Co-design of a Mobile App for Engaging Breast Cancer Patients in Reporting Health Experiences: Qualitative Case Study.

BACKGROUND: The World Health Organization recommends incorporating patient-reported experience measures and patient-reported outcome measures to ensure care processes. New technologies, such as mobile apps, could help report and monitor patients' adverse effects and doubts during treatment. However, engaging patients in the daily use of mobile apps is a challenge that must be addressed in accordance with the needs of people. OBJECTIVE: We present a qualitative case study documenting the process of identifying the information needs of breast cancer patients and health care professionals during the treatment process in a Chilean cancer institution. The study aims to identify patients' information requirements for integration into a mobile app that accompanies patients throughout their treatment while also providing features for reporting adverse symptoms. METHODS: We conducted focus groups with breast cancer patients who were undergoing chemotherapy (n=3) or who completed chemotherapy between 3 months and 1 year (n=1). We also surveyed health care professionals (n=9) who were involved in patient care and who belonged to the oncology committee of the cancer center where the study took place. Content analysis was applied to the responses to categorize the information needs and the means to satisfy them. A user interface was designed according to the findings of the focus groups and was assessed by 3 trained information system and user interaction design experts from 2 countries, using heuristic evaluation guidelines for mobile apps. RESULTS: Patients' information needs were classified into 4 areas: an overview of the disease, information on treatment and day-to-day affairs, assistance on the normality and abnormality of symptoms during treatment, and symptoms relevant to report. Health care professionals required patients to be provided with information on the administrative and financial process. We noted that the active involvement of the following 4 main actors is required to satisfy the information needs: patients, caregivers, social network moderators, and health professionals. Seven usability guidelines were extracted from the heuristic evaluation recommendations. CONCLUSIONS: A mobile app that seeks to accompany breast cancer patients to report symptoms requires the involvement of multiple participants to handle the reports and day-to-day information needs. User interfaces must be designed with consideration of the patient's social conventions and the emotional load of the disease information.

Standards, Processes, and Tools Used to Evaluate the Quality of Health Information Systems: Systematic Literature Review.

BACKGROUND: Evaluating health information system (HIS) quality is strategically advantageous for improving the quality of patient care. Nevertheless, few systematic studies have reported what methods, such as standards, processes, and tools, were proposed to evaluate HIS quality. OBJECTIVE: This study aimed to identify and discuss the existing literature that describes standards, processes, and tools used to evaluate HIS quality. METHODS: We conducted a systematic literature review using review guidelines focused on software and systems. We examined seven electronic databases-Scopus, ACM (Association for Computing Machinery), ScienceDirect, Google Scholar, IEEE Xplore, Web of Science, and PubMed-to search for and select primary studies. RESULTS: Out of 782 papers, we identified 17 (2.2%) primary studies. We found that most of the primary studies addressed quality evaluation from a management perspective. On the other hand, there was little explicit and pragmatic evidence on the processes and tools that allowed for the evaluation of HIS quality. CONCLUSIONS: To promote quality evaluation of HISs, it is necessary to define mechanisms and methods that operationalize the standards in HISs. Additionally, it is necessary to create metrics that measure the quality of the most critical components and processes of HISs.

Improvement in Quality of Life with Use of Ambient-Assisted Living: Clinical Trial with Older Persons in the Chilean Population.

In Chile, 18% of the population is over 60 years old and is projected to reach 31% in three decades. An aging population demands the development of strategies to improve quality of life (QoL). In this randomized trial, we present the implementation and evaluation of the Quida platform, which consists of a network of unintrusive sensors installed in the houses of elderly participants to monitor their activities and provide assistance. Sixty-nine elderly participants were included. A significant increase in overall QoL was observed amongst participants allocated to the interventional arm (p < 0.02). While some studies point out difficulties monitoring users at home, Quida demonstrates that it is possible to detect presence and movement to identify patterns of behavior in the sample studied, allowing us to visualize the behavior of older adults at different time intervals to support their medical evaluation.

Using Low-Resolution Non-Invasive Infrared Sensors to Classify Activities and Falls in Older Adults.

