The hourly rate of long-term home care services has increased in the United States and is expected to increase further in the future. In 2024, the cost for long-term care in the U.S. was ** U.S. dollars per hour for homemaker services and ** U.S. dollars per hour for home health aide services. By 2030, prices for such services are expected to surpass ** dollars an hour. By 2060, a price of nearly *** dollars per hour was forecasted for home health aide services.

The demand for long-term care (LTC) in Canada is forecasted to rise to *** thousand by 2031. That is a growth of nearly ** percent from 2019 levels. In 2019, there were ******* Canadians in LTC with a further ****** on the waitlist adding to a total of over *** thousand needing long-term care. Moreover, the need for home care services and support is even greater with over *** million Canadians receiving or wanting such services in 2019 (**** percent receiving and *** percent wanting professional home care services). This is forecasted to reach nearly *** million by 2031. Taken together, this amounts to **** million Canadians in need for long-term care and home care in 2031.

Nearly all states in the U.S. are employing strategies to expand home- and community-based services (HCBS). Furthermore, a large number of states are using HCBS waivers or state plan amendments (SPA) to serve individuals in the community.

The groups in need of long-term care Medicaid provides health coverage to millions of Americans, and over the years, many states have chosen to expand the availability of long-term care services. Home- and community-based services allow beneficiaries to receive care in their own home or other community settings, as opposed to institutional care provided in nursing facilities. These services target and support several population groups, including older adults, individuals with physical disabilities, and those with mental illnesses.

The rising costs of long-term care Medicaid is responsible for covering large numbers of senior citizens and individuals with disabilities, and these two enrollment groups accounted for more than half of all Medicaid expenditure in 2017 – spending per enrollee was also significantly higher for these two groups. States are being encouraged to design long-term care plans that allow individuals to live in their homes or community setting, and it is hoped that this will reduce expenditures for enrollees who would otherwise have had to enter nursing homes.

Market Size statistics on the Long Term Care Insurance industry in the US

On an annual basis (calendar year), individual LTC facilities report facility-level data on services capacity, utilization, patients, and capital/equipment expenditures.

GIS Feature class polygon of Zip codes in Jefferson County joined with Latest Confirmed Cases by Zip code without Long Term Care and Population of 2019 ACS Demographic Data by Zip code. This feature is used in the Covid-19 Jefferson County Public Hub Site https://covid-19-in-jefferson-county-ky-lojic.hub.arcgis.com/Note: This data is preliminary, routinely updated, and is subject to change.For questions about this data please contact Angela Graham (Angela.Graham@louisvilleky.gov) or YuTing Chen (YuTing.Chen@louisvilleky.gov) or call (502) 574-8279.

GIS Feature class polygon of Zip codes in Jefferson County joined with Latest Confirmed Cases by Zip code with Long Term Care and Population of 2019 ACS Demographic Data by Zip code. This feature is used in the Covid-19 Jefferson County Public Hub Site https://covid-19-in-jefferson-county-ky-lojic.hub.arcgis.com/Note: This data is preliminary, routinely updated, and is subject to change.For questions about this data please contact Angela Graham (Angela.Graham@louisvilleky.gov) or YuTing Chen (YuTing.Chen@louisvilleky.gov) or call (502) 574-8279.

's Capacity of long-term care health facilities is 7,747person which is the 16th highest in Japan (by Prefecture). Transition Graphs and Comparison chart between Fukushima and Okayama(Okayama) and Mie(Mie)(Closest Prefecture in Population) are available. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

Japan HA: Long-Term Care Insurance data was reported at 460,556.000 JPY mn in 2019. This records an increase from the previous number of 445,508.000 JPY mn for 2018. Japan HA: Long-Term Care Insurance data is updated yearly, averaging 346,454.000 JPY mn from Mar 2007 (Median) to 2019, with 13 observations. The data reached an all-time high of 460,556.000 JPY mn in 2019 and a record low of 265,850.000 JPY mn in 2007. Japan HA: Long-Term Care Insurance data remains active status in CEIC and is reported by Statistics of Tokyo. The data is categorized under Global Database’s Japan – Table JP.F035: Social Security Contributions: Tokyo Metropolitan: SNA 2008: Benchmark year=2011.

Hualien County social welfare related information in 2019

This data set reflects the number of complaints the Long-Term Care (LTC) Ombudsman Program received during Federal Fiscal Years (FFY) 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019 on behalf of residents in Residential Care Facilities for the Elderly (RCFE) settings. The LTC Ombudsman Program identifies, investigates and resolves complaints made by or on behalf of residents in LTC facilities and receives and investigates reports of suspected abuse of elder and dependent adults occurring in LTC and some community care facilities. RCFEs include smaller board and care (6 beds) and larger assisted living facilities licensed by the California Department of Social Services. This data corresponds to federally required complaint categories. Complaints that are still open at the end of the FFY would be included in the following FFY data report.

As of June 2019, about 17.6 percent of long-term care or support recipients fell under the condition due to dementia. Over 16 percent of recipients began to require care or support after they suffered from a cerebrovascular disease such as apoplectic stroke.

