TeleTracking's patient flow solutions produce a tremendous amount of data. Knowing what data to track, measure, and analyze can seem like an impossible challenge. Our team of experts has been driving change and improving patient flow for nearly three decades. That collective knowledge and expertise is now infused into Data IQ®, our next-generation, cloud-hosted, and powerful analytics solution.

Latest updates to Data IQ®

With visibility across the enterprise, staff can better understand the full picture of operations, identify workflow silos that may be impacting other departments, and quickly determine if issues are systemic or site-specific.

Operational data is presented in an easy-to-consume format with the ability to drill from the enterprise down to the individual patient or employee for deeper analysis

With Data IQ®, staff have real-time visibility and a shared understanding of changing conditions and so can work together to improve operations in the moment, remedy acute bottlenecks before they become system-wide concerns, and act cohesively in high-pressure situations.

TeleTracking’s best practices and three decades of expertise have been translated into a best-in-class reporting package. This reporting package offers a blueprint for operational improvement, helps your teams track the metrics that matter most, and can be customized based on your organization’s needs.

As organizations expand with the addition of new facilities, Data IQ® scales accordingly. Cloud hosting minimizes on-site maintenance costs and reduces the number of on-site IT resources needed to support the system. And, because the solution is hosted in the Cloud, access to new features and updates is expedited.

Subscriptions deliver snapshots of dashboards and/or views via email. Project leads, supervisors, and analysts can subscribe other Data IQ® users to the dashboards or views that are meaningful to the work they do. Subscriptions are delivered on a recurring schedule and can be removed at any time.

Unlike subscriptions, which are delivered on a scheduled basis, data-driven alerts are delivered when key thresholds are reached. The data and the threshold value that trigger the alert are specified when the alert is created.

Viewers, editors, and publishers can share observations and collaborate on dashboards and/or views through comments. Comments are specific to the dashboard and remain until they are removed by the author.

Publishers and editors will have direct access to a web-based report publishing tool to create their own content. These users will be able to create flat table reports, interactive reports, and dashboards while connected to TeleTracking published data sources.

Data IQ® provides a real-time view of operations across a health system — enabling teams to make critical patient care decisions in the moment. Enterprise dashboards are intended to display on large, wall-mounted monitors in your Command Center or other key visible areas. To facilitate in-the-moment decision making, the dashboards are set to look for and display any new data every 60 seconds. TeleTracking’s industry leading best practices are embedded into these reports as goals, allowing users to quickly identify areas of opportunity. See Command Center Dashboards

Data IQ® desktop reports provide historical reporting, drill down views, enterprise-wide visibility, and full customization. These reports are built to be interacted with, so that users build operationally valuable relationships that can answer difficult questions with a few clicks. Each report highlights different components of healthcare operations and provide insight at each level. TeleTracking’s industry leading best practices are embedded into these reports as goals, allowing users to quickly identify areas of opportunity. See Interactive Dashboards.

Access to Data IQ® is via the Analytics menu in Operations IQ® Platform. Use the following steps to sign in.

TeleTracking Technologies, Inc. has developed best practices that correlate with specific data points across the care continuum. Based on 30+ years of data collection, the following metrics are recommended as a standard of measure for their corresponding data points.

Access best practices align operational and clinical resources to accelerate the processes that take place between a patient's arrival and their placement in the correct bed.

Definition: The time from when the patient is clinically ready to move (RTM) to when the bed is assigned.

It should take less than 15 minutes for a patient to be assigned a bed once they are clinically ready to move (RTM).

Definition: The time from when the patient is clinically ready to move and has a clean bed assignment to when the patient occupies the bed in TeleTracking.

It should take less than 30 minutes for a patient to occupy a clean bed in TeleTracking once they are clinically ready to move (RTM).

Definition: The percentage of time that the patient is designated as ready to move (RTM) prior to assignment.

Patients should be designated as ready to move (RTM) before assignment 95% of the time or greater.

Definition: The time from the ED bed request to when the patient occupies the bed in TeleTracking.

It should take less than 120 minutes for a patient to occupy the bed from an ED bed request.

Definition: The percentage of time that the patient occupies a bed different from what was assigned.

Bed assignment conflicts should occur less than 10% of the time.

Definition: The time between the initial physician page and the return call.

It should take 5 minutes for a physician to return a call from the initial page.

Definition: The time between the initial call to the Transfer Center until the patient is accepted.

There should be 10 minutes between an initial call to the Transfer Center and when the patient is accepted.

Definition: The percentage of calls disconnected prior to access center agent connection.

The percentage of disconnected calls should be less than 8%.

Definition: The percentage of patients that are either canceled or denied by the Transfer Center.

Less than 10% of patients should be canceled or denied by the Transfer Center.

Definition: The time from the first ring to connection to an access center agent.

It should take 20 seconds or less to connect to an access center agent.

Throughput best practices focus on improving communication among nurses, transporters, and environmental service employees.

Definition: The time from when the patient is clinically ready to move (RTM) to when the bed is assigned.

It should take less than 15 minutes for a patient to be assigned a bed once they are clinically ready to move (RTM).

Definition: The time from when the patient is clinically ready to move and has a clean bed assignment to when the patient occupies the bed in TeleTracking.

It should take less than 30 minutes for a patient to occupy a clean bed in TeleTracking once they are clinically ready to move (RTM).

Definition: The percentage of time that the patient is designated as ready to move (RTM) prior to assignment.

Patients should be designated as ready to move (RTM) before assignment 95% of the time or greater.

Definition: The time difference between a transport job that has been accepted (dispatched) by the transporter, and when the transporter completes the job.

It should take 20 minutes for a transporter to complete a job once it has been accepted.

Definition: There should be less than 15 minutes from when a transport job is created and when it begins.

There should be less than 15 minutes from when a transport job is created and when it begins.

Definition: The time difference between a created job, and when the job is completed.

There should be 30 minutes between a jobs creation and its completion.

Definition: The percentage of time that transport jobs are cancelled, or rescheduled, after the transporter has accepted the job.

Job cancellations should occur less than 10% of the time.

Definition: The total time that a transporter is delayed throughout the transport job.

Transporters should be delayed by no more than 5 minutes during a job.

Definition: The average number of trips that a transporter completes in one hour.

Transporters should complete 3 trips within one hour.

Discharge best practices are used to coordinate, improve, and complete patient discharges.

Definition: The percentage of time that a discharge is preceded by a Pending Discharge.

Discharges should be preceded by a Pending Discharge 70% of the time or greater.

Definition: The percentage of time that a discharge is preceded by a Confirmed Discharge.

A Confirmed Discharge should precede a discharge 90% of the time or greater.

Definition: The elapsed time between when the Confirmed Discharge is received, to when the patient actually leaves and the bed is made dirty.

There should be less than 120 minutes between when a Confirmed Discharge is received to when the patient actually leaves.

Definition: The percentage of patients that were discharged before 11am.

Before or by 11am, 25% of patients should be discharged.

Definition: The percentage of patients that were discharged before 2pm.

Before or by 2pm, 50% of patients should be discharged.

Definition: The percentage of patients taken out by transporters.

Patients should be discharged by transporters 70% of the time or greater.

Definition: From the time EVS is notified of a dirty bed, to the time EVS marks the bed in progress (cleaning commences).

There should be 30 minutes or less between when EVS is notified of a dirty bed, to when the bed is marked in progress.

Definition: From the time EVS begins cleaning the room (in progress status) to the completion of the room clean (clean status).

There should be 30 minutes or less between when EVS begins cleaning the room to when the room clean is complete.

Definition: From the time EVS is notified of a dirty bed, to the time that the bed is cleaned.

