Integrated clinical pathway management for medical quality improvement-based on a semiotically inspired systems architecture

Clinical pathway is an approach to standardise care processes to support the implementations of clinical guidelines and protocols. It is designed to support the management of treatment processes including clinical and non-clinical activities, resources and also financial aspects. It provides detailed guidance for each stage in the management of a patient with the aim of improving the continuity and coordination of care across different disciplines and sectors. However, in the practical treatment process, the lack of knowledge sharing and information accuracy of paper-based clinical pathways burden health-care staff with a large amount of paper work. This will often result in medical errors, inefficient treatment process and thus poor quality medical services. This paper first presents a theoretical underpinning and a co-design research methodology for integrated pathway management by drawing input from organisational semiotics. An approach to integrated clinical pathway management is then proposed, which aims to embed pathway knowledge into treatment processes and existing hospital information systems. The capability of this approach has been demonstrated through the case study in one of the largest hospitals in China. The outcome reveals that medical quality can be improved significantly by the classified clinical pathway knowledge and seamless integration with hospital information systems.

Content validation for level of use of feature rich systems: a Delphi study of electronic medical records systems

Introduction. Feature usage is a pre-requisite to realising the benefits of investments in feature rich systems. We propose that conceptualising the dependent variable 'system use' as 'level of use' and specifying it as a formative construct has greater value for measuring the post-adoption use of feature rich systems. We then validate the content of the construct as a first step in developing a research instrument to measure it. The context of our study is the post-adoption use of electronic medical records (EMR) by primary care physicians. Method. Initially, a literature review of the empirical context defines the scope based on prior studies. Having identified core features from the literature, they are further refined with the help of experts in a consensus seeking process that follows the Delphi technique. Results.The methodology was successfully applied to EMRs, which were selected as an example of feature rich systems. A review of EMR usage and regulatory standards provided the feature input for the first round of the Delphi process. A panel of experts then reached consensus after four rounds, identifying ten task-based features that would be indicators of level of use. Conclusions. To study why some users deploy more advanced features than others, theories of post-adoption require a rich formative dependent variable that measures level of use. We have demonstrated that a context sensitive literature review followed by refinement through a consensus seeking process is a suitable methodology to validate the content of this dependent variable. This is the first step of instrument development prior to statistical confirmation with a larger sample.

An ontological approach to personalized medical knowledge recommendation

Knowledge recommendation has become a promising method in supporting the clinicians decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users requirements accurately and realize personalized recommendation. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.

An ontological approach to personalized medical knowledge matching

Knowledge management has become a promising method in supporting the clinicians′ decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users′ requirements accurately and realize personalized matching. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge matching. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthmore, the personalized matching mechanism and algorithm are illustrated.

Applying robust control theory to solve problems in bio-medical sciences: study of an apoptotic model

Biological models of an apoptotic process are studied using models describing a system of differential equations derived from reaction kinetics information. The mathematical model is re-formulated in a state-space robust control theory framework where parametric and dynamic uncertainty can be modelled to account for variations naturally occurring in biological processes. We propose to handle the nonlinearities using neural networks.

Roles of the non-medical prescribing leads within organisations across a Strategic Health Authority: perceived functions and factors supporting the role

Objectives Extending the roles of nurses, pharmacists and allied health professionals to include prescribing has been identified as one way of improving service provision. In the UK, over 50 000 non-medical healthcare professionals are now qualified to prescribe. Implementation of non-medical prescribing ( NMP) is crucial to realise the potential return on investment. The UK Department of Health recommends a NMP lead to be responsible for the implementation of NMP within organisations. The aim of this study was to explore the role of NMP leads in organisations across one Strategic Health Authority (SHA) and to inform future planning with regards to the criteria for those adopting this role, the scope of the role and factors enabling the successful execution of the role. Methods Thirty-nine NMP leads across one SHA were approached. Semi-structured telephone interviews were conducted. Issues explored included the perceived role of the NMP lead, safety and clinical governance procedures and facilitators to the role. Transcribed audiotapes were coded and analysed using thematic analytical techniques. Key findings In total, 27/39 (69.2%) NMP leads were interviewed. The findings highlight the key role that the NMP lead plays with regards to the support and development of NMP within National Health Service trusts. Processes used to appoint NMP leads lacked clarity and varied between trusts. Only two NMP leads had designated or protected time for their role. Strategic influence, operational management and clinical governance were identified as key functions. Factors that supported the role included organisational support, level of influence and dedicated time. Conclusion The NMP lead plays a significant role in the development and implementation of NMP. Clear national guidance is needed with regards to the functions of this role, the necessary attributes for individuals recruited into this post and the time that should be designated to it. This is important as prescribing is extended to include other groups of non-medical healthcare professionals.

