HDLalert – a healthcare DL alerting system: from user needs to implementation
Identifieur interne : 000B73 ( Istex/Corpus ); précédent : 000B72; suivant : 000B74HDLalert – a healthcare DL alerting system: from user needs to implementation
Auteurs : Annika Hinze ; George Buchanan ; Doris Jung ; Anne AdamsSource :
- Health Informatics Journal [ 1460-4582 ] ; 2006-06.
Abstract
In the health domain, there are many circumstances where clinicians (i.e. doctors, nurses, allied health professionals) and patients wish to track changes in medical knowledge. However, existing ‘news’ or ‘alert’ services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients’ perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material.
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DOI: 10.1177/1460458206063808
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University Singleton Park, Swansea SA2 8PP, UKg.r.buchanan@swansea.ac.uk</mods:affiliation></affiliation></author><author><name sortKey="Jung, Doris" sort="Jung, Doris" uniqKey="Jung D" first="Doris" last="Jung">Doris Jung</name><affiliation><mods:affiliation></mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: d.jung@cs.waikato.ac.nz</mods:affiliation></affiliation><affiliation><mods:affiliation>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealandd.jung@cs.waikato.ac.nz</mods:affiliation></affiliation></author><author><name sortKey="Adams, Anne" sort="Adams, Anne" uniqKey="Adams A" first="Anne" last="Adams">Anne Adams</name><affiliation><mods:affiliation></mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: a.adams@cs.ucl.ac.uk</mods:affiliation></affiliation><affiliation><mods:affiliation>UCL Interaction Centre (UCLIC), Remax House 31–32 Alfred Place, London WC1E 7DP, 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a.hinze@cs.waikato.ac.nz</mods:affiliation></affiliation><affiliation><mods:affiliation>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealanda.hinze@cs.waikato.ac.nz</mods:affiliation></affiliation></author><author><name sortKey="Buchanan, George" sort="Buchanan, George" uniqKey="Buchanan G" first="George" last="Buchanan">George Buchanan</name><affiliation><mods:affiliation></mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: g.r.buchanan@swansea.ac.uk</mods:affiliation></affiliation><affiliation><mods:affiliation>Swansea University Singleton Park, Swansea SA2 8PP, UKg.r.buchanan@swansea.ac.uk</mods:affiliation></affiliation></author><author><name sortKey="Jung, Doris" sort="Jung, Doris" uniqKey="Jung D" first="Doris" last="Jung">Doris Jung</name><affiliation><mods:affiliation></mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: d.jung@cs.waikato.ac.nz</mods:affiliation></affiliation><affiliation><mods:affiliation>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealandd.jung@cs.waikato.ac.nz</mods:affiliation></affiliation></author><author><name sortKey="Adams, Anne" sort="Adams, Anne" uniqKey="Adams A" first="Anne" last="Adams">Anne Adams</name><affiliation><mods:affiliation></mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: a.adams@cs.ucl.ac.uk</mods:affiliation></affiliation><affiliation><mods:affiliation>UCL Interaction Centre (UCLIC), Remax House 31–32 Alfred Place, London WC1E 7DP, UKa.adams@cs.ucl.ac.uk</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Health Informatics Journal</title><idno type="ISSN">1460-4582</idno><idno type="eISSN">1741-2811</idno><imprint><publisher>SAGE Publications</publisher><pubPlace>London, Thousand Oaks, CA and New Delhi</pubPlace><date type="published" 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However, existing ‘news’ or ‘alert’ services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients’ perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material.</div></front></TEI><istex><corpusName>sage</corpusName><author><json:item><name>Annika Hinze</name><affiliations><json:null></json:null><json:string>E-mail: a.hinze@cs.waikato.ac.nz</json:string><json:string>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealanda.hinze@cs.waikato.ac.nz</json:string></affiliations></json:item><json:item><name>George Buchanan</name><affiliations><json:null></json:null><json:string>E-mail: g.r.buchanan@swansea.ac.uk</json:string><json:string>Swansea University Singleton Park, Swansea SA2 8PP, UKg.r.buchanan@swansea.ac.uk</json:string></affiliations></json:item><json:item><name>Doris Jung</name><affiliations><json:null></json:null><json:string>E-mail: d.jung@cs.waikato.ac.nz</json:string><json:string>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealandd.jung@cs.waikato.ac.nz</json:string></affiliations></json:item><json:item><name>Anne Adams</name><affiliations><json:null></json:null><json:string>E-mail: a.adams@cs.ucl.ac.uk</json:string><json:string>UCL Interaction Centre (UCLIC), Remax House 31–32 Alfred Place, London WC1E 7DP, UKa.adams@cs.ucl.ac.uk</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>alerting</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>design</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>digital library</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>healthcare</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>human factors</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>user studies</value></json:item></subject><articleId><json:string>10.1177_1460458206063808</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>research-article</json:string></originalGenre><abstract>In the health domain, there are many circumstances where clinicians (i.e. doctors, nurses, allied health professionals) and patients wish to track changes in medical knowledge. 