Taking a Team Approach: Keep Up with the EHR with a Training and Optimization Program

Keywords

clinical informatics - electronic health record - burnout - health care workers - organizational culture

Background and Significance

Electronic health records (EHRs) are ubiquitous and have become an essential component of health care delivery in the United States and many other countries. EHRs have the potential to improve patient safety, facilitate population-based care, and prevent duplication of testing and procedures through interoperability.[1] [2] They also have the potential to negatively impact health care workers (HCWs) by creating administrative burdens or shifting administrative tasks from nonclinicians to clinicians, especially when health care organizations (HCOs) do not invest in EHR optimization.[3] [4] Moon et al define EHR optimization as “the ongoing process making the implemented EHR more efficient and usable for end user clinicians that results in improved efficiency in clinicians' practice and satisfaction.”[5] Clinicians spend half of their workday in the EHR, which leaves little time for more meaningful, direct patient care; there is a dose–response relationship between the time spent on meaningful work and burnout in HCWs.[6] [7] [8] [9] [10]

While EHR burden is frequently cited as a cause of HCW burnout,[11] [12] [13] [14] [15] [16] there are several other factors such as organizational culture, leadership values alignment, and job autonomy that also contribute.[17] It is now understood that addressing burnout means more than teaching EHR proficiency or efficiency. It is critical to also tackle larger issues like communication, teamwork, and workflows.[18] [19] Uniquely positioned to address some of these issues are physician informaticist (PI) and information technology (IT) leaders who can impact organizational culture and inform strategic decisions impacting EHR deployment, training, upgrades, and optimizations at the health system level.[20] [21] [22]

In the early years of widespread EHR deployment, training modeled other forms of basic software education which was largely focused on screen personalization and unidirectional “how to” actions: how to order, how to document, how to find information. Prior to EHR deployment, because HCOs had never been forced to contemplate the values of specific workflows unless they supported federal regulations, billing, or compliance, the adage “because I said so” often prevailed. The climate for EHR optimization was similarly bleak with a high bar for achieving software changes unless the change clearly and directly correlated with business metrics such as organizational growth.[23] [24]

In recent years, widespread recognition of HCW burnout as well as studies demonstrating the benefits of robust EHR training and optimization programs (ETOPs),[5] [25] [26] [27] [28] [29] [30] [31] [32] [33] have led more HCOs to invest in these comprehensive programs beyond initial implementation and clinician onboarding. This case review aims to discover how commonly ETOPs are employed, develop an understanding of the strategies, people, and processes they employ, and start a discussion about what types of outcomes are being measured and attained. Specific descriptions and measured outcomes of a variety of ETOPs (such as Sprint, Home for Dinner, and Practice Experience Program [PEP]) have been previously published and were not the focus of this survey.[26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38]

Objectives

This study aimed to better understand ways in which HCOs can impact HCWs experience with the EHR. This descriptive analysis aims to describe the current ETOP landscape with respect to both resourcing and approach.

Methods

A 72-question survey was developed, and responses were collected within the University of Vermont instance of Research Electronic Data Capture (REDCap) software. The project was determined to not meet the federal regulatory definition of research by the University of Vermont Institutional Review Board. It was distributed electronically to HCO leaders in clinical informatics (CMIO/CNIO/Medical Informatics Executive, Associate CMIO/Medical Director of, Clinical/Nurse/PI) through a variety of means including several professional organizational and EHR vendor email listservs, author presentation(s) at national conferences, and personal and professional social media accounts of the authors and author contacts. The survey was voluntary and respondent names were anonymous unless participants preferred to provide their contact information to be direct recipients of survey results.

In the case of multiple responses from the same HCO, the response from the most senior self-reported role was included in the findings because the study's purpose was to obtain the perspective of organizational leaders. Possible discordance between HCOs with multiple responders was not analyzed given the small numbers when compared with the total number of responses. The survey was open for 6 weeks. Data were analyzed using Stata 18 (StataCorp, College Station, TX) and descriptive statistics were applied. Surveys with missing values or incomplete data were included when the determination was made that the partial data available on those surveys contributed to the overall study questions.