The population is aging worldwide, creating new challenges to the quality of life of older adults and their families. Falls are an increasing, but not inevitable, threat to older adults. Information technologies provide several solutions to address falls, but smart homes and the most available solutions require expensive and invasive infrastructures. In this study, we propose a novel approach to classify and detect falls of older adults in their homes through low-resolution infrared sensors that are affordable, non-intrusive, do not disturb privacy, and are more acceptable to older adults. Using data collected between 2019 and 2020 with the eHomeseniors platform, we determine activity scores of older adults moving across two rooms in a house and represent an older adult fall through skeletonization. We find that our twofold approach effectively detects activity patterns and precisely identifies falls. Our study provides insights to physicians about the daily activities of their older adults and could potentially help them make decisions in case of abnormal behavior.

System Design for Emergency Alert Triggered by Falls Using Convolutional Neural Networks.

The world population ageing is on the rise, which has led to an increase in the demand for medical care due to diseases and symptoms prevalent in health centers. One of the most prevalent symptoms prevalent in older adults is falls, which affect one-third of patients each year and often result in serious injuries that can lead to death. This paper describes the design of a fall detection system for elderly households living alone using very low resolution thermal sensor arrays. The algorithms implemented were LSTM, GRU, and Bi-LSTM; the last one mentioned being that which obtained the best results at 93% in accuracy. The results obtained aim to be a valuable tool for accident prevention for those patients that use it and for clinicians who manage the data.

eHomeSeniors Dataset: An Infrared Thermal Sensor Dataset for Automatic Fall Detection Research.

Automatic fall detection is a very active research area, which has grown explosively since the 2010s, especially focused on elderly care. Rapid detection of falls favors early awareness from the injured person, reducing a series of negative consequences in the health of the elderly. Currently, there are several fall detection systems (FDSs), mostly based on predictive and machine-learning approaches. These algorithms are based on different data sources, such as wearable devices, ambient-based sensors, or vision/camera-based approaches. While wearable devices like inertial measurement units (IMUs) and smartphones entail a dependence on their use, most image-based devices like Kinect sensors generate video recordings, which may affect the privacy of the user. Regardless of the device used, most of these FDSs have been tested only in controlled laboratory environments, and there are still no mass commercial FDS. The latter is partly due to the impossibility of counting, for ethical reasons, with datasets generated by falls of real older adults. All public datasets generated in laboratory are performed by young people, without considering the differences in acceleration and falling features of older adults. Given the above, this article presents the eHomeSeniors dataset, a new public dataset which is innovative in at least three aspects: first, it collects data from two different privacy-friendly infrared thermal sensors; second, it is constructed by two types of volunteers: normal young people (as usual) and performing artists, with the latter group assisted by a physiotherapist to emulate the real fall conditions of older adults; and third, the types of falls selected are the result of a thorough literature review.

Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks.

Networks used in biological applications at different scales (molecule, cell and population) are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linear Wilson-Cowan system) as well as in their discrete Boolean versions (e.g., non-linear Hopfield system); in both cases, the notion of interaction graph G(J) associated to its Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J), kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems. We will give some general results available for both continuous and discrete biological networks, and then study some specific applications of three new notions of entropy: (i) attractor entropy, (ii) isochronal entropy and (iii) entropy centrality; in three domains: a neural network involved in the memory evocation, a genetic network responsible of the iron control and a social network accounting for the obesity spread in high school environment.

Evolution of social networks: the example of obesity.

The present paper deals with the effect of the social transmission of nutrition habits in a social and biological age-dependent context on obesity, and accordingly on type II diabetes and among its complications, the neurodegenerative diseases. The evolution of social networks and inside a network the healthy weight of a person are depending on the context in which this person has contacts and exchanges concerning his alimentation, physical activity and sedentary habits, inside the dominant social network in which the person lives (e.g., scholar for young, professional for adult, home or institution for elderly people). Three successive steps of evolution will be considered for social networks (like for neural one's): initial random connectivity, destruction and consolidation of links following a new transition rule called homophilic until an asymptotic architectural organization and configuration of states. The application of such a network dynamics concerns the sequence overweight/obesity/type II diabetes and neurodegenerative diseases.

Challenges in surveillance of all cancer cases: The Chilean National Cancer Registry. / Desafíos en la vigilancia de todos los casos de cáncer en Chile: Registro Nacional de Cáncer.

