Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial
Open accessAbstract
OBJECTIVE: To evaluate the use of a computerised support system for decision making for implementing evidence based clinical guidelines for the management of asthma and angina in adults in primary care. DESIGN: A before and after pragmatic cluster randomised controlled trial utilising a two by two incomplete block design. SETTING: 60 general practices in north east England. PARTICIPANTS: General practitioners and practice nurses in the study practices and their patients aged 18 or over with angina or asthma. MAIN OUTCOME MEASURES: Adherence to the guidelines, based on review of case notes and patient reported generic and condition specific outcome measures. RESULTS: The computerised decision support system had no significant effect on consultation rates, process of care measures (including prescribing), or any patient reported outcomes for either condition. Levels of use of the software were low. CONCLUSIONS: No effect was found of computerised evidence based guidelines on the management of asthma or angina in adults in primary care. This was probably due to low levels of use of the software, despite the system being optimised as far as was technically possible. Even if the technical problems of producing a system that fully supports the management of chronic disease were solved, there remains the challenge of integrating the systems into clinical encounters where busy practitioners manage patients with complex, multiple conditions.
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CDSS tools are not always used when they are available.
“Importantly there is clear evidence that CDSS tools are not always used when available, 15 with up to 96% of alerts being overridden or ignored by physicians.[16][17][18][19]”
From Computerized clinical decision support for prescribing: provision does not guarantee uptake (2010) · cites this paper as [15]
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- *Effect sizes; estimates of ratio of mean number of consultations for participants in practices that received computerised decision support system to mean number of consultations for participants in control practices based on Poisson regression model. †Patients who consulted after intervention and had not had variable recorded anywhere in their clinical record during period before intervention. Primary care page 4 of 7 BMJ VOLUME 325 26 OCTOBER 2002 bmj.com on 17 July 2023 by guest. Protected by copyright. http://www.bmj.com/ BMJ: first published as 10.1136/bmj.325.7370.941 on 26 October 2002. Downloaded from All patients 516 (43); 511 (43) 492 (42); 517 (45) 0.94 (0.67 to 1.33) Patients who consulted 515 (45); 510 (45) 491 (45); 516 (47) 0.94 (0.66 to 1.34) Compliance checked: All patients 426 (36); 442 (37) 446 (38); 471 (41) 0.82 (0.58 to 1.15) Patients who consulted 425 (37); 441 (39) 445 (40); 470 (43) 0.82 (0.58 to 1.16) Inhaler technique assessed: All patients 203 (17); 224 (19) 234 (20); 262 (23) 0.8 (0.5 to 1.28) Patients who consulted 203 (18); 224 (20) 233 (21); 262 (24) 0.81 (0.5 to 1.28) Asthma education, action plan, or both: All patients 79 (7); 60 (5) 108 (9); 78 (7) 0.84 (0.4 to 1.74) Patients who consulted 79 (7); 60 (5) 108 (10); 78 (7) 0.81 (0.39 to 1.67) Smoking status known: All patients 285 (24); 370 (32) 305 (26); 367 (32) 0.97 (0.65 to 1.45) Patients who consulted 285 (25); 369 (33) 303 (28); 367 (33) 0.98 (0.66 to 1.46) Smoking cessation advice or nicotine replacement therapy: All patients 57 (5); 81 (7) 68 (6); 103 (9) 0.75 (0.45 to 1.26) Patients who consulted 57 (5); 81 (8) 68 (6); 103 (9) 0.76 (0.46 to 1.27)
- *Guideline specifically recommended not using these combinations. Table 5 Drugs prescribed for patients with asthma before and after introduction of computerised decision support system. Values are numbers (percentages) unless stated otherwise Computerised system (n=1391) Controls (n=1385) Odds ratio (95% CI) Short acting 2 agonists 1138 (82); 1112 (80) 1160 (84); 1108 (80) 1.04 (0.83 to 1.31) Inhaled corticosteroids 1065 (77); 1001 (72) 1004 (73); 975 (70) 0.95 (0.78 to 1.16) Long acting 2 agonists 181 (13); 198 (14) 164 (12); 183 (13) 0.84 (0.59 to 1.20) Oral steroids 317 (23); 316 (23) 286 (21); 297 (21) 1.0 (0.82 to 1.22) Oral bronchodilators 100 (7); 95 (7) 120 (9); 119 (9) 1.38 (0.56 to 3.39) Primary care page 5 of 7 BMJ VOLUME 325 26 OCTOBER 2002 bmj.com on 17 July 2023 by guest. Protected by copyright. http://www.bmj.com/ BMJ: first published as 10.1136/bmj.325.7370.941 on 26 October 2002. Downloaded from
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“Further examination showed that, although the guideline was triggered appropriately, clinicians did not go past the first page and essentially did not use it.(18) Another study found that clinicians did not follow the guideline advice because they did not agree with it.”