Results

Health Care Organization Characteristics

The survey received 193 total responses from 147 distinct HCOs. As seen in [Table 1], most (140/147, 95%) HCO respondents were in the United States and the majority (92/147, 63%) included an academic center. Utilization of a single EHR was most common (131/147, 89%) and Epic was the most frequent EHR in use overall (138/147). Cerner (Oracle Health) was the second most commonly used EHR (15/147). The various HCO sizes were represented, with responses from 67 small (0–3 hospitals) HCOs, 41 medium (4–10 hospitals) HCOs, and 37 large (11+ hospitals) HCOs. Within the large HCO category, two of those surveyed reported that their system included more than 50 hospitals. Seventy-three percent of survey respondents provided their email addresses rather than remaining anonymous.

Table 1 Survey respondent characteristics

Total distinct health care organizations	n = 147
Respondent role
CMIO/CNIO/Medical Informatics Executive	65 (44%)
Clinical/Nurse/Physician Informaticist	45 (31%)
Associate CMIO/Medical Director of Informatics	23 (16%)
Other[a]	14 (9%)
Location
Within the United States	140 (95%)
Outside the United States	7 (5%)
Size of health care organization
Small (0–3 hospitals)	67 (46%)
Medium (4–10 hospitals)	41 (28%)
Large (>11 hospitals)	37 (25%)
Don't know	2 (1%)
Number of EHR systems in use
Single EHR	131 (89%)
More than one EHR	16 (11%)
EHR system(s) in use (select all that apply)
Epic	138
Cerner	15
Other[b]	5
AllScripts	4
Meditech	3
GE	2
McKesson	1

Abbreviation: EHR, electronic health record.

^a Director of oversight, risk, and ethics; medical director; practicing physician; physician builder, former physician informaticist; IT project manager; chief quality officer; project manager; physician assistant, associate director of optimization and clinical informatics; informatics director; trainer; physician champion; program director of analytics and informatics.

^b NexGen, eCW, Athena; CPRS; Systoc (occupational medicine); Athena; Accuro.

Fig. 1 Types of ongoing EHR training offered (n = 101). EHR, electronic health record.

Ongoing Training

Of the 147 survey responses, 69% (101/147) of HCOs offer ongoing EHR training, defined as training programs beyond onboarding and/or implementation. Of the 101 HCOs that offer this type of ongoing training, 52% (52/101) offer an ETOP such as Sprint, Home for Dinner, or PEP ([Fig. 1]).

Electronic Health Record Training and Optimization Programs

Survey responses showed that HCOs offering ETOPs are more likely to be large organizations and less likely to be public, and HCOs that do not offer ETOPs are more likely to have an academic component ([Table 2]). In addition, whether ETOP is offered at an HCO impacts the number of annual hours of dedicated EHR training offered to providers but does not impact the number of annual hours of dedicated EHR training offered to clinical (nurses, medical assistants, or similar roles) or nonclinical staff (registration, patient scheduling, check-in role or similar; [Fig. 2]).

Fig. 2 Annual hours of EHR training offered by HCOs that do and do not offer EHR training and optimization programs (ETOPs). EHR, electronic health record; HCO, health care organization.

Table 2 Characteristics of health care organizations that do and do not offer electronic health record training and optimization programs

	Offers ETOP (n = 51)	Does not offer ETOP (n = 49)
Type of health care organization
Academic component	27 (52%)	35 (71%)
No academic component	24 (48%)	14 (29%)
Type of health care organization
Public	16 (31%)	22 (45%)
Private	35 (69%)	19 (55%)
Health care organization size
Small (0–3 hospitals)	16 (31%)	23 (47%)
Medium (4–10 hospitals)	15 (29%)	13 (27%)
Large (>11 hospitals)	20 (39%)	13 (27%)

Abbreviation: ETOP, electronic health record training and optimization program.

