DataMeds AI (MEDS) Other Accumulated Expenses (2023 - 2026)
DataMeds AI (MEDS) recorded Other Accumulated Expenses of $1.17 million in Q1 2026, up 32.7% from $877,807 a year earlier and up 39.8% from the prior quarter.
DataMeds AI (MEDS) Other Accumulated Expenses (2023 - 2026) Analysis & Trends
At the end of FY2025, DataMeds AI reported Other Accumulated Expenses of $833,647, up 65.4% from FY2024.
- Across earlier years, Other Accumulated Expenses came in at $504,152 in FY2024 (+271.8%) and $135,586 in FY2023.
- Quarterly Other Accumulated Expenses has ranged from $135,586 in Q4 2023 to $1.2 million in Q2 2025 over the past five years.
- Per Business Quant, the preceding three quarters came in at $833,647 (Q4 2025), $422,041 (Q3 2025) and $1.2 million (Q2 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Unitedhealth | 336.54 Bn | 221.18 Bn | 36.67 Bn |
| 2 | Cvs Health | 110.50 Bn | 63.10 Bn | 47.23 Bn |
| 3 | Mckesson | 105.27 Bn | 91.73 Bn | 3.69 Bn |
| 4 | Elevance Health | 83.85 Bn | -57.90 Bn | 13.45 Bn |
| 5 | Cigna | 71.48 Bn | 41.02 Bn | 14.97 Bn |
| 6 | Cencora | 58.97 Bn | 48.06 Bn | 3.61 Bn |
| 7 | Cardinal Health | 53.10 Bn | 37.10 Bn | 2.56 Bn |
| 8 | Humana | 46.62 Bn | -41.18 Bn | 5.50 Bn |
| 9 | Centene | 31.12 Bn | -59.17 Bn | 14.55 Bn |
| 10 | DataMeds AI | 8.79 Mn | 4.04 Mn | 170,221.00 |
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 1.17 Mn |
| Dec 31, 2025 | 833,647.00 |
| Sep 30, 2025 | 422,041.00 |
| Jun 30, 2025 | 1.20 Mn |
| Mar 31, 2025 | 877,807.00 |
| Dec 31, 2024 | 504,152.00 |
| Dec 31, 2023 | 135,586.00 |
DataMeds AI Other 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=other-accumulated-expenses&ticker=MEDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "ticker": "MEDS", "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-accumulated-expenses&ticker=MEDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();