Electronic Health Records Design in the Nutrition Care Center of Teaching Factory at Politeknik Negeri Jember, Indonesia

The Nutrition Care Center (NCC) is one of the teaching factories (TEFA) at Politeknik Negeri Jember that provides community nutrition services. Preliminary data collection found that the factory did not have complete health database of their staff so that nutritionists find it difficult to screen for non-communicable disease risk factors. In this study, the use of Electronic Health Record (EHR) equipped with Clinical Decision Support System (CDSS) was incorporated to record, retrieve, archive, and update patients and other medical records in the NCC. This system provides easier health record management for the nutritionist team at the NCC TEFA Politeknik Negeri Jember. Medical records help them conduct screening on non-communicable disease (NCD) risk factors and make clinical decision support for doctors/counselors which have missions to reduce NCD cases in the productive age. This study used a waterfall method model and collected data through a literature review, observation, and interviews. The results produced an application of a clinic database management in which all data and information could be integrated well to improve the quality of services and facilitate data storage and access. This study concludes that the EHRs generates quick and accurate information to support operations and decision-making in the NCC

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis

a b s t r a c t Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making

A modular, open-source information extraction framework for identifying clinical concepts and processes of care in clinical narratives

In this thesis, a synthesis is presented of the knowledge models required by clinical informa- tion systems that provide decision support for longitudinal processes of care. Qualitative research techniques and thematic analysis are novelly applied to a systematic review of the literature on the challenges in implementing such systems, leading to the development of an original conceptual framework. The thesis demonstrates how these process-oriented systems make use of a knowledge base derived from workflow models and clinical guidelines, and argues that one of the major barriers to implementation is the need to extract explicit and implicit information from diverse resources in order to construct the knowledge base. Moreover, concepts in both the knowledge base and in the electronic health record (EHR) must be mapped to a common ontological model. However, the majority of clinical guideline information remains in text form, and much of the useful clinical information residing in the EHR resides in the free text fields of progress notes and laboratory reports. In this thesis, it is shown how natural language processing and information extraction techniques provide a means to identify and formalise the knowledge components required by the knowledge base. Original contributions are made in the development of lexico-syntactic patterns and the use of external domain knowledge resources to tackle a variety of information extraction tasks in the clinical domain, such as recognition of clinical concepts, events, temporal relations, term disambiguation and abbreviation expansion. Methods are developed for adapting existing tools and resources in the biomedical domain to the processing of clinical texts, and approaches to improving the scalability of these tools are proposed and evalu- ated. These tools and techniques are then combined in the creation of a novel approach to identifying processes of care in the clinical narrative. It is demonstrated that resolution of coreferential and anaphoric relations as narratively and temporally ordered chains provides a means to extract linked narrative events and processes of care from clinical notes. Coreference performance in discharge summaries and progress notes is largely dependent on correct identification of protagonist chains (patient, clinician, family relation), pronominal resolution, and string matching that takes account of experiencer, temporal, spatial, and anatomical context; whereas for laboratory reports additional, external domain knowledge is required. The types of external knowledge and their effects on system performance are identified and evaluated. Results are compared against existing systems for solving these tasks and are found to improve on them, or to approach the performance of recently reported, state-of-the- art systems. Software artefacts developed in this research have been made available as open-source components within the General Architecture for Text Engineering framework

Influences of Serendipity on Consumer Medical Information Personalization

Serendipity is an important concept in the field of information science. It has a potential of enhancing information seeking process by unexpected discovery. Serendipitous recommendation has been incorporated into the design of personalized systems to minimize blind spots in information delivery. Little evidence has been found to identify how serendipity influences personalization of consumer medical information delivery. This dissertation attempts to examine what roles serendipity plays in filtering consumer medical information and to understand how to incorporate serendipity in an effective manner. In addition, the study seeks to clarify user attitudes on unexpected discoveries of medical content in filtering settings as well as users' interest changes during this process. To empirically analyze the influence of serendipity, a medical news filtering system named MedSDFilter was developed. The system can personalize the delivery of news articles based on users' interest profiles. In MedSDFilter, serendipitous recommendation was integrated into personalized filtering through one of three serendipity models (randomness-based, knowledge-based and learning-based). Using Medical News Today site as information source, three different system modalities were compared by conducting user experiments. Thirty staff members were recruited to read and rate medical news delivered by one of three system modalities. The results of user study indicate that serendipity has an important role in medical news content delivery. As for how to incorporate serendipity, it is shown that using physician knowledge effectively enhanced serendipitous recommendation. In addition, the results suggest that the performance of serendipitous recommendation was further improved after learning algorithms were adopted. This study also provide some evidence to show user satisfaction on unexpected discovery and user interest change associated with this type of discovery. Finally, the study demonstrated the individual difference in seeking consumer medical information. The results of this study provide the system designers implications and suggestions to avoid potential drawbacks related to over-personalization in information delivery. This study enhances the understanding of users' behavior regarding the consumption of medical information and generates new guidelines which can be used in developing information systems in medical area.Doctor of Philosoph