Children’s physic: medical perceptions and treatment of sick children in early modern England, c. 1580-1720

Historians of medicine, childhood, and paediatrics, have often assumed that early modern doctors neither treated children, nor adapted their medicines to suit the peculiar temperaments of the young. Through an examination of medical textbooks and doctors’ casebooks, this article refutes these assumptions. It argues that medical authors and practising doctors regularly treated children, and were careful to tailor their remedies to complement the distinctive constitutions of children. Thus, this article proposes that a concept of ‘children’s physic’ existed in early modern England: this term refers to the notion that children were physiologically distinct, requiring special medical care. Children’s physic was rooted in the ancient traditions of Hippocratic and Galenic medicine: it was the child’s humoral makeup that underpinned all medical ideas about children’s bodies, minds, diseases, and treatments. Children abounded in the humour blood, which made them humid and weak, and in need of medicines of a particularly gentle nature.

Multiprobabilistic prediction in early medical diagnoses

This paper describes the methodology of providing multiprobability predictions for proteomic mass spectrometry data. The methodology is based on a newly developed machine learning framework called Venn machines. Is allows to output a valid probability interval. The methodology is designed for mass spectrometry data. For demonstrative purposes, we applied this methodology to MALDI-TOF data sets in order to predict the diagnosis of heart disease and early diagnoses of ovarian cancer and breast cancer. The experiments showed that probability intervals are narrow, that is, the output of the multiprobability predictor is similar to a single probability distribution. In addition, probability intervals produced for heart disease and ovarian cancer data were more accurate than the output of corresponding probability predictor. When Venn machines were forced to make point predictions, the accuracy of such predictions is for the most data better than the accuracy of the underlying algorithm that outputs single probability distribution of a label. Application of this methodology to MALDI-TOF data sets empirically demonstrates the validity. The accuracy of the proposed method on ovarian cancer data rises from 66.7 % 11 months in advance of the moment of diagnosis to up to 90.2 % at the moment of diagnosis. The same approach has been applied to heart disease data without time dependency, although the achieved accuracy was not as high (up to 69.9 %). The methodology allowed us to confirm mass spectrometry peaks previously identified as carrying statistically significant information for discrimination between controls and cases.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Clustering Lab value working with medical data

Data mining is a relatively new field of research that its objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available [27]. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make rather accurate decisions. In this thesis, the goal is finding a pattern among patients who got pneumonia by clustering of lab data values which have been recorded every day. By this pattern we can generalize it to the patients who did not have been diagnosed by this disease whose lab values shows the same trend as pneumonia patients does. There are 10 tables which have been extracted from a big data base of a hospital in Jena for my work .In ICU (intensive care unit), COPRA system which is a patient management system has been used. All the tables and data stored in German Language database.

An analysis of the aspects attracting medical tourists : a case study in Seoul, South Korea

Many countries recognized the potential of medicaltourism as an alternative source of economic growth. Especially after theeconomic crisis many Asian countries joined medical tourism in hopes to escapethe severe financial difficulty. However, yet only few countries have managedto become a famous medical tourism destination. With growing number ofcompetitors, newly joined countries of medical tourism, face the difficulty inintroducing them self as attractive medical tourism destination. South Koreaas a new medical tourism destination, should consider what to offer to themedical tourists to attract them. The aim of the thesis was to investigate aspects influencing the participationof medical tourists to discover how South Korea could develop anattractive medical tourism destination. After examining the casestudy and results from the text analysis, researcher reached to the conclusionthat quality, cost and accessibility to treatment are the major reasons toparticipate in medical tourism. Also in the fierce competition, it is importantto develop differentiated offers from other destinations. Therefore, Koreashould concentrate on specialized treatments and ICT system to become anattractive medical tourism destination.

Simplified follow-up after medical abortion using a low-sensitivity urinary pregnancy test and a pictorial instruction sheet in Rajasthan, India : study protocol and intervention adaptation of a randomised control trial

The World Health Organisation suggests that simplification of the medical abortion regime will contribute to an increased acceptability of medical abortion, among women as well as providers. It is expected that a home-based follow-up after a medical abortion will increase the willingness to opt for medical abortion as well as decrease the workload and service costs in the clinic. Trial design The study is a randomised, controlled, non-superiority trial . Methods Women screened to participate in the study are those with unwanted pregnancies and gestational ages equal to or less than nine weeks. Eligible women randomised to the home-based assessment group will use a low-sensitivity pregnancy test and a pictorial instruction sheet at home, while the women in the clinic follow-up group will return to the clinic for routine follow-up carried out by a doctor. The primary objective of the study is to evaluate the effectiveness of home-based assessment using a low-sensitivity pregnancy test and a pictorial instruction sheet 10-14 days after an early medical abortion. Providers or research assistants will not be blinded during outcome assessment. To ensure feasibility of the self-assessment intervention an adaption phase took place at the selected study sites before study initiation. This was to optimise and tailor-make the intervention and the study procedures and resulted in the development of the pictorial instruction sheet for how to use the low-sensitivity pregnancy test and the danger signs after a medical abortion. Discussion In this paper, we will describe the study protocol for a randomised control trial investigating the efficacy of simplified follow-up in terms of home-based assessment, 10-14 days after a medical abortion. Moreover, a description of the adaptation phase is included for a better understanding of the implementation of the intervention in a setting where literacy is low and the road-connections are poor. Trial registration: Clinicaltrials.gov NCT01827995. Registered 04 May 2013