Case studies that healthcare professionals believe.

Fictional sample. Wrenfield Health, Linnet and every person, quote and figure below are invented to show our format. They are not real results.

For: Hospital executives, procurement, CFOsProves: Operational and financial returnFormat: Interview, three voices

"The camera wasn't the hard part." Wrenfield Health on its first year of virtual nursing

On four medical-surgical units, patients left 51 minutes sooner after their discharge order, and agency nurse hours fell 54%, more than three times the drop on the system's other med-surg units. The program covered its costs in year one. Three leaders explain how, and what they would change.

In spring 2025, Wrenfield Health, a three-hospital community system, added virtual nurses to four medical-surgical units with 128 beds. Experienced registered nurses (RNs) working from a central hub now handle admission interviews, discharge teaching and medication education by two-way video. Bedside nurses keep all hands-on care, and staffing ratios did not change.

We asked three people who ran the rollout what changed, what it cost and what they would tell a peer.

What they would tell a peer

1. Write the camera rules with your nurses before go-live.
2. Staff virtual nurses for your admission and discharge peaks, not around the clock.
3. Pick your comparison units before you start, so the results hold up in front of your board.

Read this before you quote us

• Four units at one health system, over 12 months. A before-and-after comparison, not a randomized trial.
• Agency use fell on the comparison units too. The cash result counts only the difference.
• A discharge lounge opened at the main hospital in month seven and may account for part of the faster departures.
• The turnover value comes from HR's replacement-cost model and is not in the cash figure.

About

Wrenfield Health is a fictional three-hospital community health system. Linnet is a fictional virtual nursing platform from Linnet Health. It is clinical communication software, not a medical device. Linnet Health commissioned this case study, and Wrenfield received no payment or discount for taking part. All names, quotes and figures in this sample are invented.

Fictional sample. Kestrel Bay Stroke Network, Ocluva and every person, quote and figure below are invented to show our format. They are not real results.

For: Clinicians, key opinion leaders, value analysis committeesProves: Clinical benefit in practiceFormat: Evidence brief built around a pathway timeline

Real-world evidence brief

What 300 thrombectomy cases showed about stroke transfer times with Ocluva in routine care

At a glance

Design

Before-and-after review of a prospectively maintained stroke registry

Setting

One comprehensive stroke center (the hub) and five primary stroke centers (the spokes)

Product and status

Ocluva, radiological computer-aided triage and notification software (a real FDA-cleared category; this product is fictional). Notification only; not for diagnosis

Patients

300 adults with an internal carotid artery (ICA) or proximal middle cerebral artery (M1) occlusion treated with thrombectomy: 142 before, 158 after

Periods

12 months before go-live, and 12 months after a one-month run-in

Follow-up

90 days

Key points

Question:

After Ocluva went live across a six-hospital stroke network, did patients with a large vessel occlusion (LVO) reach thrombectomy sooner?

Findings:

In 300 thrombectomy cases, median time from CT angiography (CTA) to stroke-team notification fell from 24 to 6 minutes. At spoke hospitals, median door-in-door-out time fell from 141 to 112 minutes. Symptomatic hemorrhage rates did not differ.

Meaning:

Faster notification was associated with faster transfers. A before-and-after design cannot show that the software caused the change, and the review was not powered for 90-day outcomes.

The pathway, minute by minute

Most of the gain came at notification: the hub team now hears about a suspected LVO minutes after the CTA, and accepts the transfer sooner. Time from acceptance to departure barely moved, so transport is the next target.

Endpoints

Times are medians with interquartile ranges (IQR). Door-in-door-out runs from arrival at a spoke emergency department (ED) to departure for the hub. Door-to-groin runs from hub arrival to arterial puncture.

Before the review began, the network's stroke committee set 15 minutes as the smallest change in a treatment time it would call clinically meaningful [S4]. Medians were compared with the Mann–Whitney test, with bootstrap 95% confidence intervals (CI) for the difference; proportions with chi-square or Fisher's exact tests and Newcombe intervals [S1, S2].

How the software performed

In the 12 months after go-live [S3]:

• Ocluva analyzed 2,846 CTA scans and sent 412 alerts.
• 318 alerts (77%) were confirmed ICA or M1 occlusions on the radiologist's read; 94 (23%) were not.
• 23 of 341 confirmed occlusions (7%) had no alert. Their care followed the usual pathway, because the radiologist's read runs unchanged, in parallel.
• Nine of those 23 patients went on to thrombectomy. They are counted in the after group.

