8,517 research outputs found
The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support
Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component
of a learning healthcare system. Research shows that the effectiveness of CDS is mixed.
Multifaceted context, system, recommendation and implementation factors may potentially affect the success of
CDS interventions. This paper describes the development of a checklist that is intended to support professionals to
implement CDS successfully.
Methods: We developed the checklist through an iterative process that involved a systematic review of evidence
and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert
panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients
and healthcare consumers and pilot testing of the checklist.
Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for
guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains,
i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist
positively as an instrument that could support people implementing guideline-based CDS across a wide range of
settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality
improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy.
Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of
CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS
effectiveness. Relying on a structured approach may prevent that important factors are missed
A Generic Approach to Supporting the Management of Computerised Clinical Guidelines and Protocols
Clinical guidelines or protocols (CGPs) are statements that are systematically developed for the purpose of guiding the clinician and the patient in making decisions about appropriate healthcare for specific clinical problems. Using CGPs is one of the most effective and proven ways to attaining improved quality, optimised resource utilisation, cost containment and reduced variation in healthcare practice. CGPs exist mainly as paper-based natural language statements, but are increasingly being computerised. Supporting computerised CGPs in a healthcare environment so that they are incorporated into the routine used daily by clinicians is complex and presents major information management challenges. This thesis contends that the management of computerised CGPs should incorporate their manipulation (operations and queries), in addition to their specification and execution, as part of a single unified management framework. The thesis applies modern advanced database technology to the task of managing computerised CGPs. The event-condition-action (ECA) rule paradigm is recognised to have a huge potential in supporting computerised CGPs. In this thesis, a unified generic framework, called SpEM and an approach, called MonCooS, were developed for enabling computerised CGPs, to be specified by using a specification language, called PLAN, which follows the ECA rule paradigm; executed by using a software mechanism based on the ECA mechanism within a modern database system, and manipulated by using a manipulation language, called TOPSQL. The MonCooS approach focuses on providing clinicians with assistance in monitoring and coordinating clinical interventions while leaving the reasoning task to domain experts. A proof-of-concepts system, TOPS, was developed to show that CGP management can be easily attained, within the SpEM framework, by using the MonCooS approach. TOPS is used to evaluate the framework and approach in a case study to manage a microalbuminuria protocol for diabetic patients. SpEM and MonCooS were found to be promising in supporting the full-scale management of information and knowledge for the computerised clinical protocol. Active capability within modern DBMS is still experiencing significant limitations in supporting some requirements of this application domain. These limitations lead to pointers for further improvements in database management system (DBMS) functionality for ECA rule support. The main contributions of this thesis are: a generic and unified framework for the management of CGPs; a general platform and an advanced software mechanism for the manipulation of information and knowledge in computerised CGPs; a requirement for further development of the active functionality within modern DBMS; and a case study for the computer-based management of microalbuminuria in diabetes patients
Supporting Special-Purpose Health Care Models via Web Interfaces
The potential of the Web, via both the Internet and intranets, to facilitate development of clinical information systems has been evident for some time. Most Web-based clinical workstations interfaces, however, provide merely a loose collection of access channels. There are numerous examples of systems for access to either patient data or clinical guidelines, but only isolated cases where clinical decision support is presented integrally with the process of patient care, in particular, in the form of active alerts and reminders based on patient data. Moreover, pressures in the health industry are increasing the need for doctors to practice in accordance with ¿best practice¿ guidelines and often to operate under novel health-care arrangements. We present the Care Plan On-Line (CPOL) system, which provides intranet-based support for the SA HealthPlus Coordinated Care model for chronic disease management. We describe the interface design rationale of CPOL and its implementation framework, which is flexible and broadly applicable to support new health care models over intranets or the Internet
Design considerations in a clinical trial of a cognitive behavioural intervention for the management of low back pain in primary care : Back Skills Training Trial
Background
Low back pain (LBP) is a major public health problem. Risk factors for the development and persistence of LBP include physical and psychological factors. However, most research activity has focused on physical solutions including manipulation, exercise training and activity promotion.
Methods/Design
This randomised controlled trial will establish the clinical and cost-effectiveness of a group programme, based on cognitive behavioural principles, for the management of sub-acute and chronic LBP in primary care. Our primary outcomes are disease specific measures of pain and function. Secondary outcomes include back beliefs, generic health related quality of life and resource use. All outcomes are measured over 12 months. Participants randomised to the intervention arm are invited to attend up to six weekly sessions each of 90 minutes; each group has 6–8 participants. A parallel qualitative study will aid the evaluation of the intervention.
