OBJECTIVE: To develop an inventory of data sources for estimating health care costs in the United States and provide information to aid researchers in identifying appropriate data sources for their specific research questions. METHODS: We identified data sources for estimating health care costs using 3 approaches: (1) a review of the 18 articles included in this supplement, (2) an evaluation of websites of federal government agencies, non profit foundations, and related societies that support health care research or provide health care services, and (3) a systematic review of the recently published literature. Descriptive information was abstracted from each data source, including sponsor, website, lowest level of data aggregation, type of data source, population included, cross-sectional or longitudinal data capture, source of diagnosis information, and cost of obtaining the data source. Details about the cost elements available in each data source were also abstracted. RESULTS: We identified 88 data sources that can be used to estimate health care costs in the United States. Most data sources were sponsored by government agencies, national or nationally representative, and cross-sectional. About 40% were surveys, followed by administrative or linked administrative data, fee or cost schedules, discharges, and other types of data. Diagnosis information was available in most data sources through procedure or diagnosis codes, self-report, registry, or chart review. Cost elements included inpatient hospitalizations (42.0%), physician and other outpatient services (45.5%), outpatient pharmacy or laboratory (28.4%), out-of-pocket (22.7%), patient time and other direct nonmedical costs (35.2%), and wages (13.6%). About half were freely available for downloading or available for a nominal fee, and the cost of obtaining the remaining data sources varied by the scope of the project. CONCLUSIONS: Available data sources vary in population included, type of data source, scope, and accessibility, and have different strengths and weaknesses for specific research questions.
OBJECTIVE: To develop an inventory of data sources for estimating health care costs in the United States and provide information to aid researchers in identifying appropriate data sources for their specific research questions. METHODS: We identified data sources for estimating health care costs using 3 approaches: (1) a review of the 18 articles included in this supplement, (2) an evaluation of websites of federal government agencies, non profit foundations, and related societies that support health care research or provide health care services, and (3) a systematic review of the recently published literature. Descriptive information was abstracted from each data source, including sponsor, website, lowest level of data aggregation, type of data source, population included, cross-sectional or longitudinal data capture, source of diagnosis information, and cost of obtaining the data source. Details about the cost elements available in each data source were also abstracted. RESULTS: We identified 88 data sources that can be used to estimate health care costs in the United States. Most data sources were sponsored by government agencies, national or nationally representative, and cross-sectional. About 40% were surveys, followed by administrative or linked administrative data, fee or cost schedules, discharges, and other types of data. Diagnosis information was available in most data sources through procedure or diagnosis codes, self-report, registry, or chart review. Cost elements included inpatient hospitalizations (42.0%), physician and other outpatient services (45.5%), outpatient pharmacy or laboratory (28.4%), out-of-pocket (22.7%), patient time and other direct nonmedical costs (35.2%), and wages (13.6%). About half were freely available for downloading or available for a nominal fee, and the cost of obtaining the remaining data sources varied by the scope of the project. CONCLUSIONS: Available data sources vary in population included, type of data source, scope, and accessibility, and have different strengths and weaknesses for specific research questions.
Authors: Sun Hee Rim; Gery P Guy; K Robin Yabroff; Kathleen A McGraw; Donatus U Ekwueme Journal: Expert Rev Pharmacoecon Outcomes Res Date: 2016-10-06 Impact factor: 2.217
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Authors: Jonathan C Routh; Frederick D Grant; Paul Kokorowski; Richard S Lee; Frederic H Fahey; S Ted Treves; Caleb P Nelson Journal: Pediatrics Date: 2010-10-18 Impact factor: 7.124
Authors: Jaya S Khushalani; Jin Qin; John Cyrus; Natasha Buchanan Lunsford; Sun Hee Rim; Xuesong Han; K Robin Yabroff; Donatus U Ekwueme Journal: Expert Rev Pharmacoecon Outcomes Res Date: 2018-06-20 Impact factor: 2.217