Overview The Dartmouth Institute for Health Policy and Clinical Practice (TDI) has created a publicly available source of data that provides researchers, payers, regulators, and innovators with metrics that quantify temporal and regional patterns of health care spending and utilization in the United States. Using CMS Medicare claims data (mostly for age >64 enrollees), Atlas researchers built cohorts (“denominators”) and numerous measures or events (“numerators”) which were then used to calculate rates either by geography or for patients assigned to specific hospitals. These rates, which are calculated consistently across time and place, provide researchers with opportunities to evaluate spatial and temporal variation/trends. This entry contains Dartmouth Atlas rates for a variety of measures related to end-of-life care for fee-for-service (FFS) Medicare beneficiaries, age 67 to 99 at death, who were diagnosed with one or more of 12 different severe chronic illnesses in the last two years of life. Examples of measures (calculated over the last six months and last two years of life) include total Medicare spending, days in hospital, days in intensive care, number of physician visits, number of medical specialist visits, percentage of deaths occurring in hospital, and percentage of beneficiaries enrolled in hospice care. Rates are provided at the state, hospital referral region (HRR), and hospital levels, and all rates have been adjusted for age, sex, race, primary chronic condition, and the presence of more than one chronic condition. This entry also contains Dartmouth Atlas rates for a variety of measures related to end-of-life care for fee-for-service (FFS) Medicare beneficiaries, age 66 to 99 at death, who were diagnosed with a poor prognosis cancer in the last six months of life. Examples of measures include number of physician visits during the last six months of life, days in intensive care during the last month of life, percentage of patients receiving chemotherapy during the last two weeks of life, percentage of deaths occurring in hospital, and percentage of patients enrolled in hospice care. Rates are provided at the state, hospital referral region (HRR), and hospital levels, and all rates have been adjusted for age, sex, race, cancer type, and chronic illness. Users downloading data should review the methods sections of the related publications for context as well as for information about any temporal changes in methods. All reports in the Dartmouth Atlas of Health Care series are available from the National Library of Medicine https://www.ncbi.nlm.nih.gov/books/NBK584737/ Note that for the general Dartmouth Atlas rate datasets, which span multiple decades, the author list includes all Dartmouth staff (programmers, analysts, supervisors, etc.) involved in generating all types of Atlas rates across all years. We do not attempt to assign individuals to specific datasets or years.

This dataset tracks the updates made on the dataset "Percentage of Chronic Conditions among Fee-for-Service Medicare Beneficiaries, Washington State and Counties, 2007-2018" as a repository for previous versions of the data and metadata.

This table presents the number of pregnant and postpartum Medicaid and CHIP beneficiaries, 2017-2021. It includes (1) the number and percentage of beneficiaries ever pregnant in the year; (2) the number and percentage of live births in the year; (3) the number and percentage of miscarriages, stillbirths, or terminations in the year; and (4) the number and percentage of births with an unknown delivery outcome in the year. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues, making the data unusable for identifying this population. Data for a state are considered unusable based on DQ Atlas thresholds for the following topics: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Data from Maryland, Tennessee, and Utah are omitted from the tables due to data quality concerns. Maryland was excluded in 2017 due to unusable diagnosis codes in the IP file and the OT file. Tennessee was excluded due to unusable diagnosis codes in the IP file in 2017 - 2019. Utah was excluded due to unusable procedure codes on OT professional claims in 2017 - 2020. In addition, states with a high data quality concern on one or more measures are noted in the table in the "Data Quality" column. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

Comparison of baseline demographic characteristics of all study populations.

Importance: Bundled payments are an increasingly common alternative payment model for Medicare, yet there is limited evidence regarding their effectiveness. Objective: To report interim outcomes from the first year of implementation of a bundled payment model for lower extremity joint replacement (LEJR). Design, Setting, and Participants: As part of a 5-year, mandatory-participation randomized trial by the Centers for Medicare & Medicaid Services, eligible metropolitan statistical areas (MSAs) were randomized to the Comprehensive Care for Joint Replacement (CJR) bundled payment model for LEJR episodes or to a control group. In the first performance year, hospitals received bonus payments if Medicare spending for LEJR episodes was below the target price and hospitals met quality standards. This interim analysis reports first-year data on LEJR episodes starting April 1, 2016, with data collection through December 31, 2016. Exposure: Randomization of MSAs into the CJR bundled payment model group (75 assigned; 67 included) or to the control group without the CJR model (121 assigned; 121 included). Instrumental variable analysis was used to evaluate the relationship between inclusion of MSAs in the CJR model and outcomes. Main Outcomes and Measures: The primary outcome was share of LEJR admissions discharged to institutional postacute care. Secondary outcomes included the number of days in institutional postacute care, discharges to other locations, Medicare spending during the episode (overall and for institutional postacute care), net Medicare spending during the episode, LEJR patient volume and patient case mix, and quality-of-care measures. Results: Among the 196 MSAs and 1633 hospitals, 131 285 eligible LEJR procedures were performed during the study period (mean volume, 110 LEJR episodes per hospital) among 130 343 patients (mean age, 72.5 [SD, 0.91] years; 65% women; 90% white). The mean percentage of LEJR admissions discharged to institutional postacute care was 33.7% (SD, 11.2%) in the control group and was 2.9 percentage points lower (95% CI, −4.95 to −0.90 percentage points) in the CJR group. Mean Medicare spending for institutional postacute care per LEJR episode was $3871 (SD, $1394) in the control group and was $307 lower (95% CI, −$587 to −$27) in the CJR group. Mean overall Medicare spending per LEJR episode was $22 872 (SD, $3619) in the control group and was $453 lower (95% CI, −$909 to $3) in the CJR group, a statistically nonsignificant difference. None of the other secondary outcomes differed significantly between groups. Conclusions and Relevance: In this interim analysis of the first year of the CJR bundled payment model for LEJR among Medicare beneficiaries, MSAs covered by CJR, compared with those that were not, had a significantly lower percentage of discharges to institutional postacute care but no significant difference in total Medicare spending per LEJR episode. Further evaluation is needed as the program is more fully implemented. Trial Registration: ClinicalTrials.gov Identifier: NCT03407885; American Economic Association Registry Identifier: AEARCTR-0002521