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UKg.r.buchanan@swansea.ac.uk</affiliation></author><author xml:id="author-3"><persName><forename type="first">Doris</forename><surname>Jung</surname></persName><email>d.jung@cs.waikato.ac.nz</email><affiliation></affiliation><affiliation>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealandd.jung@cs.waikato.ac.nz</affiliation></author><author xml:id="author-4"><persName><forename type="first">Anne</forename><surname>Adams</surname></persName><email>a.adams@cs.ucl.ac.uk</email><affiliation></affiliation><affiliation>UCL Interaction Centre (UCLIC), Remax House 31–32 Alfred Place, London WC1E 7DP, UKa.adams@cs.ucl.ac.uk</affiliation></author></analytic><monogr><title level="j">Health Informatics Journal</title><idno type="pISSN">1460-4582</idno><idno type="eISSN">1741-2811</idno><imprint><publisher>SAGE Publications</publisher><pubPlace>London, Thousand Oaks, CA and New Delhi</pubPlace><date type="published" when="2006-06"></date><biblScope 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However, existing ‘news’ or ‘alert’ services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients’ perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material.</p></abstract><textClass><keywords scheme="keyword"><list><head>keywords</head><item><term>alerting</term></item><item><term>design</term></item><item><term>digital library</term></item><item><term>healthcare</term></item><item><term>human factors</term></item><item><term>user studies</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2006-06">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/CC47C706F64773412F12597A5968C77BAB04229E/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="corpus sage not found" wicri:toSee="no header"><istex:xmlDeclaration>version="1.0" encoding="UTF-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" URI="journalpublishing.dtd" name="istex:docType"></istex:docType><istex:document><article article-type="research-article" dtd-version="2.3" xml:lang="EN"><front><journal-meta><journal-id journal-id-type="hwp">spjhi</journal-id><journal-id journal-id-type="publisher-id">JHI</journal-id><journal-title>Health Informatics Journal</journal-title><issn pub-type="ppub">1460-4582</issn><publisher><publisher-name>SAGE Publications</publisher-name><publisher-loc>London, Thousand Oaks, CA and New Delhi</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.1177/1460458206063808</article-id><article-id pub-id-type="publisher-id">10.1177_1460458206063808</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>HDLalert – a healthcare DL alerting system: from user needs to implementation</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hinze</surname><given-names>Annika</given-names></name><aff>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealand<email xlink:type="simple">a.hinze@cs.waikato.ac.nz</email></aff></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Buchanan</surname><given-names>George</given-names></name><aff>Swansea University Singleton Park, Swansea SA2 8PP, UK<email xlink:type="simple">g.r.buchanan@swansea.ac.uk</email></aff></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jung</surname><given-names>Doris</given-names></name><aff>Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealand<email xlink:type="simple">d.jung@cs.waikato.ac.nz</email></aff></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Adams</surname><given-names>Anne</given-names></name><aff>UCL Interaction Centre (UCLIC), Remax House 31–32 Alfred Place, London WC1E 7DP, UK<email xlink:type="simple">a.adams@cs.ucl.ac.uk</email></aff></contrib></contrib-group><pub-date pub-type="ppub"><month>06</month><year>2006</year></pub-date><volume>12</volume><issue>2</issue><fpage>121</fpage><lpage>135</lpage><abstract><p>In the health domain, there are many circumstances where clinicians (i.e. doctors, nurses, allied health professionals) and patients wish to track changes in medical knowledge. However, existing ‘news’ or ‘alert’ services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients’ perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material.</p></abstract><kwd-group><kwd>alerting</kwd><kwd>design</kwd><kwd>digital library</kwd><kwd>healthcare</kwd><kwd>human factors</kwd><kwd>user studies</kwd></kwd-group><custom-meta-wrap><custom-meta xlink:type="simple"><meta-name>sagemeta-type</meta-name><meta-value>Journal Article</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>search-text</meta-name><meta-value> HDLalert a healthcare DL alerting system: from user needs to implementation Annika Hinze, George Buchanan, Doris Jung and Anne Adams In the health domain, there are many circumstances where clinicians (i.e. doctors, nurses, allied health professionals) and patients wish to track changes in medical knowledge. However, existing 'news' or 'alert' services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients' perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material. Keywords alerting, design, digital library, healthcare, human factors, user studies Introduction In the clinical domain, growing importance is placed on the use of current best evidence [1]. Evidence-based medicine highlights the importance of timely, accurate and concise information in healthcare professionals' decision making processes. Reddy and Dourish [2] confirm the importance of information being available at a glance to all members of a unit. They also identified that currently this is supported not by technology but by discussions with colleagues and the information they source. Similarly, patients increas- ingly discover their need to understand and actively deal with their health issues, as is 121 Article Copyright © 2006 SAGE Publications (London, Thousand Oaks, CA and New Delhi) Vol 12(2): 121135 [1460-4582(200606)12:2;121135; DOI: 10.1177/1460458206063808] www.sagepublications.com Health Informatics Journal reflected by the huge number of support groups as well as initiatives such as the expert patients programme (EPP) of the British health service. There is, therefore, an escalating need to improve the accessibility of reputable information sources. We will now consider how available sources meet the demanding needs of the health domain. Web-accessible information sources present the potential to