1
|
Benmessaoud C, Pfisterer KJ, De Leon A, Saragadam A, El-Dassouki N, Young KGM, Lohani R, Xiong T, Pham Q. Design of a Dyadic Digital Health Module for Chronic Disease Shared Care: Development Study. JMIR Hum Factors 2023; 10:e45035. [PMID: 38145480 PMCID: PMC10775044 DOI: 10.2196/45035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 03/08/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic forced the spread of digital health tools to address limited clinical resources for chronic health management. It also illuminated a population of older patients requiring an informal caregiver (IC) to access this care due to accessibility, technological literacy, or English proficiency concerns. For patients with heart failure (HF), this rapid transition exacerbated the demand on ICs and pushed Canadians toward a dyadic care model where patients and ICs comanage care. Our previous work identified an opportunity to improve this dyadic HF experience through a shared model of dyadic digital health. We call this alternative model of care "Caretown for Medly," which empowers ICs to concurrently expand patients' self-care abilities while acknowledging ICs' eagerness to provide greater support. OBJECTIVE We present the systematic design and development of the Caretown for Medly dyadic management module. While HF is the outlined use case, we outline our design methodology and report on 6 core disease-invariant features applied to dyadic shared care for HF management. This work lays the foundation for future usability assessments of Caretown for Medly. METHODS We conducted a qualitative, human-centered design study based on 25 semistructured interviews with self-identified ICs of loved ones living with HF. Interviews underwent thematic content analysis by 2 coders independently for themes derived deductively (eg, based on the interview guide) and inductively refined. To build the Caretown for Medly model, we (1) leveraged the Knowledge to Action (KTA) framework to translate knowledge into action and (2) borrowed Google Sprint's ability to quickly "solve big problems and test new ideas," which has been effective in the medical and digital health spaces. Specifically, we blended these 2 concepts into a new framework called the "KTA Sprint." RESULTS We identified 6 core disease-invariant features to support ICs in care dyads to provide more effective care while capitalizing on dyadic care's synergistic benefits. Features were designed for customizability to suit the patient's condition, informed by stakeholder analysis, corroborated with literature, and vetted through user needs assessments. These features include (1) live reports to enhance data sharing and facilitate appropriate IC support, (2) care cards to enhance guidance on the caregiving role, (3) direct messaging to dissolve the disconnect across the circle of care, (4) medication wallet to improve guidance on managing complex medication regimens, (5) medical events timeline to improve and consolidate management and organization, and (6) caregiver resources to provide disease-specific education and support their self-care. CONCLUSIONS These disease-invariant features were designed to address ICs' needs in supporting their care partner. We anticipate that the implementation of these features will empower a shared model of care for chronic disease management through digital health and will improve outcomes for care dyads.
Collapse
Affiliation(s)
- Camila Benmessaoud
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Kaylen J Pfisterer
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Anjelica De Leon
- Healthcare Human Factors, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Faculty of Media and Arts, Humber College, Toronto, ON, Canada
| | - Ashish Saragadam
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada
| | - Noor El-Dassouki
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Karen G M Young
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Raima Lohani
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Ting Xiong
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Quynh Pham
- Centre for Digital Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Telfer School of Management, University of Ottawa, Ottawa, ON, Canada
| |
Collapse
|
2
|
Khan DZ, Hanrahan JG, Baldeweg SE, Dorward NL, Stoyanov D, Marcus HJ. Current and Future Advances in Surgical Therapy for Pituitary Adenoma. Endocr Rev 2023; 44:947-959. [PMID: 37207359 PMCID: PMC10502574 DOI: 10.1210/endrev/bnad014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 03/14/2023] [Accepted: 05/17/2023] [Indexed: 05/21/2023]
Abstract
The vital physiological role of the pituitary gland, alongside its proximity to critical neurovascular structures, means that pituitary adenomas can cause significant morbidity or mortality. While enormous advancements have been made in the surgical care of pituitary adenomas, numerous challenges remain, such as treatment failure and recurrence. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (eg, endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient's journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, surgical abilities will be augmented by the future operative armamentarium, including advanced optical devices, smart instruments, and surgical robotics. Intraoperative support to surgical team members will benefit from a data science approach, utilizing machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, neural networks leveraging multimodal datasets will allow early detection of individuals at risk of complications and assist in the prediction of treatment failure, thus supporting patient-specific discharge and monitoring protocols. While these advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of the translation of such technologies, ensuring systematic assessment of risk and benefit prior to clinical implementation. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future.
