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Liang Y, Jing P, Gu Z, Shang L, Ge P, Zhang Y, Wang L, Qiu C, Zhu X, Tan Z. Application of the patient-reported outcome-based postoperative symptom management model in lung cancer: a multicenter randomized controlled trial protocol. Trials 2024; 25:130. [PMID: 38365704 PMCID: PMC10874066 DOI: 10.1186/s13063-024-07963-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 02/01/2024] [Indexed: 02/18/2024] Open
Abstract
INTRODUCTION Lung cancer is the most common cancer in China, with the highest mortality rate. Surgery is the primary treatment for early lung cancer. However, patients with lung cancer have a heavy burden of symptoms within 3 months after surgery, which seriously affects their quality of life (QOL). The symptom management model based on the patient-reported outcome (PRO) is considered the best caregiving model. The clinical evidence about the symptom management of lung cancer within 3 months after the operation is very limited. Herein, we propose a randomized controlled trial to evaluate the PRO score-based monitoring and alert system for follow-up on psychological and physiological symptoms of lung cancer patients within 3 months after surgery and further investigate the effect of intervention measures based on this PRO score-based system. METHODS AND ANALYSIS This multicenter, open-label, randomized, parallel superiority trial will be conducted at four hospitals in China. A total of 440 lung cancer patients will be recruited in this study, who will be randomly assigned to the intervention group or the control group in a ratio of 1:1. Any of the target symptoms reaches the preset threshold (score ≥ 4), the patients will accept the symptom management advices based on the PRO. The patients in the control group will follow the current standard procedure of symptom management. The symptom management system is an electronic management system based on WeChat mini programs. All patients will be evaluated for symptoms through the lung cancer module of the MDASI lung cancer-specific scale on the day before surgery, days 1, 3, 5, and 7 after surgery, and once a week during the 12-week post-discharge period. Simultaneously, the EORTC QLQ-C30 scale will be used to evaluate patients' quality of life at baseline and the fourth and twelfth week after the surgery. The mean number of symptom threshold events of the intervention and the control groups were compared by t-test, and the changes of PRO were compared by a mixed effect model. The primary endpoint has been set as the 12-week post-discharge period. DISCUSSION This study will test the feasibility of the symptom management system based on the mobile social media applet in postoperative caregiving and the efficacy of psychiatrist-assisted treatment and provide evidence in managing the symptoms of patients in the medium and long term. TRIALS REGISTRATION Trials registration number: ChiCTR 2200058876, Registered 18 April 2022.
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Affiliation(s)
- Ying Liang
- Department of Health Statistics, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, Shaanxi Province, China
| | - Pengyu Jing
- Department of Thoracic Surgery, Tangdu Hospital, Xi'an, 710000, Shaanxi Province, China
| | - Zhongping Gu
- Department of Thoracic Surgery, Tangdu Hospital, Xi'an, 710000, Shaanxi Province, China.
| | - Lei Shang
- Department of Health Statistics, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, Shaanxi Province, China.
| | - Peng Ge
- Department of Thoracic Surgery, The Second Affiliated Hospital of Xi'an Medical College, Xi'an, 710038, Shaanxi Province, China
| | - Yong Zhang
- Department of Thoracic Surgery, The Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, XianYang, 712000, Shaanxi Province, China
| | - Lv Wang
- Department of Thoracic Surgery, Daxing Hospital, Xi'an, 710000, Shaanxi Province, China
| | - Chun Qiu
- Department of cerebral Surgery, Tangdu Hospital, Xi'an, Shaanxi Province, 710000, China
| | - Ximing Zhu
- Department of Thoracic Surgery, Tangdu Hospital, Xi'an, 710000, Shaanxi Province, China
| | - Zhijun Tan
- Department of Health Statistics, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, Shaanxi Province, China
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Minvielle E, Fierobe A, Fourcade A, Ferrua M, di Palma M, Scotté F, Mir O. The use of patient-reported outcome and experience measures for health policy purposes: A scoping review in oncology. Health Policy 2023; 129:104702. [PMID: 36588068 DOI: 10.1016/j.healthpol.2022.12.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 12/12/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
The systematic use of patient-reported measures (PRMs) [i.e., patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs)] is advocated as an effective way to improve care practices. However, whether PRMs can lead to the performance assessment of healthcare organisations (HCOs) through valid quality indicators (QIs) for national purposes (i.e., public reporting and paying for performance) is open to debate. This study undertakes a scoping review to examine the use of PRMs as QIs for health policy purposes and to identify the challenges faced in the emblematic case of oncology. According to PRISMA guidelines, published papers, websites and reports published by national and international initiatives were analysed using five online databases (Web of Science, Scopus, PubMed, JSTOR and Google Advanced Search), and then studied using the same keywords. We selected 61 articles and 19 websites/reports and identified 29 PREMs and 48 PROMs from 14 countries and two international initiatives that routinely used them as QIs for HCOs' comparisons. Four types of barriers to this specific use were identified relating to the definition of a standard set, scientific soundness, data collection, and the actionability of such measures. Despite current developments, different barriers still must be overcome before PRMs can be used for health policy purposes in oncology. Future research is needed to ensure that valid QIs related to PRMs are applied at a national level.