greatly advance learning capabilities regardless of users' location and time restrictions [35]. Digital libraries are a key example of such web-based resources. In comparison with traditional libraries, digital libraries (DLs) can provide specialized information in a format that is easily updated, with speedy searching and access facilities. However, web-based sources in general frequently fall short of expectations in their uptake and day-to-day usage [4]. One potential problem for clinicians as well as for patients is an awareness of what is available that is relevant and in which of the frequently changing sources it can be found. The tedious effort to repeatedly access and search these sources can be too time-consuming for time-pressured clinicians. It is also beyond the expertise of many patients to evaluate the significance of the information regarding their condition. Another important problem is the complex and changing needs of different professionals and patients that vary according to their situations, i.e. the differing context of the users. Digital library alerting services are a potential solution to these problems. Currently, these systems are time-consuming to set up and do not provide the flexibility to fit with their users' personal and situational needs which are constantly changing. This paper reviews the special health user requirements for such an alerting service. It then intro- duces a novel architecture for a healthcare DL alerting system, building upon a flexible generic alerting model. Background This section is in two parts. First we examine general influences on the adoption of digital library technologies. We then introduce alerting with a discussion of alerting specifically in the health domain. Influences on DL adoption Bishop's [6] study into digital library users identifies that users can easily be deterred from using libraries and that poor awareness of library coverage prevents a full understanding of their potential. It has been argued that the reason for this is a need to have more comprehensive views of information within the context of related tasks and how that changes over time [7, 8]. Other work [9, 10] has explored how users can gain this through access to digital information while they are mobile (i.e. contextualizing the information to users' current time and place). However, most of these research directions detail searching and interpretation of digital library sources. Most systems do not relate well to users' temporal processes which start before searching commences with the awareness and initiation of information requirements. Todd et al. [11] highlight the fact that nurses' current work practices (e.g. shift patterns, ward-bound duties) restrict their access to libraries and the Internet. The difficulty some clinical professionals experience in accessing the physical library, and the push for evidenced-based medicine, have resulted in different approaches to implementing digital Health Informatics Journal 12 (2) 122 library technology such as remote DL access, computers on the wards and outreach information intermediaries. However, recent studies have identified that clinicians not only require timely high-quality information but also demand that it fits with their own personal requirements and can be accessed when they have time (e.g. on breaks) [12]. Most clinical alerting services are set up through specific publishers or digital libraries (e.g. British Medical Journal, Medline) whereby keywords are used to search titles or sometimes abstracts. However, the National electronic Library for Health now provides clinicians with access to the Zetoc current awareness service, within the JISC Information Environment and eScience applications [13]. However, as demonstrated in [14], publisher-provided alerts give only limited support for selecting the notifications that the user wishes to receive. Furthermore, these systems also fail to support the user's context, providing the same information about a topic regardless of the user's abilities or environment. For example, health priorities frequently change in response to disease threats, between different medical areas and wards, or when patients learn about long-term conditions. Finally, these systems are generally discrete, and fail to integrate with each other, leaving the user with a number of disjointed services with different controls, delivery methods and editorial styles. Alerting services in health environments An alerting service [15] informs its users about changes or news in which they are inter- ested. Information about these changes is provided by publishers, e.g. digital libraries or electronic health records (EHRs). Publishers send messages about changes to the alerting service (see Figure 1). Changes of interests may be alterations to a patient's medication, which is entered into the EHR. The interests of users are defined in profiles. These profiles are registered with the alerting service. Incoming change messages are filtered by the alerting service according to the user profiles. Whenever the alerting service identifies information that matches profiles, the respective users are alerted by a notification. There are several areas where alerting services have been applied in the health domain. A number of systems are used for emergency care and for the monitoring of laboratory results. Examples are a real-time clinical alerting service for intensive care units [16], a Hinze et al. HDLalert 123 Figure 1 Alerting service overview system supplying wireless clinical alerts for physiologic, laboratory and medication data [17], a system for wireless clinical alerts in a surgical intensive care unit [18], a system for real-time notification of laboratory data requested by users through alphanumeric pagers [19], a laboratory results alerting service for ambulatory and hospitalized patients [20], a clinical event monitor CLEM [21] as well as the ColumbiaPresbyterian Medical Center clinical