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標題: | 探討居家醫療在老年族群之照護結果與影響因素 Exploring the Outcomes and Influencing Factors of Home-Based Medical Care in the Older Adults |
作者: | 施至遠 Chih-Yuan Shih |
指導教授: | 陳雅美 Ya-Mei Chen |
關鍵字: | 居家醫療,老年人,照護結果,群組化多重軌跡模式,結構方程式, Home Care Medicine,Older Adults,Outcomes,Group-Based Multi-Trajectory Modeling,Structural Equation Modeling, |
出版年 : | 2023 |
學位: | 博士 |
摘要: | 台灣正面臨快速老化的社會,導致老年病人因為各類慢性疾病或衰弱的影響,造成生活功能依賴且侷限在家的狀況日益增加,因此需要居家醫療將醫療照護送到病人的家中。故透過此研究釐清居家醫療介入後照護結果與變化趨勢、找出最能獲益的病人族群以及關鍵的照護內容,讓居家醫療照護的品質能更加精進,且發揮最大效益。本研究中採用Andersen醫療服務利用行為模式的架構,並且於醫療照護結果之概念上,參照了經濟、臨床及人本結果 (Economic, Clinical and. Humanistic Outcomes, ECHO )模式,以期探討照護結果的全貌。
本研究分為兩個目的,目的一為探討老年族群,接受居家醫療照護後於臨床、經濟及人本三個面向結果綜合軌跡變化次群,同時分析前傾、使能與需要三個構面中的個人特質,與結果綜合變化軌跡次群的相關性。目的二首先探討居家醫療照護內容的組成類型,接著瞭解不同特質的病人與所接受照護內容組成類型的相關性,最後釐清居家醫療照護內容組成類型對於臨床、經濟及人本照護結果之影響。 本研究使用「全民健康保險保險人資訊應用整合服務中心」之健保資料檔為資料來源,以居家醫療整合照護計畫(重度居家醫療階段)收案且照護達360天以上的老年病人為研究對象。於研究目的一使用群組化多重軌跡模式(group-based multi-trajectory modeling),分析接受居家醫療照護後360天內綜合臨床、經濟及人本照護結果之變化軌跡次群。接著使用使用多元多項式邏輯回歸(multivariate multinomial logistic regression)分析,探討個人特質與照護結果軌跡次群的相關性。研究目的二首先使用潛在類別分析(latent class analysis)探討居家醫療收案後0-180天照護內容的組成類型,接著透過多元多項式邏輯回歸分析個人特質與接受照護內容類型的相關性。最後採用結構方程模式(structural equation modeling)探討所接受居家醫療照護內容類型對於181-360天期間臨床、經濟及人本照護結果之影響。 本研究結果歸納出四個綜合結果軌跡次群:(1)「持續穩定」次群(n=2,244, 49.6%):其平均年齡較高,同時女性占比於四個次群中為最高,共病症指數最低;(2)「趨向穩定」次群(n=1,339, 29.6%):較多之居住地位於低醫師密度區域,生活功能與意識狀態則相對較佳;(3)「惡化」次群(n=524, 11.6%):生活功能與意識狀態相對較差,較多使用鼻胃管;(4)「持續不穩定」次群(n=421, 9.3%):平均年齡相對較低,有較高的鼻胃管使用率,共病症指數最高。 探討個人特質與軌跡次群顯著相關的結果如下:(1)使用鼻胃管或留置導尿管、患有末期腎病、癌症、或糖尿病、心臟衰竭與肺阻塞等慢性疾病者,較不會進入「持續穩定」之軌跡次群;(2)居住於非都會區之病人,其進入「惡化」次群的機會較高。(3)高齡、女性、失智症與中風病人,較傾向進入「持續穩定」之軌跡次群。同時由綜合的軌跡變化來看,「在家天數」能夠同時反應可避免住院與總醫療費用的變化,故合適作為監測居家醫療照護結果的品質指標。 接續探討居家醫療照護內容之模式,綜合考量醫師訪視頻率、護理師訪視頻率與居家醫師照護連續性之下,可區分為四種模式,包括(1)「護理模式」(n=982, 21.7%):具有高護理師與低醫師訪視頻率,照護對象特質以女性占比較多,照護對象特質有投保區域之醫師密度偏高,留置導尿管占比為最高;(2)「均衡模式」(n=522, 11.5%):醫師與護理師訪視頻率皆為中間值,照護對象特質以女性占比較多,生活功能偏低,較多使用鼻胃管;(3)「醫師模式」(n=873, 19.3%):具有高醫師訪視頻率與高醫師照護連續性(60.8%大於0.67),照護對象年齡較高;(4) 「低照護模式」(n=2,151, 47.5%):醫師與護理師僅符合最低訪視頻率要求,照護對象之生活功能偏低,較多使用鼻胃管。病人是否接受「醫師模式」之照護,受到前傾與需要因素影響;「護理模式」則是前傾、使能、需要因素皆有部分影響;影響是否接受「均衡模式」的只有前傾因素中的性別因子。在校正個人特質之下,「均衡模式」能夠減少總醫療費用與增加在家天數,是值得進一步發展的居家照護模式。其他「醫師模式」和「護理模式」,與「低照護模式」相比,對個案結果雖然沒有顯著影響,但是除了「醫師模式」有較長的在家天數傾向,其他都傾向較為不理想的結果,包含更多的可避免住院、總醫療費用,與較少的在家天數。 總結來說,本研究呈現居家醫療病人照護結果軌跡變化以及照護內容的異質性。在照護結果的評估上,在家天數合適作為居家醫療照護的結果指標。居家醫療照護模式中,醫師與護理師共同參與且具反應性的均衡模式,能產生較佳的結果。顯示居家醫療照護應根據病人特質,預判斷可能的結果軌跡,特別針對對於共病症程度高者,建議轉銜給能提供均衡模式照護的居家醫療團隊。 Taiwan is facing a rapidly aging society, leading to an increasing number of older adult patients with various chronic diseases or frailty who rely on and are homebound due to limitations in their daily living activities. In response to this situation, home-based medical care is necessary to bring healthcare services to patients' homes. This study aims to clarify the outcomes and trajectories of post-intervention home-based medical care, identify patient groups that benefit the most, and determine key care components to enhance the quality of home-based medical care and maximize its effectiveness. The study has two main objectives. Objective One explores the trajectories of clinical, economic, and humanistic outcomes for older patients receiving home-based medical care and analyzes associations between individual characteristics and outcome trajectory subgroups. Objective Two examines the home-based medical care model and investigates its associations with diverse outcomes. The research draws data from the National Health