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The patients gave their verbal consent&#44; which was recorded in the medical history&#44; to be included in the study&#46;</p></span></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Results</span><p id="par0045" class="elsevierStylePara elsevierViewall">Of the 100 patients included&#44; 59 were men and 41 women&#44; with their ages ranging from 18 to 93 years&#46; Some 5&#37; were aged between 18 and 31 years&#59; 10&#37; between 31 and 44 years&#59; 8&#37; between 44 and 57 years&#59; 29&#37; between 57 and 70 years&#59; 26&#37; between 70 and 83 years&#59; and 22&#37; between 83 and 93 years&#46; All the patients had been admitted for pneumonia due to COVID-19 or readmitted for complications following discharge for COVID-19&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">A total of 680 called were made&#44; of which 423 were answered &#40;62&#37;&#41; and 278 completed &#40;66&#37;&#41;&#46; The average length of the calls was 2&#8239;min 16&#8239;s&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Some 15&#46;25&#37; of the calls led to an alert and were generated by 45 patients&#46; The total number of alerts detected was 85&#44; and their distribution according to age was&#58; &#60;50 years&#44; 17 alerts&#59; 50&#8211;60 years&#44; 4 alerts&#59; 60&#8211;70 years&#44; 24 alerts&#59; 70&#8211;80 years&#44; 21 alerts&#59; and &#62;80 years&#44; 19 alerts&#46; The mean number of alerts detected per each call was 1&#46;35&#46; <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> shows the alert frequency and type by age group&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">The alert for difficulty breathing was the most common as age increased&#44; while fever was the least common alert among the older patients&#46; The most frequent alerts in patients under the age of 80 were dyspnoea and general discomfort&#44; however globally fever was the most common alert&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows the evolution of the prevalence of alerts according to the time of the call&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">The highest number of alerts was detected in the calls made at 30 days&#44; the majority in relation to the onset of new symptoms unrelated to COVID-19&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">Five patients went to the Emergency Department&#44; two referred by the primary care team and three of their own volition&#46; On two occasions&#44; due to causes directly related to SARS-CoV-2 infection&#44; general discomfort&#44; and fever&#44; patients attended the Emergency Department of their own volition on a day prior to the follow-up call&#46; Neither of the two patients required admission&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">Of the 87 calls made by the nursing staff&#44; 49 &#40;56&#37;&#41; calls were alerts generated by the Tucuvi telephone assistant&#44; 42 &#40;86&#37;&#41; of which were confirmed by the nursing staff&#46; Contact was not made with the patient in four calls and the alert was not confirmed in three calls due to the following reasons&#58; having not understood the question&#44; not accurately explaining their situation leading to the generation of an alert&#44; or wanting to speak with the nursing staff&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">The nursing staff made a total of 38 &#40;44&#37;&#41; calls due to the assistant not being able to contact a patient&#46; The alert was confirmed in six of them&#59; in 17&#44; the patient&#47;caregiver did not report any alert symptoms&#44; and in 15 no response was obtained&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">In total&#44; the nursing staff confirmed 48 &#40;55&#37; of all calls&#41; alerts and referred 6&#37; to the medical team&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">One week after the end of follow-up&#44; user satisfaction was evaluated by means of a short survey&#46; A total of 46 patients completed the survey&#46; The averages ratings were&#58; the question regarding satisfaction with use of the system to improve communication with the health team&#58; 3&#46;8&#47;5&#59; regarding whether the system helped to better control the evolution of their illness&#58; 3&#46;4&#47;5&#59; and regarding the level of satisfaction with the voice used by the system that called them&#58; 4&#47;5 &#40;1 being the minimum and 5 the maximum rating&#41;&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Thirty-nine patients stated their appreciation for the virtual assistant service due to&#58; follow-up&#44; concern for the patients&#44; rapid communication&#44; frequency of contact&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">Telephone follow-up with patients following hospital discharge has been identified as a useful and cost-effective tool<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;4</span></a> that tends to be implemented in chronic pathologies such as heart failure&#44; COPD&#44; or diabetes mellitus<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5&#44;6</span></a>&#46; However&#44; this strategy uses nursing staff resources as it requires nurses to call all the discharged patients<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a>&#46; The option of selecting those that truly require a personalised call by means of an alert system that uses new technologies stands out as a significant advance&#46; Automatic calling systems are a pragmatic and economic manner of improving telephone follow-up<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8&#8211;11</span></a>&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">In our experience&#44; the virtual assistant facilitated follow-up for a highly vulnerable group&#44; namely patients admitted for COVID-19&#46; It enabled the identification of patients requiring specific health interventions and prevented any feelings of neglect or difficulty to access the health system that they might have experienced&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">The age range of the patients included in this project is wide and representative of all patients admitted for COVID-19&#46; The calls from nursing staff to patients that could not be contacted by the virtual assistant reduced the number of patients that could not be contacted down to 15 out of 100 patients&#46; The nurses resolved 94&#37; of the alerts and those that could not be solved were associated with the care pathway that the patient was to be following&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">One of the limitations to evaluating satisfaction is the small number of patients&#47;caregivers that responded to the survey&#46; Regardless&#44; it represents almost half of the sample&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">In summary&#44; the virtual caregiver is a useful tool for performing follow-up on patients following discharge&#44; regardless of their age&#46; The majority of alerts can be resolved by the nursing staff and patient satisfaction with the virtual caregiver alert system was high&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Funding</span><p id="par0130" class="elsevierStylePara elsevierViewall">None&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conflicts of interest</span><p id="par0135" class="elsevierStylePara elsevierViewall">The authors declare that they do not have any conflicts of interest&#46;</p></span></span>"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">COVID-19 has placed a significant burden on the healthcare system&#44; making it necessary to implement new tools that allow patients to be monitored remotely and guarantee quality and continuity of care&#46; The usefulness and acceptance by patients of a virtual caregiver designed for follow-up in the month following hospital discharge for COVID-19 are evaluated&#46; The virtual assistant&#44; based on voice and artificial intelligence technology&#44; made telephone calls at 48&#8239;h&#44; seven days&#44; 15 days&#44; and 30 days after discharge and asked five questions about the patient&#8217;s health&#46; If the answer to any of the questions was affirmative&#44; it generated an alert that was transferred to a healthcare professional One hundred patients were included in the project and 85 alerts were generated in 45 of the patients&#44; most at one month after hospital discharge&#46; The nursing staff resolved 94&#37; of them by telephone&#46; Patient satisfaction with the virtual caregiver was high&#46;</p></span>"
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        "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">La COVID-19 ha supuesto una gran sobrecarga para el sistema sanitario&#44; y ha sido necesario poner en marcha herramientas nuevas para realizar el seguimiento no presencial de los pacientes y garantizar la calidad de sus cuidados&#46; Se eval&#250;a la utilidad y aceptaci&#243;n de los pacientes de un cuidador virtual dise&#241;ado para su seguimiento tras el alta hospitalaria por COVID-19&#46; El asistente virtual&#44; con tecnolog&#237;a de voz e inteligencia artificial&#44; realiz&#243; llamadas telef&#243;nicas a las 48 horas&#44; 7&#44; 15 y 30 d&#237;as del alta&#44; formulando 5 preguntas sobre su estado de salud&#46; Si la contestaci&#243;n era afirmativa&#44; generaba una alerta que se transfer&#237;a a un profesional sanitario&#46; Se incluyeron 100 pacientes en el proyecto&#46; Se generaron 85 alertas en 45 de los pacientes&#44; la mayor&#237;a de ellas al mes del alta&#59; el 94&#37; lo resolvi&#243; enfermer&#237;a telef&#243;nicamente&#46; La satisfacci&#243;n de los pacientes con el cuidador virtual fue alta&#46;</p></span>"
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Journal Information
Vol. 221. Issue 8.
Pages 464-467 (October 2021)
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Vol. 221. Issue 8.
Pages 464-467 (October 2021)
Brief Original
Usefulness and acceptance of telephone monitoring by a virtual assistant for patients with COVID-19 following discharge
Utilidad y aceptación del seguimiento telefónico de un asistente virtual a pacientes COVID-19 tras el alta
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I. García Bermúdeza, M. González Mansob, E. Sánchez Sáncheza, A. Rodríguez Hitac, M. Rubio Rubiob, C. Suárez Fernándeza,
Corresponding author
csuarezf@salud.madrid.org

