Exploiting medical hierarchies for concept-based information retrieval

Search technologies are critical to enable clinical sta to rapidly and e ectively access patient information contained in free-text medical records. Medical search is challenging as terms in the query are often general but those in rel- evant documents are very speci c, leading to granularity mismatch. In this paper we propose to tackle granularity mismatch by exploiting subsumption relationships de ned in formal medical domain knowledge resources. In symbolic reasoning, a subsumption (or `is-a') relationship is a parent-child rela- tionship where one concept is a subset of another concept. Subsumed concepts are included in the retrieval function. In addition, we investigate a number of initial methods for combining weights of query concepts and those of subsumed concepts. Subsumption relationships were found to provide strong indication of relevant information; their inclusion in retrieval functions yields performance improvements. This result motivates the development of formal models of rela- tionships between medical concepts for retrieval purposes.

Exploiting SNOMED CT concepts and relationships for clinical information retrieval : Australian e-Health Research Centre and Queensland University of Technology at the TREC 2012 Medical Track

The Australian e-Health Research Centre and Queensland University of Technology recently participated in the TREC 2012 Medical Records Track. This paper reports on our methods, results and experience using an approach that exploits the concept and inter-concept relationships defined in the SNOMED CT medical ontology. Our concept-based approach is intended to overcome specific challenges in searching medical records, namely vocabulary mismatch and granularity mismatch. Queries and documents are transformed from their term-based originals into medical concepts as defined by the SNOMED CT ontology, this is done to tackle vocabulary mismatch. In addition, we make use of the SNOMED CT parent-child `is-a' relationships between concepts to weight documents that contained concept subsumed by the query concepts; this is done to tackle the problem of granularity mismatch. Finally, we experiment with other SNOMED CT relationships besides the is-a relationship to weight concepts related to query concepts. Results show our concept-based approach performed significantly above the median in all four performance metrics. Further improvements are achieved by the incorporation of weighting subsumed concepts, overall leading to improvement above the median of 28% infAP, 10% infNDCG, 12% R-prec and 7% Prec@10. The incorporation of other relations besides is-a demonstrated mixed results, more research is required to determined which SNOMED CT relationships are best employed when weighting related concepts.

Semantic judgement of medical concepts : combining syntagmatic and paradigmatic information with the tensor encoding model

This paper outlines a novel approach for modelling semantic relationships within medical documents. Medical terminologies contain a rich source of semantic information critical to a number of techniques in medical informatics, including medical information retrieval. Recent research suggests that corpus-driven approaches are effective at automatically capturing semantic similarities between medical concepts, thus making them an attractive option for accessing semantic information. Most previous corpus-driven methods only considered syntagmatic associations. In this paper, we adapt a recent approach that explicitly models both syntagmatic and paradigmatic associations. We show that the implicit similarity between certain medical concepts can only be modelled using paradigmatic associations. In addition, the inclusion of both types of associations overcomes the sensitivity to the training corpus experienced by previous approaches, making our method both more effective and more robust. This finding may have implications for researchers in the area of medical information retrieval.

Encouraging, assisting and time to EAT : improved nutritional intake for older medical patients receiving Protected Mealtimes and/or additional nursing feeding assistance

Background & Aims: Inadequate feeding assistance and mealtime interruptions during hospitalisation may contribute to malnutrition and poor nutritional intake in older people. This study aimed to implement and compare three interventions designed to specifically address mealtime barriers and improve energy intakes of medical inpatients aged ≥65 years. Methods: Pre-post study compared three mealtime assistance interventions: PM: Protected Mealtimes with multidisciplinary education; AIN: additional assistant-in-nursing (AIN) with dedicated meal role; PM+AIN: combined intervention. Dietary intake of 254 patients (pre: n=115, post: n=141; mean age 80±8) was visually estimated on a single day in the first week of hospitalisation and compared with estimated energy requirements. Assistance activities were observed and recorded. Results: Mealtime assistance levels significantly increased in all interventions (p<0.01). Post-intervention participants were more likely to achieve adequate energy intake (OR=3.4, p=0.01), with no difference noted between interventions (p=0.29). Patients with cognitive impairment or feeding dependency appeared to gain substantial benefit from mealtime assistance interventions. Conclusions: Protected Mealtimes and additional AIN assistance (implemented alone or in combination) may produce modest improvements in nutritional intake. Targeted feeding assistance for certain patient groups holds promise; however, alternative strategies are required to address the complex problem of malnutrition in this population.

