Cited by 354Clinical practice guidelines implementationElectronic Health Records SystemsHealth Sciences Research and Education

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Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial

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Eccles, M.·2002·BMJ

DOI 10.1136/bmj.325.7370.941PMC PMC130060

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Abstract

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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*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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“Certainly, the implementation of this system cannot be considered the ‘magic bullet’ 34 that provides an answer to all questions, but may provide the basis for further interventions aimed at improving preventive measures in primary care.”
Background
Process Evaluation of Implementation Strategies
Hulscher, M., & Wensing, M. (2020) · doi:10.1002/9781119488620.ch22 · Cited by 26
Independent and Supplementary Prescribing
Crown, J. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511861123 · Cited by 25
Implementing Practice Guidelines: A Workshop on Guidelines Dissemination and Implementation with a Focus on Asthma and COPD
Boulet, L., Becker, A. B., BOWIE, D. M., Hernandez, P., McIvor, A., & Rouleau, M. (2006) · Canadian Respiratory Journal · doi:10.1155/2006/287125 · Cited by 25
Effect of Clinical Decision-Support Systems
Bright, T. J., Wong, A. F., Ravi, D., Bristow, E., Bastian, L. A., Coeytaux, R. R., Samsa, G. P., Hasselblad, V., Williams, J. W., Musty, M. D., et al. (2020) · Annals of Internal Medicine · Cited by 24
Assortative mating may explain spouses' risk of same disease
Willemsen, G. A. H. M., Vink, J. M., & Boomsma, D. I. (2003) · BMJ · doi:10.1136/bmj.326.7385.396/a · Cited by 24
Effect of Patient-Specific Ratings vs Conventional Guidelines on Investigation Decisions in Angina
Junghans, C. (2007) · Archives of Internal Medicine · doi:10.1001/archinte.167.2.195 · Cited by 23
“of patients with angina per month 5 (2-8) 18 (10-30) 13 (5-20) 15 (2-50)”
COMPLIANCE WITH THE AMERICAN ACADEMY OF OPHTHALMOLOGY PREFERRED PRACTICE PATTERN FOR DIABETIC RETINOPATHY IN A RESIDENT OPHTHALMOLOGY CLINIC
Tseng, V. L., Greenberg, P. B., Scott, I. U., & Anderson, K. L. (2010) · Retina · doi:10.1097/iae.0b013e3181cd47a2 · Cited by 22
Online on-the-spot searching increases use of evidence during consultations in family practice
Duppen, D. V., Aertgeerts, B., Hannes, K., Neirinckx, J., Seuntjens, L., Goossens, F. J., & Linden, A. V. (2007) · Patient Education and Counseling · doi:10.1016/j.pec.2007.04.008 · Cited by 22
Cluster Randomized Trials of Professional and Organizational Behavior Change Interventions in Health Care Settings
Grimshaw, J., Eccles, M., Campbell, M., & Elbourne, D. (2005) · The Annals of the American Academy of Political and Social Science · doi:10.1177/0002716205274576 · Cited by 28
Improving outpatient care of depression by implementing practice guidelines: a controlled clinical trial
Bermejo, I., Schneider, F. W., Kriston, L., Gäebel, W., Hegerl, U., Berger, M., & Härter, M. C. (2008) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzn050 · Cited by 22
“asthma, depression, acute coronary syndrome) [10, 17, 18].”
A T-2 translational research perspective on interventions to improve post-fracture osteoporosis care
Majumdar, S. R. (2011) · Osteoporosis International · doi:10.1007/s00198-011-1700-4 · Cited by 21
“For example, Eccles and colleagues conducted a largescale cluster randomized trial in 60 UK primary care practices that already had electronic records and prescribing [ 10 ].”
Method
Implementation of electronic medical records: effect on the provision of preventive services in a pay-for-performance environment.
Greiver, M., Barnsley, J. M., Glazier, R. H., Moineddin, R., & Harvey, B. J. (2011) · Europe PMC (PubMed Central) · Cited by 21
