A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all
Abstract Background Adults with cancer experience symptoms that change across the disease trajectory. Due to the distress and cost associated with uncontrolled symptoms, improving symptom management is an important component of quality cancer care. Clinical decision support (CDS) is a promising stra...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-03-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-024-02466-7 |
| _version_ | 1797274383571484672 |
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| author | Hayley Dunnack Yackel Barbara Halpenny Janet L. Abrahm Jennifer Ligibel Andrea Enzinger David F. Lobach Mary E. Cooley |
| author_facet | Hayley Dunnack Yackel Barbara Halpenny Janet L. Abrahm Jennifer Ligibel Andrea Enzinger David F. Lobach Mary E. Cooley |
| author_sort | Hayley Dunnack Yackel |
| collection | DOAJ |
| description | Abstract Background Adults with cancer experience symptoms that change across the disease trajectory. Due to the distress and cost associated with uncontrolled symptoms, improving symptom management is an important component of quality cancer care. Clinical decision support (CDS) is a promising strategy to integrate clinical practice guideline (CPG)-based symptom management recommendations at the point of care. Methods The objectives of this project were to develop and evaluate the usability of two symptom management algorithms (constipation and fatigue) across the trajectory of cancer care in patients with active disease treated in comprehensive or community cancer care settings to surveillance of cancer survivors in primary care practices. A modified ADAPTE process was used to develop algorithms based on national CPGs. Usability testing involved semi-structured interviews with clinicians from varied care settings, including comprehensive and community cancer centers, and primary care. The transcripts were analyzed with MAXQDA using Braun and Clarke’s thematic analysis method. A cross tabs analysis was also performed to assess the prevalence of themes and subthemes by cancer care setting. Results A total of 17 clinicians (physicians, nurse practitioners, and physician assistants) were interviewed for usability testing. Three main themes emerged: (1) Algorithms as useful, (2) Symptom management differences, and (3) Different target end-users. The cross-tabs analysis demonstrated differences among care trajectories and settings that originated in the Symptom management differences theme. The sub-themes of “Differences between diseases” and “Differences between care trajectories” originated from participants working in a comprehensive cancer center, which tends to be disease-specific locations for patients on active treatment. Meanwhile, participants from primary care identified the sub-theme of “Differences in settings,” indicating that symptom management strategies are care setting specific. Conclusions While CDS can help promote evidence-based symptom management, systems providing care recommendations need to be specifically developed to fit patient characteristics and clinical context. Findings suggest that one set of algorithms will not be applicable throughout the entire cancer trajectory. Unique CDS for symptom management will be needed for patients who are cancer survivors being followed in primary care settings. |
| first_indexed | 2024-03-07T14:57:36Z |
| format | Article |
| id | doaj.art-924a9dc396bb41dabd126a37bdbf6776 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-03-07T14:57:36Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-924a9dc396bb41dabd126a37bdbf67762024-03-05T19:19:51ZengBMCBMC Medical Informatics and Decision Making1472-69472024-03-0124111310.1186/s12911-024-02466-7A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit allHayley Dunnack Yackel0Barbara Halpenny1Janet L. Abrahm2Jennifer Ligibel3Andrea Enzinger4David F. Lobach5Mary E. Cooley6Hartford HealthCare Cancer InstituteDana-Farber Cancer InstituteDana-Farber Cancer InstituteDana-Farber Cancer InstituteDana-Farber Cancer InstituteElimu InformaticsDana-Farber Cancer InstituteAbstract Background Adults with cancer experience symptoms that change across the disease trajectory. Due to the distress and cost associated with uncontrolled symptoms, improving symptom management is an important component of quality cancer care. Clinical decision support (CDS) is a promising strategy to integrate clinical practice guideline (CPG)-based symptom management recommendations at the point of care. Methods The objectives of this project were to develop and evaluate the usability of two symptom management algorithms (constipation and fatigue) across the trajectory of cancer care in patients with active disease treated in comprehensive or community cancer care settings to surveillance of cancer survivors in primary care practices. A modified ADAPTE process was used to develop algorithms based on national CPGs. Usability testing involved semi-structured interviews with clinicians from varied care settings, including comprehensive and community cancer centers, and primary care. The transcripts were analyzed with MAXQDA using Braun and Clarke’s thematic analysis method. A cross tabs analysis was also performed to assess the prevalence of themes and subthemes by cancer care setting. Results A total of 17 clinicians (physicians, nurse practitioners, and physician assistants) were interviewed for usability testing. Three main themes emerged: (1) Algorithms as useful, (2) Symptom management differences, and (3) Different target end-users. The cross-tabs analysis demonstrated differences among care trajectories and settings that originated in the Symptom management differences theme. The sub-themes of “Differences between diseases” and “Differences between care trajectories” originated from participants working in a comprehensive cancer center, which tends to be disease-specific locations for patients on active treatment. Meanwhile, participants from primary care identified the sub-theme of “Differences in settings,” indicating that symptom management strategies are care setting specific. Conclusions While CDS can help promote evidence-based symptom management, systems providing care recommendations need to be specifically developed to fit patient characteristics and clinical context. Findings suggest that one set of algorithms will not be applicable throughout the entire cancer trajectory. Unique CDS for symptom management will be needed for patients who are cancer survivors being followed in primary care settings.https://doi.org/10.1186/s12911-024-02466-7Cancer symptom managementClinical decision supportClinical practice guidelinesCancer-related fatigueCancer-related constipation |
| spellingShingle | Hayley Dunnack Yackel Barbara Halpenny Janet L. Abrahm Jennifer Ligibel Andrea Enzinger David F. Lobach Mary E. Cooley A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all BMC Medical Informatics and Decision Making Cancer symptom management Clinical decision support Clinical practice guidelines Cancer-related fatigue Cancer-related constipation |
| title | A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all |
| title_full | A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all |
| title_fullStr | A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all |
| title_full_unstemmed | A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all |
| title_short | A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all |
| title_sort | qualitative analysis of algorithm based decision support usability testing for symptom management across the trajectory of cancer care one size does not fit all |
| topic | Cancer symptom management Clinical decision support Clinical practice guidelines Cancer-related fatigue Cancer-related constipation |
| url | https://doi.org/10.1186/s12911-024-02466-7 |
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