Haemonetics (HAE) Other Non-Current Liabilities (2010 - 2026)
Haemonetics (HAE) reported Other Non-Current Liabilities of $57.17 million for fiscal Q1 2027 (quarter ended Jun 27, 2026), down 16.0% from $68.07 million a year earlier and down 3.7% from the prior quarter.
Haemonetics (HAE) Other Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 28, 2026), Haemonetics posted Other Non-Current Liabilities of $59.39 million, down 12.9% from FY2025.
- Other Non-Current Liabilities has a five-year compound annual growth rate of -10.0% (FY2021 to FY2026).
- By fiscal year, Other Non-Current Liabilities came in at $68.19 million in FY2025 (-9.1%), $75.04 million in FY2024 (+0.4%), $74.72 million in FY2023 (-6.5%) and $79.88 million in FY2022 (-20.4%).
- The fiscal Q1 2027 figure ranks as the lowest quarterly Other Non-Current Liabilities since fiscal Q2 2020.
- Year over year, Other Non-Current Liabilities has now declined in each of the last six quarters, with an average decline of 9.2% over the last eight quarters.
- The high point for year-over-year Other Non-Current Liabilities in five years was fiscal Q2 2025 (growth of 28.7%); the low point was fiscal Q3 2026 (a decline of 29.3%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $59.39 million (Q4 2026), $63.61 million (Q3 2026) and $66.07 million (Q2 2026).
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 | Haemonetics | 4.79 Bn | 3.66 Bn | 202.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 57.17 Mn |
| Mar 28, 2026 | 59.39 Mn |
| Dec 27, 2025 | 63.61 Mn |
| Sep 27, 2025 | 66.07 Mn |
| Jun 28, 2025 | 68.07 Mn |
| Mar 29, 2025 | 68.19 Mn |
| Dec 28, 2024 | 89.96 Mn |
| Sep 28, 2024 | 90.01 Mn |
| Jun 29, 2024 | 92.26 Mn |
| Mar 30, 2024 | 75.04 Mn |
| Dec 30, 2023 | 76.26 Mn |
| Sep 30, 2023 | 69.93 Mn |
| Jul 1, 2023 | 71.98 Mn |
| Apr 1, 2023 | 74.72 Mn |
| Dec 31, 2022 | 78.22 Mn |
| Oct 1, 2022 | 78.40 Mn |
| Jul 2, 2022 | 73.85 Mn |
| Apr 2, 2022 | 79.88 Mn |
| Jan 1, 2022 | 85.94 Mn |
| Oct 2, 2021 | 91.86 Mn |
Haemonetics Other Non-Current Liabilities 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=other-non-current-liabilities&ticker=HAE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-non-current-liabilities", "ticker": "HAE", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-non-current-liabilities&ticker=HAE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();