e.g. mhealth
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How to Improve Pancreatic Cancer Network Care Using a Human-Centered Design Sprint
Over the past decades, oncological health care services have changed considerably. For many types of cancer, the increasing complexity of care has led to the centralization of care. Centralization refers to the policy in which (parts of) oncological care, such as surgery, is concentrated to expert centers or high-volume hospitals. The main aims for centralization are improved quality of care and patient outcomes, better use of resources, and cost reduction [1].
J Med Internet Res 2025;27:e55598
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In the context of social care for older adults, continuity of care can be defined as the degree to which a series of discrete care events are perceived as coherent, connected, and consistent with the needs of older adults and personal context [12,13]. Digital care records, an example of welfare technology, provide quick access to the updated information, often entered by multiple care providers.
JMIR Nursing 2025;8:e65641
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In this context, there has been increasing emphasis on developing effective cancer care that provides continuous, comprehensive support alongside standard oncological treatment, aiming to address patients’ physical and psychological needs and to promote behavioral change across the cancer care continuum [3].
J Med Internet Res 2025;27:e76968
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Given their central role in patient care, nurses are key users of digital nursing technologies (DNTs) and play a crucial role in their adoption and effective implementation in nursing care settings [6].
J Med Internet Res 2025;27:e64616
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Regarding strategies for implementing AI-based CDSS in clinical practice, a study conducted by Peek et al [13] analyzed the literature and concluded that perspectives from groups other than health care professionals (eg, patients, carers, AI developers, health care managers, and leaders, and especially regulators and policy makers) should be investigated.
JMIR Med Inform 2025;13:e69688
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There has been no planning or design of a system to access medical care and develop health care guidelines for COVID-19 patients to ensure they can correctly and safely manage their initial care. Additionally, there is no established guideline for postrecovery care for patients returning to normalcy after recovering from COVID-19 to ensure they can resume their normal work activities.
JMIR Nursing 2025;8:e65310
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Natural language processing (NLP) of clinic text notes is one promising solution to extracting care quality data from unstructured text [9], with previous studies focusing on pain care quality in primary care and chiropractic care settings [10,11]. Use cases for NLP across other clinical domains highlight its potential utility in information extraction and analysis tasks.
JMIR Med Inform 2025;13:e66466
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We used existing data to estimate the annual health care costs related to inpatient and ED care among people experiencing homelessness. We relied on previous studies on health care utilization among people experiencing homelessness in Texas to determine the average number and range of ED [31-34] and inpatient visits [31,35] (Multimedia Appendix 1).
JMIR Form Res 2025;9:e64973
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Telemedicine helped fill several health care service gaps that emerged during the pandemic, especially in the context of SRH [11]. First, telemedicine allowed patients to consult with health care providers remotely, reducing the need for in-person visits to health care facilities [12]. This was particularly important during the pandemic when minimizing physical contact was essential to curb the spread of the virus. Second, telemedicine platforms were used for COVID-19 screening and triage [5].
J Med Internet Res 2025;27:e60369
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The prehospital setting represents a critical area of emergency medical care. Emergency medical services (EMSs) providers, such as emergency medical technicians, firefighters, and paramedics care for diverse patient populations in variable in highly acute settings; they are often the first to respond to life-threatening scenarios such as traumatic injury or cardiac arrest.
JMIR XR Spatial Comput 2025;2:e66222
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