Classifying the reported ability in clinical mobility descriptions

Assessing how individuals perform different activities is key information for modeling health states of individuals and populations. Descriptions of activity performance in clinical free text are complex, including syntactic negation and similarities to textual entailment tasks. We explore a variety of methods for the novel task of classifying four types of assertions about activity performance: Able, Unable, Unclear, and None (no information). We find that ensembling an SVM trained with lexical features and a CNN achieves 77.9% macro F1 score on our task, and yields nearly 80% recall on the rare Unclear and Unable samples. Finally, we highlight several challenges in classifying performance assertions, including capturing information about sources of assistance, incorporating syntactic structure and negation scope, and handling new modalities at test time. Our findings establish a strong baseline for this novel task, and identify intriguing areas for further research.Comment: Appearing in BioNLP 2019. 10 pages; 6 tables, 2 figure

Classifying the reported ability in clinical mobility descriptions

Assessing how individuals perform different activities is key information for modeling health states of individuals and populations. Descriptions of activity performance in clinical free text are complex, including syntactic negation and similarities to textual entailment tasks. We explore a variety of methods for the novel task of classifying four types of assertions about activity performance: Able, Unable, Unclear, and None (no information). We find that ensembling an SVM trained with lexical features and a CNN achieves 77.9% macro F1 score on our task, and yields nearly 80% recall on the rare Unclear and Unable samples. Finally, we highlight several challenges in classifying performance assertions, including capturing information about sources of assistance, incorporating syntactic structure and negation scope, and handling new modalities at test time. Our findings establish a strong baseline for this novel task, and identify intriguing areas for further research

Exercise interventions for adults and children with cerebral palsy (Protocol)

This is the protocol for a review and there is no abstract. The objectives are as follows: - The primary aim of this systematic review is to evaluate the effect of exercise interventions on activity, participation, and health-related quality of life (HRQoL) in adults and children with CP. - The secondary aim is to evaluate the effect of exercise interventions on body functions and body structures.Jennifer M Ryan is receiving funding from Action Medical Research and the Chartered Society of Physiotherapy Charitable Trust to evaluate the feasibility, acceptability, and efficacy of resistance training in adolescents with cerebral palsy

EPUAP classification system for pressure ulcers: European reliability study

‘The definitive version is available at www3.interscience.wiley.com .' Copyright Blackwell PublishingPeer reviewe

Development of holistic classification systems for children with cerebral palsy

Cerebral palsy (CP) is a complex disorder. There is a gap in the literature in classifying children with CP broadly. The purpose of this thesis was to develop holistic classification systems for children with CP. As a first step, a search was conducted to explore the strategies used to classify children with developmental co-ordination disorder and autism-spectrum disorder. Two versions of holistic classification systems named the body function index in cerebral palsy (BFI-CP) versions I and II were developed using two methods. Then, the relationship and differences among the developed classification systems and the Gross Motor Function Classification System (GMFCS) were explored. Next, differences among subsets of the classifications that did not correspond to the ordinal levels of the GMFCS were explored. Next, the relationships between the developed classification systems (BFICP- I and II) and the GMFCS and the change in outcome of motor function were explored. Exploration of the existing classification systems of childhood disorders (Chapter 2) demonstrated that none of the classification systems in CP addressed the majority of the key features in the international consensus definition of CP. The BFI-CP I was developed using a summing technique and the BFI-CP II was developed using cluster analysis. The findings demonstrated a strong correlation between the BFI-CP I and the GMFCS (r=0.92), the BFI-CP II and the GMFCS (r=0.93), and the BFI-CP I and II (r=0.92), all (pχ² = 670.49, df=16, pχ² =685.57, df=16,

Automated Coding of Under-Studied Medical Concept Domains: Linking Physical Activity Reports to the International Classification of Functioning, Disability, and Health

Linking clinical narratives to standardized vocabularies and coding systems is a key component of unlocking the information in medical text for analysis. However, many domains of medical concepts lack well-developed terminologies that can support effective coding of medical text. We present a framework for developing natural language processing (NLP) technologies for automated coding of under-studied types of medical information, and demonstrate its applicability via a case study on physical mobility function. Mobility is a component of many health measures, from post-acute care and surgical outcomes to chronic frailty and disability, and is coded in the International Classification of Functioning, Disability, and Health (ICF). However, mobility and other types of functional activity remain under-studied in medical informatics, and neither the ICF nor commonly-used medical terminologies capture functional status terminology in practice. We investigated two data-driven paradigms, classification and candidate selection, to link narrative observations of mobility to standardized ICF codes, using a dataset of clinical narratives from physical therapy encounters. Recent advances in language modeling and word embedding were used as features for established machine learning models and a novel deep learning approach, achieving a macro F-1 score of 84% on linking mobility activity reports to ICF codes. Both classification and candidate selection approaches present distinct strengths for automated coding in under-studied domains, and we highlight that the combination of (i) a small annotated data set; (ii) expert definitions of codes of interest; and (iii) a representative text corpus is sufficient to produce high-performing automated coding systems. This study has implications for the ongoing growth of NLP tools for a variety of specialized applications in clinical care and research.Comment: Updated final version, published in Frontiers in Digital Health, https://doi.org/10.3389/fdgth.2021.620828. 34 pages (23 text + 11 references); 9 figures, 2 table