The timing and mode of delivery of ETOPs varied across HCOs but there were some commonalities: 71% (37/52) offer some training sessions during clinic hours, and 86% (44/52) include a virtual component. The survey did not ask how many hours of training sessions were offered to each participant; this has been described elsewhere in the literature.[26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] All HCOs that offer ETOPs reported that the program serves providers, most also serve clinical staff 86% (44/52), and less than half serve nonclinical staff 46% (24/52). ETOP teams are composed of multiple roles that vary by HCO. Nearly all include EHR trainers and provider informaticists and they are less likely to include a project manager ([Table 3]). Of the 52 organizations that have ETOPs, 79% (41/52) offer the program to one clinic or specialty at a time. Of these, the duration varies widely but shorter programs are more common (29 offered for less than 4 weeks, 17 for 2–6 weeks, 7 for more than 6 weeks).

Table 3 Electronic health record training and optimization program characteristics

Number offering ETOPs	n = 52
Audience served by program (select all that apply)
Clinicians/providers	52 (100%)
Clinical staff	44 (85%)
Nonclinical staff	24 (46%)
Timing of ETOP training sessions
Some during patient hours	37 (71%)
Outside of patient hours only	14 (27%)
No response	1 (2%)
ETOP session modality
In person only	7 (13%)
Some virtual component	44 (85%)
No response	1 (2%)
ETOP team composition (select all that apply)
EHR trainer(s)	51 (98%)
Provider informaticist(s)	46 (88%)
Nurse informaticist(s)	34 (65%)
EHR analyst(s)	29 (56%)
Project manager(s)	21 (40%)

Abbreviations: EHR, electronic health record; ETOP, EHR training and optimization program.

Electronic Health Record System Build

Of the 52 HCOs that offer ETOPs, 62% (34/52) complete EHR build as a component of the program; only 50% (17/34) deliver the build within the time constraints of the training and optimization event. EHR analysts (28/34, 82%) and provider builders (30/34, 88%) are the most common ETOP team members who perform EHR builds. Nurse builders (11/34, 32%), trainers (8/34, 24%), and trainer–analyst combined roles (7/34, 21%) were reported as less likely to build in the system. Seventy-four percent (25/34) of programs require all build to pass through IT governance channels. Build strategies in this context were reported as largely similar, with small variations by ETOP team composition ([Fig. 3]). Overall, the least likely strategy to be utilized is “creating a burning platform” (i.e., time-limited sense of urgency as described in Kotter's 8 step change model) for build to get done.[39]

Fig. 3 Relationship between EHR build strategy and ETOP team composition. EHR, electronic health record; ETOP, EHR training and optimization program.

Electronic Health Record Training and Optimization Program Outcomes

Seventy-nine percent (41/52) of the organizations that offer ETOPs reported measuring program outcomes. Of these, the most measured outcome is EHR satisfaction which is measured by 90% (37/41) of organizations, followed by EHR efficiency at 88% (36/41), and provider burnout at 71% (29/41; [Fig. 4]). Of the 29 organizations that reported measuring burnout, just over half reported showing improvement in this outcome.

Fig. 4 EHR training and optimization program outcomes. EHR, electronic health record.

Discussion

The EHR plays a central and continuously expanding role in health care in the United States and abroad, and there is research to support the advantages of ongoing EHR training and optimization for HCWs,[5] [26] [27] [28] [29] [30] [31] [32] [33] including a trend toward reduction in HCW burnout from such efforts.[26] [27] [32] In this survey of the EHR training and optimization landscape at 147 HCOs, we discover variability of program composition and delivery but similarities in reported effectiveness and goals.

