Aligning temporal data by sentinel events: discovering patterns in electronic health records
06 Apr 2008-pp 457-466
TL;DR: An interactive visual tool is presented that complements query formulation by providing operations to align, rank and filter the results, and to visualize estimates of the intervals of validity of the data.
Abstract: Electronic Health Records (EHRs) and other temporal databases contain hidden patterns that reveal important cause-and-effect phenomena. Finding these patterns is a challenge when using traditional query languages and tabular displays. We present an interactive visual tool that complements query formulation by providing operations to align, rank and filter the results, and to visualize estimates of the intervals of validity of the data. Display of patient histories aligned on sentinel events (such as a first heart attack) enables users to spot precursor, co-occurring, and aftereffect events. A controlled study demonstrates the benefits of providing alignment (with a 61% speed improvement for complex tasks). A qualitative study and interviews with medical professionals demonstrates that the interface can be learned quickly and seems to address their needs.
Citations
More filters
TL;DR: i2b2 software may be used by an enterprise's research community to find sets of interesting patients from electronic patient medical record data, while preserving patient privacy through a query tool interface.
815 citations
TL;DR: This lecture introduces exploratory search, relates it to relevant extant research, outline the features of exploratorySearch systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratorysearch.
Abstract: As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model support d by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world. Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks
725 citations
Cites methods from "Aligning temporal data by sentinel ..."
...Projects such as Lifelines2 (Wang et al., 2008) have used larger sets of data from patients’ electronic health records and medical test results, enabling medical professionals to align-rank and sort them according to the attributes available on the data....
[...]
01 Aug 2013
TL;DR: It is argued that this presents a number of challenges for CSCW research moving forward: in having a greater impact on larger-scale health IT projects; broadening the scope of settings and perspectives that are studied; and reflecting on the relevance of the traditional methods in this field - namely workplace studies - to meet these challenges.
Abstract: CSCW as a field has been concerned since its early days with healthcare, studying how healthcare work is collaboratively and practically achieved and designing systems to support that work. Reviewing literature from the CSCW Journal and related conferences where CSCW work is published, we reflect on the contributions that have emerged from this work. The analysis illustrates a rich range of concepts and findings towards understanding the work of healthcare but the work on the larger policy level is lacking. We argue that this presents a number of challenges for CSCW research moving forward: in having a greater impact on larger-scale health IT projects; broadening the scope of settings and perspectives that are studied; and reflecting on the relevance of the traditional methods in this field - namely workplace studies - to meet these challenges.
393 citations
07 May 2011
TL;DR: A novel interactive visual overview of event sequences called LifeFlow is introduced, which is scalable, can summarize all possible sequences, and represents the temporal spacing of the events within sequences.
Abstract: Event sequence analysis is an important task in many domains: medical researchers may study the patterns of transfers within the hospital for quality control; transportation experts may study accident response logs to identify best practices. In many cases they deal with thousands of records. While previous research has focused on searching and browsing, overview tasks are often overlooked. We introduce a novel interactive visual overview of event sequences called \emph{LifeFlow}. LifeFlow is scalable, can summarize all possible sequences, and represents the temporal spacing of the events within sequences. Two case studies with healthcare and transportation domain experts are presented to illustrate the usefulness of LifeFlow. A user study with ten participants confirmed that after 15 minutes of training novice users were able to rapidly answer questions about the prevalence and temporal characteristics of sequences, find anomalies, and gain significant insight from the data.
318 citations
Cites background or methods from "Aligning temporal data by sentinel ..."
...events (in the same approach as LifeLines2 [34])....
[...]
...Those tools typically provide searching and filtering mechanisms, such as LifeLines2 [34], Similan [38] or ActiviTree [33]....
[...]
...Ho using LifeLines2 [34] and Similan [38] to locate patients with specific known event sequences such as the one described above....
[...]
TL;DR: This paper presents a series of user-driven data simplifications that allow researchers to pare event records down to their core elements, and presents a novel metric for measuring visual complexity, and a language for codifying disjoint strategies into an overarching simplification framework.
Abstract: Electronic Health Records (EHRs) have emerged as a cost-effective data source for conducting medical research. The difficulty in using EHRs for research purposes, however, is that both patient selection and record analysis must be conducted across very large, and typically very noisy datasets. Our previous work introduced EventFlow, a visualization tool that transforms an entire dataset of temporal event records into an aggregated display, allowing researchers to analyze population-level patterns and trends. As datasets become larger and more varied, however, it becomes increasingly difficult to provide a succinct, summarizing display. This paper presents a series of user-driven data simplifications that allow researchers to pare event records down to their core elements. Furthermore, we present a novel metric for measuring visual complexity, and a language for codifying disjoint strategies into an overarching simplification framework. These simplifications were used by real-world researchers to gain new and valuable insights from initially overwhelming datasets.
262 citations
Cites background from "Aligning temporal data by sentinel ..."
...…of gaining understanding on two different levels: • Intra-Record Understanding: Knowledge is gained about the sequence of events that comprises a single record (i.e. a patient record or a shipment record): Why was this patient transferred from the Emergency Room to the Intensive Care Unit (ICU)?...
[...]
References
More filters
13 Apr 1996
TL;DR: The paper describes the use of LifeLines for youth records of the Maryland Department of Juvenile Justice and also for medical records, and Techniques to deal with complex records are reviewed and issues of a standard personal record format are discussed.
