Total quality management (TQM) approach is often used to carry out company-wide continuous quality improvement plans in manufacturing and service industries. Similarly, TQM can also play a critical role for quality management in health care. Aiming to improve health care quality, experiences showed that major problems of non-patient care, patient records and vital signs monitoring are encountered. In this study, we aim to introduce TQM for quality improvement for intensive care unit (ICU) operations, including some solutions and the prototype of quality management. And vital signs monitoring at ICU is taken as an example of process. For quality improvement of non-patient care, Health Care Quality Development Life Cycle, including (1) quality requirement analysis, (2) quality specification review, (3) quality design, (4) quality implementation, (5) quality testing, (6) quality maintaining, and (7) quality validation, is discussed. The prototype of the first three phases for quality improvement at ICU is explored. Through quality requirement analysis, non-patient care quality at ICU is defined in areas of administration, facility and environment. For quality improvement of patient records maintaining, firstly, scope of health care information systems is categorized as administrative operational system, decision support system, clinical information system, and medical information system. According to this categorization and experience, some interesting result is found. For instance, the current applications of information systems for teaching hospitals in southern Taiwan surveyed are that most applications are administrative and clinical. And the essential information of patient records used in each information system is not complete or not easily accessed. Model of the patient record maintaining is introduced and the prototype design of patient records is recommended for quality improvement of patient records maintaining at ICU. To improve quality of vital signs monitoring is one essential requirement and specification for ICU quality improvement. Effective outcome measures of vital signs monitoring and early detecting of abnormal vital signs is considered important. For quality improvement of vital signs monitoring at ICU, heart rate graphs are taken as examples in our study through the heart rate graphs monitoring. Health professionals can understand the interactions of human autonomic nervous system. By use of digitizer, the computable heart rate data is acquired from each graph and grouped into mortality and near-to-normal cases. Then spectrum form of heart rate data, describing more about heart function, is used for statistical analysis. Several control chart methods have been experimented to detect small heart rate shifts from target, cumulative sum control chart (Cusum) is adopted in our study. The observable variable is the patient¡¦s heart rate, the purpose is to check the alarms pointed out by Cusum that could be partially be ascribed to changes of heart rate trend over time, and to a shift in the monitoring process mean. From summaries of nonconformities in the Cusum charts, mortality cases obviously have more nonconformities. It is obvious that Cusum control charts of mortality cases provide diagnostic information for vital signs monitoring process. In addition, Cusum charts may also inform ICU professionals that there is a small shift of patient heart rate, a continuously increasing or decreasing heart rate, and the adjustment of sympathetic nerve and parasympathetic nerve. In those cases, some special care is needed.

Made available in DSpace on 2016-06-02T20:44:11Z (GMT). No. of bitstreams: 1 4831.pdf: 2096066 bytes, checksum: d367da2e084bdb67e171029ec907527a (MD5) Previous issue date: 2012-12-18 / Financiadora de Estudos e Projetos / The clinical documentation in occupational therapy is developed whenever the service is offered to a client to register and report information pertaining to care. The aim of the study is to identify how this is done and what the perception of occupational therapists about the practice of outpatient clinical documentation is. The research was conducted in two stages: documentary research, through qualitative research of legal documents in Brazil; and field research, descriptive and exploratory study, conducted with 104 active occupational therapists in the state of Sao Paulo who worked in outpatient services. This was carried out using an online questionnaire and data was analyzed using quantitative methods, descriptive statistics and specific tests for comparison and correlation of variables. The results of the field research show: 64.4% of the records are held only on paper; all respondents perform assessment records; one makes no record of intervention / monitoring; and 13.5% do not carry records of patient discharge. Also, 91.9% reported some level of satisfaction with their own record. Virtually all clinical documentation was considered to be necessary and useful. The results revealed a significant correlation (p <0.05) with the level of satisfaction with their own practice of clinical documentation the variables: considered have sufficient knowledge for the development of the records, and values attributed to the practice of clinical documentation (those who consider it complex or difficult present a lower level of satisfaction when compared to those who consider it simple or easy). As for documentary research, 123 documents of different organs of origin were selected and will be analyzed qualitatively, with 103 consisting of reports, technical notes or orders, and the rest, ordinances, resolutions, and Decree. Only 13 of them are specific to the occupational therapy. It was considered that the data obtained allowed an initial approach to the topic, identifying as clinical records are held by occupational therapists working in outpatient care and what their perception of this practice, and identify aspects that influence this perception. The documentary research helped to understand and contextualize the practice of clinical documentation in Brazil, especially in relation to occupational therapy. The study could also contribute to the identification of topics of interest for future research on the topic and to produce knowledge that can guide the development of better quality of clinical documentation by occupational therapists. / A documentação clínica em terapia ocupacional é desenvolvida sempre que o serviço é oferecido a um cliente, para registrar e comunicar as informações pertinentes ao seu atendimento. Este estudo teve por objetivo identificar como é realizada e qual a percepção dos terapeutas ocupacionais sobre a prática da documentação clínica ambulatorial. A pesquisa foi desenvolvida em duas etapas: pesquisa documental, através de investigação e análise qualitativa de documentos jurídicos brasileiros; e pesquisa de campo, descritiva e exploratória, realizada com 104 terapeutas ocupacionais ativos do estado de São Paulo, que atuavam em serviços ambulatoriais. Esta etapa foi realizada através de aplicação on-line de questionário e os dados foram analisados por métodos quantitativos, com uso de estatística descritiva e testes específicos para comparação e correlação das variáveis. Os resultados da pesquisa de campo revelaram que 64,4% dos registros são realizados somente em papel. Todos os respondentes realizam registros de avaliação, um não realiza registros de intervenção/acompanhamento e 13,5% não realizam registros de alta. 91,9% referiram algum nível de satisfação com o próprio registro. Praticamente todos consideram a documentação clínica necessária e útil. Revelaram correlação significativa (p<0,05) com a satisfação em relação à própria prática da documentação clínica as variáveis: considerar possuir conhecimento suficiente para o desenvolvimento dos registros, e valores atribuídos à prática da documentação clínica, sendo que os que a consideram complexa, difícil e desgastante apresentam pior avaliação da satisfação do que aqueles que a consideram simples, fácil e tranqüila. Quanto à pesquisa documental, 123 documentos de diferentes órgãos de origem foram selecionados, sendo 103 constituídos por pareceres, notas técnicas ou despachos, e o restante, portarias, resoluções e decretos. Apenas 13 deles são específicos da terapia ocupacional. Considerou-se que os dados obtidos possibilitaram uma aproximação inicial com o tema, identificando como os registros clínicos são realizados pelos terapeutas ocupacionais que atuam em assistência ambulatorial e qual a percepção deles sobre esta prática, assim como a identificação dos aspectos que interferem nesta percepção. A pesquisa documental auxiliou a compreender e contextualizar a prática da documentação clínica no Brasil, especialmente em relação à terapia ocupacional. O estudo também pôde contribuir para a identificação de focos de interesse para futuras investigações sobre o tema e para a produção de conhecimento que possa orientar o desenvolvimento com melhor qualidade da documentação clínica por terapeutas ocupacionais.

Electronic health records (EHRs) are used in Sweden's healthcare systems to store patients' medical information. Patients in Sweden have the right to access and read their health records. Unfortunately, the language used in EHRs is very complex and presents a challenge for readers who lack medical knowledge. Simplifying the language used in EHRs could facilitate the transfer of information between medical staff and patients. This project investigates the possibility of generating Swedish medical synonyms automatically. These synonyms are intended to be used in future systems for lexical simplification that can enhance the readability of Swedish EHRs and simplify medical terminology. Current publicly available Swedish corpora that provide synonyms for medical terminology are insufficient in size to be utilized in a system for lexical simplification. To overcome the obstacle of insufficient corpora, machine learning models are trained to generate synonyms and terms that convey medical concepts in a more understandable way. With the purpose of establishing a foundation for analyzing complex medical terms, a simple mechanism for Complex Word Identification (CWI) is implemented. The mechanism relies on matching strings and substrings from a pre-existing corpus containing hand-curated medical terms in Swedish. To find a suitable strategy for generating medical synonyms automatically, seven different machine learning models are queried for synonym suggestions for 50 complex sample terms. To explore the effect of different input data, we trained our models on different datasets with varying sizes. Three of the seven models are based on BERT and four of them are based on Word2Vec. For each model, results for the 50 complex sample terms are generated and raters with medical knowledge are asked to assess whether the automatically generated suggestions could be considered synonyms. The results vary between the different models and seem to be connected to the amount and quality of the data they have been trained on. Furthermore, the raters involved in judging the synonyms exhibit great disagreement, revealing the complexity and subjectivity of the task to find suitable and widely accepted medical synonyms. The method and models applied in this project do not succeed in creating a stable source of suitable synonyms. The chosen BERT approach based on Masked Language Modelling cannot reliably generate suitable synonyms due to the limitation of generating one term per synonym suggestion only. The Word2Vec models demonstrate some weaknesses due to the lack of context consideration. Despite the fact that the current performance of our models in generating automatic synonym suggestions is not entirely satisfactory, we have observed a promising number of accurate suggestions. This gives us reason to believe that with enhanced training and a larger amount of input data consisting of Swedish medical text, the models could be improved and eventually effectively applied.

Implant terms are terms like "pacemaker" which indicate the presence of artifacts in the body of a human. These implant terms are key to determining if a patient can safely undergo Magnetic Resonance Imaging (MRI). However, to identify these terms in medical records is time-consuming, laborious and expensive, but necessary for taking the correct precautions before an MRI scan. Automating this process is of great interest to radiologists as it ideally saves time, prevents mistakes and as a result saves lives. The electronic medical records (EMR) contain the documented medical history of a patient, including any implants or objects that an individual would have inside their body. Information about such objects and implants are of great interest when determining if and how a patient can be scanned using MRI. This information is unfortunately not easily extracted through automatic means. Due to their sparse presence and the unusual structure of medical records compared to most written text, makes it very difficult to automate using simple means. By leveraging the recent advancements in Artificial Intelligence (AI), this thesis explores the ability to identify and extract such terms automatically in Swedish EMRs. For the task of identifying implant terms in medical records a generally trained Swedish Bidirectional Encoder Representations from Transformers (BERT) model is used, which is then fine-tuned on Swedish medical records. Using this model a variety of approaches are explored two of which will be covered in this thesis. Using this model a variety of approaches are explored, namely BERT-KDTree, BERT-BallTree, Cosine Brute Force and unsupervised NER. The results show that BERT-KDTree and BERT-BallTree are the most rewarding methods. Results from both methods have been evaluated by domain experts and appear promising for such an early stage, given the difficulty of the task. The evaluation of BERT-BallTree shows that multiple methods of extraction may be preferable as they provide different but still useful terms. Cosine brute force is deemed to be an unrealistic approach due to computational and memory requirements. The NER approach was deemed too impractical and laborious to justify for this study, yet is potentially useful if not more suitable given a different set of conditions and goals. While there is much to be explored and improved, these experiments are a clear indication that automatic identification of implant terms is possible, as a large number of implant terms were successfully discovered using automated means.