There should be 60 minutes from the time EVS is notified of a dirty bed to when it's cleaned.

Definition: The percentage of admitted patients badged with a Location Tracking badge.

Admitted patients should be badged with a Location Tracking badge 95% of the time.

Google Chrome is the recommended browser for Data IQ®.

MiNiFi Java Agent 1.8

MiNiFi should be installed on a virtual server with the specifications below. The agent installs a specific version of Java needed to run Data IQ® properly.

For clients that have Capacity Management Suite® and/or Data IQ®, the virtual server set up for Data IQ® should be separate from the Capacity Management Suite® server.

Updating Java on your machine doesn't present a problem for this application. However, if you see the window below after updating Java, do not uninstall any previous versions as this will prevent Data IQ® from functioning properly.

You will need 100 GB+ of free disk space, which will mostly be used for the initial load.

All traffic is encrypted using PKI/TLS encryption. Access control is handled by client X509 certificates, and the certificates are unique to each customer.

To connect to the on-premise SQL Server databases, you use either Windows Authentication or SQL authentication. Windows Authentication is preferred; however, in cases where Windows Authentication is not possible, use SQL Authentication. Details are in the tables below.

You will be able to whitelist Data IQ® using the domains listed in the table below. Traffic with a Web Proxy Capable value of "YES" may be used with a web proxy to perform content-based filtering rather than IP whitelisting.

Traffic with a Web Proxy Capable value of "NO" will have to be either DNS or IP address whitelisted.

All traffic ingress is fronted by high-performance elastic load balancers. The IP addresses of these load balancers are static, and must be whitelisted. This also means that the URL patterns listed should not run through a network proxy on the way out of the hospital network.

Amazon Web Services (AWS)-based services with dynamic IP addressing (such as SnowFlake) cannot be whitelisted by a single IP address. Therefore, the entire IP block for the given AWS region must be whitelisted if DNS whitelisting cannot be used.

AWS publishes its current IP address ranges in JSON format. To view the current ranges, see the .json file. To maintain history, save successive versions of the .json file on your system.

To determine whether there have been changes since the last time that you saved the file, check the publication time in the current file and compare it to the publication time in the last file that you saved.

Notes: Server reports, Dashboards, Publishing Content

This network rule should be trusted at the end user's laptop or desktop.

Notes: Database connection

This network rule should be trusted at the end user's laptop or desktop.

Notes: Data ingest

*.*.teledev.io may be needed when using a Palo firewall. Otherwise, *.teledev.io should suffice.

Notes: Query data from Capacity IQ®/Transfer IQ® applications

Users with the Admin role set up and manage user accounts. The process for provisioning users is described in the following sections. The method by which Data IQ® users are provisioned is determined by (1) your health system’s current licensing for the Operations IQ® Platform and (2) the identity provider you will use. The following sections explain the options.

If you are currently using the Operations IQ® Platform and are provisioning users for Data IQ®, you will likely use your existing user setup process to provision these users. Your TeleTracking representative can provide guidance.

You set up and manage users through either your health system’s Active Directory or TeleTracking's Active Directory.

If you plan to use or are currently using your health system’s Active Directory (AD) to manage users, the first step to provisioning users is adding security groups to your AD. The security groups map to reciprocal user roles in Data IQ®.

If you plan to use or are using TeleTracking’s Active Directory, you can use either the Data Import option or the User option on the Admin menu in the TeleTracking IQ® platform. To determine which option is best for you, work with your TeleTracking representative.

User role determines the levels of permissions allowed for a user, including whether a user can publish, interact with, or only view content published to the server. You assign one or more roles to each user either in your active directory or when creating the user account in the Operations IQ® Platform.

To provision Data IQ® users in your Active Directory, follow these steps:

Provide each user the URL to the Operations IQ® Platform and the username and password required for sign in.

You can edit a user's role at any time. Do one of the following:

The next time the user signs in, the role change will be in place.

You manage expiring and resetting passwords in your Active Directory.

User role determines the levels of permissions allowed for a user, including whether a user can publish, interact with, or only view content.

Report Viewers are typically consumers of the information on a dashboard and use the information to understand the health of the hospital, drive decisions, or monitor key indicators such as completed placements or averages for ready-to-move to occupied. Report viewers have access to the following options when looking at dashboard:

Report viewers cannot create a new workbook and will not see the option.

Report editors have the same permissions as a report viewer, plus these:

Report publishers have the same permissions as a report editor, plus the ability to create new workbooks using an existing data source.

Dashboards are a collection of several views (also referred to as reports or charts) that enable you to compare a variety of data simultaneously. Data IQ® offers two types of dashboards: interactive, which are intended for desktop use, and enterprise, which are intended for a Command Center or huddle wall.

Dashboards that track performance, such as Environmental Services and Transport, include ...

Interactive reports present historical data in aggregate form. Historical data can range from five minutes ago to several months ago. Users that want to go deeper into more specific layers of the data or information being analyzed can drill down by hovering and/or clicking an area of the report.

Intended to display on large, wall-mounted monitors in your Command Center or other key visible areas. Enterprise dashboards show similar information as interactive reports except the information shown is for the current day. Because they are intended for viewing, enterprise dashboards do not have filters and do not offer drill down features. Another key difference between enterprise and interactive dashboards is the color of the dashboard. Because enterprise dashboards are intended for display in corridors or Command Centers, the dark background and the contrast colors enhance the readability of the information making it easier for viewers to analyze and act.

Thresholds are defined by TeleTracking's Best Practices and are used on interactive and desktop dashboards to help you track operational performance. The icons described below provide a visual snapshot of performance.

You can customize threshold values to suit your health system's operations.

This dashboard replaces our Executive App and recreates its functionality in Data IQ®. This dashboard is designed specifically for a mobile device and it’s recommended to view using the Tableau Mobile App. The dashboard can also be viewed using a web browser. To view the Mobile view on a desktop, select the Device Layouts button in the top right.

This dashboard displays the Enterprise Census, Census by Campus, Census by Unit Category, and Emergency Department Metrics- Patients Waiting in ED, Current Longest Wait in ED, and Current Avg Wait Time in ED.

Data Source: Census Current + Current Patient Placement

This dashboard shows the current status of EVS employees. The dashboard displays the number of employees in each status, the number of employees in each status by campus, and the number of idle employees sorted by longest time being idle (meaning the employee at the top of the list has been idle for the longest amount of time).

Data Source: Current BedTracking Employee Status
​This data source should only be used with Capacity IQ® or Capacity Management Suite® version 2021.1 or earlier.

This dashboard shows the current status of Transport employees. The dashboard displays the number of employees in each status, the number of employees in each status by campus, and the number of idle employees sorted by longest time being idle (meaning the employee at the top of the list has been idle for the longest amount of time).

Data Source: Current TransportTracking Employee Status
​This data source should only be used with Capacity IQ® or Capacity Management Suite® version 2021.1 or earlier.

This dashboard displays the activity of a single transfer center and indicates durations, percentages, and values that fall within or outside performance goals. The top sets of numbers are enterprise-wide values while the bottom sets of numbers are for facilities, campuses, and service lines.