event monitor [22]. Another group of health-focused information systems are workflow systems. Examples are a clinical reminder system for ambulatory care [23], a careflow management system for chronic patients [24] and a framework for clinical test request protocols, PLAN [25]. Some decision support tools provide reminder functionalities, such as the paediatric diag- nostic reminder tool ISABEL [26]. Alerting is also provided in disease surveillance systems, such as RODS (Real-time Outbreak and Disease Surveillance) [27]. These current alerting services for healthcare share several severe drawbacks. First, these systems are highly tailored to the specific task for which they were designed. Many rely on receiving technical (numerical) measurements from instruments, which map poorly onto the textual analysis required for alerts in libraries. Also, the profiles that define when an alert should be sent inherently have a simple structure. They rely on the relative sparsity of notifiable changes or on a few selecting options to limit the number of alerts received by the user. In DL contexts, greater flexibility is required to support large volumes of heterogeneous data. Similarly, the tasks supported in a DL are also fluid with complex information needs. In addition, none of these clinical systems are intended for patient use or support (we have elaborated this point in more detail in [28]). Health support user studies Alerting-related findings were sourced and reanalysed from four studies conducted within the UK healthcare domain over a four year period. In-depth interviews, focus groups and observational studies were conducted with 125 clinicians (nurses, junior doctors, consult- ants, surgeons, occupational therapists, psychologists, nutritionists etc.), library and health information personnel, managers and IT department members. Studies 1 and 2 looked at two comparative hospitals (i.e. city-based and provincial); study 3 appraised the use of outreach librarians; while study 4 evaluated a patient health call centre. Further findings are also presented from an online survey focusing on requirements for a patient-centred mobile alerting system. The survey lasted for 2 weeks in February 2005. It was based on a series of interviews taken in a university clinic, participant evidence from actively following condition-relevant newsgroups (over several years prior to the research study) and several use-case developments. Here we will consider the aspects of the survey that were directed towards patients, doctors, nurses and IT department employees of clinics within Germany and New Zealand. This analysis refers to the patient participants. DL awareness and alerts Clinicians' awareness of what was in digital libraries and mechanisms to support their usage (e.g. alerting systems) was identified as very poor. Of the clinicians interviewed, approximately 80 per cent had not heard of the largest UK national clinical digital library (National Library for Health), or were unaware of how it could support their specific needs. Health Informatics Journal 12 (2) 124 However, a project placing information intermediaries within clinical teams was found to support increased awareness of digital resources and their relevance to clinicians' needs. Intermediaries attended team meetings and ward rounds, recording queries and searches in situ or actively proposing searches. [The information intermediary] would sort of raise the flag and she became very good also at predicting and anticipating . . . a clinical question. (consultant) All the clinicians noted how the clinical intermediary provided flexible support for their use of digital information sources to raise awareness and initiate future DL information requirements. The skill of the librarians highlighted how clinicians could use alerts to support their specific needs. However, frequently these mechanisms increase the likeli- hood of information overload through poor personalization and thus delivery of more content than needed. Press alerts Patients' information requirements were identified as often initiated by fears induced by press, family or friends. Because there is a lot of information out there in the media and in the press. People hear about it and they call us because I think they're worried about it, or they think it's going to affect them. I mean we certainly have a lot more health alerts than we ever had. (health information officer) It was also noted by clinicians that they were being forced to become more aware of current press issues, both to allay patients' fears and to find out what position was being taken by their professional body or their hospital. Nursing staff reported that it would be useful to have a resource that captured these changing issues and related them to current evidence, organizational and national health perspectives. The findings highlighted the need for press alerts that would link recent press articles on a particular subject with related current research and professional articles and then collate them for the user. Patient information alerts Qualitative data were collected from participants taking part in condition-related news- groups. Patients identified a need to be informed about information on their condition. This need intensifies whenever a change in their condition takes place (e.g. change in medication, the necessity to undergo an operation). This finding was verified by an online survey that triangulated both quantitative and qualitative data [14]. Moreover, 71 per cent of patients highlighted a need to be alerted about educational material (i.e. research findings, research funding). Other participants highlighted the need to be notified about more practical information. What to look for in emergency situations of the disease (i.e. something to tell me if a given symptom will go away on its own, or is worthy of a visit to the hospital). (patient) Hinze et al. HDLalert 125 Contextualizing resources The immediate