This dataset presents the footprint of the percentage of patients with costs, the total out-of-pocket cost per patient at the 25th, 50th, 75th and 90th percentile and various statistics for all …Show full descriptionThis dataset presents the footprint of the percentage of patients with costs, the total out-of-pocket cost per patient at the 25th, 50th, 75th and 90th percentile and various statistics for all patients. The data spans the financial year of 2016-2017 and is aggregated to Statistical Area Level 3 (SA3) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS). The data is sourced from the Medicare Benefits Schedule (MBS) claims data, which are administered by the Australian Government Department of Health. The claims data are derived from administrative information on services that qualify for a Medicare benefit under the Health Insurance Act 1973 and for which a claim has been processed by the Department of Human Services. Data are reported for claims processed between 1 July 2016 and 30 June 2017. The data also contains the results from the ABS 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. The Patient Experience Survey is conducted annually by the Australian Bureau of Statistics (ABS) and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patients' spending on Medicare Services data accompanies the Patients' out-of-pocket spending on Medicare services 2016-17 Report. For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Patients' out-of-pocket spending on Medicare services Data Tables. Please note: AURIN has spatially enabled the original data. Non-hospital Medicare services are Medicare-subsidised medical services that were provided to patients who were not admitted into a hospital at the time of receiving the service. These include GP and practice nurse attendances, specialist attendances, obstetric attendances, pathology tests and collection items, diagnostic imaging, operations, assistance at operations, optometry, allied health attendances, radiotherapy and therapeutic nuclear medicine that were provided to patients not admitted into a hospital. This includes eligible telehealth services. Total out-of-pocket cost per patient is the net cost to the patient for all non-hospital Medicare-subsidised health services they claim in a year, after deducting the Medicare benefit paid. The data is based on the patient's Medicare enrolment postcode, not where they received the health care service. Most peoples' Medicare enrolment postcode will be their residential postcode. If a service was flagged as bulk-billed, then the fee charged was set to equal the benefit paid (so there was no out-of-pocket cost for that service). Patients were excluded if the sum of eligible services in the year was less than one, or if their annual out-of-pocket expenditure on the eligible services was equal to or less than zero. Costs associated with bulk-billing incentives or other top-up items are included in the analysis. Total out-of-pocket cost per patient is for patients with out-of-pocket costs greater than zero. All patients include all patients with out-of-pocket costs equal to, or greater than, zero. NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null. Copyright attribution: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare, (2018): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)

