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

Decision Support for Health Professionals (1127) Clinical Information and Decision Making (1314) Adoption and Change Management of eHealth Systems (670)
Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

Authors of this article:

Paolo Fraccaro1, 2, 3 Author Orcid Image ;   Mercedes Arguello Casteleiro4 Author Orcid Image ;   John Ainsworth1, 2 Author Orcid Image ;   Iain Buchan1, 2, 3 Author Orcid Image
Article Authors Cited by (70) Tweetations (13) Metrics

Journals

  1. Hsiao J, Chen R. Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: an integrative model of activity theory and the technology acceptance model. BMC Medical Informatics and Decision Making 2015;16(1) View
  2. Konstantinidis S, Bamidis P. Why decision support systems are important for medical education. Healthcare Technology Letters 2016;3(1):56 View
  3. Piovesan L, Terenziani P, Theseider Dupré D. Conformance analysis for comorbid patients in Answer Set Programming. Journal of Biomedical Informatics 2020;103:103377 View
  4. Bowles J, Caminati M, Cha S, Mendoza J. A framework for automated conflict detection and resolution in medical guidelines. Science of Computer Programming 2019;182:42 View
  5. Excoffier S, Herzig L, N’Goran A, Déruaz-Luyet A, Haller D. Prevalence of multimorbidity in general practice: a cross-sectional study within the Swiss Sentinel Surveillance System (Sentinella). BMJ Open 2018;8(3):e019616 View
  6. MacLean R, Sofuoglu M, Rosenheck R. Tobacco and alcohol use disorders: Evaluating multimorbidity. Addictive Behaviors 2018;78:59 View
  7. Palese A, Brusaferro S. A multidimensional vector model measuring clinical complexity may increase effectiveness in patient assessment. Internal and Emergency Medicine 2017;12(8):1287 View
  8. Anselma L, Piovesan L, Terenziani P. Temporal detection and analysis of guideline interactions. Artificial Intelligence in Medicine 2017;76:40 View
  9. Sinnott C, Byrne M, Bradley C. Improving medication management for patients with multimorbidity in primary care: a qualitative feasibility study of the MY COMRADE implementation intervention. Pilot and Feasibility Studies 2017;3(1) View
  10. Theis S, Rasche P, Bröhl C, Wille M, Mertens A. Task-Data Taxonomy for Health Data Visualizations: Web-Based Survey With Experts and Older Adults. JMIR Medical Informatics 2018;6(3):e39 View
  11. Harry M, Truitt A, Saman D, Henzler-Buckingham H, Allen C, Walton K, Ekstrom H, O’Connor P, Sperl-Hillen J, Bianco J, Elliott T. Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study. BMC Health Services Research 2019;19(1) View
  12. Bunn F, Goodman C, Russell B, Wilson P, Manthorpe J, Rait G, Hodkinson I, Durand M. Supporting shared decision-making for older people with multiple health and social care needs: a realist synthesis. Health Services and Delivery Research 2018;6(28):1 View
  13. Leiva-Fernández F, Prados-Torres J, Prados-Torres A, del-Cura-González I, Castillo-Jimena M, López-Rodríguez J, Rogero-Blanco M, Lozano-Hernández C, López-Verde F, Bujalance-Zafra M, Pico-Soler M, Gimeno-Feliu L, Poblador-Plou B, Martinez-Cañavate M, Muth C. Training primary care professionals in multimorbidity management: Educational assessment of the eMULTIPAP course. Mechanisms of Ageing and Development 2020;192:111354 View
  14. Yeung P, Severinsen C, Good G, O’Donoghue K. Social environment and quality of life among older people with diabetes and multiple chronic illnesses in New Zealand: Intermediary effects of psychosocial support and constraints. Disability and Rehabilitation 2022;44(5):768 View
