Ellen Harper, DNP, RN-BC, MBA, FAAN 
eharper3@kumc.edu

We will describe how researchers, nursing and information technology teams used large and complex data sets to identify, extract, anonymize patient and nurse information and transfer files for analysis while complying with security and confidentiality requirements. There is a growing need to devise methods to better understand how nursing costs and resources are expended for each patient and how these resources relate to quality and outcomes. Time-stamped data can provide useful information and several means to identify both the clinical trajectory as well as the sequence of nursing care and nurses’ engagement during a patient during hospitalization. Nurses are linked to individual patients in several ways e.g., the electronic capture of the nurse-patient assignment and data from barcoding technologies used for medication administration. Automatic capture of nurse-generated clinical observations and nursing interventions data for secondary use can provide new and unique opportunities to measure nursing care in several different dimensions. 

Part of a panel presentation Nursing Knowledge Big Data Science: A National Collaborative to Achieve Sharable and Comparable Nurse-Sensitive Data. 

August 28, 2019, Lyon France

Bonnie L. Westra, PhD, RN, FAAN, FACMI

westr006@umn.edu

Part of a panel presentation Nursing Knowledge Big Data Science: A National Collaborative to Achieve Sharable and Comparable Nurse-Sensitive Data.

August 28, 2019, Lyon France
 

Author(s): Bonnie Westra & Tristan Fin

A fake data set generated from 2 organizations, de-identified, duplicated to achieve 10,000 patients, massaged to calculate data elements i.e. age . This data set can be used for practicing data visualization skills.

Shannon Hulett DNP, RN, CNL
Gundersen Health System and Transforming Nursing Documentation WG co-chair
slhulett@gundersenhealth.org

A podium presentation in the Summer Institute for Nursing Informatics 2019 Documentation Burden Deep Dive Track - purpose to share the story of  Gundersen Health System's nursing  informatics approach to documentation burden reduction.  

• Introduce nursing informatics at Gundersen Health
• Outline phased approach to a pain assessment project
• Describe the execution of an acute admission redesign
• Summarize a care plan upgrade and practice reset
• Review usability assessments and lean principles used
• Discuss potential for related strategies in other organizations 

This is an resource for faculty and educators as they teach about the implications of social determinants of health data on informatics processes. 

Contact for further information: 

Marisa L. Wilson
mwilsoa@uab.edu

Lynn Choromanski, PhD, RN-BC
Clients diagnosed with pediatric asthma may experience an increased incidence of poorly controlled chronic disease management that lead to poor health and academic outcomes and might be influenced by social or behavioral factors. 

OMAHA SYSTEM GUILDELINE METADATA: SDOH Unstable Housing

Name of guideline:

SDOH Acute or Chronic Unstable Housing

Description: The purpose of the SDOH Acute or Chronic Unstable Housing guideline is to provide a shared care plan for individuals experiencing acute or chronic challenges to stable housing. The Big Data Nursing Science (BDNS) Social Determinants of Health workgroup set as a 2018 goal the creation of a user story as a test case for data stored in the Big Data warehouse.  The concept of unstable housing was chosen because of the frequency and high impact of unstable housing on individual health and ability to fully participate in the healthcare system. The workgroup identified the problems included in this guideline.  Nursing experts from various practice venues are included in this workgroup including individuals in public health, school health, vendors, informatics, and pediatrics. This workgroup modified a user story template created by the BDNS Nursing Value workgroup to accommodate the Omaha System Problem, Signs and Symptoms, Category, Target, Knowledge, Behavior and Status schema.  There were four problems identified as impactful to unstable housing: communication with community resources, income, mental health and substance use.  The interventions were selected from the SDOH pathway problems and interventions developed by the Omaha System Community of Practice.

Unique to this guideline is the use of a single sign/symptom as the focus of a care guideline.  Stable housing is recognized as an important factor in the areas of school success and overall health and wellbeing.  Additionally the guideline is coded to the Omaha System, SNOMED and LOINC across the entire schema. 

Omaha System Problems

                Communication with Community Resources

                Income

                Mental Health

                Substance Abuse

                Residence

Population: Individuals in unstable housing circumstances.

Diseases/Conditions: None

Practice Setting: All

Levels of Practice: Individual

Date of most recent guideline revision: May 2018

Lynn Choromanski, MVNA

Karen A. Monsen, University of Minnesota School of Nursing

Encoded by: Lynn Choromanski

Encoded date: May 2018

Contributors: Lynn Choromanski, Karen A. Monsen

Source: Hennepin Healthcare System (HCMC and MVNA) Minneapolis, Minnesota

References:

Monsen KA, Finn RS, Fleming TE, Garner EJ, LaValla AJ, Riemer JG. (2015, August). Rigor in electronic health record knowledge representation: lessons learned from a SNOMED CT clinical content encoding exercise. Informatics for Health and Social Care, 21, 1-15.

Martin KS. (2005). The Omaha System: A key to practice, documentation, and information management (Reprinted 2nd ed.). Omaha, NE: Health Connections Press.

Monsen KA, Neely C, Oftedahl G, Kerr MJ, Pietruszewski P, Farri O. (2012, August). Feasibility of encoding the Institute for Clinical Systems Improvement Depression Guideline using the Omaha System. Journal of Biomedical Informatics, 45(4), 719-725. Available: www.j-biomed-inform.com/article/S1532-0464(12)00094-9/fulltext.

Monsen KA, Foster DJ, Gomez T, Poulsen JK, Mast J, Westra BL, Fishman E. (2011, Fall). Evidence-based standardized care plans for use internationally to improve home care practice and population health. Applied Clinical Informatics, 2(3), 373-383. Available: http://aci.schattauer.de/en/contents/archive/issue/1422/manuscript/16710/show.html

Chan A, Hinz A, Heinstad D, Horgan D, Smith A, Porte E, Shelton E. (2008) Housing stability and school success for children: the effectiveness of the kids collaborative project. Paper discussion 2008 Annual Meeting of American Educational Research Association, New York, NY Available: http://rea.mpls.k12.mn.us/uploads/2008_aera_-_housing_stability_and_school_success_of_chlidren_03-27-2008_4.pdf

Stahre M, VanEenwyk J, Siegel P, Njai R. Housing Insecurity and the Association with Health Outcomes and Unhealthy Behaviors, Washington State, 2011. Prev Chronic Dis 2015;12:140511.  DOI: http://dx.doi.org/10.5888/pcd12/140511

NKBDS Encoding-Modeling Part1 Orientation 2017-06-20
Susan Matney & Tess Settergren

Policy Recommendation
The NCSBN ID should be used by key stakeholders as a nurse identifier to help demonstrate the value of nurses through research, and enhance patient care and outcomes via more comprehensive documentation in the EHR, ERP, and other health IT systems.

Dr. Jennifer P. Lundblad

President & CEO, Stratis Health, Minnesota

Dr. Lisa Moon

CEO Advocate Consulting, Minnesota

Clinical Assistant Professor, University of MN