Advancing healthcare system performance in Peru through data analytics.

The utilization of data analytics as an approach to improvement in healthcare system performance through the support of evidence-based decisions, predictive epidemiology, operational efficiency, and equitable distribution of health care resources is becoming increasingly significant. Emerging economies such as Peru are experiencing an increased number of opportunities due to the introduction of digital health initiatives and the implementation of health information systems to improve health service delivery. Evidence related to digital health and health information systems is not fully developed or adequately synthesized with respect to the Peruvian context. Thus, the objective of this study is to generate a Systematic Literature Review (SLR) using PRISMA 2020 Guidelines to describe the contributions of data analytics to improving Healthcare System Performance in Peru, as well as to identify opportunities, obstacles, and future directions of healthcare data analytics in Peru. A systematic search of literature was conducted through Scopus, Web of Science, PubMed/MEDLINE, Scielo, and LILACS using a search strategy that included the following key search terms: Digital Health, Healthcare Analytics, Health Information Systems, Predictive Epidemiology and Data-Driven Healthcare Interventions and was limited to articles written in English or Spanish that were published within the time frame of between 2015 and 2026. Peer-reviewed studies were included when they addressed digital health, healthcare analytics, health information systems, predictive epidemiology, and data-driven healthcare interventions relevant to, or transferable to, the Peruvian healthcare system. The studies selected were based on PRISMA processes for identification, screening, eligibility, and inclusion; the results are synthesized and reported using thematic analysis. The findings of the review show that healthcare analytics has positive effects on disease control, optimization of hospital performance, access to health care, digital governance, and decision-making based on data in public health. However, numerous structural barriers still exist, such as lack of interoperability between fragmented information technology systems, disparity in digital infrastructure between rural and urban areas, regulatory and policy gaps, and disparities in access to health care between rural and urban areas. Ultimately, this review concludes that there is great potential for improvement of Healthcare System Performance in Peru using data analytics, however, in order for there to be sustainable changes, there needs to be continued investment into governance, interoperability between digital ecosystems, ethical management of data, and the development of analytical skills and infrastructure. Future research on healthcare data analytics should be aimed at developing empirical evaluations and context-specific implementation strategies to promote equitable and resilient health care transformation.