Using machine learning for automated de-identification and clinical coding of free text data in electronic medical records

The widespread adoption of Electronic Medical Records (EMRs) in hospitals continues to increase the amount of patient data that are digitally stored. Although the primary use of the EMR is to support patient care by making all relevant information accessible, governments and health organisations are looking for ways to unleash the potential of these data for secondary purposes, including clinical research, disease surveillance and automation of healthcare processes and workflows. EMRs include large quantities of free text documents that contain valuable information. The greatest challenges in using the free text data in EMRs include the removal of personally identifiable information and the extraction of relevant information for specific tasks such as clinical coding. Machine learning-based automated approaches can potentially address these challenges. This thesis aims to explore and improve the performance of machine learning models for automated de-identification and clinical coding of free text data in EMRs, as captured in hospital discharge summaries, and facilitate the applications of these approaches in real-world use cases. It does so by 1) implementing an end-to-end de-identification framework using an ensemble of deep learning models; 2) developing a web-based system for de-identification of free text (DEFT) with an interactive learning loop; 3) proposing and implementing a hierarchical label-wise attention transformer model (HiLAT) for explainable International Classification of Diseases (ICD) coding; and 4) investigating the use of extreme multi-label long text transformer-based models for automated ICD coding. The key findings include: 1) An end-to-end framework using an ensemble of deep learning base-models achieved excellent performance on the de-identification task. 2) A new web-based de-identification software system (DEFT) can be readily and easily adopted by data custodians and researchers to perform de-identification of free text in EMRs. 3) A novel domain-specific transformer-based model (HiLAT) achieved state-of-the-art (SOTA) results for predicting ICD codes on a Medical Information Mart for Intensive Care (MIMIC-III) dataset comprising the discharge summaries (n=12,808) that are coded with at least one of the most 50 frequent diagnosis and procedure codes. In addition, the label-wise attention scores for the tokens in the discharge summary presented a potential explainability tool for checking the face validity of ICD code predictions. 4) An optimised transformer-based model, PLM-ICD, achieved the latest SOTA results for ICD coding on all the discharge summaries of the MIMIC-III dataset (n=59,652). The segmentation method, which split the long text consecutively into multiple small chunks, addressed the problem of applying transformer-based models to long text datasets. However, using transformer-based models on extremely large label sets needs further research. These findings demonstrate that the de-identification and clinical coding tasks can benefit from the application of machine learning approaches, present practical tools for implementing these approaches, and highlight priorities for further research

El tratamiento personalizado de la insuficiencia velofaríngea mediante injerto adiposo autólogo de la faringe

