Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research

<b>Background</b> Patients with chronic disease may experience complicated management plans requiring significant personal investment. This has been termed ‘treatment burden’ and has been associated with unfavourable outcomes. The aim of this systematic review is to examine the qualitative literature on treatment burden in stroke from the patient perspective.<p></p> <b>Methods and findings</b> The search strategy centred on: stroke, treatment burden, patient experience, and qualitative methods. We searched: Scopus, CINAHL, Embase, Medline, and PsycINFO. We tracked references, footnotes, and citations. Restrictions included: English language, date of publication January 2000 until February 2013. Two reviewers independently carried out the following: paper screening, data extraction, and data analysis. Data were analysed using framework synthesis, as informed by Normalization Process Theory. Sixty-nine papers were included. Treatment burden includes: (1) making sense of stroke management and planning care, (2) interacting with others, (3) enacting management strategies, and (4) reflecting on management. Health care is fragmented, with poor communication between patient and health care providers. Patients report inadequate information provision. Inpatient care is unsatisfactory, with a perceived lack of empathy from professionals and a shortage of stimulating activities on the ward. Discharge services are poorly coordinated, and accessing health and social care in the community is difficult. The study has potential limitations because it was restricted to studies published in English only and data from low-income countries were scarce.<p></p> <b>Conclusions</b> Stroke management is extremely demanding for patients, and treatment burden is influenced by micro and macro organisation of health services. Knowledge deficits mean patients are ill equipped to organise their care and develop coping strategies, making adherence less likely. There is a need to transform the approach to care provision so that services are configured to prioritise patient needs rather than those of health care systems

Telemedicine framework using case-based reasoning with evidences

Telemedicine is the medical practice of information exchanged from one location to another through electronic communications to improve the delivery of health care services. This research article describes a telemedicine framework with knowledge engineering using taxonomic reasoning of ontology modeling and semantic similarity. In addition to being a precious support in the procedure of medical decision-making, this framework can be used to strengthen significant collaborations and traceability that are important for the development of official deployment of telemedicine applications. Adequate mechanisms for information management with traceability of the reasoning process are also essential in the fields of epidemiology and public health. In this paper we enrich the case-based reasoning process by taking into account former evidence-based knowledge. We use the regular four steps approach and implement an additional (iii) step: (i) establish diagnosis, (ii) retrieve treatment, (iii) apply evidence, (iv) adaptation, (v) retain. Each step is performed using tools from knowledge engineering and information processing (natural language processing, ontology, indexation, algorithm, etc.). The case representation is done by the taxonomy component of a medical ontology model. The proposed approach is illustrated with an example from the oncology domain. Medical ontology allows a good and efficient modeling of the patient and his treatment. We are pointing up the role of evidences and specialist's opinions in effectiveness and safety of care

Piloting VAKE (Values and Knowledge Education) in the Education for Practice of Nurses.

Imagine the following situation: You are a nurse for elderly people, going to the homes of your patients. A female patient tells you on our first visit after hospital discharge following a hip fracture surgery that she does not want to be at home, because she is not well enough to be alone and she needs therapy with oxygen in permanent basis until she recovers from a respiratory temporary infection situa¬tion. This kind of situations is the starting point for an educational sequence that ad-dresses both values (here: life, human dignity, respect, loneliness) and knowledge (different medical treatments, legal rules, etc.). The example shows how intensely interrelated the values and the facts are. Based on this example we introduce the constructivist didactical tool VaKE (Values and Knowledge Education) that permits to combine both issues, and present a pilot study using this method in the education of nurses.Tempus/LLAF; VAKEinfo:eu-repo/semantics/publishedVersio

Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model

Recommender systems are gaining traction in healthcare because they can tailor recommendations based on users' feedback concerning their appreciation of previous health-related messages. However, recommender systems are often not grounded in behavioral change theories, which may further increase the effectiveness of their recommendations. This paper's objective is to describe principles for designing and developing a health recommender system grounded in the I-Change behavioral change model that shall be implemented through a mobile app for a smoking cessation support clinical trial. We built upon an existing smoking cessation health recommender system that delivered motivational messages through a mobile app. A group of experts assessed how the system may be improved to address the behavioral change determinants of the I-Change behavioral change model. The resulting system features a hybrid recommender algorithm for computer tailoring smoking cessation messages. A total of 331 different motivational messages were designed using 10 health communication methods. The algorithm was designed to match 58 message characteristics to each user pro le by following the principles of the I-Change model and maintaining the bene ts of the recommender system algorithms. The mobile app resulted in a streamlined version that aimed to improve the user experience, and this system's design bridges the gap between health recommender systems and the use of behavioral change theories. This article presents a novel approach integrating recommender system technology, health behavior technology, and computer-tailored technology. Future researchers will be able to build upon the principles applied in this case study.European Union's Horizon 2020 Research and Innovation Programme under Grant 68112