Mastering medical terminology : Australia and New Zealand Workbook

Mastering Medical Terminology: Australia and New Zealand Workbook is the indispensable companion to Mastering Medical Terminology Textbook. Packed with a range of exercises and activities to accompany the main text, the Workbook provides an ideal resource for self-testing and revision in a fun, practical and accessible format, and forms a key part of the Mastering Medical Terminology suite of products which are all available for separate purchase enabling you to pick and choose the right package for your learning requirements. Featuring a variety of question types including crossword puzzles, anagrams, multiple-choice questions and label-the-diagram exercises, the Workbook uses entirely Australian spelling and aligns to the chapters of the main text. When used in combination with the main text and MedWords app, Mastering Medical Terminology: Australia and New Zealand Workbook will make the scholarship of medical terminology not only manageable, but fun!

(Mis)Using Pulse Oximetry : A Review of Pulse Oximetry use in Acute Care Medical Wards

Background: Nurses routinely use pulse oximetry (SpO2) monitoring equipment in acute care. Interpretation of the reading involves physical assessment and awareness of parameters including temperature, haemoglobin, and peripheral perfusion. However, there is little information on whether these clinical signs are routinely measured or used in pulse oximetry interpretation by nurses. Aim: The aim of this study was to review current practice of SpO2 measurement and the associated documentation of the physiological data that is required for accurate interpretation of the readings. The study reviewed the documentation practices relevant to SpO2 in five medical wards of a tertiary level metropolitan hospital. Method: A prospective casenote audit was conducted on random days over a three-month period. The audit tool had been validated in a previous study. Results: One hundred and seventy seven episodes of oxygen saturation monitoring were reviewed. Our study revealed a lack of parameters to validate the SpO2 readings. Only 10% of the casenotes reviewed had sufficient physiological data to meaningfully interpret the SpO2 reading and only 38% had an arterial blood gas as a comparator. Nursing notes rarely documented clinical interpretation of the results. Conclusion: The audits suggest that medical and nursing staff are not interpreting the pulse oximetry results in context and that the majority of the results were normal with no clinical indication for performing this observation. This reduces the usefulness of such readings and questions the appropriateness of performing “routine” SpO2 in this context.

Dying in hospital: medical failure or natural outcomes?

The purpose of this study was to describe patterns of medical and nursing practice in the care of patients dying of oncological and hematological malignancies in the acute care setting in Australia. A tool validated in a similar American study was used to study the medical records of 100 consecutive patients who died of oncological or hematological malignancies before August 1999 at The Canberra Hospital in the Australian Capital Territory. The three major indicators of patterns of end-of-life care were documentation of Do Not Resuscitate (DNR) orders, evidence that the patient was considered dying, and the presence of a palliative care intention. Findings were that 88 patients were documented DNR, 63 patients' records suggested that the patient was dying, and 74 patients had evidence of a palliative care plan. Forty-six patients were documented DNR 2 days or less prior to death and, of these, 12 were documented the day of death. Similar patterns emerged for days between considered dying and death, and between palliative care goals and death. Sixty patients had active treatment in progress at the time of death. The late implementation of end-of-life management plans and the lack of consistency within these plans suggested that patients were subjected to medical interventions and investigations up to the time of death. Implications for palliative care teams include the need to educate health care staff and to plan and implement policy regarding the management of dying patients in the acute care setting. Although the health care system in Australia has cultural differences when compared to the American context, this research suggests that the treatment imperative to prolong life is similar to that found in American-based studies.

Changing learning to improve practice : hand hygiene education in Queensland medical schools

The aim of Queensland Health’s ‘Clean hands are life savers’ program is to change the culture and behaviour of healthcare workers related to hand hygiene. Hand hygiene is considered to be the most effective means of preventing pathogen cross-transmission and healthcare-associated infections. Most hospitals throughout Queensland as well as Australia now manage a hand hygiene program to increase the hand hygiene compliance of all healthcare workers. Reports taken from routine hand hygiene observations reveal that doctors are usually less compliant in their hand-washing practices than other healthcare worker groups. The Centre for Healthcare Related Infection Surveillance and Prevention (CHRISP) has attempted to have an impact on this challenging group through their Medical Leadership Initiative. With education as a core component of the program, efforts were made to ensure our future doctors were receiving information that aligned with Queensland Health standards during their formative years at medical school. CHRISP met with university instructors to understand what infection prevention education was currently included in the curriculum and support the introduction of new learning activities that specifically focused on hand hygiene. This prompted change to the existing curriculum and a range of interventions were employed with mixed success. Although met with challenges, methods to integrate more infection prevention teaching were found.

Graph-based concept weighting for medical information retrieval

This paper presents a graph-based method to weight medical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text documents using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag-of-words representations. We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsulates terms belonging to a single medical entity into a single concept. In addition, we further extend previous graph-based approaches by injecting domain knowledge that estimates the importance of a concept within the global medical domain. Retrieval experiments on the TREC Medical Records collection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.