La incompetencia velofaríngea (IVP), definida por Lermoyez como un “desajuste anatómico y funcional entre el paladar blando y la faringe durante el habla”, es un problema funcional que requiere una gestión multidisciplinar con un estudio dinámico de las dos estructuras implicadas en el emisión de las palabras mediante la visión directa de los movimientos musculares durante la producción de fonemas. Varios estudios radiológicos han trabajado en la visualización dinámica del cierre velofaríngeo. Pigott fue el primero en introducir la nasofibroscopia en el estudio de la IVP. Ahora, el uso de la resonancia magnética funcional para el estudio del habla está en pleno desarrollo. Éste es un trabajo muy prometedor, pero todavía está en el campo de la investigación. El historial de tratamiento de la IVP depende estrictamente de la cirugía secundaria de fisura palatina. Se han descrito varios procedimientos, que se pueden clasificar en faringoplastias activas y pasivas. Las faringoplastias activas son un conjunto de procedimientos que tienen el objetivo de avanzar la pared faríngea posterior o reducir el espacio entre las paredes faríngeas laterales con una sutura del paladar a la faringe, a través de uno o dos colgajos faríngeos. Estas técnicas tienen muchas complicaciones importantes: obstrucción de vías respiratorias, sangrado intraoperatorio y aletracion de la ventilación nasal. En los pacientes que padecen una apnea obstructiva conocida, la intervención está contraindicada. Para dar una solución a los pacientes con contraindicaciones y a los pacientes con insuficiencia velofaríngea moderada, se han propuesto alternativas menos invasivas: el objetivo de las faringoplastias pasivas es facilitar el rol oclusivo del paladar mediante la reducción de la distancia de la pared faríngea posterior , a través de un complemento a la obturación natural que ofrece el anillo de Passavant. Clasicamente se han utilizado diversos materiales, pero últimamente la técnica más utilizada es el autoinjerto del retrofaringe con células adiposas, por la facilidad de muestreo y manejo del tejido adiposo. La cirugía del habla es una cirugía funcional que requiere un enfoque multidisciplinar cuyo resultado está estrictamente relacionado con la indicación adecuada. El cirujano debe integrar la información de los diferentes profesionales, adaptarla al patrón clínico ya la historia del paciente, valorar los riesgos en relación con los beneficios esperados y, finalmente, decidir la técnica más adecuada en la clínica y en la anatomía funcional específica del paciente. Se trata, pues, de una decisión con muchas variables, aunque en pacientes pediátricos debe considerarse también la cuarta dimensión del tiempo: la intervención debe realizarse en el momento màs adecuado a la etapa evolutiva del paciente. La presencia de todas estas variables dificulta mucho el momento de la toma de decisiones del médico, complicada además por la falta de consenso en la literatura. OBJECTIVO DE LA TESIS El objetivo de esta tesis es estudiar la toma de decisiones entre las opciones quirúrgicas existentes y adaptarlo a cada sujeto que presenta IVP, con el objetivo de construir planes quirúrgicos personalizados. Históricamente, este proceso de toma de decisiones se llevó a cabo, por un lado, a partir de la experiencia personal del cirujano y, por otro, teniendo en cuenta el estudio de la bibliografía. El resultado esperado de este trabajo es sumar a la experiencia personal del cirujano y a la incertidumbre por una literatura muy controvertida, un componente científico a través del análisis matemático de las variables que pueden ayudar a la decisión quirúrgica. Para ello, mediante un modelo reproducible de las variables, hemos construido un diagrama de decisión, que permite la mejor interpretación de los resultados quirúrgicos, para ayudar a escoger la técnica más adecuada para el paciente según su situación anatómica, clínica y evolutiva. METODOLOGIA Esta tesis se basa en un estudio observacional retrospectivo sobre 244 pacientes consecutivos sometidos a cirugía velofaríngea para el tratamiento de la IVP en un único centro hospitalario de tercer nivel entre 1982 y 2019. 130 pacientes fueron excluidos del estudio porque su historia clínica y/o su seguimiento postoperatorio (12 meses) estaban incompletos. Hemos incluido todas las etiologías (fisura palaciega, fisura labial y palaciega, fisura palaciega submucosa, IVP aislada). Todos los pacientes son francófonos. La revisión preoperatoria incluye logopedia con aerofonoscopio, nasofibroscopia y evaluación ORL. Los grados de gravedad de la IVP se clasificaron según la clasificación de Borrel Maisonny (BM). El análisis de los resultados utiliza, en primer lugar, métodos estadísticos tradicionales como la regresión logística y lineal, el índice de propensión y el análisis marginal. Estos métodos requieren datos clínicos a gran escala para garantizar una reproducibilidad y especificidad significativas. Por otro lado, un análisis estadístico sobre muestras grandes corre el riesgo de dar un punto de vista despersonalizado que no tenga en cuenta la especificidad única del sujeto. Para resolver este problema, exploramos las fronteras de la inteligencia artificial con técnicas de aprendizaje automático con dos beneficios esperados. En primer lugar, el análisis algorítmico del aprendizaje automático mediante modelos matemáticos mucho más complejos puede ser más adecuado a la