Surprisingly, one-third of survey respondents reported that their HCO offered no EHR training beyond onboarding and implementation. Of the 101 HCOs that offer some ongoing training, including those with ETOPs, approximately 50% of their HCWs receive none or less than 1 hour of dedicated EHR training per year. Additionally, nearly three-quarters of ETOPs engage with HCWs at least partially during patient care hours. In our experience, this can lead to shortened and sometimes hurried training sessions due to the inherent unpredictability of the clinical time and space. In 2019, a study of 72,000 EHR users found that investment in training was critical to end-user EHR satisfaction, and the authors suggested that 3 to 5 hours of EHR training per year for HCWs was optimal.[29] When considering frequent upgrades and optimizations as well as high HCW turnover, HCOs that use ETOPs for ongoing training need to have consistent funding to revisit clinical sites on a regular cadence to accomplish these goals. Given the continuously evolving nature of both clinical care and the health IT required to support it, we call on HCO leaders to resist focusing on lost clinical revenue incurred from ongoing EHR training and optimization and instead consider the time spent by HCWs to be important for their clinical efficiency, EHR satisfaction, overall well-being, and ultimately the best interests of the HCO. One-third of survey respondents who do offer ongoing training reported that their HCO does not invest in formal ETOPs. In 2018, Moon et al reported that “dedicated resources were the biggest facilitator and the second biggest barrier to [EHR] optimization.”[5] Some smaller HCOs cite the prohibitive cost of investing in these programs, but using a number of hospitals as a surrogate for HCO size, we find the presence of ETOPs in our survey to be well-distributed among HCOs of varying size. At UCHealth, the cost of a 10-person, dedicated, multidisciplinary Sprint team that provides intervention to 1,000 clinicians and staff each year costs $1.2 million per year. At the University of Vermont Health Network, the Sprint team and associated cost is simply scaled down by half (5 team members, serves 450 clinicians and staff per year). While the investment in ETOPs can be scaled to the size of the HCO, the $500,000 to 1 million cost of replacing one burned-out physician is fixed.[40]

The value proposition for elevating end-user and care team voice in the EHR goes beyond the Return on Investment (ROI) on HCW burnout; PIs often lead ETOPs and have a sphere of influence that extends outside of IT and into the clinical and operational leadership of HCOs.[41] [42] For this reason, they are well-positioned to empathize, engage, and promote change within an HCO.[43] [44] Training for PIs is variable, so it is not surprising to find that ETOPs that include PIs were employing basic principles of informatics such as starting with the why, creating a burning platform, facilitating productive conversations, and building relationships only 50% of the time. Perhaps more intriguing is that ETOP teams that include IT analysts use these tactics more than 50% of the time. Despite this finding, ETOPs were more likely to employ PIs (90%, 46/51) than IT analysts (57%, 29/51). Survey numbers were insufficient to provide an analysis of team member composition and program success, though based on prior findings from KLAS Arch Collaborative, it is likely that the specific composition of the program team matters less than the goals, philosophy, and general approach.[45] [46] In our opinion, this should include at a minimum trainers and analysts with a clinical background whenever possible, a project manager, and a physician or clinical informaticist leader who is attentive to problems and working to implement interventions that fit within the organizational culture. In this survey, we noted that only 60% of ETOPs conducted workflow analysis and optimization and only 56% offered EHR build as part of their program.

The most commonly measured outcome for ETOPs is EHR satisfaction, which was measured 90% of the time and showed improvement in all cases. This was followed closely by EHR efficiency, measured 88% of the time, and when measured, was reported to improve 78% of the time. Burnout was measured by two-thirds of ETOPs. Since drivers of burnout are varied and multifaceted (including but not limited to efficiency of practice, resources, organizational culture/values, control, flexibility, meaning in work, workload, specific job demands, work–life integration, social support, and community work) and require complex intervention,[17] [47] [48] it is notable that half of the ETOPs measuring burnout report an improvement ([Fig. 4]). EHR training alone primarily addresses EHR efficiency and proficiency, and to impact other drivers of burnout, we need high-performing teams who can meet HCWs where they are and move them forward.

