Published on in Vol 22, No 2 (2020): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16866, first published .
The Economic Impact of Artificial Intelligence in Health Care: Systematic Review

The Economic Impact of Artificial Intelligence in Health Care: Systematic Review

The Economic Impact of Artificial Intelligence in Health Care: Systematic Review

Journals

  1. Adly A, Adly A, Adly M. Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review. Journal of Medical Internet Research 2020;22(8):e19104 View
  2. Zhang Y, zhang X, Wu Q, Gu C, Wang Z. Artificial Intelligence-Aided Colonoscopy for Polyp Detection: A Systematic Review and Meta-Analysis of Randomized Clinical Trials. Journal of Laparoendoscopic & Advanced Surgical Techniques 2021;31(10):1143 View
  3. von Wedel P, Hagist C. Economic Value of Data and Analytics for Health Care Providers: Hermeneutic Systematic Literature Review. Journal of Medical Internet Research 2020;22(11):e23315 View
  4. Delso G, Cirillo D, Kaggie J, Valencia A, Metser U, Veit-Haibach P. How to Design AI-Driven Clinical Trials in Nuclear Medicine. Seminars in Nuclear Medicine 2021;51(2):112 View
  5. He Q, Du F, Simonse L. A Patient Journey Map to Improve the Home Isolation Experience of Persons With Mild COVID-19: Design Research for Service Touchpoints of Artificial Intelligence in eHealth. JMIR Medical Informatics 2021;9(4):e23238 View
  6. Petersen C, Smith J, Freimuth R, Goodman K, Jackson G, Kannry J, Liu H, Madhavan S, Sittig D, Wright A. Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper. Journal of the American Medical Informatics Association 2021;28(4):677 View
  7. Sachar S, Dakessian M, Beitari S, Badrinarayanan S. Artificial Intelligence Alongside Physicians in Canada: Reality and Risks. Journal of Science Policy & Governance 2020;17(01) View
  8. Stanimirović D, Matetić V. Can the COVID-19 pandemic boost the global adoption and usage of eHealth solutions?. Journal of Global Health 2020;10(2) View
  9. Nicol G, Ricchio A, Metts C, Yingling M, Ramsey A, Schweiger J, Miller J, Lenze E. A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment. JMIR mHealth and uHealth 2020;8(11):e18609 View
  10. Yin J, Ngiam K, Teo H. Role of Artificial Intelligence Applications in Real-Life Clinical Practice: Systematic Review. Journal of Medical Internet Research 2021;23(4):e25759 View
  11. Shivakumar N, Chandrashekar A, Handa A, Lee R. Use of deep learning for detection, characterisation and prediction of metastatic disease from computerised tomography: a systematic review. Postgraduate Medical Journal 2022;98(1161):e20 View
  12. Balagurunathan Y, Mitchell R, El Naqa I. Requirements and reliability of AI in the medical context. Physica Medica 2021;83:72 View
  13. van Leeuwen K, de Rooij M, Schalekamp S, van Ginneken B, Rutten M. How does artificial intelligence in radiology improve efficiency and health outcomes?. Pediatric Radiology 2022;52(11):2087 View
  14. Yan K, Balijepalli C, Druyts E. The Impact of Digital Therapeutics on Current Health Technology Assessment Frameworks. Frontiers in Digital Health 2021;3 View
  15. Wolff J, Pauling J, Keck A, Baumbach J. Success Factors of Artificial Intelligence Implementation in Healthcare. Frontiers in Digital Health 2021;3 View
  16. Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Frontiers in Digital Health 2021;3 View
  17. Abbasgholizadeh Rahimi S, Légaré F, Sharma G, Archambault P, Zomahoun H, Chandavong S, Rheault N, T Wong S, Langlois L, Couturier Y, Salmeron J, Gagnon M, Légaré J. Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal. Journal of Medical Internet Research 2021;23(9):e29839 View
  18. Ziegelmayer S, Graf M, Makowski M, Gawlitza J, Gassert F. Cost-Effectiveness of Artificial Intelligence Support in Computed Tomography-Based Lung Cancer Screening. Cancers 2022;14(7):1729 View
  19. Svedberg P, Reed J, Nilsen P, Barlow J, Macrae C, Nygren J. Toward Successful Implementation of Artificial Intelligence in Health Care Practice: Protocol for a Research Program. JMIR Research Protocols 2022;11(3):e34920 View
