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Citing this Article

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Published on 17.12.09 in Vol 11, No 4 (2009): Oct-Dec

This paper is in the following e-collection/theme issue:

Works citing "An Electronic Clinical Decision Support Tool to Assist Primary Care Providers in Cardiovascular Disease Risk Management: Development and Mixed Methods Evaluation"

David Peiris, Rohina Joshi, Ruth Webster, Patrick Groenestein, Tim Usherwood, Emma Heeley, Fiona Turnbull, Alexandra Lipman, Anushka Patel

J Med Internet Res 2009 (Dec 17); 11(4):e51 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.1258):

(note that this is only a small subset of citations)

  1. Wright A, Sittig DF, Ash JS, Feblowitz J, Meltzer S, McMullen C, Guappone K, Carpenter J, Richardson J, Simonaitis L, Evans RS, Nichol WP, Middleton B. Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems. Journal of the American Medical Informatics Association 2011;18(3):232
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  2. B Sussman J, Holleman RG, Youles B, Lowery JC. Quality Improvement and Personalization for Statins: the QUIPS Quality Improvement Randomized Trial of Veterans’ Primary Care Statin Use. Journal of General Internal Medicine 2018;33(12):2132
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  3. Tseng Y, Wu J, Ping X, Lin H, Chen Y, Shang R, Chen M, Lai F, Chen Y. A Web-Based Multidrug-Resistant Organisms Surveillance and Outbreak Detection System with Rule-Based Classification and Clustering. Journal of Medical Internet Research 2012;14(5):e131
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  4. Peiris D, Brown A, Howard M, Rickards BA, Tonkin A, Ring I, Hayman N, Cass A. Building better systems of care for Aboriginal and Torres Strait Islander people: findings from the Kanyini health systems assessment. BMC Health Services Research 2012;12(1)
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  5. Abimbola S, Patel B, Peiris D, Patel A, Harris M, Usherwood T, Greenhalgh T. The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme. BMC Medicine 2019;17(1)
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  6. Willis A, Crasto W, Gray L, Dallosso H, Waheed G, Gray G, Davies MJ, Khunti K. The General Practitioner Prompt Study to Reduce Cardiovascular and Renal Complications in Patients With Type 2 Diabetes and Renal Complications: Protocol and Baseline Characteristics for a Cluster Randomized Controlled Trial. JMIR Research Protocols 2018;7(6):e152
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  7. Kennedy G, Gallego B. Clinical prediction rules: A systematic review of healthcare provider opinions and preferences. International Journal of Medical Informatics 2019;123:1
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  8. Rosenkranz N, Eckhardt A, Kühne M, Rosenkranz C. Gesundheitsinformationen im Internet. WIRTSCHAFTSINFORMATIK 2013;55(4):257
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  9. Kappen TH, van Loon K, Kappen MA, van Wolfswinkel L, Vergouwe Y, van Klei WA, Moons KG, Kalkman CJ. Barriers and facilitators perceived by physicians when using prediction models in practice. Journal of Clinical Epidemiology 2016;70:136
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  10. Chalasani S, Peiris DP, Usherwood T, Redfern J, Neal BC, Sullivan DR, Colagiuri S, Zwar NA, Li Q, Patel A. Reducing cardiovascular disease risk in diabetes: a randomised controlled trial of a quality improvement initiative. Medical Journal of Australia 2017;206(10):436
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  11. Regan T, Paul C, Ishiguchi P, D’Este C, Koller C, Forshaw K, Noble N, Oldmeadow C, Bisquera A, Eades S. Comparison of Two Sources of Clinical Audit Data to Assess the Delivery of Diabetes Care in Aboriginal Communities. International Journal of Environmental Research and Public Health 2017;14(10):1236
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  12. Praveen D, Patel A, McMahon S, Prabhakaran D, Clifford GD, Maulik PK, Joshi R, Jan S, Heritier S, Peiris D. A multifaceted strategy using mobile technology to assist rural primary healthcare doctors and frontline health workers in cardiovascular disease risk management: protocol for the SMARTHealth India cluster randomised controlled trial. Implementation Science 2013;8(1)
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  13. Peiris D, Williams C, Holbrook R, Lindner R, Reeve J, Das A, Maher C. A Web-Based Clinical Decision Support Tool for Primary Health Care Management of Back Pain: Development and Mixed Methods Evaluation. JMIR Research Protocols 2014;3(2):e17
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  14. Maher L, Dawson A, Wiley K, Hope K, Torvaldsen S, Lawrence G, Conaty S. Influenza vaccination during pregnancy: a qualitative study of the knowledge, attitudes, beliefs, and practices of general practitioners in Central and South-Western Sydney. BMC Family Practice 2014;15(1)
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  15. Ramkumar D, Rao SS. Efficacy and Safety of Traditional Medical Therapies for Chronic Constipation: Systematic Review. The American Journal of Gastroenterology 2005;100(4):936