Data Source: IQ Case

This dashboard displays the durations of activities within facilities and provides reasoning for the declines of patients within singular facilities.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: IQ Facility Case + IQ Case

This dashboard displays the average response times by physicians across the enterprise with emphasis on the response time and volume of declines created by physicians.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: IQ Physician Communication + Transfer Center

This dashboard allows you to track bed availability and capacity with the consideration of additional census metrics.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Census Current

This dashboard displays the average duration of Transports and indicates durations that fall within or outside performance goals.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Current Transport Tracking

This dashboard displays the average duration of EVS jobs and indicates durations that fall within or outside performance goals. The first set of numbers along Average Response Time, Average Clean Time, and Average Turn Time represent enterprise-wide durations.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: EVS Streaming

This dashboard compares enterprise-wide durations, variables, and percentages against the prior month.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Sources: EVS Streaming, Census Current, IQ Case Patient Visit, and Current Transport Tracking

This dashboard breaks down environmental service metrics by employee to illustrate who is or is not meeting the thresholds of their position.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: BTJOBS

This dashboard is designed to quantify the individual facility interactions that occur with every transfer case. Seeing these interactions can help monitor performance and accountability measures for your facilities.

Data Source: Transfer Center Facility Communications Detail

This dashboard displays the average duration of patient placement in multiple fields and indicates durations that fall within or outside performance goals. In addition, the numerical value of patient statuses is tracked.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Patient Placement

This dashboard displays the key time intervals from when a bed becomes empty to when the next patient occupies the bed. The dashboard shows an average interval figure for all placements that have been completed. The pipeline highlights which parts of the process meet the best practice goals and those parts which might be causing delays to patient flow.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Sources: Current Patient Placement, Current Patient Visit, Current Transport Tracking, and EVS Streaming

This dashboard displays the progress of discharges across an enterprise. The top set of numbers represents enterprise-wide durations, values, and percentages. The lower part of the dashboard shows discharge percentages by facility.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Patient Visit

Note that the Discipline dimension for this data source is derived from the patient's current or last unit.

This dashboard shows the current observation patients in real time.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Current Patient Visit

This dashboard compares the activity of different services from the current month to the prior month through numeric values and percent changes.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Sources: Transfer Center + Current Transport Tracking

This dashboard displays the rate and progress of transfers per facility within an enterprise along with their geographic location on a topographic map.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Sources: IQ Case + Transfer IQ® Enterprise

This dashboard breaks down transporter metrics by employee to help illustrate who is or is not meeting the thresholds of their position.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Source: Current Transport Tracking

This dashboard displays key metrics such as ICU capacity and confirmed COVID-19 patients to help health systems combat COVID-19. The latest version of this dashboard also distinguishes between COVID-19 patients and all other patients and identifies patients by gender.

Data Sources: Census Current + Census Snapshot + Patient Visit

Users must filter out any isolation type that is either “None” or “Standard” for the total number of isolations (which appear at the top of the dashboard) to display accurate counts.

This dashboard displays the number of currently blocked beds by reason and location. This dashboard is connected to the new fast lane data source, Current Location Action Status. The currently blocked beds are defined as those that have an Action of Blocked, and an End Status Timestamp that is Null (meaning the blocked action is still active). By default, this dashboard shows all currently blocked beds by campus. This can be filtered to specific campuses using the filter menu in the top-left corner. This can also be further broken out to show by Unit or by Location by hovering over the “Campus” header until a +/- button appears.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Data Sources: Current Location Action Status + Location Action Status

Backdated Discharge Time is the time from the documented time of patient discharge (what is manually entered into the ADT) to the time it was actually entered and TeleTracking was notified of that patient's departure. By default, the Backdated Discharges interactive report shows only those with durations longer than 30 minutes but can be changed by using the parameter at the top of the report. Clicking on a bar in the Backdated Discharge Volume chart will filter the table below. The Backdated Discharge report is built from data in the Patient Visit data source.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Historical Blocked Beds interactive report contains information for any bed that was ever blocked during the selected date range. The report shows the total number of blocked beds by both the reason and the bed location. By default, this report shows the last full month of data but can be changed using the menu button in the top-left corner. Similar to the command center version, this dashboard can easily change the level of aggregation by hovering over the campus header until the +/- button appears.

The Care Progression Indicators interactive report displays data relating to the Care Progression Indicators contained within the Capacity IQ® solution. The interactive report displays the care progression indicators by status, grouping, and duration.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Census Historical Trends interactive report allows users to see their census percent over time. A unique calendar view makes it easy to follow the trends throughout the calendar year. This report also breaks out census by campus, month, day of the week, and hour of the day. Users can switch between physical and staffed census by using the parameter in the menu.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Discharge Milestones interactive report displays data relating to the Discharge Milestones functionality contained within the Capacity IQ® solution. The interactive report displays the discharge milestones by status, duration, and location. It also lists the number of delays by location and reason.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard displays the average duration of bed requests along with the placement of patients. Except for RTM Compliance by Campus/Unit, the dashboard’s numbers represent enterprise-wide durations and values. The data is pulled from the Patient Placement flat table. You can filter the data by Date, Placement Type, and/or Campus.

The following sections describe the views that are available in the dashboard.

The average number of completed placements displayed by Origin Unit Category and Origin Unit.

Patient Placement statistics. Data points included in the view are:

Admit Type =/= ‘Null’

Placement Status = Completed

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE 0 END

Use to monitor where placements are coming from.

The percentage of placements where RTM Time is before Bed-Assign Time.

Patient Placement statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE 0 END

Use to elevate the number of placements per campus.

The average time (in minutes) from when a bed was requested to when the bed was assigned, shown by the hour.

Patient Placement statistics. Data points included in the view are:

ED bedrequest To Bedoccupy Time - Average (IF [Origin Unit Category]="ED" THEN [Bedrequested To Bedoccupied Time] END)

BedRequest_Timestamp - Hour

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average ED Request to bed occupied time less than 15 minutes.

The average time (in minutes) from when a patient was Ready To Move (RTM) to when the bed was assigned, shown by the hour.

Patient Placement statistics. Data points included in the view are:

RTM To Bedassigned Time - Average

BedRequest_Timestamp - Hour

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommends an average RTM to assigned time of less than 15 minutes.

The average time (in minutes) from when a bed is requested to when the bed is finally occupied, shown by the hour.

Patient Placement statistics. Data points included in the view are:

BedRequested_to_BedOccupied_Time - Average

BedRequest_Timestamp - Hour

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE END

TeleTracking’s Best Practices recommend an average bed request to bed occupied time of less than 30 minutes.

The average time (in minutes) from when a patient is Read to Move (RTM) to when the bed is finally occupied, shown by the hour.

Patient Placement statistics. Data points included in the view are:

RTM_to_BedOccupied_Time - Average

BedRequest_Timestamp - Hour

Date Selector = 1

IF Date Type = “Today” THEN

IF Bedrequest Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Bedrequest Timestamp >= Start Date AND Bedrequest Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommends an average RTM to bed occupied time of less than 30 minutes.

This interactive dashboard displays the progress of environmental services across an enterprise. The data is pulled from the BTJobs flat table. You can filter the data by Date, Campus, and/or Adjusted Clean Flag.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The following sections describe the views that are available in the dashboard.

When the Adjusted Cleans Flag checkbox is selected, the cleaned beds included are only those that fall within the thresholds set by Total_InProgress_Time OR Response_Time. The percentage is the number of beds that have been cleaned vs all other beds.

Bed cleaning job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END
ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END

Use to monitor the number of open and clean beds versus all other beds in the network.

When the Adjusted Cleans Flag checkbox is selected, the cleaned beds included are only those that fall within the thresholds set by Total_InProgress_Time OR Response_Time. The percentage is the number of beds that have been cleaned versus all other beds.

Bed cleaning job statistics. Data points included in the view are:

Count Adjust Cleans (yes)

SUM(IF [Adjusted Cleans Flag]="Y" THEN [Number of Records]END)

% yes adjust cleans

SUM(IF [Adjusted Cleans Flag]="Y" THEN [Number of Records]END/TOTAL(SUM([Number of Records]))

Date Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END

Use to monitor the number of open and clean beds versus all other beds in the network

The number of beds that have been found dirty without a requested job.