  20. Caudai C, Galizia A, Geraci F, Le Pera L, Morea V, Salerno E, Via A, Colombo T. AI applications in functional genomics. Computational and Structural Biotechnology Journal 2021;19:5762 View
  21. Gomez Rossi J, Feldberg B, Krois J, Schwendicke F. Evaluation of the Clinical, Technical, and Financial Aspects of Cost-Effectiveness Analysis of Artificial Intelligence in Medicine: Scoping Review and Framework of Analysis. JMIR Medical Informatics 2022;10(8):e33703 View
  22. de Vos J, Visser L, de Beer A, Fornasa M, Thoral P, Elbers P, Cinà G. The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge. Value in Health 2022;25(3):359 View
  23. Weinert L, Müller J, Svensson L, Heinze O. Perspective of Information Technology Decision Makers on Factors Influencing Adoption and Implementation of Artificial Intelligence Technologies in 40 German Hospitals: Descriptive Analysis. JMIR Medical Informatics 2022;10(6):e34678 View
  24. Zhang J, Budhdeo S, William W, Cerrato P, Shuaib H, Sood H, Ashrafian H, Halamka J, Teo J. Moving towards vertically integrated artificial intelligence development. npj Digital Medicine 2022;5(1) View
  25. Martinho A, Kroesen M, Chorus C. A healthy debate: Exploring the views of medical doctors on the ethics of artificial intelligence. Artificial Intelligence in Medicine 2021;121:102190 View
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  27. Yang L, Ene I, Arabi Belaghi R, Koff D, Stein N, Santaguida P. Stakeholders’ perspectives on the future of artificial intelligence in radiology: a scoping review. European Radiology 2022;32(3):1477 View
  28. Voets M, Veltman J, Slump C, Siesling S, Koffijberg H. Systematic Review of Health Economic Evaluations Focused on Artificial Intelligence in Healthcare: The Tortoise and the Cheetah. Value in Health 2022;25(3):340 View
  29. Liu H, Li R, Zhang Y, Zhang K, Yusufu M, Liu Y, Mou D, Chen X, Tian J, Li H, Fan S, Tang J, Wang N. Economic evaluation of combined population-based screening for multiple blindness-causing eye diseases in China: a cost-effectiveness analysis. The Lancet Global Health 2023;11(3):e456 View
  30. Zipori A, Kerley C, Klein A, Kenney R. Real-World Translation of Artificial Intelligence in Neuro-Ophthalmology: The Challenges of Making an Artificial Intelligence System Applicable to Clinical Practice. Journal of Neuro-Ophthalmology 2022;42(3):287 View
  31. Tachkov K, Zemplenyi A, Kamusheva M, Dimitrova M, Siirtola P, Pontén J, Nemeth B, Kalo Z, Petrova G. Barriers to Use Artificial Intelligence Methodologies in Health Technology Assessment in Central and East European Countries. Frontiers in Public Health 2022;10 View
  32. Gurevich E, El Hassan B, El Morr C. Equity within AI systems: What can health leaders expect?. Healthcare Management Forum 2023;36(2):119 View
  33. Wawer Matos P, Reimer R, Rokohl A, Caldeira L, Heindl L, Große Hokamp N. Artificial Intelligence in Ophthalmology – Status Quo and Future Perspectives. Seminars in Ophthalmology 2023;38(3):226 View
  34. Sharma M, Savage C, Nair M, Larsson I, Svedberg P, Nygren J. Artificial Intelligence Applications in Health Care Practice: Scoping Review. Journal of Medical Internet Research 2022;24(10):e40238 View
  35. Spanos K, Giannoukas A, Kouvelos G, Tsougos I, Mavroforou A. Artificial intelligence application in vascular diseases. Journal of Vascular Surgery 2022;76(3):615 View
  36. Pietris J, Lam A, Bacchi S, Gupta A, Kovoor J, Chan W. Health Economic Implications of Artificial Intelligence Implementation for Ophthalmology in Australia: A Systematic Review. Asia-Pacific Journal of Ophthalmology 2022;11(6):554 View
  37. Wamala-Andersson S, Richardson M, Landerdahl Stridsberg S, Ryan J, Sukums F, Goh Y. Artificial Intelligence and Precision Health Through Lenses of Ethics and Social Determinants of Health: Protocol for a State-of-the-Art Literature Review. JMIR Research Protocols 2023;12:e40565 View
  38. khan B, Fatima H, Qureshi A, Kumar S, Hanan A, Hussain J, Abdullah S. Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector. Biomedical Materials & Devices 2023;1(2):731 View
