Implementation of an EMR System for a Comprehensive Dental Service within a Large Regional Hospital Network: Challenges and Opportunities Presented by the Introduction of new Technology.

Abstract

Objectives: The development of new information technology has significant effects on the health care system, and its implementation and the associated change management process can bring some positive changes and gains in understanding, but there are challenges with making the transition. These benefits and challenges are explored in the context of a hospital based dental department. Additionally, the concept of the integration of oral health to overall systemic health is explored in context with an Electronic Medical Records system implementation, and the American Dental Association's recent recognition of dental anesthesiology as a clinical subspecialty.

Method: Qualitative survey of attending dental faculty members of the department, who represent a broad range of dental specialties and experience in private practice, hospital based practice, teaching, and public health practice.

Results: The faculty survey yielded some consistent themes, ranging from enhanced information to make better diagnoses, to challenges in transitioning to EMR, as well as concerns about data security and too much time and effort in front of a computer screen.

Discussion: A brief summary of the history of the stand-alone development of dentistry is given, which contributed to the separate development of dental EMRs from hospital EMRs. The various modalities of clinical care provided by the Department of Dentistry at Advocate Illinois Masonic Medical Center, Chicago, IL are presented to give a scope of the areas of need a successful EMR solution must meet in a hospital based dental setting. Public health aspects are included in the discussion.

Conclusion: Macro level health data sets (ie NHANES, state level datasets) have the potential to be expanded to include more thorough data, combining medical health data and oral health data in the same datasets.