研究背景: 個案管理是被認為可以提高癌症照護品質的護理模式；但過去大多數個案管理的研究設計常有著介入措施、或服務提供者混合多樣性的狀況，這可能低估了由護理人員主導的個案管理對癌症治療照護的影響。
研究目的: 本研究之目的包括兩個部分，第一部分之研究目的為辨識與統整護理主導之個案管理改善癌症治療的成果；第二部分之研究目的為評估護理主導之個案管理對台灣肺癌病人的成本效益。
研究方法: 首先，第一部分為通過檢索六個文獻資料庫（包括PubMed，MEDLINE，CINAHL，EMBASE，Cochrane和CEPS）進行系統性文獻回顧與統合分析，於2020 年 1 月完成檢索2019 年 6 月前發表之文章；審查遵循系統審查和統合分析 (PRISMA) 聲明指南的報告項目，並使用 Joanna Briggs Institute 關鍵評估工具評估證據質量，通過使用 95% 置信區間 (CI)、p 值和基於測試結果異質性的擬合模型的數據池分析結果。在第二部分中，使用台灣國家健康保險研究數據庫（NHIRD）進行2010年至2015年的肺癌診斷人口世代研究，將應用傾向得分配對方法來形成個案管理（CM）和非個案管理（non-CM）組，使用配對比較兩組之間的成本與癌症治療效果差異，進而計算增量成本效果比（ICER）來估計由護理人員主導的肺癌個案管理成本效益；經濟分析是從第三方支付者和醫療保健部門的角度進行的，研究結果包括預防一例臨床事件（即未治療病例）所需治療的數量（NNT）、醫療保健成本、和避免每一例事件的成本，費用則是以 2021 年美元 (USD) 為單位。
研究結果: 在第一部份研究中，11 篇文章被納入統合分析，分析結果發現，與常規護理組相比，護士主導的個案管理組具有：(1)從診斷到治療的時間縮短了 9.07 天，(2)提高了治療完成率（OR = 2.45），(3)更多病人接受賀爾蒙療法。而第二部份研究結果，無論癌症階段如何，護士主導的 CM 模型都有更高的治療率，肺癌病人診斷後的一年中，與非個案管理組相比，個案管理組需要干預的病人數減少了35例和27例來避免1例未治療個案；從第三方支付者和醫療保健部門的角度來看，與非個案管理組相比，採用個案管理將分別為每個未治療個案節省 7,175 美元、和 7,945 美元。
結論: 在系統性文獻回顧與統合分析結果表明，護理師主導的個案管理在提高治療及時性、治療完成率和激素治療率方面比常規護理更有效；但在以現實世界中台灣健康保險研究數據庫的分析，護理師主導的個案管理提高了病人對肺癌治療的接受度，從而節省了避免肺癌患者未接受治療的成本。個案管理模式可以被認為是肺癌治療的經濟合理選擇介入措施。

Background: Case management is considered a care model that can improve cancer care quality. However, most studies included a mix of interventions or service providers, underestimating the effect of nurse-led CM on cancer treatment quality.
Purpose: This study aims (1) to identify and synthesize the outcomes of nurse-led CM interventions on improving cancer treatment, (2) to estimate the cost and effectiveness of the nurse-led CM model among lung cancer patients in treatment, and (3) to determine the cost-effectiveness of the nurse-led CM model in clinically meaningful outcomes of lung cancer treatment.
Method: First, we conducted a systematic review with the meta-analysis by searching six literature databases, namely PubMed, MEDLINE, CINAHL, EMBASE, Cochrane Library, and CEPS. This review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. We analyzed the outcomes by using a pool of data of 95% confidence intervals (CIs), p-value, and a fitting model based on the heterogeneity of test results. Second, we conducted a population-based retrospective cohort study on patients diagnosed with lung cancer by using the 2005–2015 Taiwan National Health Insurance Research Database. We formed the matched pairs of CM and non-CM cohorts through propensity score matching. Using the matched pair, we compared the clinical outcomes, including retention rate, the days from diagnosis to treatment, treatment acceptance rate, treatment completion rate, and survival rate between the CM and non-CM groups. Then we used the number needed to treat (NNT) to prevent one case of clinical events (e.g., non-treated, non-completion of treatment) to estimate the intervention effectiveness in this cost-effectiveness analysis (CEA). The incremental cost-effectiveness ratio (ICER) was calculated as the difference in the average per-patient healthcare costs from the third-party payer and healthcare sector perspectives with adjustment for baseline healthcare costs between the two groups. All cost estimates were standardized to 2021 United States dollars (USB, $).
Results: In the first part, we included eleven articles in the meta-analysis. When compared to the regular care group, the nurse-led case management group had: 91) a shorter time from diagnosis to treatment by 9.07 days (95% CI −14.08, −4.06; p < 0.001), 92) an improved treatment completion rates odds ratio (2.45; 95% CI 1.56, 3.87; p < 0.001), and 93) more number of patients received hormone therapy (1.60; 95% CI 1.19, 2.16; p < 0.01). In the second part, this study reported a consistently higher retention rate (CM vs. non-CM: 93.7% vs. 92.7%, p=0.004) and treatment acceptance rates across all cancer stages (CM vs. non-CM: 83.9% vs. 80.5%, p < .001). The results showed that regardless of cancer stage, the CM group had significantly lower risks of being non-treated (HR [95% CI]: 0.81 [0.70, 0.94], p < 0.01). In one year following a lung cancer diagnosis, compared to the non-CM, 35 and 27 cases less needed to be intervened with the CM model to avoid one patient being untreated. The adoption of the CM model compared to non-CM would save USD 7,175 and USD 7,945 per untreated case prevented, respectively, from the payer and healthcare sector perspectives.
Conclusion: We conducted a systematic review and a cohort study that applied nationwide longitudinal data at the individual patient level from a real-world setting to demonstrate that the nurse-led CM model had a higher treatment rate regardless of cancer stage, leading to cost-saving for preventing lung cancer patients from being untreated. The CM model could be considered an economically reasonable choice for lung cancer treatment.

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