Metrics from individual Marketplaces during the current reporting period. The report includes data for the states using HealthCare.gov. Sources: HealthCare.gov application and policy data through October 6, 2024, HealthCare.gov inbound account transfer data through November 7, 2024, and T-MSIS Analytic Files (TAF) through July 2024 (TAF version 7.1). The table includes states that use HealthCare.gov. Notes: This table includes Marketplace consumers who submitted a HealthCare.gov application from March 6, 2023 - October 6, 2024 or who had an inbound account transfer from April 3, 2023 - November 7, 2024, who can be linked to an enrollment record in TAF that shows a last day of Medicaid or CHIP enrollment from March 31, 2023 - July 31, 2024. Beneficiaries with a leaving event may have continuous coverage through another coverage source, including Medicaid or CHIP coverage in another state. However, a beneficiary that lost Medicaid or CHIP coverage and regained coverage in the same state must have a gap of at least 31 days or a full calendar month. This table includes Medicaid or CHIP beneficiaries with full benefits in the month they left Medicaid or CHIP coverage. ‘Account Transfer Consumers Whose Medicaid or CHIP Coverage was Terminated’ are consumers 1) whose full benefit Medicaid or CHIP coverage was terminated and 2) were sent by a state Medicaid or CHIP agency via secure electronic file to the HealthCare.gov Marketplace in a process referred to as an inbound account transfer either 2 months before or 4 months after they left Medicaid or CHIP. 'Marketplace Consumers Not on Account Transfer Whose Medicaid or CHIP Coverage was Terminated' are consumers 1) who applied at the HealthCare.gov Marketplace and 2) were not sent by a state Medicaid or CHIP agency via an inbound account transfer either 2 months before or 4 months after they left Medicaid or CHIP. Marketplace consumers counts are based on the month Medicaid or CHIP coverage was terminated for a beneficiary. Counts include all recent Marketplace activity. HealthCare.gov data are organized by week. Reporting months start on the first Monday of the month and end on the first Sunday of the next month when the last day of the reporting month is not a Sunday. HealthCare.gov data are through Sunday, October 6. Data are preliminary and will be restated over time to reflect consumers most recent HealthCare.gov status. Data may change as states resubmit T-MSIS data or data quality issues are identified. See the data and methodology documentation for a full description of the data sources, measure definitions, and general data limitations. Data notes: The percentages for the 'Marketplace Consumers Not on Account Transfer whose Medicaid or CHIP Coverage was Terminated' data record group are marked as not available (NA) because the full population of consumers without an account transfer was not available for this report. Virginia operated a Federally Facilitated Exchange (FFE) on the HealthCare.gov platform during 2023. In 2024, the state started operating a State Based Marketplace (SBM) platform. This table only includes data about 2023 applications and policies obtained through the HealthCare.gov Marketplace. Due to limited Marketplace activity on the HealthCare.gov platform in November 2023, data from November 2023 onward are excluded. The cumulative count and percentage for Virginia and the HealthCare.gov total reflect Virginia data from April 2023 through October 2023. APTC: Advance Premium Tax Credit; CHIP: Children's Health Insurance Program; QHP: Qualified Health Plan; NA: Not Available

Number of excess deaths by location, diagnosis, and method of calculation.

Comparison of matching characteristics for Covid-19 subjects versus non-Covid-19 controls in the community and LTC/SNF subgroups.

This dataset presents the footprint of the percentage of patients with specialist and obstetric costs, and out-of-pocket cost per specialist and obstetric attendance at the 25th, 50th, 75th and 90th …Show full descriptionThis dataset presents the footprint of the percentage of patients with specialist and obstetric costs, and out-of-pocket cost per specialist and obstetric attendance at the 25th, 50th, 75th and 90th percentile. The data spans the financial year of 2016-2017 and is aggregated to Statistical Area Level 3 (SA3) from the 2016 Australian Statistical Geography Standard (ASGS). The data is sourced from the Medicare Benefits Schedule (MBS) claims data, which are administered by the Australian Government Department of Health. The claims data are derived from administrative information on services that qualify for a Medicare benefit under the Health Insurance Act 1973 and for which a claim has been processed by the Department of Human Services. Data are reported for claims processed between 1 July 2016 and 30 June 2017. The data also contains the results from the ABS 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. The Patient Experience Survey is conducted annually by the Australian Bureau of Statistics (ABS) and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patients' spending on Medicare Services data accompanies the Patients' out-of-pocket spending on Medicare services 2016-17 Report. For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Patients' out-of-pocket spending on Medicare services Data Tables. Please note: AURIN has spatially enabled the original data. Specialist attendances are Medicare-subsidised referred patient/doctor encounters, such as visits, consultations, and attendances by video conference, involving medical practitioners who have been recognised as specialists or consultant physicians for Medicare benefits purposes. Obstetric attendances are Medicare-subsidised antenatal visits and attendances for the planning and management of pregnancy, as well as obstetric procedures involving non-admitted patients. These services can be provided by an obstetrician or GP. Selected services can also be provided by a midwife, nurse or Aboriginal and Torres Strait Islander health practitioner when the service is provided on behalf of, and under the supervision of, a medical practitioner. Out-of-pocket cost per service is the net cost to the patient of a health service, after deducting the Medicare benefit paid. The measure is calculated per patient (patients' annual out-of-pocket cost for eligible attendances, divided by the number of eligible attendances that the patient claimed in the year), for patients with out-of-pocket costs. The data is based on the patient's Medicare enrolment postcode, not where they received the health care service. Most peoples' Medicare enrolment postcode will be their residential postcode. If a service was flagged as bulk-billed, then the fee charged was set to equal the benefit paid (so there was no out-of-pocket cost for that service). Patients were excluded if the sum of eligible services in the year was less than one, or if their annual out-of-pocket expenditure on the eligible services was equal to or less than zero. Includes non-hospital Medicare-subsidised services only. NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null. Copyright attribution: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare, (2018): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)

Comparison of baseline demographic characteristics for no Covid-19, confirmed Covid-19 and probable Covid-19 populations in the community and LTC/SNF subgroups.