Taxonometric applications in radiotherapy incident analysis.

Recent publications in both the scientific and the popular press have highlighted the risks to which patients expose themselves when entering a healthcare system. Patient safety issues are forcing us to, not only acknowledge that incidents do occur, but also actively develop the means for assessing and managing the risks of such incidents. To do this, we ideally need to know the probability of an incident's occurrence, the consequences or severity for the patient should it occur, and the basic causes of the incident. A structured approach to the description of failure modes is helpful in terms of communication, avoidance of ambiguity, and, ultimately, decision making for resource allocation. In this report, several classification schemes or taxonomies for use in risk assessment and management are discussed. In particular, a recently developed approach that reflects the activity domains through which the patient passes and that can be used as a basis for quantifying incident severity is described. The estimation of incident severity, which is based on the concept of the equivalent uniform dose, is presented in some detail. We conclude with a brief discussion on the use of a defined basic-causes table and how adding such a table to the reports of incidents can facilitate the allocation of resources.

Probabilistic fault tree analysis of a radiation treatment system.

Inappropriate administration of radiation for cancer treatment can result in severe consequences such as premature death or appreciably impaired quality of life. There has been little study of vulnerable treatment process components and their contribution to the risk of radiation treatment (RT). In this article, we describe the application of probabilistic fault tree methods to assess the probability of radiation misadministration to patients at a large cancer treatment center. We conducted a systematic analysis of the RT process that identified four process domains: Assessment, Preparation, Treatment, and Follow-up. For the Preparation domain, we analyzed possible incident scenarios via fault trees. For each task, we also identified existing quality control measures. To populate the fault trees we used subjective probabilities from experts and compared results with incident report data. Both the fault tree and the incident report analysis revealed simulation tasks to be most prone to incidents, and the treatment prescription task to be least prone to incidents. The probability of a Preparation domain incident was estimated to be in the range of 0.1-0.7% based on incident reports, which is comparable to the mean value of 0.4% from the fault tree analysis using probabilities from the expert elicitation exercise. In conclusion, an analysis of part of the RT system using a fault tree populated with subjective probabilities from experts was useful in identifying vulnerable components of the system, and provided quantitative data for risk management.

The Equivalent Uniform Dose as a severity metric for radiation treatment incidents.

In allocating resources within a risk management program, ideally we would like to know both the probabilities and consequences of potential incidents. We simulate, on a treatment planning computer, several commonly reported incidents in radiation treatment and explore their consequences for the EUDs of targets and organs at risk.

Risk analysis in radiation treatment: application of a new taxonomic structure.

BACKGROUND AND PURPOSE: Radiation treatment (RT) for cancer is susceptible to clinical incidents resulting from human errors and equipment failures. A systematic approach to collecting and processing incidents is required to manage patient risks. We describe the application of a new taxonomic structure for RT that supports risk analysis and organizational learning. MATERIALS AND METHODS: A systematic analysis of the RT process identified five process domains. Within each domain we defined incident type groups. We then constructed a database reflecting this taxonomic structure and populated it with incidents from publicly available sources. Querying this database provides insights into the nature and relative frequency of incidents in RT. RESULTS: There are relatively few reports of incidents in the Prescription domain compared with the Preparation and Treatment domains. There are also fewer reports of systematic and infrastructure incidents in comparison to sporadic and process incidents. Infrastructure incidents are mainly systematic in nature, while process incidents are more likely to be sporadic. CONCLUSIONS: The lack of a standard, systems-oriented framework for incident reporting makes it difficult to learn from existing incident report sources. A clear understanding of the potential consequences and relationships between different incident types will guide incident reporting, resource allocation, and risk management efforts.

Implications of cancer staging uncertainties in radiation therapy decisions.

INTRODUCTION: Radiation therapy (RT) for cancer is a critical medical procedure that occurs in a complex environment involving numerous health professionals, hardware, software, and equipment. Uncertainties and potential incidents can lead to inappropriate administration of radiation to patients, with sometimes catastrophic consequences such as premature death or appreciably impaired quality of life. The authors evaluate the impact of incorrectly staging (i.e., estimation of extent of cancer) breast cancer patients and resulting inappropriate treatment decisions. METHODS: The authors employ analytic and simulation methods in an influence-diagram framework to estimate the probability of incorrect staging and treatment decisions. As inputs, they use a combination of literature information on the accuracy and precision of pathology and tests as well as expert judgment. Sensitivity and value-of-information analyses are conducted to identify important uncertainties. RESULTS AND CONCLUSIONS: The authors find a small but nontrivial probability that breast cancer patients will be incorrectly staged and thus may be subjected to inappropriate treatment. Results are sensitive to a number of variables, and some routinely used tests for metastasis have very limited information value. This work has implications for the methods used in cancer staging, and the methods are generalizable for quantitative risk assessment of treatment errors.