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MethodElectronic Health Record–Based Decision Support to Improve Asthma Care: A Cluster-Randomized Trial
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“four reviews, 16 studies [16,19,21,28,40,44,45,53,55, 59,62,64,68,69,74,77-79,82,85,89] to three reviews, and 27 studies [20,22,23,26,27,29,31,32,34,35,39,41-43,4648,50,52,54,60,63,66,70,72,75,81,86-88] to two reviews; but we focused here on drug prescribing-relevant outcomes.”
BackgroundMethodInfluentialOverview of Clinical Decision Support Systems
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“The 10 questions address different aspects of asthma symptoms such as breathlessness, coughing, disturbed sleep and fear; each is given equal weighting and there are no separate domains. The scale is specifically designed for use in ambulatory care and has been used in randomised trials,”
MethodRoshanov, P. S., You, J. J., Dhaliwal, J., Koff, D., Mackay, J. A., Weise-Kelly, L., Navarro, T., Wilczynski, N. L., Haynes, R. B., & the CCDSS Systematic Review Team (2011) · Implementation Science · doi:10.1186/1748-5908-6-88 · Cited by 126 · see citing works
“In this review, we included 35 trials described in 45 publications because they measured the impact on test ordering behavior of CCDSSs that gave suggestions for ordering or performing diagnostic tests [15,25-57,57-67].”
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“CDSS provide patient-specific advice by using algorithms to compare patient characteristics against a knowledge base [7-9].”
A taxonomic description of computer-based clinical decision support systems
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“Eccles [31] 2002 EMR with recommendations for treatment of angina and asthma No recommendations Etter [32] 2001 Mailed, computer-generated, personalized smoking cessation counseling materials No letter”
MethodMahadevaiah, G., RV, P., Bermejo, I., Jaffray, D., Dekker, A., & Wee, L. (2020) · Medical Physics · doi:10.1002/mp.13562 · Cited by 114 · see citing works
“Some forms of CDSSs have been in use for decades, but their use is not yet widespread due to a number of issues related to design and implementation, such as clinicians not using them due to lack of time or lack of confidence in the CDSS’s output.(29,30)”
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“A number of controlled evaluations of CDS systems that are integrated with electronic medical records (EMRs) have been conducted in the areas of CVD risk and diabetes [15-19].”
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Interventions to Modify Health Care Provider Adherence to Asthma Guidelines: A Systematic Review
Okelo, S. O., Butz, A. M., Sharma, R., Diette, G. B., Pitts, S. I., King, T. M., Linn, S. T., Reuben, M., Chelladurai, Y., & Robinson, K. A. (2013) · PEDIATRICS · doi:10.1542/peds.2013-0779 · Cited by 109 · see citing works
Rebbeck, T., Maher, C. G., & Refshauge, K. M. (2006) · Australian Journal of Physiotherapy · doi:10.1016/s0004-9514(06)70025-3 · Cited by 102 · see citing works
Goldstein, M. K., Coleman, R. W., Tu, S. W., Shankar, R., O’Connor, M. J., Musen, M. A., Martins, S. B., Lavori, P. W., Shlipak, M. G., Oddone, E. Ž., et al. (2004) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1534 · Cited by 104 · see citing works
“In some cases, clinicians have low rates of using the system, for example, not interacting directly with a guideline by using the computer(5) or not accessing a clinical decision support system.(6) We developed a decision support system for hypertension, ATHENA DSS, that automates evidence-based guidelines for managem…”
InfluentialRandell, R., Mitchell, N., Dowding, D., Cullum, N., & Thompson, C. (2007) · Journal of Health Services Research and Policy · doi:10.1258/135581907782101543 · Cited by 116 · see citing works
“6 CDSSs are being used by nurses in a number of extended roles, including management of asthma, 7,8 angina 7 and diabetes 9 and first contact care.”