Cancer causes millions of deaths worldwide, making its registration essential. There are clinical, hospital, and population-based registries in place. The latter is the gold standard for information on cancer incidence and survival in a defined region. Chile has five population-based registries located in specific areas of the country. The Chilean National Cancer Registry emerged with the challenge of creating a tool encompassing all three types of registries to identify the number of cancer cases by type. Its design involved a series of actions to achieve consensus among various actors regarding information, validation, and events to be registered. Four stages were identified in the care and registration process: suspected diagnosis, morphological confirmation (biopsy), clinical resolution (oncology committee, including treatment recommendations), treatment, and oncological follow-up. The platform's development (from 2018 to 2021) involved gathering information and agreements on the requirements for co-designing the registry, including a successful pilot program with over 20 public and private healthcare facilities that recorded nearly 7500 cancer cases. The deployment and use of the National Cancer Registry at a national level depends on the healthcare authority. It is an information system that continuously and systematically collects, stores, processes, and analyzes data on all cancer cases and types occurring in the country. This work presents the design and development of the tool, the challenges addressed, as well as its strengths and weaknesses.

El cáncer causa millones de muertes a nivel mundial por lo que su registro es fundamental, existiendo registros clínicos, hospitalarios y poblacionales. Estos últimos son el estándar de oro para la información sobre incidencia y supervivencia de cáncer en una región definida. En Chile se cuenta con cinco registros poblacionales ubicados en ciertas zonas del país. El Registro Nacional del Cáncer chileno surge como un desafío para conformar una herramienta transversal a los tres tipos de registro con la finalidad de, al menos, conocer la cantidad de casos por tipo de cáncer. Su diseño implicó un despliegue de acciones orientadas a lograr consensos entre diversos actores respecto de la información, validación y eventos necesarios de registrar. Se identificaron cuatro etapas en el proceso de atención y el registro: sospecha de diagnóstico, confirmación morfológica (biopsia), resolución clínica (comité oncológico incluyendo la indicación de tratamiento), tratamiento y seguimiento oncológico. A su vez, el desarrollo de la plataforma (años 2018 a 2021) implicó levantamiento de información y acuerdos sobre los requerimientos para el co-diseño del registro, incluyendo un exitoso pilotaje con más de 20 establecimientos de salud del sector público y privado con registro de cerca de 7500 casos de cáncer. El despliegue y uso del Registro Nacional de Cáncer a nivel nacional depende de la autoridad sanitaria. Se trata de un sistema de información que recolecta, almacena, procesa y analiza de forma continua y sistemática datos sobre todos los casos y tipos de cánceres que ocurren en el país. En este trabajo se presenta el diseño y desarrollo de la herramienta, los desafíos abordados, sus fortalezas y debilidades.

A contemporary review of breast cancer risk factors and the role of artificial intelligence.

Background: Breast cancer continues to be a significant global health issue, necessitating advancements in prevention and early detection strategies. This review aims to assess and synthesize research conducted from 2020 to the present, focusing on breast cancer risk factors, including genetic, lifestyle, and environmental aspects, as well as the innovative role of artificial intelligence (AI) in prediction and diagnostics. Methods: A comprehensive literature search, covering studies from 2020 to the present, was conducted to evaluate the diversity of breast cancer risk factors and the latest advances in Artificial Intelligence (AI) in this field. The review prioritized high-quality peer-reviewed research articles and meta-analyses. Results: Our analysis reveals a complex interplay of genetic, lifestyle, and environmental risk factors for breast cancer, with significant variability across different populations. Furthermore, AI has emerged as a promising tool in enhancing the accuracy of breast cancer risk prediction and the personalization of prevention strategies. Conclusion: The review highlights the necessity for personalized breast cancer prevention and detection approaches that account for individual risk factor profiles. It underscores the potential of AI to revolutionize these strategies, offering clear recommendations for future research directions and clinical practice improvements.

How effective are mobile apps in managing people with type 2 diabetes mellitus? A systematic literature review protocol.