  39. Tamura H, Akune Y, Hiratsuka Y, Kawasaki R, Kido A, Miyake M, Goto R, Yamada M. Real-world effectiveness of screening programs for age-related macular degeneration: amended Japanese specific health checkups and augmented screening programs with OCT or AI. Japanese Journal of Ophthalmology 2022;66(1):19 View
  40. Ciecierski-Holmes T, Singh R, Axt M, Brenner S, Barteit S. Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review. npj Digital Medicine 2022;5(1) View
  41. Gama F, Tyskbo D, Nygren J, Barlow J, Reed J, Svedberg P. Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice: Scoping Review. Journal of Medical Internet Research 2022;24(1):e32215 View
  42. Prodan A, Deimel L, Ahlqvist J, Birov S, Thiel R, Toivanen M, Kolitsi Z, Kalra D. Success Factors for Scaling Up the Adoption of Digital Therapeutics Towards the Realization of P5 Medicine. Frontiers in Medicine 2022;9 View
  43. Petersson L, Larsson I, Nygren J, Nilsen P, Neher M, Reed J, Tyskbo D, Svedberg P. Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Services Research 2022;22(1) View
  44. Lahiri A, Jha S. Machine learning to deep learning: Artificially intelligent approaches toward precision in public health. Journal of Public Health and Primary Care 2021;2(2):25 View
  45. Monteith S, Glenn T, Geddes J, Whybrow P, Achtyes E, Bauer M. Expectations for Artificial Intelligence (AI) in Psychiatry. Current Psychiatry Reports 2022;24(11):709 View
  46. Khamisy-Farah R, Gilbey P, Furstenau L, Sott M, Farah R, Viviani M, Bisogni M, Kong J, Ciliberti R, Bragazzi N. Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature. International Journal of Environmental Research and Public Health 2021;18(17):8989 View
  47. Bakker L, Aarts J, Uyl-de Groot C, Redekop K. How can we discover the most valuable types of big data and artificial intelligence-based solutions? A methodology for the efficient development of the underlying analytics that improve care. BMC Medical Informatics and Decision Making 2021;21(1) View
  48. Ruamviboonsuk P, Chantra S, Seresirikachorn K, Ruamviboonsuk V, Sangroongruangsri S. Economic Evaluations of Artificial Intelligence in Ophthalmology. Asia-Pacific Journal of Ophthalmology 2021;10(3):307 View
  49. Wolff J, Matschinske J, Baumgart D, Pytlik A, Keck A, Natarajan A, von Schacky C, Pauling J, Baumbach J. Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare – a proof of concept study for the prediction of coronary artery calcification scores. Journal of Integrative Bioinformatics 2022;19(4) View
  50. Schwendicke F, Cejudo Grano de Oro J, Garcia Cantu A, Meyer-Lueckel H, Chaurasia A, Krois J. Artificial Intelligence for Caries Detection: Value of Data and Information. Journal of Dental Research 2022;101(11):1350 View
  51. Morris M, Song E, Rajesh A, Asaad M, Phillips B. Ethical, Legal, and Financial Considerations of Artificial Intelligence in Surgery. The American Surgeon 2023;89(1):55 View
  52. Hashiguchi T, Oderkirk J, Slawomirski L. Fulfilling the Promise of Artificial Intelligence in the Health Sector: Let’s Get Real. Value in Health 2022;25(3):368 View
  53. Ramessur R, Raja L, Kilduff C, Kang S, Li J, Thomas P, Sim D. Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology. Asia-Pacific Journal of Ophthalmology 2021;10(3):317 View
  54. Gomez Rossi J, Rojas-Perilla N, Krois J, Schwendicke F. Cost-effectiveness of Artificial Intelligence as a Decision-Support System Applied to the Detection and Grading of Melanoma, Dental Caries, and Diabetic Retinopathy. JAMA Network Open 2022;5(3):e220269 View
  55. Day S, Shah V, Kaganoff S, Powelson S, Mathews S. Assessing the Clinical Robustness of Digital Health Startups: Cross-sectional Observational Analysis. Journal of Medical Internet Research 2022;24(6):e37677 View
  56. Khan W, Seto E. A “Do No Harm” Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence–Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework. Journal of Medical Internet Research 2023;25:e43386 View