Bed cleaning job statistics. Data points included in the view are:

Found Beds

IF [Job Create Reason Type] = "Found Bed" THEN [Number of Records]

ELSE 0

END

Data Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END END

Use to monitor how many beds are being found without a requested clean job.

The amount of Total Requested Jobs vs the Completed Jobs displayed by Campus.

Bed cleaning job statistics. Data points included in the view are:

Campus

Unit

Clean beds (IF Job Status Type = “Complete” THEN Number of Records ELSE 0 END)

This should be used as a gauge to the productivity of each campus. The productivity is the number of clean beds divided by the number of requested jobs.

Response time is number of minutes from when a bed cleaning job was created until it is put to In Progress. This view shows the average response time between the specified start and end dates.

Bed cleaning job statistics. Data points included in the view are:

Response Time - Average

Created Timestamp - Hour

Avg(Response Time) =/='Null'

Date Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend a Response Time of under 30 minutes.

The average time in minutes that it took for EVS to clean a bed from in-progress status to clean status.

Bed cleaning job statistics. Data points in the view are:

Total Inprogress Time - Average

Created Timestamp - Hour

Avg(Total Inprogress Time) =/='Null'

Date Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend a Clean Time of under 30 minutes.

The average time from when a bed cleaning job was created until it was completed.

Bed cleaning job statistics. Data points included in the view are:

Overall Turn Time - Average

Created Timestamp - Hour

Avg(Overall Turn Time) =/='Null'

Date Selector = 1

IF Date Type = “Today” THEN

IF Created Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Created Timestamp >= Start Date AND Created Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend a Turn Time of under 60 minutes.

This dashboard breaks down environmental service metrics by employee to illustrate who is or is not meeting the specified thresholds. The data is pulled from the BT Jobs flat table. You can filter the data by Date and Employee.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This dashboard is designed to quantify the individual facility interactions that occur with every transfer case. Seeing these interactions can help monitor performance and accountability measures for your facilities. You can filter the data by Date Type, Start / End Date, and Facility Name.

This on-premise transfer center interactive dashboard displays the durations of activities within facilities and provides reasoning to the declines of patients by facility. The data is pulled from the Transfer Center Facility Communication Detail flat table. You can filter the data by Start / End Date, Referring Facility, Destination Unit, and/or Level of Care.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard displays length of stay, discharge, and census metrics calculated from the Patient Visit data source. Length of Stay is based on the amount of time between the Admit Timestamp and the Actual Discharge Timestamp. This dashboard also displays metrics for all hospital patients as well as ICU patients specifically. Any patient with a unit category name of "critical care" will be considered an ICU patient.

The data is pulled from the Patient Visit data source. You can filter the data by Campus and Date Range.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Observation Patients interactive report shows all observation patients for the past two weeks, including patients who have been discharged. This allows you to monitor observation patients by location and observation duration.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard compares the activity of different services from the current month to the prior month through numeric values and percent changes. The data is pulled from the Transfer IQ® and Transport Tracking flat tables. You can filter the data by Hospital Service, Referring Facility, and/or Referring Unit.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard displays the progress of discharges. The data is pulled from the Patient Visit data source. Note that the Discipline dimension for this data source is derived from the patient's current or last unit. You can filter the data by Date, Campus, and/or Unit.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Performance Trending Scorecard is designed to help users look at the key Capacity IQ® metrics needed to improve patient flow all in one place. Each metric is a key indicator of where the patient flow opportunities and successes are and can help users understand what processes to focus on. Additionally, users can see these metrics over different time spans to help narrow or broaden the view of performance.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Performance Trending Scorecard displays Full Historical data from Placement (broken out into multiple areas), Patient Visit, Transport, and EVS Standard Lane data sources. By default, the dashboard displays the data by month for the past 12 months. Daily, weekly, and monthly view options are provided to help users better understand which direction their patient flow efforts are heading.

To change these date aggregations and refine which campuses/units to include, simply click the filter menu in the top-left corner of the screen. Similar reports in Capacity IQ® were heavily filtered to include only certain campuses/units, so we recommend looking at all of the available filters to remove any unwanted units:

This scorecard can be further configured to modify the target metric values. For example, if your health enterprise has a different target metric for an EVS response time, click Show Target Values in the top-right corner of the screen. Then, type in the desired value to change the target, which will change the color calculations to match.

This interactive dashboard displays the average duration of response times by physicians with emphasis on the response time and volume of declines created by physicians. The data is pulled from the Transfer Center and Transfer Center Consult flat tables. You can filter the data by Start / End Date, Campus Name, and/or Referring Facility.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Predictive Admissions interactive report leverages Tableau's built-in forecasting feature to predict campus admissions for the next 2 weeks. By default, the data is displayed for all units that have a full 90 days' worth of data. The blue line shows the actual admits, while the green line displays the predictions, as well as the confidence interval in the lighter shaded areas.

The tables on the right show a history of past forecasts. In this example below, we can see what the estimates were for each campus, as well as the actual admissions.

This report is not meant to predict admissions with 100% accuracy. During testing, the forecast accuracy still performed closer to 90% accuracy. The forecast simply looks at Full Historical data in order to create a trend for the next 2 weeks. These are the full forecast options:

If there is not enough Full Historical data to create a forecast, the report will show a "No forecast" tag on the chart. The example below shows a campus with partial data that breaks the forecast. We've added a filter to only show units with full data. To see which units are filtered out with partial data, hover over the "Missing Units" text in the top right of the screen.

For more information on how the forecasting feature works, please review this Tableau white paper.

This interactive dashboard allows users to view notes attached to Transfer IQ® cases and recreate previous History reports. The data is pulled from the IQ Notes, IQ Issues, and IQ Issue Notes data sources.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Transfer Case Volume Analysis report is a new Interactive report that allows you to easily see the detailed case volume information for a given date range. This report connects to the IQ_Case Standard Lane data source and allows for a Full Historical picture of Transfer IQ® cases. Clicking on any bar in one of the charts will filter all of the other charts in the report. The report breaks out the total cases by a number of metrics, including:

Users can also choose to look at this data in a row-by-row tabular view. Clicking the “Open Table” text at the top of the dashboard will bring the user to this tabular view:

Filters can also be applied on the tabular view by clicking the menu icon in the top-left corner.

This interactive dashboard displays the overall case cancellations by campus and service line and shows trends in cancellations from previous years. The data is pulled from the Transfer IQ® flat tables (IQ Case or Transfer IQ®). You can filter the data by Date, Destination Facility, EMC Status, and/or Referring Unit.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard displays the overall case declines by campus and service line and trends in declines from previous years. The data is pulled from the Transfer IQ® flat tables (IQ Case or Transfer IQ®). You can filter the data by Date, Destination Facility, EMC Status, and/or Referring Unit.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The following sections describe the views that are available in the dashboard.

The total amount of declined dispositions.

The Transfer Center Data point included in the view is the SUM(Number of Records).

Case Disposition = Declined

Use to monitor overall declined dispositions.

The amount of declined dispositions displayed over time by the Campus Name.

The Transfer Center Data points included in the view are:

Campus Name

SUM(Number of Records)

Case Disposition = Declined

Use to monitor which campuses are declining the most cases.

The amount of cancelled dispositions displayed over time by the month and year of Case Created Date.

Transfer Center Data points included in the view are:

Case Create Date – Month and year

SUM(Number of Records)

Case Created Date = Last 3 Years

Case Disposition = Declined

User to monitor the volume of declined dispositions over time.

