1Master's Student, Hospital Administration, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: anjalianjali2519@gmail.com, Mob: 7876578135, ORCID: 0009-0007-2531-411X
2Master's Student, Hospital Administration, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: sharmaishika944@gmail.com, Mob: 7876698794, ORCID: 0009-0003-1377-0311
3Master's Student, Hospital Administration, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: devdeshwal520@gmail.com, Mob: 8168993438, ORCID: 0009-0000-8985-6718
4Master's Student, Hospital Administration, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: Rahuldeshwal9812@gmail.com, Mob: 8168385461, ORCID: 0009-0003-2046-875
5Master's Student, Hospital Administration, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: moksh8552@gmail.com, Mob: 7017876731, ORCID: 0009-0004-7323-3195
6Assistant Professor, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: shivshankartiwari@gmail.com, Mob: 6395893171, ORCID: 0009-0006-4248-3487
7Assistant Professor, Uttaranchal College of Health Sciences, Uttaranchal University, Prem Nagar, Dehradun- 248007, Uttarakhand, India. Email: gopal4ogod11@gmail.com, Mob: 9756189726, ORCID: 0009-0005-7726-3858
The integration of artificial intelligence (AI) into healthcare systems has generated substantial interest among clinicians, administrators, and policymakers worldwide. Among the most pressing challenges in modern healthcare delivery are prolonged patient waiting times in outpatient departments (OPD) and the inefficiencies that characterize hospital discharge processes. These operational bottlenecks contribute not only to patient dissatisfaction but also to adverse clinical outcomes, staff burnout, and escalating healthcare costs. This systematic review evaluates the existing body of literature concerning AI-driven interventions aimed at reducing waiting times in OPD settings and optimizing discharge workflows. A total of forty-two peer-reviewed studies published between 2015 and 2024 were identified, screened, and reviewed following PRISMA guidelines. The findings reveal that AI-based tools—including machine learning algorithms, natural language processing systems, predictive analytics platforms, and intelligent scheduling engines—demonstrate measurable efficacy in reducing patient wait times by between 20% and 65%, depending on the clinical context and implementation fidelity. Furthermore, AI-assisted discharge planning systems have been associated with a reduction in average length of stay and improved resource utilization. Despite these promising outcomes, the review also identifies significant barriers to widespread adoption, including data privacy concerns, interoperability challenges, high implementation costs, and clinician resistance. The paper concludes with recommendations for future research and practical guidance for healthcare institutions seeking to leverage AI solutions for operational improvement.
Keywords: Artificial intelligence, outpatient department, waiting time, discharge process, machine learning, healthcare operations, systematic review, patient flow.
How to cite this article: Anjali, Sharma I, Deshwal D, Deshwal R, Kumar M, Tiwari SS, Gopal. Evaluating the Impact of AI-driven Solutions on Reducing Patient Waiting Time in Outpatient Departments (OPD) and Discharge Processes: A Systematic Review. Int J Drug Deliv Technol. 2026;16(1s): 1015-1026. DOI: 10.25258/ijddt.16.1s.113
Source of support: Nil.
Conflict of interest: None