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Electronic Alerts and Clinician Turnover: The Influence of User Acceptance
Sylvia J. Hysong, PhD; Christiane Spitzmuller, PhD; Donna Espadas, BS; Dean F. Sittig, PhD; and Hardeep Singh, MD, MPH
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Electronic Alerts and Clinician Turnover: The Influence of User Acceptance

Sylvia J. Hysong, PhD; Christiane Spitzmuller, PhD; Donna Espadas, BS; Dean F. Sittig, PhD; and Hardeep Singh, MD, MPH
Users' acceptance of electronic health record-based asynchronous alerts can negatively impact provider satisfaction, intentions to quit, and ultimately turnover.
Final model. An important feature of the original model is that the factors in the model were considered orthogonal, independent predictors of satisfaction, intention to quit, and turnover. Bivariate correlations, however, suggested this was an incorrect assumption. Consequently, based on the initial model results and the simple bivariate correlations, we trimmed unnecessary relationships from the model, and allowed the predictors to covary. The resulting model showed good fit (RMSEA = 0.04, PCLOSE = 0.47), and is presented in Figure 1 (depicted by the green and red lines). As can be seen from the figure and consistent with the bivariate correlations analyses, the 4 factors are significantly correlated, and thus cannot be treated as independent predictors of pro- vider satisfaction. After accounting for intercorrelations amongst the independent variables, monitoring/feed- back significantly predicted intention to quit (b = 0.30, P <.01), and PPOV predicted both provider satisfaction b = 0.58, P <.01) and facility level turnover (b = –0.19, P <.05), all without relying on either provider satisfaction or intention to quit as intermediary mechanisms. Of note, high levels of monitoring and feedback were associated with increased intentions to quit.


This study sought to examine the impact of user acceptance factors of electronic health record-based alert notification systems on the satisfaction, intentions to quit, and turnover of providers who used them. Contrary to existing theory (both the JDRM and the UTAUT), we found that monitoring/feedback on EASs practices, training on the use of EASs, and supportive norms about EAS had little impact on provider satisfac- tion. However, monitoring/feedback were associated with increased intention to quit.

Our results suggest that EASs, and by extension EHRs, could become catalysts for turnover, unless providers clearly understand their value to delivering high-quality care effectively and efficiently. As evidenced by the non-significant relationships between monitoring/feedback and provider satisfaction, as well as the nonsignificant relationship between training and both satisfaction and intention to quit, our data suggest that the aforementioned facilitating conditions may be insufficient to accomplish this goal, though we have no specific details in our data about the quality of the feedback or training. More importantly, when providers do not perceive the value of these electronic aids to their practice, they might become dissatisfied with their work environment, and potentially seek work elsewhere altogether.

EASs likely represent one of the most frustrating components of EHRs for providers54-56—compared with paper communication systems, they are perceived to “increase the number of work items, inflate the time to process each, and divert work previously done by office staff to them.”57 Other work has shown that providers perceive many of the alerts they receive to be unnecessary,58 and has documented variable physician ac- ceptance of features like computerized reminders and electronic alerts.59 Therefore, future work should target the problem from multiple angles, such as content and design of feedback, effectiveness of training, and social influence factors, in addition to already ongoing efforts to optimize EAS design, so that it is inherently perceived as valuable by providers. The United States already has a shortage of primary care providers,2 and research shows dissatisfied providers are both leaving primary care for other specialties and/or leaving medi- cine completely.3

Several possible reasons might exist to explain the positive effect of monitoring/feedback on intention to quit. First, participants might have reacted more strongly to the monitoring aspect than to the feedback aspect of this construct. Second, the nature of the feedback provided could minimize feedback’s impact on satisfaction. Feedback characteristics can have a significant impact on its effectiveness at changing cognitions and behavior.60,61 Our ongoing research in another domain has found that feedback is often delivered primarily via written reports providing only numeric scores without correct solution information62 (one of the most powerful single characteristics of feedback interventions).60,61 Third, both feedback delivery mechanisms and providers’ perceptions of being monitored constantly by the organization could have led to the observed result.

