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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

CDR table row proportions
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f1-2087004: CDR table row proportions

Mentions: The flowsheet data comprised the largest volume of information (table rows) in the CDR at 34% (Figure 1). That was more than double the second largest volume of data, Orders and Procedures. The flowsheet data consisted of 14,564 measures (each measure is one type of row) in 2,972 groups in 562 templates. There were over 1.2 billion observations stored in the flowsheets. Ninety-five percent (95%) of all of the observations were covered by 2,000 measures; 65% of the measures (9,505) were choice lists. There were 56,965 values within those choice lists.


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)

CDR table row proportions
© Copyright Policy
Related In: Results  -  Collection

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

f1-2087004: CDR table row proportions
Mentions: The flowsheet data comprised the largest volume of information (table rows) in the CDR at 34% (Figure 1). That was more than double the second largest volume of data, Orders and Procedures. The flowsheet data consisted of 14,564 measures (each measure is one type of row) in 2,972 groups in 562 templates. There were over 1.2 billion observations stored in the flowsheets. Ninety-five percent (95%) of all of the observations were covered by 2,000 measures; 65% of the measures (9,505) were choice lists. There were 56,965 values within those choice lists.

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