Browsing by Author "Capurro, Daniel"

Now showing 1 - 19 of 19
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    A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images
    (2022) Messina, Pablo; Pino, Pablo; Parra Santander, Denis; Soto Arriaza, Álvaro Marcelo; Besa, Cecilia; Uribe Arancibia, Sergio A.; Andía Kohnenkampf, Marcelo Edgardo; Tejos Núñez, Cristián Andrés; Prieto Vásquez, Claudia; Capurro, Daniel
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    Analysis of Emergency Room Episodes Duration Through Process Mining
    (2019) Rojas, Eric; Cifuentes Soto, Andrés Alonso; Burattin, A.; Muñoz Gama, Jorge; Sepúlveda, Marcos; Capurro, Daniel
    This study presents the proposal of a performance analysis method for ER Processes through Process Mining. This method helps to determine which activities, sub-processes, interactions and characteristics of episodes explain why the process has long episode duration, besides providing decision makers with additional information that will help to decrease waiting times, reduce patient congestion and increment quality of provided care. By applying the exposed method to a case study, it was discovered that when a loop is formed between the Examination and Treatment sub-processes, the episode duration lengthens. Moreover, the relationship between case severity and the number of repetitions of the Examination-Treatment loop was also studied. As the case severity increases, the number of repetitions increases as well.
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    Analyzing medical emergency processes with process mining: the stroke case
    (2019) Fernandez-Llatas, Carlos; Ibanez-Sanchez, Gema; Celda, Angeles; Mandingorra, Jesus; Aparici-Tortajada, Lucia; Martinez-Millana, Antonio; Munoz-Gama, Jorge; Sepúlveda, Marcos; Rojas, Eric; Gálvez, Víctor; Capurro, Daniel; Traver, Vicente
    Medical emergencies are one of the most critical processes that occurs in a hospital. The creation of adequate and timely triage protocols, can make the difference between the life and death of the patient. One of the most critical emergency care protocols is the stroke case. This disease demands an accurate and quick diagnosis for ensuring an immediate treatment in order to limit or even, avoid, the undesired cognitive decline. The aim of this paper is perform an analysis of how Process Mining techniques can support health professionals in the interactive analysis of emergency processes considering critical timing of Stroke, using a Question Driven methodology. To demonstrate the possibilities of Process Mining in the characterization of the emergency process, we have used a real log with 9046 emergency episodes from 2145 stroke patients that occurred from January of 2010 to June of 2017. Our results demonstrate how Process Mining technology can highlight the differences of the stroke patient flow in emergency, supporting professionals in the better understanding and improvement of quality of care.
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    Association between demographic, clinical characteristics and severe complications by SARS-CoV-2 infection in a community-based healthcare network in Chile
    (2024) Leniz Martelli, Javiera; Hernández Jaña, Sam Steven; Soto Durán, Mauricio Javier; Soto, Mauricio; Arenas, Eduardo; Margozzini Maira, Paula Andrea; Suárez, Francisco; Capurro, Daniel; Rojas Villar, María Paulina; Bambs Sandoval, Claudia Elena
    Background Most of the evidence on risk factors for COVID-19 complications comes from North America or Europe with very little research from Latin-America. We aimed to evaluate the association between sociodemographic, clinical factors and the risk of COVID-19 complications among adults in Chile, the fifth Latin-American country with more COVID-19 reported cases since de beginning of the Pandemic. Methods A retrospective population-based cohort study using data from electronic health records from a large Primary Care Network, linked to national hospital, immunization, Covid-19 PCR surveillance, mortality and birth records. We included people 18+ years old enrolled in the Primary Care Network between 1st January 2020 and 31st December 2021. Using Multivariate Cox proportional hazard models, we evaluate the association between sociodemographic, clinical characteristics with three COVID-19 complications: (1) a hospital admission, (2) an ICU admission, and (3) death due to a COVID-19 infection that occurred between the 1st January 2020 and the 31st December 2021. Results 44,674 people were included. The mean age was 44.30 (sd 17.31), 55.6% were female, 15.9% had a type of healthcare insurance for people from the lowest category of income, 11.6% and 9.4% had a record of hypertension or diabetes mellitus diagnosis. Among the 44,674 people, 455 (1.02%) had a hospital admission due to a COVID-19 infection and 216(0.48%) of them also had an ICU admission. Among the 44,674 people,148(0.33%) died due to COVID-19 infection. Older age and male sex were consistently associated with a higher risk of the three COVID-19 complications. Hypertension and diabetes were associated with a higher risk of a hospital admission and death, but not with an ICU admissions due to COVID-19 infection. Having two or more COVID-19 vaccine doses compared with no doses was associated with a lower risk of any hospital admission (HR 0.81; 95% CI 0.77–0.84), an ICU admission (HR 0.60; 95% CI 0.57–0.63) and death (HR 0.50; 95% CI 0.46–0.54). Pregnant or puerperal women were more likely to be admitted to hospital (HR 2.89; 95% CI 1.41–5.89) or ICU (HR 3.04; 95% CI 1.01–9.14). Conclusions Sociodemographic and clinical factors associated with COVID-19 complications such as age, sex and pre-existing conditions were comparable to those reported in similar studies from higher-income countries, and can be used to predict severity in COVID-19 patients.