Abstract: LifeLines provide a general visualization environment for personal histories that can be applied to medical and court records, professional histories and other types of biographical data. A one screen overview shows multiple facets of the records. Aspects, for example medical conditions or legal cases, are displayed as individual time lines, while icons indicate discrete events, such as physician consultations or legal reviews. Line color and thickness illustrate relationships or significance, rescaling tools and filters allow users to focus on part of the information. LifeLines reduce the chances of missing information, facilitate spotting anomalies and trends, streamline access to details, while remaining tailorable and easily transferable between applications. The paper describes the use of LifeLines for youth records of the Maryland Department of Juvenile Justice and also for medical records. User's feedback was collected using a Visual Basic prototype for the youth record. Techniques to deal with complex records are reviewed and issues of a standard personal record format are discussed.
575 citations
"Aligning temporal data by sentinel ..." refers background in this paper
...Lifelines [15,16] presents personal history record data organized in expandable facets and allows both point event and interval event representations....
[...]
...The output of a query (e.g. Find all patients who had a diagnosis of asthma and pneumonia-or-influenza) becomes the input data of Lifelines2....
[...]
...DESCRIPTION OF THE INTERFACE Lifelines2 is an extension of Lifelines [15,16]....
[...]
...Plaisant, C., Milash, B., Rose, A., Widoff, S., Shneiderman, B., Lifelines: visualizing personal histories....
[...]
...We gave the only introduction that Lifelines2 is used to view results from a search in patient databases....
[...]
12 Nov 1998
TL;DR: A Java user interface is described, which presents a one-screen overview of a computerized patient record using timelines using LifeLines, which acts as a giant menu, giving direct access to the data.
Abstract: LifeLines provide a general visualization environment for personal histories. We explore its use for clinical patient records. A Java user interface is described, which presents a one-screen overview of a computerized patient record using timelines. Problems, diagnoses, test results or medications can be represented as dots or horizontal lines. Zooming provides more details; line color and thickness illustrate relationships or significance. The visual display acts as a giant menu, giving direct access to the data.
394 citations
"Aligning temporal data by sentinel ..." refers background in this paper
...Lifelines [15,16] presents personal history record data organized in expandable facets and allows both point event and interval event representations....
[...]
...The output of a query (e.g. Find all patients who had a diagnosis of asthma and pneumonia-or-influenza) becomes the input data of Lifelines2....
[...]
...DESCRIPTION OF THE INTERFACE Lifelines2 is an extension of Lifelines [15,16]....
[...]
...Plaisant, C., Milash, B., Rose, A., Widoff, S., Shneiderman, B., Lifelines: visualizing personal histories....
[...]
...We gave the only introduction that Lifelines2 is used to view results from a search in patient databases....
[...]
22 Oct 2001
TL;DR: The extension of the spiral visualization to 3D gives access to concepts for zooming and focusing and linking in the data set and complements other visualization techniques for time series and specifically enhance the identication of periodic patterns.
Abstract: In this paper, we present a new approach for the visualization of time-series data based on spirals. Different to classical bar charts and line graphs, the spiral is suited to visualize large data sets and supports much better the identification of periodic structures in the data. Moreover, it supports both the visualization of nominal and quantitative data based on a similar visualization metaphor. The extension of the spiral visualization to 3D gives access to concepts for zooming and focusing and linking in the data set. As such, spirals complement other visualization techniques for time series and specifically enhance the identication of periodic patterns.
377 citations
"Aligning temporal data by sentinel ..." refers background or methods in this paper
...However, these alignments are non-interactive [12,19], non-data-driven [4, 22 ], or require manual specification of objects or time points to be aligned [7]....
[...]
...Aside from calendars, researchers have used spirals to visualize periodic data [4, 22 ]....
[...]
TL;DR: It is concluded that a polylithic approach is most suitable for toolkit builders, visual design software where code is automatically generated, and application builders where there is much customization of the toolkit.
Abstract: Here, we analyze toolkit designs for building graphical applications with rich user interfaces, comparing polylithic and monolithic toolkit-based solutions. Polylithic toolkits encourage extension by composition and follow a design philosophy similar to 3D scene graphs supported by toolkits including JavaSD and Openlnventor. Monolithic toolkits, on the other hand, encourage extension by inheritance, and are more akin to 2D graphical user interface toolkits such as Swing or MFC. We describe Jazz (a polylithic toolkit) and Piccolo (a monolithic toolkit), each of which we built to support interactive 2D structured graphics applications in general, and zoomable user interface applications in particular. We examine the trade offs of each approach in terms of performance, memory requirements, and programmability. We conclude that a polylithic approach is most suitable for toolkit builders, visual design software where code is automatically generated, and application builders where there is much customization of the toolkit. Correspondingly, we find that monolithic approaches appear to be best for application builders where there is not much customization of the toolkit.
341 citations
"Aligning temporal data by sentinel ..." refers methods in this paper
...It is a Java application, utilizing the Piccolo 2D graphics framework [ 3 ]....
[...]
TL;DR: Extended case studies involving the analysis of two different types of data from molecular biology experiments provided valuable feedback and validated the utility of both the timebox model and the TimeSearcher tool.
Abstract: Timeboxes are rectangular widgets that can be used in direct-manipulation graphical user interfaces (GUIs) to specify query constraints on time series data sets. Timeboxes are used to specify simultaneously two sets of constraints: given a set of N time series profiles, a timebox covering time periods x1...x2 (x1
289 citations