ArticleHealth care analysis : HCA : journal of health philosophy and policy2005
The effects of fraud on the evaluation of health care.
Article in Health care analysis : HCA : journal of health philosophy and policy, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Prospective payment systems and discretionary coding-Evidence from English mental health providers.Health economics · 2019Article
- Potential loss of revenue due to errors in clinical coding during the implementation of the Malaysia diagnosis related group (MY-DRGBMC health services research · 2018Article
- The Power and Pitfalls of Big Data Research in Obstetrics and Gynecology: A Consumer's Guide.Obstetrical & gynecological survey · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies on health care practices, financing, and organization increasingly rely on Medicare and other expanded data sets. These studies are of critical importance for public policy and for the development of strategies to contain escalating health care costs, but they often use data that have been corrupted by fraud and abuse. Mistaken conclusions, as to the effectiveness of policy and procedures, are likely being reached in studies that have used corrupted data. Researchers need to consider the suspect nature of results obtained from the corrupted data, and determine methods for making the data more valid.
Indexed as
Identifiers
16223213What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.