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  16. Schwarz D, Dhungana S, Kumar A, Acharya B, Agrawal P, Aryal A, Baum A, Choudhury N, Citrin D, Dangal B, Dhimal M, Gauchan B, Gupta T, Halliday S, Karmacharya B, Kishore S, Koirala B, Kshatriya U, Levine E, Maru S, Rimal P, Sapkota S, Schwarz R, Shrestha A, Thapa A, Maru D. An integrated intervention for chronic care management in rural Nepal: protocol of a type 2 hybrid effectiveness-implementation study. Trials 2020;21(1)
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  17. Rozenkranz N, Eckhardt A, Kühne M, Rosenkranz C. Health Information on the Internet. Business & Information Systems Engineering 2013;5(4):259
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  18. Praveen D, Patel A, Raghu A, Clifford GD, Maulik PK, Mohammad Abdul A, Mogulluru K, Tarassenko L, MacMahon S, Peiris D. SMARTHealth India: Development and Field Evaluation of a Mobile Clinical Decision Support System for Cardiovascular Diseases in Rural India. JMIR mHealth and uHealth 2014;2(4):e54
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  19. Feldstein AC, Schneider JL, Unitan R, Perrin NA, Smith DH, Nichols GA, Lee NL. Health Care Worker Perspectives Inform Optimization of Patient Panel-Support Tools: A Qualitative Study. Population Health Management 2013;16(2):107
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  20. Peiris D, Usherwood T, Panaretto K, Harris M, Hunt J, Redfern J, Zwar N, Colagiuri S, Hayman N, Lo S, Patel B, Lyford M, MacMahon S, Neal B, Sullivan D, Cass A, Jackson R, Patel A. Effect of a Computer-Guided, Quality Improvement Program for Cardiovascular Disease Risk Management in Primary Health Care. Circulation: Cardiovascular Quality and Outcomes 2015;8(1):87
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  21. Phillips K, Steel EJ, Collins I, Emery J, Pirotta M, Mann GB, Butow P, Hopper JL, Trainer A, Moreton J, Antoniou AC, Cuzick J, Keogh L. Transitioning to routine breast cancer risk assessment and management in primary care: what can we learn from cardiovascular disease?. Australian Journal of Primary Health 2016;22(3):255
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  22. Johnson KW, Shameer K, Glicksberg BS, Readhead B, Sengupta PP, Björkegren JL, Kovacic JC, Dudley JT. Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine. JACC: Basic to Translational Science 2017;2(3):311
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  23. Jonnagaddala J, Liaw S, Ray P, Kumar M, Chang N, Dai H. Coronary artery disease risk assessment from unstructured electronic health records using text mining. Journal of Biomedical Informatics 2015;58:S203
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  24. Federman AD, Kil N, Kannry J, Andreopolous E, Toribio W, Lyons J, Singer M, Yartel A, Smith BD, Rein DB, Krauskopf K. An Electronic Health Record–based Intervention to Promote Hepatitis C Virus Testing Among Adults Born Between 1945 and 1965. Medical Care 2017;55(6):590
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  25. . Challenge of introducing evidence based medicine into clinical practice. Clinical Governance: An International Journal 2011;16(3):231
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  26. Mahle WT, Simpson SA, Fye P, McConnell ME. Management of Warfarin in Children With Heart Disease. Pediatric Cardiology 2011;32(8):1115
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  27. Hayek A, Joshi R, Usherwood T, Webster R, Kaur B, Saini B, Armour C, Krass I, Laba T, Reid C, Shiel L, Hespe C, Hersch F, Jan S, Lo S, Peiris D, Rodgers A, Patel A. An integrated general practice and pharmacy-based intervention to promote the use of appropriate preventive medications among individuals at high cardiovascular disease risk: protocol for a cluster randomized controlled trial. Implementation Science 2015;11(1)
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  28. Adepoju IO, Albersen BJA, De Brouwere V, van Roosmalen J, Zweekhorst M. mHealth for Clinical Decision-Making in Sub-Saharan Africa: A Scoping Review. JMIR mHealth and uHealth 2017;5(3):e38
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  29. Ivers N, Pylypenko B, Tu K. Identifying Patients With Ischemic Heart Disease in an Electronic Medical Record. Journal of Primary Care & Community Health 2011;2(1):49
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  30. Zbib A, Hodgson C, Calderwood S. Can eHealth Tools Enable Health Organizations to Reach Their Target Audience?. Healthcare Management Forum 2011;24(3):155
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  31. Leykum LK, Palmer R, Lanham H, Jordan M, McDaniel RR, Noël PH, Parchman M. Reciprocal learning and chronic care model implementation in primary care: results from a new scale of learning in primary care. BMC Health Services Research 2011;11(1)
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  32. Hsiao C, Shiau C, Liu Y, Chao MM, Lien C, Chen C, Yen S, Tang S. Use of a Rich Internet Application Solution to Present Medical Images. Journal of Digital Imaging 2011;24(6):967
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  33. Kilsdonk E, Peute L, Jaspers M. Factors influencing implementation success of guideline-based clinical decision support systems: A systematic review and gaps analysis. International Journal of Medical Informatics 2017;98:56