Health problems and disability in long-term sickness absence: ICF coding of medical certificates

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to test the feasibility of International Classification of Functioning, Disability and Health (ICF) and to explore the distribution, including gender differences, of health problems and disabilities as reflected in long-term sickness absence certificates.</p> <p>Methods</p> <p>A total of 433 patients with long sick-listing periods, 267 women and 166 men, were included in the study. All certificates exceeding 28 days of sick-listing sent to the local office of the Swedish Social Insurance Administration of a municipality in the Stockholm area were collected during four weeks in 2004-2005. ICD-10 medical diagnosis codes in the certificates were retrieved and free text information on disabilities in body function, body structure or activity and participation were coded according to ICF short version.</p> <p>Results</p> <p>In 89.8% of the certificates there were descriptions of disabilities that readily could be classified according to ICF. In a reliability test 123/131 (94%) items of randomly chosen free text information were identically classified by two of the authors. On average 2.4 disability categories (range 0-9) were found per patient; the most frequent were 'Sensation of pain' (35.1% of the patients), 'Emotional functions' (34.1%), 'Energy and drive functions' (22.4%), and 'Sleep functions' (16.9%). The dominating ICD-10 diagnostic groups were 'Mental and behavioural disorders' (34.4%) and 'Diseases of the musculoskeletal system and connective tissue' (32.8%). 'Reaction to severe stress and adjustment disorders' (14.7%), and 'Depressive episode' (11.5%) were the most frequent diagnostic codes. Disabilities in mental functions and activity/participation were more commonly described among women, while disabilities related to the musculoskeletal system were more frequent among men.</p> <p>Conclusions</p> <p>Both ICD-10 diagnoses and ICF categories were dominated by mental and musculoskeletal health problems, but there seems to be gender differences, and ICF classification as a complement to ICD-10 could provide a better understanding of the consequences of diseases and how individual patients can cope with their health problems. ICF is feasible for secondary classifying of free text descriptions of disabilities stated in sick-leave certificates and seems to be useful as a complement to ICD-10 for sick-listing management and research.</p

Inter‐relationships of functional status in cerebral palsy: analyzing gross motor function, manual ability, and communication function classification systems in children

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92118/1/j.1469-8749.2012.04312.x.pd

Strengthening health-related rehabilitation services at national levels.

OBJECTIVE: One of the aims of the World Health Organization\u27s Global Disability Action Plan is to strengthen rehabilitation services. Some countries have requested support to develop (scale-up) rehabilitation services. This paper describes the measures required and how (advisory) missions can support this purpose, with the aim of developing National Disability, Health and Rehabilitation Plans. RECOMMENDATIONS: It is important to clarify the involvement of governments in the mission, to define clear terms of reference, and to use a systematic pathway for situation assessment. Information must be collected regarding policies, health, disability, rehabilitation, social security systems, the need for rehabilitation, and the existing rehabilitation services and workforce. Site visits and stakeholder dialogues must be done. In order to develop a Rehabilitation Service Implementation Framework, existing rehabilitation services, workforce, and models for service implementation and development of rehabilitation professions are described. Governance, political will and a common understanding of disability and rehabilitation are crucial for implementation of the process. The recommendations of the World Report on Disability are used for reporting purposes. CONCLUSION: This concept is feasible, and leads to concrete recommendations and proposals for projects and a high level of consensus stakeholders

Clinical Classification of Cerebral Palsy

The classification of cerebral palsy (CP) remains a challenge; hence the presence of so many classifications and a lack of consensus. Each classification used alone is incomplete. Therefore, a multiaxial classification gives a more comprehensive description of a child with CP. The recent WHO International Classification of Functioning, Disability and Health (ICF) emphasizes the importance of focusing on the functional consequences of various states of health and has stimulated the development of newer functional scales in CP. It is widely accepted that the functional classification is the best classification for the patient because it guides management. The objectives of this chapter are to review the various classifications of CP, to highlight the clinical features used in the various classifications, to outline the recent functional classifications of CP and to highlight how these recent classifications guide current management. It is expected that at the end of this chapter, the reader should be able to understand the difficulties in classifying CP, enumerate and discuss the various classifications of CP, understand the merits and shortcomings of each classification scheme, clinically evaluate and classify a child with CP multiaxially and understand how functional scales predict current and future needs of children with CP