WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

Analysis of ‘WA-APCD Quality and Cost Summary Report: Hospital Quality’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/13e6499e-0f20-42f7-b51c-0dc0174855a9 on 12 November 2021.

--- Dataset description provided by original source is as follows ---

WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

--- Original source retains full ownership of the source dataset ---

This dataset contains data for the Healthcare Payments Data (HPD): Medical Out-of-Pocket Costs and Chronic Conditions report. The data covers three measurement categories: annual member count, annual median out-of-pocket count, annual median claim count. The annual member count quantify the number of unique individuals who received at least one medical service in the reporting year. Annual median out-of-pocket measurements quantifies the sum of copay, coinsurance, and deductible incurred by members. Annual median claim count measurements quantifies the number of distinct claims or encounters associated with members. Both 25th and 75th percentiles for out-of-pocket cost and claim count are also included. Measures are grouped by payer types, chronic conditions flag, chronic condition types, and chronic condition numbers.

IntroductionThis study aimed to estimate the direct medical costs and out-of-pocket (OOP) expenses associated with inpatient and outpatient care for IHD, based on types of health insurance. Additionally, we sought to identify time trends and factors associated with these costs using an all-payer health claims database among urban patients with IHD in Guangzhou City, Southern China.MethodsData were collected from the Urban Employee-based Basic Medical Insurance (UEBMI) and the Urban Resident-based Basic Medical Insurance (URBMI) administrative claims databases in Guangzhou City from 2008 to 2012. Direct medical costs were estimated in the entire sample and by types of insurance separately. Extended Estimating Equations models were employed to identify the potential factors associated with the direct medical costs including inpatient and outpatient care and OOP expenses.ResultsThe total sample included 58,357 patients with IHD. The average direct medical costs per patient were Chinese Yuan (CNY) 27,136.4 [US dollar (USD) 4,298.8] in 2012. The treatment and surgery fees were the largest contributor to direct medical costs (52.0%). The average direct medical costs of IHD patients insured by UEBMI were significantly higher than those insured by the URBMI [CNY 27,749.0 (USD 4,395.9) vs. CNY 21,057.7(USD 3,335.9), P < 0.05]. The direct medical costs and OOP expenses for all patients increased from 2008 to 2009, and then decreased during the period of 2009–2012. The time trends of direct medical costs between the UEBMI and URBMI patients were different during the period of 2008-2012. The regression analysis indicated that the UEBMI enrollees had higher direct medical costs (P < 0.001) but had lower OOP expenses (P < 0.001) than the URBMI enrollees. Male patients, patients having percutaneous coronary intervention operation and intensive care unit admission, patients treated in secondary hospitals and tertiary hospitals, patients with the LOS of 15–30 days, 30 days and longer had significantly higher direct medical costs and OOP expenses (all P < 0.001).ConclusionsThe direct medical costs and OOP expenses for patients with IHD in China were found to be high and varied between two medical insurance schemes. The type of insurance was significantly associated with direct medical costs and OOP expenses of IHD.

This data includes the top 25 list for costliest prescribed drugs, most frequently prescribed drugs and the prescribed drugs with the highest monthly median out-of-pocket cost for members. Each of these top 25 lists are broken out by payer type (i.e., All Payers, All Payers W/O Medi-Cal, Commercial, Medicare or Medi-Cal) and drug category (i.e., All, Brand, Generic, Biosimilar or Biologic). The includes National Drug Code (NDC), Year, Top 25 Ranking, National Drug Code, Drug Name, number of prescriptions, number of individuals, total costs, average cost per unit, average dispensed units per fill, drug unit of measure, monthly median out-of-pocket cost, 25th percentile for monthly out-of-pocket cost, 75th percentile for monthly out-of-pocket cost, and percent of monthly out-of-pocket cost with zero dollar amounts for each NDC in each top 25 list.

This dataset contains information submitted by New York State Article** 282 Hospitals** as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions.

The file contains information on the** volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge.**

This dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided. For more information, check out: http://www.health.ny.gov/statistics/sparcs/ or go to the "About" tab.

The Nationwide Emergency Department Sample (NEDS) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). The NEDS is the largest all-payer emergency department (ED) database in the United States, yielding national estimates of hospital-based ED visits. The NEDS enables analyses of ED utilization patterns and supports public health professionals, administrators, policymakers, and clinicians in their decisionmaking regarding this critical source of care.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all payers and the uninsured. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in health care data - the lack of nationally representative information on hospital readmissions for all ages. Outcomes of interest include national readmission rates, reasons for returning to the hospital for care, and the hospital costs for discharges with and without readmissions. Unweighted, the NRD contains data from approximately 18 million discharges each year. Weighted, it estimates roughly 35 million discharges. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The NRD is drawn from HCUP State Inpatient Databases (SID) containing verified patient linkage numbers that can be used to track a person across hospitals within a State, while adhering to strict privacy guidelines. The NRD is not designed to support regional, State-, or hospital-specific readmission analyses.

The NRD contains more than 100 clinical and non-clinical data elements provided in a hospital discharge abstract. Data elements include but are not limited to: diagnoses, procedures, patient demographics (e.g., sex, age), expected source of payer, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge, discharge month, quarter, and year, total charges, length of stay, and data elements essential to readmission analyses. The NIS excludes data elements that could directly or indirectly identify individuals.