MethodStrategies to improve retention in randomised trials
Brueton, V. C., Tierney, J., Stenning, S., Harding, S., Meredith, S., Nazareth, I., & Rait, G. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.mr000032.pub2 · Cited by 279 · see citing works
Wilson, B. J., Torrance, N., Mollison, J., Wordsworth, S., Gray, J. A. M., Haites, N. E., Grant, A., Campbell, M., Miedyzbrodzka, Z., Clarke, A., et al. (2005) · Health Technology Assessment · doi:10.3310/hta9030 · Cited by 97 · see citing works
Ahmadian, L., van Engen-Verheul, M. M., Bakhshi‐Raiez, F., Peek, N. B., Ronald Cornet, A., & de Keizer, N. F. (2010) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2010.11.006 · Cited by 95 · see citing works
“However, integrating CDSSs with independent information systems has been shown difficult [6].”
Cunningham, S., Logan, C., Lockerbie, L., Dunn, M., McMurray, A., & Prescott, R. J. (2007) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2007.09.033 · Cited by 96 · see citing works
Payne, P., Johnson, S. B., Starren, J. B., Tilson, H. H., & Dowdy, D. W. (2005) · Journal of Investigative Medicine · doi:10.2310/6650.2005.00402 · Cited by 93 · see citing works
“53,54”
Filippi, A., Sabatini, A., Badioli, L., Samani, F., Mazzaglia, G., Catapano, A. L., & Cricelli, C. A. (2003) · Diabetes Care · doi:10.2337/diacare.26.5.1497 · Cited by 91 · see citing works
Review: What Can We Learn From Quality Improvement Research?
Alexander, J. A., & Hearld, L. R. (2009) · Medical Care Research and Review · doi:10.1177/1077558708330424 · Cited by 91 · see citing works
Decision tools in health care: focus on the problem, not the solution
Liu, J. K., Wyatt, J. C., & Altman, D. G. (2006) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-6-4 · Cited by 90 · see citing works
A pilot study of distributed knowledge management and clinical decision support in the cloud
Dixon, B. E., Simonaitis, L., Goldberg, H., Paterno, M. D., Schaeffer, M. H., Hongsermeier, T., Wright, A. T., & Blackford Middleton, A. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.03.004 · Cited by 85 · see citing works
One-on-One Coaching to Improve Pain Assessment and Management Practices of Pediatric Nurses
Johnston, C. C., Gagnon, A. J., Rennick, J. E., Rosmus, C., Patenaude, H., Ellis, J., Shapiro, C. R., Filion, F., Ritchie, J. A., & Byron, J. (2007) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2007.07.004 · Cited by 84 · see citing works
Persell, S. D., Kaiser, D., Dolan, N. C., Andrews, B., Levi, S., Khandekar, J. D., Gavagan, T. F., Thompson, J. A., Friesema, E. M., & Baker, D. W. (2010) · Medical Care · doi:10.1097/mlr.0b013e318202913d · Cited by 83 · see citing works
Kwok, R., Dinh, M. M. Q., Dinh, D. M., & Chu, M. (2009) · Emergency Medicine Australasia · doi:10.1111/j.1742-6723.2008.01149.x · Cited by 82 · see citing works
Arts, D. L., Abu–Hanna, A., Medlock, S. K., & van Weert, H. C. P. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170974 · Cited by 79 · see citing works
Internet-based interventions for the secondary prevention of coronary heart disease
Devi, R., Singh, S., powell, J. A., Fulton, E. A., Igbinedion, E., & Rees, K. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009386.pub2 · Cited by 82 · see citing works
Selecting, presenting and delivering clinical guidelines: are there any “magic bullets”?
Eccles, M., & Grimshaw, J. (2004) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2004.tb05946.x · Cited by 81 · see citing works
Rare disease diagnosis: A review of web search, social media and large-scale data-mining approaches
Svenstrup, D. T., Jørgensen, H. L., & Winther, O. (2015) · Rare Diseases · doi:10.1080/21675511.2015.1083145 · Cited by 80 · see citing works
“29,30, 31,32, 33 In an older review article on the use of the first generations of CDDSS systems, 34 Miller concludes that even though niche systems for specific areas are perceived as very useful, the perceived usefulness of the more general systems is less certain, despite the fact that these…”
BackgroundEvaluating and Improving Physician Prescribing
Soumerai, S. B., Majumdar, S. R., & Lipton, H. L. (2000) · Pharmacoepidemiology · doi:10.1002/0470842555.ch30 · Cited by 74 · see citing works
Goud, R., de Keizer, N. F., ter Riet, G., Wyatt, J. C., Hasman, A., Hellemans, I. M., & Peek, N. B. (2009) · BMJ · doi:10.1136/bmj.b1440 · Cited by 75 · see citing works
Getting guidelines into practice: a literature review
Richens, Y., Anderson, E. G., Rycroft-Malone, J., & Morrell, C. (2004) · Nursing Standard · doi:10.7748/ns2004.08.18.50.33.c3677 · Cited by 76 · see citing works
Kattan, M., Crain, E. F., Steinbach, S., Visness, C. M., Walter, M., Stout, J. W., Evans, R., Smartt, E., Gruchalla, R. S., Morgan, W. J., et al. (2006) · PEDIATRICS · doi:10.1542/peds.2005-2160 · Cited by 75 · see citing works
Ara, R., & Brazier, J. E. (2008) · Value in Health · doi:10.1111/j.1524-4733.2008.00428.x · Cited by 74 · see citing works
Why most interventions to improve physician prescribing do not seem to work.
