4162 Improving Data Capacity and Predictive Capability of NSQIP-P Using Designed Sampling from Databases
Martha-Conley Ingram, Yao Tian, Sanjay Mehrotra and 2 more
Journal of Clinical and Translational Science · 2020
doi:10.1017/cts.2020.407 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
OBJECTIVES/GOALS: Designed sampling from databases (DSD) methods have been used to cross-check electronic medical records for errors, structure study design, and, we hypothesize, can be used to make data collection for surgical quality metrics more efficient, particularly within national databases. We plan to apply statistical and DSD methods to accomplish the following aims: 1.Identify the most important elements in managing post-operative pain2.Identify the most informative procedure or population-based targets to focus collection of additional, labor-intense detail surrounding adequacy of pain control (i.e., Patient Reported Outcome Measures (PROMs)).
Abstract licence: CC BY-NC-SA
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.