Following are practices for developing comprehensive health IT systems.
Something I realized early on is that such systems should be flexible enough to continually adapt to new healthcare knowledge and concepts; data models; value sets; data format, terminology and transport standards; use cases; workflows; and diverse user needs.
It should be able to accommodate the needs of PCPs and all clinical specialties, approaches and user roles, as well as patients, with highly useful and useable tools.
It should be able to work in centralized, distributed, point-to-point, and tightly- and loosely-coupled networks using client-server and standalone (desktop) tools.
It should be able to leverage cloud-based storage and computing (all flavors), as well as the local resources of untethered devices that may connect to the internet occasionally.
It should be able to work with third-party tools that provide additional relevant capabilities.
And if it provides decision support, it should focus on enabling knowledge-feedback loops among diverse groups of collaborators who build, share and refine models aimed at continually increasing the value of care patients receive through systematic process and outcomes research that cross organizational and geopolitical boundaries. These models should include ones that focus on the whole person (biomedical and psychosocial), social determinants of health (SDH), precision medicine, clinical workflows, population health, finances, and prevention (wellness care) as well as treatment and self-maintenance of chronic conditions.