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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.

Objectives

Use of certain components of electronic health records (EHRs), such as EHR-based alerting systems (EASs), might reduce provider satisfaction, a strong precursor to turnover. We examined the impact of factors likely to influence providers’ acceptance of an alerting system, designed to facilitate electronic communication in outpatient settings, on provider satisfaction, intentions to quit, and turnover.

Study Design and Methods

We conducted a cross-sectional Web-based survey of EAS-related practices from a nationwide sample of primary care providers (PCPs) practicing at Department of Veterans Affairs (VA) medical facilities. Of 5001 invited VA PCPs, 2590 completed the survey.

We relied on Venkatesh’s Unified Theory of Acceptance and Use ofTechnology to create survey measures of 4 factors likely to impact user acceptance of EAS: supportive norms, monitoring/ feedback, training, and providers’ perceptions of the value (PPOV) of EASs to provider effectiveness. Facility-level PCP turnover was measured via the VA’s Service Support Center Human Re- sources Cube. Hypotheses were tested using structural equation modeling.

Results

After accounting for intercorrelations among predictors, monitoring/feedback regarding EASs significantly predicted intention to quit (b = 0.30, P <.01), and PPOV of EASs predicted both overall provider satisfaction (b = 0.58, P <.01) and facility-level provider turnover levels (b = –0.19, P <.05), all without relying on any intervening mechanisms.

Conclusions

Design, implementation, and use of EASs might impact provider satisfaction and retention. Institutions should consider strategies to help providers perceive greater value in these clinical tools.

Am J Manag Care. 2014;20(11 Spec No. 17):SP520-SP530


How electronic health record (EHR)-based alerting systems are implemented, accepted, and used in real-world clinical settings can impact not just quality of care, but also provider satisfaction and retention.

  • Our study is the first to our knowledge to link provider perceptions of the value of EHR-based alert notifications to actual turnover in a large national sample.
  • When providers do not perceive EHR features to be of high value to their practice, they can become dissatisfied with their work.
  • EHR-based alerting systems could become catalysts for turnover, unless providers clearly understand their value for delivering high-quality care effectively and efficiently.

Retaining primary care providers (PCPs) is critical to ensuring healthcare access and quality. However, PCPs are moving to other specialty areas or leaving medicine altogether, a significant threat to high-quality care in many US regions.1-4 Recent healthcare legislation and initiatives such as the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the Affordable Care Act of 2010, and the Patient-Centered Medical Home make explicit resource provisions such as training, additional staff, and resources to implement electronic health records (EHRs), all of which could make primary care more attractive.5-7 While PCPs’ decisions to seek alternate employment might be determined by a multitude of factors,8 provider dissatisfaction with the implementation and meaningful use of EHRs9 may pose unique retention challenges despite the HITECH Act’s strong incentives for their use.

Implementing a full-service EHR constitutes a major organizational intervention; it presents a significant change in clinician-to-clinician communication and in some instances can require additional skills beyond those that were needed in paper-based systems to deliver care of comparable quality.10,11 For example, providers spend an average of 49 minutes per day reviewing and responding to electronic alert notifications, yet nearly half of these notifications do not contain messages that providers perceive to contain “high value” information.12 This volume of information is significantly higher than what would be expected in a paper system (given the additional resources involved with physical mail and messaging), and thus requires a different work strategy for accurate and timely handling. In addition, research has also shown marked differences in workflow efficiency of paper-based versus EHR13-15; paper-based clinical information often gets “lost in the shuffle” and becomes untrackable.16,17 The needed changes in communication and work flow attributable to EHR use are significant enough that despite their benefits, 12% of pediatric urologists reported they would retire if EHR use were mandated.18

Recent research has demonstrated a relationship between the use of health information technology (HIT) and physician satisfaction,9 although different components

of HIT have different effects on physician satisfaction. For example, compared with traditional, paper-based forms of communication, PCPs who communicated electronically with patients and other providers, and who shared their visit notes electronically with patients, were more likely to report higher satisfaction levels19; in contrast, PCPs who wrote prescriptions electronically were less likely to report high satisfaction levels.20 Ensuring physicians’ satisfaction with their work is important because poor satisfaction often leads to several undesirable results, including turnover, mental health concerns (eg, anxiety, depression, burnout), poorer relationships with patients, and reduced quality of care.21


