Last month we introduced our public Capacity Planning Tool to support your ongoing COVID-19 response and recovery. We have introduced a major update allowing you to forecast infections based upon actual county level data and dynamic infection spread rates (Empirical Model), as well as better classification of ICU patients. You can still run multiple scenarios and estimate demand for beds, mechanical ventilators, supplies such as personal protection equipment (PPE), and staff. We hope that you will view this demo as our experts explain how to best use these new features and answer questions from the audience. The topics covered include: - A brief review of the Capacity Planning Tool - How to forecast infections based upon actual county level data and dynamic infection spread rates - Improved classification of ICU patients - Where to get additional help if needed - Q&A session with our experts

1. Capacity Planning Tool
Demonstration and Q&A Session
“Empirical Data Modeling”
May 12, 2020
Jason Jones & John Hansmann
Confidential and Proprietary

2. Agenda
1. Introductions
a. Jason Jones, John Hansmann
2. Health Catalyst Capacity Planning Tool
a. Review of the Health Catalyst
Capacity Planning Tool
b. New Features
a. Empirical Model
b. Length of Stay for ICU Admissions
3. Demonstration of Health Catalyst
Capacity Planning Tool
4. Q&A Session

3. © 2020
Health
Catalyst
Health Catalyst Capacity Planning Tool
• Address capacity planning and how
the COVID-19 pandemic crisis may affect
your individual hospital or hospitals in a
system
• Provide a planning tool that looks forward 30-
60 days to estimate the number of resources
(e.g., beds, vents, etc.) required to take care
of your patients
• Provide time to identify available bed
options (e.g. hospital, clinic, community)
• Existing Features / Characteristics
o Built upon respected Penn Med demand model
o Input parameters (eg. population, infection rates,
LOS, vent days, bed capacity, etc.)
o ICU and non-ICU demand and capacity
o Staffing and PPE Impact
o Flexible, “what if” analyses
o Load actuals, Save scenarios
• Users for Capacity Planning tools
o COVID-19 Task Forces
o Hospital Incident Command Centers
o Planners
o COO / CNO / CMO / Operations Officers /
Quality / Risk / Facilities
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Health
Catalyst
HC Capacity Planning Tool – New Features (V2.1)
• New Features
o Empirical Model
• State selection
• County selection
• Override Population
• Forecast Methods
Ø Exponential Smoothing (ETS)
Ø Local Regression (LOESS)
Ø Spline
Ø Linear
o Length of Stay
• ICU admission – separated into ICU days and
non-ICU days portions
• Non-ICU admission
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Total 13
days

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Health
Catalyst
Demonstration Health Catalyst Capacity Planner
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https://www.healthcatalyst.com/
https://www.healthcatalyst.com/covid19-capplan/

6. Q & A
Capacity Planning Tool

7. © 2020
Health
Catalyst
Thank You for Participating
Development Team
Evan Sanders
Haider Syed
Jason Jones
John Hansmann
Josh Ferguson
Larry Lofgreen
Max Taggart
Mike Mastanduno
For more information, please
contact us at:
covidcapacity@healthcatalyst.com
Capacity Planning Tool:
https://www.healthcatalyst.com/covid
19-capplan/
Website:
https://www.healthcatalyst.com/
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Health
Catalyst
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Appendix
Training Example

