Sprint-inspired One-on-One Post-Go-Live Training Session (Mini-Sprint) Improves Provider Electronic Health Record Efficiency and Satisfaction

Abstract

Background Inefficient electronic health record (EHR) usage increases the documentation burden on physicians and other providers, which increases cognitive load and contributes to provider burnout. Studies show that EHR efficiency sessions, optimization sprints, reduce burnout using a resource-intense five-person team. We implemented sprint-inspired one-on-one post-go-live efficiency training sessions (mini-sprints) as a more economical training option directed at providers.

Objectives We evaluated a post-go-live mini-sprint intervention to assess provider satisfaction and efficiency.

Methods NorthShore University HealthSystem implemented one-on-one provider-to-provider mini-sprint sessions to optimize provider workflow within the EHR platform. The physician informaticist completed a 9-point checklist of efficiency tips with physician trainees covering schedule organization, chart review, speed buttons, billing, note personalization/optimization, preference lists, quick actions, and quick tips. We collected postsession survey data assessing for net promoter score (NPS) and open-ended feedback. We conducted financial analysis of pre- and post-mini-sprint efficiency levels and financial data.

Results Seventy-six sessions were conducted with 32 primary care physicians, 28 specialty physicians, and 16 nonphysician providers within primary care and other areas. Thirty-seven physicians completed the postsession survey. The average NPS for the completed mini-sprint sessions was 97. The proficiency score had a median of 6.12 (Interquartile range (IQR): 4.71–7.64) before training, and a median of 7.10 (IQR: 6.25–8.49) after training. Financial data analysis indicates that higher level billing codes were used at a greater frequency post-mini-sprint. The revenue increase 12 months post-mini-sprint was $213,234, leading to a return of $75,559.50 for 40 providers, or $1,888.98 per provider in a 12-month period.

Conclusion Our data show that mini-sprint sessions were effective in optimizing efficiency within the EHR platform. Financial analysis demonstrates that this type of training program is sustainable and pays for itself. There was high satisfaction with the mini-sprint training modality, and feedback indicated an interest in further mini-sprint training sessions for physicians and nonphysician staff.

 

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Keywords

electronic health records - EHR usability - training - physician informaticist - sprint - burnout - provider satisfaction - efficiency

Background and Significance

Parallels are often drawn between the airline industry and health care.[1] More often than not, the focus is on safety: air accidents are major events, but when set against the millions of miles and hours flown, the industry's record is exemplary. Our study also emulates an aspect of this safe industry, on training and the complexity of technology. To the uninitiated, a cockpit presents a bewildering array of dials, levers, and controls. Becoming a pilot means learning to read the dials and to synthesize their message, and then knowing what to touch to operate the right controls. Novices are trained by experienced pilots, in simulators first and then in training aircraft. A “sprint” training program represents an intensive engagement between an expert physician informaticist (PI) and the provider trainee who is insufficiently familiar with the electronic health record (EHR).[2] [3] [4] [5] [6] The process of streamlining tasks and resolving problems in the EHR through the use of clinical informatics and technology resources is known as EHR optimization.[7] EHR optimization is necessary to reduce physician burnout, which is costly to the health care system medically and financially.[8] [9] [10] [11] [12] [13] [14] [15] A personalized EHR layout reduces physicians' cognitive load, as the complexity of the standard EHR layout places a cognitive burden on the user.[16] This also decreases information siloing, allowing physicians to more easily access the information stored in the EHR.[17]

Inefficient EHR usage and computerized documentation requirements add to the time demands on physicians, often requiring physicians to work after hours.[18] [19] [20] Physicians report that numerous factors of EHR use are associated with stress and burnout, including excessive data entry requirements, inaccessibility of information, interference with work–life balance, and problems with posture and pain.[21] [22] [23] [24] The American Medical Informatics Association has launched a program to reduce EHR time to 25% within the next 5 years.[25] The 25 × 5 program aims for the use of strategic initiatives to reduce burden within U.S. health care organizations through the adoption and utilization of task force tools and exemplars' solutions. Alternative training is necessary to improve EHR efficiency and reduce documentation time burden, which must be repeated over time.[26]

