개발, 그리고 퇴원간호중재 적용을 위한 기초자료로 활용될 수 있을 것이다.

1. Introduction The emphasis on medical cost efficiency of medical institutions has stimulated the reduction of hospital stay and early discharge policies to improve bed turnover. The related readmission management has become an important issue in terms of system efficiency of medical institutions, the quality of medical services provided, and medical costs. Heart failure (HF) was identified as the disease group with the highest readmission rate in tertiary hospitals in Korea for the past 10 years. The transition to an aging society requires management of chronic diseases, especially appropriate post-discharge management of HF patients with high readmission rates. The quality of discharge of a person who has been discharged from a hospital may be improved by reducing the length of stay, managing after discharge necessary for early discharge, and preventing risk factors for readmission. Therefore, this study developed a discharge nursing service model (DNSM) including high risk factors, the job standard of discharge nurses, and the overall discharge nursing process of high readmission rates and confirm clinical feasibility. 2. Objective The purpose of this study is to develop a DNSM for HF with high readmission rates, and the specific objectives are as follows. 1) Collect basic data for the development of a draft DNSM for HF patients. A) Through systematic literature review and electronic medical record (EMR) analysis, high-risk factors of HF readmission patients are derived. B) Develop job standards for discharge nurses who will provide discharge nursing services to patients with HF. C) Develop a discharge nursing process to reduce readmissions for HF. 2) Evaluate the validity of the DNSM based on the basic data. 3) Develop a final DNSM for HF patients. 3. Theoretical framework This study’s conceptual framework is based on Donabedian's Structure- Process-Outcome (SPO, 1998) model as a theoretical foundation for DNSM for HF. Structure aspects are defined as the physical environment and human resources, and process aspects are defined as treatment or diagnosis, prevention activities and education conducted on patients. Finally, outcomes are defined as patient achievements, such as health status, changes in behavior or knowledge for health, and patient satisfaction. In this study, the structure is defined as a high-risk factors for readmission of HF patients and job standards for discharge nurses derived through literature review and EMR analysis. The job standards for discharge nurses were implemented through systematic literature review and benchmarking of domestic and foreign medical institutions, and expert validity was checked. The process refers to the discharge nursing process, and consists of the activities of the discharge nurse, including nursing management, nursing diagnosis, nursing intervention, and nursing evaluation. The results indicate the effect of the DNSM on the patient's health status. In this study, it was defined as self-care behavior and readmission within 30 days of discharge of HF patients. 4. Research method 1) Research design This study is a methodological study that develops DNSM for HF with high readmission rates and confirms clinical validity. 2) Research process STEP 1. Development of a Draft DNSM for HF ① Selection of high risk factors for readmission of HF A) Identification of high risk factors for readmission of HF patients through literature review B) To verify the validity of high risk factors through the analysis of EMR data of HF patients who are hospitalized after being discharged from the hospital C) Presentation of a functional model of high risk factors for readmission of HF patients ② Development of job standards for discharge nurses A) Identification of specific roles of discharge nurses through literature review B) Verification of discharge nurses’ activities through benchmarking of domestic and foreign institutions C) Development of job standards (proposed) for discharge nurses ③ Development of discharge nursing process A) Discharge nursing process analysis through literature review B) Development of discharge nursing process STEP 2. Validation of DNSM for HF (Delphi) Validation of the feasibility of DNSM for HF was conducted by organizing a panel of experts to utilize Delphi techniques. Specialists for Delphi techniques should not exceed 3 to 10 (Lynn, 1985), before collecting the data, each expert was provided with information such as research topics, purpose, number of surveys, and anonymity by wire or mail to confirm her/his intention to participate and receive consent. Expert feasibility assessment uses the Content Value Index (CVI) and is interpreted to have obtained validity if the CVI is 0.78 or higher for each measurement item. The data collection was conducted by e-mail or printed questionnaires, with a total response rate of 100 percent from nine experts. The first Delphi data collection period was from 12 April to 12 May 2021, and the second Delphi data collection period was from 14 to 27 May 2021. STEP 3. Finalizations of DNSM for HF Based on the results of the practical suitability verification, such as content validity, the DNSM for patients discharged from the hospital with HF was finalized. 