Showing 961 - 980 results of 2,677 for search 'care function (generated OR general)', query time: 0.21s Refine Results
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    Demand and Influencing factors for community health services during chemotherapy of patients with advanced cancer by Qianqian Li, Xunrui Chen, Wenying Zhang, Haihua Yuan, Yanjie Zhang, Bin Jiang, Feng Liu

    Published 2024-06-01
    “…It includes three demand dimensions (psychological, medical care, social support) and 38 demand items. The contents cover general information such as demographic and sociological information(educational level, marital status, source of medical expenses, disposable monthly household income, patient group participation), and tumor diagnosis(type and time of diagnosis, pain score, comorbidities), along with items on psychological demand (6 items), medical care demand (24 items), and social support demand (8 items). …”
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    Designing and validating a clinical decision support algorithm for diabetic nephroprotection in older patients by Simon LeClerc, Nicolas Fernandez, Kelley Kilpatrick, Cheryl Sadowski, Noor Alsalemi, Naoual Elftouh, Jean-Philippe Lafrance, Sherilyn Houle

    Published 2024-09-01
    “…The aim of this research is to design and validate a CDS algorithm for prescribing renin-angiotensin-aldosterone system inhibitors (RAASi) for older patients with diabetes.Methods The design of the CDS tool included the following phases: (1) gathering evidence from systematic reviews and meta-analyses of randomised clinical trials to determine the number needed to treat (NNT) and time-to-benefit (TTB) values applicable to our target population for use in the algorithm. (2) Building a list of potential cases that addressed different prescribing scenarios (starting, adding or switching to RAASi). (3) Reviewing relevant guidelines and extracting all recommendations related to prescribing RAASi for DKD. (4) Matching NNT and TTB with specific clinical cases. (5) Validating the CDS algorithm using Delphi technique.Results We created a CDS algorithm that covered 15 possible scenarios and we generated 36 personalised and nine general recommendations based on the calculated and matched NNT and TTB values and considering the patient’s life expectancy and functional capacity. …”
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