EHR optimization programs have been implemented at many institutions, typically lasting multiple days of training with a team of EHR specialists.[27] [28] [29] [30] EHR efficiency sessions called optimization sprints have been shown to reduce burnout by optimizing physician, nursing, and ancillary staff EHR workflow. Two-week-long optimization sprints conducted by Sieja et al utilize a multiple-person team consisting of a project manager, a clinical informaticist (CI), a PI, and ambulatory-certified trainers and EHR analysts.[2] [3] [4] [5] During these sessions, physician trainees received group and individual training, workflow analysis, and new or adjusted EHR build. Sieja et al found that clinicians who attended at least two optimization sessions saved 20 minutes per day. Optimization sprints also result in financial benefits: an 11-member team costs $1.2 million annually and can save $2.5 million in costs of replacing physicians due to turnover and burnout.[6] Optimization sprints are resource-intensive, requiring multiple team members, financial investment, and extended time commitment on the part of physicians. Sprint-inspired, single-day PI-led, post-go-live efficiency training sessions (which we will refer to as mini-sprints) may offer a more economical and convenient training option directed at providers without disrupting clinical schedules.

 

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Objectives

We evaluated a mini-sprint intervention to assess provider satisfaction and efficiency. The objective of this study is to supplement initial training for providers who are new to a recently launched EHR while engaged in its use and respecting their workflow, to configure the user interface of the EHR to their individual needs and preferences, to address systematic errors in their use of the EHR and in billing, and to improve their efficiency and satisfaction in using the EHR.

 

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Methodology

NorthShore University HealthSystem implemented one-on-one provider-to-provider mini-sprint sessions at Swedish Hospital within the EHR platform (EPIC Systems, Verona, WI) from June 2021 to October 2022. Swedish Hospital transitioned to the current EHR platform on September 29, 2020, with providers receiving a 2-hour in-person and a 2-hour virtual training session from EHR trainers, neither of which covered workflow and billing. In preparation for the mini-sprint, the PI completed power user training and developed the mini-sprint curriculum. Seventy-six sessions were conducted with primary care physicians, specialists, and nonphysician providers. The providers had approximately 1 year of experience with the current EHR platform. As the goal was to target providers with the highest rates of burnout, the PI went to office-by-office and began with training primary care providers, then moved onto specialists.[31] Every primary care provider at this location received mini-sprint training.

The PI completed a 9-point checklist of efficiency tips with provider trainees covering EHR efficiency data review, schedule organization, chart review, speed buttons, billing optimization, note personalization/optimization, preference lists, EHR QuickActions, and quick tips. Billing optimization included review of EPIC Signal billing data (a dashboard at the provider level that provides efficiency and billing data), education on use of Billing Wizard (an automated tool to support billing code selection), and configuration of level of service and modifier buttons specific to specialty needs. Efforts were also made to ensure the availability of relevant buttons for modifiers, as their absence often resulted in billing discrepancies. Billing optimization did not include note auditing. QuickActions are one-click shortcuts in the EHR to review results and send clinical and patient messages all at once. These 2- to 4-hour sessions were scheduled during clinic hours without a reduction in patient visits, to minimize clinic disruption and to optimize within the care provider's workflow.