INTRODUCTION: The rise of new technologies in the field of health is yielding promising results. In certain chronic conditions such as type 2 diabetes mellitus, which ranks among the top five causes of global mortality, it could be useful in supporting patient management. MATERIALS AND METHODS: A systematic review will be conducted on scientific publications from the last 5 years (January 2019 to October 2023) to describe the effect of mobile app usage on glycated hemoglobin for the management of adult patients with type 2 diabetes mellitus who participated in randomized controlled clinical trials. The search will be carried out in the databases of MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), CENTRAL, WoS, Scopus, Epistemonikos, and LILACS. The search strategy will be constructed using both controlled and natural language. Additionally, the Cochrane filter will be applied to identify randomized controlled trials. The review will include scientific articles reporting studies that present results from randomized controlled trials, with texts in Spanish, English, or French, utilizing mobile applications for the management of adult individuals (over 18 years) with type 2 diabetes mellitus, and whose outcomes report the effects on glycated hemoglobin. The Cochrane Risk of Bias Tool will be used to assess the quality of the studies, and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology will be implemented to evaluate the certainty of the evidence. RESULTS: The analysis will be conducted by observing the value of the glycated hemoglobin levels of the participants. Given that this data is a quantitative and continuous value, it facilitates the identification of the effects of the mobile applications used for the management of type 2 diabetes mellitus (T2DM) in adults. Furthermore, if sufficient data are available, a meta-analysis will be conducted using IBM-SPSS. The effect of the intervention will be estimated by the mean difference. All point estimates will be accompanied by 95% confidence intervals. A random effects model will be used. The heterogeneity of the results will be assessed using Cochrane's Q and I2 statistics. DISCUSSION: Considering that the quality of content and functionality of certain applications in the healthcare field is highly variable, it is necessary to evaluate the scientific evidence reported on the effect of the use of this type of technology in people with T2DM.

Differential Effects of a Telemonitoring Platform in the Development of Chemotherapy-Associated Toxicity: A Randomized Trial Protocol.

Chemotherapy requires careful monitoring, but traditional follow-up approaches face significant challenges that were highlighted by the COVID-19 pandemic. Hence, exploration into telemonitoring as an alternative emerged. The objective is to assess the impact of a telemonitoring platform that provides clinical data to physicians overseeing solid tumor patients, aiming to enhance the care experience. The methodology outlines a parallel-group randomized clinical trial involving recently diagnosed patients with solid carcinomas preparing for curative intent chemotherapy. Eligible adult patients diagnosed with specific carcinoma types and proficient in Spanish, possessing smartphones, will be invited to participate. They will be randomized using concealed allocation sequences into two groups: one utilizing a specialized smartphone application called Contigo for monitoring chemotherapy toxicity symptoms and accessing educational content, while the other receives standard care. Primary outcome assessment involves patient experience during chemotherapy using a standardized questionnaire. Secondary outcomes include evaluating severe chemotherapy-associated toxicity, assessing quality of life, and determining user satisfaction with the application. The research will adhere to intention-to-treat principles. This study has been registered at ClinicalTrials.gov (NCT06077123).

Effects on Quality of Life of a Telemonitoring Platform amongst Patients with Cancer (EQUALITE): A Randomized Trial Protocol.

Cancer, a pervasive global health challenge, necessitates chemotherapy or radiotherapy treatments for many prevalent forms. However, traditional follow-up approaches encounter limitations, exacerbated by the recent COVID-19 pandemic. Consequently, telemonitoring has emerged as a promising solution, although its clinical implementation lacks comprehensive evidence. This report depicts the methodology of a randomized trial which aims to investigate whether leveraging a smartphone app called Contigo for disease monitoring enhances self-reported quality of life among patients with various solid cancers compared to standard care. Secondary objectives encompass evaluating the app's impact on depressive symptoms and assessing adherence to in-person appointments. Randomization will be performed independently using an allocation sequence that will be kept concealed from clinical investigators. Contigo offers two primary functions: monitoring cancer patients' progress and providing educational content to assist patients in managing common clinical situations related to their disease. The study will assess outcomes such as quality of life changes and depressive symptom development using validated scales, and adherence to in-person appointments. Specific scales include the EuroQol Group's EQ-5D questionnaire and the Patient Health Questionnaire (PHQ-9). We hypothesize that the use of Contigo will assist and empower patients receiving cancer treatment, which will translate to better quality of life scores and a reduced incidence of depressive symptoms. All analyses will be undertaken with the intention-to-treat principle by a statistician unaware of treatment allocation. This trial is registered in ClinicalTrials under the registration number NCT06086990.

Architecture Assessment of the Chilean Epidemiological Surveillance System for Notifiable Diseases (EPIVIGILA): Qualitative Study.