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    Epistemonikos: a comprehensive database of systematic reviews for health decision-making
    (2020) Rada G., Gabriel; Bravo Soto, Gonzalo A.; Bravo Jeria, Rocío; Capurro, Daniel; Morel Marambio, Macarena; Neumann Burotto, Gonzalo Ignacio; Ortiz Muñoz, Luis; Peña Durán, José Esteban; Rivera Mercado, Solange; Soto Subiabre, Mauricio Andrés
    Abstract Background Systematic reviews allow health decisions to be informed by the best available research evidence. However, their number is proliferating quickly, and many skills are required to identify all the relevant reviews for a specific question. Methods and findings We screen 10 bibliographic databases on a daily or weekly basis, to identify systematic reviews relevant for health decision-making. Using a machine-based approach developed for this project we select reviews, which are then validated by a network of more than 1000 collaborators. After screening over 1,400,000 records we have identified more than 300,000 systematic reviews, which are now stored in a single place and accessible through an easy-to-use search engine. This makes Epistemonikos the largest database of its kind. Conclusions Using a systematic approach, recruiting a broad network of collaborators and implementing automated methods, we developed a one-stop shop for systematic reviews relevant for health decision making.
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    Implementation science : Implications for intervention research in hospice and palliative care
    (2014) Demiris, George; Parker Oliver, Debra; Capurro, Daniel; Wittenberg-Lyles, Elaine
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    Importancia de la intención de tratar y el seguimiento en la validez interna de un estudio clínico randomizado
    (2004) Capurro, Daniel; Gabrielli, Luigi; Letelier Saavedra, Luz María
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    Mapping the patient’s journey in healthcare through process mining
    (2020) Arias, M.; Rojas, Eric; Aguirre, S.; Cornejo, F.; Muñoz Gama, Jorge; Sepúlveda Fernández, Marcos Ernesto; Capurro, Daniel
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    Messages for your health : mobile use and cancer prevention for underserved Latinas in Santiago, Chile
    (2016) Martínez Gutiérrez, Javiera; Soto Subiabre, Mauricio Andrés; Momany, Mckenzie; Ciampi, Francis; Capurro, Daniel; Cea, Emilia; Puschel Illanes, Klaus
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    Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care : Analysis Using Process Mining
    (2018) Conca, T.; Saint-Pierre Cortés, Cecilia; Herskovic, Valeria; Sepúlveda Fernández, Marcos Ernesto; Capurro, Daniel; Prieto Ugarte, Florencia; Fernandez Llatas, C.
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    PALIA-ER: Bringing question-driven process mining closer to the emergency room
    (2017) Rojas, Eric; Fernández-Llatas, Carlos; Traver, Vicente; Muñoz-Gama, Vicente; Sepúlveda, Marcos; Herskovic, Valeria; Capurro, Daniel
    This paper presents PALIA-ER, a web-based tool for question-driven process mining in Emergency Room. PALIA-ER uses Palia discovery algorithm and includes model simplification and filtering features specially domain-specific for ER. Most PALIA-ER functionalities can be easily applied to other interdisciplinary contexts such as other healthcare units, education, or logistics.