Discussion
In this paper we describe the rationale and design of a randomised evaluation of a group based cognitive behavioural intervention for low back pain
Proposal to Strenghern Health Information System [HIS]
\ud
The HMIS Program described in this document aims at improving and strengthening the current Health Management Information System (HMIS) in Tanzania, known as MTUHA. The consortium behind the HMIS Program is headed by the Ministry of Health & Social Welfare (MOHSW) and consists of the following additional partners; Ifakara Health Research and Development Centre, University of Dar es Salaam and the University of Oslo, representing national and international capacity in HMIS. The HMIS Program is linked to the Payment for performance (P4P) funding scheme which is initiated by the Norway Tanzania Partnership Initiative. The P4P has a focus on maternal and child health and relies upon quality indicators on performance in these areas from health facilities and districts. The provision of quality data and indicators on MDG 4 & 5 is therefore a key target for the HMIS Program. The chosen approach is, however, to derive these data from the HMIS and not to establish a separate data collection structure, hence the HMIS Program. Quality information by way of essential indicators, such as for monitoring the Millennium Development Goals 4 & 5, are crucial for health services delivery and program management as well as for M&E. Currently, however, the HMIS is not providing such needed data of sufficient completeness, timeliness and quality, leading health programs and funding agencies to establish their own structures for data collection, and thus creating fragmentation and adding to the problem. The HMIS Program aims at changing this negative trend and turning the HMIS into the key source of shared essential quality information in Tanzania by; focusing on action oriented use of information for management at each level of the health services and by providing timely quality information to all stakeholders, including all health programs and funding agencies in the HMIS strengthening process – making it an all-inclusive national process, focusing on capacity development; on-site support and facilitation, short courses and continuous education, building capacity in the MOHSW and establishing a national network of HMIS support, and by building on experience, methods and tools from Africa’s “best practices” HMIS, such as South Africa – and Zanzibar Within this proposal the aim is to carry out the HMIS strengthening process in 1/3 of the districts in the country, 7 regions, during the first 3 years. The objective, however, is to cover the entire country during the 5 years duration of the NTPI. By aiming at quick and tangible results, the expectation is that other funding agencies will join forces and thereby ensuring national coverage.\ud
\u
Preventive medical care in remote Aboriginal communities in the Northern Territory: a follow-up study of the impact of clinical guidelines, computerised recall and reminder systems, and audit and feedback
Background
Interventions to improve delivery of preventive medical services have been shown to be effective in North America and the UK. However, there are few studies of the extent to which the impact of such interventions has been sustained, or of the impact of such interventions in disadvantaged populations or remote settings. This paper describes the trends in delivery of preventive medical services following a multifaceted intervention in remote community health centres in the Northern Territory of Australia.
Methods
The intervention comprised the development and dissemination of best practice guidelines supported by an electronic client register, recall and reminder systems and associated staff training, and audit and feedback. Clinical records in seven community health centres were audited at regular intervals against best practice guidelines over a period of three years, with feedback of audit findings to health centre staff and management.
Results
Levels of service delivery varied between services and between communities. There was an initial improvement in service levels for most services following the intervention, but improvements were in general not fully sustained over the three year period.
Conclusions
Improvements in service delivery are consistent with the international experience, although baseline and follow-up levels are in many cases higher than reported for comparable studies in North America and the UK. Sustainability of improvements may be achieved by institutionalisation of relevant work practices and enhanced health centre capacity
Knowledge engineering complex decision support system in managing rheumatoid arthritis.
Background: The management of rheumatoid arthritis (RA) involves partially recursive attempts to make optimal treatment decisions that balance the risks of the treatment to the patient against the benefits of the treatment, while monitoring the patient closely for clinical response, as inferred from prior and residual disease activity, and unwanted drug effects, including abnormal laboratory findings. To the extent that this process is logical, based on best available evidence and determined by considered opinion, it should be amenable to capture within a Clinical Decision Support Systems (CDSSs). The formalisation of logical transformations and their execution by computer tools at point of patient encounter holds the promise of more efficient and consistent use of treatment rules and more reliable clinical decision making.
Research Setting: The early Rheumatoid Arthritis (eRA) clinic of the Royal Adelaide Hospital (RAH) with approximately 20 RA patient visits per week, and involving 160 patients with a median duration of treatment of more than 4.5 years.
