Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings

Coreference resolution in clinical discharge summaries, progress notes, surgical and pathology reports: a unified lexical approach

We developed a lexical rule-based system that uses a unified approach to resolving coreference across a wide variety of clinical records comprising discharge summaries, progress notes, pathology, radiology and surgical reports from two corpora (Ontology Development and Information Extraction (ODIE) and i2b2/VA) provided for the fifth i2b2/VA shared task. Taking the unweighted mean between 4 coreference metrics, validation of the system against the i2b2/VA corpus attained an overall F-score of 87.7% across all mention classes, with a maximum of 93.1% for coreference of persons, and a minimum of 77.2% for coreference of tests. For the ODIE corpus the overall F-score across all mention classes was 79.4%, with a maximum of 82.0% for coreference of persons and a minimum of 13.1% for coreference of diagnostic reagents. For the ODIE corpus our results are comparable to the mean reported inter-annotator agreement with the gold standard. We discuss the four categories of errors we identified, and how these might be addressed. The system uses a number of reusable modules and techniques that may be of benefit to the research community

A tool for enhancing MetaMap performance when annotating clinical guideline documents with UMLS concepts

We developed a tool that integrates the National Library of Medicine's MetaMap software with GATE, an open-source text an- alytics framework. The tool allows non-ASCII encoded documents of numerous formats to be annotated with UMLS concepts. We created a GATE pipeline to chunk cardiovascular disease guideline text into default segments (blank-line delimited), XML element content, sentences and phrases, which were sequentially submitted to MetaMap for annotation. XML element, sentence and phrase chunking allowed term extraction and mapping to be completed in around 1/3 of the time taken with de- fault chunking, although with slight loss of accuracy (F1.0s=0.94-0.99). However, phrase chunking allows more complex input to be processed in real time, which is not possible with the other approaches. We discuss the results in relation to use of MetaMap's --term processing option for generating pre- and post-coordinated mappings from composite phrases

Automated recognition and post-coordination of complex clinical terms

One of the key tasks in integrating guideline-based decision support systems with the electronic patient record is the mapping of clinical terms contained in both guidelines and patient notes to a common, controlled terminology. However, a vocabulary of pre-coordinated terms cannot cover every possible variation - clinical terms are often highly compositional and complex. We present a rule-based approach for automated recognition and post-coordination of clinical terms using minimal, morpheme-based thesauri, neoclassical combining forms and part-of-speech analysis. The process integrates MetaMap with the open-source GATE framework

Conceptual analysis of a diverse set of healthcare quality indicators

Ontologies, described as a specification of a representational vocabulary for a shared domain of discourse [1], can facilitate automated quality monitoring by categorising and establishing relationships between concepts. In terms of ontology development, conceptualisation is the informal representation of domain terms in the form of concepts, instances, relations, and properties [2]. Chan et al [3] suggest a need for research into attributes of quality indicators to support electronic health record (EHR) compatibility. Identification of levels of indicator relationships can serve as a step towards repackaging formulas into reusable components. A 2009 set of over 200 indicators, collated by the English National Health Service Health and Social Care Information Centre (NHS HSCIC) was chosen to attempt to address some of the gaps in research exploring ontologies and healthcare quality indicators [4]. The gaps included: research on healthcare quality indicator purposes, an ontology for healthcare quality indicators that is not dependent on data available in EHRs, an ontology that covers many clinical subject areas, and a healthcare quality indicator ontology that does not require a framework for indicator development. We set out to identify relationships and layers of inclusion and exclusion criteria for a large, diverse set of quality indicators from the English NHS. The indicators, originating from different sources ranging from the UK Renal Registry to the NHS Quality and Outcomes Framework, are measures related to processes and outcomes. Our analysis served as the conceptualisation stage for an ontology for the indicators

MicroRNA-129-1 acts as tumour suppressor and induces cell cycle arrest of GBM cancer cells through targeting IGF2BP3 and MAPK1

Background MicroRNA-129-1 (miR-129-1) seems to behave as a tumour suppressor since its decreased expression is associated with different tumours such as glioblastoma multiforme (GBM). GBM is the most common form of brain tumours originating from glial cells. The impact of miR-129-1 downregulation on GBM pathogenesis has yet to be elucidated. Methods MiR-129-1 was overexpressed in GBM cells, and its effect on proliferation was investigated by cell cycle assay. MiR-129-1 predicted targets (CDK6, IGF1, HDAC2, IGF2BP3 and MAPK1) were also evaluated by western blot and luciferase assay. Results Restoration of miR-129-1 reduced cell proliferation and induced G1 accumulation, significantly. Several functional assays confirmed IGF2BP3, MAPK1 and CDK6 as targets of miR-129-1. Despite the fact that IGF1 expression can be suppressed by miR-129-1, through 30-untranslated region complementary sequence, we could not find any association between IGF1 expression and GBM. MiR-129-1 expression inversely correlates with CDK6, IGF2BP3 and MAPK1 in primary clinical samples. Conclusion This is the first study to propose miR129-1 as a negative regulator of IGF2BP3 and MAPK1 and also a cell cycle arrest inducer in GBM cells. Our data suggests miR-129-1 as a potential tumour suppressor and presents a rationale for the use of miR-129-1 as a novel strategy to improve treatment response in GBM

The relationship between body image and marital adjustment in infertile women

Introduction: Body image is one of the most important issues in women's mental health and due to its relationship with physical, cognitive and emotional aspects of women’s life; it can predict their healthy or unhealthy behaviors. According to some research reports, women’s negative or positive body image can affect their marital relationships. Considering the impact of infertility on both body image and marital adjustment and the lack of evidence regarding the relationship of these two variables in infertility, this study aimed to investigate the relationship of body image with marital adjustment in infertile women in 2010 in Mashhad. Methods: This correlational study was carried out on 130 infertile women referred to Montaserie Infertility Research Center in Mashhad who were selected through convenient sampling. Research tools were consisted of valid and reliable demographic questionnaire including personal and infertility-related information, modified Younesi Body Image Questionnaire and Spanier marital adjustment scale (DAS) which were completed by subjects. Data analysis was carried out by SPSS software (version 15/5) using t-tests, one way ANOVA, and Spearman and Pearson correlation test. Results: 93/1% of women reported positive body image and 76/9% had high marital adjustment. There was a direct correlation between the overall score of body image with marital adjustment (P<0/001). There was also a direct correlation between the scores of body image subscales including body in loneliness (P= 0/001), real body (P=0/014), public image of body (P=0/016), spouse image of body (P<0/001) and spouse family image of body (P<0/001) with marital adjustment. However, this relationship was not observed between the subscale of ideal body and marital adjustment. Conclusion: The presence of a direct correlation between body image and marital adjustment could guide developing educational or counseling programs particularly for infertile women who suffer from marital disputes. Keywords: Body image, Marital adjustment, Infertilit