During these sessions, the PI reviewed the trainee's EHR efficiency data, the proficiency score, which is a composite measure of how frequently software tools are used in EPIC. The proficiency score is measured on a scale of 0 to 10, with 0 indicating no use of efficiency configurations and 10 indicating high use of efficient configurations, factoring in use of quick actions, preference lists, SmartTool, chart tools, and personalization of features, such as default charge codes.[32] After each session, the provider was sent a satisfaction survey, which included a question assessing net promoter score (NPS) and other satisfaction and quality improvement feedback questions.[33] These surveys were sent to the first 50 providers who completed mini-sprints, which includes every primary care provider at Swedish Hospital. Pre- and postintervention efficiency levels, comparing proficiency scores before and after mini-sprint sessions, were analyzed by Wilcoxon matched-pair signed-rank test. Additional efficiency metrics were collected, including time spent in EHR, quick action usage, documentation length, and time to close appointments. Data for each metric were collected for each provider 3 months before and 1 year after the mini-sprint session, excluding the month of intervention. We conducted a comparison of efficiency metrics using paired Wilcoxon tests when dealing with non-normal distributions. In cases where the data followed a normal distribution, a paired t-test was employed. Bonferroni correction was not applied because we did not have an initial hypothesis for this analysis. Additionally, we analyzed the time-based efficiency metrics using a linear mixed-effects model, which allowed us to control for the total number of appointments scheduled per day for each physician.[34]

A financial cost–benefit analysis was performed. The financial cost of this program was calculated based on physician salary cost and the opportunity cost of the PI being unable to see patients during the time allotted. The PI spent 6 hours of dedicated time each week and was paid $961.50 per week. Between April and May 2021, the PI participated in power user training—a sequence of efficiency classes, each an hour long, provided by the EHR vendor—and concurrently developed the curriculum for the mini-sprint. This intensive preparatory period culminated in the initiation of one-on-one instructional sessions starting June 1, 2021. The opportunity cost was assumed to be the loss in collections the PI could have made for the hospital. Based on the PI's average per hour collections, there is an estimated loss of $2,087 per week. Over 48 weeks, there is a loss of $100,176. However, the PI's colleagues had the capacity to see these patients. The total cost of training of $37,498.50 includes training to 70 providers, or $535.69 per provider. The financial cost including training and opportunity cost amount to $137,674.50. There were no financial costs to the trainees' patient schedule, as sessions occurred during clinic times. Trainees frequently had no prior knowledge of mini-sprint session plans; thus, there was no change in the number of patients seen.

The financial data analysis compared EHR billing codes and revenue for providers 3 months before and 1 year after the mini-sprint session, excluding the month of intervention. Analyses were conducted in early-to-mid 2023. Financial revenue was analyzed for providers trained up until December 2021 to allow for 12 months of post-mini-sprint data, which includes 40 providers. Billing codes range from levels 1 through 5, with 5 generating the most revenue and 1 generating the least revenue depending on the level of services provided.[35] To account for the difference in number of patients seen pre- and post-mini-sprint, the billing revenue for each time frame was normalized by the number of patients seen during the 3 months pre-mini-sprint. Expected revenue was calculated according to the frequency of code level usage post-mini-sprint, using the number of patients for each code level pre-mini-sprint. Billing accuracy is validated through an auditing process. Prior studies have shown that up to 33% of billing codes are coded at a lower level than the level of services provided.[36]

 

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Results

Seventy-six sessions were conducted with 32 primary care physicians, 28 specialty physicians, and 16 nonphysician providers within primary care and other areas. Thirty-seven of the 50 polled providers (74%) completed the postsession survey. Over 90% of responders indicated that they were very satisfied with the session, and over 90% thought that the session took about the right amount of time. The average NPS for the completed mini-sprint sessions was 97. The collected subjective feedback indicates a need for more stable ancillary support and nonphysician optimization sessions, which could be achieved by expanding mini-sprint sessions to other health care team members. Five providers expressed interest in further mini-sprint training sessions. The proficiency score had a median of 6.12 (IQR: 4.71–7.64) before training, and a median of 7.10 (IQR: 6.25–8.49) after training ([Table 1]). The entire IQR shifted up after training, indicating increased proficiency among all participants. The increase in scores was statistically significant (p < 0.001). Analysis of efficiency metrics also shows a significant increase in the use of Quick Actions (from 2.00 to 8.00). Time-based efficiency metrics show a slight increase in time spent in orders per day (3.89 min) and time spent in system per day (9.79 min) when adjusted for appointments per day ([Table 2]). There was no significant change in other time metrics.