1. Evaluation results of long-term care facilities for the elderly from 2019 to 2024 - Evaluation conducted every three years by type of benefit: ('19) Home even → ('20) Home odd → ('21) Facility → ('23) Home odd → ('24) Home even * Due to COVID-19, the 2021 facility evaluation was extended to 2022 2. Evaluation category, long-term care facility symbol, long-term care facility name, benefit type, establishment entity, jurisdiction city/province name, jurisdiction city/county name, evaluation date. Evaluation grade, total evaluation score, institution operation, environment and safety, protection of recipient rights, benefit provision process, benefit provision result * The total evaluation score will be disclosed from the 2021 regular evaluation ※ Excerpted data as of June 27, 2025. Same as the list name and status of evaluation grades for long-term care facilities previously provided

This data set reflects the number of complaints the Long-Term Care (LTC) Ombudsman Program received during Federal Fiscal Years (FFY) 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019 on behalf of residents in Skilled Nursing Facility (SNF) and Intermediate Care Facility (ICF) settings. The LTC Ombudsman Program identifies, investigates and resolves complaints made by or on behalf of residents in LTC facilities and receives and investigates reports of suspected abuse of elder and dependent adults occurring in LTC and some community care facilities. SNFs and ICFs are Nursing Facility (NF) settings licensed by the California Department of Public Health. This data corresponds to federally required complaint categories. Complaints that are still open at the end of the FFY would be included in the following FFY data report.

On an annual basis (based on individual Long-Term Care (LTC) facility fiscal year end), California licensed LTC facilities report detailed financial data on facility information, ownership information, patient days & discharges, Balance Sheet, Equity Statement, Cash Flows, Income Statement, Revenue by type and payer, Expense Detail, and Labor Detail. Based on the selected data set, the pivot tables display summarized data on a Profile page and also provides charts on various data items such as Patient Days, Revenue & Expense, and Revenue.

Japan SSC: Long-Term Care Insurance data was reported at 585,965.000 JPY mn in 2019. This records an increase from the previous number of 568,512.000 JPY mn for 2018. Japan SSC: Long-Term Care Insurance data is updated yearly, averaging 438,148.000 JPY mn from Mar 2007 (Median) to 2019, with 13 observations. The data reached an all-time high of 585,965.000 JPY mn in 2019 and a record low of 338,609.000 JPY mn in 2007. Japan SSC: Long-Term Care Insurance data remains active status in CEIC and is reported by Statistics of Tokyo. The data is categorized under Global Database’s Japan – Table JP.F035: Social Security Contributions: Tokyo Metropolitan: SNA 2008: Benchmark year=2011.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Long-Term Care Licensing licenses and inspects Arizona nursing homes facilities. Long-Term Care staff also perform Medicaid certification inspections for Arizona's Intermediate Care Facilities for the Developmentally Disabled (ICFDD).Records are created and maintained by Bureau of Long-Term Care Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including long-term care facilities. Last Updated: February 2025Updated frequency: MonthlyData FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

United States Life Insurers: Expenditures: Contract Payments: Health Insurance: Long term care data was reported at 9.584 USD bn in 2023. This records an increase from the previous number of 6.167 USD bn for 2022. United States Life Insurers: Expenditures: Contract Payments: Health Insurance: Long term care data is updated yearly, averaging 8.040 USD bn from Dec 2019 (Median) to 2023, with 5 observations. The data reached an all-time high of 9.584 USD bn in 2023 and a record low of 6.167 USD bn in 2022. United States Life Insurers: Expenditures: Contract Payments: Health Insurance: Long term care data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG006: Life Insurance: Contract Payments.

The table contains quarterly figures on the number of actively waiting (shorter and longer than the Treek norm) and non-active waiting for long-term care under the Long-Term Care Act (Wlz) with and without bridging care. The figures are measured quarterly on the first day of January, April, July and October and are available for the nursing and care, disabled care and mental health care sectors. The figures relate to care in kind, not to care paid for from personal budgets. The figures in this table come from the Long-Term Care Waiting Lists (Information Standard Long-Term Care Act or iWlz) that are supplied by care offices to the National Health Care Institute (ZiNL). Due to the introduction of the new release of the message traffic (iWlz 2.0), no data on active waiting (shorter than the treek standard) with reference date 1 April 2018 are included, and the figures on active (shorter and longer than the treek standard) and non-active people are missing. actively waiting with reference date 1 July 2018. Due to new connections with administrations, waiting list figures on 1 October may deviate from the figures with reference date 1 April 2018. The figures broken down by self-employed persons only relate to intramural care until April 2018 and from April 2018 to both intramural and extramural care. Due to the classification by sector on the basis of the self-employed person instead of the primary basis of the client, the sum of the figures on self-employed persons deviates shorter than the treek standard for the 3rd and 4th quarters of 2016, the 4th quarter of 2018 and the 3rd quarter of 2019 for those actively waiting per healthcare sector from the totals per healthcare sector in the table. Data available from 2015 up to and including the 1st quarter of 2021 Status of the figures: The quarterly figures for the most recent reporting year are provisional. The other quarterly figures are final. Since the table has been discontinued, the data is no longer finalized. Change as of October 5, 2021: This table has been discontinued and has been replaced by the new table 'Waiting in long-term care; sector, quarter' (see section 3). Changes as of March 2, 2021: - Provisional figures on reference date January 1, 2021 have been added. - The provisional figures for 2020 have been finalized unchanged. - The selection 'Health care sector' has been further subdivided into care intensity package with retroactive effect. The name has therefore been changed from 'Healthcare sector' to 'Health care package'. Changes as of December 16, 2020: In May 2020, quarterly figures were added for 2015 to 2019 for those actively waiting shorter than the treek standard with a different reference date (February 1, May 1, August 1 and November 1). This has been corrected for these figures and the higher total figures, so that all figures in the table again have the correct reference date (1 January, 1 April, 1 July and 1 October). When will new numbers come out? Not applicable anymore.