BACKGROUND: To fulfill their epidemiological vigilance function, authorities require valid, complete, timely, precise, and reliable information. Advancements in new technologies have facilitated public health control through vigilance systems for notifiable diseases; these systems can gather large numbers of simultaneous notifications, process a wide array of data, and deliver updated information in real time to relevant decision-makers. A large worldwide deployment of new information technologies was seen during the COVID-19 pandemic; these technologies proved to be efficient, resourceful tools . Platform developers should seek self-evaluation strategies to optimize functionality or improve the capacity of national vigilance systems. These tools exist in the Latin American region at various development stages, although publications reporting architectural characteristics of these tools are scarce. International publications are more abundant a nd serve as a basis for comparing the standards that need to be met. OBJECTIVE: This study aimed to assess the architecture of the Chilean epidemiological surveillance system for notifiable diseases (EPIVIGILA), as compared to that of the international systems reported in scientific publications. METHODS: A search for scientific publications was conducted to identify systematic reviews that documented the architectural characteristics of disease notification and vigilance systems. EPIVIGILA was compared to other systems from countries in Africa, the Americas, Asia, Europe, and Oceania. RESULTS: The following aspects of the architecture were identified: (1) notification provenance, (2) minimum data set, (3) database users, and (4) data quality control. The notifying organizations, including hospitals, clinics, laboratories, and medical consultation offices, were similar among the 13 countries analyzed; this contrasted with Chile, where the reporting agent is the physician who can belong to an organization. The minimum data set include patient identification, disease data, and general codifications. EPIVIGILA includes all these elements, in addition to symptomatology, hospitalization data, type of medicine and treatment result, and laboratory test types. The database users or data analyzers include public health organizations, research organizations, epidemiological organizations, health organizations or departments, and the Centers for Disease Control and Prevention. Finally, for data quality control, the criteria most often used were completeness, consistency, validity, timeliness, accuracy, and competencies. CONCLUSIONS: An efficient notification and vigilance system must be capable of promptly identifying probable risks as well as incidence and prevalence of the diseases under surveillance. EPIVIGILA has been shown to comply with high quality and functionality standards, at the level of developed countries, by achieving total national coverage and by providing timely, trustworthy, and complete information at high-security levels, thus obtaining positive assessment from national and international authorities.

Barriers and Facilitators of Ambient Assisted Living Systems: A Systematic Literature Review.

Ambient Assisted Living Systems (AALSs) use information and communication technologies to support care for the growing population of older adults. AALSs focus on providing multidimensional support to families, primary care facilities, and patients to improve the quality of life of the elderly. The literature has studied the qualities of AALSs from different perspectives; however, there has been little discussion regarding the operational experience of developing and deploying such systems. This paper presents a literature review based on the PRISMA methodology regarding operational facilitators and barriers of AALSs. This study identified 750 papers, of which 61 were selected. The results indicated that the selected studies mentioned more barriers than facilitators. Both barriers and facilitators concentrate on aspects of developing and configuring the technological infrastructure of AALSs. This study organizes and describes the current literature on the challenges and opportunities regarding the operation of AALSs in practice, which translates into support for practitioners when developing and deploying AALSs.

Effects of internet-based telemonitoring platforms on the quality of life of oncologic patients: A systematic literature review protocol.

INTRODUCTION: Telemonitoring involves the transmission of clinical information through digital means, including internet-connected devices such as smartphones, health tracking apps and video conferencing platforms. This strategy could provide a viable alternative to facilitate follow-up in several conditions, including cancer. OBJECTIVES: To synthesise the available evidence on the effectiveness of internet-based telemonitoring platforms amongst oncological patients. Relevant endpoints include overall quality of life, the ability to detect postoperative complications, severe toxicity reactions attributable to chemotherapy, reducing the frequency of hospitalisations, emergency department visits and mortality. METHODS: A systematic review of published and unpublished randomised and controlled studies will be carried out. Iterative searches in PubMED/MEDLINE, EMBASE, Epistemonikos, LILACS, and Cochrane CENTRAL repositories from January 2000 to January 2023 will be conducted. Grey literature repositories, such as Clinicaltrials, BioRxiv and MedRxiv will be searched as well. The Cochrane risk of bias tool will be used to assess the quality of the eligible studies. If possible, a meta-analysis based on the random-effects model will be conducted to evaluate changes in any of the aforementioned outcomes. Heterogeneity will be assessed with Cochrane's Q and I2 statistics. Its exploration will be carried out using subgroup and sensitivity analyses. Relevant subgroups include the proportion of elderly patients in each study, characteristics of each platform, study type, type of funding and moment of conduction (i.e. before or after the COVID-19 pandemic). Publication bias will be assessed using funnel plots and Egger's test. REGISTRATION: This systematic review protocol is registered in PROSPERO. Its registration number is CRD42023412705.