  15. Sadler E, Porat T, Marshall I, Hoang U, Curcin V, Wolfe C, McKevitt C, Valdes-Sosa P. Shaping innovations in long-term care for stroke survivors with multimorbidity through stakeholder engagement. PLOS ONE 2017;12(5):e0177102 View
  16. Freedman S, Lin H, Prince J. Information Technology and Patient Health: An Expanded Analysis of Outcomes, Populations, and Mechanisms. SSRN Electronic Journal 2014 View
  17. Brown B, Balatsoukas P, Williams R, Sperrin M, Buchan I. Multi-method laboratory user evaluation of an actionable clinical performance information system: Implications for usability and patient safety. Journal of Biomedical Informatics 2018;77:62 View
  18. Sinnige J, Korevaar J, van Lieshout J, Westert G, Schellevis F, Braspenning J. Medication management strategy for older people with polypharmacy in general practice: a qualitative study on prescribing behaviour in primary care. British Journal of General Practice 2016;66(649):e540 View
  19. Fraccaro P, Kontopantelis E, Sperrin M, Peek N, Mallen C, Urban P, Buchan I, Mamas M. Predicting mortality from change-over-time in the Charlson Comorbidity Index. Medicine 2016;95(43):e4973 View
  20. Bauer M, Monteith S, Geddes J, Gitlin M, Grof P, Whybrow P, Glenn T. Automation to optimise physician treatment of individual patients: examples in psychiatry. The Lancet Psychiatry 2019;6(4):338 View
  21. Khalil H, Shamliyan T, Middleton M. Interventions for Community-Dwelling Patients with Multiple Chronic Illnesses. The American Journal of Medicine 2017;130(2):148 View
  22. Sinnott C. Interactions: understanding people and process in prescribing in primary care. BMJ Quality & Safety 2018;27(3):176 View
  23. Freedman S, Lin H, Prince J. Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms. American Journal of Health Economics 2018;4(1):51 View
  24. Keasberry J, Scott I, Sullivan C, Staib A, Ashby R. Going digital: a narrative overview of the clinical and organisational impacts of eHealth technologies in hospital practice. Australian Health Review 2017;41(6):646 View
  25. Xu X, Mishra G, Jones M. Evidence on multimorbidity from definition to intervention: An overview of systematic reviews. Ageing Research Reviews 2017;37:53 View
  26. Riaño D, Ortega W. Computer technologies to integrate medical treatments to manage multimorbidity. Journal of Biomedical Informatics 2017;75:1 View
  27. Walton D, Oliveira T, Satoh K, Mebane W. Argumentation Analytics for Treatment Deliberations in Multimorbidity Cases: An Introduction to Two Artificial Intelligence Approaches. Topoi 2021;40(2):373 View
  28. Riahi S, Fischler I, Stuckey M, Klassen P, Chen J. The Value of Electronic Medical Record Implementation in Mental Health Care: A Case Study. JMIR Medical Informatics 2017;5(1):e1 View
  29. de Wit H, Hurkens K, Mestres Gonzalvo C, Smid M, Sipers W, Winkens B, Mulder W, Janknegt R, Verhey F, van der Kuy P, Schols J. The support of medication reviews in hospitalised patients using a clinical decision support system. SpringerPlus 2016;5(1) View
  30. Meguerditchian A, Tamblyn R, Meterissian S, Law S, Prchal J, Winslade N, Stern D. Adjuvant Endocrine Therapy in Breast Cancer: A Novel e-Health Approach in Optimizing Treatment for Seniors (OPTIMUM): A Two-Group Controlled Comparison Pilot Study. JMIR Research Protocols 2016;5(4):e199 View
  31. Prados-Torres A, del Cura-González I, Prados-Torres J, Leiva-Fernández F, López-Rodríguez J, Calderón-Larrañaga A, Muth C. Multimorbilidad en medicina de familia y los principios Ariadne. Un enfoque centrado en la persona. Atención Primaria 2017;49(5):300 View
  32. Bijlsma N, Cohen M. Environmental Chemical Assessment in Clinical Practice: Unveiling the Elephant in the Room. International Journal of Environmental Research and Public Health 2016;13(2):181 View
