- Enter the daily cost of care. Use the expected cost for the type and setting of care you want to model.
- Enter the expected number of care days. Use total days of covered-care need before applying the policy elimination period.
- Add the daily benefit limit. Enter the maximum daily amount the policy would pay under your scenario.
- Enter the elimination period. This is the number of modeled care days that must pass before benefit payments begin.
- Set the probability. Enter the probability of needing this covered-care scenario, from 0% to 100%.
- Review expected and maximum values. The main result is probability-weighted; the breakdown also shows the unweighted maximum modeled payout.
Long Term Care Insurance Expected Claim Calculator
Estimate the probability-weighted claim payout from a long-term care insurance policy using a daily care cost, expected duration of care, benefit limit, elimination period, and probability of needing covered care. It turns a possible future claim into an expected-value figure that can be compared with premiums, savings, or alternative coverage designs. The calculator separates three ideas that are often mixed together: the gross cost of care, the maximum amount the policy could pay under the entered benefit limit, and the expected claim value after weighting that payout by the assumed probability. This makes it useful for scenario analysis, not for predicting whether a specific person will qualify for benefits.
Enter your assumptions
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Result
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Expected claim payout
Gross modeled care cost—
Eligible days after elimination—
Maximum modeled policy payout—
Expected uncovered care cost—
Eligible days = max(0, Care days − Elimination days)Maximum modeled payout = min(Daily care cost, Daily benefit) × Eligible daysExpected claim payout = Maximum modeled payout × Probability
Where:
- Care days = modeled duration of care, in days
- Elimination days = days before modeled benefit payments begin
- Daily care cost = estimated cost per day
- Daily benefit = policy benefit cap per eligible day
- Probability = assumed chance of this covered-care scenario, as a decimal
Assumptions: The model assumes a simple daily reimbursement structure and a single care episode. It does not model shared-care features, benefit pools, inflation protection, different care settings, eligibility triggers, exclusions, or insurer claim adjudication.
What the result means
The expected claim payout is the modeled maximum payout multiplied by the entered probability; it is useful for comparing scenarios but is not a guaranteed benefit.
Actual long-term care insurance contracts define covered services, benefit triggers, elimination periods, reimbursement methods, and maximum benefits differently.
Given: Daily care costs are estimated at $280 for 730 days. The policy pays up to $220 per day after a 90-day elimination period, and the modeled probability of needing covered care is 35%.
Calculation: Eligible days = 730 − 90 = 640. Gross care cost = $280 × 730 = $204,400. Maximum modeled payout = min($280, $220) × 640 = $140,800. Expected claim payout = $140,800 × 0.35 = $49,280.
Result: The probability-weighted expected claim payout is $49,280.
Interpretation: The policy could pay up to $140,800 in this modeled episode, but the expected-value figure is lower because it weights that payout by a 35% probability.
Why is the main result lower than the maximum payout?
The main result is probability-weighted. A policy may pay the modeled maximum only if the covered-care event occurs and the claim meets the contract terms.
Should care duration include the elimination period?
Yes. Enter the total modeled care duration; the calculator subtracts the elimination days when estimating payable days.
What happens if the daily benefit is higher than the care cost?
The model limits the daily payout to the entered care cost. This avoids creating a reimbursement amount above the modeled daily expense.
Does the calculator include a lifetime benefit maximum?
No separate lifetime pool is included. If your policy has a total-dollar or maximum-benefit-period cap, the modeled payout may need an additional cap.
Can I use this result to decide whether a policy is worth its premium?
You can use it as one scenario input, but a full comparison should also consider contract terms, premium changes, liquidity needs, tax treatment, and the value of risk transfer.