What this review cannot tell you

• Cause. A before-and-after comparison picks up anything else that changed. Teams also knew their times were being tracked.
• One staffing change overlapped. The hub added a second overnight neurointerventionalist in month nine. Excluding months nine to twelve, the door-in-door-out gain held at −29 minutes (95% CI −44 to −17). The door-to-groin gain shrank to −10 minutes (95% CI −24 to 5).
• Outcomes. The review was not powered for 90-day function or mortality. The 5.4-point difference in functional independence may be chance.
• Case mix. Groups were similar in age (median 71 and 70), stroke severity (median National Institutes of Health Stroke Scale score 15 and 16) and share of transfers (57% and 58%). Unmeasured differences may remain.
• Device accuracy. Performance was measured against routine radiologist reads, not a blinded expert panel.

Clinician perspectives

"We used to spend the first 20 minutes on the phone finding the right person. Now the images are on my phone before the spoke radiologist finishes the read."

"The software sped up the call. It didn't speed up the helicopter."

Regulatory status and About

Ocluva is a fictional product from Ocluva Health, and no FDA clearance is claimed for it. In this sample it stands in for FDA-cleared radiological computer-aided triage and notification software. It flags CTA scans with a suspected ICA or M1 occlusion and notifies the stroke team in parallel with standard image review. It does not mark findings on the image or remove cases from the reading queue, and it is not for diagnosis. Clinicians decide on treatment from the full imaging and clinical exam.

Kestrel Bay Stroke Network is a fictional network of one comprehensive stroke center and five primary stroke centers. Ocluva Health commissioned this brief, and the network pays the standard license fee. No clinician was paid for taking part, and neither quoted physician has a financial relationship with Ocluva Health. All names, quotes and figures in this sample are invented.

Fictional sample. Copperleaf Health Plan, HeartStead and every person, quote and figure below are invented to show our format. They are not real results.

For: Payers, formulary committees, employersProves: Cost, budget impact and returnFormat: Data-led, numbers first

HeartStead and the cost of heart failure: what Copperleaf Health Plan found over 12 months

$73 net savings per member per month (PMPM), after paying the $95 PMPM program fee. Medicare Advantage members with heart failure, 1,146 enrolled and 1,146 matched, 12 months after enrollment [S1–S3].

Net savings

$73 PMPM

Return per $1 of program fee

$1.77

Admissions vs expected

138 fewer per 1,000 member-years (−14%)

Break-even

76 fewer per 1,000 member-years

At month six, 74% of enrolled members were sending readings at least five days a week [S5].

Both groups improved. The gap is the program.

Every member in both groups had just been in the hospital, so admissions fell in both groups the next year, partly by chance (regression to the mean). The program's effect is the extra drop: 138 admissions per 1,000 member-years (95% CI 75 to 201).

Where the $73 comes from

Fewer admissions carry most of the savings. More outpatient visits and medicines offset part of it, consistent with closer follow-up.

What would change the answer

Holding the other effects constant, the program breaks even when it prevents 76 admissions per 1,000 member-years. Copperleaf saw 138, but the low end of the confidence interval sits right at break-even.

Budget impact per 1,000 member-years

Copperleaf's own year covered 1,067 member-years and came to $0.94 million net.

Method

Limits

• Members chose to enroll. Matching cannot balance motivation or family support, which may inflate the effect.
• One plan, one region, 12 months. Whether the effect lasts beyond a year is unknown.
• Deaths were similar (8.1% and 8.6%), and the analysis was not powered for mortality.
• Unit costs and the program fee are Copperleaf's. Other plans should rerun the model with their own.

Voice

"Everyone we enrolled had just been in the hospital, so we knew both groups would look better a year later. The only number we cared about was the gap."

About

Copperleaf Health Plan is a fictional Medicare Advantage plan. HeartStead is a fictional home heart failure monitoring program from HeartStead Health. Members get a connected scale and an FDA-cleared blood pressure monitor, and nurses review the readings and call members. The software sorts readings for nurse review and does not make treatment decisions. HeartStead Health commissioned this case study, and Copperleaf received no payment for taking part. All names, quotes and figures in this sample are invented.