5. Research results STEP 1: Development of a draft DNSM for HF ① Selection of high risk factors for readmission of HF A total of 28 high risk factors for readmission of HF patients were identified through systematic literature review. A) Results of checking high risk factors for readmission of HF through literature review : Readmission high-risk factors for patients with severe HF, gender, age, economic status, income levels, hospitalization history, polypharmacy, over the past six months hospitalization with emergency room, severity, hyperlipidemia and depression, presence of chronic obstructive pulmonary disease (COPD), NYHA functional class, systolic blood pressure, left ventricular effusion coefficient, prescription of discharge medication for β-Blocker and ACEI/ARB, and Na and NT-proBNP blood test levels. B) Results of feasibility of high risk factors through EMR data analysis of HF patients who are hospitalized after being discharged from hospital : A total of 267 (14.4%) of 1,857 patients with HF was readmitted. Age (p=0.048), initial body weight at hospitalization (p=0.031), body weight change (p=0.009), and hospitalization for 6 months prior to hospitalization and emergency room visit (p<0.001), pulse rate (p=0.010), number of medications discharged (p<0.001), Hg (p<0.001), Hct (p<0.001), BUN (p=0.002), Na (p<0.001) level at admission, Hg (p<0.001), Hct (p<0.001), BUN (p=0.041), Na (p<0.001), CRP (p=0.043) level at discharge, main diagnosis of emergency room (p<0.001) and ACEI/ARB medication discharge prescription (p=0.025) were found to be significantly related to readmission. C) Functional model of high risk factors for readmission of HF : After confirming the validity of high-risk factors through EMR data analysis, multivariate logistic regression analysis was performed with explanatory variables with a p-value of less than 0.05 between the readmission group and the non-readmission group. As a result, for each increase in the number of discharge medications, the readmission odds ratio was 1.030 times, that is, the readmission rate increased by about 3.0% (p<0.001). For each increase in Na level at admission, a 5.4% decrease in readmission (OR=0.946, p=0.021), a 6.6% decrease in readmission for each increase in Na level at discharge (OR=0.934, p=0.028). For each increase in CRP level at discharge, readmission decreased by 1.1% (OR=0.989, p=0.049), and AUC was 0.735. ② Development of job standards for nurses in charge of discharge A) Results of identifying specific roles of nurses in charge of discharge through literature review : A total of 15 specific details of the job of nurses in charge of discharge were identified through systematic literature review. B) Results of verifying work activities through benchmarking of domestic and foreign discharge nurses' operating institutions : In Korea, all five general hospitals did not operate nurses exclusively for discharge. Overseas, team leaders from three U. S. hospitals, one in China, and one in Poland, who conducted research on the discharge care system for HF patients, explained the purpose of the study via e-mail and asked for data on job descriptions or role of discharge nurses. Among the five hospitals, one hospital in the U. S. and China responded, and in the U. S. one discharge nurse managed five HF during the study, but now one case manager managed about 30 to 50 patients with various diseases but failed to manage them after discharge. In the case of China, all HF nurses without discharge nurses were answered to provide discharge nursing services, and there was no written job description. C) Development of job standards for nurses in charge of discharge : The job standard (proposed) of a discharge nurse who is directly in charge of the discharge process of HF patients is the core competency of professional nursing practice suggested by Hamric et al. (2013) and the core competency and job scope of a professional nurse suggested by the Korean Nursing Association (2012). It was developed based on the core competency standards of professional nurses in the rapid response team developed by Lee (2019) by integrating the standard contents. The roles of the discharge nurse were identified as 28 work activities based on 9 core competencies: professional nursing practice, education, counseling, advice, ethical decision-making, research, collaboration, evidence-based practice, and leadership. The job standard (proposed) for discharge nurses was developed with 9 standards (proposed), 15 criteria (proposed), and 42 indicators (proposed) focusing on the identified tasks. ③ Development of discharge nursing process A) Results of analysis of discharge nursing process through literature review : The discharge nursing process was searched along with the job standard of discharge nurse. B) Development of discharge nursing process : The discharge nursing process is based on the structure, process, and outcomes of Donabedian, the theoretical framework, and is classified into five stages, from hospitalization to pre-discharge stage, discharge stage, post-discharge stage (telephone counseling and home visiting), outpatient care, and discharge care service termination. The goals for each stage, discharge nursing interventions for discharge nurses, and achievement indicators and evaluation tools for patients and main caregivers. STEP 2. Validation of DNSM for HF (Delphi) result ① General characteristics of expert panels The group of experts to investigate the validity of the DNSM were consisted of nine, two cardiologists, two nursing professors, two cardiovascular hospital wards and outpatient managers, one cardio nurse practitioner, one HF clinic nurse, and one cardio outpatient nurse. Clinical experience averages 14 years, and professors have an average of 13 years of teaching experience. Of the nine professionals are four doctors, four masters, and one bachelor's degree. With the exception of two nursing professors, the average length