Evolution of health information management and information technology in emergency medicine
Dinh, M. M. Q., & Chu, M. (2006) · Emergency Medicine Australasia · doi:10.1111/j.1742-6723.2006.00855.x · Cited by 21
Linking guidelines to Electronic Health Record design for improved chronic disease management.
Barretto, S. A., Warren, J., Goodchild, A., Bird, L., Heard, S., & Stumptner, M. (2003) · Europe PMC (PubMed Central) · Cited by 20
Evaluating decision aids – where next?
O’Cathain, A., & Thomas, K. J. (2004) · Health Expectations · doi:10.1111/j.1369-7625.2004.00258.x · Cited by 20
The Use of Computerized Decision Support Systems in Preventive Cardiology—Principal Results from the National Precard® Survey in Denmark
Bonnevie, L., Thomsen, T. F., & Jørgensen, T. (2005) · European Journal of Cardiovascular Prevention & Rehabilitation · doi:10.1097/01.hjr.0000159280.26933.b7 · Cited by 20
Section 1: Health and Clinical Mangement: The Safety and Quality of Decision Support Systems
Westbrook, J. I., Wyatt, J. C., & Coiera, E. W. (2006) · Yearbook of Medical Informatics · doi:10.1055/s-0038-1638469 · Cited by 20
“How do we know when a CDSS provides its advice safely and in a format which will encourage use [7]? Even the simplest paper-based decision tools frequently lead to the wrong answer being generated [8], with serious consequences for patient care.”
Background
The doctor, his patient, and the computerized evidence‐based guideline
Lipman, T. (2004) · Journal of Evaluation in Clinical Practice · doi:10.1111/j.1365-2753.2004.00499.x · Cited by 20
A systematic review on the effectiveness and impact of clinical decision support systems for breathlessness
Sunjaya, A. P., Ansari, S., & Jenkins, C. R. (2022) · npj Primary Care Respiratory Medicine · doi:10.1038/s41533-022-00291-x · Cited by 19
Risks to patient safety associated with implementation of electronic applications for medication management in ambulatory care - a systematic review
Carling, C. L. L., Kirkehei, I., Dalsbø, T. K., & Paulsen, E. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-133 · Cited by 21
“[8]); or supporting rational decision making and/or accurate use of clinical logarithms [9,10].”
Background
Angina on the Palm: randomized controlled pilot trial of Palm PDA software for referrals for cardiac testing.
Greiver, M., Drummond, N., White, D., Weshler, J., & Moineddin, R. (2005) · PubMed Central · Cited by 19
Kidney disease management in UK primary care: guidelines, incentives and Information Technology
Klebe, B., Farmer, C., Cooley, R. E., de Lusignan, S., Middleton, R., O'Donoghue, D. J., New, J. P., & Stevens, P. E. (2007) · Family Practice · doi:10.1093/fampra/cmm026 · Cited by 19
Design and Implementation of a Nursing Clinical Decision Support System to Promote Guideline Adherence
Lyerla, F. (2008) · CIN Computers Informatics Nursing · doi:10.1097/01.ncn.0000304800.93003.b4 · Cited by 19
Opening the Black Box: Cognitive Strategies in Family Practice
Christensen, R. E. (2005) · The Annals of Family Medicine · doi:10.1370/afm.264 · Cited by 19
Improving the delivery of care for patients with diabetes through understanding optimised team work and organisation in primary care
Eccles, M., Hawthorne, G., Johnston, M., Hunter, M., Steen, N., Francis, J., Hrisos, S., Elovainio, M. J., & Grimshaw, J. (2009) · Implementation Science · doi:10.1186/1748-5908-4-22 · Cited by 18
“We have conducted a range of relevant work, including: studies of quality of care in diabetes in primary care [1618]; pragmatic randomised controlled trials of various quality improvement (QI) strategies, including computerisation of guidelines [19], educational messages attached to test results [20,21], an enhanced a…”
A Process-Oriented Approach for Supporting Clinical Decisions for Infection Management