benefits of updated, locally relevant, day-to-day clinical information (e.g. policies, procedures, induction data, guidelines, and protocols), electronically stored and quickly retrievable, were recognized. Clinicians, however, require more than simple elec- tronic representations of documents. These information sources would be invaluable if, subject to appropriate authentication, they could fulfil specific user needs, provide local knowledge and prompt updating requirements. How to care for a wound point 6 ohhh yes I have to use this type of dressing and where are they kept ohhhh right they're kept under there. (nurse) Users also detailed the need for flexible libraries of organizational information (e.g. job title, role, contact details, schedules and diaries) that would then link into communication media such as e-mail and ultimately the electronic patient record and evidence-based medicine resources. Summary of user requirements In this section, we have identified a number of user requirements for alerting in health digital libraries. In the course of discussing these requirements, we have demonstrated that there is a wide variety of material that users may wish to track. The needs of a consultant are very different from those of the patient they treat or of nursing and other clinical staff. These differences are often reflected in the form of material that a specific user wishes to read. However, particularly for medical staff, their current environment or clinical demands have a strong influence on their information needs. Coarse-grained alerting systems that provide many alerts on a broad topic are unlikely to supply the targeted, timely infor- mation that they require. Patients' needs are no less complex: responding to one source of health news, they may wish to discover related material that 'makes sense' of clinical material in terms that they comprehend and have practical value for their day-to-day life. System requirements Given our user studies outlined above, we have arrived at a number of requirements for a health alerting service. To illuminate these, we will first introduce three simple scenarios requirements R1, R2 and R3 to clarify some uses of such a service (for illustration see Figure 1). R1 A clinician (e.g. doctor, nurse) would like to be notified with relevant research results, whenever there is an important new press release and it is likely that his or her patients will make inquiries about this topic: 'Send related research results when a new press release is published.' Here, the alerting service has to filter a digital library in order to find out more information relevant to each new press release. When relevant documents have been found, the clinician is then sent relevant research results, together with the original press release. R2 A nurse works in several units of a hospital. In these units they have differing treatment guidelines for certain conditions; it is difficult to keep track of these differences. Therefore the nurse wants to be reminded about the respective Health Informatics Journal 12 (2) 126 guidelines whenever he or she changes unit: 'Send treatment guidelines when clinical unit has changed.' A location sensor (for indoor [29] or outdoor [30] use) can supply the alerting service with the position of the nurse. Whenever the nurse moves from one unit to another, the nurse will be supplied with the appropriate treatment guidelines. R3 A patient would like to be sent educational material whenever his or her condition has changed, e.g. when starting on a new medication. This would be defined in a profile as: 'Send educational material when patient's condition has changed.' For this kind of profile, the alerting service would filter the EHR and, whenever an entry describing a relevant change has been found, the patient would receive appropriate educational material in a notification from the alerting service. All three requirements call for a system that combines an alerting service with a health- care digital library feed. Each of these requirements focuses on different aspects of this system. Due to the lack of space we will enact and focus here on requirement R1, the information need of clinicians, i.e. doctors, nurses and allied health professionals (AHPs). Returning now to the earlier user studies, one novel challenge in providing alerting services in the health area is the variability of language between professional and patient. Differences may also occur between disciplines. Though humans cope well with such barriers, computers do not. Thus, any alerting service will have to be open to supporting matching between technical and 'common' terms, or even between natural languages (cf. R1, R2). This language barrier reflects a deeper difference in knowledge. Clinicians not only have a wide and comprehensive technical vocabulary but also possess a systematic under- standing of how the human body behaves and reacts. Useful literature for them will leverage these strengths in making diagnostic decisions, and directing the course of treatment. For a patient, though, these tools are absent, and material will often be of a practical, directive form. Furthermore, variability between patients will be large from proactive individuals who seek to understand their conditions fully to those who 'only want it fixed'. A comprehensive system will thus not only perform textual matches, but also consider the form and purpose of the material needed to respond to the current environment be it differing clinical and/or management practices and priorities (cf. R3), the temporal terms of disease progression, or the time of day. Finally, some material such as electronic health records needs appropriate processing to ensure that the current context is properly captured. Together, these factors create a demand for a complex filtering architecture. We will now introduce our current architecture and illustrate how it matches these demands. HDLalert architecture To meet the