**Background:** Digital transformation is reshaping all sectors of society, including healthcare. Inpatient care, which accounts for a large share of healthcare spending, faces pressure from new technologies, changing patient expectations, demographic shifts (aging populations, declining birth rates), and workforce shortages. This study examines how current digitization trends influence inpatient service delivery, with a special reference to the German hospital system as a reference model for other European and international settings.
**Methods:** The authors conducted a sequential mixed-methods study combining a scoping review and qualitative expert interviews. The scoping review followed PRISMA guidelines and searched PubMed, MEDLINE, EconLit, EconBiz, and ScienceDirect between October 2020 and February 2021. Inclusion criteria were: reference to the future or trends, reference to digital/technology terms, and reference to inpatient service provision or hospitals. Papers published between 2016 and 2021 in English were included. After removing duplicates, 1,030 articles were screened by title and abstract, 74 full-text articles were read, and 44 studies met eligibility criteria. Two independent researchers performed screening and data extraction. The identified trends were then validated and refined through 12 semi-structured, guide-based interviews with experts from four groups: inpatient care suppliers, digital service providers in healthcare, overarching institutions, and relevant scientists. Interviews were analyzed deductively using MAXQDA software. Data from both sources were synthesized into a heuristic logic model.
**Key Results:** From the 44 included studies, 8 core trends were identified: (1) Changing the patient role — patients become active participants with transparency in their own data; (2) Connected and integrated delivery of care — providers collaborate across sector barriers using EHRs, IoT, and e-prescriptions; (3) Data-driven resource allocation — real-time data analysis optimizes capacity planning and resource use; (4) Performance optimization in primary processes — technology supports staff in diagnostics and therapy decisions; (5) New information and communications media — avatars, VR, AR, and mobile health broaden communication channels; (6) Increased technological intensity — hospitals deploy more smart devices, robotics, and cloud services; (7) Outcome improvement and personalized treatments — early detection and disease prediction enable individualized therapy; (8) Emergence of new ecosystems — providers link via platforms to allocate services optimally. The closest linkage was between trends 3 and 4 (15 common factors), followed by trends 4 and 7. Trend 1 showed the fewest connections. Expert interviews identified positive effects (e.g., transparency, efficiency, quality) and negative effects (e.g., disinformation risk, competitive pressure, data protection risks) for each trend. Prerequisites included trust, data availability, investments, and acceptance. Drivers included health literacy, digital competencies, medical progress, and patient expectations. The heuristic impact model shows three levels of effects: first-degree effects from the 8 trends, second-degree effects (additional patient value, meeting patient needs, patient integration), and a third-degree effect of patient-centric care. The trend development corridor shows that technological intensity and care quality both increase over time, with data-driven value contribution exceeding technology-driven value. Barriers were classified as external (regulatory frameworks, data protection, interoperability, insufficient investment) and internal (lack of digital knowledge, workforce resistance to change, cybersecurity needs, lack of strategic positioning).
**Clinical Implications:** The study demonstrates that digital transformation can make hospital care more patient-centric, enabling earlier disease detection and treatment, and potentially relieving strained healthcare systems. For medical professionals, this means relief through technology support but also requires new skills and changed working methods. Patients need higher health literacy and digital competencies. Decision-makers must prepare hospitals for their changed role in digitally driven ecosystems, adapt reimbursement systems, ensure data interoperability, and invest in infrastructure and qualifications. The authors note that while opportunities dominate risks in the included studies, job losses, data privacy concerns, and imbalanced market power are potential negative consequences that must be addressed.