![]() ![]() Staff shortages: Nursing home staff plunged during pandemic "So much so that we try to educate the family about this before this happens so it doesn't devastate them when they suddenly pass after doing so well for a few days."ĭeath and TikTok: A woman on TikTok wasn't afraid to show her death. "It happens to probably a third of our hospice patients," McFadden says in the video. Many patients die within hours or days of "The Rally." The burst of energy is short lived, however. One of those videos discusses a phenomenon dubbed "The Rally." Hospice patients will suddenly seem like they're getting better – many resume eating, some start walking again and others will talk or laugh. It just kept happening over and over again." "I think I made like three or four TikToks and four days later, one of them blew up. ![]() I felt like it was a very taboo topic that shouldn't be so taboo," McFadden told USA TODAY. ![]() However, these phenomena need further specification for clinical use."I knew I wanted to get information out in general. Conclusion Experts from different professional backgrounds identified a set of categories describing a structure within which clinical phenomena can be clinically assessed, in order to more accurately predict whether someone will die within the next days or hours. Based on these findings, the changes in the following categories (each consisting of up to three phenomena) were considered highly relevant to clinicians in identifying and predicting a patient's last hours/days of life: "breathing", "general deterioration", "consciousness/cognition", "skin", "intake of fluid, food, others", "emotional state" and "non-observations/expressed opinions/other". Twenty-one phenomena were determined to have "high relevance" by more than 50 % of the experts. In the third cycle, these 58 phenomena were ranked by a group of palliative care experts (78 professionals, including physicians, nurses, psycho-social-spiritual support response rate 72 %, see Table 1) in terms of clinical relevance to the prediction that a person will die within the next few hours/days. Fifty-eight phenomena achieved more than 80 % expert consensus and were grouped into nine categories. In the second cycle, these phenomena were checked for their specific ability to diagnose the last hours/days of life. Results The first Delphi cycle of 252 participants (health care professionals, volunteers, public) generated 194 different phenomena, perceptions and observations. Each cycle included: (1) development of the questionnaire, (2) distribution of the Delphi questionnaire and (3) review and synthesis of findings. The Delphi process was set up in three cycles to collate a set of useful and relevant phenomena that identify and predict the last hours and days of life. Method The phenomena associated with approaching death were generated using Delphi technique. ![]() This study is part of the OPCARE9 project, funded by the European Commission's Seventh Framework Programme. The aim of this study was to provide expert consensus on phenomena for identification and prediction of the last hours or days of a patient's life. Abstract : Background Providing the highest quality care for dying patients should be a core clinical proficiency and an integral part of comprehensive management, as fundamental as diagnosis and treatment. ![]()
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