requirements discussed in the previous section, we have designed a novel healthcare DL alerting architecture, HDLalert. The prototype of this architecture has been developed around the established Greenstone digital library and its alerting service. These two components have been joined through additional alerting-related components. In the next section, we describe a usage scenario and demonstrate in particular how the system matches clinician-based requirement R1 as described above. Hinze et al. HDLalert 127 The overall HDLalert architecture is shown in Figure 2. Different compositions of systems can be created through connecting the components of the system in varying ways. In the figure, we illustrate the creation of a supplemented alerting service, with each alert received being supplemented with links to relevant material. In a first step, clinicians (and/or patients, information intermediaries) define their interests in profiles; a thesaurus replaces or enriches the original term with a translation (see our previous work in [14]). Incoming alerts or source documents have keyphrases extracted through the extractor module. These data are then passed into the filter system with the user's profile and context for the appropriate supplementary documents to be selected. Matched documents are dispatched to the user with the original alert through the final notification module. We will now describe each of the four component elements in more detail. Profile definition and enrichment Users of the system first have to specify their interests. Here, we have to note again the problem of differing languages used by different users clinicians and patients, for example. In addition, one would not expect the medical terms to appear as such in news clippings. For this to be addressed, we use a thesaurus that facilitates the translation of key terms in one form of language into the equivalent terms in another. In Greenstone, we have long used multilingual thesauri for supporting cross-language retrieval. In HDLalert, we utilize this same technology within the same human language. For example, clinical text highlighting the presence of 'glucose' will retrieve patient-centred documents about 'blood sugar'. In addition, we are able to identify concepts that belong to a common group or other hierarchical relationships using an ontology for the representation of Health Informatics Journal 12 (2) 128 Figure 2 An architecture for health DL alerting medical knowledge (see our previous work on profile extensions [11]). Our ontology to describe terms and concepts uses XML and RDF/S [31], as typically employed in the context of semantic web. The expressiveness of healthcare thesauri and the particular potency of knowledge representation for healthcare and medical applications are discussed in later. Press alerts and keyphrase extraction These user profiles now have to be matched with the incoming press alerts. In addition to this classical task of an alerting service (filtering of documents and user profiles), the scenarios introduced earlier in this paper identified the requirement for matching the content of one document against a set of other documents. For example, in the press alert scenario, one wishes to match important terms or phrases from the press text against supplementary documents in a supporting digital library. However, both tasks of filtering and supplementary document matching require a more selective match than by simply comparing all the text in the press alert document with the text in the profiles or the additional documents. The key features of the press document need to be identified and extracted, and then those matched against the profiles and the expert corpus. In our HDLalert architecture, this knowledge extraction process is performed by the extractor component. The extractor component may be realized through different implementations. There are many circumstances where specific extractors would be required. For example, press alerts are usually distributed in plain text form or with only simple markup, whilst EHRs may be stored in complex database or XML formats. For accurate retrieval, the input content needs to be correctly processed, to avoid false positives amongst other problems. One such false positive could be matching a warning about medication interactions for a drug no longer being administered to the patient. Where extraction relies on identifying features of the document using machine learning or other 'intelligent' tools, error rates are frequently high [32]. In our current implemen- tation, we therefore take a much more conservative approach: a keyphrase list of medical terms is used that provides known and defined phrases which can be expected to arise in the press alert texts. This technique has already proved effective in the case of UN collec- tions of social and economic development literature using the Agrovoc thesaurus [32]. Filtering and supplementing Once the extraction has been achieved, the press keywords are first passed to the filter component. There, the press keywords are compared to an index of enriched user profiles. The enrichments may use a cost function that is used in the filter process such that partial matches or approximate matches are allowed. Thus, the more similar a keyword is to the original profile term, the better the match. We allow for approximate matching (for details of our approximate matching approach, see [33]). In a second step, the press documents that match at least one user profile are then supplemented with further information. For these matches against reference documents, we use an established matching system of the digital library. It uses the principle of query-by-example, requesting supplementary documents that refer to similar content to the press document. Hinze et al. HDLalert 129 In [14, 34] we demonstrated that a digital library and an alerting service can use a common syntax. Therefore, we can abstract above both static