Boston Scientific (BSX) Accumulated Expenses (2009 - 2026)
Boston Scientific (BSX) recorded Accumulated Expenses of $2.76 billion in Q2 2026, down 1.5% from $2.8 billion a year earlier but up 9.6% from the prior quarter.
Boston Scientific (BSX) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Boston Scientific reported Accumulated Expenses of $3.2 billion, up 15.4% from FY2024.
- Annual Accumulated Expenses has increased for three straight years, with a five-year compound annual growth rate of 7.8% (FY2020 to FY2025).
- Across earlier years, Accumulated Expenses came in at $2.77 billion in FY2024 (+4.8%), $2.65 billion in FY2023 (+22.5%), $2.16 billion in FY2022 (-11.3%) and $2.44 billion in FY2021 (+10.9%).
- Quarterly Accumulated Expenses has ranged from $1.92 billion in Q1 2023 to $3.2 billion in Q4 2025 over the past five years.
- On a year-over-year basis, Accumulated Expenses rose in seven of the last eight quarters, with growth averaging 11.2%.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 22.5% in Q4 2023, against a decline of 18.4% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $2.51 billion (Q1 2026), $3.2 billion (Q4 2025) and $2.98 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn |
| 10 | Agilent Technologies | 48.58 Bn | 41.47 Bn | 1.04 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.76 Bn |
| Mar 31, 2026 | 2.51 Bn |
| Dec 31, 2025 | 3.20 Bn |
| Sep 30, 2025 | 2.98 Bn |
| Jun 30, 2025 | 2.80 Bn |
| Mar 31, 2025 | 2.35 Bn |
| Dec 31, 2024 | 2.77 Bn |
| Sep 30, 2024 | 2.46 Bn |
| Jun 30, 2024 | 2.32 Bn |
| Mar 31, 2024 | 2.08 Bn |
| Dec 31, 2023 | 2.65 Bn |
| Sep 30, 2023 | 2.26 Bn |
| Jun 30, 2023 | 2.16 Bn |
| Mar 31, 2023 | 1.92 Bn |
| Dec 31, 2022 | 2.16 Bn |
| Sep 30, 2022 | 1.97 Bn |
| Jun 30, 2022 | 2.20 Bn |
| Mar 31, 2022 | 2.31 Bn |
| Dec 31, 2021 | 2.44 Bn |
| Sep 30, 2021 | 2.42 Bn |
Boston Scientific Accumulated 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=accumulated-expenses&ticker=BSX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=BSX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();