Table 1 Efficiency metrics 3 months preintervention and 12 months postintervention

	Before	After	p-Value
Quick actions available (n, quick actions/provider)	2.00 (0.00, 9.00)	8.00 (4.00, 12.00)	< 0.001
Proficiency score (points)	6.12 (4.71, 7.64)	7.10 (6.18, 8.40)	< 0.001
Appointments per day (n)	12.91 (6.77, 16.46)	13.21 (8.19, 17.75)	0.0141
Level of service entered by speed button (%)	85.00 (4.50, 174.00)	100.00 (36.00, 197.00)	0.1495
Documentation length (characters)	4,190.47 (1,367.59)	3,497.68 (1,586.20)	0.2898
Orders from preference lists and SmartSets (n)	89 (82, 94)	91 (84, 94)	0.1456
Appointments closed within 48 hours (n)	16.00 (1.50, 44.00)	9.00 (2.00, 39.00)	0.139

Table 2 Time-based efficiency metrics 3 months preintervention and 12 months postintervention

	Unadjusted			Adjusted
	Before	After	p-Value	Mean difference	p-value
Time in orders per day (min)	15.40 (8.22, 29.60)	20.51 (9.10, 37.27)	0.002	3.89 (0.69, 7.12)	0.020
Time in system per day (min)	126.18 (78.00, 159.67)	132.39 (84.75, 186.87)	0.006	9.79 (0.26, 19.33)	0.048
Time outside of 7 a.m. to 7 p.m. (min)	9.69 (5.05, 29.12)	21.49 (8.18, 37.65)	0.033	6.42 (−0.32, 13.18)	0.067
Time in visit navigator per day (min)	4.74 (2.60, 7.73)	3.47 (1.81, 6.13)	0.038	−0.91 (−2.18, 0.36)	0.165
Time in notes per day (min)	41.50 (24.87, 63.05)	45.70 (29.76, 63.84)	0.063	1.94 (−1.68, 5.53)	0.294
Pajama time (min)	11.38 (3.82, 35.41)	14.10 (2.58, 44.86)	0.385	2.01 (−4.26, 8.36)	0.532
Time outside scheduled hours (min)	23.57 (10.11, 49.00)	24.87 (8.01, 53.71)	0.425	3.15 (−0.82, 7.12)	0.125
Time in in-basket per day (min)	13.04 (6.63, 21.32)	14.55 (6.74, 21.78)	0.605	0.23 (−1.06, 1.51)	0.724
Time in schedule per day (min)	9.39 (6.90, 13.28)	9.14 (7.01, 15.06)	0.819	0.71 (−0.84, 2.26)	0.371
Time on unscheduled days (min)	33.13 (19.03, 72.50)	32.27 (18.59, 49.81)	0.937	−7.76 (−22.65, 7.13)	0.309

Financial data analysis indicates that higher level billing codes increased from a frequency of 54 to 55% 12 months post-mini-sprint ([Table 3]). The revenue increase 12 months post-mini-sprint was $213,234, leading to a return of $75,559.50 for 40 providers, or $1888.98 per provider in a 12-month period ([Table 4]).