Restricted access data files are available with a data use agreement and brief online security training.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) is the largest all-payer emergency department (ED) database in the United States. yielding national estimates of hospital-owned ED visits. Unweighted, it contains data from over 30 million ED visits each year. Weighted, it estimates roughly 145 million ED visits nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

Sampled from the HCUP State Inpatient Databases (SID) and State Emergency Department Databases (SEDD), the HCUP NEDS can be used to create national and regional estimates of ED care. The SID contain information on patients initially seen in the ED and subsequently admitted to the same hospital. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The NEDS contain information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 85% of patients, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.Restricted access data files are available with a data use agreement and brief online security training.

This dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided. For more information, check out: http://www.health.ny.gov/statistics/sparcs/ or go to the "About" tab.

The Healthcare Cost and Utilization Project (HCUP) Kids' Inpatient Database (KID) is the largest publicly available all-payer pediatric inpatient care database in the United States, containing data from two to three million hospital stays each year. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, such as congenital anomalies, as well as uncommon treatments, such as organ transplantation. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The KID is a sample of pediatric discharges from 4,000 U.S. hospitals in the HCUP State Inpatient Databases yielding approximately two to three million unweighted hospital discharges for newborns, children, and adolescents per year. About 10 percent of normal newborns and 80 percent of other neonatal and pediatric stays are selected from each hospital that is sampled for patients younger than 21 years of age.

The KID contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes discharge status, diagnoses, procedures, patient demographics (e.g., sex, age), expected source of primary payment (e.g., Medicare, Medicaid, private insurance, self-pay, and other insurance types), and hospital charges and cost.

Restricted access data files are available with a data use agreement and brief online security training.

This line chart compares the median cost vs. median charge for other pneumonia with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

This dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided. For more information, check out: http://www.health.ny.gov/statistics/sparcs/ or go to the "About" tab.

The Nationwide Inpatient Sample (NIS) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). The NIS is the largest all-payer inpatient health care database in the United States, yielding national estimates of hospital inpatient stays. The NIS can be used to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. Data may not be available for all states across all years.

The largest all-payer ambulatory surgery database in the United States, the Healthcare Cost and Utilization Project (HCUP) Nationwide Ambulatory Surgery Sample (NASS) produces national estimates of major ambulatory surgery encounters in hospital-owned facilities. Major ambulatory surgeries are defined as selected major therapeutic procedures that require the use of an operating room, penetrate or break the skin, and involve regional anesthesia, general anesthesia, or sedation to control pain (i.e., surgeries flagged as "narrow" in the HCUP Surgery Flag Software). Unweighted, the NASS contains approximately 9.0 million ambulatory surgery encounters each year and approximately 11.8 million ambulatory surgery procedures. Weighted, it estimates approximately 11.9 million ambulatory surgery encounters and 15.7 million ambulatory surgery procedures.

Sampled from the HCUP State Ambulatory Surgery and Services Databases (SASD) and State Emergency Department Databases (SEDD) in order to capture both planned and emergent major ambulatory surgeries, the NASS can be used to examine selected ambulatory surgery utilization patterns. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The NASS contains clinical and resource-use information that is included in a typical hospital-owned facility record, including patient characteristics, clinical diagnostic and surgical procedure codes, disposition of patients, total charges, facility characteristics, and expected source of payment, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NASS excludes data elements that could directly or indirectly identify individuals, hospitals, or states. The NASS is limited to encounters with at least one in-scope major ambulatory surgery on the record, performed at hospital-owned facilities. Procedures intended primarily for diagnostic purposes are not considered in-scope.

Restricted access data files are available with a data use agreement and brief online security training.

This dataset provides a comprehensive view of healthcare provider contracts with payers, detailing contracted rates, payment terms, credentialing status, effective and expiration dates, participation status, and network tier assignments. It enables analysis of provider-payer relationships, reimbursement trends, and network management for claims processing and compliance.

HCUPnet is an on-line query system that provides free, instant access to the largest set of all-payer health care databases that are publicly available. Using HCUPnet's easy step-by-step query system, you can generate tables and graphs on statistics and trends for acute care hospitals in the U.S.

HCUPnet provides:
 National and regional estimates for inpatient stays and emergency department visits;
 State counts of inpatient stays and emergency department visits for those states that agreed to participate;
 National estimates on readmissions and readmission rates;
 County-level statistics on hospital use and potentially preventable admissions, based on the AHRQ Quality Indicators (QIs)*

For most queries, detailed information is available for conditions and procedures (by ICD-9-CM codes and Clinical Classification Software), and for diagnosis related groups (DRGs).

HCUPnet allows easy access to information from datasets that are part of the Healthcare Cost and Utilization Project (HCUP); details on obtaining these datasets are also available in www.healthdata.gov

The dataset contains hospital stroke designation and Coverdell registry participation status, acute stroke discharges counts (numerators, denominators), observed, expected and risk-adjusted acute stroke in-hospital/30-day post admission mortality rates with corresponding 95% confidence intervals. Mortality rates risk adjustment was based on the methodology developed by the New York State Department of Health.

The purpose of this data set is reporting of hospital-specific risk adjusted acute stroke mortality rates (RAMR) to inform hospitals, to aid initiatives to improve hospital quality performance and measurement, and to identify performance outliers for public reporting. The "About" tab contains additional details concerning this dataset.