Microcosting Quantity Data Collection Methods
Bibliographic Data
| ID | 9101928 |
|---|---|
| Authors | Kevin D Frick (0000-0002-0178-5319, Health Services Research & Development, corresponding author) |
| Year | 2009 |
| Volume | 47 |
| Issue | 7_Supplement_1 |
| Pages | S76-S81 |
| Publication date | 2009-07-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0b013e31819bc064 |
| PMID | 19536026 |
| PMCID | PMC2714580 |
| OpenAlex | W2101703186 |
| Language | EN |
| Citations received | 13 |
| References cited | 25 |
BACKGROUND: Microcosting studies collect detailed data on resources used and the value of those resources. Such studies are useful for estimating the cost of new technologies or new community-based interventions, for producing estimates in studies that include nonmarket goods, and for studying within-procedure cost variation. OBJECTIVES: The objectives of this article were to (1) describe basic microcosting methods focusing on quantity data collection; and (2) suggest a research agenda to improve methods in and the interpretation of microcosting. RESEARCH DESIGN: Examples in the published literature were used to illustrate steps in the methods of gathering data (primarily quantity data) for a microcosting study. RESULTS: Quantity data collection methods that were illustrated in the literature include the use of (1) administrative databases at single facilities, (2) insurer administrative data, (3) forms applied across multiple settings, (4) an expert panel, (5) surveys or interviews of one or more types of providers; (6) review of patient charts, (7) direct observation, (8) personal digital assistants, (9) program operation logs, and (10) diary data. CONCLUSIONS: Future microcosting studies are likely to improve if research is done to compare the validity and cost of different data collection methods; if a critical review is conducted of studies done to date; and if the combination of the results of the first 2 steps described are used to develop guidelines that address common limitations, critical judgment points, and decisions that can reduce limitations and improve the quality of studies
Business · Cost database · Data collection · Data quality · Data science · Database · Management science · Psychological intervention · Quality (philosophy) · Raw data · Research design · Chronic Disease Management Strategies · Computer Science · Health Systems, Economic Evaluations, Quality of Life · Healthcare Policy and Management · Marketing · Medicine · Nursing
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| Unique citing works | 13 |
|---|---|
| Citations per year | 0,76 |
| Citation span | 2009 - 2025 (17) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 13 |