{"title":"腹膜透析患者远程管理:一个未满足的临床需求的答案。","authors":"Oommen John, Vivekanand Jha","doi":"10.1159/000496305","DOIUrl":null,"url":null,"abstract":"<p><p>The burden of chronic kidney disease is increasing globally. Novel methods for the management of end-stage kidney disease at home have been available for several years, however uptake of home peritoneal dialysis (PD) has been suboptimal for a variety of reasons. Non-adherence is an important factor that determines the outcomes of PD; patients on home dialysis are subject to feeling isolated and are anxious to lack of routine clinical oversight. When patients feel disconnected from their health care professionals, their compliance to medical advice drops and their confidence in self-care comes down. Remote patient management (RPM) has the potential to improve outcomes in PD through telehealth platforms that facilitate virtual clinical presence, enable patient-generated clinical documentation and feedback mechanism, and promote self-monitoring. Bi-directional communications between patients and clinicians provide an enabling environment for autonomy while being clinically monitored through a co-presence, resulting in collaborative care that could alleviate the anxiety of the patients about not being under the direct care of a physician. RPM enables the clinicians to closely monitor and detect early issues, provide feedback in real-time, and initiate early interventions such as prescription modifications and contextual clinical decision support. As the computational capabilities improve and clinical data are collated, machine learning and artificial intelligence algorithms would help detect patterns and predict impending complications such as fluid overload, heart failure or peritonitis, thereby allowing early detection and interventions to avoid hospitalizations. The technical framework and essential features for a RPM system in PD is outlined in this chapter.</p>","PeriodicalId":10725,"journal":{"name":"Contributions to nephrology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000496305","citationCount":"19","resultStr":"{\"title\":\"Remote Patient Management in Peritoneal Dialysis: An Answer to an Unmet Clinical Need.\",\"authors\":\"Oommen John, Vivekanand Jha\",\"doi\":\"10.1159/000496305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The burden of chronic kidney disease is increasing globally. Novel methods for the management of end-stage kidney disease at home have been available for several years, however uptake of home peritoneal dialysis (PD) has been suboptimal for a variety of reasons. Non-adherence is an important factor that determines the outcomes of PD; patients on home dialysis are subject to feeling isolated and are anxious to lack of routine clinical oversight. When patients feel disconnected from their health care professionals, their compliance to medical advice drops and their confidence in self-care comes down. Remote patient management (RPM) has the potential to improve outcomes in PD through telehealth platforms that facilitate virtual clinical presence, enable patient-generated clinical documentation and feedback mechanism, and promote self-monitoring. Bi-directional communications between patients and clinicians provide an enabling environment for autonomy while being clinically monitored through a co-presence, resulting in collaborative care that could alleviate the anxiety of the patients about not being under the direct care of a physician. RPM enables the clinicians to closely monitor and detect early issues, provide feedback in real-time, and initiate early interventions such as prescription modifications and contextual clinical decision support. As the computational capabilities improve and clinical data are collated, machine learning and artificial intelligence algorithms would help detect patterns and predict impending complications such as fluid overload, heart failure or peritonitis, thereby allowing early detection and interventions to avoid hospitalizations. The technical framework and essential features for a RPM system in PD is outlined in this chapter.</p>\",\"PeriodicalId\":10725,\"journal\":{\"name\":\"Contributions to nephrology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1159/000496305\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contributions to nephrology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1159/000496305\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/4/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contributions to nephrology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000496305","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/4/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
Remote Patient Management in Peritoneal Dialysis: An Answer to an Unmet Clinical Need.
The burden of chronic kidney disease is increasing globally. Novel methods for the management of end-stage kidney disease at home have been available for several years, however uptake of home peritoneal dialysis (PD) has been suboptimal for a variety of reasons. Non-adherence is an important factor that determines the outcomes of PD; patients on home dialysis are subject to feeling isolated and are anxious to lack of routine clinical oversight. When patients feel disconnected from their health care professionals, their compliance to medical advice drops and their confidence in self-care comes down. Remote patient management (RPM) has the potential to improve outcomes in PD through telehealth platforms that facilitate virtual clinical presence, enable patient-generated clinical documentation and feedback mechanism, and promote self-monitoring. Bi-directional communications between patients and clinicians provide an enabling environment for autonomy while being clinically monitored through a co-presence, resulting in collaborative care that could alleviate the anxiety of the patients about not being under the direct care of a physician. RPM enables the clinicians to closely monitor and detect early issues, provide feedback in real-time, and initiate early interventions such as prescription modifications and contextual clinical decision support. As the computational capabilities improve and clinical data are collated, machine learning and artificial intelligence algorithms would help detect patterns and predict impending complications such as fluid overload, heart failure or peritonitis, thereby allowing early detection and interventions to avoid hospitalizations. The technical framework and essential features for a RPM system in PD is outlined in this chapter.
期刊介绍:
The speed of developments in nephrology has been fueled by the promise that new findings may improve the care of patients suffering from renal disease. Participating in these rapid advances, this series has released an exceptional number of volumes that explore problems of immediate importance for clinical nephrology. Focus ranges from discussion of innovative treatment strategies to critical evaluations of investigative methodology. The value of regularly consolidating the newest findings and theories is enhanced through the inclusion of extensive bibliographies which make each volume a reference work deserving careful study.