Insurance Research Database, focusing on elderly patients in the Home-Based Primary Care Plus (HBPC-Plus) program who received care for over 360 days. In Objective One, group-based multi-trajectory modeling (GBMTM) and multivariate multinomial logistic regression are utilized to analyze trajectory subgroups and the correlation between individual characteristics and these subgroups. In Objective Two, latent class analysis and multivariate multinomial logistic regression are applied to identify the care model during the initial 180 days of HBPC-Plus, exploring the impact of care composition types on outcomes during days 181-360. The study identifies four comprehensive outcome trajectory subgroups: "Persistent Stable" (n=2,244, 49.6%), "Toward Stability"(n=1,339, 29.6%), "Deterioration" (n=524, 11.6%), and "Persistent Unstable"(n=421, 9.3%), each with distinct characteristics and comorbidity levels. Results shed light on the correlation between individual characteristics and trajectory subgroups, offering valuable insights into tailoring care for improved patient outcomes. Results regarding the correlation between individual characteristics and trajectory subgroups are as follows: (1) Patients with chronic diseases such as end-stage renal disease, cancer, diabetes mellitus, heart failure, and chronic obstructive pulmonary disease, and those using nasogastric or Foley catheters, are less likely to belong to the "Stable Continuation" subgroup. (2) Patients residing in non-metropolitan areas have a higher likelihood of belonging to the "Deterioration" subgroup. (3) Older age, female, dementia, and stroke patients are more likely to belong to the "Persistent Stable" subgroup. Additionally, when considering comprehensive trajectory changes, the number of "days spent at home" can reflect changes in avoidable hospitalizations and total medical costs, making it an appropriate quality indicator for monitoring home-based medical care outcomes. Moreover, the study classifies home-based medical care content patterns based on physician visit frequency, nurse visit frequency, and continuity of home physician care, revealing four distinct model: "Nurse-Led," "Balanced," "Physician-Led," and "Low-Care." The "Balanced" model emerges as promising, significantly reducing total medical costs and increasing days spent at home when adjusting for individual characteristics. Whether a patient receives "Physician-led" model is influenced by predisposing and need factors; "Nurse-led " model is influenced by predisposing, enabling, and need factors; and being in the "Balanced" model is only influenced by the gender factor in predisposing factors. In conclusion, this study presents trajectory changes in home-based medical care patient outcomes and the heterogeneity of care content. When evaluating care outcomes, days spent at home are a suitable indicator for home-based medical care results. Among home-based medical care models, the balanced model, where physicians and nurses participate together with a responsive approach, produces better outcomes. This indicates that home-based medical care should predict possible outcome trajectories based on patient characteristics, particularly recommending a referral to a home-based medical care team providing balanced model of care for patients with high comorbidity levels. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91654 |
DOI: | 10.6342/NTU202304284 |
全文授權: | 同意授權(限校園內公開) |
顯示於系所單位: | 健康政策與管理研究所 |
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