realidad, dando explicaciones específicas de cada caso también en el ámbito local. En segundo lugar, el análisis algorítmico permite estudiar a su vez diferentes modalidades de variables y ordenarlas en importancia en función de la expresión probabilística en la realidad. Este punto es muy importante para la priorización de la toma de decisiones. Se han utilizado dos métodos de aprendizaje automático: el árbol de decisión y el algoritmo "interpreto-ML Explainable Boosting Machine". De acuerdo a los resultados obtenidos, hemos construido un árbol de decisión que describe las variables preoperatorias, con la selección de parámetros que estadísticamente estaban asociados a una gran probabilidad de éxito o fracaso. RESULTADOS Se han estudiado las historias clínicas de 114 pacientes de edades comprendidas entre los 4 y los 48 años, de los cuales 63 (55,26%) fueron sometidos a faringoplastia y 51 (44,74%) a injerto, técnica introducida en el servicio en 2006. En el grupo de faringoplastia, el 42,86% fueron hombres y el 57,14% mujeres. La media de edad era de 6 años (IQR: 5-7). 18 (28,57%) de ellos tenían trastornos genéticos o sindrómicos. El diagnóstico más frecuente fue la fisura labiopalatina (30 pacientes, 47,62%), seguido de la fisura palatina con 22 pacientes (34,92%) y la IVP aislada con 11 pacientes (17,46%). Un BMpre de 3 fue el valor inicial más representado (28 pacientes, 44,44%), mientras que BMpre = 2m y BMpre = 2b y BMpre = 1-2 se encontraron en 11 (17,46%), 22 ( 34,92%) y 2 (3,17%) pacientes respectivamente. Por lo que se refiere al grupo de pacientes sometidos a injerto de tejido adiposo, mujeres y hombres fueron, respectivamente, el 50,98% (26 pacientes) y el 49,02% (25 pacientes). La media de edad era de 7 años (IQR: 6-11). 17 pacientes (33,33%) sufrían trastornos genéticos y el diagnóstico más frecuente fue la fisura palatina (26 pacientes, 50,98%), seguido de la fisura labiopalatina (21 pacientes, 41,18%) e IVP aislada (4 pacientes, 7,84%). El valor inicial de BM fue significativamente superior en el del grupo de faringoplastia (p<0,001). Por el contrario, la edad de los pacientes sometidos a injerto de grasa fue significativamente superior a la de los pacientes tratados con faringoplastia, tanto cuando la edad se considera continua (p<0,001) como categórica (p<0,001). El seguimiento medio es de 19,5 años. Mediante el análisis de las fichas de los pacientes operados por injerto graso pudimos demostrar que los pacientes menores de 7 años obtienen resultados postoperatorios más favorables (p=0,03) en comparación con los niños mayores. Si comparamos a los pacientes operados por injerto de grasa con los pacientes operados por faringoplastia, encontramos que los pacientes que se sometieron a una faringoplastia tenían puntuaciones de BM significativamente peores en comparación con los pacientes operados por injerto de tejido adiposo, pero la edad de los pacientes sometidos a injerto de tejido adiposo era significativamente más alta. No hemos encontrado ninguna superioridad significativa de una técnica sobre otra. No tenemos complicaciones en el grupo del injerto de grasa, pero la tasa de fracaso ha sido del 7,84%, resuelta con una nueva faringoplastia. Por otra parte, la faringoplastia de primera línea no registró ningún fracaso, pero un paciente presentó un síndrome de apnea obstructiva del sueño postoperatorio. El análisis marginal demostró que la edad por debajo de los 7 años, la fisura de labiopalatina, la ausencia de síndrome y el IVP intermitente son un importante predictor de buen resultado independientemente de la técnica quirúrgica. El análisis con aprendizaje automático, por un lado, confirmó los resultados de las estadísticas tradicionales y, por otro, nos permitió introducir las variables relativas a los datos fibroscópicos en el modelo de la elección quirúrgica. Por tanto, podemos concluir que el factor más importante que discrimina la elección quirúrgica es la fibroscopia. Entre las diferentes observaciones que ofrece la exploración fibroscópica, la característica más importante para realizar una elección está representada por las dimensiones del gap velofaríngeo, seguida del tono y la movilidad del paladar blando. El otro elemento clave a la hora de elegir una técnica sobre la otra es el BM preoperatorio. Las variables edad, etiología y alteraciones genéticas son también de gran interés para predecir el éxito postoperatorio. CONCLUSIONES La bibliografía de cirugía del habla está dominada por estudios caracterizados por diagramas de decisión basados en la experiencia de las diferentes escuelas quirúrgicas. Cada escuela prioriza de manera distinta la importancia de las variables en la toma de decisión. En este contexto, presentamos los resultados a largo plazo de una técnica mínimamente invasiva para el tratamiento de la IPV mediante injerto de grasa, demostrando que si se realiza pronto (antes de los 7 años), a pesar de la posibilidad conocida de reabsorción del tejido adiposo, los resultados obtenidos en el primer año de seguimiento se mantienen estables en el tiempo. Hemos comparado esta técnica con las faringoplastias clásicas, sin encontrar diferencias significativas. Para conseguir una personalización perfecta del tratamiento, hemos construido a partir del análisis marginal un perfil de paciente con un resultado postoperatorio perfecto para ofrecer una herramienta de toma de decisiones al cirujano para una previsión