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Introduction
Heart failure (HF) is a major disease with increasing
prevalence and incidence. [1] It is a progressive
disease with a poor prognosis that causes substantial
burden to patients, their carers and families and to
the health system, generally. [2-3]. HF care is
provided in many settings including hospitals,
residential aged care facilities and the community.
More recently, there has been growing interest in the
intersect of heart failure and palliative care. [4-5] For
HF patients, quality of life and advance care planning
are important issues.
Searching for literature can be difficult and time
consuming for clinicians and yet they rely on access
to inform their clinical practice. [6] Filters, or
experimentally tested search strategies objectively
assessed for their retrieval effectiveness, are an
important mechanism to support health professionals
searching for clinical information.
Results
Four HF guidelines were selected by the Clinical
Advisory Group for the study. All references were
reviewed to determine whether they were relevant to
HF and could be retrieved as HF. This led to a Gold
Standard Set with 876 articles. (Figure 2)
Frequency analysis of MeSH terms and text word
analysis of titles and abstracts in the Term
Development Set (TDS) identified possible search
terms for use in filter development. (Table 1)
Other frequently occurring
content terms were identified
to inform the development
of topic searches.
The filter development work
is nearing completion. The
relative recall rates for the
identified MeSH and text
words are being determined.
The performance of the
best performing search will
be then be tested in the
Filter Test Set (FTS). This
will then form the HF filter.
Discussion
The frequency analysis work has demonstrated some
of the searching complexities. ‘Heart failure’ as a
MeSH term did not retrieve all the articles from HF
guidelines that had been checked for relevance and
retrieval. Some articles that included ‘heart failure’
as a textword in the title or abstract were not
indexed with ‘heart failure’ as a MeSH term.
Topics that are frequently occurring in the HF articles
will be developed into expert searches to run in
combination with the HF filter. Topic searches will
also be developed for palliative care issues such as
advance care planning or bereavement within the HF
context. This could support the use of palliative care
approaches by clinical groups caring for HF patients.
Following a PubMed equivalence study a public online
PubMed HF Filter will be made available through the
web.
Implementation
Facilitating access to relevant HF literature and
evidence would be an important step in enhancing
clinicians’ knowledge.
This research work will create an entry point for
health professionals in palliative care and in
cardiology to support searching for HF literature. A
public web page will provide access to the HF filter
plus the HF filter combined with a set of clinically
important topics such as dyspnoea, decompensated,
advance care planning. By clicking on a hyperlink
using the PubMed version of the HF filter, a real time
automated search will be initiated.
A similar entry point has been developed for
palliative care literature within the CareSearch
website. (Figure 3) This has 60 searches that broker
access to the literature within PubMed.
The heart failure filter and associated content pages
will be available within the CareSearch website at
www.caressearch.com.au from September 2010.
Aim
The initial aim of this study was to develop an
advanced heart failure filter. Preliminary analysis of
literature and feedback from a Clinical Advisory
Group indicated that given mortality and morbidity
rates and an uncertain trajectory, palliative care
issues should be considered for all HF patients.
The aims were revised as follows:
1. To develop a subject search filter for Heart Failure
using included studies from multiple evidence based
HF guidelines as a gold standard.
2. To experimentally test this HF filter using relative
recall as a measure of its performance.
Conclusion
Search filters can facilitate access to literature and
evidence and reduce the burden on clinicians with
respect to searching. A HF filter could support patient
care and clinical decision-making.
For further information:
Jennifer.Tieman@flinders.edu.au
References
1. Mosterd A, Hoes AW. Clinical epidemiology of heart failure. Heart.
2007 93(9):1137-46.
2. Aranda JM Jr, Johnson JW, Conti JB. Current trends in heart failure
readmission rates: analysis of Medicare data. Clin Cardiol. 2009
32(1):47-52.
3. Cheng JW, Nayar M. A review of heart failure management in the
elderly population. Am J Geriatr Pharmacother. 2009 7(5):233-49.
4. Goodlin SJ. Palliative care in congestive heart failure. J Am Coll
Cardiol. 2009 54(5):386-96.
5. Hupcey JE, Penrod J, Fenstermacher K. A model of palliative care
for heart failure. Am J Hosp Palliat Care. 2009 26(5):399-404
6. Davies K The information-seeking behaviour of doctors: a review of
the evidence Health Info & Libr J. 24(2):78 - 94
Funding: This work is part of the CareSearch project funded by
the Australian Government Department of Health and Ageing.
