TY - JOUR
T1 - An Electronic Dashboard to Monitor Patient Flow at the Johns Hopkins Hospital
T2 - Communication of Key Performance Indicators Using the Donabedian Model
AU - Martinez, Diego A.
AU - Kane, Erin
AU - Jalalpour, Mehdi
AU - Scheulen, James
AU - Rupani, Hetal
AU - Toteja, Rohit
AU - Barbara, Charles
AU - Bush, Bree
AU - Levin, Scott R.
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.
AB - Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.
KW - Dashboard
KW - Hospital capacity
KW - Hospital overcrowding
KW - Patient flow
KW - Systems engineering
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UR - http://www.scopus.com/inward/citedby.url?scp=85048714534&partnerID=8YFLogxK
U2 - 10.1007/s10916-018-0988-4
DO - 10.1007/s10916-018-0988-4
M3 - Article
C2 - 29915933
AN - SCOPUS:85048714534
SN - 0148-5598
VL - 42
JO - Journal of medical systems
JF - Journal of medical systems
IS - 8
M1 - 133
ER -