RAGs: A Novel Approach to Computerized Genetic Risk Assessment and Decision Support from Pedigrees

Argumentation schemes for clinical decision support

This paper demonstrates how argumentation schemes can be used in decision support systems that help clinicians in making treatment decisions. The work builds on the use of computational argumentation, a rigorous approach to reasoning with complex data that places strong emphasis on being able to justify and explain the decisions that are recommended. The main contribution of the paper is to present a novel set of specialised argumentation schemes that can be used in the context of a clinical decision support system to assist in reasoning about what treatments to offer. These schemes provide a mechanism for capturing clinical reasoning in such a way that it can be handled by the formal reasoning mechanisms of formal argumentation. The paper describes how the integration between argumentation schemes and formal argumentation may be carried out, sketches how this is achieved by an implementation that we have created and illustrates the overall process on a small set of case studies.

Making sense of personal health information: challenges for information visualization

This article presents a systematic review of the literature on information visualization for making sense of personal health information. Based on this review, five application themes were identified: treatment planning, examination of patients' medical records, representation of pedigrees and family history, communication and shared decision making, and life management and health monitoring. While there are recognized design challenges associated with each of these themes, such as how best to represent data visually and integrate qualitative and quantitative information, other challenges and opportunities have received little attention to date. In this article, we highlight, in particular, the opportunities for supporting people in better understanding their own illnesses and making sense of their health conditions in order to manage them more effectively.

Clinical prediction rules in practice: review of clinical guidelines and survey of GPs

BACKGROUND

The publication of clinical prediction rules (CPRs) studies has risen significantly. It is unclear if this reflects increasing usage of these tools in clinical practice or how this may vary across clinical areas.

AIM

To review clinical guidelines in selected areas and survey GPs in order to explore CPR usefulness in the opinion of experts and use at the point of care.

DESIGN AND SETTING

A review of clinical guidelines and survey of UK GPs.

METHOD

Clinical guidelines in eight clinical domains with published CPRs were reviewed for recommendations to use CPRs including primary prevention of cardiovascular disease, transient ischaemic attack (TIA) and stroke, diabetes mellitus, fracture risk assessment in osteoporosis, lower limb fractures, breast cancer, depression, and acute infections in childhood. An online survey of 401 UK GPs was also conducted.

RESULTS

Guideline review: Of 7637 records screened by title and/or abstract, 243 clinical guidelines met inclusion criteria. CPRs were most commonly recommended in guidelines regarding primary prevention of cardiovascular disease (67%) and depression (67%). There was little consensus across various clinical guidelines as to which CPR to use preferentially.

SURVEY

Of 401 responders to the GP survey, most were aware of and applied named CPRs in the clinical areas of cardiovascular disease and depression. The commonest reasons for using CPRs were to guide management and conform to local policy requirements.

CONCLUSION

GPs use CPRs to guide management but also to comply with local policy requirements. Future research could focus on which clinical areas clinicians would most benefit from CPRs and promoting the use of robust, externally validated CPRs.

Clinical decision support for genetically guided personalized medicine: a systematic review

OBJECTIVE

To review the literature on clinical decision support (CDS) for genetically guided personalized medicine (GPM).

MATERIALS AND METHODS

MEDLINE and Embase were searched from 1990 to 2011. The manuscripts included were summarized, and notable themes and trends were identified.

RESULTS

Following a screening of 3416 articles, 38 primary research articles were identified. Focal areas of research included family history-driven CDS, cancer management, and pharmacogenomics. Nine randomized controlled trials of CDS interventions for GPM were identified, seven of which reported positive results. The majority of manuscripts were published on or after 2007, with increased recent focus on genotype-driven CDS and the integration of CDS within primary clinical information systems.

DISCUSSION

Substantial research has been conducted to date on the use of CDS to enable GPM. In a previous analysis of CDS intervention trials, the automatic provision of CDS as a part of routine clinical workflow had been identified as being critical for CDS effectiveness. There was some indication that CDS for GPM could potentially be effective without the CDS being provided automatically, but we did not find conclusive evidence to support this hypothesis.

CONCLUSION

To maximize the clinical benefits arising from ongoing discoveries in genetics and genomics, additional research and development is recommended for identifying how best to leverage CDS to bridge the gap between the promise and realization of GPM.