of work at a cardiovascular hospital was 11 years. ② Results of verification of validity of DNSM for HF This study achieved expert consensus on the discharge nurse's job standard and discharge nursing process of DNSM for HF twice content validity verification of Delphi experts. A) Results of verification of the validity of job standards, criteria, and indicators of discharge nurses : The roles of the discharge nurse were identified as 28 work activities based on 9 core competencies: professional nursing practice, education, counseling, advice, ethical decision-making, research, collaboration, evidence-based practice, and leadership. The job standard (proposed) for discharge nurses was developed with 9 standards (proposed), 15 criteria (proposed), and 42 indicators (proposed) focusing on the identified tasks. The developed job standard (proposed) was verified as having an average CVI of 0.94 by verifying its content validity using the Delphi technique conducted twice. B) Results of verification of validity of discharge nursing process : The discharge nursing process for HF patients was analyzed and integrated by time period from hospitalization to 30 days after discharge through systematic literature review. The discharge nursing process is divided into a total of 5 stages from hospitalization to pre-discharge stage, discharge stage, post-discharge stage (telephone counseling and home visiting), outpatient treatment, and discharge nursing service termination. The developed discharge nursing process was also verified for content validity using the Delphi technique of the expert group conducted twice, and the average CVI was found to be 0.92. STEP 3. Confirmation of final DNSM for HF High risk factors of the DNSM for HF, and the content validity verification result of the discharge nurse’s job standard (proposed) 9 standards (proposed), 15 criteria (proposed), 42 indicators (proposed) all had a CVI of 0.78 or higher. In the case of the discharge nursing process, it was confirmed that the CVI of all items was 0.78 or higher, and the DNSM was confirmed as follows . 6. Discussion 1) Nursing problems related to high-risk factors for readmission of HF In order for the prevention and post-discharge management of readmission patients with high readmission rates to be successful, the identification, prevention and management of high risk factors that cause readmission must be carried out systematically. The rapid increase in the elderly population contributes to the social stimulus burden, including medical and social services, and the increase in health insurance benefits for senior citizens. In this study, more than 70% of hospitalized patients under diagnosis of HF were elderly patients, which is a result of the transition to an ultra-aged society and the absence of caregivers or care families. In the case of elderly patients, it is important to use easy terms in discharge education, provide audio-visual materials using pictures, photos, and repeat learning due to a decline in cognitive function. In this study, it can be seen that the period from discharge to readmission is an average of 14 days, and appropriate post-hospital care is required for two weeks after discharge. The effect can be expected if self-care training is conducted by discharge nurses before discharge from the hospital, and telephone counseling by discharge nurses and 1:1 retraining by home visiting nurses for two weeks after discharge. The average number of discharged medications for readmission HF is 23, indicating the importance of drug education for treatment and symptom management of HF. The importance of polypharmacy use, one of the reasons for the readmission of HF, has already been highlighted in prior studies. Therefore, it is essential to ensure that home visiting nurses are taking the medications accurately after discharge and to manage them later through retraining. Difficulty breathing, the main symptom of HF, will be identified as the chief complaint of emergency room, and education on prevention and symptom management will be important before and after discharge. The application of a program that includes telephone-based self-care training for at least two times a month for three months and self-care and readmission within 30 days of discharge for HF discharged from the emergency room. In this study, Hg and Hct levels in readmission HF averaged 11.4 g/dL and 34.7%, lower than 12.0 g/dL and 36.5% in patients without readmission (p<0.001). This is the same result of Chung’s (2008) studies in which readmission due to HF may be higher if Hg levels are above 17 g/dL or below 13 g/dL (the lower the levels of hemoglobin in patients with HF). BUN levels averaged 32.7 mg/dL in the readmission group, higher than 29.0 g/dL in the non-admission group. On the other hand, Na levels averaged 136.7 mmol/L in the readmission group, lower than 138.4 mmol/L in the non-admission group. This is equivalent to the results of low Na and high BUN levels affecting readmission in the Get With the Guidelines HF (GWTG-HF) program of the American Heart Association. Therefore, if selected for high-risk HF patients are hospitalized, regular blood tests should be conducted once a week through a home visiting nurse's visit up to two weeks after discharge to prevent readmission by managing the symptoms and signs of HF. Risk score for predicting 30-day HF-specific readmission developed by Lim et al. in 2019 is based on age, NYHA functional class, presence of hypertension, hospitalization in the previous 6 months, presence of COPD, presence of cardiomyopathy, presence of systolic blood pressure, left