collections and dynamic streams of content. The rich filtering languages introduced in [15, 33, 34] support a wide range of functional requirements. Our architecture presented here adds an additional element to the filtering system: it also adjusts the output of the filtering process depending on the user's current context. Again, this element is modular and can be realized in different ways; it feeds rules and data to the filtering system to be used in the filtering process. For example, in the case of a DL that delivered different information depending on the physical location of the user, the context module would supply positioning information to ensure that any material selected was appropriate for a nurse's current ward. Dispatching Finally, the information is forwarded to the user through the notification module. Again, this can be implemented in different ways: in some cases this may simply send notifica- tions by e-mail, but in others it may choose from a variety of different methods depending on the criteria sent forward from the filtering engine, e.g. the patient's ability to see or hear. There are a number of design decisions surrounding the dispatch of information. One is the issue of delivery mechanism: here, technologies such as RSS can be used, and delivery can be through e-mail and/or a website. A second issue is the form of notifi- cation. Large, extensive text is probably undesirable, so the primary notification will be in a brief format, with links to more extensive information. Unfortunately, space does not permit us to discuss these issues in full here. It is important to note that the proposed alerting service only provides information. It does not, of itself, provide decision support. Our experience is that such systems are poorly received by clinicians, and in any case are usually irrelevant to patients. The architecture proposed here may also be used to fulfil patient needs: online patient communities form an important part of the information repertoire of patients [35]. One additional digital resource for patients could be a reference to known online communi- ties, with further annotation from professional information intermediaries (medical librarians) to verify the appropriateness and quality of the information. HDLalert clinician usage scenario To illustrate our architecture, we sketch its operation for enriched press alerts for clinicians (i.e. doctors, nurses, AHPs). Refer again to Figure 2 to see some of the specific items for the example indicated in italics outside the step boxes. The system works in four steps: 1 Clinicians define their interest in profiles. 2 Profiles are enriched with background knowledge. 3 Press clippings are preprocessed. 4 Profiles and press alerts are matched and the result is supplemented with relevant additional information. Health Informatics Journal 12 (2) 130 Profile definition Clinicians describe their information needs in profiles. This can be done by defining terms directly or selecting keywords from a list. Clinicians can also select predefined profiles that are typical for certain specialization areas. Using an advanced module for profile defi- nition, clinicians may define synonyms and further terms as well as a cost function for personalized profile enrichment. Profile enrichment The clinicians' profiles are supplemented with alternative terms from the thesaurus as required. This currently occurs automatically. However, as in the case of [36], this mapping could be done with manual assistance from a librarian/expert. We are also experimenting using topic maps [37] or ontologies [38]. An ontology (as used in the context of the semantic web) is an extension of a thesaurus with further concepts and options. Relations between terms can be homonyms and synonyms (as in a thesaurus) but also hierarchies and subsets (e.g. a particular medical condition being defined as a subgroup or side-effect of a more general disease). As pointed out by several parties [39], there is currently no universally accepted medical ontology that may be used in all healthcare applications. However, several standards organizations aim to develop uniform specifications for managing health care infor- mation, such as the American Society for Testing and Materials (ASTM), the Technical Committee 251 of the European Committee for Standardization (CEN/TC251), the Health Informatics Group of the International Organization for Standardization (ISO, TC 215) and Health Level 7 (HL7). We have to note that it is not enough to use medical terms such as specified in the Unified Medical Language System (UMLS). Specific terms from the health- care domain need to be included as well as common terms for medical terminology. Consequently, we need to address the challenge of using several ontologies (or language systems/thesauri) in cooperation. Press alert keyphrase extraction New press alerts are received from news databases, and passed into the system. At present, HDLalert receives news alerts from the British Broadcasting Corporation (BBC) and the Nexis news clippings service. In each case, the press content is supplied in plain text, wrapped in a simple XML casing. Each press clipping is then processed by a keyphrase extraction system to identify clinical terms (in common or technical form). The terms will be used later, during the filtering process, to match documents. Filtering and supplementing The system filters the terms according to the clinicians' profiles. If a match is found, the system then searches a number of medical DLs (e.g. MedLine) to discover material relevant to the press article. Additional context is also used to improve the selectivity of the material (e.g. for the clinician's domain of expertise). Finally, the press clipping is sent to the user, accompanied by references to relevant journal articles selected from MedLine. Hinze et al. HDLalert 131 Conclusion In this paper, we identified the need for alerts in health DLs. Though some existing systems