DDHA 8503 Week 5 Stakeholder Analysis Example

Who Ends Up Holding the Work When Messages Are Billed and Routed to Nurses First: A Stakeholder Analysis That Follows the Cost to Groups Nobody Consulted

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Walden University

DDHA 8503: Strategic Management and Systems Thinking

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Month Day, Year

Who Ends Up Holding the Work When Messages Are Billed and Routed to Nurses First: A Stakeholder Analysis That Follows the Cost to Groups Nobody Consulted

The Change Under Analysis

Brightwater Medical Group's finance committee has proposed two linked changes to patient messaging across its fourteen primary care clinics. First, messages that require clinical judgment, such as a new symptom or a medication change, would be billed as online visits where payer rules allow. Second, every message categorized as a medical question would go first to the nurse triage pool, which would answer it or decide that a clinician must. The proposal's stated aims are to reduce clinicians' after-hours inbox time and to recover some revenue for work currently unpaid. This analysis asks who carries the change once it lands.

Defining the Groups

Groups are defined by their relationship to the flows described in earlier weeks rather than by job family. That produces some divisions an organizational chart would not. Day-shift triage nurses and the two evening triage nurses appear separately, because the evening nurses handle the messages that arrive after clinics close and have no clinician on site to consult. Patients appear as several groups, because a billing change reaches a patient with a high-deductible plan very differently from one whose plan waives cost sharing.

Table 1

Groups, Gains, Losses, Discretion and Likely Responses

Entries come from Brightwater's messaging reports, interviews with two clinic managers and the nursing director, and the finance committee's proposal.

Where Work Is Displaced

The most important pattern in the table is work that leaves one group and arrives at another without anyone deciding it should. Three displacements stand out.

The first runs from clinicians to triage nurses. That is intended, and the proposal estimates it will move about 2,000 messages a week into the nurse pool. The proposal does not add nurses. It assumes that nurses will answer many messages without escalation, but nurses hold discretion over escalation, and when unsure they will send the message on. Lipsky (2010), describing frontline public service workers, showed how people who hold discretion under heavy caseloads develop routines that protect them from risk, often at the cost of the service's stated aims. For triage nurses, the protective routine is escalation, which would send much of the work back to clinicians.

The second runs from the portal to the telephone. Patients who face a possible charge for a message may call instead, since a phone call is not billed. Holmgren et al. (2023) found that billing reduced message volume only slightly at one health system, but even a modest shift would land on the medical assistants who staff the phone queue and who also route messages. That group was not consulted.

The third runs from day to evening. Evening triage nurses already defer some messages to the next morning, and a larger volume would make deferral routine, producing a Monday-to-Friday morning surge that the day nurses would absorb.

Influence and Interest as Inputs

Influence and interest matter here mainly as predictors of response. In the salience model of Mitchell et al. (1997), a group commands managers' notice when it can force outcomes, when its stake is widely seen as rightful and when its demands cannot wait. By those measures, clinicians are the most salient: they hold the power to decline billing and the legitimacy of clinical judgment. Triage nurses have legitimacy and urgency but less formal power. Patients with high-deductible plans have urgency but little power inside the organization, though they have the power of exit. Medical assistants on the phone queue score low on all three, which is why they were not consulted and why the displacement toward them is likely to go unnoticed until callback times rise.

One group is missing from the table because it sits just outside the boundary drawn for this system: the specialists who receive questions forwarded from primary care. If triage nurses forward more questions to specialty clinics rather than escalating them to primary care clinicians, part of the displaced work will land in specialty inboxes, where it is neither expected nor measured. The pilot should track forwarded messages for that reason, even though specialty clinics are not part of the change.

Groups Whose Reaction Would Most Change the Outcome

Three groups' responses would determine whether the change achieves its aims. Day triage nurses come first: if they escalate most messages, clinicians' inbox time will not fall, and the nurse pool will have added work without reducing anyone else's. Clinicians come second: if they decline to bill, revenue will not appear, and the billing half of the proposal will exist only as policy. Patients with high-deductible plans come third: if they shift to the phone, the change will move volume rather than reduce it and will add burden to the least consulted group.

The analysis recommends that the finance committee consult the triage nurses and the phone queue staff before approving the change, test it in two clinics with an escalation rate target agreed with the nurses and measure callback times as well as inbox time.

References

Holmgren, A. J., Byron, M. E., Grouse, C. K., & Adler-Milstein, J. (2023). Association between billing patient portal messages as e-visits and patient messaging volume. JAMA, 329(4), 339-342. https://doi.org/10.1001/jama.2022.24710

Lipsky, M. (2010). Street-level bureaucracy: Dilemmas of the individual in public services (30th anniversary expanded ed.). Russell Sage Foundation.

Mitchell, R. K., Agle, B. R., & Wood, D. J. (1997). Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts. Academy of Management Review, 22(4), 853-886. https://doi.org/10.2307/259247