ventricular ejection fraction, β-Blocker and ACEI/ARB prescriptions for discharge, Na and NT-proBNP levels during blood tests are assigned scores for a total of 12 high-risk indicators. It is defined as a high risk of readmission. In this study, when the results of EMR data analysis were applied to Lim et al.'s tool, the indicators significantly related to readmission among 12 items were age (p=0.002), previous hospitalization for HF (p<0.001), and Cardiomyopathy (p=0.026), systolic blood pressure less than 110mmHg at discharge (p=0.018), without ACEI/ARB discharge medication prescription (p=0.021), Na<135mmol/L (p<0.001), BNP≧700 or NT-proBNP≧8,000 pg/mL (p=0.004), etc. in total. The total score was 12.6 on the average in the readmission group, and 10.6 in the non-readmission group, which was confirmed to be significantly related to readmission (p<0.001). If the reliability and validity of the Risk score for predicting 30-day HF-specific readmission tool developed by Lim et al. is proven through continuous research, it is applied to the EMR system and utilized as a high-risk factor function, standardized DNSM. It is considered that it can be connected to effective disease management through the application of the process and the management of home visiting nurses. 2) Identification of job standards and discharge nursing processes for discharge nurses In this study, discharge nurses will perform a combination of professional nursing practice, education, counseling, advice, ethical decision making, research, collaboration, evidence-based practice, and leadership. Based on the high risk factors of readmission, the DNSM is classified into five stages: pre-discharge, discharge, post-discharge (telephone counseling & home visiting), outpatient care, and discharge nursing service termination. In Korea, discharge nursing has been conducted by nurses or charge nurses on the day of discharge, not by certain personnel. However, the absence of standardized discharge nursing processes, such as nurses' preparation for discharge education and lack of relevant knowledge, may lead to inadequate post-discharge care and cause readmission. The effectiveness of discharge education on HF patients in this study showed positive results in self-care, including readmission prevention and symptom monitoring, adherence to medication, and low-sodium diets. Therefore, discharge nurses can be said to be responsible for providing sufficient education to patients and caregiver managing the disease after discharge. The discharge nursing process based on the job standards, criteria, and indicators of discharge nurses developed in this study could lead to successful role performance in the discharge process and improved prognosis for HF. In this study, out of a total of 1,857 HF patients admitted to a first-class general hospital over the past three years, a total of 90 HF counseling were conducted in outpatient areas. HF counseling training can be conducted multiple times for patients and caregivers as needed. Counseling is consist of hight, weight, body mass index (BMI), current medication, NYHA class, presence of or readmission of HF symptoms within the last 6 months, dyspnea, drinking, smoking, eating habits, awareness, daily adherence to HF medication. HF education has been shown to be highly associated with self-care in HFs, and nurse-led training has been effective in reducing readmission in HFs. The reason for the failure to expand HF counseling education is the lack of manpower to take charge of education. However, as suggested in the developed DNSM, if HF counseling is provided by discharge nurses prior to discharge, greater effect can be expected. After discharge, the actual HF counseling training was conducted from at least 6 days to 1,088 days, and the average number of readmission patients was 140 days after discharge and 110 days after no readmission occurred. As shown in the HF counseling training, this training should be conducted for patients and caregivers before discharge, not outpatient, so that post-discharge management can be efficient. After discharge, it can be linked to re-education and evaluation through home visiting nurses. In a study analyzing the relationship between the average length of stay in general hospitals and the level of nurse placement from 1996 to 2016, it was found that a decrease in the average number of days in hospital increased patient severity, nursing demand, and nursing intensity. Nurses working in wards with a short or medium length of stay had a faster work speed in order to solve a high nursing demand, and the higher the work demand, the more burnout, job satisfaction, and turnover intention increased. In order to solve this problem, if the discharge nursing process is carried out based on the job standards, criteria, indicators developed in this study, the discharge nursing process can be performed successfully in the discharge process of HF patients, as well as improving the prognosis of HF patients and treating HF patients. It can lead to effective nursing work performance through efficient division of duties among nurses in charge. 