Background and Objective The Health Information Technology for Economic and Clinical Health (HITECH) Act has distributed billions of dollars to physicians as incentives for adopting certified ...electronic health records (EHRs) through the meaningful use (MU) program ultimately aimed at improving healthcare outcomes. The authors examine the extent to which the MU program impacted the EHR adoption curve that existed prior to the Act.
Methods Bass and Gamma Shifted Gompertz (G/SG) diffusion models of the adoption of “Any” and “Basic” EHR systems in physicians’ offices using consistent data series covering 2001–2013 and 2006–2013, respectively, are estimated to determine if adoption was stimulated during either a PrePay (2009–2010) period of subsidy anticipation or a PostPay (2011–2013) period when payments were actually made.
Results Adoption of Any EHR system may have increased by as much as 7 percentage points above the level predicted in the absence of the MU subsidies. This estimate, however, lacks statistical significance and becomes smaller or negative under alternative model specifications. No substantial effects are found for Basic systems. The models suggest that adoption was largely driven by “imitation” effects (q-coefficient) as physicians mimic their peers’ technology use or respond to mandates. Small and often insignificant “innovation” effects (p-coefficient) are found suggesting little enthusiasm by physicians who are leaders in technology adoption.
Conclusion The authors find weak evidence of the impact of the MU program on EHR uptake. This is consistent with reports that many current EHR systems reduce physician productivity, lack data sharing capabilities, and need to incorporate other key interoperability features (e.g., application program interfaces).
Introduction Electronic cigarettes (e-cigarettes) are gaining in popularity as an alternative to regular cigarettes, as they are viewed as potentially less harmful. However, it remains unclear how ...awareness about e-cigarettes is permeating through the general U.S. population. This study seeks to extend previous research and examine trends in e-cigarette awareness and perceived harmfulness, and their association with smoking-cessation efforts. Methods Data from three cycles (2012, 2013, and 2014) of the Health Information National Trends Survey were combined into a single data set. Controlling for survey year, multivariate logit models were used to determine the association between demographic characteristics and e-cigarette awareness, perceived harmfulness, quit attempts, and quit intentions. Data were analyzed in 2015. Results Awareness of e-cigarettes increased from 77.1% in 2012 to 94.3% in 2014. Controlling for demographic characteristics, e-cigarette awareness significantly increased in both 2013 and 2014, relative to 2012. Perception that e-cigarettes were less harmful than regular cigarettes declined from 50.7% in 2012 to 43.1% in 2014. Among smokers, no relationship was observed between e-cigarette awareness and past-year quit attempts or quit intentions, but those that viewed e-cigarettes as less harmful were less likely to have a past-year quit attempt. Conclusions These analyses reveal a continued increase in overall public awareness of e-cigarettes and shifting harm perceptions relative to regular cigarettes. New regulatory oversight by the U.S. Food and Drug Administration may have major effects on both dimensions, which are worth continued monitoring.
The Meaningful Use (MU) program has promoted electronic health record adoption among US hospitals. Studies have shown that electronic health record adoption has been slower than desired in certain ...types of hospitals; but generally, the overall adoption rate has increased among hospitals. However, these studies have neither evaluated the adoption of advanced functionalities of electronic health records (beyond MU) nor forecasted electronic health record maturation over an extended period in a holistic fashion. Additional research is needed to prospectively assess US hospitals' electronic health record technology adoption and advancement patterns.
This study forecasts the maturation of electronic health record functionality adoption among US hospitals through 2035.
The Healthcare Information and Management Systems Society (HIMSS) Analytics' Electronic Medical Record Adoption Model (EMRAM) dataset was used to track historic uptakes of various electronic health record functionalities considered critical to improving health care quality and efficiency in hospitals. The Bass model was used to predict the technological diffusion rates for repeated electronic health record adoptions where upgrades undergo rapid technological improvements. The forecast used EMRAM data from 2006 to 2014 to estimate adoption levels to the year 2035.
In 2014, over 5400 hospitals completed HIMSS' annual EMRAM survey (86%+ of total US hospitals). In 2006, the majority of the US hospitals were in EMRAM Stages 0, 1, and 2. By 2014, most hospitals had achieved Stages 3, 4, and 5. The overall technology diffusion model (ie, the Bass model) reached an adjusted R-squared of .91. The final forecast depicted differing trends for each of the EMRAM stages. In 2006, the first year of observation, peaks of Stages 0 and 1 were shown as electronic health record adoption predates HIMSS' EMRAM. By 2007, Stage 2 reached its peak. Stage 3 reached its full height by 2011, while Stage 4 peaked by 2014. The first three stages created a graph that exhibits the expected "S-curve" for technology diffusion, with inflection point being the peak diffusion rate. This forecast indicates that Stage 5 should peak by 2019 and Stage 6 by 2026. Although this forecast extends to the year 2035, no peak was readily observed for Stage 7. Overall, most hospitals will achieve Stages 5, 6, or 7 of EMRAM by 2020; however, a considerable number of hospitals will not achieve Stage 7 by 2035.
We forecasted the adoption of electronic health record capabilities from a paper-based environment (Stage 0) to an environment where only electronic information is used to document and direct care delivery (Stage 7). According to our forecasts, the majority of hospitals will not reach Stage 7 until 2035, absent major policy changes or leaps in technological capabilities. These results indicate that US hospitals are decades away from fully implementing sophisticated decision support applications and interoperability functionalities in electronic health records as defined by EMRAM's Stage 7.
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