Post-discharge after surgery Virtual Care with Remote Automated Monitoring-1 (PVC-RAM-1) technology versus standard care: randomised controlled trial,The BMJ

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Post-discharge after surgery Virtual Care with Remote Automated Monitoring-1 (PVC-RAM-1) technology versus standard care: randomised controlled trial
The BMJ ( IF 93.6 ) Pub Date : 2021-09-30 , DOI: 10.1136/bmj.n2209
Michael H McGillion _{1,

2} , Joel Parlow _{3,

4} , Flavia K Borges _{2,

5,

6} , Maura Marcucci _{5,

6} , Michael Jacka ₇ , Anthony Adili _{8,

9} , Manoj M Lalu _{10,

11} , Carley Ouellette ₁ , Marissa Bird ₁ , Sandra Ofori _{2,

12} , Pavel S Roshanov ₁₃ , Ameen Patel _{5,

14} , Homer Yang _{15,

16} , Susan O'Leary _{14,

17} , Vikas Tandon _{5,

9} , Gavin M Hamilton _{10,

11} , Marko Mrkobrada ₁₃ , David Conen _{2,

5,

6} , Valerie Harvey ₂ , Jennifer Lounsbury _{1,

14} , Rajibul Mian ₂ , Shrikant I Bangdiwala _{2,

6} , Ramiro Arellano _{3,

4} , Ted Scott ₁₄ , Gordon H Guyatt _{5,

6} , Peggy Gao ₂ , Michelle Graham ₁₈ , Rahima Nenshi _{8,

9} , Alan J Forster _{11,

19} , Mahesh Nagappa _{15,

16} , Kelsea Levesque ₁ , Kristen Marosi ₂₀ , Sultan Chaudhry ₅ , Shariq Haider ₅ , Lesly Deuchar ₂₁ , Brandi LeBlanc ₉ , Colin J L McCartney ₁₀ , Emil H Schemitsch ₂₂ , Jessica Vincent ₂ , Shirley M Pettit ₁₄ , Deborah DuMerton ₄ , Angela Djuric Paulin ₁₄ , Marko Simunovic ₈ , David C Williams ₂₃ , Samantha Halman _{11,

19} , John Harlock ₈ , Ralph M Meyer _{14,

24} , Dylan A Taylor ₁₈ , Harsha Shanthanna ₁₇ , Christopher M Schlachta ₂₂ , Neil Parry ₂₂ , David R Pichora ₂₅ , Haroon Yousuf ₅ , Elizabeth Peter ₂₆ , Andre Lamy _{2,

8,

14} , Jeremy Petch ₁₄ , Husein Moloo _{11,

27} , Herman Sehmbi _{13,

15} , Melissa Waggott ₂₈ , Jessica Shelley ₄ , Emilie P Belley-Cote _{2,

5} , P J Devereaux _{5,

6,

29} ,

Affiliation

School of Nursing, McMaster University, Hamilton, Ontario, Canada.
Population Health Research Institute, Hamilton, Ontario, Canada.
Department of Anesthesiology and Perioperative Medicine, Queen's University, Kingston, Ontario, Canada.
Department of Anesthesiology and Perioperative Medicine, Kingston Health Sciences Centre, Kingston, Ontario, Canada.
Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
Departments of Critical Care and Anesthesiology, University of Alberta, Edmonton, Alberta, Canada.
Department of Surgery, McMaster University, Hamilton, Ontario, Canada.
St Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada.
Department of Anesthesiology and Pain Medicine, The University of Ottawa and The Ottawa Hospital, Ottawa, Ontario, Canada.
The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Department of Internal Medicine, University of Port Harcourt, Port Harcourt, Nigeria, West Africa.
Department of Medicine, Schulich School of Medicine, University of Western Ontario, London, Ontario, Canada.
Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Department of Anesthesia and Perioperative Medicine, Schulich School of Medicine, University of Western Ontario, London, Ontario, Canada.
Department of Anesthesia & Perioperative Medicine, London Health Sciences Centre, London, Ontario, Canada.
Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada.
Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Department of Medicine, The University of Ottawa and The Ottawa Hospital, Ottawa, Ontario, Canada.
Department of Medicine, Queen's University, Kingston, Ontario, Canada.
Alberta Health Services, Alberta, Canada.
Department of Surgery, University of Western Ontario and London Health Sciences Centre, London, Ontario, Canada.
Department of Surgery, University of Alberta, Edmonton, Alberta, Canada.
Department of Oncology, McMaster University, Hamilton, Ontario, Canada.
Department of Surgery, Queen's University and Kingston Health Sciences Centre, Kingston, Ontario, Canada.
Lawrence S Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.
Department of Surgery, The University of Ottawa and The Ottawa Hospital, Ottawa, Ontario, Canada.
The Ottawa Hospital, Ottawa, Ontario, Canada.
Population Health Research Institute, Hamilton, Ontario, Canada