  33. Čyras K, Oliveira T, Karamlou A, Toni F. Assumption-based argumentation with preferences and goals for patient-centric reasoning with interacting clinical guidelines. Argument & Computation 2021;12(2):149 View
  34. Kogan A, Peleg M, Tu S, Allon R, Khaitov N, Hochberg I. Towards a goal-oriented methodology for clinical-guideline-based management recommendations for patients with multimorbidity: GoCom and its preliminary evaluation. Journal of Biomedical Informatics 2020;112:103587 View
  35. Sharma V, Piscoran O, Summers A, Woywodt A, van der Veer S, Ainsworth J, Augustine T. The use of health information technology in renal transplantation: A systematic review. Transplantation Reviews 2021;35(2):100607 View
  36. Ji M, Yu G, Xi H, Xu T, Qin Y. Measures of success of computerized clinical decision support systems: An overview of systematic reviews. Health Policy and Technology 2021;10(1):196 View
  37. Karimi M, Tsiachristas A, Looman W, Stokes J, Galen M, Rutten-van Mölken M. Bundled payments for chronic diseases increased health care expenditure in the Netherlands, especially for multimorbid patients.. Health Policy 2021;125(6):751 View
  38. Souza-Pereira L, Ouhbi S, Pombo N. Quality-in-use characteristics for clinical decision support system assessment. Computer Methods and Programs in Biomedicine 2021;207:106169 View
  39. Roth C, Papassotiropoulos A, Brühl A, Lang U, Huber C. Psychiatry in the Digital Age: A Blessing or a Curse?. International Journal of Environmental Research and Public Health 2021;18(16):8302 View
  40. Sinha A, Kerketta S, Ghosal S, Kanungo S, Lee J, Pati S. Multimorbidity and Complex Multimorbidity in India: Findings from the 2017–2018 Longitudinal Ageing Study in India (LASI). International Journal of Environmental Research and Public Health 2022;19(15):9091 View
  41. Piovesan L, Terenziani P, Molino G. GLARE-SSCPM: An Intelligent System to Support the Treatment of Comorbid Patients. IEEE Intelligent Systems 2018;33(6):37 View
  42. Chen W, O’Bryan C, Gorham G, Howard K, Balasubramanya B, Coffey P, Abeyaratne A, Cass A. Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation. Implementation Science Communications 2022;3(1) View
  43. Souza-Pereira L, Ouhbi S, Pombo N. A process model for quality in use evaluation of clinical decision support systems. Journal of Biomedical Informatics 2021;123:103917 View
  44. Guo H, Li J, Liu H, He J. Learning dynamic treatment strategies for coronary heart diseases by artificial intelligence: real-world data-driven study. BMC Medical Informatics and Decision Making 2022;22(1) View
  45. Hahn W, Schütte K, Schultz K, Wolkenhauer O, Sedlmayr M, Schuler U, Eichler M, Bej S, Wolfien M. Contribution of Synthetic Data Generation towards an Improved Patient Stratification in Palliative Care. Journal of Personalized Medicine 2022;12(8):1278 View
  46. Chen W, Howard K, Gorham G, O’Bryan C, Coffey P, Balasubramanya B, Abeyaratne A, Cass A. Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis. Journal of the American Medical Informatics Association 2022;29(10):1757 View
  47. Mouazer A, Tsopra R, Sedki K, Letord C, Lamy J. Decision-support systems for managing polypharmacy in the elderly: A scoping review. Journal of Biomedical Informatics 2022;130:104074 View
  48. Ntalindwa T, Nduwingoma M, Karangwa E, Rashid Soron T, Uworwabayeho A, Uwineza A. Development of a Mobile App to Improve Numeracy Skills of Children With Autism Spectrum Disorder: Participatory Design and Usability Study. JMIR Pediatrics and Parenting 2021;4(3):e21471 View