postoperatoria del resultado quirúrgico. El análisis por aprendizaje automático, incluyendo los datos de los informes de fibroscopias, completa el estudio priorizando las variables. Todos estos datos se han recogido en un árbol de decisión que tiene en cuenta toda la trayectoria asistencial del paciente. El injerto ha demostrado ser una técnica quirurgica segura y reproducible que no altera la anatomía de la faringe y que permite, si cabe, una revisión quirúrgica más fácil. Pretendemos ampliar sus indicaciones en los casos de IPV más graves y en pacientes con un pronóstico menos favorable o con mayor riesgo de recurrencia (pacientes mayores de 7 años, pacientes con síndrome velocardiofacial o pacientes con IVP aislada). Esta elección puede evitar o, en cualquier caso, puede preceder sin riesgos añadidos la realización de una faringoplastia, una intervención técnicamente más agresiva que requiere una estancia hospitalaria más larga y sujeta a un mayor riesgo de complicaciones.Velopharyngeal insufficiency (VPI), defined by Lermoyez as an "anatomical and functional mismatch between the soft palate and the pharynx during speech", is a functional problem that requires multidisciplinary management with a dynamic study of the two structures involved in speech emission through direct vision of muscle movements during the production of phonemes. Several radiological studies study the dynamic visualization of velopharyngeal closure. Pigott was the first to introduce nasofibroscopy in the study of VPI. Now, the use of functional magnetic resonance imaging for the study of speech is in full development. This is very promising work, but it is still in the field of research. The treatment history of VPI strictly depends on the secondary cleft palate surgery. Various procedures have been described, which can be classified into active and passive pharyngoplasties. Active pharyngoplasties are a set of procedures that aim to advance the posterior pharyngeal wall or reduce the space between the lateral pharyngeal walls with a suture from the palate to the pharynx, through one or two pharyngeal flaps. These techniques have many important complications: airway obstruction, intraoperative bleeding, and impaired nasal ventilation. In patients with known obstructive sleep apnoea, intervention is contraindicated. To provide a solution to patients with contraindications and to patients with moderate velopharyngeal insufficiency, less invasive alternatives have been proposed: the objective of passive pharyngoplasties is to facilitate the occlusive role of the palate by reducing the distance from the posterior pharyngeal wall, through a complement to the natural seal offered by the Passavant ring. Classically, various materials have been used, but lately the most widely used technique is autografting of the retropharynx with adipose cells, for ease of sampling and handling of adipose tissue. Speech surgery is a functional surgery that requires a multidisciplinary approach whose result is strictly related to the appropriate indication. The surgeon must integrate the information from the different professionals, adapt it to the clinical pattern and the patient's history, assess the risks in relation to the expected benefits and, finally, decide the most appropriate technique in the clinic and in the specific functional anatomy of the patient. . It is, therefore, a decision with many variables, although in paediatric patients the fourth dimension of time must also be considered: the intervention must be performed at the most appropriate moment for the evolutionary stage of the patient. The presence of all these variables makes it very difficult for the physician to make decisions, further complicated by the lack of consensus in the literature. OBJECTIVE OF THE THESIS The objective of this thesis is to study decision-making among the existing surgical options and adapt it to each subject that presents VPI, with the aim of building personalized surgical plans. Historically, this decision-making process was carried out, on the one hand, based on the personal experience of the surgeon and, on the other hand, taking into account the study of the bibliography. The expected result of this work is to add to the personal experience of the surgeon and the uncertainty caused by highly controversial literature, a scientific component through the mathematical analysis of the variables that can help surgical decision. To do this, through a reproducible model of the variables, we have built a decision diagram, which allows the best interpretation of the surgical results, to help choose the most appropriate technique for the patient according to their anatomical, clinical and evolutionary situation. METHODOLOGY This thesis is based on a retrospective observational study on 244 consecutive patients who underwent velopharyngeal surgery for the treatment of VPI in a single tertiary hospital between 1982 and 2019. 