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    Preferences of Underserved Chilean Women on a Mobile Technology Intervention for Cervical Cancer Screening : Qualitative Study
    (2018) Soto Subiabre, Mauricio Andrés; Martínez Gutiérrez, Javiera; Momany, McKenzie; Capurro, Daniel; Ciampi Spode, Francis; Cea, Emilia; Mergudich, Tania; Puschel Illanes, Klaus
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    Question-Driven Methodology for Analyzing Emergency Room Processes Using Process Mining
    (2017) Rojas, Eric; Sepúlveda Fernández, Marcos Ernesto; Muñoz Gama, Jorge; Capurro, Daniel; Traver, Vicente; Fernandez Llatas, Carlos
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    System-Wide Accelerated Implementation of Telemedicine in Response to COVID-19 : Mixed Methods Evaluation
    (2020) Garcia Huidobro Munita, Diego Nicolas; Rivera Mercado, Solange; Valderrama Chang, Sebastián Matías; Bravo, P.; Capurro, Daniel
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    System-Wide Accelerated Implementation of Telemedicine in Response to COVID-19: Mixed Methods Evaluation (Preprint)
    (2020) García-Huidobro Munita, Diego Nicolás; Rivera, Solange; Valderrama Chang, Sebastián; Bravo, Paula; Capurro, Daniel
    Background: As the COVID-19 pandemic disrupted medical practice, telemedicine emerged as an alternative to outpatient visits. However, it is unknown how patients and physicians respond to an accelerated implementation of this model of medical care. Objective: To report the system-wide accelerated implementation of telemedicine, compare patient satisfaction between telemedicine and in-person visits, and report provider perceptions. Methods: A convergent parallel mixed-methods study design consisting of simultaneous use of both qualitative and quantitative methods. This study was conducted at the UC-Christus Health Network, a large private academic health network in Santiago, Chile. Satisfaction of patients receiving telemedicine care between March and April, 2020, was compared to those receiving in-person care during the same period (concurrent control group) and during March and April, 2019 (retrospective control group). Patient satisfaction with in-person care was measured using the Net Promoter Score (NPS) survey. Satisfaction with telemedicine was assessed by patients using an online survey assessing similar domains. Providers rated their satisfaction and responded to open-ended questions assessing challenges, strategies to address them, the diagnostic process, treatment, and the patient-provider relationship. Results: A total of 3,962 patients receiving telemedicine, 1,187 patients from the concurrent control group, and 1,848 from the retrospective control group completed the surveys. Satisfaction was very high with both telemedicine and in-person services. Overall, 263 physicians from over 41 specialties responded the survey. During telemedicine visits, most providers felt their clinical skills were challenged (61.8%). Female providers felt more challenged than male providers (70.7% vs 50.9%, P = .002). Surgeons, obstetricians and gynecologists felt their clinical skills were challenged the least, compared to providers from non-surgical specialties (P < .001). Challenges related to the delivery modality, diagnostic process, and patient-provider relationship differed according to the provider’s specialty (P = .046, P < .001, and P = .022, respectively). Conclusions: Telemedicine implemented in response to the COVID-19 pandemic produced high patient and provider satisfaction. Specialty groups perceive the impact of this new mode of clinical practice differently.
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    Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms : The Stroke Case
    (2019) Ibáñez Sánchez, G.; Fernández Llatas, C.; Martínez Millana, A.; Celda, A.; Mandingorra, J.; Aparici Tortajada, L.; Valero Ramón, Z.; Muñoz Gama, Jorge; Sepúlveda Fernández, Marcos Ernesto; Rojas, E.; Gálvez, V.; Capurro, Daniel; Traver, V.
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    Using Crowdsourcing Technology for Testing Multilingual Public Health Promotion Materials
    (JMIR PUBLICATIONS, INC, 2012) Turner, Anne M.; Kirchhoff, Katrin; Capurro, Daniel
    Background: Effective communication of public health messages is a key strategy for health promotion by public health agencies. Creating effective health promotion materials requires careful message design and feedback from representatives of target populations. This is particularly true when the target audiences are hard to reach as limited English proficiency groups. Traditional methods of soliciting feedback-such as focus groups and convenience sample interviews-are expensive and time consuming. As a result, adequate feedback from target populations is often insufficient due to the time and resource constraints characteristic to public health.