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

Neuroanatomical substrates for the volitional regulation of heart rate

The control of physiological arousal can assist in the regulation of emotional state. A subset cortical and subcortical brain regions are implicated in autonomic control of bodily arousal during emotional behaviors. Here, we combined human functional neuroimaging with autonomic monitoring to identify neural mechanisms that support the volitional regulation of heart rate, a process that may be assisted by visual feedback. During functional magnetic resonance imaging (fMRI), 15 healthy adults performed an experimental task in which they were prompted voluntarily to increase or decrease cardiovascular arousal (heart rate) during true, false, or absent visual feedback. Participants achieved appropriate changes in heart rate, without significant modulation of respiratory rate, and were overall not influenced by the presence of visual feedback. Increased activity in right amygdala, striatum and brainstem occurred when participants attempted to increase heart rate. In contrast, activation of ventrolateral prefrontal and parietal cortices occurred when attempting to decrease heart rate. Biofeedback enhanced activity within occipito-temporal cortices, but there was no significant interaction with task conditions. Activity in regions including pregenual anterior cingulate and ventral striatum reflected the magnitude of successful task performance, which was negatively related to subclinical anxiety symptoms. Measured changes in respiration correlated with posterior insula activation and heart rate, at a more lenient threshold, change correlated with insula, caudate, and midbrain activity. Our findings highlight a set of brain regions, notably ventrolateral prefrontal cortex, supporting volitional control of cardiovascular arousal. These data are relevant to understanding neural substrates supporting interaction between intentional and interoceptive states related to anxiety, with implications for biofeedback interventions, e.g., real-time fMRI, that target emotional regulation

Southern African Treatment Resistance Network (SATuRN) RegaDB HIV drug resistance and clinical management database: supporting patient management, surveillance and research in southern Africa

Substantial amounts of data have been generated from patient management and academic exercises designed to better understand the human immunodeficiency virus (HIV) epidemic and design interventions to control it. A number of specialized databases have been designed to manage huge data sets from HIV cohort, vaccine, host genomic and drug resistance studies. Besides databases from cohort studies, most of the online databases contain limited curated data and are thus sequence repositories. HIV drug resistance has been shown to have a great potential to derail the progress made thus far through antiretroviral therapy. Thus, a lot of resources have been invested in generating drug resistance data for patient management and surveillance purposes. Unfortunately, most of the data currently available relate to subtype B even though >60% of the epidemic is caused by HIV-1 subtype C. A consortium of clinicians, scientists, public health experts and policy markers working in southern Africa came together and formed a network, the Southern African Treatment and Resistance Network (SATuRN), with the aim of increasing curated HIV-1 subtype C and tuberculosis drug resistance data. This article describes the HIV-1 data curation process using the SATuRN Rega database. The data curation is a manual and time-consuming process done by clinical, laboratory and data curation specialists. Access to the highly curated data sets is through applications that are reviewed by the SATuRN executive committee. Examples of research outputs from the analysis of the curated data include trends in the level of transmitted drug resistance in South Africa, analysis of the levels of acquired resistance among patients failing therapy and factors associated with the absence of genotypic evidence of drug resistance among patients failing therapy. All these studies have been important for informing first- and second-line therapy. This database is a free password-protected open source database available on www.bioafrica.net

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Towards validation of a new computerised test of goal neglect: preliminary evidence from clinical and neuroimaging pilot studies

Objective: Goal neglect is a significant problem following brain injury, and is a target for rehabilitation. It is not yet known how neural activation might change to reflect rehabilitation gains. We developed a computerised multiple elements test (CMET), suitable for use in neuroimaging paradigms. Design: Pilot correlational study and event-related fMRI study. Methods: In Study 1, 18 adults with acquired brain injury were assessed using the CMET, other tests of goal neglect (Hotel Test; Modified Six Elements Test) and tests of reasoning. In Study 2, 12 healthy adults underwent fMRI, during which the CMET was administered under two conditions: self-generated switching and experimenter-prompted switching. Results: Among the clinical sample, CMET performance was positively correlated with both the Hotel Test (r = 0.675, p = 0.003) and the Modified Six Elements Test (r = 0.568, p = 0.014), but not with other clinical or demographic measures. In the healthy sample, fMRI demonstrated significant activation in rostro-lateral prefrontal cortex in the self-generated condition compared with the prompted condition (peak 40, 44, 4; ZE = 4.25, p(FWEcorr) = 0.026). Conclusions: These pilot studies provide preliminary evidence towards the validation of the CMET as a measure of goal neglect. Future studies will aim to further establish its psychometric properties, and determine optimum pre- and post-rehabilitation fMRI paradigms

Automated Measurement of Adherence to Traumatic Brain Injury (TBI) Guidelines using Neurological ICU Data

Using a combination of physiological and treatment information from neurological ICU data-sets, adherence to traumatic brain injury (TBI) guidelines on hypotension, intracranial pressure (ICP) and cerebral perfusion pressure (CPP) is calculated automatically. The ICU output is evaluated to capture pressure events and actions taken by clinical staff for patient management, and are then re-expressed as simplified process models. The official TBI guidelines from the Brain Trauma Foundation are similarly evaluated, so the two structures can be compared and a quantifiable distance between the two calculated (the measure of adherence). The methods used include: the compilation of physiological and treatment information into event logs and subsequently process models; the expression of the BTF guidelines in process models within the real-time context of the ICU; a calculation of distance between the two processes using two algorithms (“Direct” and “Weighted”) building on work conducted in th e business process domain. Results are presented across two categories each with clinical utility (minute-by-minute and single patient stays) using a real ICU data-set. Results of two sample patients using a weighted algorithm show a non-adherence level of 6.25% for 42 mins and 56.25% for 708 mins and non-adherence of 18.75% for 17 minutes and 56.25% for 483 minutes. Expressed as two combinatorial metrics (duration/non-adherence (A) and duration * non-adherence (B)), which together indicate the clinical importance of the non-adherence, one has a mean of A=4.63 and B=10014.16 and the other a mean of A=0.43 and B=500.0