Majumdar, S. R., & Soumerai, S. B. (2003) · PubMed Central · Cited by 73 · see citing works
Brusamento, S., Legido‐Quigley, H., Пантели, Д., Turk, E., Knai, C., Saliba, V., Car, J., McKee, M., & Busse, R. (2012) · Health Policy · doi:10.1016/j.healthpol.2012.08.005 · Cited by 74 · see citing works
“In total, two studies assessed the implementation of guidelines on osteoarthritis [19,20,37], four on COPD [13,14,25,33,34], four on hypertension [24,32,36,37], six on coronary heart disease [17,18,23,26,32,36,37], six on asthma [13,14,26,27,30,33,34] and finally seven on type two diabetes mellitus [11,12,15,16,21,22,…”
BackgroundMethodResultInfluentialHeselmans, A., de Velde, S. V., Donceel, P., Aertgeerts, B., & Ramaekers, D. (2009) · Implementation Science · doi:10.1186/1748-5908-4-82 · Cited by 70 · see citing works
Price, M., & Lau, F. (2014) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-14-43 · Cited by 70 · see citing works
“[40] to evaluate the use of computerized guidelines in managing adult patients with asthma and angina in primary care.”
MethodThe case for randomized controlled trials to assess the impact of clinical information systems
Liu, J. L. Y., & Wyatt, J. C. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.010306 · Cited by 66 · see citing works
Method of electronic health record documentation and quality of primary care
Linder, J. A., Schnipper, J. L., & Blackford Middleton, A. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000788 · Cited by 68 · see citing works
Impact of an Evidence-Based Computerized Decision Support System on Primary Care Prescription Costs
McMullin, S. T. (2004) · The Annals of Family Medicine · doi:10.1370/afm.233 · Cited by 68 · see citing works
McMullin, S. T., Lonergan, T. P., & Rynearson, C. S. (2005) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2005.11.4.322 · Cited by 65 · see citing works
A quantitative analysis of qualitative studies in clinical journals for the 2000 publishing year
McKibbon, K. A., & Gadd, C. S. (2004) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-4-11 · Cited by 63 · see citing works
Boulet, L., Becker, A. B., BOWIE, D. M., Hernandez, P., McIvor, A., Rouleau, M., Bourbeau, J., Graham, I. D., Logan, J., Légaré, F., et al. (2006) · Canadian Respiratory Journal · doi:10.1155/2006/810978 · Cited by 63 · see citing works
Hutton, J. L., Eccles, M., & Grimshaw, J. (2008) · Implementation Science · doi:10.1186/1748-5908-3-52 · Cited by 62 · see citing works
“Within the COGENT trial [13], we sought consent from one representative doctor within each participating general practice in the belief that, in this matter, they represented their whole practice.”
Computer decision support systems for asthma: a systematic review
Matui, P., Wyatt, J. C., Pinnock, H., Sheikh, A., & McLean, S. (2014) · npj Primary Care Respiratory Medicine · doi:10.1038/npjpcrm.2014.5 · Cited by 63 · see citing works
“13,21,42 41 Usage rate of the systems should be a core standard for reporting trials of CDSSs.”
BackgroundMethodResultInfluentialKooij, F. O., Vos, N. S., Siebenga, P. S., Klok, T., Hollmann, M. W., & Kal, J. E. (2012) · British Journal of Anaesthesia · doi:10.1093/bja/aes024 · Cited by 62 · see citing works
Architectures and tools for innovative Health Information Systems: The Guide Project
Ciccarese, P., Ezio Caffi, B., Quaglini, S., & Mario Stefanelli, A. (2005) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2005.02.001 · Cited by 61 · see citing works
Technology and its role in respiratory care
Smith, S. M. S., Elkin, S., & Partridge, M. R. (2009) · Primary Care Respiratory Journal · doi:10.4104/pcrj.2009.00038 · Cited by 56 · see citing works
“In some instances the guideline itself forms the basis of the technological intervention as part of a decision-making system for clinicians in primary care and other health care providers.(13,14) Asthma Asthma monitoring has been the focus of extensive research in the past decade.”
