Dataset Information

Improving Clinical Trial Participant Tracking Tools Using Knowledge-anchored Design Methodologies.

ABSTRACT: OBJECTIVE: Rigorous human-computer interaction (HCI) design methodologies have not traditionally been applied to the development of clinical trial participant tracking (CTPT) tools. Given the frequent us of iconic HCI models in CTPTs, and prior evidence of usability problems associated with the use of ambiguous icons in complex interfaces, such approaches may be problematic. Presentation Discovery (PD), a knowledge-anchored HCI design method, has been previously demonstrated to improve the design of iconic HCI models. In this study, we compare the usability of a CTPT HCI model designed using PD and an intuitively designed CTPT HCI model. METHODS: An iconic CPTP HCI model was created using PD. The PD-generated and an existing iconic CTPT HCI model were subjected to usability testing, with an emphasis on task accuracy and completion times. Study participants also completed a qualitative survey instrument to evaluate subjective satisfaction with the two models. RESULTS: CTPT end-users reliably and reproducibly agreed on the visual manifestation and semantics of prototype graphics generated using PD. The performance of the PD-generated iconic HCI model was equivalent to an existing HCI model for tasks at multiple levels of complexity, and in some cases superior. This difference was particularly notable when tasks required an understanding of the semantic meanings of multiple icons. CONCLUSION: The use of PD to design an iconic CTPT HCI model generated beneficial results and improved end-user subjective satisfaction, while reducing task completion time. Such results are desirable in information and time intensive domains, such as clinical trials management.

SUBMITTER: Payne PR

PROVIDER: S-EPMC3225206 | biostudies-other | 2010

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundCurrently, the most promising therapies for Duchenne muscular dystrophy (DMD) are exon skipping and stop codon read-through, two strategies aimed at restoring the expression of dystrophin. A phase 3 clinical trial with drisapersen, a drug designed to induce exon 51-skipping, has failed to show significant improvement of the primary outcome measure, the six-minute walk test.DiscussionHere, we review some key points that should be considered when designing clinical trials for these new therapies. First, younger patients have more functional abilities and more muscle fibers to preserve than older patients and therefore are better subjects for trials designed to demonstrate the success of new treatments. Second, the inclusion of patients on corticosteroids both in the treatment and placebo groups is of concern because the positive effect of corticosteroids might mask the effect of the treatment being tested. Additionally, the reasonable expectation from these therapies is the slowing of disease progression rather than improvement. Therefore, the appropriate clinical endpoints are the prolongation of the ability to stand from the floor, climb stairs, and walk, not an increase in muscle strength or function. Hence, the time frames for the detection of new dystrophin, which occurs within months, and the ability to demonstrate a slowing of disease progression, which requires years, are strikingly different. Finally, placebo-controlled trials are difficult to manage if years of blindness are required to demonstrate a slowing of disease progression. Thus, accelerated/conditional approval for new therapies should be based on surrogate biochemical outcomes: the demonstration of de novo dystrophin production and of its beneficial effect on the functional recovery of muscle fiber. These data suggest that clinical trials for DMD patients must be adapted to the particular characteristics of the disease in order to demonstrate the expected positive effect of new treatments.

Project description:BackgroundClinical trials are the primary mechanism for advancing clinical care and evidenced-based practice, yet challenges with the recruitment of participants for such trials are widely recognized as a major barrier to these types of studies. Data warehouses (DW) store large amounts of heterogenous clinical data that can be used to enhance recruitment practices, but multiple challenges exist when using a data warehouse for such activities, due to the manner of collection, management, integration, analysis, and dissemination of the data. A critical step in leveraging the DW for recruitment purposes is being able to match trial eligibility criteria to discrete and semi-structured data types in the data warehouse, though trial eligibility criteria tend to be written without concern for their computability. We present the multi-modal evaluation of a web-based tool that can be used for pre-screening patients for clinical trial eligibility and assess the ability of this tool to be practically used for clinical research pre-screening and recruitment.MethodsThe study used a validation study, usability testing, and a heuristic evaluation to evaluate and characterize the operational characteristics of the software as well as human factors affecting its use.ResultsClinical trials from the Division of Cardiology and the Department of Family Medicine were used for this multi-modal evaluation, which included a validation study, usability study, and a heuristic evaluation. From the results of the validation study, the software demonstrated a positive predictive value (PPV) of 54.12% and 0.7%, respectively, and a negative predictive value (NPV) of 73.3% and 87.5%, respectively, for two types of clinical trials. Heuristic principles concerning error prevention and documentation were characterized as the major usability issues during the heuristic evaluation.ConclusionsThis software is intended to provide an initial list of eligible patients to a clinical study coordinators, which provides a starting point for further eligibility screening by the coordinator. Because this software has a high "rule in" ability, meaning that it is able to remove patients who are not eligible for the study, the use of an automated tool built to leverage an existing enterprise DW can be beneficial to determining eligibility and facilitating clinical trial recruitment through pre-screening. While the results of this study are promising, further refinement and study of this and related approaches to automated eligibility screening, including comparison to other approaches and stakeholder perceptions, are needed and future studies are planned to address these needs.

Project description:BackgroundPositive impacts of quality improvement initiatives on health care and services have not been substantial. Knowledge translation (KT) strategies (tools, products and interventions) strive to facilitate the uptake of knowledge thereby the potential to improve care, but there is little guidance on how to develop them. Existing KT guidance or planning tools fall short in operationalizing all aspects of KT practice activities conducted by knowledge users (researchers, clinicians, patients, decision-makers), and most do not consider their variable needs or to deliver recommendations that are most relevant and useful for them.MethodsWe conducted a 3-phase study. In phase 1, we used several sources to develop a conceptual framework for creating optimized Knowledge-activated Tools (KaT) (consultation with our integrated KT team, the use of existing KT models and frameworks, findings of a systematic review of multimorbidity interventions and a literature review and document analysis on existing KT guidance tools). In phase 2, we invited KT experts to participate in a Delphi study to refine and evaluate the conceptual KaT framework. In phase 3, we administered an online survey to knowledge users (researchers, clinicians, decision-makers, trainees) to evaluate the potential usefulness of an online mock-up version of the KaT framework.ResultsWe developed the conceptual KaT framework, and iteratively refined it with 35 KT experts in a 3-round Delphi study. The final framework represents the blueprint for what is needed to create KT strategies. Feedback from 201 researcher, clinician, decision-maker and trainee knowledge users on the potential need and usefulness of an online, interactive version of KaT indicated that they liked the idea of it (mean score 4.36 on a 5-point Likert scale) and its proposed features (mean score range 4.30-4.79).ConclusionsOur findings suggest that mostly Canadian KT experts and knowledge users perceived the KaT framework and the future development of an online, interactive version to be important and needed. We anticipate that the KaT framework will provide clarity for knowledge users about how to identify their KT needs and what activities can address these needs, and to help streamline the process of these activities to facilitate efficient uptake of knowledge.

Dataset Information

Improving Clinical Trial Participant Tracking Tools Using Knowledge-anchored Design Methodologies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets