Long-Term Care Utilization Rates
This dataset provides detailed long-term care utilization metrics, including nursing home admission rates, assisted living usage, home health care frequency, and care duration, segmented by age group, year, and region. It is designed to support actuarial analysis, insurance reserve modeling, and healthcare planning for aging populations. The flat structure enables easy integration with business intelligence and actuarial systems.
Sample rows
preview · 8 of 500 rows · all 11 columns| record_idstring | age_groupstring | average_duration_of_care_daysfloat | genderstring | nursing_home_admission_ratefloat | assisted_living_usage_ratefloat | home_health_care_frequencyfloat | ltc_insurance_reserve_factorfloat | yearinteger | regionstring | data_sourcestring |
|---|---|---|---|---|---|---|---|---|---|---|
| R001 | 65-69 | 22.1 | female | 14.6 | 11.3 | 7.5 | 1.08 | 2017 | California | Insurer A Claims |
| R002 | 70-74 | 27.6 | male | 21.2 | 15.7 | 9.4 | 1.19 | 2021 | Texas | Government Health Survey |
| R003 | 75-79 | 35.8 | female | 32.8 | 23.4 | 12.8 | 1.46 | 2015 | New York | Insurer B Annual Report |
| R004 | 80+ | 78.2 | male | 59.5 | 50.1 | 24.2 | 2.85 | 2019 | Florida | Regional Hospital Data |
| R005 | 68-72 | 25 | female | 18.2 | 13.9 | 8.7 | 1.12 | 2022 | Ohio | Insurer C Utilization |
| R006 | 65+ | 0.5 | unknown | 0.2 | 0.5 | 0 | 0.01 | 2099 | Montana | Synthetic Boundary Value |
| R007 | 75-80 | 42.6 | male | 38.1 | 27.9 | 16.4 | 1.58 | 2020 | Illinois | Insurer D Claims |
| R008 | 70-74 | 28.9 | other | 23.4 | 19.8 | 10.1 | 1.23 | 2018 | Georgia | Hospital Survey |
| R009 | 65-69 | 17.4 | male | 12.9 | 7.6 | 5.2 | 0.94 | 2014 | Arizona | Medicaid State Report |
| R010 | 80+ | 120 | female | 66.7 | 60 | 35 | 4.25 | 2016 | New Jersey | Edge Case Test Data |
| R011 | 75-79 | 37.7 | female | 36.4 | 22.5 | 13.2 | 1.41 | 2017 | Virginia | Insurer E Claims |
| R012 | 65-70 | 21.3 | male | 15.8 | 12 | 6.3 | 1.03 | 2012 | Colorado | Government Health Survey |
| R013 | 75-80 | 54.3 | other | 41.5 | 32 | 19.2 | 2.11 | 2023 | Oregon | Synthetic Model Case |
| R014 | 65+ | 0 | blank | 0 | 0 | 0 | blank | 1900 | Alabama | Boundary Value Report |
| R015 | 70-74 | 29.1 | female | 20.3 | 16.5 | 9.7 | 1.17 | 2011 | Michigan | Insurer F Annual Data |
| R016 | 80+ | 180 | unknown | 100 | 95 | 80 | 9.99 | 2100 | Hawaii | Synthetic Extreme Value |
| R017 | 68-72 | 23.5 | other | 19.3 | 14.8 | 8.9 | 1.11 | 2018 | Missouri | Hospital Utilization Study |
| R018 | 65-69 | 10.2 | blank | 6.2 | 4.9 | 2.8 | 0.84 | 2007 | Indiana | Sparse Utilization Study |
| R019 | 75-79 | 40.3 | male | 35.7 | 27.2 | 15.5 | 1.62 | 2010 | Minnesota | Insurer G Claims |
| R020 | 65+ | 18.9 | female | 11.5 | 12.7 | 8.1 | 0.93 | 2013 | Washington | Medicare Claims Data |
What the 500 rows show
from the 500-row sample80+ (age group) stands out: mean average_
- 20.9median average_
duration_ of_ care_ days - 51regions
- 22.4median nursing_
home_ admission_ rate - 15.1median assisted_
living_ usage_ rate - 8.2median home_
health_ care_ frequency - 1.1median ltc_
insurance_ reserve_ factor
Median 20.9, from 0.0 to 180.0.
- string 5
- integer 1
- float 5
Columns
11 columns in two groups| column | type | description | example |
|---|---|---|---|
| Text 5 columns | |||
record_id | string | Unique identifier for each utilization recordunique | R001 |
age_group | string | Age group category (e.g., '65-69', '70-74', '75-79', '80+')8 groups | 65-69 |
gender | string | Gender of the insured individual (male, female, other, unknown)male · female · other · unknown · optional | female |
region | string | Geographic region or state where data was collectedoptional | California |
data_source | string | Name or description of the data source (e.g., insurer, government report)optional | Insurer A Claims |
| Numbers 6 columns | |||
nursing_home_admission_rate | float | Annual rate of nursing home admissions per 1,000 insureds in this age group0 or more | 14.6 |
assisted_living_usage_rate | float | Annual rate of assisted living facility usage per 1,000 insureds in this age group0 or more | 11.3 |
home_health_care_frequency | float | Average number of home health care visits per insured per year in this age group0 or more | 7.5 |
average_duration_of_care_days | float | Average duration of care in days per episode for this age group0 or more | 22.1 |
ltc_insurance_reserve_factor | float | Reserve factor used for LTC insurance calculations for this age group0 or more · optional | 1.08 |
year | integer | Year the data was collected1,900 to 2,100 | 2017 |
Use it for
An insurance dashboard
Average_
duration_ of_ care_ days by age_ group and a breakdown of gender. Excel, Power BI or Tableau. Why do the 76 80+ rows have a mean average_
duration_ of_ care_ days of 92.2? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Records500R00122.165-69R00227.670-74R00335.875-79
A software demo
Believable records with age_
group, gender and nursing_ home_ admission_ rate to fill a screen in front of a buyer.
blueprint · long-term-care-utilization-rates
Behind this dataset
Same schema. As many rows as you need.
These 500 rows came out of a blueprint — 11 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- LTC need increases significantly with age
- Activities of Daily Living (ADL) triggers: 2 of 6 typical
- Cognitive impairment as alternative trigger
- Elimination period before benefits: 0, 30, 60, 90, 100 days
- Care settings: nursing home, assisted living, home care
- Daily benefit amount and benefit period
- Inflation protection: simple, compound, CPI
- Average length of stay in nursing home: 2-3 years
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- long-term-care-utilization-rates