HLTH 6882 Week 5 Peer Benchmark Comparison Paper Example

Benchmark Comparison: Prairie Bend and a Peer Critical Access Hospital on Kept Specialist Slots and Booking Practice

Student Name

Walden University

HLTH 6882: Improving Healthcare Performance Through Social Entrepreneurship

Instructor Name

Month Day, Year

Benchmark Comparison: Prairie Bend and a Peer Critical Access Hospital on Kept Specialist Slots and Booking Practice

Introduction

The gap analysis set Prairie Bend Community Hospital an internal target of keeping 90% of booked specialist slots, based on its own best months. An internal target shows what the clinic has managed; a peer shows what a similar organization manages under ordinary conditions. This paper pairs Prairie Bend with Cedar Ford Memorial Hospital, a composite peer: another critical access hospital in the same state network, with a visiting specialist clinic of similar size. Both hospitals and all figures are illustrative. The comparison runs in three layers. It first reconciles how each hospital counts a lost slot, then compares performance and finally compares practice, which is where most of the paper's attention goes.

Choosing the Partner

Cedar Ford was chosen because it resembles Prairie Bend where it matters for this problem. Like Prairie Bend, it holds critical access status with 25 beds, and it sits about 90 miles away, serving a rural population of similar size and age. Its visiting clinic hosts cardiology and orthopedics from the same regional specialist groups, plus general surgery, on four session days a month. It has no staffed call center; one scheduler and a part-time clerk run its specialist bookings. A large urban system with a central scheduling department would show better figures and prove little, because Prairie Bend could not copy its staffing.

The state rural hospital network's data-sharing agreement allows member hospitals to exchange monthly aggregate figures on specialist clinic bookings and visits, and to describe their scheduling practices to one another. It does not allow patient-level records to be shared. Every Cedar Ford figure in this paper is therefore an aggregate from its monthly network reports for the same 12 months covered by Prairie Bend's gap analysis.

Layer One: Reconciling Definitions

The two hospitals did not count lost slots in the same way, so their raw rates could not be compared.

Table 1

How Each Hospital Counts Slot Outcomes, and the Adjustment Made (Illustrative)

Layer Two: Performance

Before adjustment, Cedar Ford reported a kept rate of 91% over the 12 months. After re-counting late cancellations at two business days, its rate fell to 88%; re-counting same-day moves as kept added about half a point, for an adjusted rate of about 88%. Prairie Bend's rate over the same months was 75%. On comparable definitions, Cedar Ford kept about 13 more slots in every 100 booked. At Prairie Bend's volume of about 160 booked slots a month, that difference would mean about 21 more visits a month.

Cedar Ford's rate was also steadier, ranging from 84% to 92% across the year, against Prairie Bend's range of 68% to 91%. Prairie Bend's best months reached Cedar Ford's typical performance, which supports the internal target of 90% as reachable.

Layer Three: Practice

Cedar Ford's scheduler described four practices that differ from Prairie Bend's.

A three-week booking window. Cedar Ford does not book a referral into the next open slot on arrival. Referrals go onto a holding list, and session slots are opened for booking only three weeks before each session day. Urgent referrals, flagged by the referring provider, are booked at once. As a result, almost no Cedar Ford visit is booked more than about three weeks ahead. This is the practice most directly tied to Prairie Bend's root cause, which was an unwritten rule of booking every referral as soon as it arrives. Advanced access work in primary care made the broader argument that the delay between request and visit is a product of scheduling rules and can be redesigned (Murray & Berwick, 2003).

A short-notice list. Cedar Ford keeps a list of patients on the holding list who have said they can come at a day or two's notice. When a late cancellation occurs, the scheduler calls down the list. The scheduler estimates that about half of late cancellations are refilled this way.

Text reminders one week ahead. A week ahead of each visit, Cedar Ford texts the patient, who can answer the message to cancel. A Cochrane review found moderate quality evidence that texted reminders raise attendance: 78.6% of patients attended in reminder groups, and 67.8% in groups that received none (Gurol-Urganci et al., 2013).

Volunteer drivers. Cedar Ford's county aging office runs a volunteer driver program that will take patients to the specialist clinic on request.

What Could Transfer

The booking window and the short-notice list could transfer to Prairie Bend with little change. Both are rules about how the scheduler works, they do not depend on anything particular to Cedar Ford and they act directly on the root cause found in Week 4. Long lead time is one of the factors most often associated with missed appointments in the research literature (Dantas et al., 2018), and capping how far ahead visits can be booked strips out most of those distant bookings.

Text reminders could transfer if Prairie Bend's scheduling system can send them, which needs to be checked with its vendor. They are supported by evidence but address forgetting rather than the long lead time that causes it, so they are a supporting practice rather than the main change.

The volunteer driver program depends on Cedar Ford's county, not on the hospital. Prairie Bend's root cause analysis rejected transport as the main cause of lost slots, so a driver program would not address the problem diagnosed. It may still help in one specific way: patients on a short-notice list need to reach the clinic at short notice, and some may need a ride to do so. Whether Prairie Bend's counties have a comparable program is a question for the change proposal.

Limits of the Comparison

The comparison has three limits. Cedar Ford's figures are aggregates reported by Cedar Ford, and Prairie Bend cannot verify them against patient records. The adjustment to two-business-day cancellations relies on Cedar Ford's own re-count of its cancellation log. And Cedar Ford differs in ways not captured here, including its general surgery sessions and its scheduler's longer tenure. The benchmark shows that a similar hospital keeps about 88% of slots with practices Prairie Bend could adopt; it does not prove that adopting them would produce the same result. That is what the change proposal and pilot are for.

References

Dantas, L. F., Fleck, J. L., Cyrino Oliveira, F. L., & Hamacher, S. (2018). No-shows in appointment scheduling: A systematic literature review. Health Policy, 122(4), 412-421. https://doi.org/10.1016/j.healthpol.2018.02.002

Gurol-Urganci, I., de Jongh, T., Vodopivec-Jamsek, V., Atun, R., & Car, J. (2013). Mobile phone messaging reminders for attendance at healthcare appointments. Cochrane Database of Systematic Reviews, (12), Article CD007458. https://doi.org/10.1002/14651858.CD007458.pub3

Murray, M., & Berwick, D. M. (2003). Advanced access: Reducing waiting and delays in primary care. JAMA, 289(8), 1035-1040. https://doi.org/10.1001/jama.289.8.1035