Methods: The study applied a Knowledge Engineering approach to interpret the complexities of RA management, in order to implement a knowledge-based CDSS. The study utilised Knowledge Acquisition processes to elicit and explicitly define the RA management rules underpinning the development of the CDSS; the processes were (1) conducting a comprehensive literature review of RA management, (2) observing clinic consultations and (3) consulting with local clinical experts/leaders. Bayes’
Theorem and Bayes Net were used to generate models for assessing contingent probabilities of unwanted events. A questionnaire based on 16 real patient cases was developed to test the concordance agreement between CDSS generated guidance in response to real-life clinical scenarios and decisions of rheumatologists in response to the scenarios.
Results: (1) Complex RA management rules were established which included (a) Rules for Changes in Dose/Agent and (b) Drug Toxicity Monitoring Rules. (2) A computer interpretable dynamic model for implementing the complex clinical guidance was found to be applicable. (3) A framework for a methotrexate (MTX) toxicity prediction model was developed, thereby allowing missing risk ratios (probabilities) to be identified. (4) Clinical decision-making processes and workflows were described.
Finally, (5) a preliminary version of the CDSS which computed Rules for Changes in Dose/Agent and Drug Toxicity Monitoring Rules was implemented and tested. One hundred and twenty-eight decisions collected from the 8 participating rheumatologists established the ability of the CDSS to match decisions of clinicians accustomed to application of Rules for Changes in Dose/Agent; rheumatologists unfamiliar with the rules displayed lower concordance (0.7857 vs. 0.3929, P = 0.0027). Neither group of rheumatologists matched the performance of the CDSS in making decisions based on highly complex Drug Toxicity Monitoring Rules (0.3611 vs. 0.4167, P = 0.7215).
Conclusion: The study has made important contributions to the development of a CDSS suitable for routine use in the eRA clinic setting. Knowledge Acquisition processes were used to elicit domain knowledge, and to refine, validate and articulate eRA management rules, that came to form the knowledge base of the CDSS. The development of computer interpretable guideline models underpinned the CDSS development. The alignment of CDSS guidance in response to clinical scenarios with questionnaire responses of rheumatologists familiar with and accepting of the management rules (and divergence with responses by rheumatologists not familiar with the rules) indicates that the CDSS can be used to guide toward evidence-based considered opinion. The poor correlation between CDSS generated guidance regarding out of range blood results and response of rheumatologists to questions regarding toxicity scenarios, underlines the value of computer aided guidance when decisions involve greater complexity. It also suggests the need for attention to rule development and considered opinion in this area.
Discussion: Effective utilisation of extant knowledge is fundamental to knowledgebased systems in healthcare. CDSSs development for chronic disease management is a complex undertaking which is tractable using Knowledge Engineering and Knowledge Acquisition approaches coupled with modelling into computer interpretable algorithms. Complexities of drug toxicity monitoring were addressed using Bayes’ Theorem and Bayes Net for making probability based decisions under conditions of uncertainty. While for logistic reasons the system could not be developed to full implementation, preliminary analyses support the utility of the approach, both for intensifying treatment on a response contingent basis and also for complex drug toxicity monitoring. CDSSs are inherently suited to iterative refinements based on new knowledge including that arising from analyses of the data they capture during their use. This study has achieved important steps toward implementation and refinement.Thesis (Ph.D.) -- University of Adelaide, School of Medicine, 201
Effective implementation of research into practice: an overview of systematic reviews of the health literature
<p>Abstract</p> <p>Background</p> <p>The gap between research findings and clinical practice is well documented and a range of interventions has been developed to increase the implementation of research into clinical practice.</p> <p>Findings</p> <p>A review of systematic reviews of the effectiveness of interventions designed to increase the use of research in clinical practice. A search for relevant systematic reviews was conducted of Medline and the Cochrane Database of Reviews 1998-2009. 13 systematic reviews containing 313 primary studies were included. Four strategy types are identified: audit and feedback; computerised decision support; opinion leaders; and multifaceted interventions. Nine of the reviews reported on multifaceted interventions. This review highlights the small effects of single interventions such as audit and feedback, computerised decision support and opinion leaders. Systematic reviews of multifaceted interventions claim an improvement in effectiveness over single interventions, with effect sizes ranging from small to moderate. This review found that a number of published systematic reviews fail to state whether the recommended practice change is based on the best available research evidence.</p> <p>Conclusions</p> <p>This overview of systematic reviews updates the body of knowledge relating to the effectiveness of key mechanisms for improving clinical practice and service development. Multifaceted interventions are more likely to improve practice than single interventions such as audit and feedback. This review identified a small literature focusing explicitly on getting research evidence into clinical practice. It emphasizes the importance of ensuring that primary studies and systematic reviews are precise about the extent to which the reported interventions focus on changing practice based on research evidence (as opposed to other information codified in guidelines and education materials).</p
- …