  57. Hickok M, Dorsey C, O'Brien T, Baur D, Ingram K, Chauhan C, Gamundani A. Case Study: The Distilling of a Biased Algorithmic Decision System through a Business Lens. SSRN Electronic Journal 2022 View
  58. Channa R, Wolf R, Abràmoff M, Lehmann H. Effectiveness of artificial intelligence screening in preventing vision loss from diabetes: a policy model. npj Digital Medicine 2023;6(1) View
  59. Brauner P, Hick A, Philipsen R, Ziefle M. What does the public think about artificial intelligence?—A criticality map to understand bias in the public perception of AI. Frontiers in Computer Science 2023;5 View
  60. Stonko D, Morrison J, Hicks C. A review of mature machine learning- and artificial intelligence-enabled applications in aortic surgery. JVS-Vascular Insights 2023;1:100016 View
  61. Kelly L, Coote L, Dinnes J, Fleming C, Holmes H, Matin R. Key issues when considering adopting a skin cancer diagnostic tool that uses artificial intelligence. British Journal of Dermatology 2023;189(2):219 View
  62. Langius-Wiffen E, de Jong P, Hoesein F, Dekker L, van den Hoven A, Nijholt I, Boomsma M, Veldhuis W. Retrospective batch analysis to evaluate the diagnostic accuracy of a clinically deployed AI algorithm for the detection of acute pulmonary embolism on CTPA. Insights into Imaging 2023;14(1) View
  63. Rizvi A, Rizvi F, Lalakia P, Hyman L, Frasso R, Sztandera L, Das A. Is Artificial Intelligence the Cost-Saving Lens to Diabetic Retinopathy Screening in Low- and Middle-Income Countries?. Cureus 2023 View
  64. Langius-Wiffen E, de Jong P, Mohamed Hoesein F, Dekker L, van den Hoven A, Nijholt I, Boomsma M, Veldhuis W. Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT. European Radiology 2023;34(1):367 View
  65. Chinnasamy V, Sakulsaengprapha V, Mathews S. The Benefit of Artificial Intelligence-Based Diagnosis in Gastroenterology and Hepatology Is Highly Variable: A Diagnostic Need and Burden Analysis. Gastroenterology 2023;165(3):788 View
  66. Kumar D, Ingole A, Choudhari S. Towards Ideal Health Ecosystem With Artificial Intelligence-Driven Medical Services in India: An Overview. Cureus 2023 View
  67. Neher M, Petersson L, Nygren J, Svedberg P, Larsson I, Nilsen P. Innovation in healthcare: leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden. Implementation Science Communications 2023;4(1) View
  68. Kumar R, Sood P, Nirala R, Ade R, Sonaji A. Uses of AI in Field of Radiology- What is State of Doctor & Pateints Communication in Different Disease for Diagnosis Purpose. Journal for Research in Applied Sciences and Biotechnology 2023;2(5):51 View
  69. Heeres T, Tran T, Noort B. Drivers and Barriers to Implementing the Internet of Things in the Health Care Supply Chain: Mixed Methods Multicase Study. Journal of Medical Internet Research 2023;25:e48730 View
  70. Jacobs F, D'Amico S, Benvenuti C, Gaudio M, Saltalamacchia G, Miggiano C, De Sanctis R, Della Porta M, Santoro A, Zambelli A. Opportunities and Challenges of Synthetic Data Generation in Oncology. JCO Clinical Cancer Informatics 2023;(7) View
  71. Li L, Haley L, Boyd A, Bernstam E. Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review. Journal of Biomedical Informatics 2023;147:104531 View
  72. Kondo T, Diwani S, Nyamawe A, Mjahidi M. Exploring the status of artificial intelligence for healthcare research in Africa: a bibliometric and thematic analysis. AI and Ethics 2023 View
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Books/Policy Documents

  1. Cross D, Adler-Milstein J, Holmgren A. Responding to the Grand Challenges in Health Care via Organizational Innovation. View
  2. Anderson D, Bjarnadottir M, Nenova Z. Innovative Technology at the Interface of Finance and Operations. View
  3. Penteado B, Fornazin M, Castro L. Progress in Artificial Intelligence. View
  4. Chavda V, Patel K, Patel S, Apostolopoulos V. Bioinformatics Tools for Pharmaceutical Drug Product Development. View
  5. Monlezun D. The Thinking Healthcare System. View
  6. Monlezun D. The Thinking Healthcare System. View
  7. Shah R, Reese V, Oselkin M, P. Stawicki S. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 1. View