+ Site Statistics
References:
54,258,434
Abstracts:
29,560,870
PMIDs:
28,072,757
+ Search Articles
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ PDF Full Text
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Translate
+ Recently Requested

A real-world evidence-based approach to laboratory reorganization using e-Valuate benchmarking data



A real-world evidence-based approach to laboratory reorganization using e-Valuate benchmarking data



Clinical Chemistry and Laboratory Medicine 55(3): 435-440



Pressure to cut health-care costs has involved clinical laboratories underpinning the need to reduce cost per test through programs designed to consolidate activities and increase volumes. Currently, however, there is little evidence of the effectiveness of these measures. The aim of the present study was to verify whether a rational, evidence-based decision-making process might be achieved based on an activity-based cost analysis performed by collecting the data of all variables affecting cost per test. An activity-based costing analysis was performed using a program that provides collected data on performance indicators, benchmark between different laboratories based on performance indicators, and information on reorganization initiatives. The data provided were used in two different settings to (1) verify the results of the internal re-organization of specific protein assay and (2) simulate some scenarios for the reorganization of autoimmune testing in the network of clinical laboratories in a large territory. The data produced by the e-Valuate project enabled the quantification of variation in costs, the utilization of human and technological resources and efficiency, both as final result of a reorganization project (proteins) and as a simulation of a possible future organization (autoimmune tests).

(PDF emailed within 0-6 h: $19.90)

Accession: 057092904

Download citation: RISBibTeXText

PMID: 27658152

DOI: 10.1515/cclm-2016-0393


Related references

Assessing Real-World Data Quality: The Application of Patient Registry Quality Criteria to Real-World Data and Real-World Evidence. Therapeutic Innovation and Regulatory Science 2019: 2168479019837520, 2019

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach. Frontiers in Neuroinformatics 10: 7, 2016

A Pragmatic Approach to Data Source Selection for use In Real-World Evidence (Rwe) Generation. Value in Health 18(7): A488, 2015

Finding treatment-resistant depression in real-world data: How a data-driven approach compares with expert-based heuristics. Depression and Anxiety 35(3): 220-228, 2017

Real-World Evidence and Real-World Data for Evaluating Drug Safety and Effectiveness. JAMA 320(9): 867-868, 2018

From Clinical Trial to Real-World Evidence: A Systematic Approach to Identifying Data Sources for Observational Research. Value in Health 16(7): A583-A584, 2013

Real-world evidence research based on big data: Motivation-challenges-success factors. Der Onkologe 24(Suppl 2): 91-98, 2018

Proceed with Caution When Using Real World Data and Real World Evidence. Journal of Korean Medical Science 34(4): E28-E28, 2019

A real option-based model to valuate CDM projects under uncertain energy policies for emission trading. Applied Energy 131: 288-296, 2014

A real-world approach to Evidence-Based Medicine in general practice: a competency framework derived from a systematic review and Delphi process. Bmc Medical Education 17(1): 78, 2018

Developing a predictive model for vertigo using demographic and laboratory data: An evidence-based medicine approach. Acta Oto-Laryngologica 126(1): 20-24, 2005

The US Food and Drug Administration's Real-World Evidence Framework: A Commitment for Engagement and Transparency on Real-World Evidence. Clinical Pharmacology and Therapeutics 2019, 2019

Finding the Evidence in Real-World Evidence: Moving from Data to Information to Knowledge. Journal of the American College of Surgeons 224(1): 1-7, 2016

A Novel Approach to Lossy Real-Time Image Compression: Hierarchical Data Reorganization on a Low-Cost Massively Parallel System. Real-Time Imaging 1(5): 339-353, 1995

Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records. AMIA ... Annual Symposium Proceedings. AMIA Symposium 2018: 592-601, 2019