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Modeling Flowsheet Data for Clinical Research.

Johnson SG, Byrne MD, Christie B, Delaney CW, LaFlamme A, Park JI, Pruinelli L, Sherman SG, Speedie S, Westra BL - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: Health care data included in clinical data repositories (CDRs) are increasingly used for quality reporting, business analytics and research; however, extended clinical data from interprofessional practice are seldom included.This study characterizes the extended clinical data derived from EHR flowsheet data that is available in the University of Minnesota's CDR and describes a process for creating an ontology that organizes that data so that it is more useful and accessible to researchers.The challenges of the manual process and difficulties combining similar concepts are discussed.

View Article: PubMed Central - PubMed

Affiliation: University of Minnesota, Institute for Health Informatics.

ABSTRACT
Health care data included in clinical data repositories (CDRs) are increasingly used for quality reporting, business analytics and research; however, extended clinical data from interprofessional practice are seldom included. With the increasing emphasis on care coordination across settings, CDRs need to include data from all clinicians and be harmonized to understand the impact of their collaborative efforts on patient safety, effectiveness and efficiency. This study characterizes the extended clinical data derived from EHR flowsheet data that is available in the University of Minnesota's CDR and describes a process for creating an ontology that organizes that data so that it is more useful and accessible to researchers. The process is illustrated using a pressure ulcer ontology and compares ease of finding concepts in i2b2 for different data organization approaches. The challenges of the manual process and difficulties combining similar concepts are discussed.

No MeSH data available.


Related in: MedlinePlus

Template based navigation (i2b2)
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f3-2087004: Template based navigation (i2b2)

Mentions: In order to further test the organization of the concepts, i2b2 was used to illustrate how researchers would navigate concepts to answer simple questions, e.g. “How many patients have pressure ulcers?” There were two flowsheet measures that are used to record whether a patient has a pressure ulcer. One of the fields expects “Yes/No” answers. The other has “Suspected/No” as answers. Unfortunately, these measures are named the same in the CDR and they appear on 14 different templates. A researcher using i2b2 would have to follow 14 different paths to find one of the two measures and either put in a “Yes” or “Suspected” (depending on the measure) to find all of the patients with pressure ulcers. Figure 3 shows what the researcher would see in i2b2 if they were using they template/group/measure hierarchy. The i2b2 diagram is only a partial view since it is not possible to open the hierarchy and show all 14 data elements simultaneously. If the researcher used the ontology based navigation, the concept of “Pressure Ulcer Present” would only exist once. Figure 4 shows what the researcher would see in this case. The concept of “Pressure Ulcer Present” is still shown to have two forms. The confirmed form has “Yes/No” answers and the suspected form as “Suspected/No” as answers. However, from a researcher’s point of view, all of the concepts and information needed to specify answers to the question were located near each other in the navigation hierarchy.


Modeling Flowsheet Data for Clinical Research.

Johnson SG, Byrne MD, Christie B, Delaney CW, LaFlamme A, Park JI, Pruinelli L, Sherman SG, Speedie S, Westra BL - AMIA Jt Summits Transl Sci Proc (2015)

Template based navigation (i2b2)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525247&req=5

f3-2087004: Template based navigation (i2b2)
Mentions: In order to further test the organization of the concepts, i2b2 was used to illustrate how researchers would navigate concepts to answer simple questions, e.g. “How many patients have pressure ulcers?” There were two flowsheet measures that are used to record whether a patient has a pressure ulcer. One of the fields expects “Yes/No” answers. The other has “Suspected/No” as answers. Unfortunately, these measures are named the same in the CDR and they appear on 14 different templates. A researcher using i2b2 would have to follow 14 different paths to find one of the two measures and either put in a “Yes” or “Suspected” (depending on the measure) to find all of the patients with pressure ulcers. Figure 3 shows what the researcher would see in i2b2 if they were using they template/group/measure hierarchy. The i2b2 diagram is only a partial view since it is not possible to open the hierarchy and show all 14 data elements simultaneously. If the researcher used the ontology based navigation, the concept of “Pressure Ulcer Present” would only exist once. Figure 4 shows what the researcher would see in this case. The concept of “Pressure Ulcer Present” is still shown to have two forms. The confirmed form has “Yes/No” answers and the suspected form as “Suspected/No” as answers. However, from a researcher’s point of view, all of the concepts and information needed to specify answers to the question were located near each other in the navigation hierarchy.

Bottom Line: Health care data included in clinical data repositories (CDRs) are increasingly used for quality reporting, business analytics and research; however, extended clinical data from interprofessional practice are seldom included.This study characterizes the extended clinical data derived from EHR flowsheet data that is available in the University of Minnesota's CDR and describes a process for creating an ontology that organizes that data so that it is more useful and accessible to researchers.The challenges of the manual process and difficulties combining similar concepts are discussed.

View Article: PubMed Central - PubMed

Affiliation: University of Minnesota, Institute for Health Informatics.

ABSTRACT
Health care data included in clinical data repositories (CDRs) are increasingly used for quality reporting, business analytics and research; however, extended clinical data from interprofessional practice are seldom included. With the increasing emphasis on care coordination across settings, CDRs need to include data from all clinicians and be harmonized to understand the impact of their collaborative efforts on patient safety, effectiveness and efficiency. This study characterizes the extended clinical data derived from EHR flowsheet data that is available in the University of Minnesota's CDR and describes a process for creating an ontology that organizes that data so that it is more useful and accessible to researchers. The process is illustrated using a pressure ulcer ontology and compares ease of finding concepts in i2b2 for different data organization approaches. The challenges of the manual process and difficulties combining similar concepts are discussed.

No MeSH data available.


Related in: MedlinePlus