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  34. Peiris D, Usherwood T, Weeramanthri T, Cass A, Patel A. New tools for an old trade: a socio‐technical appraisal of how electronic decision support is used by primary care practitioners. Sociology of Health & Illness 2011;33(7):1002
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  35. Seneviratne MG, Hersch F, Peiris DP. HealthNavigator: a mobile application for chronic disease screening and linkage to services at an urban Primary Health Network. Australian Journal of Primary Health 2018;24(2):116
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  36. Orchard J, Neubeck L, Freedman B, Li J, Webster R, Zwar N, Gallagher R, Ferguson C, Lowres N. eHealth Tools to Provide Structured Assistance for Atrial Fibrillation Screening, Management, and Guideline‐Recommended Therapy in Metropolitan General Practice: The AF‐SMART Study. Journal of the American Heart Association 2019;8(1)
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  37. Lugomirski P, Guo H, Boom NK, Donovan LR, Ko DT, Tu JV. Quality of Diabetes and Hyperlipidemia Screening Before a First Myocardial Infarction. Canadian Journal of Cardiology 2013;29(11):1382
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  38. Peiris D, Sun L, Patel A, Tian M, Essue B, Jan S, Zhang P. Systematic medical assessment, referral and treatment for diabetes care in China using lay family health promoters: protocol for the SMARTDiabetes cluster randomised controlled trial. Implementation Science 2015;11(1)
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  39. Groenhof TKJ, Asselbergs FW, Groenwold RHH, Grobbee DE, Visseren FLJ, Bots ML. The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making 2019;19(1)
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  40. Joshi R, John O, Jha V. The Potential Impact of Public Health Interventions in Preventing Kidney Disease. Seminars in Nephrology 2017;37(3):234
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  41. Denig P, Dun M, Schuling J, Haaijer-Ruskamp FM, Voorham J. The effect of a patient-oriented treatment decision aid for risk factor management in patients with diabetes (PORTDA-diab): study protocol for a randomised controlled trial. Trials 2012;13(1)
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  42. Westerbeek L, Ploegmakers KJ, de Bruijn G, Linn AJ, van Weert JC, Daams JG, van der Velde N, van Weert HC, Abu-Hanna A, Medlock S. Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review. International Journal of Medical Informatics 2021;152:104506
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  43. Jolyane B, Nabil A. Breast cancer risk prediction models’ adoption by Canadian providers - an in-depth qualitative comparative analysis. Journal of Business Research 2023;157:113625
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  44. Burns A, Donnelly B, Feyi-Waboso J, Shephard E, Calitri R, Tarrant M, Dean SG. How do electronic risk assessment tools affect the communication and understanding of diagnostic uncertainty in the primary care consultation? A systematic review and thematic synthesis. BMJ Open 2022;12(6):e060101
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  45. Fletcher E, Burns A, Wiering B, Lavu D, Shephard E, Hamilton W, Campbell JL, Abel G. Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review. BMC Primary Care 2023;24(1)
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  46. Horwood C, Luthuli S, Mapumulo S, Haskins L, Jensen C, Pansegrouw D, McKerrow N. Challenges of using e-health technologies to support clinical care in rural Africa: a longitudinal mixed methods study exploring primary health care nurses’ experiences of using an electronic clinical decision support system (CDSS) in South Africa. BMC Health Services Research 2023;23(1)
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  47. Heron N, O’Connor SR, Kee F, Thompson DR, Cupples M, Donnelly M. Refining a primary care shared decision-making aid for lifestyle change: a mixed-methods study. BJGP Open 2022;6(1):BJGPO.2021.0100
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  48. Horwood C, Haskins L, Mapumulo S, Connolly C, Luthuli S, Jensen C, Pansegrouw D, McKerrow N. Electronic Integrated Management of Childhood Illness (eIMCI): a randomized controlled trial to evaluate an electronic clinical decision-making support system for management of sick children in primary health care facilities in South Africa. BMC Health Services Research 2024;24(1)
    CrossRef
  49. Lorenc T, Stokes G, Fulbright H, Sutcliffe K, Sowden A. Communicating cardiovascular risk: Systematic review of qualitative evidence. Patient Education and Counseling 2024;123:108231
    CrossRef
  50. Jungo KT, Deml MJ, Schalbetter F, Moor J, Feller M, Lüthold RV, Huibers CJA, Sallevelt BTGM, Meulendijk MC, Spruit M, Schwenkglenks M, Rodondi N, Streit S. A mixed methods analysis of the medication review intervention centered around the use of the ‘Systematic Tool to Reduce Inappropriate Prescribing’ Assistant (STRIPA) in Swiss primary care practices. BMC Health Services Research 2024;24(1)
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.1258):

  1. Moon JD, Galea MP. Medical Imaging. 2017. chapter 64:1501
    CrossRef
  2. O’Grady C, Patel B, Candlin S, Candlin CN, Peiris D, Usherwood T. Communicating Risk. 2016. Chapter 17:285
    CrossRef
  3. Moon JD, Galea MP. Improving Health Management through Clinical Decision Support Systems. 2016. chapter 1:1
    CrossRef