130 patients were excluded from the study because their medical history and/or their Postoperative follow-up (12 months) were incomplete. We have included all etiologies (cleft palate, cleft lip and palate, submucous cleft palate, isolated VPI). All patients are French-speaking. The preoperative review includes speech therapy with an aerofonoscope, nasofibroscopy, and ENT evaluation. The degrees of severity of VPI were classified according to the Borrel Maisonny (BM) classification. The analysis of the results uses, first of all, traditional statistical methods such as logistic and linear regression, the propensity index and marginal analysis. These methods require large-scale clinical data to ensure significant reproducibility and specificity. On the other hand, a statistical analysis on large samples runs the risk of giving a depersonalized point of view that does not take into account the unique specificity of the subject. To solve this problem, we explore the frontiers of artificial intelligence with machine learning techniques with two expected benefits. In the first place, the algorithmic analysis of machine learning using much more complex mathematical models may be more adherent to reality, giving specific explanations for each case at the local level to. Secondly, the algorithmic analysis makes it possible to study different modalities of variables and order them in importance based on the probabilistic expression in reality. This point is very important for the prioritization of decision-making. Two machine-learning methods have been used: the decision tree and the "interpret-ML Explainable Boosting Machine" algorithm. Based on the results obtained, we have built a decision tree that describes the preoperative variables, with the selection of parameters that were statistically associated with a high probability of success or failure. RESULTS The medical records of 114 patients between the ages of 4 and 48 years have been studied, of whom 63 (55.26%) underwent pharyngoplasty and 51 (44.74%) graft, a technique introduced in the service in 2006. In the pharyngoplasty group, 42.86% were men and 57.14% women. The mean age was 6 years (IQR: 5-7). 18 (28.57%) of them had genetic or syndromic disorders. The most frequent diagnosis was cleft lip and palate (30 patients, 47.62%), followed by cleft palate with 22 patients (34.92%) and isolated VPI with 11 patients (17.46%). A BMpre of 3 was the most represented initial value (28 patients, 44.44%), while BMpre = 2m and BMpre = 2b and BMpre = 1-2 were found in 11 (17.46%), 22 (34, 92%) and 2 (3.17%) patients respectively. Regarding the group of patients who underwent adipose tissue graft, women and men were, respectively, 50.98% (26 patients) and 49.02% (25 patients). The mean age was 7 years (IQR: 6-11). 17 patients (33.33%) suffered from genetic disorders and the most frequent diagnosis was cleft palate (26 patients, 50.98%), followed by cleft lip and palate (21 patients, 41.18%) and isolated VPI (4 patients , 7.84%). The initial value of BM was significantly higher in the pharyngoplasty group (p<0.001). In contrast, the age of the patients who underwent fat grafting was significantly higher than that of the patients treated with pharyngoplasty, both when age is considered continuous (p<0.001) and categorical (p<0.001). The mean follow-up is 19.5 years. By analyzing the records of patients operated on for fat grafting, we were able to demonstrate that patients under 7 years of age obtain more favourable postoperative results (p=0.03) compared to older children. If we compare the patients who underwent fat grafting with the patients who underwent pharyngoplasty, we found that the patients who underwent pharyngoplasty had significantly worse BM scores compared with the patients who underwent fat grafting, but the age of the patients undergoing adipose tissue grafting was significantly higher. We have not found any significant superiority of one technique over another. We did not have complications in the fat graft group, but the failure rate was 7.84%, resolved with a new pharyngoplasty. On the other hand, first-line pharyngoplasty did not register any failure, but one patient presented postoperative obstructive sleep apnoea syndrome. The marginal analysis showed that age under 7 years; cleft lip and palate, absence of syndrome, and intermittent VPI are an important predictor of good outcome regardless of the surgical technique. The analysis with machine learning, on the one hand, confirmed the results of the traditional statistics and, on the other, allowed us to introduce the variables related to the fibroscopic data in the model of surgical choice. Therefore, we can conclude that the most important factor that discriminates the surgical choice is fibroscopy. Among the different observations offered by fibroscopic exploration, the most important characteristic for making a choice is represented by the dimensions of the velopharyngeal gap, followed by the tone and mobility of the soft palate. The other key element when choosing one technique over the other is the preoperative BM. The variables age, etiology and genetic alterations are also of great interest to predict postoperative success. CONCLUSIONS The speech surgery literature is dominated by studies characterized by decision diagrams based on the experience of different surgical schools. Each school prioritizes the importance of variables in decision making in a different way. In this context, we present the long-term results of a minimally invasive technique for the treatment of VPI by fat grafting, demonstrating that if performed early (before 7 years), despite the known possibility of tissue resorption adipose, the results obtained in the first year of follow-up remain stable over time. We have compared this technique with classic pharyngoplasties, without finding significant differences. In order to achieve a perfect personalization of