Summary
Just as researchers and clinicians struggle to pin down the benefits attendant to
health information technology (IT), management scholars have long labored to identify
the performance effects arising from new technologies and from other organizational
innovations, namely the reorganization of work and the devolution of decision-making
authority. This paper applies lessons from that literature to theorize the likely
sources of measurement error that yield the weak statistical relationship between
measures of health IT and various performance outcomes. In so doing, it complements
the evaluation literature’s more conceptual examination of health IT’s limited performance
impact. The paper focuses on seven issues, in particular, that likely bias downward
the estimated performance effects of health IT. They are 1.) negative self-selection,
2.) omitted or unobserved variables, 3.) mis-measured contextual variables, 4.) mismeasured
health IT variables, 5.) lack of attention to the specific stage of the adoption-to-use
continuum being examined, 6.) too short of a time horizon, and 7.) inappropriate units-of-analysis.
The authors offer ways to counter these challenges. Looking forward more broadly,
they suggest that researchers take an organizationally-grounded approach that privileges
internal validity over generalizability. This focus on statistical and empirical issues
in health IT-performance studies should be complemented by a focus on theoretical
issues, in particular, the ways that health IT creates value and apportions it to
various stakeholders.
Keywords
Health information technology - electronic health records - research methods - organizational
behavior