3) Application and expansion of the developed DNSM to the home management pilot project by Ministry of Health and Welfare HF itself has complicated pathogenesis and can cause complex problems depending on the severity of accompanying diseases such as diabetes (34.8%) and kidney diseases (33.3%). The extension of life expectancy will require proper management of patients with chronic diseases, and the Ministry of Health and Welfare will initiate a home care policy in 2019. The purpose of this policy is to provide medical institutions with periodic compensation for home care services through education, counseling, and regular monitoring of patients in need of continuous care. The home care pilot project aims to improve patients' quality of life and reduce medical expenditure by providing continuous management and feedback of home patients, as well as by improving public access to health care. The pilot project for at-home medical care for patients with heart disease is to provide medical services such as education, counseling, and monitoring to prevent worsening of diseases and improve the quality of life of patients with heart disease who require continuous management. Accordingly, it consists of calculating the appropriate level of educational counseling fees (face-to-face) and patient management fees (non-face-to-face). Of these, when a doctor or nurse provides counseling and education on how to use the device and self-management to heart disease patients (including their caregivers) visited by a doctor or nurse, the education consultation fee is calculated at KRW 24,810 (30 minutes or more per frequency, initial year: no more than 6 times a year, next year: up to 4 times a year) is possible. In addition, when a doctor or nurse checks the patient's condition at least once a month and provides a non-face-to-face management service for two-way communication such as checking the patient's condition using telephone calls or text messages, the patient management fee of KRW 26,610 can be calculated. The DNSM developed in this study is systematically managed from hospitalization to post-discharge of HF patients by a discharge nurse, and includes all the contents to be implemented in the at-home care pilot project for patients with heart disease. If there was difficulty in maintaining continuity of treatment because the existing discharge nursing was conducted by the patient's nurse or chief nurse on the day of discharge, the developed discharge nursing service is provided by the discharge nurse from the time of admission to the hospital for 30 days, up to 90 days after discharge continuous management is possible. In addition, it can be used as a basis for setting the number of nurses' education, counseling, continuous management and monitoring, and teach back. In this study, it is considered that high-quality management is possible according to a continuous treatment plan through management through a home visiting nurses. 4) Utilization of medical big data: Utilization of readmission high risk factors by improving the EMR system In the United States, about $25 billion is spent on preventable readmission, so it was attempted to predict readmission for HF patients and implement appropriate management through the establishment of a readmission prediction system combining EMR and Information Technology (IT). In a study by Bardhan et al., it was analyzed that the high risk factors for readmission for HF patients affects readmission according to the patient's personal information, hospital admission reason, insurance type, and hospital type. Medical big data, such as medical information in the medical information system and result data linked with test equipment, creates new medical information through integration and analysis. Medical big data built based on EMR should be utilized to create new values ​​as well as to generate various information for disease prevention and treatment. The high-risk factors for readmission presented in this study is classified as a high-risk HF patient by automatically applying and analyzing the EMR contents when a patient is hospitalized. Effective disease management should be achieved through. For this purpose, like the Risk score for predicting 30-day HF-specific readmission tool developed by Lim et al., a functional model that can predict the high risk of readmission with the total score should be established by scoring the relevant items of high-risk factors. In addition, the achievement indicators and evaluation tools of patients and their primary caregivers at each stage of the discharge nursing process should be reflected in the EMR system and used as basic data for future evaluation and research. This will maximize the utilization of medical big data through the improvement of the EMR system. It can be said that it is a matter that needs to be continuously discussed from the point of view that it is possible. 7. Conclusion In this study, the DNSM for patients with HF was based on the high risk factors for readmission, the job standard of the discharge nurses, and the result of the discharge nursing process was the performance of the HF patient's self-care behavior and readmission within 30 days after discharge. In terms of quality management, readmission is an important indicator, a result of patient care, and a major cause of medical cost increase, so it is necessary to develop an efficient system or service that can reduce it. The development of the DNSM in this study started with recognition of this problem and could be used as basic data such as job description of discharge nurses, preparation and evaluation of work guidelines, and development of discharge nurses curriculum. It is suggested that for the application of the DNSM, the establishment of the system along with the hospital's policy should precede, and that follow-up research should be carried out to examine its effectiveness in actual clinical sites.
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3. College of Nursing (간호대학) > Others (기타) > 3. Dissertation
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