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

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

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

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

Journals

  1. Wright A, Sittig D, Ash J, Feblowitz J, Meltzer S, McMullen C, Guappone K, Carpenter J, Richardson J, Simonaitis L, Evans R, Nichol W, 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 View
  2. B Sussman J, Holleman R, Youles B, Lowery J. 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 View
  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 View
  4. Peiris D, Brown A, Howard M, Rickards B, 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) View
  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) View
  6. Willis A, Crasto W, Gray L, Dallosso H, Waheed G, Gray G, Davies M, 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 View
  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 View
  8. Rosenkranz N, Eckhardt A, Kühne M, Rosenkranz C. Gesundheitsinformationen im Internet. WIRTSCHAFTSINFORMATIK 2013;55(4):257 View
  9. Kappen T, van Loon K, Kappen M, van Wolfswinkel L, Vergouwe Y, van Klei W, Moons K, Kalkman C. Barriers and facilitators perceived by physicians when using prediction models in practice. Journal of Clinical Epidemiology 2016;70:136 View
  10. Chalasani S, Peiris D, Usherwood T, Redfern J, Neal B, Sullivan D, Colagiuri S, Zwar N, 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 View
  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 View
  12. Praveen D, Patel A, McMahon S, Prabhakaran D, Clifford G, Maulik P, 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) View
  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 View
  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) View
  15. Ramkumar D, Rao S. Efficacy and Safety of Traditional Medical Therapies for Chronic Constipation: Systematic Review. The American Journal of Gastroenterology 2005;100(4):936 View
  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) View
  17. Rozenkranz N, Eckhardt A, Kühne M, Rosenkranz C. Health Information on the Internet. Business & Information Systems Engineering 2013;5(4):259 View
  18. Praveen D, Patel A, Raghu A, Clifford G, Maulik P, 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 View
  19. Feldstein A, Schneider J, Unitan R, Perrin N, Smith D, Nichols G, Lee N. Health Care Worker Perspectives Inform Optimization of Patient Panel-Support Tools: A Qualitative Study. Population Health Management 2013;16(2):107 View
  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 View
  21. Phillips K, Steel E, Collins I, Emery J, Pirotta M, Mann G, Butow P, Hopper J, Trainer A, Moreton J, Antoniou A, 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 View
  22. Johnson K, Shameer K, Glicksberg B, Readhead B, Sengupta P, Björkegren J, Kovacic J, Dudley J. Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine. JACC: Basic to Translational Science 2017;2(3):311 View
  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 View
  24. Federman A, Kil N, Kannry J, Andreopolous E, Toribio W, Lyons J, Singer M, Yartel A, Smith B, Rein D, 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 View
  25. Ogundele M. Challenge of introducing evidence based medicine into clinical practice. Clinical Governance: An International Journal 2011;16(3):231 View
  26. Mahle W, Simpson S, Fye P, McConnell M. Management of Warfarin in Children With Heart Disease. Pediatric Cardiology 2011;32(8):1115 View
  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) View
  28. Adepoju I, Albersen B, 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 View
  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 View
  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 View
  31. Leykum L, Palmer R, Lanham H, Jordan M, McDaniel R, Noël P, 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) View
  32. Hsiao C, Shiau C, Liu Y, Chao M, 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 View
  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 View
  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 View
  35. Seneviratne M, Hersch F, Peiris D. 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 View
  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) View
  37. Lugomirski P, Guo H, Boom N, Donovan L, Ko D, Tu J. Quality of Diabetes and Hyperlipidemia Screening Before a First Myocardial Infarction. Canadian Journal of Cardiology 2013;29(11):1382 View
  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) View
  39. Groenhof T, Asselbergs F, Groenwold R, Grobbee D, Visseren F, Bots M. 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) View
  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 View
  41. Denig P, Dun M, Schuling J, Haaijer-Ruskamp F, 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) View
  42. Westerbeek L, Ploegmakers K, de Bruijn G, Linn A, van Weert J, Daams J, van der Velde N, van Weert H, 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 View

Books/Policy Documents

  1. Moon J, Galea M. Medical Imaging. View
  2. O’Grady C, Patel B, Candlin S, Candlin C, Peiris D, Usherwood T. Communicating Risk. View
  3. Moon J, Galea M. Improving Health Management through Clinical Decision Support Systems. View