Boston Scientific (BSX) Operating Expenses (2009 - 2026)
Boston Scientific (BSX) posted Operating Expenses of $2.67 billion for Q2 2026, up 2.5% from $2.61 billion a year earlier and up 6.2% from the prior quarter.
Boston Scientific (BSX) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Boston Scientific was $10.53 billion, up 11.1% year-over-year; for FY2025, it was $10.24 billion, up 15.2% from FY2024.
- Annual Operating Expenses has increased for eight consecutive years, with a five-year compound annual growth rate of 9.4% (FY2020 to FY2025).
- In prior years, Boston Scientific's Operating Expenses was $8.89 billion in FY2024 (+17.7%), $7.55 billion in FY2023 (+6.7%), $7.08 billion in FY2022 (+1.4%) and $6.98 billion in FY2021 (+6.9%).
- Quarterly Operating Expenses has run from a low of $1.61 billion in Q1 2022 to a high of $2.85 billion in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 11 quarters, with growth averaging 14.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2024, with growth of 24.9%; the weakest was Q3 2021, with a decline of 17.5%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $2.51 billion (Q1 2026), $2.85 billion (Q4 2025) and $2.49 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Agilent Technologies | 49.40 Bn | 42.29 Bn | 1.04 Bn | 1.43 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.67 Bn |
| Mar 31, 2026 | 2.51 Bn |
| Dec 31, 2025 | 2.85 Bn |
| Sep 30, 2025 | 2.49 Bn |
| Jun 30, 2025 | 2.61 Bn |
| Mar 31, 2025 | 2.29 Bn |
| Dec 31, 2024 | 2.42 Bn |
| Sep 30, 2024 | 2.16 Bn |
| Jun 30, 2024 | 2.33 Bn |
| Mar 31, 2024 | 1.97 Bn |
| Dec 31, 2023 | 2.00 Bn |
| Sep 30, 2023 | 1.73 Bn |
| Jun 30, 2023 | 2.03 Bn |
| Mar 31, 2023 | 1.80 Bn |
| Dec 31, 2022 | 1.83 Bn |
| Sep 30, 2022 | 1.83 Bn |
| Jun 30, 2022 | 1.81 Bn |
| Mar 31, 2022 | 1.61 Bn |
| Dec 31, 2021 | 1.98 Bn |
| Sep 30, 2021 | 1.65 Bn |
Boston Scientific Operating 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=operating-expenses&ticker=BSX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BSX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=BSX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();