Insulet (PODD) Change in Accrued Expenses (2009 - 2026)
Insulet's Change in Accured Expenses came in at $74.9 million for Q2 2026, up 11.3% from $67.3 million a year earlier.
Insulet (PODD) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Insulet reported Change in Accured Expenses of $147.1 million, up 94.6% year-over-year; for FY2025, it came in at $160.2 million, up 252.1% from FY2024.
- Change in Accured Expenses carries a five-year compound annual growth rate of 41.9% (FY2020 to FY2025).
- Going back by year, Change in Accured Expenses was $45.5 million in FY2024 (-35.3%), $70.3 million in FY2023 (-47.5%), $133.9 million in FY2022 (+489.9%) and $22.7 million in FY2021 (-18.3%).
- The five-year range for quarterly Change in Accured Expenses is -$69.3 million (Q1 2026) to $77.1 million (Q4 2025).
- Year-over-year, Change in Accured Expenses increased in five of the last six quarters, with growth averaging 88.6%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q4 2025 (growth of 497.7%), and the weakest in Q2 2023 (a decline of 77.6%).
- Business Quant data shows PODD's Change in Accured Expenses at -$69.3 million (Q1 2026), $77.1 million (Q4 2025) and $64.4 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 266.22 Bn | 242.86 Bn | 5.13 Bn | - |
| 2 | Abbott Laboratories | 191.31 Bn | 165.77 Bn | 7.39 Bn | - |
| 3 | Danaher | 166.16 Bn | 145.82 Bn | 3.84 Bn | 30.00 Mn |
| 4 | Intuitive Surgical | 155.98 Bn | 136.40 Bn | 2.08 Bn | 80.10 Mn |
| 5 | Medtronic | 130.05 Bn | 96.18 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 123.40 Bn | 109.59 Bn | 4.25 Bn | 77.00 Mn |
| 7 | Boston Scientific | 64.81 Bn | 60.48 Bn | 3.43 Bn | 89.00 Mn |
| 8 | Edwards Lifesciences | 59.87 Bn | 43.18 Bn | 1.35 Bn | 67.20 Mn |
| 9 | Medline | 53.84 Bn | 50.96 Bn | 1.93 Bn | 255.00 Mn |
| 10 | Insulet | 10.27 Bn | 7.96 Bn | 632.10 Mn | 34.50 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 34.50 Mn |
| Jun 30, 2026 | 74.90 Mn |
| Mar 31, 2026 | -69.30 Mn |
| Sep 30, 2025 | 64.40 Mn |
| Jun 30, 2025 | 67.30 Mn |
| Mar 31, 2025 | -48.60 Mn |
| Dec 31, 2024 | 12.90 Mn |
| Sep 30, 2024 | 44.00 Mn |
| Jun 30, 2024 | 50.90 Mn |
| Mar 31, 2024 | -62.30 Mn |
| Dec 31, 2023 | 53.40 Mn |
| Sep 30, 2023 | 36.70 Mn |
| Jun 30, 2023 | 16.10 Mn |
| Mar 31, 2023 | -35.90 Mn |
| Dec 31, 2022 | 46.10 Mn |
| Sep 30, 2022 | 49.60 Mn |
| Jun 30, 2022 | 71.90 Mn |
| Mar 31, 2022 | -33.70 Mn |
| Dec 31, 2021 | 28.30 Mn |
| Sep 30, 2021 | -300,000.00 |
Insulet Change in Accrued 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=PODD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "PODD", "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=PODD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();