HINF 510 Week 4 End-User Training, Support and Stakeholder Buy-In Example

Sixteen Hours for a Dentist, Four for the Front Desk and a Skeptic on the Steering Committee: Training, Support and Buy-In for a New Health Center Record

[Student Name]

University of Phoenix

HINF/510: The Systems Life Cycle

Week 4 Assignment

[Instructor Name]

[Date]

The health center network, its staff, hours and plans are composites written for a model paper; research findings come from the sources listed.

At the steering committee's fourth meeting, a family physician who had practiced at the network's largest clinic for 22 years said what many were thinking: the new record would slow her down, her patients would wait longer and nothing she had seen convinced her it would help. She was respected, and other clinicians would follow her lead. The project team had to answer her concerns and train about 390 users across medical, dental, behavioral health and administrative roles. This paper sets out the training, support and buy-in plan.

Why Training Matters More Than the Vendor

The quality of training may matter more than the software. In a survey of more than 72,000 physicians, nurses, advanced practice professionals and residents at 156 organizations, less than 20% of the variation in satisfaction with the record was explained by which vendor an organization used, and users' ratings of their record-specific training were the strongest predictor of experience. Physicians who reported poor training were more than three times as likely to say their record did not enable them to deliver quality care, and organizations requiring more initial training hours had much higher satisfaction scores (Longhurst et al., 2019).

User Groups

The team identified eight user groups: front-desk and call center staff, medical assistants, nurses, physicians and advanced practice clinicians, dentists and dental staff, behavioral health clinicians, billing staff and managers. Each group's work was drawn from the workflow analysis completed earlier.

A Role-Based Curriculum

Training is organized around tasks, not screens. Front-desk staff receive 4 hours on registration, sliding-fee eligibility, scheduling and portal enrollment. Medical assistants receive 8 hours on rooming, intake questionnaires, standing orders and care gap closure. Nurses receive 10 hours. Physicians, advanced practice clinicians, dentists and behavioral health clinicians each receive 16 hours, split between classroom sessions and personalization time. Each session uses realistic scenarios from the network, such as a diabetic patient seen by three disciplines in one morning.

Personalization

A large part of clinicians' time is spent in the record, so personalization matters. Each clinician spends two of the 16 hours with an analyst setting up favorite orders, note preferences and shortcuts. Clinicians who arrive at go-live with personalized tools start faster.

Proficiency Before Access

Each user completes a proficiency check of realistic tasks before receiving access. Those who do not pass receive additional coaching. The rule applies to leaders as well, which signals that training is not optional.

Timing

Training begins six weeks before each clinic group's go-live and ends one week before, so skills are fresh. Clinic schedules are reduced during training time, and the budget covers staff backfill.

The Super User Network

Forty-two super users, three per clinic plus central staff, receive 24 hours of training and serve as first-line support, spending most of their time during the first two weeks helping colleagues in clinics and relaying problems to the project team. They are chosen for patience and credibility, not only technical skill.

Go-Live Support

For two weeks after each go-live, clinics run reduced schedules, super users and vendor staff are on site, a command center meets twice daily to review problems and a dedicated support line answers calls. A visible board in each clinic lists reported issues and their status, so staff see that problems are being fixed.

After Go-Live

Support continues after the first weeks. Monthly tip sheets, short optimization sessions for each role at three and six months and a one-on-one session for clinicians who spend the most time in the record after hours help users move from basic use to efficient use.

Understanding Acceptance

Theory helps explain resistance. Under the technology acceptance model, whether someone plans to use a new tool turns chiefly on two beliefs: that it will help with the work and that it will not be hard to learn; a review of its use in health care found the model predictive but noted that clinicians' acceptance is also shaped by their work context, colleagues and patients (Holden & Karsh, 2010). The skeptical physician did not doubt technology in general; she doubted that this system would be useful to her and easy for her patients.

Managing Change

Change in health care organizations succeeds when leaders understand that people resist losing control and familiar routines, not technology itself, and when change is managed with clear vision, involvement of those affected and attention to organizational culture (Lorenzi & Riley, 2000). People rarely resist a new system; they resist losing the way they know how to do their work.

Winning Over the Skeptic

The team invited the skeptical physician to lead testing of the diabetes visit template. She found three problems: too many required fields, a medication reconciliation screen that took five clicks and a care gaps list buried two screens deep. The analysts fixed all three and showed her the changes. She then timed a scripted visit and found it faster than in the old system. At the next medical staff meeting, she described the changes she had requested. Other clinicians listened to her in a way they would not have listened to the project team.

Training for Managers

Clinic managers need their own training because they will run clinics during the disruption. Their 6-hour course covers the scheduling templates and reduced schedules for go-live weeks, the reports they will use to track wait times and productivity, how to escalate problems to the command center and how to support staff who struggle. Managers also learn to recognize fatigue and frustration in the first weeks, when productivity drops and tempers shorten, and to protect time for staff to practice.

The Budget for People

Training and support account for about $1.1 million of the $4.2 million project, mostly in backfill for staff time and reduced clinic schedules. The finance director questioned the cost of 16 hours for each clinician. The team answered with the survey finding that training predicts satisfaction and with a simple calculation: if better training saves each clinician even ten minutes a day in the record, the time recovered across 95 clinicians within a year exceeds the training hours spent.

Other Stakeholders

Buy-in extends beyond clinicians. The board receives monthly updates on budget and risks. Patients hear about the change through signs, the portal and front-desk scripts. Payers and partners are notified of new interfaces and contact procedures.

Measures

The network will measure training quality through post-course surveys, proficiency pass rates, support call volume and time to resolution, clinician satisfaction with the record at three and twelve months and time spent in the record after hours.

Conclusion

A new record succeeds only when people can use it well. Research showing that training predicts satisfaction better than vendor choice justified 16 hours for clinicians and proficiency checks for everyone. Super users, go-live support and ongoing learning carry users through the difficult first months, and theory on acceptance and change guided a buy-in plan that turned a respected skeptic into the project's most credible advocate.

References

Holden, R. J., & Karsh, B.-T. (2010). The technology acceptance model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159-172. https://doi.org/10.1016/j.jbi.2009.07.002

Longhurst, C. A., Davis, T., Maneker, A., Eschenroeder, H. C., Jr., Dunscombe, R., Reynolds, G., Clay, B., Moran, T., Graham, D. B., Dean, S. M., & Adler-Milstein, J. (2019). Local investment in training drives electronic health record user satisfaction. Applied Clinical Informatics, 10(2), 331-335. https://doi.org/10.1055/s-0039-1688753

Lorenzi, N. M., & Riley, R. T. (2000). Managing change: An overview. Journal of the American Medical Informatics Association, 7(2), 116-124. https://doi.org/10.1136/jamia.2000.0070116