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Affiliation(s)
- E Minvielle
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France; I3-CRG, Ecole polytechnique-CNRS, Institut Polytechnique de Paris, Palaiseau, France.
| | - A Fierobe
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France; I3-CRG, Ecole polytechnique-CNRS, Institut Polytechnique de Paris, Palaiseau, France
| | - A Fourcade
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France
| | - M Ferrua
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France
| | - M di Palma
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France
| | - F Scotté
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France
| | - O Mir
- Gustave Roussy, Division of Interdisciplinary Patient Care Pathways (DIOPP), Villejuif, France
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van der Willik EM, van Zwet EW, Hoekstra T, van Ittersum FJ, Hemmelder MH, Zoccali C, Jager KJ, Dekker FW, Meuleman Y. Funnel plots of patient-reported outcomes to evaluate health-care quality: Basic principles, pitfalls and considerations. Nephrology (Carlton) 2021; 26:95-104. [PMID: 32725679 PMCID: PMC7891340 DOI: 10.1111/nep.13761] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022]
Abstract
A funnel plot is a graphical method to evaluate health-care quality by comparing hospital performances on certain outcomes. So far, in nephrology, this method has been applied to clinical outcomes like mortality and complications. However, patient-reported outcomes (PROs; eg, health-related quality of life [HRQOL]) are becoming increasingly important and should be incorporated into this quality assessment. Using funnel plots has several advantages, including clearly visualized precision, detection of volume-effects, discouragement of ranking hospitals and easy interpretation of results. However, without sufficient knowledge of underlying methods, it is easy to stumble into pitfalls, such as overinterpretation of standardized scores, incorrect direct comparisons of hospitals and assuming a hospital to be in-control (ie, to perform as expected) based on underpowered comparisons. Furthermore, application of funnel plots to PROs is accompanied by additional challenges related to the multidimensional nature of PROs and difficulties with measuring PROs. Before using funnel plots for PROs, high and consistent response rates, adequate case mix correction and high-quality PRO measures are required. In this article, we aim to provide insight into the use and interpretation of funnel plots by presenting an overview of the basic principles, pitfalls and considerations when applied to PROs, using examples from Dutch routine dialysis care.
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Affiliation(s)
| | - Erik W. van Zwet
- Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
| | - Tiny Hoekstra
- Department of NephrologyAmsterdam University Medical CentreAmsterdamThe Netherlands
- Nefrovisie FoundationUtrechtThe Netherlands
| | | | - Marc H. Hemmelder
- Nefrovisie FoundationUtrechtThe Netherlands
- Department of Internal MedicineMedical Centre LeeuwardenLeeuwardenThe Netherlands
| | - Carmine Zoccali
- CNR‐IFC, Clinical Epidemiology and Physiopathology of Renal Diseases and HypertensionReggio CalabriaItaly
| | - Kitty J. Jager
- ERA‐EDTA Registry, Department of Medical InformaticsAmsterdam UMC, Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Friedo W. Dekker
- Department of Clinical EpidemiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Yvette Meuleman
- Department of Clinical EpidemiologyLeiden University Medical CenterLeidenThe Netherlands
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Stone E, Rankin N, Currow D, Fong KM, Phillips JL, Shaw T. Optimizing lung cancer MDT data for maximum clinical impact-a scoping literature review. Transl Lung Cancer Res 2020; 9:1629-1638. [PMID: 32953537 PMCID: PMC7481624 DOI: 10.21037/tlcr.2020.01.02] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Multidisciplinary care in is widely recommended as best practice for lung cancer in many countries and jurisdictions. A number of studies suggest multidisciplinary care benefits patient outcomes, with analyses based on a range of data sources including national, state and local registries as well as multidisciplinary team meeting (MDT)-based data collections, often focused on different questions depending on data sources. MDT data collection and linkage are not standardized and not routine although data collection and feedback are specifically recommended by at least one statutory body. We performed a scoping review of current evidence for lung cancer MDT data collection and analysis, to identify discrete strategies through illustrative examples and to make recommendations for future approaches. Thirteen studies were identified that presented lung cancer MDT-related clinical outcomes, three included MDTs from multiple tumour streams while 10 studies focussed on lung cancer MDT meetings. Eleven studies measured the effect of MDT discussion on clinical outcomes of which eight were positive. Data sources included MDT records (3 studies), medical or hospital records (3 studies), institutional registries (5 studies) and state or national administrative datasets (6 studies), with some overlap. Examples of studies based on different data sources (local MDT, institutional registry, national registry) exemplified the different types of clinical research questions appropriate for each data source. While MDT data collection is not well-defined, the importance of clinical audit and data feedback and the potential for real-time analysis to improve outcomes deserve further investigation. Optimized datasets and linkage strategies are likely to maximize benefits for patients.
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Affiliation(s)
- Emily Stone
- Department of Thoracic Medicine, St Vincent's Hospital Sydney, Kinghorn Cancer Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Nicole Rankin
- Research in Implementation Science and e-Health (RISe), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - David Currow
- IMPACCT, University of Technology Sydney, Ultimo, New South Wales, Australia
| | - Kwun M Fong
- UQ Thoracic Research Centre and The Prince Charles Hospital, Metro North Hospital and Health Service, Brisbane, QLD, Australia
| | - Jane L Phillips
- IMPACCT, University of Technology Sydney, Ultimo, New South Wales, Australia
| | - Tim Shaw
- Director of Research in Implementation Science and eHealth Group (RISe), Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
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