Cánovas-Segura, B., Zerbato, F., Oliboni, B., Combi, C., Campos, M., Morales, A., Juárez, J. M., Marı́n, R., & Palacios, F. (2017) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi.2017.73 · Cited by 18
“Besides, whenever physicians do not agree with the guideline and want to follow a different approach, such systems may be perceived as restrictive rather than supporting [13].”
Background
Anesthesiology Control Tower—Feasibility Assessment to Support Translation (ACTFAST): Mixed-Methods Study of a Novel Telemedicine-Based Support System for the Operating Room
Murray-Torres, T. M., Casarella, A., Bollini, M. L., Wallace, F., Avidan, M. S., & Politi, M. C. (2019) · JMIR Human Factors · doi:10.2196/12155 · Cited by 19
“Successful systems are those that achieve high levels of usability [23,24] by meeting thresholds for efficiency, effectiveness, and satisfaction [25-27] in the actual environment in which they will be used [22,28,29].”
Clinical evidence continuous medical education: a randomised educational trial of an open access e-learning program for transferring evidence-based information – ICEKUBE (Italian Clinical Evidence Knowledge Utilization Behaviour Evaluation) – study protocol
Moja, L., Moschetti, I., Cinquini, M., Sala, V., Compagnoni, A., Duca, P., Deligant, C., Manfrini, R., Clivio, L., Satolli, R., et al. (2008) · Implementation Science · doi:10.1186/1748-5908-3-37 · Cited by 18
“When evaluating educational interventions aimed at improving clinical practice, a number of non-specific effects may influence estimates of the effect of an intervention, grouped together under the term Hawthorne effect [13-17].”
Background
Longitudinal adoption rates of complex decision support tools in primary care
McCullagh, L., Mann, D., Rosen, L. M., Kannry, J. L., & McGinn, T. G. (2014) · BMJ Evidence-Based Medicine · doi:10.1136/ebmed-2014-110054 · Cited by 18
A randomized trial to assess the impact of opinion leader endorsed evidence summaries on the use of secondary prevention strategies in patients with coronary artery disease: the ESP-CAD trial protocol [NCT00175240]
McAlister, F. A., Fradette, M., Graham, M. M., Majumdar, S. R., Ghali, W. A., Williams, R., Tsuyuki, R. T., McMeekin, J., Grimshaw, J., & Knudtson, M. L. (2006) · Implementation Science · doi:10.1186/1748-5908-1-11 · Cited by 18
Feasibility and impact of a computerised clinical decision support system on investigation and initial management of new onset chest pain: a mixed methods study
Johnson, R., Evans, M. A., Cramer, H., Bennert, K., Morris, R. W., Eldridge, S. M., Jüttner, K. V., Zaman, M. J., Hemingway, H., Denaxas, S., et al. (2015) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-015-0189-8 · Cited by 17
“Previous qualitative studies have identified CDSSs having little impact on decisions either through non-use of the CDSS [15], or use after the consultation has been completed [16].”
Background
Evaluating Health Information Technology: Provider Satisfaction with an HIV-Specific, Electronic Clinical Management and Reporting System
Magnus, M., Herwehe, J., Andrews, L., Gibson, L., Daigrepont, N., Leon, J. M. D., Hyslop, N. E., Styron, S., Wilcox, R. D., Kaiser, M., et al. (2009) · AIDS Patient Care and STDs · doi:10.1089/apc.2008.0053 · Cited by 17
Evidence‐Based Medicine and Primary Care: Keeping Up Is Hard to Do
Zipkin, D. A., Greenblatt, L., & Kushinka, J. T. (2012) · Mount Sinai Journal of Medicine: A Journal of Translational and Personalized Medicine · doi:10.1002/msj.21337 · Cited by 16
Self Determination Theory and Preventive Care Delivery: A Research Involving Outpatient Settings Network (RIOS Net) Study
Sussman, A. L., Williams, R. L., Leverence, R. R., Gloyd, P. W., & Crabtree, B. F. (2008) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2008.04.070159 · Cited by 17
Interventions to Educate Family Physicians to Change Test Ordering
Thomas, R. E., Vaska, M. M., Naugler, C. T., & Turin, T. C. (2016) · Academic Pathology · doi:10.1177/2374289516633476 · Cited by 16