Corresponding author.
a Servicio de Medicina Interna, Hospital Universitario de La Princesa, Madrid, Spain
b Tucuvi Care S.L., Madrid, Spain
c Unidad de Apoyo a la Innovación, nodo de La Plataforma ITEMAS, Hospital Universitario de La Princesa, Madrid, Spain
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Abstract

COVID-19 has placed a significant burden on the healthcare system, making it necessary to implement new tools that allow patients to be monitored remotely and guarantee quality and continuity of care. The usefulness and acceptance by patients of a virtual caregiver designed for follow-up in the month following hospital discharge for COVID-19 are evaluated. The virtual assistant, based on voice and artificial intelligence technology, made telephone calls at 48 h, seven days, 15 days, and 30 days after discharge and asked five questions about the patient’s health. If the answer to any of the questions was affirmative, it generated an alert that was transferred to a healthcare professional One hundred patients were included in the project and 85 alerts were generated in 45 of the patients, most at one month after hospital discharge. The nursing staff resolved 94% of them by telephone. Patient satisfaction with the virtual caregiver was high.

Keywords:
COVID-19
Virtual caregiver
Virtual assistant
Artificial intelligence
Follow-up after discharge
Resumen

La COVID-19 ha supuesto una gran sobrecarga para el sistema sanitario, y ha sido necesario poner en marcha herramientas nuevas para realizar el seguimiento no presencial de los pacientes y garantizar la calidad de sus cuidados. Se evalúa la utilidad y aceptación de los pacientes de un cuidador virtual diseñado para su seguimiento tras el alta hospitalaria por COVID-19. El asistente virtual, con tecnología de voz e inteligencia artificial, realizó llamadas telefónicas a las 48 horas, 7, 15 y 30 días del alta, formulando 5 preguntas sobre su estado de salud. Si la contestación era afirmativa, generaba una alerta que se transfería a un profesional sanitario. Se incluyeron 100 pacientes en el proyecto. Se generaron 85 alertas en 45 de los pacientes, la mayoría de ellas al mes del alta; el 94% lo resolvió enfermería telefónicamente. La satisfacción de los pacientes con el cuidador virtual fue alta.

Palabras clave:
COVID-19
Cuidador virtual
Asistente virtual
Inteligencia artificial
Seguimiento tras el alta

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