Acknowledgements: Ms Raechel Damarell, Research Officer,
has been instrumental in developing this research work.
Figure 2: Development of Gold Standard Set
Between chronic and advanced: Developing a heart failure search filter
Tieman JJ1
, Davidson P2
, Sladek RM3
1 Palliative and Supportive Services, Flinders University; 2 Professor, Cardiovascular and Chronic Care, Curtin
University; 3 Flinders University, Flinders Medical Centre, Bedford Park
Method
A Clinical Advisory Group was established. A Gold
Standard set of articles was derived from the articles
of four HF guidelines. This set was then randomly
divided into three subsets for - search term
identification, filter development and filter testing.
Performance of individual terms and the subject filter
was assessed using relative recall, i.e., the number
of items from the Gold Standard set that were
retrieved. All development work was in Ovid Medline.
References from 4 HF guidelines
Review by researcher for HF in title/
abstract (n=1081)
“HF” in title/
abstract (n=827)
Review by
clinician (n=254)
Relevant to
HF (n=38)
Uncertain
(n=35)
Not relevant
to HF
(n=181)
Reviewed by
Chief Investigator
(Clinical) (n=35)
Relevant to HF
(n=11)
Not relevant to
HF(n=24)
Gold Standard
Set (n=876)
Figure 3: Example of entry page allowing automated
access
Project Initiation
Guideline
Selection
Search Term
Identification
Gold Standard Set
Development
Filter
Development
Filter Test
MeSH thesaurus
review
Clinical Advisory
Group Input
Frequency
Analysis (TDS)
TDS: Term
Development Set
FDS: Filter
Development Set
FTS: Filter Test
Set
Search Term
Ranked List
Filter Translation
(PubMed)
Filter
Implementation
Figure 1: Schematic Representation of Filter Development
Table 1: Frequencies of MeSH terms and
Textwords (TDS)
Mesh No. %
Heart Failure 62 70%
Ventricular Dysfunction, Left 14 16%
Natriuretic Peptide, Brain 10 11%
Heart rate 10 11%
Haemodynamics 10 11%
Prognosis 10 11%
Quality of Life 10 11%
Severity of Illness 10 11%
Survival Analysis 10 11%
Textword Analysis No %
Heart Failure 77 88%
Congestive Heart Failure 36 41%
New York Heart Association 24 27%
Left Ventricular Ejection
Fraction 23 26%
CHF 20 23%
Chronic heart failure 17 19%
Cardiomyopathy 15 17%

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between chronic and advanced: developing a heart failure search filter

  • 1. Introduction Heart failure (HF) is a major disease with increasing prevalence and incidence. [1] It is a progressive disease with a poor prognosis that causes substantial burden to patients, their carers and families and to the health system, generally. [2-3]. HF care is provided in many settings including hospitals, residential aged care facilities and the community. More recently, there has been growing interest in the intersect of heart failure and palliative care. [4-5] For HF patients, quality of life and advance care planning are important issues. Searching for literature can be difficult and time consuming for clinicians and yet they rely on access to inform their clinical practice. [6] Filters, or experimentally tested search strategies objectively assessed for their retrieval effectiveness, are an important mechanism to support health professionals searching for clinical information. Results Four HF guidelines were selected by the Clinical Advisory Group for the study. All references were reviewed to determine whether they were relevant to HF and could be retrieved as HF. This led to a Gold Standard Set with 876 articles. (Figure 2) Frequency analysis of MeSH terms and text word analysis of titles and abstracts in the Term Development Set (TDS) identified possible search terms for use in filter development. (Table 1) Other frequently occurring content terms were identified to inform the development of topic searches. The filter development work is nearing completion. The relative recall rates for the identified MeSH and text words are being determined. The performance of the best performing search will be then be tested in the Filter Test Set (FTS). This will then form the HF filter. Discussion The frequency analysis work has demonstrated some of the searching complexities. ‘Heart failure’ as a MeSH term did not retrieve all the articles from HF guidelines that had been checked for relevance and retrieval. Some articles that included ‘heart failure’ as a textword in the title or abstract were not indexed with ‘heart failure’ as a MeSH term. Topics that are frequently occurring in the HF articles will be developed into expert searches to run in combination with the HF filter. Topic searches will also be developed for palliative care issues such as advance care planning or bereavement within the HF context. This could support the use of palliative care approaches by clinical groups caring for HF patients. Following a PubMed equivalence study a public online PubMed HF