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Health
Catalyst
• Left Panel (input): Settings,
load/save scenarios, load actuals
• Right Panel (output): Results,
including text, graphs, and
download
• Currently showing defaults
• Version number and date in the top
left (with link to features)
Site Loaded With Defaults
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Health
Catalyst
• Still showing defaults…
• Scroll down on right panel to see
chart of new hospital admissions,
hospital census, etc.
• Text indicates admission peaks and
other relevant information
immediately below charts.
Site Loaded With Defaults
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Health
Catalyst
• Left Panel (input): Scroll to “Spread
and Contact Parameters” and
change “Doubling Time” from 4 to 6
days.
• Right Panel (output): Charts and
text change.
• Note y-axis has adjusted to lower
values (e.g., 400 to 200)
• Note text has reflected lower peaks
(e.g., peak admissions dropped
from 388 on Jun 9 to 193 on Jul 13)
Changing One Parameter
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Health
Catalyst
Scenario:
• Place to load scenarios—used to rapidly load and modify previously saved scenarios
• Author name for scenario—used to label the scenario file
• Scenario name—used to label the scenario file
Hospital Parameters:
• Regional Population—entire relevant catchment area population
• Hospital Market Share—used to determine how many patients hospital will receive
• Current COVID-19 Total Hospital Census—used to estimate the infection & demand curves and checked again any uploaded data
• Current Date—used to estimate infection & demand curves and place vertical line in charts
COVID-19 Hospital Capacity:
• Total # of Best for COVID-19 Patients—used to compare demand and capacity
• Total # ICU Beds for COVID-19 Patients—used to compare demand and capacity
• Total # of Ventilators for COVID-19 Patients—used to compare demand and capacity
Spread and Contact Parameters:
• I know the date of the first hospitalized case—used to show or hide estimated doubling time or date of first hospitalization. If the first
hospitalization is known, the application will try to estimate the doubling time
• Doubling time in days—used to estimate the infection & demand curves
• Date of first hospitalized case—if known, used to estimate the doubling time
• Social distancing (% reduction)—applied to infection & demand curves only from “today” forward
Current Parameters
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Catalyst
Severity Parameters:
• Hospitalization %(total infections)—Percent of all infected patients who will be admitted to the hospital
• ICU %(total infections)—Percent of all infected patients who will be admitted to ICU (note: this is added to patients hospitalized)
• Ventilators %(total infections)—Percent infected patients who will need mechanical ventilators (note: not added to patients
hospitalized)
• Infectious Days—changes infection & demand curves (longer infection spreads infection to more people)
• Average Hospital Length of Stay (days)—Length of stay for a non-ICU hospital stay
• Average Days in ICU—Length of stay for an ICU patient (note: assumes entire LoS is in the ICU)
• Average Days on Ventilator—Number of days a ventilator is in use
Display Parameters:
• Number of days to project—changes the number of days to project forward (changes the x-axis in charts)
• Hospital Market Share—used to determine how many patients hospital will receive
• Set the Y-axis to a static value—can be used to easily visualize how parameter changes impact all charts
• Save Scenario—press to download a scenario file to a local or network drive. This file can then be dropped on the “Load Scenario”
section near the top of the left panel to recreate the scenario.
Actuals:
• Load Actuals—used to compare model results with actuals. Create the file, per instructions, and drop here to load in the application
Current Parameters
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Health
Catalyst
• Back to defaults…
• Scroll down on right panel to see
Capacity chart for total hospital
beds, ICU beds, and ventilators for
COVID-19 patients.
• Text indicates when resources will
be exhausted
• Note: This scenario calculates the
doubling rate based upon entering
the current COVID-19 patients and
the date the first patient was
admitted.
Loading a Scenario and
Looking at Capacity
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Health
Catalyst
• Dragged and dropped a
“Pessimistic” scenario
• Capacity chart for total hospital
beds, ICU beds, and ventilators for
COVID-19 patients has changed
(e.g., peak deficit in total beds went
from ~2,500 to ~500)
• Text for when resources will be
exhausted has changed (e.g.,
running out of total hospital beds
went from May 9 to Apr 18)
Loading a Scenario and
Looking at Capacity
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Health
Catalyst
• Using “Pessimistic” Scenario…
• Admissions per the scenario
• No actuals have been loaded so far
Loading Actuals and
Looking at Admissions
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Health
Catalyst
• Using “Pessimistic” Scenario…
• Admissions per model/scenario are
represented as lines and filled
circles now show actuals
• Dropped a ActualDataExample.csv
file (per instructions)
Loading Actuals and
Looking at Admissions
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Health
Catalyst
• Using “Pessimistic” Scenario…
• Admissions per model/scenario are
represented as lines and filled
circles now show actuals
• Changed number of days to project
from 100 to 30 to zoom in and see
differences
• Dropped a ActualDataExample.csv
file (per instructions)
Loading Actuals and
Looking at Admissions
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Health
Catalyst
• Using “Pessimistic” Scenario…
• Entered more recent values for
COVID-19 hospitalized patients and
the date
• Doubling rate is re-estimated,
admissions (and all other
demand/capacity) curves are
updated
• Can save the updated scenario for
future use
Loading Actuals and
Looking at Admissions
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