Si-Bone (SIBN) Change in Accured Expenses (2017 - 2026)
Si-Bone's Change in Accured Expenses came in at $1.24 million for Q2 2026, up 28.9% from $962,000 a year earlier.
Powered by 
Analysis
Si-Bone (SIBN) Change in Accured Expenses (2017 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Si-Bone reported Change in Accured Expenses of -$757,000; for FY2025, it was $179,000, down 90.6% from FY2024.
- Going back by year, Change in Accured Expenses was $1.91 million in FY2024 (-50.9%), $3.89 million in FY2023 (+222.1%), $1.21 million in FY2022 (-29.9%) and $1.72 million in FY2021.
- The five-year range for quarterly Change in Accured Expenses is -$5.66 million (Q1 2024) to $3.86 million (Q4 2023).
- Year-over-year, Change in Accured Expenses increased in 1 of the last six quarters, with an average decline of 19.7%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q3 2021 (growth of 699.5%), and the weakest in Q2 2025 (a decline of 43.8%).
- Business Quant data shows SIBN's Change in Accured Expenses at -$5.64 million (Q1 2026), $2.11 million (Q4 2025) and $1.54 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | - |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | - |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | -249.00 Mn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 55.00 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 298.00 Mn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | 234.00 Mn |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | 123.70 Mn |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | - |
| 10 | Si-Bone | 808.13 Mn | 223.93 Mn | 44.55 Mn | 1.24 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.24 Mn |
| Mar 31, 2026 | -5.64 Mn |
| Dec 31, 2025 | 2.11 Mn |
| Sep 30, 2025 | 1.54 Mn |
| Jun 30, 2025 | 962,000.00 |
| Mar 31, 2025 | -4.43 Mn |
| Dec 31, 2024 | 3.31 Mn |
| Sep 30, 2024 | 2.55 Mn |
| Jun 30, 2024 | 1.71 Mn |
| Mar 31, 2024 | -5.66 Mn |
| Dec 31, 2023 | 3.86 Mn |
| Sep 30, 2023 | 2.93 Mn |
| Jun 30, 2023 | 732,000.00 |
| Mar 31, 2023 | -3.63 Mn |
| Dec 31, 2022 | 2.29 Mn |
| Sep 30, 2022 | 1.01 Mn |
| Jun 30, 2022 | 1.07 Mn |
| Mar 31, 2022 | -3.17 Mn |
| Dec 31, 2021 | 1.40 Mn |
| Sep 30, 2021 | 1.74 Mn |
API Access
Si-Bone 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=SIBN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "SIBN", "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=SIBN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();