Collapse
Affiliation(s)
- Danyal Z Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, UK
| | - John G Hanrahan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, UK
| | - Stephanie E Baldeweg
- Department of Diabetes & Endocrinology, University College London Hospitals NHS Foundation Trust, London NW1 2BU, UK
- Centre for Obesity and Metabolism, Department of Experimental and Translational Medicine, Division of Medicine, University College London, London WC1E 6BT, UK
| | - Neil L Dorward
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, UK
- Digital Surgery Ltd, Medtronic, London WD18 8WW, UK
| | - Hani J Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, UK
| |
Collapse
|
3
|
Vercell A, Gasteiger N, Yorke J, Dowding D. Patient-facing cancer mobile apps that enable patient reported outcome data to be collected: A systematic review of content, functionality, quality, and ability to integrate with electronic health records. Int J Med Inform 2023; 170:104931. [PMID: 36462398 DOI: 10.1016/j.ijmedinf.2022.104931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/30/2022] [Accepted: 11/16/2022] [Indexed: 11/27/2022]
Abstract
PURPOSE Enabling cancer patients to self-manage symptoms through mobile applications can result in more informed, autonomous patients who are partners in their care, consequently reducing the burden on health services. Electronic patient reported outcomes completed before a clinical review can increase the frequency and quality of holistic assessments, while integration into electronic health records can maximise clinical utility. The ability of apps to integrate with electronic health records is key to providing a real-time interface between patient reports and healthcare response. This review identifies patient-facing cancer apps which can record patient reported outcomes, and explores their purpose, functionality, quality, and ability to integrate with electronic health records. METHODS A systematic app review and content synthesis was conducted on patient-facing cancer apps available in the United Kingdom. Where applicable, the review aligned with the Preferred Reporting Items for Systematic Reviews and meta-Analysis. Two validated scales assessed functionality and quality: The IMS Institute for Healthcare Informatics functionality score and the Mobile App Rating Scale. Flesch-Kincaid metrics explored readability. RESULTS Apple App and Google Play stores identified 405 apps, of which 12 met the eligibility criteria. All were free to download, 1 (8%) had in-app purchases/subscriptions. Nine (75%) were affiliated with a professional health body/charity. Six (50%) analysed inputted data and provided medical advice based on answers. The average Flesch Reading Ease score was 42.7 out of 100. The apps had an average of 7.3 functions each and a mean MARS score of 4/5. None integrated with electronic health records. CONCLUSION While many cancer apps exist, few enable patient reported outcomes to be recorded and shared with clinicians in real-time. Further research is warranted to explore the feasibility of integrating with electronic health records, as this function can improve patient experience and outcomes, and increase efficiency of hospital resources through more proactive care.
Collapse
Affiliation(s)
- Amy Vercell
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, United Kingdom; Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.
| | - Norina Gasteiger
- Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Janelle Yorke
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, United Kingdom; Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Dawn Dowding
- Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| |
Collapse
|
4
|
Williams S, Layard Horsfall H, Funnell JP, Hanrahan JG, Khan DZ, Muirhead W, Stoyanov D, Marcus HJ. Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm. Cancers (Basel) 2021; 13:cancers13195010. [PMID: 34638495 PMCID: PMC8508169 DOI: 10.3390/cancers13195010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/02/2021] [Accepted: 10/03/2021] [Indexed: 01/01/2023] Open
Abstract
Artificial intelligence (AI) platforms have the potential to cause a paradigm shift in brain tumour surgery. Brain tumour surgery augmented with AI can result in safer and more effective treatment. In this review article, we explore the current and future role of AI in patients undergoing brain tumour surgery, including aiding diagnosis, optimising the surgical plan, providing support during the operation, and better predicting the prognosis. Finally, we discuss barriers to the successful clinical implementation, the ethical concerns, and we provide our perspective on how the field could be advanced.
Collapse
Affiliation(s)
- Simon Williams
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
- Correspondence:
| | - Hugo Layard Horsfall
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Jonathan P. Funnell
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - John G. Hanrahan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Danyal Z. Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - William Muirhead
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Danail Stoyanov
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Hani J. Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| |
Collapse
|