Steris (STE) Change in Accured Expenses (2018 - 2026)
Steris' Change in Accured Expenses was $4.8 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), compared with -$9.2 million a year earlier and down 93.5% from the prior quarter.
Steris (STE) Change in Accured Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Steris' Change in Accured Expenses was $61.8 million through Jun 30, 2026, up 119.1% year-over-year; for FY2026 (ended Mar 31, 2026), it was $47.8 million, up 22.9% from FY2025.
- Change in Accured Expenses shows a five-year compound annual growth rate of 37.0% (FY2021 to FY2026).
- In earlier fiscal years, Change in Accured Expenses was $38.9 million in FY2025 (-2.8%), $40 million in FY2024, -$22.05 million in FY2023 and -$16.4 million in FY2022.
- Quarterly Change in Accured Expenses has moved between -$85.94 million (fiscal Q2 2023) and $74.3 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last four quarters, with growth averaging 39.3%.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q3 2023 (growth of 165.7%); the worst was fiscal Q1 2025 (a decline of 96.0%).
- Per Business Quant data, STE's Change in Accured Expenses in the three fiscal quarters before Q1 2027 was $74.3 million (Q4 2026), $25.6 million (Q3 2026) and -$42.9 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 241.25 Bn | 220.40 Bn | 4.88 Bn | - |
| 2 | Abbott Laboratories | 167.33 Bn | 138.41 Bn | 7.27 Bn | - |
| 3 | Danaher | 148.83 Bn | 132.65 Bn | 3.61 Bn | -249.00 Mn |
| 4 | Intuitive Surgical | 142.00 Bn | 121.55 Bn | 1.96 Bn | 55.00 Mn |
| 5 | Medtronic | 110.70 Bn | 76.57 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 104.72 Bn | 90.84 Bn | 4.50 Bn | 298.00 Mn |
| 7 | Boston Scientific | 62.66 Bn | 57.67 Bn | 3.85 Bn | 234.00 Mn |
| 8 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn | 123.70 Mn |
| 9 | Becton Dickinson | 48.51 Bn | 45.66 Bn | 2.32 Bn | - |
| 10 | Steris | 20.41 Bn | 18.76 Bn | 684.20 Mn | 4.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.80 Mn |
| Mar 31, 2026 | 74.30 Mn |
| Dec 31, 2025 | 25.60 Mn |
| Sep 30, 2025 | -42.90 Mn |
| Jun 30, 2025 | -9.20 Mn |
| Mar 31, 2025 | 43.40 Mn |
| Dec 31, 2024 | 30.80 Mn |
| Sep 30, 2024 | -36.80 Mn |
| Jun 30, 2024 | 1.50 Mn |
| Mar 31, 2024 | 18.25 Mn |
| Dec 31, 2023 | 47.20 Mn |
| Sep 30, 2023 | -63.37 Mn |
| Jun 30, 2023 | 37.92 Mn |
| Mar 31, 2023 | 44.86 Mn |
| Dec 31, 2022 | 45.99 Mn |
| Sep 30, 2022 | -85.94 Mn |
| Jun 30, 2022 | -26.96 Mn |
| Mar 31, 2022 | 1.28 Mn |
| Dec 31, 2021 | 17.31 Mn |
| Sep 30, 2021 | 6.91 Mn |
Steris Change in Accured Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=STE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "STE", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=STE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();