BUSI 691 Week 8 Discussion Board Forum 4 Example

Discussion Board Forum 4: Strategic Leadership and the Future of Health Care Organizations

BUSI 691 Healthcare Administration Capstone, Discussion Board Forum 4

Thread by [Student Name]

The health system, its adoption figures and the other groups are composites; the textbook, Scripture and the peer-reviewed sources cited are real.

Our group studied Crestline Health, a six-hospital system with 1,400 employed physicians and advanced practice clinicians. A vendor has offered an enterprise license for an ambient artificial intelligence scribe, which records the conversation during a visit and drafts the note for the clinician to review, at $4.2 million a year for every clinician in the system. Physician leaders are enthusiastic, since clinicians say they finish charts at home for as long as two hours each evening, and the medical group's burnout survey is the worst it has been. Finance leaders, meanwhile, have asked for proof that the tool will repay its cost.

Walston (2018) describes strategic leadership as setting direction while managing uncertainty, matching an organization's ambition to its capabilities and making sure strategies are executed and measured. Applying the course's tools, the external environment favors adoption: competitors are offering scribes as a recruiting benefit, and the technology is improving quickly. Internally, Crestline has a strong informatics team but a history of technology projects launched system-wide before workflows were ready. The strategic question is therefore not whether to adopt the technology but how fast, where first and with what safeguards. The financial case also deserves scrutiny. At $4.2 million a year, the license costs about $3,000 per clinician, which would be repaid if it retained even a handful of physicians who might otherwise leave, but only if clinicians actually use it. A license that sits unused in departments where the tool does not fit would add cost without benefit.

The evidence is promising but uneven. Alcázar-Peral et al. (2026) evaluated sixteen months of an ambient scribe in outpatient care across a Spanish health network. Adoption grew from 2.7% to about 31% of outpatient visits, exceeding 2.3 million assisted encounters; the notes' semantic agreement with the conversation stayed between 87% and 89%; and clinicians reported improvements in five of seven areas of their professional experience, while visit length changed only modestly. Stults et al. (2026) studied an inpatient rollout at a large California organization. Among 59 physicians, the scribe was used for only 3% of inpatient notes, mostly admission and consult notes, and time spent in notes per day did not change, from 41.9 to 41.6 minutes. Physicians asked for features suited to inpatient work, such as building on previous notes. The contrast is instructive for strategy: one product may thrive in clinics yet go unused on the wards, and a system that buys licenses for every clinician at once will pay for many that are rarely used. Our group's earlier analyses in this course reached a similar lesson about execution, that the setting and the people matter as much as the plan. Together, the studies suggest that ambient scribes fit outpatient visits far better than inpatient workflows at present.

Our group recommends a staged strategy rather than the enterprise contract. In phase one, Crestline would license the scribe for 300 outpatient clinicians in primary care and the specialties with the heaviest documentation, negotiating a per-user price and the right to expand. Before launch, a governance committee would set policies for patient consent, note review and data retention, and the system would measure after-hours documentation time, note quality audits, clinician burnout and patient experience. After six months, the committee would decide whether to expand to other outpatient clinicians, and inpatient use would wait until the vendor offers inpatient features. This approach captures the benefits where evidence is strongest while protecting the system from paying for licenses that sit unused.

Proverbs contrasts diligent planning, which leads to gain, with hurried action, which leads to want (English Standard Version Bible, 2001/2016, Proverbs 21:5). A leader who wants to relieve weary clinicians honors them most by adopting the tool carefully enough that it actually helps, rather than quickly enough to make an announcement.

Reply to Group 1

Group 1, your thread recommended deploying ambient AI scribes first in your system's emergency departments, where documentation pressure is intense and physician burnout is highest. We understand the logic, and Walston (2018) encourages leaders to direct resources toward their most pressing problems. The evidence suggests caution about where to start. Gancz et al. (2026) found only six studies of ambient scribes in emergency departments, with between 6 and 24 physicians each; some reported better cognitive workload and faster first notes, but one found longer charting time than with human scribes, and challenges included fragmented workflows, noise, note accuracy and clinician distrust. Zhou et al. (2026) concluded from a leadership analysis that success depends less on the technology than on governance, consent, workflow redesign, training and monitoring of errors such as omitted or invented content. We would suggest a small pilot with willing physicians in one department, with note accuracy audits, before wider rollout. Paul told the church in Thessalonica to examine every claim and keep only what proves good (English Standard Version Bible, 2001/2016, 1 Thessalonians 5:21), which is exactly what a careful pilot does. A pilot also lets emergency physicians shape how the tool is configured, which would build the trust the review found lacking.

