The Health Information Technology Special Issue: Evolving Tech, Fundamental Methods

Am J Manag Care. 2025;31(3):108. https://doi.org/10.37765/ajmc.2025.89694

In this special issue on health information technology in The American Journal of Managed Care, we have a range of topics that reflect the current state of research in digital health platforms and tools. These papers represent the critical types of research in data science, long-term impacts of telehealth post COVID-19 pandemic, and core implementation issues related to digital and technology programs. Thus, this spectrum of research represents relevant topics that will continue to permeate the field in the coming years.

First, this special issue includes papers on artificial intelligence/machine learning (AI/ML), which reflect the overall rapid proliferation of studies in this space. The AI/ML papers included in this issue also specifically emphasize the need to focus on the rollout of these models in real-world practice and settings, which is a critical area for deeper research and exploration. For example, Bennett et al at the San Francisco Health Network found that a tailored readmission algorithm for a safety-net health care setting resulted in subsequent significant clinical improvements as well as a reduction in outcome disparities in their setting. Similarly, a thought piece from Tierney et al expands this implementation thinking by setting forth new considerations for large language models integrated into clinical practice, with an emphasis on the essential equity considerations.

Second, this special issue has several papers focused on telehealth, with a specific emphasis on telehealth utilization in the post–public health emergency phase of the COVID-19 pandemic. This research is essential given that we have a lot to study related to the long-term use of telehealth in routine practice, especially as both patients and clinicians are looking for the right balance of in-person vs virtual care that upholds the highest quality of care while maintaining relationships. For example, Mandal et al studied sustained telemedicine use across more than 500 ambulatory practices in New York, comparing trends in behavioral health vs primary care settings as well as by complexity of the encounters. Stein et al focused on telehealth failure rates (eg, starting but not completing a visit virtually), identifying an area of telemedicine that deserves attention with respect to quality of the encounter—overall and within subgroups experiencing higher failure rates. And notably, the examination by Hu et al of telemental health care utilization among children with Medicaid highlighted the rapid expansion, but also the exacerbation of disparities, in the use of telehealth within this population.

Finally, we have another set of papers in this special issue that go even deeper into the implementation outcomes of established technology programs. For example, Kim et al used in-depth qualitative methods to characterize the barriers to and facilitators of uptake of e-consult rollout across California Medicaid managed care plans, which is variably offered across plans and affected across multiple levers of influence. Finally, Abraham et al examined the reach and subgroup effectiveness of an employer-based diabetes management program, highlighting potential areas where the program can be improved for broader population health benefits.

Taken together, these studies highlight many additional important themes in health technology research. First, all papers in this issue examined disparities or equity/bias considerations in their approach, signaling the centrality of addressing equity in any study that will effect widespread change. Second, the studies in this issue (whether they included a specific implementation-focused outcome or not) all focused on real-world considerations for practice, rather than discovery of new platforms or products alone. Third, the outcomes examined in this issue spanned from clinical and health metrics to process and utilization measures to implementation outcomes—showcasing the need to match rigorous evaluation to the appropriate variables and domains that matter most for the technology at hand.

Moving forward, the field of health technology and digital health research will only continue to evolve at an accelerated pace, with considerable potential to advance practice as well as to improve health. However, the fundamental methods in applied and health services research (as showcased throughout this issue) will remain essential for assessing the real-world impacts as technology advancements unfold.