The amount of declined dispositions displayed over time by the Service Line.

Transfer Center Data points included in the view are:

Service Line

SUM(Number of Records)

SUM(Contribution Margin)

Where [Number of Records * Contribution Margin Parameter]

Case Disposition = Declined

Use to monitor which service lines have the highest amount of declined dispositions.

The amount of declined dispositions displayed over time by the Case Disposition Reason.

Transfer Center Data points included in the view are:

Case Disposition Reason

SUM(Number of Records)

Case Disposition = Declined

Use to monitor the top reasons that cases are being declined.

This interactive dashboard displays the overall transfer case inbound requests by campus, service line, and trending volumes month over month. The data is pulled from the Transfer IQ® flat tables (IQ Case or Transfer IQ®). You can filter the data by Date, Destination Facility, EMC Status, and/or Disposition.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The following sections describe the views that are available in the dashboard.

The total amount of inbound transfer requests.

The Transfer Center Data point included in the view is the SUM(Number of Records).

None

Use to monitor overall inbound transfer requests.

The amount of inbound requests displayed by the Destination Facility.

The Transfer Center Data points included in the view are:

Destination Facility

SUM(Number of Records)

None

Use to monitor which facilities are receiving the most inbound transfer requests.

The amount of inbound transfer requests displayed over time by the month and year of Case Entry Timestamp.

Transfer Center Data points included in the view are:

Case Entry Timestamp– Month and year

SUM(Number of Records)

Case Entry Timestamp = Last 3 Years

User to monitor the volume of inbound requests over time.
​

The amount of inbound requests displayed over time by the Hospital Service.

Transfer Center Data points included in the view are:

Hospital Service

SUM(Number of Records)

SUM(Contribution Margin) (Where [Number of Records * Contribution Margin Parameter])

None

Use to monitor which service lines have the highest amount of inbound requests.
​

The amount of cancelled dispositions displayed over time by the Referring Facility. Can show all campuses or lets the user see the Top N (selectable parameter) campuses compared to all others.

Transfer Center Data points included in the view are:

Referring Facility

SUM(Number of Records)

None

Use to monitor which facilities are receiving the most inbound transfer requests.

This interactive dashboard displays the overall transfer case outbound requests by campus, service line, and trending volumes month over month. The data is pulled from the Transfer IQ® flat tables (IQ Case or Transfer IQ®). You can filter the data by Date, Referring Facility, and/or EMC Status.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The following sections describe the views that are available in the dashboard.

The total amount of outbound transfer requests.

The Transfer Center Data point included in the view is the SUM(Number of Records).

Case Disposition = Accepted

Use to monitor overall outbound transfer requests.

The amount of outbound requests displayed over time by the Transfer Reason.

The Transfer Center Data points included in the view are:

Transfer Reason

SUM(Number of Records)

Case Disposition = Accepted

Use to monitor the top transfer reasons for outbound requests.
​

The amount of outbound transfer requests displayed over time by the month and year of Case Entry Timestamp.

Transfer Center Data points included in the view are:

Case Entry Timestamp– Month and year

SUM(Number of Records)

Case Entry Timestamp = Last 3 Years

Case Disposition = Accepted

User to monitor the volume of outbound requests over time.

The amount of outbound requests displayed over time by the Service Line.

Transfer Center Data points included in the view are:

Hospital Service

SUM(Number of Records)

SUM(Contribution Margin) (Where [Number of Records * Contribution Margin Parameter])

Case Disposition = Accepted

Use to monitor which service lines have the highest amount of outbound requests.

The amount of cancelled dispositions displayed over time by the Referring Facility. Can show all campuses or lets the user see the Top N (selectable parameter) campuses compared to all others.

Transfer Center Data points included in the view are:

Referring Facility

SUM(Number of Records)

Case Disposition = Accepted

Use to monitor which campuses are receiving the most inbound transfer requests.

This Full Historical report displays information related to the case team assigned to transfer cases and a detailed breakdown of transfer cases.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Shows transfers on a given year, month, and/or day. The data is pulled from the Transfer Case OR IQ Case data sources. You can filter the data by Month, Year, Campus Name, and/or Case Disposition.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The Transfer Center Case Breakout interactive report displays trending information for all Transfer IQ® cases over a given period of time. By default, the report shows the cases broken out by week and disposition. Each section also displays the cases by In

Network and Out of Network. Each cell is compared to the previous value with both the text color and arrows.

The Transfer Center Case Breakout report is connected to the IQ_Case_Enterprise and Case_Physician_Communication Standard Lane data sources. This report is also highly configurable, with multiple filters for each section to ensure the most accurate data is being displayed. Please review the filter options when initially setting up the report:

The Lost Business section at the bottom displays the number of cases and a percentage calculated as (Cancelled + Declined Cases)/(All Cases – Consults – Other).

The Current Transfer Milestones fast lane data source and Interactive Report allows users to view Transfer Milestone data from the Capacity IQ® solution. The interactive report gives a detailed table view of the Transfer Milestones, focusing on Transfer Assign Time, Transfer Request Time, Patient Transfer Time, Patient Expected Discharge Time, and Actual Patient Discharge Time. The indicator in the rightmost column shows if the patient was discharged within 24 hours of the transfer taking place.

The Transfer Center Case Breakout interactive report displays trending information for all On Premise Transfer cases over a given period of time. This report differs slightly from the Transfer IQ® version that displays the cases by in and out of network. Users can still see the cases by in network and out of network by using the Destination Health System in the filter menu. By default, the report shows the cases broken out by week and disposition. Each cell is compared to the previous value with both the text color and arrows. This report is connected to the Transfer_Center_Consult Standard Lane data source.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

Displays case volumes by location, disposition, case type, service line, and destination/referring facilities. Clicking on any of the bars will filter the map to those specific locations. This interactive report is connected to the IQ_Case Standard Lane data source.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This dashboard breaks down transporter metrics by employee to help illustrate who is or is not meeting the thresholds of their position. The data is pulled from the Transport Tracking Jobs flat table. You can filter the data by Date and metrics Completed by User.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

This interactive dashboard displays the average duration of Transport requests along with the time taken by cancels and delays after dispatch. The charts on the right side of the dashboard show enterprise-wide durations. The data is pulled from the Transport Tracking flat table. You can filter the data by Date, Requesting Campus, and/or Destination Campus.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

The following sections describe the views that are available in the dashboard.

The average delay time shown by Origin Campus and Origin Unit.

Transport job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END
ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

Use this to gauge which campuses have the highest delay times.

The average time (in minutes) that it took from Dispatched to Cancelled for different Job Types, displayed by Cancelled Reason. Color also indicated the volume of cancels for each reason.

Transport job statistics. Data points in the view are:

Use to monitor the top cancel reasons for transport requests.
​

The average time (in minutes) that it took from when a job is requested to when the job is in progress. The line chart shows this by the Hour of Completed Timestamp.

Transport job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average Request to Inprogress time be less than 15 minutes.
​

The average time (in minutes) that it took from Pending to Dispatch Time. The line chart shows this by the Hour of Completed Timestamp. This is the time it takes from a pending transfer request until it is in progress.

Transport job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average Pending to Dispatch Job completion time of less than 5 minutes.
​

The average time (in minutes) to progress a task from Dispatch to Completed. The line chart shows the Hour of Completed Timestamp., which is the time it takes from when a task is dispatched until it is complete.

Transport job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average Dispatch to Completed be less than 20 minutes.
​

The average time (in minutes) to progress a task from Inprogress to Completed. The line chart shows the Hour of Completed Timestamp., which is the time it takes from when a task is dispatched[TL1] until it is complete.