Within the Accountable Care Organization model, EHRs are expected to facilitate communication and coordination, especially in the outpatient setting.22 Increasingly, practices are relying on EHR-based alerting systems (EASs) within their EHR to track, route, and communicate clinical information such as test results.23 This electronic communication may occur through an “asynchronous” alert notification inbox, much like email, where the sender and recipient need not be simultaneously engaged. Notifications transmitted through these systems could include test results, referrals, status updates on patients, and other provider-to-provider communications. Although many commercial EHRs already feature EASs functionality for communication, its use is expected to grow. For example, results management is one of the core EHR functionalities24 and key criteria for achieving Stage 2 meaningful use25 due to its potential to reduce lag time in recognition and treatment of medical problems, reduce redundant testing, and improve appropriate and timely follow-up. Unlike other EHR components, how- ever, the impact of EASs on provider satisfaction and turnover is not well documented.

PCPs’ utilization of EHR-based EASs has become an integral job characteristic, especially because PCPs utilizing EASs tend to spend significant amounts of time interfacing with them.12,26-28 Consequently, problems related to EASs could potentially impact PCP job attitudes such as satisfaction and intentions to quit, both known ante- cedents of turnover.29 For example, our previous research suggests providers using EASs receive an average of 56 to 63 alert notifications per day12,22,30; in addition, providers do little to customize their alerts interface to optimize efficiency and effectiveness. Rather, they employ varying strategies for managing these notifications, with mixed success,31 leading to information overload.32

PCPs have requested new visualization tools such as color coding and advanced filtering to address some of these problems.33 Thus, without modifications, EASs use could lead to a combination of high-volume, low-value work that could function as a driver of turnover for PCPs, rather than a source of retention. As there is no prior research that explores the relationship between EHR variables and provider outcomes, our objective was to conduct an initial examination to identify how providers’ perceptions of the use of EASs may impact their satisfaction and intention to quit. This research could inform strategies about how those perceptions could be altered if needed, and can also serve as a stepping-stone for the integration of EHR research with turnover research.

METHODS

Conceptual Model

To answer our research questions, we took guidance from 2 theoretical models to ultimately derive the model depicted in Figure 1. The Job Demands Resource Model of burnout (JDRM)34 posits that job demands (ie, aspects of the job such as, potentially, the use of EASs) that require sustained physical or mental effort and lead to increased workload can lead to negative outcomes such as low satisfaction, intentions to quit one’s job, and eventually actual turnover. The model further proposes that job resources (ie, aspects of the job that are functional in achieving work goals) that reduce job demands, or stimulate personal growth and development, relate to positive attitudinal outcomes and lower levels of withdrawal.

With respect to EASs, it is unclear whether PCPs perceive EASs as a demand or a resource. The second model, Venkatesh’s Unified Theory of Acceptance and Use of Technology (UTAUT),35 sheds some light on what may drive this decision for providers. The UTAUT proposes several factors that could impact the aforementioned outcomes; among these are performance expectancy (the extent to which the user believes the system will help attain gains in performance); social influence (the extent to which the user perceives that important others, such as family and friends, believe the system should be used), and facilitating conditions (the extent to which the user perceives that technical and organizational resources exist to support system use). We thus examined 4 specific examples of the types of factors proposed by Venkatesh and their impact on physician satisfaction, intention to quit, and turnover: (1) EAS-supportive norms, such as the extent to which colleagues use and see value in the notifications (an example of social influence), (2) whether providers receive feedback about their use of EASs, (3) whether providers receive training on the use of notifica- tions (both examples of facilitating conditions), and (4) the perceived contribution of EASs to provider effectiveness (an example of performance expectancy, henceforth referred to as provider perceptions of value [PPOV]). Based on the JDRM and UTAUT, we hypothesized that each of the 4 factors will positively impact provider satisfaction, and inversely relate to intention to quit. Furthermore, intention to quit and provider satisfaction will significantly impact turnover.

Design

The present study is part of a larger cross-sectional Web-based survey of EAS practices conducted between June and November 2010 on a nationwide sample of PCPs practicing at Department of Veterans Affairs (VA) medical facilities.30,32,33


Setting

 
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