Digital Self-Check-In Tools in Primary Care Clinics: A Scoping Review of Value Optimization and Return on Investment

Self-check-in via digital technology is becoming increasingly prevalent to streamline workflows and improve primary care efficiency, including kiosks, eCheck-in via portals, mobile check-in apps, and pre-appointment questionnaires. This scoping review examines the value-creation potential of digital self-check-in tools by assessing the quality of intake data generated with these tools and their reuse. Following the Joanna Briggs Institute guidelines for conducting scoping reviews and the PRISMA-ScR reporting criteria, searches were conducted across the CINAHL, PubMed, and Google Scholar databases to identify English-language peer-reviewed studies published between 2021 and 2026. In total, 488 studies were identified; 361 were assessed based on titles and abstracts after duplicate removal, 65 were reviewed in full text, and 15 studies were included in the final review and graded using the Johns Hopkins Nursing Evidence-Based Practice (JHEBP) levels and quality ratings. Most of the evidence was level III with a B quality rating. Findings showed that the portal and pre-visit questionnaire approaches provided the most reliable support for data structuring, visit preparation, and communication between the patient and the clinician. In turn, improvements in workflow efficiency, reduced patient congestion, increased throughput, and minimized front-desk burden could be achieved primarily through studies focused on kiosks and registration processes. Across the study, the strongest evidence supports operational and informational value rather than return on investment (ROI). The main barriers to the effective implementation of the interventions included access inequity, workflow integration, staff training, and bad data quality. Overall, digital self-check-in tools create value in primary care when patient-generated intake data are timely, complete, structured, and reusable across downstream clinical and administrative workflows. However, stronger evidence is still needed regarding measurable economic return.