DDBA 8561 Week 11 Delivery System Paper Example

The Pace Is Set Far From the Waiting Room: A System Paper Linking a Hospital's Elective Schedule and a Late Discharge Estimate to Emergency Boarding, Handoff Failures and Call Center Overload as One Causal Chain

Student Name

Walden University

DDBA 8561: Seminar in Managing Healthcare Delivery Systems

Instructor Name

Month Day, Year

The Pace Is Set Far From the Waiting Room: A System Paper Linking a Hospital's Elective Schedule and a Late Discharge Estimate to Emergency Boarding, Handoff Failures and Call Center Overload as One Causal Chain

Abstract

This paper argues that the pace of patient flow at Ridgeway Regional, the North Carolina community hospital studied in earlier weeks, is set by two decisions far from the places where patients notice waiting: the weekly pattern of elective surgical admissions and the time of day when expected discharges become known. Each finding from the term's earlier work is one link in a causal chain running from those decisions through inpatient occupancy and bed placement to emergency department boarding, and from there to handoffs and staffing that absorb the residue. The paper restates each finding for Ridgeway, adds the evidence connecting it to the next and closes with what managers should change first.

Thesis

Managers at Ridgeway see congestion where patients wait: the emergency department, the call center, the discharge lounge. The thesis is that those are symptoms. The cause is upstream, in a schedule the hospital sets for itself and in information the hospital produces too late.

The Chain

[after]

Table 1

Links in the Causal Chain

Links One and Two: Schedule and Occupancy

The change proposal showed that elective admissions concentrated midweek push surgical units above 95 percent occupancy on Tuesday and Wednesday. Litvak et al. (2005) argued that such peaks are artificial variability, created by the organization's own scheduling, and that they compound the natural variability of emergency admissions. At high occupancy, small fluctuations in arrivals produce long waits, a relationship Hopp and Spearman (2008) described for any system with limited capacity and variable demand. The mechanism linking link one to link two is therefore occupancy: the schedule determines how close the units run to their ceiling.

Links Two and Three: Occupancy and Information

When units run near capacity, placement depends on discharges. The information brief found that expected discharge times arrive after 2:00 p.m., hours after placement staff need them. Galbraith (1974) held that rising uncertainty leaves an organization two broad routes: needing less information or handling more of it. At low occupancy, placement does not need discharge estimates; empty beds serve as slack. At high occupancy, the slack is gone and the missing estimate becomes decisive.

Links Three and Four: Information and Assignment

The measurement note defined bed request to bed assignment as an inpatient measure and found its median near four hours. That interval exists because assignment waits for confirmed discharges, which wait for afternoon orders. Asplin et al. (2003) placed this delay in the output component of emergency department crowding.

Links Four and Five: Assignment and Boarding

The flow paper showed that admitted patients board a median of 5 hours 40 minutes and occupy about a third of treatment spaces in mid-afternoon, and that arrival-to-provider times for other patients rise on high-boarding days. Boarding is the visible result of the earlier links.

Link Six: The Residue

When placement happens late in the day, discharges on inpatient units compress into the late afternoon and evening, the period when the handoff study found medication changes and pending results most likely to arrive late or go unowned. Gittell (2002) found that coordination suffers most when conditions are uncertain and time is short. Meanwhile, patients who cannot get through to schedule follow-up appointments call again, as the staffing model showed, adding load to a center already short in the morning.

The Rival View

The rival view, common at Ridgeway, holds that congestion is driven by rising emergency volume and by patients who should be seen elsewhere. Hoot and Aronsky (2008), whose review the flow paper used, gave that view a hearing and found output factors more consistently tied to crowding. At Ridgeway, emergency visits grew about 4 percent a year, while boarding hours rose far faster, a pattern the input view does not explain.

What to Change First

Goldratt and Cox (1984) argued that improvement should begin at the constraint. The chain suggests two upstream changes with the most effect for their cost: smoothing elective admissions across the week and moving expected discharge times to a mid-morning huddle. Both are within the hospital's control and cost little relative to new beds. Changes further down the chain, a fast-track area or more call center agents, treat symptoms and will be overwhelmed if the upstream causes remain.

Boundaries of the System

Shortell et al. (1994) defined organized delivery systems by coordination and accountability across a continuum, and the chain crosses into post-acute providers and referring practices the hospital does not own. Burns and Pauly (2002) found that ownership seldom produced integration. The chain therefore argues for coordination with partners, such as shared discharge timing with skilled nursing facilities, rather than acquisition.

Limits

The findings come from separate composite analyses restated for one hospital; a single dataset following patients through every link would test the chain more directly. Some links rest on medians that hide variation across days.

Conclusion

The waits patients notice are produced far from where they occur. A hospital that manages its elective schedule and the timing of its discharge information can relieve pressure at every later link.

References

Asplin, B. R., Magid, D. J., Rhodes, K. V., Solberg, L. I., Lurie, N., & Camargo, C. A., Jr. (2003). A conceptual model of emergency department crowding. Annals of Emergency Medicine, 42(2), 173-180. https://doi.org/10.1067/mem.2003.302

Burns, L. R., & Pauly, M. V. (2002). Integrated delivery networks: A detour on the road to integrated health care? Health Affairs, 21(4), 128-143. https://doi.org/10.1377/hlthaff.21.4.128

Galbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4(3), 28-36. https://doi.org/10.1287/inte.4.3.28

Gittell, J. H. (2002). Coordinating mechanisms in care provider groups: Relational coordination as a mediator and input uncertainty as a moderator of performance effects. Management Science, 48(11), 1408-1426. https://doi.org/10.1287/mnsc.48.11.1408.268

Goldratt, E. M., & Cox, J. (1984). The goal: A process of ongoing improvement. North River Press.

Hoot, N. R., & Aronsky, D. (2008). Systematic review of emergency department crowding: Causes, effects, and solutions. Annals of Emergency Medicine, 52(2), 126-136. https://doi.org/10.1016/j.annemergmed.2008.03.014

Hopp, W. J., & Spearman, M. L. (2008). Factory physics (3rd ed.). McGraw-Hill/Irwin.

Litvak, E., Buerhaus, P. I., Davidoff, F., Long, M. C., McManus, M. L., & Berwick, D. M. (2005). Managing unnecessary variability in patient demand to reduce nursing stress and improve patient safety. Joint Commission Journal on Quality and Patient Safety, 31(6), 330-338. https://doi.org/10.1016/S1553-7250(05)31044-0

Shortell, S. M., Gillies, R. R., & Anderson, D. A. (1994). The new world of managed care: Creating organized delivery systems. Health Affairs, 13(5), 46-64. https://doi.org/10.1377/hlthaff.13.5.46