Table 3 Difference in level 4/5 coding 3 months preintervention and 12 months postintervention

N (billing codes of interest)	Before	After	p-Value
Overall	14,623	63,606	–
High level codes, n (%)	6,454 (44.1%)	32,617 (51.3%)	<0.001
New patient codes	1,704	5,801	–
High level codes, n (%)	668 (39.2%)	2,563 (44.2%)	0.0003
Established patient codes	12,919	57,805	–
High level codes, n (%)	5,786 (44.8%)	30,054 (52.0%)	<0.001

Table 4 Cost analysis 3 months preintervention and 12 months postintervention

	Before	Expected	After	Difference (After − Before)	Difference (After − Expected)
New patients	$233,048.00	$793,631.47	$809,078.80	$576,030.80	$15,447.33
Established patients	$1,432,463.00	$6,409,635.34	$6,607,422.00	$5,174,959.00	$197,786.66
Overall (New + Established)	$1,665,511.00	$7,203,266.81	$7,416,501.00	$5,750,990.00	$213,234.19
Cost of program	$(137,674.50)
Overall return (Overall difference − Cost of program)				$5,613,315.50	$75,559.50

 

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Discussion

Our mini-sprint intervention was implemented as an addition to the initial EHR training at a single hospital. This intervention targeted providers who were new to a recently launched EHR system. The results were positive, showing improvements in provider satisfaction, efficiency, and financial reimbursement. Evaluating the costs against the increased financial reimbursement shows that this type of 1:1 training program conducted by a PI is sustainable.

Provider satisfaction was very high via the NPS and other subjective feedback. The initial training delivered to providers was run by EHR trainers without CIs. While helpful in getting acclimated to a new EHR, this study shows that providers enjoy being trained by a fellow clinician who deeply understands and can optimize the clinical workflow and can provide pilot to pilot training in how to fly the plane “on the tarmac.”

The EHR efficiency metrics collected include proficiency and time-based efficiency metrics. Among the proficiency metrics we assessed, QuickAction usage and the EHR's proprietary proficiency score increased significantly. We found a significant increase in time-based metrics including orders per day and time in system per day when adjusted for appointments per day. While a variety of proficiency and efficiency metrics improved, a notable increase of time spent in the EHR was found. The coronavirus disease 2019 (COVID-19) pandemic's transition to remote work might have been a contributing factor in this observation. During this period, an increased number of providers were granted remote access to the EHR, facilitating their ability to work from home. However, it is essential to highlight that working remotely might not always yield the same productivity levels as working from a clinic setting.[37] While the transition to remote work might have played a role in this finding, it is pertinent to note that the primary objective of the mini-sprint training was to enhance EHR usability, not to reduce the time spent in the EHR. A major contributor to overall time spent in the EHR, note documentation was not addressed in the mini-sprint training sessions. Other operational factors that improve time spent in the EHR, including stable ancillary support and ancillary support training, were also not addressed but were brought up in subjective feedback. The mini-sprint program with usability training from a PI improves proficiency which in turn can increase usability and provider satisfaction and engagement. Usability further reinforces key components of intrinsic motivation (the most powerful motivator in health care): goal-based decision-making, the drive for sense making and meaning, and the need for agency, autonomy, and control.[38]

The review of billing codes and observations during the mini-sprint revealed that providers often bill lower than the provided level of service. The training program assessed for basic billing understanding, implemented the use of Billing Wizard to facilitate accurate billing practices and educated on the availability of relevant buttons for modifiers. For example, during the course of the program, one provider categorized all patients as established, failing to distinguish between new and established patients as required, resulting in significant underbilling for a half of his total patient visits. Another provider was omitting billing a secondary code for specific visits. Both of these issues were corrected during the mini-sprint. A key finding of this work is that this type of program, which is much smaller than the typical optimization sprint but still valuable for proficiency, efficiency, and provider satisfaction, can be financially stable. In a time of budgetary tightening across health systems, this mini-sprint single-day PI intervention that addresses physician training by reducing cognitive load and improving usability while at the same time improving net financial return.

Future work should evaluate the longer term effect of the mini-sprint on proficiency, usability and evaluate effect on physician and other clinical provider burnout. Additionally, evaluating other sprint concepts that focus on usability via focusing on ancillary staff and effect on team burnout are also of interest.

