ArticleBMC health services research2007
Validation of a method for identifying nursing home admissions using administrative claims.
Article in BMC health services research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Outcomes of Older Patients with Pulmonary Fibrosis and Non-Small Cell Lung Cancer.Annals of the American Thoracic Society · 2019Article
- Are Trends in Hospitalization Prior to Hospice Use Associated With Hospice Episode Characteristics?The American journal of hospice & palliative care · 2017Observational
- Exploring the concurrent validity of the nationwide assessment of permanent nursing home residence in Denmark - A cross-sectional data analysis using two administrative registries.BMC health services research · 2017Article
- Comparison of methods to identify long term care nursing home residence with administrative data.BMC health services research · 2017Article
- Pharmacotherapeutic management of dementia across settings of care.Journal of the American Geriatrics Society · 2013Article
- Resource use trajectories for aged medicare beneficiaries with complex coronary conditions.Health services research · 2013Article
- The effect of dementia on medication use and adherence among Medicare beneficiaries with chronic heart failure.The American journal of geriatric pharmacotherapy · 2012Article
- Algorithms can be used to identify fragility fracture cases in physician-claims databases.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2012Article
- Home care patients in four Nordic capitals - predictors of nursing home admission during one-year followup.Journal of multidisciplinary healthcare · 2010Article
- Ability of Medicare claims data to identify nursing home patients: a validation study.Medical care · 2008Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundCurrently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.
methodsThe computer algorithms for identifying nursing home admissions were created by using provider type, place of service, and procedure codes from the 2000 - 2002 MarketScan Medicare COB database. After the algorithms were reviewed and refined, they were compared with a detailed claims review by an expert reviewer. A random sample of 150 subjects from the claims was selected and used for the validity analysis of the algorithms. Contingency table analysis, comparison of mean differences, correlations, and t-test analyses were performed. Percentage agreement, sensitivity, specificity, and Kappa statistics were analyzed.
resultsThe computer algorithm showed strong agreement with the expert review (99.9%) for identification of the first month of nursing home residence, with high sensitivity (96.7%), specificity (100%) and a Kappa statistic of 0.97. Weighted Pearson correlation coefficient between the algorithm and the expert review was 0.97 (p < 0.0001).
conclusionA reliable algorithm indicating evidence of nursing home admission was developed and validated from administrative claims data. Our algorithm can be a useful tool to identify patient transitions from and to nursing homes, as well as to screen and monitor for factors associated with nursing home admission and nursing home discharge.
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