provide coarse-grained alerting, this fails to meet the requirements of clinicians and cannot support the needs of patients. Furthermore, the user requirements for health alerts are diverse: different types of information are required to support different tasks. Alerts themselves could be simple messages or more complex packages detailing the new infor- mation and supportive background material. Therefore, we argued that a new system is required that provides a richer and more fine-grained service than exists at present. We introduced a new alerting architecture for health DLs that is built upon innovative but established DL tools. These reliable elements can be combined in different ways through the same architecture to achieve the varying alert forms that our users required. We have introduced the HDLalert architecture, and briefly illustrated its application to an enriched alerting service for clinicians. Our novel architecture differs from existing health alerting services in supporting fine-grained matching using the proven alerting technologies of the Greenstone alerting service (GSDL-AS) [14, 33], which can also be implemented over a variety of DL systems. Furthermore, it extends the advantages of GSDL-AS by introducing supplementary material to alerts and also facilitating selection across different reader groups through the use of a thesaurus. Returning to the user requirements discussed earlier, our system responds to the growing influence of press information on patients' information demands, and their interest in educational material relevant to their conditions. HDLalert can supplement incoming press notices with further, targeted information from other sources. Further- more, the detail of the current context can influence this process through the use of reader profiles (for clinicians and patients alike) and context data from sensors, if relevant. As pointed out earlier, our motivation for the development of HDLalert is based on alert-relevant findings from several international user studies. The HDLalert architecture embraces the variations in requirements and contexts of different user groups and local backgrounds by using cross-language thesauri and personalizable ontologies. In addition, our modular approach ideally allows for adaptation of the service as needed. The implemented system provides a novel means of raising awareness of both clinicians and patients through targeted alerts for both groups. These alerts are enriched by supple- menting the original news item with related material in a form and language relevant to the reader. This system is built upon extensive study of users in the medical arena. To date, this study has unearthed the significance of context and change, and through this explained the lack of uptake of digital resources in many areas. 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HDLalert 135 Doris Jung Department of Computer Science, University of Waikato PB 3105, Hamilton, New Zealand E-mail: d.jung@cs.waikato.ac.nz Anne Adams UCL Interaction Centre (UCLIC), Remax House 3132 Alfred Place, London WC1E 7DP, UK E-mail: a.adams@cs.ucl.ac.uk</meta-value></custom-meta></custom-meta-wrap></article-meta></front><back><ref-list><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Sackett D</surname></name> , <name name-style="western"><surname>Rosenberg W</surname></name> , <name name-style="western"><surname>Gray M</surname></name> , <name name-style="western"><surname>Haynes B</surname></name> , <name name-style="western"><surname>Richardson S</surname></name> . <article-title>Evidence based medicine: what it is and what it isn’t</article-title> . <source>British Medical Journal</source><year>1996</year>; <volume>312</volume>; <fpage>71</fpage>–<lpage>72</lpage> .</citation></ref><ref><citation citation-type="confproc" xlink:type="simple"><name name-style="western"><surname>Reddy M</surname></name> , <name name-style="western"><surname>Dourish P</surname></name> . <article-title>A finger on the pulse: temporal rhythms and information seeking in medical work</article-title> . 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However, existing ‘news’ or ‘alert’ services provide relatively limited means for selecting which information to receive. The result is that clinicians and patients often receive information that is inappropriate, irrelevant or simply too much. In this paper, we detail alert-relevant findings from several international user studies (e.g. UK, Germany and New Zealand) incorporating both clinical staff (across several hospitals) and patients’ perceptions. These findings demonstrate the importance of context, in terms of both the user's task and immediate environment. We introduce a novel alerting architecture that can provide a finely tailored stream of alerts to the user, and provides further support to assist the interpretation of received material.</abstract><subject><genre>keywords</genre><topic>alerting</topic><topic>design</topic><topic>digital library</topic><topic>healthcare</topic><topic>human factors</topic><topic>user studies</topic></subject><relatedItem type="host"><titleInfo><title>Health Informatics Journal</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">1460-4582</identifier><identifier type="eISSN">1741-2811</identifier><identifier type="PublisherID">JHI</identifier><identifier type="PublisherID-hwp">spjhi</identifier><part><date>2006</date><detail type="volume"><caption>vol.</caption><number>12</number></detail><detail type="issue"><caption>no.</caption><number>2</number></detail><extent unit="pages"><start>121</start><end>135</end></extent></part></relatedItem><identifier type="istex">CC47C706F64773412F12597A5968C77BAB04229E</identifier><identifier type="DOI">10.1177/1460458206063808</identifier><identifier type="ArticleID">10.1177_1460458206063808</identifier><recordInfo><recordContentSource>SAGE</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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