Vivek Patkar

Evidence-based guidelines and decision support services: a discussion and evaluation in triple assessment of suspected breast cancer

Widespread health service goals to improve consistency and safety in patient care have prompted considerable investment in the development of evidence-based clinical guidelines. Computerised decision support (CDS) systems have been proposed as a means to implement guidelines in practice. This paper discusses the general concept in oncology and presents an evaluation of a CDS system to support triple assessment (TA) in breast cancer care. Balanced-block crossover experiment and questionnaire study. One stop clinic for symptomatic breast patients. Twenty-four practising breast clinicians from United Kingdom National Health Service hospitals. A web-based CDS system. Clinicians made significantly more deviations from guideline recommendations without decision support (60 out of 120 errors without CDS; 16 out of 120 errors with CDS, P<0.001). Ignoring minor deviations, 16 potentially critical errors arose in the no-decision-support arm of the trial compared with just one (P=0.001) when decision support was available. Opinions of participating clinicians towards the CDS tool became more positive after they had used it (P<0.025). The use of decision support capabilities in TA may yield significant measurable benefits for quality and safety of patient care. This is an important option for improving compliance with evidence-based practice guidelines.

Argumentation about treatment efficacy

The volume and complexity of knowledge produced by medical research calls for the development of technology for automated management and analysis of such knowledge. In this paper, we identify scenarios where a researcher or a clinician may wish to use automated systems for analysing knowledge from clinical trials. For this, we propose a language for encoding, capturing and synthesising knowledge from clinical trials and a framework that allows the construction of arguments from such knowledge. We develop this framework and demonstrate its use on a case study regarding chemotherapy regimens for ovarian cancer.

Goal-Based Decisions for Dynamic Planning

The need for clinical guidelines to be implemented at different sites, to adapt to rapidly changing environments, and to be carried out by distributed clinical teams, implies a degree of flexibility beyond that of current guideline languages. We propose an extension to the PROforma language allowing hierarchical goal-based plans. Sub-plans to achieve goals are proposed at runtime so that changing circumstances may be flexibly accommodated without redefining the workflow.

Challenges in delivering decision support systems: the MATE experience

Cancer Multidisciplinary Meeting (MDM) is a widely endorsed mechanism for ensuring high quality evidence-based health care. However, there are shortcomings that could ultimately result in unintended patient harm. On the other hand, clinical guidelines and clinical decision support systems (DSS) have been shown to improve decision-making in various measures. Nevertheless, their clinical use requires seamlessly interoperation with the existing electronic health record (EHR) platform to avoid the detrimental effects that duplication of data and work has in the quality of care. The aim of this work is to propose a computational framework to provide a clinical guideline-based DSS for breast cancer MDM. We discuss a range of design and implementation issues related to knowledge representation and clinical service delivery of the system, and propose a service oriented architecture based on the HL7 EHR functional model. The main result is the DSS named MATE (Multidisciplinary Assistant and Treatment sElector), which demonstrates that decision support can be effectively deployed in a real clinical setting and suggest that the technology could be generalised to other cancer MDMs.

Using computerized decision support to improve compliance of cancer multidisciplinary meetings with evidence-based guidance.

79 Background: The cancer multidisciplinary team (MDT) meeting is regarded as the best platform to reduce unwarranted variation in cancer care through evidence-compliant management. However, MDT meetings are often overburdened with many different agendas, and hence struggle to achieve their full potential. METHODS We have developed an interactive computer system called MATE to facilitate explicit, evidence-based decision-making in MDT meetings for breast cancer care. MATE provides prognostication and risk assessment and also flags up patients eligible for recruiting into ongoing research trials. We describe the system; share our experience of implementing MATE and report initial audit and survey results. MATE was used to record the proceedings of breast MDT meetings between 2008-2009 to gather 1,295 cases discussed in the MDMs during this period and to audit the MDT decisions and MATE recommendations against NICE, NHSBSP, and NCCN guidelines. RESULTS MATE identified 61% more patients who were eligible for recruitment into clinical trials than the MDT and its recommendations demonstrated high concordance with MDT decisions (93.2 %). MATE is in routine use in breast MDT meetings at Royal Free Hospital, London, and deployment of the system in other NHS trusts is being explored. CONCLUSIONS Sophisticated decision support systems can enhance the conduct of MDT meetings in a way that is acceptable to and valued by the clinical team. Further rigorous evaluations are required to examine cost-effectiveness, measure the impact on patient outcomes and test the generalizability of the system in different hospital setups and in different cancers.

