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Developing a standardized healthcare cost data warehouse
by
Reinalda, Megan S.
, Yawn, Barbara P.
, Borah, Bijan J.
, Anderson, Stephanie S.
, Visscher, Sue L.
, Naessens, James M.
in
Analysis
/ Anesthesia
/ Cancer
/ Cost data warehouse
/ Data warehouses
/ Data Warehousing
/ Databases, Factual
/ Decision support systems
/ Delivery of Health Care - economics
/ Economic aspects
/ economics and financing systems
/ Electronic Health Records
/ Epidemiology
/ expenditure
/ Fees & charges
/ Health Administration
/ Health care costs
/ Health Care Costs - standards
/ Health care expenditures
/ Health Informatics
/ Health services
/ Hospital costs
/ Hospitals
/ Humans
/ Infrastructure
/ Joint surgery
/ Medicaid
/ Medical equipment
/ Medical laboratories
/ Medical personnel
/ Medicare
/ Medicare - economics
/ Medicine
/ Medicine & Public Health
/ Microcosting
/ Nursing Research
/ Olmsted County Healthcare Expenditure and Utilization Database (OCHEUD)
/ Patients
/ Population
/ Prospective payment systems
/ Prostheses
/ Public Health
/ Reference Standards
/ Registries
/ Reimbursement
/ Rochester Epidemiology Project (REP)
/ Schedules
/ Standardized healthcare costs
/ Technical Advance
/ United States
/ Utilization
/ Warehouses
2017
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Developing a standardized healthcare cost data warehouse
by
Reinalda, Megan S.
, Yawn, Barbara P.
, Borah, Bijan J.
, Anderson, Stephanie S.
, Visscher, Sue L.
, Naessens, James M.
in
Analysis
/ Anesthesia
/ Cancer
/ Cost data warehouse
/ Data warehouses
/ Data Warehousing
/ Databases, Factual
/ Decision support systems
/ Delivery of Health Care - economics
/ Economic aspects
/ economics and financing systems
/ Electronic Health Records
/ Epidemiology
/ expenditure
/ Fees & charges
/ Health Administration
/ Health care costs
/ Health Care Costs - standards
/ Health care expenditures
/ Health Informatics
/ Health services
/ Hospital costs
/ Hospitals
/ Humans
/ Infrastructure
/ Joint surgery
/ Medicaid
/ Medical equipment
/ Medical laboratories
/ Medical personnel
/ Medicare
/ Medicare - economics
/ Medicine
/ Medicine & Public Health
/ Microcosting
/ Nursing Research
/ Olmsted County Healthcare Expenditure and Utilization Database (OCHEUD)
/ Patients
/ Population
/ Prospective payment systems
/ Prostheses
/ Public Health
/ Reference Standards
/ Registries
/ Reimbursement
/ Rochester Epidemiology Project (REP)
/ Schedules
/ Standardized healthcare costs
/ Technical Advance
/ United States
/ Utilization
/ Warehouses
2017
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Developing a standardized healthcare cost data warehouse
by
Reinalda, Megan S.
, Yawn, Barbara P.
, Borah, Bijan J.
, Anderson, Stephanie S.
, Visscher, Sue L.
, Naessens, James M.
in
Analysis
/ Anesthesia
/ Cancer
/ Cost data warehouse
/ Data warehouses
/ Data Warehousing
/ Databases, Factual
/ Decision support systems
/ Delivery of Health Care - economics
/ Economic aspects
/ economics and financing systems
/ Electronic Health Records
/ Epidemiology
/ expenditure
/ Fees & charges
/ Health Administration
/ Health care costs
/ Health Care Costs - standards
/ Health care expenditures
/ Health Informatics
/ Health services
/ Hospital costs
/ Hospitals
/ Humans
/ Infrastructure
/ Joint surgery
/ Medicaid
/ Medical equipment
/ Medical laboratories
/ Medical personnel
/ Medicare
/ Medicare - economics
/ Medicine
/ Medicine & Public Health
/ Microcosting
/ Nursing Research
/ Olmsted County Healthcare Expenditure and Utilization Database (OCHEUD)
/ Patients
/ Population
/ Prospective payment systems
/ Prostheses
/ Public Health
/ Reference Standards
/ Registries
/ Reimbursement
/ Rochester Epidemiology Project (REP)
/ Schedules
/ Standardized healthcare costs
/ Technical Advance
/ United States
/ Utilization
/ Warehouses
2017
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Journal Article
Developing a standardized healthcare cost data warehouse
2017
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Overview
Background
Research addressing value in healthcare requires a measure of cost. While there are many sources and types of cost data, each has strengths and weaknesses. Many researchers appear to create study-specific cost datasets, but the explanations of their costing methodologies are not always clear, causing their results to be difficult to interpret. Our solution, described in this paper, was to use widely accepted costing methodologies to create a service-level, standardized healthcare cost data warehouse from an institutional perspective that includes all professional and hospital-billed services for our patients.
Methods
The warehouse is based on a National Institutes of Research–funded research infrastructure containing the linked health records and medical care administrative data of two healthcare providers and their affiliated hospitals. Since all patients are identified in the data warehouse, their costs can be linked to other systems and databases, such as electronic health records, tumor registries, and disease or treatment registries.
Results
We describe the two institutions’ administrative source data; the reference files, which include Medicare fee schedules and cost reports; the process of creating standardized costs; and the warehouse structure. The costing algorithm can create inflation-adjusted standardized costs at the service line level for defined study cohorts on request.
Conclusion
The resulting standardized costs contained in the data warehouse can be used to create detailed, bottom-up analyses of professional and facility costs of procedures, medical conditions, and patient care cycles without revealing business-sensitive information.
After its creation, a standardized cost data warehouse is relatively easy to maintain and can be expanded to include data from other providers. Individual investigators who may not have sufficient knowledge about administrative data do not have to try to create their own standardized costs on a project-by-project basis because our data warehouse generates standardized costs for defined cohorts upon request.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Cancer
/ Delivery of Health Care - economics
/ economics and financing systems
/ Health Care Costs - standards
/ Humans
/ Medicaid
/ Medicare
/ Medicine
/ Olmsted County Healthcare Expenditure and Utilization Database (OCHEUD)
/ Patients
/ Rochester Epidemiology Project (REP)
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