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

A qualitative investigation on patient empowerment in prostate cancer

Purpose: Men with prostate cancer often describe low levels of empowerment. eHealth interventions may represent useful tools to deliver care and education and to meet patients' needs within an empowerment framework. In order to design a platform for cancer patients' empowerment within the H2020 iManageCancer project, the perspective of the target population for the platform was assessed. The present study aims to assess the qualitative experience of prostate cancer patients during treatment in order to provide insights for clinical practice with a particular focus on the design of a web platform to promote cancer patients' empowerment. Methods: Ten patients undergoing radiation therapy treatment took part in a semi-structured interview to explore different aspects of patient empowerment. Four main thematic areas were addressed: patient-healthcare providers' communication, decision-making, needs, and resources. A qualitative approach using thematic analysis was followed. Results: Half of the patients reported little to no possibility to share information and questions with healthcare providers. With regards to decision-making, the role of healthcare providers was perceived as directive/informative, but half of the patients perceived to assume an active role in at least one interaction. Difficulties and needs included the choice of the specialist or of the structure after diagnosis, clinicians' support in self-management, surgical consequences, and side effects, preparation for radiation therapy. Resources included family and social support both from a practical and from an emotional perspective, coping style, and work schedule management. Conclusions: These results suggest that relations with healthcare providers should be supported, especially immediately after diagnosis and after surgery. Support to self-management after surgery and at the beginning of radiation therapy treatment also constitutes a priority. The adoption of a personalized approach from the beginning of prostate cancer care flow may promote patient empowerment,overcoming the aforementioned needs and mobilizing resources. The social network represents an important resource that could be integrated in interventions. These considerations will be taken into account in the design of a cancer self-management platform aiming to increase patients' empowerment

Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol

Introduction In the UK, primary care is seen as the optimal context for delivering care to an ageing population with a growing number of long-term conditions. However, if it is to meet these demands effectively and efficiently, a more precise understanding of existing care processes is required to ensure their configuration is based on robust evidence. This need to understand and optimise organisational performance is not unique to healthcare, and in industries such as telecommunications or finance, a methodology known as ‘process mining’ has become an established and successful method to identify how an organisation can best deploy resources to meet the needs of its clients and customers. Here and for the first time in the UK, we will apply it to primary care settings to gain a greater understanding of how patients with two of the most common chronic conditions are managed. Methods and analysis The study will be conducted in three phases; first, we will apply process mining algorithms to the data held on the clinical management system of four practices of varying characteristics in the West Midlands to determine how each interacts with patients with hypertension or type 2 diabetes. Second, we will use traditional process mapping exercises at each practice to manually produce maps of care processes for the selected condition. Third, with the aid of staff and patients at each practice, we will compare and contrast the process models produced by process mining with the process maps produced via manual techniques, review differences and similarities between them and the relative importance of each. The first pilot study will be on hypertension and the second for patients diagnosed with type 2 diabetes

HDLalert – a healthcare DL alerting system: from user needs to implementation

In the health domain, there are many circumstances where clinicians (i.e. doctors, nurses, allied health professionals) and patients wish to track changes in medical knowledge. However, existing 'news' or 'alert' services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients' perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material

Healthcare Process Support: Achievements, Challenges, Current Research

Healthcare organizations are facing the challenge of delivering high-quality services to their patients at affordable costs. To tackle this challenge, the Medical Informatics community targets at formalisms for developing decision-support systems (DSSs) based on clinical guidelines. At the same time, business process management (BPM) enables IT support for healthcare processes, e.g., based on workflow technology. By integrating aspects from these two fields, promising perspectives for achieving better healthcare process support arise. The perspectives and limitations of IT support for healthcare processes provided the focus of three Workshops on Process-oriented Information Systems (ProHealth). These were held in conjunction with the International Conference on Business Process Management in 2007-2009. The ProHealth workshops provided a forum wherein challenges, paradigms, and tools for optimized process support in healthcare were debated. Following the success of these workshops, this special issue on process support in healthcare provides extended papers by research groups who contributed multiple times to the ProHealth workshop series. These works address issues pertaining to healthcare process modeling, process-aware healthcare information system, workflow management in healthcare, IT support for guideline implementation and medical decision support, flexibility in healthcare processes, process interoperability in healthcare and healthcare standards, clinical semantics of healthcare processes, healthcare process patterns, best practices for designing healthcare processes, and healthcare process validation, verification, and evaluation

Knowledge-driven delivery of home care services

The version of record is available online at: http://dx.doi.org/10.1007/s10844-010-0145-0Home Care (HC) assistance is emerging as an effective and efficient alternative to institutionalized care, especially for the case of senior patients that present multiple co-morbidities and require life long treatments under continuous supervision. The care of such patients requires the definition of specially tailored treatments and their delivery involves the coordination of a team of professionals from different institutions, requiring the management of many kinds of knowledge (medical, organizational, social and procedural). The K4Care project aims to assist the HC of elderly patients by proposing a standard HC model and implementing it in a knowledge-driven e-health platform aimed to support the provision of HC services.Peer ReviewedPostprint (author's final draft

Information Systems and Healthcare XXXIV: Clinical Knowledge Management Systems—Literature Review and Research Issues for Information Systems

Knowledge Management (KM) has emerged as a possible solution to many of the challenges facing U.S. and international healthcare systems. These challenges include concerns regarding the safety and quality of patient care, critical inefficiency, disparate technologies and information standards, rapidly rising costs and clinical information overload. In this paper, we focus on clinical knowledge management systems (CKMS) research. The objectives of the paper are to evaluate the current state of knowledge management systems diffusion in the clinical setting, assess the present status and focus of CKMS research efforts, and identify research gaps and opportunities for future work across the medical informatics and information systems disciplines. The study analyzes the literature along two dimensions: (1) the knowledge management processes of creation, capture, transfer, and application, and (2) the clinical processes of diagnosis, treatment, monitoring and prognosis. The study reveals that the vast majority of CKMS research has been conducted by the medical and health informatics communities. Information systems (IS) researchers have played a limited role in past CKMS research. Overall, the results indicate that there is considerable potential for IS researchers to contribute their expertise to the improvement of clinical process through technology-based KM approaches

Development and implementation of clinical guidelines : an artificial intelligence perspective

Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst-OE/EEI/UI0752/2011"