Inpatient Mortality Prediction Algorithm Clinical Trial (IMPACT)

Dascena

Overview

Through the mapping of retrospective patient data into a discrete multidimensional space, a novel algorithm for homeostatic analysis, was built to make outcome predictions. In this prospective study, the ability of the algorithm to predict patient mortality and influence clinical outcomes, will be investigated.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

DIAGNOSTIC

Masking

NONE

Conditions

Decompensation, Heart Decompensation; Heart, Congestive Death

Interventions

Patient mortality predictionOTHER

Healthcare provider is notified of patient mortality prediction.

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * All adult patients admitted to the participating units will be eligible. Exclusion Criteria: * All patients younger than 18 years of age will be excluded.

Locations (1)

UCSF Moffit-Long Hospital

San Francisco, California, United States

Outcomes

Primary Outcomes

In-hospital mortality

Time frame: Through study completion, an average of 30 days

Secondary Outcomes

Hospital length of stay

Time frame: Through study completion, an average of 30 days

Data from ClinicalTrials.gov

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