An advanced computerized decision support technology to support breast multidisciplinary meetings

658 Background: Cancer multidisciplinary meetings (MDM) or tumour boards have become standard of care in management of breast cancer. As the number of cases continue to increase, better tools are required to support these heavily loaded meetings which play a pivotal role in patient management. We investigate the role of an advanced computerized decision support (CDS) technology in further enhancing the outputs of breast MDM. Methods: We have built a novel decision-support system called MATE to assist evidence-based decision making in breast MDM. MATE implements recommendations from 17 high quality breast screening, diagnosis and management guidelines. MATE provides prognostication and risk assessment and also flags up patients eligible for trials. In our pilot study, the data of 1,000 consecutive breast cases presented at the Royal Free Hospital breast MDM along with their documented MDM recommendations were entered into MATE. MDM recommendations and MATE suggestions were analyzed and compared. Results: T...

A Novel Evidence-Adaptive Computerised Decision Support System for Breast Cancer Multidisciplinary Meetings: Results of an Evaluation Study.

Background: Multidisciplinary meetings (MDM) also known as multidisciplinary cancer conferences are a forum for providing evidence-based care and are widely accepted as a part of standard cancer care worldwide. In United Kingdom, it is a mandatory requirement that the care of all breast cancer patients is managed through breast MDMs. However the lack of required support for conducting MDM is documented in many recent reviews. Advanced Computerised Decision Support (CDS) technology can play an important role in supporting MDMs and improving its functioning. We present a novel breast MDM support tool which integrates a CDS system into an electronic patient record to assist breast Multi Disciplinary Team (MDT) in making an evidence based, transparent treatment decisions during MDM. To the best of our knowledge there are no published studies of implementing computerised decision support systems for breast MDM. Methods: The Multi-disciplinary meeting Assistant and Treatment sElector (MATE) is a tool designed to assist breast clinicians in making management decisions for their patients in MDM. MATE is developed using a PRO forma CDS technology which is funded by the Cancer Research UK. The tool is implemented in the breast unit of Royal Free hospital, London for its pilot testing. MATE evaluates patient9s clinical facts and suggests optimal management options according to incorporated national and international clinical guidelines. The evidence base used in MATE can be updated as and when new evidence is published. MATE recommendations are not binding and the final decision is taken by breast MDT. MATE facilitates the flexible conduct of MDM. Additionally, it highlights if the patient is eligible to take part in any local, national or international clinical trials. In the evaluation study, the data of 300 consecutive breast patients presented at the Royal Free breast MDM along with their documented MDM recommendations are entered in MATE. MDM recommendations and MATE suggestions are analysed. Results: MATE system is able to suggest the treatment recommendations in concordance with breast MDT in most of the cases (91 %). MATE suggested more management options per patient than the documented MDT recommendations (3.4% vs. 1.2 %). MATE also identified 65% more patients suitable for ongoing clinical trials. Deviations that occur specially in unaided MDMs can be minimised using electronic data capture and decision support system like MATE. Conclusion: This evaluation study has shown the feasibility of implementing MATE into MDM and its potential to improve certain aspects of MDM by helping overburdened clinicians. The evidence adaptive decision support component of MATE can improve the guideline-compliance and transparency in the decision-making and also identify more patients to be considered for recruitment in clinical trials. Another important benefit could be completeness of documentation. Further evaluations of MATE in a randomised controlled trial are under way. If found beneficial, the system could easily be adapted for other cancers. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 5118.