 

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Limitations

The study is subject to several limitations. Conducted solely at a single institution where all providers recently switched over from another EHR vendor, the findings from the mini-sprint education sessions might not apply broadly, given the diverse EHR systems and training protocols in other organizations. The lack of a control group adds complexity to evaluate the effectiveness of the mini-sprint sessions, with observed changes potentially attributable to external factors, not just the intervention. That being said this mini-sprint intervention was the only formal systematic EHR-based training provided during the study period.

The COVID-19 pandemic added a significant limitation that impacted EHR workflows, as the transition to remote work occurred during the time frame of this program. These changes affected provider EHR access and work schedules, as providers were gaining remote access and had the ability to work outside of standard business hours. This limits our ability to measure the impact of this program in terms of time-based metrics.

The participant pool might introduce selection and nonresponse bias. This was controlled for by training all primary care providers and dropping in on some providers without prior notice. The first 50 providers out of 73 were surveyed and they were primarily primary care providers which may have introduced minimal selection bias. Providers with a less satisfactory experience might have chosen not to complete the postsession survey, contributing to data bias. These limitations should be factored in when interpreting the study's findings.

We note also that our financial analysis has a limitation in that the model used for calculating the program cost focused solely on the PI salary and opportunity cost, without considering other factors such as facility expenses and material costs. However, it is important to highlight that this intervention was implemented in a pragmatic manner, making use of the existing office space and clinical time dedicated to clinical work by the providers. This approach ensured minimal disruption to patient care while conducting the training program.

 

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Conclusion

Our data suggest that mini-sprint sessions effectively optimize provider efficiency with the EHR platform. There was also high satisfaction with the mini-sprint training modality, which provides the equivalent of pilot-to-pilot training in a flight simulator, not while the plane is in flight. Organizing EHR training programs around a dyad partnership between trainers and “test pilots” who oversee curriculum and ensure providers are trained in EHR configuration and workflows to ensure the tool is used optimally may optimize usability and improve provider engagement. Feedback indicated an interest in further mini-sprint training sessions for physicians and nonphysician staff. Mini-sprints are also cost-effective and can pay for themselves by improving reimbursement making them an effective way to improve usability and provider engagement.

 

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Clinical Relevance Statement

These results present an effective method to improve EHR proficiency and address EHR documentation burden among providers, with implications for reducing burnout in health care practitioners.

 

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Multiple Choice Questions

1. What effect do the current time requirements for EHR documentation have on health care providers' schedules?

   • Providers can choose not to complete EHR data entry if they do not have time during work hours.

   • Providers often have to enter EHR information outside of work hours and during “pajama time.”

   • Providers can easily complete EHR documentation within their scheduled work hours.

   • Providers rely on other health care staff to complete EHR documentation for the patients that they see.

   Correct answer: b. The studies show that providers often do not have time to finish entering EHR documentation during work hours and must complete this work outside of work hours. In the evening, this is called pajama time.

2. Which statement accurately compares optimization sprints to mini-sprints?

   • Optimization sprints typically last less than 1 day, while mini-sprints last for 2 weeks.

   • Optimization sprints require a smaller team of one PI, while mini-sprints require a larger team of multiple trainers and analysts.

   • Mini-sprints typically last less than 1 day, while optimization sprints last for 2 weeks.

   • Mini-sprints address EHR proficiency, while optimization sprints teach billing and finance skills.

   Correct answer: c. The optimization sprints as conducted by Sieja et al[2] [3] [4] [5] [6] lasted for 2 weeks, while the mini-sprints conducted at our institution lasted 2 to 4 hours.

 

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Conflict of Interest

None declared.

Protection of Human and Animal Subjects

This study was submitted to the Institutional Review Board at Endeavor Health and was deemed to be an exempt quality improvement study.

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Publikationsverlauf

Eingereicht: 10. November 2023

Angenommen: 14. März 2024

Artikel online veröffentlicht:
24. April 2024