HA599 Unit 8 Arrival Point Risk Assessment Example

When Success Brings More Ambulances: A Capstone Risk Assessment Scoring Nine Risks Specific to Tessford's Planned Ambulance Arrival Area, From Boarding Creep to Early Signatures, Each With an Owner, a Warning Sign and a Response

[Student Name]

Purdue University Global

HA599: Master's Capstone in Health Care Administration

Unit 8 Risk Assessment

[Instructor Name]

[Date]

The hospital, the risks and every score are composite and bracketed for the writer's own data.

The Entry Test

A risk entered the register only if it was specific to the arrival point at Tessford. Generic entries such as scope creep and poor communication were struck out, because they apply to every project and lead to no specific action.

Scoring

Likelihood and impact are each scored one to five, and multiplied. Reasons are given for each score, since a number without a reason cannot be challenged.

The Register

1. Boarding creep: admitted patients waiting for beds are held in the alcove until it stops receiving ambulances. Likelihood [4]: the department boards [12] or more patients on many afternoons. Impact [5]: the arrival point would fail entirely. Score [20]. Owner: emergency department director. Indicator: any admitted patient in the alcove. Prevention: a written rule that the alcove never holds an admitted patient. Contingency: a breach triggers a bed huddle within [30] minutes.

2. Reassigned nurse: the arrival nurse is pulled to cover a bedside on busy shifts. Likelihood [4]. Impact [4]. Score [16]. Owner: nurse manager. Indicator: weekly count of every time the nurse was reassigned. Prevention: the role is protected in the staffing grid and cannot be pulled without the house supervisor's approval. Contingency: if pulled more than [twice] a week, the sponsor reviews staffing.

3. Early signatures: nurses sign for patients before a real handoff to stop the clock. Likelihood [3]. Impact [5]: numbers improve while nothing else does. Score [15]. Owner: quality specialist. Indicator: gaps between badge time, signature time and the time a patient leaves the stretcher. Prevention: audit [ten] handoffs a week by direct observation. Contingency: retraining and, if repeated, a change in what the signature records.

The most dangerous success would be one that exists only in the data.

4. More ambulances: faster handoffs lead dispatchers to send more patients to Tessford. Likelihood [3]. Impact [4]. Score [12]. Owner: emergency department medical director. Indicator: Tessford's share of county transports. Prevention: agree with the county that destination rules remain based on patient need and distance. Contingency: if the share rises more than [ten] percent, review with the county.

5. Patient deterioration in the alcove. Likelihood [2]. Impact [5]. Score [10]. Owner: arrival nurse lead. Indicator: rapid response calls from the alcove. Prevention: anyone arriving with abnormal vital signs goes straight to a treatment bed; vital signs every [30] minutes. Contingency: immediate move to a resuscitation bay.

6. Walk-in waits lengthen. Likelihood [3]. Impact [3]. Score [9]. Owner: triage nurse lead. Indicator: walk-in door-to-provider time.

7. Float pool shortfall. Likelihood [3]. Impact [3]. Score [9]. Owner: float pool manager.

8. Badge data gaps. Likelihood [3]. Impact [2]. Score [6]. Owner: informatics lead.

9. Crews bypass the arrival point. Likelihood [2]. Impact [3]. Score [6]. Owner: county EMS training officer.

Why Boarding Creep Scores Highest

Boarding creep is likely because the pressure behind it is constant. On afternoons when the department holds a dozen or more admitted patients, every open stretcher space looks like relief, and an alcove staffed by a nurse looks like the safest place to put one more patient. The first time it happens will feel reasonable; by the third, the alcove will have become a holding area, ambulances will wait at the door again and the project will have failed without anyone deciding it should. That is why the response is a rule written into the proposal itself rather than a guideline, and why a breach triggers a meeting about beds rather than a note in a log. The rule protects the arrival point from good intentions.

Risks Struck Out

Besides generic entries, the team struck out the risk that crews would refuse to use the alcove, because the county medical director's protocol requires it, and kept a narrower version, crews bypassing it on busy nights, as risk 9.

Heat Map in Words

High: boarding creep and reassignment. Medium-high: early signatures and more ambulances. Medium: deterioration, walk-in waits and float shortfall. Low: badge data and crew bypass.

Why Early Signatures Matter So Much

When a target is attached to a measure, people sometimes change the measure rather than the result (Bevan & Hood, 2006). Here, a signature entered before a real handoff would show success on the primary measure while crews still waited. Auditing against direct observation keeps the measure honest.

Safety Risks From the Literature

A hazard analysis of offload zones identified high-risk failures in monitoring and accountability while patients wait (Carter et al., 2015). Risks 5 and 9 respond to those findings.

The County's View

The county EMS medical director agreed that destination decisions must stay with patient need, consistent with national guidance that offload delay and diversion are shared problems for hospitals and EMS systems (Cooney et al., 2011).

Review

The register is reviewed weekly for the first [eight] weeks after opening, then monthly. Scores are updated as indicators move.

Conclusion

The top three risks would each defeat the project quietly. Each has a rule, an indicator and an owner before the first ambulance arrives.

References

Bevan, G., & Hood, C. (2006). What's measured is what matters: Targets and gaming in the English public health care system. Public Administration, 84(3), 517-538. https://doi.org/10.1111/j.1467-9299.2006.00600.x

Carter, A. J., Gould, J. B., Vanberkel, P., Jensen, J. L., Cook, J., Carrigan, S., Wheatley, M. R., & Travers, A. H. (2015). Offload zones to mitigate emergency medical services (EMS) offload delay in the emergency department: A process map and hazard analysis. CJEM, 17(6), 670-678. https://doi.org/10.1017/cem.2015.15

Cooney, D. R., Millin, M. G., Carter, A., Lawner, B. J., Nable, J. V., & Wallus, H. J. (2011). Ambulance diversion and emergency department offload delay: Resource document for the National Association of EMS Physicians position statement. Prehospital Emergency Care, 15(4), 555-561. https://doi.org/10.3109/10903127.2011.608871