Transport job statistics. Data points included in the view are:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average Time on Task be less than 10 minutes.
​

The average time (in minutes) that it took to complete a task from Pending to Completed Time. The line chart shows this by the Hour of Completed Timestamp. This is the time it takes from when a task is pending until it is complete.

Transport job statistics. These are the data points included:

Date Selector = 1

IF Date Type = “Today” THEN

IF Completed Timestamp = Today() THEN 1 ELSE 0 END

ELSEIF Date Type = “Custom Date” THEN

IF Completed Timestamp >= Start Date AND Completed Timestamp >= End Date THEN 1 ELSE 0 END

TeleTracking’s Best Practices recommend the average Time on Task be less than 30 minutes.

The Volume Analysis interactive report enables you to review summary information captured every hour by Capacity IQ®. This data shows the total number of admits, transfers, confirmed discharges, and other events that occurred during a specified timeframe. To see a list of all available fields in the Volume Analysis data source, please view the recently updated Data Sources tab.

More details are provided here. You must be authenticated via the platform url to access this confidential information.

You can subscribe to a dashboard to receive recurring updates on data from a particular view or entire workbook.

For example, if you wanted to review performance metrics every morning at 8am, you could create a custom email subscription which would forward the previous day's metrics to your inbox at the scheduled time.

Before setting up your subscription, ensure that your dashboard or report is set to the correct view.

Only interactive reports are available for subscription.

Once you've set up your subscription, you can manage it (and any other subscriptions based on the same workbook) from the Subscriptions tab in your workbook.

On certain dashboards, thresholds can be changed without having to create new custom calculations. This allows you to set thresholds such as Response Time or Clean Time to your own hospital's standards.

The following dashboards have adjustable parameter thresholds:

Interactive dashboards contain a text box that allows you to change a threshold by typing in a new metric. Once you change the default threshold metric, the visualization will automatically be updated.

The thresholds on a Command Center dashboard can be adjusted in Edit mode.

Once you return to the dashboard, any metrics affected by the threshold you've edited will adjust to present data based on your new threshold.

Dashboard tooltips can be customized to display only the information most relevant to your health system.

Creating a parameter in web allows users to filter between data sources that are not linked.

For instance, a single Campus parameter could be created that's used to drive the campus field for each of the data sources associated with that dashboard.

Once a parameter has been successfully created, you can create calculations that include the new parameter in each of the data sources you want to filter between.

The tables below outline the average load times for the standard content Interactive and Command Center dashboards available in Data IQ®.

BTJob is a Standard Lane data source showing Environmental Services data from Capacity IQ®. Each row in this data source shows an individual cleaning job. The unique identifier for this dataset is a combination of Instance_ID and Job_Id. This data source contains historical data and has a latency of ~45-90 minutes.

Care Progression Indicators is a Standard Lane data source that contains Care Progression Group information where there is at least one ordered Care Type. This data source also includes Patient Visit information associated with the Care Progression Group. The unique identifier for this dataset is a combination of Instance ID and Milestone_Entity_Id. This data source contains historical data and has a latency of 3 hours.

Care Progression Indicators Detail is a Standard Lane data source that contains Care Type information for each Ordered Care Progression Group. This data source also includes Patient Visit information associated with the Care Progression Group. Each row consists of Milestone_Entity_Detail_Id. This data source contains historical data and has a latency of 3 hours.

Case Physician CommunicationIQ Case is a Standard Lane data source that provides a historical perspective on physician communication records originating from Transfer IQ®. It encompasses timestamps of various communication events, including the initial contact, the initial response (when the call is returned), and the most recent timestamp associated with physician disposition (Cancelled, Consulted, Declined, Accepted, Admitting). Typically, each row corresponds to a single physician communication card, and multiple rows may exist in cases where communication cards for the physician were deleted. Currently, each row in this data set is uniquely identified by Case_Communication_Id. Prior to 2022, the unique identifier for this dataset is a combination Transfer_Id and Physician_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

Census Snapshot is a Standard Lane data source that contains hourly census data for each unit. All measures and dimensions relate to the unit. The unit must have a discipline other than 'None' in order to calculate any measures. Each row in this data set represents a snapshot of a given hour for an individual unit. Each row in this data set is uniquely identified by a combination of Instance ID and Statistic_Snapshot_Id. This data source contains historical data and has a latency of ~45-90 minutes.

Discharge Milestone is a Standard Lane data source that contains historical view of Discharge Milestones recorded, the times they are marked as delayed or completed, and any notes associated with them. Each row in this data set represents an individual discharge milestone for a patient record. The unique identifier for this dataset is a combination of Instance ID and Milestone_Entity_Detail_Id. This data source contains historical data and has a latency of 3 hours.

IQ Behavioral Health is a Standard Lane data source that contains historical details about behavioral health assessments recorded in Transfer IQ®. Each row in this data set represents a single assessment in a Transfer Center Case. A transfer center case may have more than one assessment associated with it. The unique identifier for this dataset is a combination of Behavioral_Id. This data source contains historical data and has a latency of ~45-90 minutes.

IQ Case is a Standard Lane data source that contains transfer case data. Each row in this data set represents an individual transfer center case. The unique identifier for this dataset is a combination of Transfer_Id. This data source contains historical data and has a latency of ~45-90 minutes.

IQ Case Escalation Communication is a Standard Lane data source that contains a historical view of escalation communication records from Transfer IQ®. It includes the times they are created, the initial contact recorded, when the call is initially returned (Initial Response), and the latest time an escalation disposition is recorded (cancelled, resolved, unresolved). Each row in this data source represents an individual escalation communication card. The unique identifier for this dataset is a combination of Transfer_Id and Staff_Id or Physician_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Escalation Communication Detail data source contains the detailed events occurring in escalation communications in each transfer center case. Each of the events in the communications history will be a unique row in this data set, including the times contacted, the times where the call is returned, and the times when any disposition is set on the communication record. The unique identifier for this dataset is Communication_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Facility Communication is a Standard Lane data source that provides a historical perspective on facility communication records originating from Transfer IQ®. It encompasses timestamps of various communication events, including the initial contact, the initial response (when the call is returned), and the most recent timestamp associated with facility disposition (Cancelled, Consulted, Accepted, Redirected and Declined). Each row corresponds to a single facility communication card, and multiple rows may exist in cases where communication cards for the facility were deleted. The unique identifier for this dataset is a combination of Facility_Id and Transfer_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

The IQ Case Facility Communication Detail is a Standard Lane data source that captures comprehensive communication events within a facility communication card for each transfer center case. Each event in the communication history is represented as a distinct row in this dataset. It provides timestamps for contact, when a call is returned, and when any disposition is applied to the facility communication record. The unique identifier for this dataset is Communication\_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Issue is a Standard Lane data source that contains issue data recorded in transfer cases. Each row in this data set represents an individual issue recorded for a transfer case. This data source includes deleted issues. The unique identifier for this data set is Issue_Id. This data source contains historical data and has a latency of ~45-90 minutes. This data source is joined against the IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Issue Note is a Standard Lane data source that contains notes recorded against issues in a transfer case. Each row in this data set represents a note recorded in an issue. This data source includes deleted notes. The unique identifier for this data set is Issue_Note_Id. This data source contains historical data and has a latency of ~45-90 minutes. This data source is joined against the IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Note is a Standard Lane data source that contains any notes recorded to a transfer center case. Each row represents individual case notes. The unique identifier for this dataset is Note_Id. This data source contains historical data and has a latency of ~45-90 minutes. This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

The IQ Case Physician Communication Detail data source contains the detailed events occurring in physician communications in each transfer center case. Each of the events in the communications history will be a unique row in this data set, including the times contacted, the times when the call is returned, the times conferenced, and the times when any disposition is set on the communication record. The unique identifier for this dataset is Communication_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

As pictured below, each history item recorded will be in this data source.

