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Sjattar EL, Arafat R, Ling LW. Cancer pain self-management interventions in adults: scoping review. BMJ Support Palliat Care 2024; 14:411-415. [PMID: 38719570 PMCID: PMC11671981 DOI: 10.1136/spcare-2024-004893] [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: 03/20/2024] [Accepted: 04/04/2024] [Indexed: 11/22/2024]
Abstract
BACKGROUND The predominant trend in cancer treatment now leans towards outpatient care, placing the responsibility of pain management largely on the patients themselves. Moreover, a significant portion of treatment for advanced cancer occurs in the home environment, so patient self-management becomes increasingly crucial for the effective treatment of cancer pain. OBJECTIVES To map self-management for pain in patients with cancer at all phases of the disease before examining the potential of pain self-care interventions for ill patients with cancer. METHODS A search was conducted on six electronic databases to locate studies published in English, from 2013 to 2023. We followed Arskey and O'Malley's Scoping Reviews guidelines. RESULTS This study thoroughly examined the provision of cancer pain self-management by healthcare professionals and identified four intervention types from 23 studies. Education emerged as the most prevalent form of self-management for cancer pain. CONCLUSION Guiding patients in managing their pain effectively, starting from their hospitalisation and extending to their discharge.
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Yang H, Zhang S, Ma X, Li X, Yu W, Hao L, Lu Y. Pain Intensity and Satisfaction of Pain Relief in Discharged Cancer Patients: A Large Sample Study in China. Pain Manag Nurs 2024; 25:e295-e301. [PMID: 38609804 DOI: 10.1016/j.pmn.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Many studies have focused on the quality of pain management in hospitalized patients with cancer pain, while what happens after discharge remains unclear. AIM The purpose of this study was to investigate the pain intensity and satisfaction of pain relief among a large sample of Chinese patients with cancer pain after discharge. DESIGN Cross-sectional, descriptive, correlational research. SETTINGS AND SAMPLE ABOUT: 1,013 patients were recruited in a tertiary cancer hospital, and their residence addresses were distributed in 6 geographical regions, including 26 provinces, municipalities, and autonomous regions. METHODS The 1,013 patients with cancer pain were discharged from the wards of a national cancer hospital in China from July 2020 to October 2021. A nurse in the pain clinic followed the patients based on a whole-process information system and collected the data after the cancer pain patients were discharged. The study methods followed the STROBE guidelines. RESULTS The average age of 1,013 discharged patients was 61.30 (±12.56) years. Moderate and severe background pain (BGP) was reported in 749 patients (73.94%), and more than 3 instances of breakthrough pain (BTP) in the past 24 hours were reported in 541 patients (53.41%). More severe BGP was associated with more frequent BTP (p < .01). In addition, there were 572 patients (56.47%) whose satisfaction with pain relief was lower than 70%. More severe BGP was associated with a lower satisfaction degree (r = -0.796, p < .01). CONCLUSIONS Pain among discharged Chinese patients with cancer is poorly managed, and there is a low degree of satisfaction with pain relief. Nurses can do more work to assist cancer patients in managing pain more effectively by ensuring they have a plan to report and manage pain after discharge.
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Affiliation(s)
- Hong Yang
- Nursing Department, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Shiyi Zhang
- School of Nursing, Peking University, Beijing, China
| | - Xiaoxiao Ma
- Department of Interventional Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Xin Li
- Nursing Department, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Wenhua Yu
- Nursing Department, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Lihua Hao
- Pain Clinic, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Yuhan Lu
- Nursing Department, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China.
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Liu AW, Odisho AY, Brown Rd W, Gonzales R, Neinstein AB, Judson T. Patient Experience and Feedback after Use of an EHR-integrated COVID-19 Symptom Checker. JMIR Hum Factors 2022; 9:e40064. [PMID: 35960593 PMCID: PMC9472505 DOI: 10.2196/40064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/20/2022] [Accepted: 08/06/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24/7 self-service triage option. Although studies suggest that users may positively perceive online symptom checkers, no studies have quantified user feedback after use of an electronic health record (EHR)-integrated COVID-19 symptom checker with self-scheduling functionality. OBJECTIVE We aimed to understand user experience, user satisfaction, and user-reported alternatives to use of a COVID-19 symptom checker with self-triage and self-scheduling functionality. METHODS We launched a patient-portal based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker. RESULTS Between December 16th, 2021 and March 28th, 2022, there were 395 unique responses to the survey. Overall, respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10, and 47.6% of respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the online tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for respondents. The most common categories of user feedback were regarding other COVID-19 services (e.g. telephone hotline), policies or procedures, or requesting additional features or functionality. CONCLUSIONS This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools like this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. The study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction. .
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Affiliation(s)
- Andrew Wayne Liu
- Center for Digital Health Innovation, University of California, San Francisco, 1700 Owens St, Suite 541, San Francisco, US
| | - Anobel Youhana Odisho
- Center for Digital Health Innovation, University of California, San Francisco, 1700 Owens St, Suite 541, San Francisco, US.,Department of Urology, University of California, San Francisco, San Francisco, US
| | - William Brown Rd
- Center for Digital Health Innovation, University of California, San Francisco, 1700 Owens St, Suite 541, San Francisco, US.,Department of Medicine, University of California, San Francisco, 521 Parnassus Avenue, Suite U127, Box 0131, San Francisco, US.,Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, US
| | - Ralph Gonzales
- Department of Medicine, University of California, San Francisco, 521 Parnassus Avenue, Suite U127, Box 0131, San Francisco, US.,Clinical Innovation Center, University of California, San Francisco, San Francisco, US
| | - Aaron B Neinstein
- Center for Digital Health Innovation, University of California, San Francisco, 1700 Owens St, Suite 541, San Francisco, US.,Department of Medicine, University of California, San Francisco, 521 Parnassus Avenue, Suite U127, Box 0131, San Francisco, US
| | - Timothy Judson
- Center for Digital Health Innovation, University of California, San Francisco, 1700 Owens St, Suite 541, San Francisco, US.,Department of Medicine, University of California, San Francisco, 521 Parnassus Avenue, Suite U127, Box 0131, San Francisco, US.,Office of Population Health, University of California, San Francisco, San Francisco, US
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