Population-oriented ICT-supported preventive care: Coping with local circumstances|
|- candidate number||3075|
|- NTR Number||NTR1227|
|- ISRCTN||ISRCTN wordt niet meer aangevraagd|
|- Date ISRCTN created|
|- date ISRCTN requested|
|- Date Registered NTR||17-mrt-2008|
|- Secondary IDs||6100.0011 ZONMW|
|- Public Title||Population-oriented ICT-supported preventive care: Coping with local circumstances|
|- Scientific Title||Population-oriented ICT-supported preventive care: Coping with local circumstances in primary health care|
|- hypothesis||Computerized decision support (CDSS) for tailoring prevention to the local circumstances using the guidelines of the Dutch college of general practitioners has impact on preventive activities in the primary care setting|
|- Healt Condition(s) or Problem(s) studied||Primary care, Prevention, Computerized decision support, Electronic health record, Information and Communication Technology (ICT)|
|- Inclusion criteria||1. Primary care practices in the Netherlands that use the HetHIS (Microbias) EHR to record patient encounters|
|- Exclusion criteria||1. Practices that have been working with the HetHIS EHR for less than a year preceding enrollment |
2. Practices that use paper to record patient interactions
|- mec approval received||yes|
|- multicenter trial||no|
|- Type||2 or more arms, randomized|
|- planned startdate ||1-apr-2008|
|- planned closingdate||31-mrt-2009|
|- Target number of participants||50|
|- Interventions||Software module (SUNRISE) in the group randomized to recieve intervention that alerts users to the preventitive activities needed in their population based on the recommendations of the Dutch college of general practitioners. This module will be installed at the GP practices randomized to recieve the intervention for 360 days or until GP stops using the HEThis GP information system. The preventative activities can be tailored to the local practice profile and practice preference. |
|- Primary outcome||The change in preventive activities performed by general practitioners in the participating practices during the study compared to the year preceding the study. That is the number of preventive activities that should be performed against the number of preventive activities that were performed as determined by the SUNRISE system. This is logged in the EHR during the study.|
|- Secondary outcome||The change in DISEASE SPECIFIC preventive by general practitioners in the participating practices during the study compared to the year preceding the study. That is the number of preventive activities that should be performed against the number of preventive activities that were performed as determined by the SUNRISE system. This is logged in the EHR during the study.|
|- Timepoints||- 2007 - contruction software |
- up to 2008/03 - validation
- up to 2008/04 - recruitment
- 2008/04 - 2009/03 - trial
- 2009 Analysis
|- Trial web site||N/A|
|- CONTACT FOR PUBLIC QUERIES||Prof. Dr. Johan Lei, van der |
|- CONTACT for SCIENTIFIC QUERIES||Prof. Dr. Johan Lei, van der |
|- Sponsor/Initiator ||Erasmus Medical Center, Department of Medical Informatics|
(Source(s) of Monetary or Material Support)
|ZON-MW, The Netherlands Organization for Health Research and Development|
|- Publications||1. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based decision support systems on
physician performance and patient outcomes: A systematic review. Journal of the American Medical
Association 1998;280(15):1339-1346. |
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3. Grol RPTM. Successes and failures in the implementation of evidence-based guidelines for clinical
practice. Medical Care 2001;39:1146-54.
4. Knottnerus JA. The role of electronic patient records in the development of generla practice in the
Netherlands. Methods of Information in Medicine 1999;38:350-355.
5. Institute of Medicine. Crossing the quality chasm: A new health system for the 21st century.
Washington DC: National Academy Press; 2001.
6. Bates D, Gawanda A. Improving safety with information technology. New England Journal of Medicine
7. Van Wijk MAM, Bohnen AM, Van der Lei J. Analysis of the practice guidelines of the Dutch College of
General Practitioners with respect to the use of blood tests. Journal of the American Medical Informatics
8. Van Wijk MAM, Mosseveld BMT, Van der Lei J. The design of a decision-support system for test
ordering in general practice: Choices and decisions to make. Methods of Information in Medicine
9. Van Wijk MAM, Van der Lei J, Mosseveld BMT, Bohnen AM, Van Bemmel JH. Assessment of
decision support for blood test ordering in primary care: A randomized trial. Annals of Internal Medicine
10. Van Wijk MAM, Van der Lei J, Mosseveld BMT, Bohnen AM, van Bemel JH. Compliance of general
practitioners with a guideline-based decision support system for ordering blood tests. Clinical Chemistry
