Abstract
Purpose: To summarize key issues in the eHealth field from an implementation science perspective and to highlight illustrative processes, examples and key directions to help more rapidly integrate research, policy and practice. Methods: We present background on implementation science models and emerging principles; discuss implications for eHealth research; provide examples of practical designs, measures and exemplar studies that address key implementation science issues; and make recommendations for ways to more rapidly develop and test eHealth interventions as well as future research, policy and practice. Results: The pace of eHealth research has generally not kept up with technological advances, and many of our designs, methods and funding mechanisms are incapable of providing the types of rapid and relevant information needed. Although there has been substantial eHealth research conducted with positive short-term results, several key implementation and dissemination issues such as representativeness, cost, unintended consequences, impact on health inequities, and sustainability have not been addressed or reported. Examples of studies in several of these areas are summarized to demonstrate this is possible. Conclusions: eHealth research that is intended to translate into policy and practice should be more contextual, report more on setting factors, employ more responsive and pragmatic designs and report results more transparently on issues important to potential adopting patients, clinicians and organizational decision makers. We outline an alternative development and assessment model, summarize implementation science findings that can help focus attention, and call for different types of more rapid and relevant research and funding mechanisms.
| Original language | English (US) |
|---|---|
| Pages (from-to) | e1-e11 |
| Journal | International Journal of Medical Informatics |
| Volume | 83 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2014 |
Funding
Implementation science (IS) can address the above issues by studying the multi-level eHealth implementation context [13] , participatory implementation process [14] , and intervention effects. Harmonized practical measures [15,16] and IS models and frameworks can be used in the design and evaluation of eHealth interventions to better understand contextual and setting factors, employ more responsive and pragmatic designs, and report results and issues important to potential adopting patients, clinicians and organizational decision makers [14,17–19] . Additionally, the surge of eHealth technology and development of new innovations far outpaces traditional research trajectories. As can be seen in Fig. 1 a [20] (modified from Riley et al., in press) the typical research timeline in eHealth and most other scientific areas, is relatively slow and incongruent with the speed of technological advancement. Currently, an eHealth grant funded under standard NIH mechanisms (optimistically assuming funding upon the initial submission) would take a total of approximately 6–7 years before publications are available. The content of this research is likely to be considerably dated, if not rapidly obsolete. As exhibited in the figure, many fundamental innovations and widespread platforms would not be possible to study given the current research timelines.
Keywords
- EHealth
- Implementation science
- Internet
- MHealth
- Methodology
- Recommendations
- Review
ASJC Scopus subject areas
- Health Informatics
