Omaha System Partnership Research Overview

Madeleine Kerr, PhD, RN

Background

Purpose

• Describe completed and in-progress studies of the partnership research teams (41 to date)

• Studies are listed and available through links at omahasystempartnership.org

Investigators and co-investigators

• Multidisciplinary teams (n=27)• International teams (n=8)• Students (n=25)• Community partners (n=22)

Subjects

• High risk families served by public health nurses (n=22)

• Elders receiving home care services (n=12)• Mothers with intellectual disabilities• Children with special health care needs• Diabetics• Firefighters

Settings

• Public health• Home health• Community advocacy organizations• Community coalitions• Nurse-managed wellness centers• Workforce studies

Electronic health record data

Study Methods

• Descriptive (n=37)• Inferential (n=26)• Text mining (n=3)• Machine learning (n=2)• Data visualization (n=1)

Machine learning example

Data Management for Intervention Effectiveness Research:

Comparing Deductive and Inductive Approaches

• Purpose: To use data mining techniques to create meaningful intervention clusters from structured Omaha System intervention data

Monsen, K.A., et al. (2009). Research in Nursing and Health, 32 (6),647-656

• Method: Intervention data from 2,862 clients from 15 home care agencies managed using 3 deductive approaches and 1 inductive (data mining) method.

• Results: The data mining approach generated more intervention groups (24) compared to action category, theoretical and clinical expert consensus approaches.

Intervention SchemeIntervention Scheme

Text mining example

Informing Standard Development and Understanding User Needs with Omaha System Signs and Symptoms Text Entries in Community-

Based Care Settings• Purpose: To study free text with Omaha System data, to improve use in computerized platforms, identify gaps, and propose improvements. Melton, G. B., et al. (2010). Proceedings of the 2010 American Medical Informatics Association Symposium, 512-516.

• Method: Free text data for ‘other’ signs and symptoms from 2 years of client records analyzed by content experts into categories.

• Results: Five categories: 1) duplicate entries, 2) multiple concepts, 3) medical diagnoses, 4)interventions and 5) comments.

Signs and SymptomsSigns and

Symptoms

Descriptive inferential example

Benchmark Attainment by Maternal and Child Health Clients Across

Public Health Nursing Agencies

• Purpose: To demonstrate benchmarking of public health nursing outcomes

Monsen, K.A., et al. (2011). Public Health Nursing, 29(1), 11-18.

• Method: MCH data from from 6 counties using a benchmark of 4 (1=lowest, 5=highest)

• Results: All counties showed significant increases in client knowledge benchmark attainment; 4 of 6 counties showed increases for behavior & status.

KnowledgeKnowledge BehaviorBehavior StatusStatus

Studies in progress

Using Visualization Methodsto Discover Tailoring in PHN Intervention Data

Evaluating Effects of PHN Home Visiting on Health Literacy (NI2012 AMIA-0421)

Occupational Health Nursing Informatics: Mapping Hearing Health Outcomes to the Omaha System (NI2012 AMIA-0413)

Questions?

Omaha System Partnership omahasystempartnership.org

Madeleine Kerr kerrx010@umn.edu