Filter will be made available through the web. Implementation Facilitating access to relevant HF literature and evidence would be an important step in enhancing clinicians’ knowledge. This research work will create an entry point for health professionals in palliative care and in cardiology to support searching for HF literature. A public web page will provide access to the HF filter plus the HF filter combined with a set of clinically important topics such as dyspnoea, decompensated, advance care planning. By clicking on a hyperlink using the PubMed version of the HF filter, a real time automated search will be initiated. A similar entry point has been developed for palliative care literature within the CareSearch website. (Figure 3) This has 60 searches that broker access to the literature within PubMed. The heart failure filter and associated content pages will be available within the CareSearch website at www.caressearch.com.au from September 2010. Aim The initial aim of this study was to develop an advanced heart failure filter. Preliminary analysis of literature and feedback from a Clinical Advisory Group indicated that given mortality and morbidity rates and an uncertain trajectory, palliative care issues should be considered for all HF patients. The aims were revised as follows: 1. To develop a subject search filter for Heart Failure using included studies from multiple evidence based HF guidelines as a gold standard. 2. To experimentally test this HF filter using relative recall as a measure of its performance. Conclusion Search filters can facilitate access to literature and evidence and reduce the burden on clinicians with respect to searching. A HF filter could support patient care and clinical decision-making. For further information: Jennifer.Tieman@flinders.edu.au References 1. Mosterd A, Hoes AW. Clinical epidemiology of heart failure. Heart. 2007 93(9):1137-46. 2. Aranda JM Jr, Johnson JW, Conti JB. Current trends in heart failure readmission rates: analysis of Medicare data. Clin Cardiol. 2009 32(1):47-52. 3. Cheng JW, Nayar M. A review of heart failure management in the elderly population. Am J Geriatr Pharmacother. 2009 7(5):233-49. 4. Goodlin SJ. Palliative care in congestive heart failure. J Am Coll Cardiol. 2009 54(5):386-96. 5. Hupcey JE, Penrod J, Fenstermacher K. A model of palliative care for heart failure. Am J Hosp Palliat Care. 2009 26(5):399-404 6. Davies K The information-seeking behaviour of doctors: a review of the evidence Health Info & Libr J. 24(2):78 - 94 Funding: This work is part of the CareSearch project funded by the Australian Government Department of Health and Ageing. Acknowledgements: Ms Raechel Damarell, Research Officer, has been instrumental in developing this research work. Figure 2: Development of Gold Standard Set Between chronic and advanced: Developing a heart failure search filter Tieman JJ1 , Davidson P2 , Sladek RM3 1 Palliative and Supportive Services, Flinders University; 2 Professor, Cardiovascular and Chronic Care, Curtin University; 3 Flinders University, Flinders Medical Centre, Bedford Park Method A Clinical Advisory Group was established. A Gold Standard set of articles was derived from the articles of four HF guidelines. This set was then randomly divided into three subsets for - search term identification, filter development and filter testing. Performance of individual terms and the subject filter was assessed using relative recall, i.e., the number of items from the Gold Standard set that were retrieved. All development work was in Ovid Medline. References from 4 HF guidelines Review by researcher for HF in title/ abstract (n=1081) “HF” in title/ abstract (n=827) Review by clinician (n=254) Relevant to HF (n=38) Uncertain (n=35) Not relevant to HF (n=181) Reviewed by Chief Investigator (Clinical) (n=35) Relevant to HF (n=11) Not relevant to HF(n=24) Gold Standard Set (n=876) Figure 3: Example of entry page allowing automated access Project Initiation Guideline Selection Search Term Identification Gold Standard Set Development Filter Development Filter Test MeSH thesaurus review Clinical Advisory Group Input Frequency Analysis (TDS) TDS: Term Development Set FDS: Filter Development Set FTS: Filter Test Set Search Term Ranked List Filter Translation (PubMed) Filter Implementation Figure 1: Schematic Representation of Filter Development Table 1: Frequencies of MeSH terms and Textwords (TDS) Mesh No. % Heart Failure 62 70% Ventricular Dysfunction, Left 14 16% Natriuretic Peptide, Brain 10 11% Heart rate 10 11% Haemodynamics 10 11% Prognosis 10 11% Quality of Life 10 11% Severity of Illness 10 11% Survival Analysis 10 11% Textword Analysis No % Heart Failure 77 88% Congestive Heart Failure 36 41% New York Heart Association 24 27% Left Ventricular Ejection Fraction 23 26% CHF 20 23% Chronic heart failure 17 19% Cardiomyopathy 15 17%