IQ Case Staff Communication is a Standard Lane data source that provides a historical perspective on staff communication records originating from Transfer IQ®. It encompasses timestamps of various communication events, including the initial contact, the initial response (when the call is returned), and the most recent timestamp associated with staff disposition (Cancelled, Declined, Accepted, and Consulted). Typically, each row corresponds to a single staff communication card, and multiple rows may exist in cases where communication cards for the staff member were deleted. The unique identifier for this dataset is Case_Communication\_Id. This data source contains historical data and has a latency of ~45-90 minutes.

This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Case Staff Communication Detail is a Standard Lane data source that captures comprehensive communication events with a staff member within each transfer center case. Each event in the communication history is represented as a distinct row in this dataset, providing timestamps for contact, when a call is returned, and when any disposition is applied to the staff communication record. The unique identifier for this dataset is Communication_Id. This data source contains historical data and has a latency of ~45-90 minutes. This data source is joined against IQ Case data source within Data IQ®. Data IQ® Warehouse Connector customers will need to perform this join within their queries.

IQ Enterprise structure is a Standard Lane data source that contains the Enterprise Structure configured in the IQ Enterprise Settings. Each row in this data set represents a facility and what hierarchy they are placed within the Enterprise Structure(Enterprise 1 is the top most level of the Enterprise Structure and Enterprise 26 is the lowest level). This data source excludes Deleted Facilities. The unique identifier for this data set is Facility_Id. This data source contains historical data, and has a latency of ~45-90 minutes. This data source in Data IQ® is joined against the IQ Case data source in three possible ways: Referring Facility, Destination Facility, Preferred Facility. Data Warehouse Connector customers will need to perform this join within their queries.

Location Action Status is a Standard Lane Data Source that contains bed location and status level information from Capacity IQ® for beds with EVS Service enabled. The granularity of this data source is at the Location Status Change Level for a given location – meaning each row represents a different status change for a bed and contains the start and end time for that status. If the status change was associated with a patient visit, then the patient visit and MRN information will be available. The unique identifier for this dataset is a combination of Instance ID, Source_Table and Source_table_primarykey_id. This data source has a latency of ~45-90 minutes.

For example, the image below shows the Actions on a two-bed location for two days. Each action has a Status Start Timestamp (when the action began) and a Status End Timestamp (when the status was removed). In the cases where there are 2 rows for an action (Dirty and Pending), both of those actions were started and completed at the same time.

The following image provides a visual example of the actions for a given location:

In this example, Bed 1 was occupied from Midnight until 4 PM, then it was set to a status of Pending/Dirty for about an hour. Then, the action status was briefly changed to action statuses of In Progress and Complete before being Clean for about 5 hours.

In the Blocked Beds standard content, users can see the currently blocked beds by looking at any location that has an Action of “Blocked” and a Status End Timestamp of “Null”. This means that the action has been set to “Blocked”, but that action has not been removed.

This same logic can be used to create a list of currently occupied patients. Any patient that has an Action of “Occupied” and a Status End Timestamp of “Null” are currently occupying a bed in the health system.

For any additional questions, please contact TeleTracking® Support.

Patient Placement is a Standard Lane data source that contains data related to Patient Placements. Each row in this data source represents an individual patient placement request (Preadmits and Pending Transfers). The unique identifier for this data set is a combination of Instance_ID and Placement_Id. This data source contains historical data, and has a latency of ~45-90 minutes.

Patient Visit is a Standard Lane data source that contains a historical view of patient visit records, the latest times they are admitted, marked as pending/confirmed discharge, and actually discharged. This data source also includes all the patient details dimensions. Each row in this data source represents an individual patient visit record on an instance of the Capacity IQ® solution. The unique identifier for this dataset is a combination of Instance_ID and Patient_Visit_Id. The Patient_Visit_Id is a different field from the Patient_Visit_Number. The Patient_Visit_Number is visible on the front end of the Capacity IQ® application, the Patient_Visit_Id is the unique identifier. This data source contains historical data and has a latency of ~45-90 minutes.

Transporter Employee Performance is a Standard Lane data source that contains data related to hourly metrics of each transporter. Each row in this data source contains metrics for a given transporter in a given hour of the day. Details about a transporter will only be available if the transporter was logged in during those hours. The unique identifier for this data set is a combination of Instance_ID, Enterprise_User_ID, Start_Date and Hour. This data source contains historical data and has a latency of 3 hours.

Transport Tracking is a Standard Lane data source which contains a historical view of metrics related to physical patient moves done by Transporters within the Capacity IQ® application. Each row in this data source represents an individual transport job. This includes both patient and item jobs. The unique identifier for this dataset is a combination of Instance_ID and TT_Job_Id. This data source contains historical data and has a latency of ~45-90 minutes.

Volume Analysis is a Standard Lane data source that contains hourly volume data for each unit. The number of admits, discharges, transfers and more are available in this data source. All measures and dimensions relate to the unit. Each row in this data set represents a snapshot of a given hour for an individual unit. The unique identifier for this dataset is a combination of Instance_ID and Statistics_Cumulative_Id. This data source contains historical data and has a latency of ~45-90 minutes.

For more detailed information, go to Data Points – Historical.

Census Current is a Fast lane data source showing unit level Census data from Capacity IQ®. Each row in this data source contains the current census metrics. This data source has a latency of ~5-15 minutes.

Current Bed Status is a Fast lane data source showing the latest location status in Capacity IQ®. Each row in this data source is at the bed level and shows the latest bed status for that location. This data source has a latency of ~5-15 minutes.

The Current BedTracking Employee Status data source is a fast lane data source. Each row of this data source shows the latest status of each EVS employee. There is one row per employee. This data source has a latency of 5-15 minutes. This data source should only be used with Capacity IQ® or Capacity Management Suite® version 2021.1 or earlier.

The Current Care Progression Indicators Detail is a Fast Lane data source that contains Care Type information for each Ordered Care Progression Group. This data source also includes Patient Visit information associated with the Care Progression Group. Each row consists of Milestone_Entity_Detail_Id. The fast lane data source retains records where the patient's discharge date time is less than 72 hours, and patients who are in the Current Patient Visit (fast lane data source). This data source is subject to a latency period ranging from 5-15 minutes.

The Current Discharge Milestones data source includes discharge milestones for active patients as well as milestones that have been updated within the last 72 hours. Each row in this data set represents an individual discharge milestone for a patient record. This data source has a latency of 5-15 minutes.

Current IQ Case is a Fast Lane data source that contains transfer case data. Each row in this data set represents latest record for a transfer center case and retains all the cases where the Case Complete Timestamp is within the last 72 hours or is null. This data source has a latency of ~5-15 minutes.

Current Patient Attributes is a Fast lane data source showing the start and end times for the Patient Attributes associated with the patients from Capacity IQ®. Each row in this data source contains the start and end times for a given attribute for a given patient. This data source retains records for all patients in the Current Patient Visit data source. The Current Patient Visit data source includes all current patient visit records (in house, preadmit, pending transfer, pending discharge, confirmed discharge) and those in a discharged and cancelled status for the last 72 hours based on the latest last mod date. This data source has a latency of ~5-15 minutes.