Despite the inherent complexity of HCW burnout, it is encouraging that many HCOs that offer ETOPs are measuring burnout and most that measured reported finding improvement. One possibility is that the mere existence of an ETOP with clearly stated goals of reducing EHR burden may function to impact burnout both directly (by improving EHR satisfaction and efficiency) and indirectly, by recognizing and validating HCWs, demonstrating organizational level shared core values, and offering professional development opportunities.[48]

Several factors are likely contributing to this proposed indirect impact. First, most ETOPs bring a large and coordinated group of resources to HCWs, rather than asking unsatisfied and burned-out HCWs to independently seek help. Second, the intensive training sessions with a focus on personalization that are characteristic of ETOPs empower HCWs to change their relationship with the EHR by imparting both practical knowledge and self-help strategies that allow participants to get top-of-mind questions answered and complaints aired, which helps reclaim control over the ways the technology is used to deliver care. Lastly, successful problem-solving of inefficient EHR workflows as a clinical and operational team under the guidance of ETOP leadership can lead to improvements in organizational culture. We have seen this occur when the cycle of depersonalization and hopelessness inherent in HCW burnout[48] is broken and the clinical and operational team in a clinical setting starts to drive together toward the improvement of both EHR and non-EHR-related challenges. In this way, solving a relatively small EHR-related problem opens the door for team formation and alignment. Trends toward improved teamwork have been described,[26] and the measurement of whether ETOPs can improve health care team functioning and performance is an important area for ongoing study. Using this framework, we can start to expand from the Institute of Medicine concept of the EHR as an essential component of the “learning health care system”[49] and consider that the lessons learned from impacting change within EHR-related workflows can serve as a model for making changes in the health care delivery system as a whole.

Limitations

Survey distribution through informal professional networks and electronic communication groups such as email listservs, does not allow for a survey response rate calculation. There is no single list of unique HCOs nationwide (especially given the current environment of frequent mergers and acquisitions in U.S.-based HCOs) and no definitive list of informatics executives at each HCO. The American Hospital Association approximates that there are 404 “health systems” (broadly defined as either a multihospital system of two or more hospitals or a single diversified hospital system of one hospital and three or more pre- or postacute HCOs) in the United States.[50] Using this estimate, the survey response rate for U.S. HCOs is 35% (140/404). There were also seven international respondents; it would be nearly impossible to generate a response rate for this subset. An additional limitation is this heavy skewing toward U.S. HCOs and HCOs where Epic is the EHR in use. Response bias is also possible given that those who feel most opinionated or invested in either the authors (due to a prior professional relationship or collaboration on an ETOP) or the survey topic as evidenced by the title (“Keeping up with the EHR”) as it came into their email inbox were more likely to take the time to respond. An additional limitation is that the process for ensuring nonduplication of specific HCOs relied on including the responses from the most senior role; this is therefore a functional rather than statistical method for de-duplication of responses. Lastly, there is a wide variety of clinical informatics programs and ETOPs around the country such that drawing direct comparisons between them is difficult. The survey was not exhaustive in collecting ETOP details. For example, it was not asked whether the ETOP was mandatory or optional, or whether clinician time to participate was “protected” or compensated. Both of these factors could have a significant impact on program outcomes and costs. We have therefore attempted to summarize and extract thematic patterns in a descriptive manner rather than undertake a quantitative exercise of statistical analysis.

Conclusion

ETOPs are a promising intervention to enhance HCW experience with the EHR and to reduce burnout. Additional research is needed to identify the optimal team composition, delivery method, and outcomes of ETOPs.

Clinical Relevance Statement

This study suggests that ETOPs can have a positive impact on physicians by improving their satisfaction and efficiency with the EHR and potentially reducing burnout. ETOPs may have both direct and indirect effects on physician burnout by driving organizational culture toward teamwork and flexible problem-solving. PIs, uniquely situated in the space between clinical, operational, and IT components of HCOs, are key drivers of these programs.

Multiple-Choice Questions

Question 1: What proportion of surveyed HCOs offer some ongoing EHR training beyond onboarding and implementation?

• All of them.

• One-third

• Two-thirds

• None of them.

Correct Answer: The correct answer is option c. Approximately two-thirds of surveyed HCOs offer some ongoing EHR training.

Question 2: What was the most commonly measured outcome for ETOPs?

• HCW burnout

• EHR satisfaction

• EHR efficiency

• No outcomes were measured.

Correct Answer: The correct answer is option b. Ninety percent of HCOs that offer ETOPs measured EHR satisfaction as an outcome of the program.

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