Reply to Group 3

Group 3, your thread proposed adopting AI-drafted replies to patient portal messages to reduce the time physicians spend in their inboxes, and you projected savings of an hour a day per physician. The goal is important, and Walston (2018) stresses that every strategy needs measurable targets. Two evaluations suggest your target should focus on burden rather than time. Garcia et al. (2024) studied 162 clinicians at an academic center who could use AI drafts; they used drafts for 20% of replies, and time spent reading and replying did not change, yet task load and work exhaustion scores improved significantly. Tai-Seale et al. (2024) randomized 52 primary care physicians and found that AI drafts increased time spent reading messages by 21.8% and reply length by 17.9%, with no significant change in reply time, although physicians saw value in the tool. We would suggest measuring exhaustion and message quality alongside time, since relief may come before efficiency does. Jesus called the weary and overburdened to come to him and promised them rest (English Standard Version Bible, 2001/2016, Matthew 11:28), and a tool that lightens the burden of the inbox has value even when the clock does not move, provided leaders do not use it to add more messages to each physician's day.

References

Alcázar-Peral, J. M., Álvaro-de la Parra, J. A., Blanco, D., Blanco, Á., Barrios, M. E., Cristóbal, I., & Caramés, C. (2026). Real-world evaluation of an ambient AI scribe in Spanish outpatient care after 2.3 million uses: Impact on clinician experience, semantic agreement, and workflow efficiency. Frontiers in Digital Health, 8, 1874919. https://doi.org/10.3389/fdgth.2026.1874919

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Gancz, L., Duffy, E. I., Mathies, I., Schmidt, J., English, B., Chale, S., & Heslin, S. (2026). Ambient artificial intelligence scribes in the emergency department: A scoping review of current evidence. The Journal of Emergency Medicine, 88, 235-243. https://doi.org/10.1016/j.jemermed.2026.05.043

Garcia, P., Ma, S. P., Shah, S., Smith, M., Jeong, Y., Devon-Sand, A., Tai-Seale, M., Takazawa, K., Clutter, D., Vogt, K., Lugtu, C., Rojo, M., Lin, S., Shanafelt, T., Pfeffer, M. A., & Sharp, C. (2024). Artificial intelligence-generated draft replies to patient inbox messages. JAMA Network Open, 7(3), e243201. https://doi.org/10.1001/jamanetworkopen.2024.3201

Stults, C. D., Deng, S., Martinez, M. C., Wilcox, J., Szwerinski, N., Wilde, J., Liu, R. C., Rabbani, N., Driscoll, S., & Jones, V. G. (2026). Ambient artificial intelligence scribe implementation in inpatient setting. Journal of Hospital Medicine. Advance online publication. https://doi.org/10.1002/jhm.70451

Tai-Seale, M., Baxter, S. L., Vaida, F., Walker, A., Sitapati, A. M., Osborne, C., Diaz, J., Desai, N., Webb, S., Polston, G., Helsten, T., Gross, E., Thackaberry, J., Mandvi, A., Lillie, D., Li, S., Gin, G., Achar, S., Hofflich, H., . . . Longhurst, C. A. (2024). AI-generated draft replies integrated into health records and physicians' electronic communication. JAMA Network Open, 7(4), e246565. https://doi.org/10.1001/jamanetworkopen.2024.6565

Walston, S. L. (2018). Strategic healthcare management: Planning and execution (2nd ed.). Health Administration Press.

Zhou, K. X., Ng, Q. X., Tan, H. K., Er, E. Y. W., Wu, D. T., Nguyen, T. T., Gigliotti, J., Siqueira, W. L., & Makhoul, N. (2026). Implementation of ambient AI scribes in hospitals: Lessons for healthcare leadership, governance, and change management. Journal of Healthcare Leadership, 18, 1-20. https://doi.org/10.2147/JHL.S622179