Occupational Therapy Assistant Mental Health Case-Based Learning Activities

Occupational Therapy Assistants (OTA) need to be skilled in clinical reasoning and able to apply principles, theories and approaches to functional problems (Neistadt, 1998; Royeen,1995; VanLeit, Crowe and Waterman, 2001). Occupational therapy assistant educational standards require that students be able to apply models of occupational performance and theories of occupation (Accreditation Council for Occupational Therapy Education, 2008). Research has shown that learners actively engaged in the learning process have increased satisfaction with their education (Robinson, 1994) and perform better on exams (Lord, 1997; Wilden, Crowther, Gubanich and Cannon, 2002). Scaffa and Wooster (2004) found self directed learning can significantly facilitate the development of students\u27 clinical reasoning skills. Case-based learning methods of instruction can be used to help meet the challenges that are experienced in occupational therapy assistant education while meeting the needs of adult learners. Fink\u27s taxonomy of significant learning provides a framework for developing questions that correspond with the various dimensions of clinical reasoning as described by Neistadt (1998) and Lysaght and Bent (2005). Case-based resources that address mental health topics across the lifespan and link knowledge of theory to practice have not been developed for occupational therapy assistant students. This product employs case-based learning which includes adult and active learning principles as an instructional strategy for OTA. Through the use of this product, students are able to apply knowledge of occupational behavior models and frames of references to mental health clinical conditions across the lifespan

An Exploration in Accountable Care Organization Structure, Contingency and Performance, 2015-2017

The Patient Protection and Affordable Care Act of 2010 enacted one of the most significant reforms seen in the United States healthcare landscape. The Center for Medicare and Medicaid (CMS) led transformation efforts in regulatory reform and coverage expansion across the U.S. population. Since 2010, care delivery systems have been shifting from episodic, decentralized and fee-for-service models to value-based population health models, like accountable care organizations (ACO). ACOs have been specifically primed for local response to improve the health of their communities. ACO research has traditionally focused on performance measures like mortality, readmissions, quality outcomes and savings. ACO organizational characteristics analyzed in the literature have focused on provider composition, health information technology, leadership structures and provider access. According to CMS, readmissions account for one of the greatest contributors in healthcare spend, and studies by The Commonwealth Fund detail the top percentile of the population as high need, high cost (HNHC) patients who further contribute to the majority of healthcare spend. Opportunity exists to explore the diversity among ACO structures, their relationship to local environments and influence on top contributors to healthcare spend, like readmissions and high need, high cost populations. The objectives of this study are to better understand existing ACO structures, explore relationships among ACO organizational structures, their local environment in which they operate and directional impact on performance, with emphasis on at risk patients like high need, high cost populations. Theoretically, this study applies Structural Contingency Theory (SCT) for its empirical analyses, specifically a multiple contingency approach. In the extant literature, SCT has not been commonly applied due to its longitudinal nature and limited public access to ACO organizational data. The study sample consists of 45 ACOs that entered into the Medicare Shared Savings Program under Track 1 for the entire term from 2015 to 2017. ACO performance is represented by total shared savings, change in rate of readmissions and change in rate of inpatient psychiatric admissions. Four contingency-structure relationships are analyzed from the National Survey of Accountable Care Organizations and CMS Public Use Files, 1) ACO governance structure and strategy alignment, 2) Interdependency from complex coordination and formalized provider agreement types, 3) interdependency from complex coordination and formalized relationships with mental and behavioral health specialists, and 4) complex coordination and health IT integration and interoperability. Regression analyses were used to analyzed potential misfit and directional impact on performance and the contingency-structure pairs. Results indicate that wide variety exists among ACO structures, that conventional investments in provider agreements and fully integrated health IT do not clearly present positive performance effect. Future research opportunities exist to further examine the impact ACO programs have on meeting community needs and populations. This study offers the theoretical application of a multiple contingency approach from Structural Contingency Theory and a practical exploration of ACO structure, its contextual operations and performance on high need, high cost populations