“5-13); PSA (22; 7-143) Per diabetic patient: HbA1C (1.”
ResultInfluential
Measuring asthma quality in primary care: Can we develop better measures?
Yawn, B. P., & Yawn, R. A. (2005) · Respiratory Medicine · doi:10.1016/j.rmed.2005.04.010 · Cited by 16
“For example, stating that a certain practice has lower rates of inhaled corticosteroid use than other similar clinics suggests no specific strategy to resolve the problem.(68,72) Outcome or quality measures suggested by the National Institute for Child HealthCare Quality (NICHQ) are based on assumptions that symptoms…”
Background
Ontology Driven CPG Authoring and Execution via a Semantic Web Framework
Hussain, S., & Abidi, S. S. R. (2007) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2007.408 · Cited by 16
“Functionally speaking, CDSS compare a patient’s medical condition with a medical knowledge base and then guide a practitioner by offering patient and diseasespecific advice [4].”
Background
Patient-Specific Prompts in the Cholesterol Management of Renal Transplant Outpatients: Results and Analysis of Underperformance
Garthwaite, E. A., Will, E. J., Bartlett, C., Richardson, D., & Newstead, C. G. (2004) · Transplantation · doi:10.1097/01.tp.0000137340.22880.c8 · Cited by 15
“In contrast, in a large and recent study involving 60 general practices in North England, no effect was found of a computerized decision support system on prescribing or reported patient outcomes for asthma and angina (14).”
Result
Indiscriminate investigations have adverse effects
Barth, J. H., & Jones, R. G. (2003) · BMJ · doi:10.1136/bmj.326.7385.393 · Cited by 15
Development and evaluation of a mobile-based asthma clinical decision support system to enhance evidence-based patient management in primary care
Abtahi, H., Amini, S., Gholamzadeh, M., & Gharabaghi, M. A. (2023) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2023.101168 · Cited by 16
The disparate management of superficial venous thrombosis in primary and secondary care
Lane, T. R. A., Sritharan, K., Herbert, J. R., Franklin, I. J., & Davies, A. H. (2014) · Phlebology The Journal of Venous Disease · doi:10.1177/0268355514521184 · Cited by 14
Severe Asthma Global Evaluation (SAGE): An Electronic Platform for Severe Asthma
Denton, E. J., Hore‐Lacy, F., Radhakrishna, N., Gilbert, A., Tay, T. R., Lee, J., Dabscheck, E. J., Harvey, E. S., Bulathsinhala, L., Fingleton, J., et al. (2019) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2019.02.042 · Cited by 14
A computerized pneumococcal vaccination reminder system in the adult emergency department
Dexheimer, J. W., Talbot, T. R., Ye, F., Shyr, Y., Jones, I., Gregg, W. M., & Aronsky, D. (2011) · Vaccine · doi:10.1016/j.vaccine.2011.07.032 · Cited by 14
“18 Table 2: Study Type and Location Study Paper-Based Computer Generated Computerized Ansari (46) Display Bankhead (47) Flag, GP Letter Barnett (15) Front Becker (48) Front Burack (49) In-chart Burack (50) In-chart Burack (51) In-chart Burack (10) In-chart Buschbaum (28) Front Chambers (52) Front Chambers (53) Front C…”
The use of electronic alerts in primary care computer systems to identify the excessive prescription of short-acting beta2-agonists for people with asthma: a systematic review
McKibben, S., Simoni, A. D., Bush, A., Thomas, M. D., & Griffiths, C. (2018) · npj Primary Care Respiratory Medicine · doi:10.1038/s41533-018-0080-z · Cited by 15
“Interventions in the two older studies 28,29 were poorly described which may have limited our interpretation of the ﬁ ndings.”
BackgroundMethodInfluential

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
DOI: 10.1136/bmj.325.7370.941
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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Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial

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