11. Kuilboer MM, van Wijk MA, Mosseveld M, van der Does E, Ponsioen BP, de Jongste JC, et al.
Feasibility of AsthmaCritic, a decision-support system for asthma and COPD which generates
patient-specific feedback on routinely recorded data in general practice. Family Practice
12. Kuilboer MM, van Wijk MA, Mosseveld M, van der Lei J. AsthmaCritic: issues in designing a
noninquisitive critiquing system for daily practice. Journal of the American Medical Informatics
13. Van Bemmel JH, Musen MA, editors. Handbook of Medical Informatics. Heidelberg, Germany:
Springer Verlag; 1997.
14. Kuilboer MM. AsthmaCritic: a critiquing system and Asthma and COPD. PhD Thesis. Rotterdam: Erasmus University; 2003.
15. Vlug AE, Van der Lei J, Mosseveld BMT, Van Wijk MAM, Van der Linden PD, Sturkenboom MCJM,
et al. Postmarketing surveillance based on electronic patient records: The IPCI project. Methods of
Information in Medicine 1999;38:339-344.
16. Eland IA, Sturkenboom MC, van der Lei J, Wilson JH, Stricker BH. Incidence of acute pancreatitis.
Scandinavian Journal of Gastroenterology 2002;37(1):124.
17. GW TJ, Eland IA, Sturkenboom MC, van den Anker JN, Stricker BH. Unlicensed and off label
prescription of drugs to children: population based cohort study. British Medical Journal
18. Verboom P, Hakkaart-Van L, Sturkenboom M, De Zeeuw R, Menke H, Rutten F. The cost of atopic
dermatitis in the Netherlands: an international comparison. British Journal of Dermatology
19. Verhamme KM, Dieleman JP, Bleumink GS, Bosch JL, Stricker BH, Sturkenboom MC. Treatment
strategies, patterns of drug use and treatment discontinuation in men with LUTS suggestive of benign
prostatic hyperplasia: the Triumph project. European Journal of Urology 2003;44(5):539-45.
20. Voordouw BC, van der Linden PD, Simonian S, van der Lei J, Sturkenboom MC, Stricker BH.
Influenza vaccination in community-dwelling elderly: impact on mortality and influenza-associated
morbidity. Archives of Internal Medicine 2003;163(9):1089-94.
21. Van der Lei J, Duisterhout JS, Westerhof HP, Van der Does E, Cromme PVM, Boon WM, et al. The
introduction of computer-based patient records in the Netherlands. Annals of Internal Medicine
22. Van der Lei J, Musen MA, Van der Does E, Man in 't Veld AJ, Van Bemmel JH. Comparison of
computer-aided and human review of general practitioners' management of hypertension. The Lancet
|- Brief summary||Prevention is usually positioned as a separate, disease-specific activity (prevention of diabetes mellitus,
prevention of cardiac diseases, etc.). In daily practice, workers in the health care system and often even
the target groups themselves have to integrate (or select between) these separate preventive activities
and merge them with other activities (e.g., curative care).
Information and Communication Technology (ICT) is increasingly used to support preventive tasks. The
intervention strategies developed for this purpose, however, are also characterized by a fragmented,
disease oriented approach (one software module for cardiovascular screening, another module for
diabetes, etc) -- even though the risk factors for individual diseases may overlap.
Ideally, ICT aids an individual practitioner to deliver an effective, integrated set of preventive activities
tailored to the special characteristics of the population served by that individual practitioner. As
illustrated by the separate disease-specific modules, current intervention strategies that use ICT to
support preventive tasks are based on the prevention in the setting of an individual disease; these
interventions do not address the issue of providing, in an environment characterized by limited
resources, the optimal set of preventive activities for an individual population over all diseases.
In this study we will investigate the impact of an ICT-based intervention that allows the practitioner to
tailor preventive activities to a local population and to local procedures. The intervention takes as
starting point the generic activity prevention rather than prevention based on an individual disease.
Rather than support preventive care in the context of an individual disease, we propose an intervention
that supports selecting and tailoring prevention over multiple diseases to the characteristics of the local
population in the light of the local circumstances.
In this study we will conduct a randomized trial to study the feasibility of the intervention. |
|- Main changes (audit trail)|
|- RECORD||18-feb-2008 - 17-mrt-2008|
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