In contrast, PPOV showed a direct positive relation- ship to provider satisfaction (providers who perceived greater value in electronic notifications were more likely to be satisfied); a direct negative relationship to turnover (providers who perceived greater value in electronic notifications were less likely to quit); and an indirect link to intention to quit via provider satisfaction (providers who perceived greater value in alert notifications were more likely to be satisfied, and in turn less likely to express intentions to quit.) The relationship between provider satisfaction and intention to quit is not surprising, as it has been well documented in the literature.63,64 The more novel finding in this research is the direct, negative relationship between PPOV and turnover (ie, providers at facilities with higher provider turnover rates have lower perceptions of value for EASs). We are not aware of any studies directly linking these types of perceptions to actual turnover, particularly at the organizational level with a national sample as large as this one: 2590 respondents at 131 facilities. From a scientific perspective, this finding links the JDRM and UTAUT: if users do not perceive EASs to be of value, EASs are more likely to be considered a demand rather than a resource (and thereby less likely to be accepted), thus leading to increased turnover. From a practical perspective knowing that EASs have to be perceived as performance enhancing by physicians in order for them to not nega- tively affect turnover should signal facility leadership to take care regarding how such systems are designed, marketed within the facility, and supported.

In addition to this important finding, we are also not aware of any studies simultaneously examining the ef- fects of satisfaction, intention to quit, and turnover in the healthcare setting. Understanding the interrelationships among user acceptance of technological tools intended to help providers, factors that impact this acceptance, and provider outcomes can help the design and implementation of HIT tools with which providers will want to work.


The study was conducted within the VA system, representing one of the largest and most sophisticated healthcare systems in the United States. Hence, in the spirit of constructive replication and to enhance external validity, we recommend that our findings be replicated in subsequent studies at other facilities without centralized organizational structure. Nevertheless, alerting systems such as the one we studied are being increasingly used across commercial EHRs. Second, the structure of the archival turnover data obtained for this study limits turnover analysis over time and prevents the application of statistical techniques such as survival analysis that lead to the most informative results for turnover-type data. Third, our sample consisted of employees who were all using the same EAS-capable EHR, limiting our ability to generalize results to other commonly used EAS-capable EHR systems (eg, Epic Systems, Verona, Wisconsin) that are officially certified (by an Office of the National Coordinator for Health Information Technology-Authorized Testing and Certification Body). Hence, we recommend that future research focus on more heterogeneous samples, examining different types of EASs and EHRs. Finally, although this study identified a new, very specific source of dissatisfaction and potential turnover among providers, future studies should examine the incremental contribution of this source in the context of more traditional predictors of provider satisfaction such as supervisory relations, availability of resources, and work environment condi- tions.65,66 We further encourage future research to closely investigate how providers’ perceptions of EHR variables develop over time, and whether system characteristics or more distal factors (eg, supervisory behavior) impact these perceptions.


We conclude that designing and implementing EHR-based notification systems effectively may no longer simply be assumed to be an antecedent to efficiency, safety, or quality of care; how these systems are implemented, accepted, and used in real-world practice, as our research shows, might also impact provider satisfaction and retention. Given the recent HITECH stimulus and the new healthcare law, EHRs will be a reality nationwide in a few short years and will connect members of the healthcare team like never before. In fact, one reason for the heavy emphasis on EHR adoption is to improve communication. Depending on how the EHR is designed and implemented, it can become a source of competitive advantage (or turnover) for clinical practices. In addition, how an organization creates and manages its internal policies can make or break both the safety and efficiency of the clinicians’ work. As EHRs become more widespread and providers increasingly communicate clinical information through EASs, institutions should consider strategies to help providers perceive greater value in these vital clinical tools.

Author Affiliations: Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX; Baylor College of Medicine, Houston, TX (SJH, DE, HS); University of Houston, TX (CS); University of Texas Health Science Center at Houston, (DFS).

Source of Funding: This work was supported by the VA National Cen- ter of Patient Safety and partially supported by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (#CIN 13-413).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (SJH, CS, HS, DFS); acquisition of data (SJH, CS, DE, DFS, HS); analysis and interpretation of data (SJH, CS, DE, DFS, HS); drafting of the manuscript (SJH, CS, DE, DFS, HS); critical revision of the manuscript for important intellectual content (SJH, CS, DFS, HS); statistical analysis (SJH, CS); obtaining funding (HS); administrative, technical or logistic support (SJH, CS, DE, DFS); and supervision (HS).

Address correspondence to: Sylvia J. Hysong, PhD, Center for Innovations in Quality, Effectiveness and Safety (152), Michael E. DeBakey VA Medical Center, 2002 Holcombe Blvd, Houston, TX 77030. E-mail:

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