Format

Send to

Choose Destination
J Am Med Inform Assoc. 2017 Apr 1;24(e1):e111-e120. doi: 10.1093/jamia/ocw124.

Identifying collaborative care teams through electronic medical record utilization patterns.

Author information

1
Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
2
School of Nursing, Vanderbilt University.
3
Department of Anesthesiology, Vanderbilt University.
4
Healthcare Leadership Program, School of Nursing, Vanderbilt University.
5
Department of Electrical Engineering and Computer Science, Vanderbilt University.

Abstract

Objective:

The goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system.

Materials and Methods:

To perform this investigation, we designed a data-mining framework that relies on a combination of latent topic modeling and network analysis to infer patterns of collaborative teams. We applied the framework to the EMR utilization records of over 10 000 employees and 17 000 inpatients at a large academic medical center during a 4-month window in 2010. Next, we conducted an extrinsic evaluation of the patterns to determine the plausibility of the inferred care teams via surveys with knowledgeable experts. Finally, we conducted an intrinsic evaluation to contextualize each team in terms of collaboration strength (via a cluster coefficient) and clinical credibility (via associations between teams and patient comorbidities).

Results:

The framework discovered 34 collaborative care teams, 27 (79.4%) of which were confirmed as administratively plausible. Of those, 26 teams depicted strong collaborations, with a cluster coefficient > 0.5. There were 119 diagnostic conditions associated with 34 care teams. Additionally, to provide clarity on how the survey respondents arrived at their determinations, we worked with several oncologists to develop an illustrative example of how a certain team functions in cancer care.

Discussion:

Inferred collaborative teams are plausible; translating such patterns into optimized collaborative care will require administrative review and integration with management practices.

Conclusions:

EMR utilization records can be mined for collaborative care patterns in large complex medical centers.

KEYWORDS:

collaborative networks; data mining; electronic medical records; health care organization modeling

PMID:
27570217
PMCID:
PMC6080725
DOI:
10.1093/jamia/ocw124
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center