Current Patient Placement is a Fast lane data source showing placements data from Capacity IQ®. Each row in this data source contains an individual placement record. This data source excludes requested (but not activated), completed and cancelled placements older than 72 hours based on bed request timestamp. This data source has a latency of ~5-15 minutes.

Current Patient Visit is a fast lane data source that contains current patient visit records, the latest times they are admitted, marked as pending/confirmed discharge, and actually discharged. This data source also includes all the patient details dimensions. This data source has a latency of 5-15 minutes. The fast lane data source retains discharged and visit cancelled records for the last 72 hours based on the latest last mod date. The date limitation does not apply to records that are in confirmed discharge, In house, Pending Discharge, Pending Transfer, or PreAdmit Status.

Current Transfer Milestones is a Fast Lane data source that includes transfer milestones that have an active record in the Current Patient Placement data source. The Current Patient Placement data source includes all current patient placement records. The Current Patient Placement data source excludes requested (but not activated), completed and cancelled placements older than 72 hours based on bed request timestamp. Each row in this data set represents an individual transfer milestone for a patient placement record. This data source has a latency of ~5-15 minutes.

Current TransportTracking is a Fast lane data source. It contains active Capacity IQ® jobs, as well as those jobs last modified within the last 72 hours. This data source has a latency of 5-15 minutes. Each row of this data source represents an individual transport job. This includes both patient and item jobs.

The Current TransportTracking Employee Status data source is a fast lane data source. Each row of this data source shows the latest status of each Capacity IQ® employee. There is one row per employee. This data source has a latency of 5-15 minutes. This data source should only be used with Capacity IQ® or Capacity Management Suite® version 2021.1 or earlier.

The EVS Streaming data source is a Fast lane data source showing Environmental Services data from Capacity IQ®. This data source has a latency of ~5-15 minutes. Each row in this data source shows an individual cleaning job. Bed cleaning jobs that were updated within the last 72 hours.

For more detailed information, go to Data Points – Fast Lane.

Data source extracts are a way to store data within the Tableau Server, instead of within Snowflake, to allow for significantly faster content load times.

We are implementing data source extracts into Data IQ® for standard lane throughput data

This will allow interactive throughput reports using a Data Source Extract to open up to 15x faster.

In testing the majority of historical throughput dashboards open within 3-7 seconds

This is significantly faster than previous live connection load times.

Using multiple data sources, blending, or poorly designed dashboards can result in longer load times.

We implemented Data Source Extracts to all customers in mid-January 2024.

Previously our interactive throughput reports that pull historical data would have load times between 30 seconds and 1 minute.

Using data source extracts the dashboards will load significantly faster.

Example:

The extracts will be updated at 2AM each night and include data from the last 2 years (730 days) through the entirety of the previous day.

Extracts will not be updated more than once per day.

The refresh time will be managed on a customer-by-customer level depending on the number of time zones spanned.

Extract will be based off of tenant time zone.

In testing, we found that the vast majority of use cases for historical data were within the last year with a much smaller amount being within the last two years. Use cases beyond two years were seen to be exceptionally rare. As we need to be cognizant of data storage and Data Source Extract refresh time we decided to limit these to two years.

In this case you will need to edit your dashboard and replace the Data Source Extract connection with the new standard lane connection that contains ‘FULL_HISTORICAL’ in the data source name.

If you only need data for the current day, it is recommended you use our Fast Lane data sources.

We are not changing anything with the existing fast lane connections.

This data will not be changed and will continue to operate how they currently do.

Fast Lane

Historical Extracts

Standard Lane Full Historical

Fast Lane - “What’s happening right now.”

Historical Extracts - “How have we been trending over the last 2 years?”

Standard Lane Full Historical - “How much have we improved since 2016?”

This diagram shows what data is retained and the refresh rate of each type of data source.

This table shows each ‘lane’ of data available for our data sources.

You can export data from your dashboards using tabular reports. Tabular reports present the data points and metrics you see on an interactive dashboard in a table format.

Currently, tabular reports are available for the following dashboards:

From a report, you can edit your view of the data by including or excluding specific objects. To do so, click on a data point and hover over it:

With the dialog that appears, you can:

You can also filter your report using the filter panel:

The availability of filters and the option to edit the view of your data varies between reports.

Ask Data is a feature that utilizes natural language processing to let users ask data questions and in response, Data IQ® will create a basic visualization to answer the question.

In this example, we'll be asking the question: "what is overall turn time by campus?".

A visualization will automatically be created to satisfy your request. You can also use the drop-down in the upper right-hand corner to change the type of visualization displayed.

This feature allows users to discover potential reasons for why certain data points are higher or lower than expected. For instance, if Average Response Time is higher than usual on a given day you could use the Explain Data feature to learn potential reasons for the increase in response time.

The information provided in the Explain Data window will offer potential explanations as to why certain data points are higher or lower than expected using AI-driven insights.

The date format of datetime and date fields within Data IQ® are displayed based off of your browser's language setting.

At a high level the US uses the MM-DD-YYYY format, while most other countries use DD-MM-YYYY.

In this example, MAX(Createddate) is used to display the date formatting.

If the browser language is set to 'English (United States)' the date format will appear similar to the image below.

To transform date records into the more widely used international format the browser language should be set to a non-US option. By choosing 'English (United Kingdom)' , the date format will appear similar to the image below, where the date is displayed as DD-MM-YYYY.

To edit these settings in Chrome, follow the steps below:

Every data source in the Data IQ® contains the parameters necessary to add a refresh timer to a report. The timer will automatically update your data source every 60 seconds.

Once the workbook is published, the refresh timer will appear on your server and update your connected data source every 60 seconds.

The refresh timer uses parameters that you can customize to modify the default auto-refresh settings. Using any of the values below to edit the timer's behavior without editing the server's JavaScript files.

To edit a parameter, select a value from the drop-down below and create a parameter in Data IQ®. Name the parameter after the value you want to change (e.g. autoRefresh_seconds) and save it to apply your preferred settings.

The Data IQ® Warehouse Connector is a feature of the Data IQ® product and cannot be purchased as a stand-alone solution. It serves as a gateway for customers to access historical information that is warehoused in a TeleTracking data repository for reporting and analytics. The benefit of this solution is to give customers the ability to extract patient logistics information using industry-standard languages (ODBC and JDBC) and integrate it with other data from various other sources (clinical, financial, etc.) that are beyond the solutions provided by TeleTracking.

Data IQ® Warehouse Connector allows historical access to all Data Points labeled as Standard Lane. Details on those Data Points are available here.

The Data IQ® Warehouse Connector feature of the Data IQ® product requires the customer to provide the technical staff to take advantage of the available capabilities. This section defines the responsibilities of TeleTracking and the responsibilities of the customer.

If your company signed a contract for Data IQ® prior to December 2021, you will need a contract addendum to access the Data IQ® Warehouse Connector feature. Please coordinate with your Customer Representative for additional information.

The Data IQ® Warehouse Connector is designed to allow customers to extract data directly from the Snowflake database via a standard query language (ODBC/JDBC).

Chronic abuse of the utilization of the Data Warehouse Connector can result in permanent disabling of the account(s).

When you confirm that your organization has the resources required to use Data Warehouse Connector, contact your TeleTracking Commercial Representative. They can make sure that the following issues are addressed:

When you have completed the prerequisite requirements, use the following section to proceed with the Data IQ® Warehouse Connector setup.

Operating Systems supported from Snowflake are found on their requirements page, minimum and recommended client versions, and Snowflake support policies.

Detailed instructions for installing, configuring, and using the Snowflake-provided drivers and connectors for JDBC, ODBC, Python, Spark, Go, and other clients are available on their drivers page.