  49. Samal L, Fu H, Camara D, Wang J, Bierman A, Dorr D. Health information technology to improve care for people with multiple chronic conditions. Health Services Research 2021;56(S1):1006 View
  50. Andolina A, Guazzone M, Piovesan L, Terenziani P. Temporal reasoning and query answering with preferences and probabilities for medical decision support. Expert Systems with Applications 2022;195:116565 View
  51. Zhou Y, Dai X, Ni Y, Zeng Q, Cheng Y, Carrillo-Larco R, Yan L, Xu X. Interventions and management on multimorbidity: An overview of systematic reviews. Ageing Research Reviews 2023;87:101901 View
  52. Marashi-Hosseini L, Jafarirad S, Hadianfard A. A fuzzy based dietary clinical decision support system for patients with multiple chronic conditions (MCCs). Scientific Reports 2023;13(1) View
  53. Jones J, Simons K, Manski-Nankervis J, Lumsden N, Fernando S, de Courten M, Cox N, Hamblin P, Janus E, Nelson C. Chronic disease IMPACT (chronic disease early detection and improved management in primary care project): An Australian stepped wedge cluster randomised trial. DIGITAL HEALTH 2023;9 View
  54. Domínguez J, Prociuk D, Marović B, Čyras K, Cocarascu O, Ruiz F, Mi E, Mi E, Ramtale C, Rago A, Darzi A, Toni F, Curcin V, Delaney B. ROAD2H: Development and evaluation of an open‐source explainable artificial intelligence approach for managing co‐morbidity and clinical guidelines. Learning Health Systems 2024;8(2) View
  55. Wiwatkunupakarn N, Aramrat C, Pliannuom S, Buawangpong N, Pinyopornpanish K, Nantsupawat N, Mallinson P, Kinra S, Angkurawaranon C. The Integration of Clinical Decision Support Systems Into Telemedicine for Patients With Multimorbidity in Primary Care Settings: Scoping Review. Journal of Medical Internet Research 2023;25:e45944 View
  56. Yu T, Gao M, Sun G, Graffigna G, Liu S, Wang J. Cardiac rehabilitation engagement and associated factors among heart failure patients: a cross-sectional study. BMC Cardiovascular Disorders 2023;23(1) View
  57. Hempel S, Bolshakova M, Hochman M, Jimenez E, Thompson G, Motala A, Ganz D, Gabrielian S, Edwards S, Zenner J, Dennis B, Chang E. Caring for high-need patients. BMC Health Services Research 2023;23(1) View
  58. Woodman R, Koczwara B, Mangoni A. Applying precision medicine principles to the management of multimorbidity: the utility of comorbidity networks, graph machine learning, and knowledge graphs. Frontiers in Medicine 2024;10 View
  59. Shakibaei Bonakdeh E, Sohal A, Rajabkhah K, Prajogo D, Melder A, Nguyen D, Bingham G, Tong E. Influential factors in the adoption of clinical decision support systems in hospital settings: a systematic review and meta-synthesis of qualitative studies. Industrial Management & Data Systems 2024;124(4):1463 View
  60. Kastner M, Hayden L, Wong G, Lai Y, Makarski J, Treister V, Chan J, Lee J, Ivers N, Holroyd-Leduc J, Straus S. Underlying mechanisms of complex interventions addressing the care of older adults with multimorbidity: a realist review. BMJ Open 2019;9(4):e025009 View

Books/Policy Documents

  1. Piovesan L, Terenziani P. Advances in Artificial Intelligence - IBERAMIA 2016. View
  2. Oliveira T, Dauphin J, Satoh K, Tsumoto S, Novais P. Logic and Argumentation. View
  3. Bottrighi A, Piovesan L, Terenziani P. Biomedical Engineering Systems and Technologies. View
  4. Grace A, O'Donoghue J, Mahony C, Heffernan T, Molony D, Carroll T. Encyclopedia of E-Health and Telemedicine. View
  5. Ratner S, DeWalt D. Chronic Illness Care. View
  6. Charalambous A. Developing and Utilizing Digital Technology in Healthcare for Assessment and Monitoring. View
  7. Silva A, Silva A, Oliveira T, Novais P. Intelligent Data Engineering and Automated Learning – IDEAL 2020. View