The GRAIDS Trial: The development and evaluation of computer decision support for cancer genetic risk assessment in primary care

The development and evaluation of computer decision support for the assessment of cancer genetic risk in primary care is reported with two series of studies described: the RAGs (Risk Assessment in Genetics) studies and the GRAIDS (Genetic Risk Assessment in an Intranet and Decision Support) Trial. In the GRAIDS Trial, 45 general practices in Eastern England have been recruited and randomised. Comparison practices attend an educational session and receive clinical guidelines about familial breast and colorectal cancer. In the intervention practices a lead clinician is trained in cancer genetics and use of the GRAIDS software. The GRAIDS software is a simple pedigree-drawing program that implements clinical guidelines for familial breast and colorectal cancer and presents individualised information about breast cancer risk in a range of formats. Outcome measures of the trial include: frequency of software use, practitioners' attitudes towards the software, total number of referrals to secondary care about familial cancer and the proportion that meet regional referral criteria, and a patient-centred measure of informed decision making. The family history will become an increasingly important tool in primary care to assess genetic risk. This research evaluates an approach to support high-quality advice about cancer genetics in primary care which could be applied more broadly as our understanding of complex disease genetics increases.

Developing decision support systems in clinical bioinformatics

There is a growing demand for tools to support clinicians utilize genomic results generated by molecular diagnostic and cytogenetic methods in support of their decision-making. This chapter reviews existing experience and methods for the design, implementation and evaluation of clinical bioinformatics electronic decision support systems (EDSS). It provides a roadmap for identifying decision tasks for automation and selecting optimal tools for building task-specific systems. Key success factors for EDSS implementation and evaluation are also outlined.

Risk Communication During Screening for Genomic Breast Cancer Susceptibility

Screening for genomic predisposition to diseases of adulthood is emerging in standard medical practice. Breast cancer predisposition testing provides a useful example for understanding the potential implications of risk-related screening in practice. Risk is an important and complex psychological construct that is understood differently both between scientific disciplines and between medical and lay persons. The process of establishing thresholds for classifying whether one's risk reaches levels warranting departure from standard preventive strategies is an important predictor of both physician feedback and patient interpretation of their risk. Messages about genomic breast cancer risk arising during the pedigree screening context are conveyed via explicit and implicit modes of communication. Best practices for communicating about genomic risk and the implications for health disparities related to screening for genomic susceptibility remain unknown. More work is urgently needed given the societal forces that are catalyzing population-based screening for genomic predisposition into the routine practice of preventive medicine.

Association between screening family medical history in general medical care and lower burden of cancer worry among women with a close family history of breast cancer

PURPOSE

Soliciting family medical history (FMH) is the initial step in the process of screening for heritable cancer risk in medical care. We investigate whether recent solicitation of FMH in general medical care is associated with cancer worry among a sample of women having a first-degree relative with a breast cancer diagnosis.

METHODS

Surveys were mailed to women registered with the Cancer Genetics Network having a first-degree relative with a breast cancer diagnosis and a regular source of medical care. The independent measure consisted of two items for solicitation of FMH based on validated measures of clinical interactions with one's physician; the dependent measure was a novel measure of cancer worry based on validated patient-centered measure of distress; and the secondary measures were 6-point scales for perceived likelihood of developing breast cancer and perceived severity of breast cancer as a health outcome.

RESULTS

A total of 353 women responded and met eligibility criteria (76.4% minimum response rate). One fifth reported no cancer worry during the past 4 weeks. After adjustment for age, education, pedigree features, and clustering within families, recent FMH solicitation was associated with lower odds of cancer worry (odds ratio = 0.58; 95% confidence interval = 0.51-0.70). FMH solicitation was associated with lower perceptions of the severity of developing breast cancer but not with the perception of cancer likelihood.

CONCLUSIONS

Our data do not support the hypothesis that FMH solicitation in general medical practice causes cancer worry. In fact, we observed a protective association possibly explained by influences on perceptions of breast cancer severity. Prospective research among less select populations is necessary.

The syntax and semantics of the PROforma guideline modeling language

PROforma is an executable process modeling language that has been used successfully to build and deploy a range of decision support systems, guidelines, and other clinical applications. It is one of a number of recent proposals for representing clinical protocols and guidelines in a machine-executable format (see <www.openclinical.org>). In this report, the authors outline the task model for the language and provide an operational semantics for process enactment together with a semantics for expressions, which may be used to query the state of a task during enactment. The operational semantics includes a number of public operations that may be performed on an application by an external agent, including operations that change the values of data items, recommend or make decisions, manage tasks that have been performed, and perform any task state changes that are implied by the current state of the application. Disclosure: PROforma has been used as the basis of a commercial decision support and guideline technology Arezzo (Infermed, London, UK; details in text).