BackgroundPrimary Care Physicians and Oncologists Are Players on the Same Team
Grunfeld, E. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2007.15.7081 · Cited by 56 · see citing works
Clinical practice guidelines: barriers to durability after effective early implementation
Brand, C. A., Landgren, F., Hutchinson, A. F., Jones, C., MacGregor, L., & Campbell, D. A. (2005) · Internal Medicine Journal · doi:10.1111/j.1445-5994.2004.00763.x · Cited by 56 · see citing works
Unverzagt, S., Oemler, M., Braun, K., & Klement, A. (2013) · Family Practice · doi:10.1093/fampra/cmt080 · Cited by 53 · see citing works
Effect of Alerts for Drug Dosage Adjustment in Inpatients with Renal Insufficiency
Sellier, É., Colombet, I., Sabatier, B., Breton, G., Niès, J., Zapletal, É., Arlet, J. B., Somme, D., & Durieux, P. (2008) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2805 · Cited by 53 · see citing works
“Indeed, if a system providing recommendations is dependent on the initiative of the physicians for use, they seldom make the required effort.(21) However, the manner chosen to provide overdosing alerts in our study may partly explain the negative results.”
Impact of a Multifaceted Intervention on Cholesterol Management in Primary Care Practices
Bertoni, A. G., Bonds, D. E., Chen, H., Hogan, P. E., Crago, L., Rosenberger, E. L., Barham, A. H., Clinch, C. R., & Goff, D. C. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.44 · Cited by 52 · see citing works
“In ATP III practices, at AD visit 2, 83% of the providers’ PDAs indicated use of the CDSS.”
BackgroundInfluentialClinical decision support in cardiovascular medicine
Lu, Y., Melnick, E. R., & Krumholz, H. M. (2022) · BMJ · doi:10.1136/bmj-2020-059818 · Cited by 50 · see citing works
Ramnarayan, P., Winrow, A. P., Coren, M., Nanduri, V. R., Buchdahl, R., Jacobs, B., Fisher, H., Taylor, P. M., Wyatt, J. C., & Britto, J. F. (2006) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-6-37 · Cited by 52 · see citing works
The Alchemy of Clinical Trials
Will, C. M. (2007) · BioSocieties · doi:10.1017/s1745855207005078 · Cited by 52 · see citing works
Delvaux, N., Thienen, K. V., Heselmans, A., de Velde, S. V., Ramaekers, D., & Aertgeerts, B. (2017) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2016-0115-ra · Cited by 50 · see citing works
Lieu, T. A., Au, D. H., Krishnan, J. A., Moss, M., Selker, H. P., Harabin, A. L., TAGGART, V. S., & Connors, A. F. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201104-0634ws · Cited by 50 · see citing works
“Cluster-randomized trials Groups rather than individuals are randomized Does computerized decision support enhance the management of asthma and angina in primary care? This study randomized 60 general practices (41) These trials are useful for comparing alternative established therapies (11) and for comparing changes…”
MethodComputer-Based Clinical Decision Support Systems and Patient-Reported Outcomes: A Systematic Review
Blum, D., Raj, S. X., Oberholzer, R., Riphagen, I. I., Strasser, F., & Kaasa, S. (2014) · Patient · doi:10.1007/s40271-014-0100-1 · Cited by 50 · see citing works
“Workflow may be disturbed, and integration in routine practice may be considered difficult [29].”
Background
- Authors
- Eccles, M.
- Affiliations
- Newcastle University (GB)
- Corresponding author
- Eccles, M.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2002-10-26
- Volume
- 325
- Issue
- 7370
- Pages
- 941-941
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- PMC
- PMC130060
- OpenAlex
- W1996469473
- Cited by
- 354
- References
- 24
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 4 · 2023: 3 · 2022: 9 · 2021: 7 · 2020: 7 · 2019: 5 · 2018: 9 · 2017: 7 · 2016: 12 · 2015: 10 · 2014: 14 · 2013: 19 · 2012: 14
- FWCI
- 29.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Keywords
- computerised decision support, clinical guidelines, asthma management, angina management, guideline adherence, primary care, general practitioners, practice nurses, drug prescribing, patient-reported outcomes, chronic disease management
- MeSH terms
- Angina Pectoris, Asthma, Decision Making, Computer-Assisted, Family Practice, Humans, Treatment Outcome, Practice Guidelines as Topic, Evidence-Based Medicine, Guideline Adherence
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