Search

The use of mobile health apps to improve diet and nutrition behaviors has increased in recent years. Several studies have described the benefits and advantages of this technology as a complement to interventions for improving nutrition behaviors and nutrition‐related health outcomes, including obesity indices and clinical parameters. Few of these works have developed clinical mobile health apps for children, and although parents play a critical role in children's nutrition behaviors, work targeting parents is scarce. The work presented in this paper describes the development of the PersuHabit app, a stand-alone mobile health app targeting parents to promote the intake of fruits and vegetables (FVs) and reduce the intake of ultra-processed foods (UPF) in children aged 6 to 10 years. The paper also presents the execution of an exploratory pilot study to assess the feasibility, acceptability, and preliminary effects of the PersuHabit app. The results are presented and discussed, and actions for further improvement of the PersuHabit app are identified. [ABSTRACT FROM AUTHOR]

Employing software engineering to build an integrated, standardized, and scalable solution is closely associated with the healthcare domain. Furthermore, new diagnostic techniques have been developed to obtain better results in less time, saving costs, and bringing services closer to the most unprotected areas. This paper presents the integration of a top-notch component, such as hardware, software, telecommunications, and medical equipment, to produce a complete system of Electronic Health Record (EHR). The EHR implementation aims to contribute to the expansion of the health services offer concerning people who live in locations where typically have difficult access to medical care. The methodology throughout the work is a Strategic Planning to set priorities, focus energy and resources, strengthen operations, ensure that directors, managers, employees, and other stakeholders are working toward common goals, establish agreement around intended outcomes/results. A medical and technical team is incorporated to complete the tasks of process and requirements analysis, software coding and design, technical support, training, and coaching for EHR system users throughout the implementation process. The adoption of those tools reflect notably some expected results and benefits on patient care. The EHR implementation ensures that information collection does not duplicate already existing information or duplicate effort and maximize the practical use of the data collected. Moreover, the EHR reduces mistakes in hospital readmissions, improves paperwork, promotes the progress of the state's health care system providing emergency, specialty, and primary health care in a rural area of Campeche. The EHR implementation is critical to support decision making and to promote public health. The total number of consults increased markedly from 2012 (14021) to 2019 (34751). The most commonly treated diseases in this region of Mexico are hypertension (17632) and diabetes (13156). The best results are obtained in the Nutrition (20,61%) and clinical psychology services (16,67%), and the worst levels are registered in pediatric and surgical oncology services where only 1,59% and 1,97% of the patients are admitted in less than 30 min, respectively. [ABSTRACT FROM AUTHOR]

One of the most common chronic diseases that causes missed school days and workdays is pediatric asthma, producing education, health and economic delays in low and middle-income countries. A patient-centered remarkable therapeutic strategy in the prevention and treatment of chronic diseases is the Therapeutic Patient Education (TPE) which denotes an outstanding difference in the outcomes, from the awareness, to the personal treatment adaption to prevent crises. In this paper, an intervention of TPE with learning objects (LOs) of a pediatric asthma course, designed to train the uncontrolled patient and the caregiver as a team on the specific knowledge to self-control the disease, was carried out at a health facility in Mexico. The Asthma Control Test (ACT) was used and the learning performance was evaluated with formative quizzes. A randomized controlled trial was designed, with pairs of children patients and caregivers during 60 days; the control group was trained with the usual approach, receiving general information about the disease. ACT measures showed statistical significance for the TPE group after the use of the LOs, achieving a controlled state, while the control group did not show difference. Also, the intervention group obtained a higher score in learning performance assessment. The users learned how to avoid risks, the personal triggers of the patient, how to correctly use the different treatments and accessories, consequently, they learned how to self-manage the disease. Our study also confirmed that control of asthma is not only a matter of knowledge, but financial issues to afford the treatment. [ABSTRACT FROM AUTHOR]

It is known that the data preparation phase is the most time consuming in the data mining process, using up to 50 % or up to 70 % of the total project time. Currently, data mining methodologies are of general purpose and one of their limitations is that they do not provide a guide about what particular task to develop in a specific domain. This paper shows a new data preparation methodology oriented to the epidemiological domain in which we have identified two sets of tasks: General Data Preparation and Specific Data Preparation. For both sets, the Cross-Industry Standard Process for Data Mining (CRISP-DM) is adopted as a guideline. The main contribution of our methodology is fourteen specialized tasks concerning such domain. To validate the proposed methodology, we developed a data mining system and the entire process was applied to real mortality databases. The results were encouraging because it was observed that the use of the methodology reduced some of the time consuming tasks and the data mining system showed findings of unknown and potentially useful patterns for the public health services in Mexico. [ABSTRACT FROM AUTHOR]

Identifying risk factors associated with COVID-19 lethality is crucial in combating the ongoing pandemic. In this study, we developed lethality predictive models for each epidemiological wave and for the overall dataset using the Extreme Gradient Boosting technique and analyzed them using Shapley values to determine the contribution levels of various features, including demographics, comorbidities, medical units, and recent medical information from confirmed COVID-19 cases in Mexico between February 23, 2020, and April 15, 2022. The results showed that pneumonia and advanced age were the most important factors predicting patient death in all cohorts. Additionally, the medical unit where the patient received care acted as a risk or protective factor. IMSS medical units were identified as high-risk factors in all cohorts, except in wave four, while SSA medical units generally were moderate protective factors. We also found that intubation was a high-risk factor in the first epidemiological wave and a moderate-risk factor in the following waves. Female gender was a protective factor of moderate-high importance in all cohorts, while being between 18 and 29 years old was a moderate protective factor and being between 50 and 59 years old was a moderate risk factor. Additionally, diabetes (all cohorts), obesity (third wave), and hypertension (fourth wave) were identified as moderate risk factors. Finally, residing in municipalities with the lowest Human Development Index level represented a moderate risk factor. In conclusion, this study identified several significant risk factors associated with COVID-19 lethality in Mexico, which could aid policymakers in developing targeted interventions to reduce mortality rates. [ABSTRACT FROM AUTHOR]

The article presents the study which examined the application of parameter weighting for linear prediction cepstral coefficients (LPCC) for the robust representation of infant cry signals. Also cited are the three classes of infant cry signals like normal cry signals and the cry signals from babies with asphyxia, the use of probabilistic neural network (PNN) to classify infant cry signals, and the possible reasons why an infant cries like pain, hunger, and discomfort.

We present a study on the quality of operation and the characteristics of the medical imaging equipment in three specialty hospitals of the Mexican Health System. Six month residencies were carried out in order to better understand the problems and internal functioning of the three imaging departments. The kinds of equipment, the types of equipment failures and the internal operation of these services were analyzed. The results allow us to identify four factors that are linked to faults in the quality of the health care delivered to patients. The first factor is equipment obsolescence; the second is related to deficient preventive maintenance procedures and problems associated the supervising of external service providers. The third factor is derived from the equipment’s (over) workload, which is indirectly tied to the age of the imaging modalities and the fourth factor is misuse of the equipment. The solutions to these problems include the modernization of the equipment and a better supervision by the clinical engineering department of all the processes involving the medical imaging services in each hospital. In addition to this, a special effort of the continuing education of personnel associated with medical imaging at all levels should be carried out. [ABSTRACT FROM AUTHOR]