Global Pain and Aging: A Cross-Sectional Study on Age Differences in the Intensity of Chronic Pain Among Middle-Aged and Older Adults in 20 Countries.

OBJECTIVES: This study aims to examine age differences in the intensity of chronic pain among middle-aged and older adults, where intensity is measured on a scale differentiating between chronic pain that is often troubling and likely requires intervention versus more endurable sensations. We aim to explore whether individual health and national gross domestic product (GDP) explain these differences as well. METHODS: Cross-nationally harmonized data from 20 countries on self-reported intensity of chronic pain (0 = no, 1 = mild, 2 = moderate, 3 = severe) in 104,826 individuals aged 50+ observed in 2012-2013. Two-level hierarchical ordinal linear models with individuals nested within countries were used to isolate estimations from heterogeneity explained by methodological differences across single-country studies. RESULTS: Overall, mean participant age was 66.9 (SD = 9.9), 56.1% were women, and 41.9% of respondents reported any chronic pain. Chronic pain intensity rose sharply with age in some countries (e.g., Korea and Slovenia), but this association waned or reversed in other countries (e.g., the United States and Denmark). Cross-country variation and age differences in chronic pain were partly explained (85.5% and 35.8%, respectively) by individual-level health (especially arthritis), country-level wealth (as indicated by GDP per capita), and demographics. DISCUSSION: Chronic pain intensity is not an inevitable consequence of chronological age, but the consequence of potential selection effects and lower activity levels combined with individual-level health and country-level wealth. Our findings suggest further investigation of health conditions and country affluence settings as potential targets of medical and policy interventions aiming to prevent, reduce, or manage chronic pain among older patients and aging populations.

Detection of COVID-19 Patients Using Machine Learning Techniques: A Nationwide Chilean Study.

Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in Chile. Nevertheless, given the extensive volume of data controlled by Epivigila, it is difficult for health professionals to classify vast volumes of data to determine which symptoms and comorbidities are related to infected patients. This paper aims to compare machine learning techniques (such as support-vector machine, decision tree and random forest techniques) to determine whether a patient has COVID-19 or not based on the symptoms and comorbidities reported by Epivigila. From the group of patients with COVID-19, we selected a sample of 10% confirmed patients to execute and evaluate the techniques. We used precision, recall, accuracy, F1-score, and AUC to compare the techniques. The results suggest that the support-vector machine performs better than decision tree and random forest regarding the recall, accuracy, F1-score, and AUC. Machine learning techniques help process and classify large volumes of data more efficiently and effectively, speeding up healthcare decision making.

Sensitivity and Specificity of Patient-Reported Clinical Manifestations to Diagnose COVID-19 in Adults from a National Database in Chile: A Cross-Sectional Study.

(1) Background: The diagnosis of COVID-19 is frequently made on the basis of a suggestive clinical history and the detection of SARS-CoV-2 RNA in respiratory secretions. However, the diagnostic accuracy of clinical features is unknown. (2) Objective: To assess the diagnostic accuracy of patient-reported clinical manifestations to identify cases of COVID-19. (3) Methodology: Cross-sectional study using data from a national registry in Chile. Infection by SARS-CoV-2 was confirmed using RT-PCR in all cases. Anonymised information regarding demographic characteristics and clinical features were assessed using sensitivity, specificity, and diagnostic odds ratios. A multivariable logistic regression model was constructed to combine epidemiological risk factors and clinical features. (4) Results: A total of 2,187,962 observations were available for analyses. Male participants had a mean age of 43.1 ± 17.5 years. The most common complaints within the study were headache (39%), myalgia (32.7%), cough (31.6%), and sore throat (25.7%). The most sensitive features of disease were headache, myalgia, and cough, and the most specific were anosmia and dysgeusia/ageusia. A multivariable model showed a fair diagnostic accuracy, with a ROC AUC of 0.744 (95% CI 0.743-0.746). (5) Discussion: No single clinical feature was able to fully confirm or exclude an infection by SARS-CoV-2. The combination of several demographic and clinical factors had a fair diagnostic accuracy in identifying patients with the disease. This model can help clinicians tailor the probability of COVID-19 and select diagnostic tests appropriate to their setting.