Objective To determine if virtual care with remote automated monitoring (RAM) technology versus standard care increases days alive at home among adults discharged after non-elective surgery during the covid-19 pandemic. Design Multicentre randomised controlled trial. Setting 8 acute care hospitals in Canada. Participants 905 adults (≥40 years) who resided in areas with mobile phone coverage and were to be discharged from hospital after non-elective surgery were randomised either to virtual care and RAM (n=451) or to standard care (n=454). 903 participants (99.8%) completed the 31 day follow-up. Intervention Participants in the experimental group received a tablet computer and RAM technology that measured blood pressure, heart rate, respiratory rate, oxygen saturation, temperature, and body weight. For 30 days the participants took daily biophysical measurements and photographs of their wound and interacted with nurses virtually. Participants in the standard care group received post-hospital discharge management according to the centre’s usual care. Patients, healthcare providers, and data collectors were aware of patients’ group allocations. Outcome adjudicators were blinded to group allocation. Main outcome measures The primary outcome was days alive at home during 31 days of follow-up. The 12 secondary outcomes included acute hospital care, detection and correction of drug errors, and pain at 7, 15, and 30 days after randomisation. Results All 905 participants (mean age 63.1 years) were analysed in the groups to which they were randomised. Days alive at home during 31 days of follow-up were 29.7 in the virtual care group and 29.5 in the standard care group: relative risk 1.01 (95% confidence interval 0.99 to 1.02); absolute difference 0.2% (95% confidence interval −0.5% to 0.9%). 99 participants (22.0%) in the virtual care group and 124 (27.3%) in the standard care group required acute hospital care: relative risk 0.80 (0.64 to 1.01); absolute difference 5.3% (−0.3% to 10.9%). More participants in the virtual care group than standard care group had a drug error detected (134 (29.7%) v 25 (5.5%); absolute difference 24.2%, 19.5% to 28.9%) and a drug error corrected (absolute difference 24.4%, 19.9% to 28.9%). Fewer participants in the virtual care group than standard care group reported pain at 7, 15, and 30 days after randomisation: absolute differences 13.9% (7.4% to 20.4%), 11.9% (5.1% to 18.7%), and 9.6% (2.9% to 16.3%), respectively. Beneficial effects proved substantially larger in centres with a higher rate of care escalation. Conclusion Virtual care with RAM shows promise in improving outcomes important to patients and to optimal health system function. Trial registration ClinicalTrials.gov [NCT04344665][1]. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT04344665&atom=%2Fbmj%2F374%2Fbmj.n2209.atom

中文翻译：

术后出院后采用远程自动监测 1 (PVC-RAM-1) 技术的虚拟护理与标准护理：随机对照试验

目的确定采用远程自动监测 (RAM) 技术的虚拟护理与标准护理相比是否可以增加在 covid-19 大流行期间非选择性手术后出院的成年人的在家生存天数。设计多中心随机对照试验。在加拿大设立8家急症护理医院。参与者 905 名居住在手机覆盖地区且在非选择性手术后即将出院的成年人（≥ 40 岁）被随机分配到虚拟护理和 RAM (n=451) 或标准护理 (n=454) 。 903 名参与者 (99.8%) 完成了 31 天的随访。干预实验组的参与者接受了平板电脑和 RAM 技术，用于测量血压、心率、呼吸频率、氧饱和度、温度和体重。在 30 天的时间里，参与者每天进行生物物理测量并拍摄伤口照片，并与护士进行虚拟互动。标准护理组的参与者按照中心的常规护理接受出院后管理。患者、医疗保健提供者和数据收集者都了解患者的分组分配。结果评审员对分组分配不知情。主要结果指标主要结果是 31 天的随访期间在家中存活的天数。 12 项次要结局包括急性住院护理、药物错误的检测和纠正，以及随机分组后 7、15 和 30 天的疼痛情况。结果所有 905 名参与者（平均年龄 63.1 岁）均按随机分组进行分析。在 31 天的随访期间，虚拟护理组的在家存活天数为 29.7 天，标准护理组的在家存活天数为 29.5 天：相对风险 1.01（95% 置信区间 0.99 至 1.02）；绝对差异 0.2%（95% 置信区间 -0。5％至0.9％）。虚拟护理组中有 99 名参与者 (22.0%) 和标准护理组有 124 名参与者 (27.3%) 需要紧急住院护理：相对风险 0.80（0.64 至 1.01）；绝对差异 5.3%（-0.3% 至 10.9%）。虚拟护理组中检测到用药错误的参与者多于标准护理组（134 例（29.7%）v 25 例（5.5%）；绝对差异 24.2%、19.5% 至 28.9%）并纠正了药物错误（绝对差异 24.4%），19.9% 至 28.9%）。虚拟护理组中报告随机化后 7、15 和 30 天疼痛的参与者少于标准护理组：绝对差异为 13.9%（7.4% 至 20.4%）、11.9%（5.1% 至 18.7%）和 9.6%（分别为 2.9% 至 16.3%）。事实证明，护理升级率较高的中心的有益效果要大得多。结论 RAM 虚拟护理有望改善对患者重要的结果和优化卫生系统功能。试验注册 ClinicalTrials.gov [NCT04344665][1]。 [1]：/lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT04344665&atom=%2Fbmj%2F374%2Fbmj.n2209。原子

更新日期：2021-09-30

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