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Description
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EHR integrations
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Jump to:
Categories
Solutions
Description
Compatibility Level
Clients
Product Capabilities
Use cases
EHR integrations
Client types
Awards
Differentiators
Health equity
Keywords
Media
Company details
HIM Indexing Bot
HIM Indexing Bot

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Sickbay
Sickbay

Categories

Solutions

Description

Product Description:

Regardless of the document format and structure, using Intelligent Document Processing, the CampTek HIM Indexing Bot can contextualize the data and input into any application

Some examples:

Standardized Systems this works with (add links):  

Epic 

OnBase 

Cerner (Oracle) 

eCW 

Siemens 

Availity 

Evicore 

Magellan 

UHC 

Cigna 

Any Payor with a Portal and/or API Capability 

Any EMR/HER, both large and small. 

About CampTek Software:

CampTek Software is a Full-Life-Cycle Intelligent Automation SaaS Provider with proven results implementing and supporting automation solutions through our successful methodology. Our unique hosted model offers many powerful advantages including a shorter time to market, 24/7 support and overall lower cost of entry. Our approach is simple and repeatable.

CampTek will be with you on every step of your RPA & AI Journey!

Product Description:
Sickbay is an FDA-cleared clinical platform providing hospitals with the only vendor-neutral, integrated patient monitoring solution in healthcare. Sickbay consolidates disparate sourced, time-sequenced patient monitoring data with an average of 25 milliseconds per patient. Sickbay drives cost-effective patient monitoring and powers analytics by providing instantaneous and persisted physiological data to clinicians, researchers, and algorithm developers. Viewing data consolidated in Sickbay on any laptop or mobile device, on wallboards, and in on-prem or remote command centers enables clinicians to deliver the best possible care to patients throughout the hospital.
About Medical Informatics Corp:

Medical Informatics Corp.’s (MIC) mission is to deliver next-generation technologies to unify patient monitoring workflows for healthcare systems. MIC’s decade of innovation with its clinical platform, Sickbay, integrates over 30,000 vendor-neutral signals on two percent of hospital beds with over 10,000 clinical users in the United States. Most hospital systems lack native resolution data aggregated through a single source, instead deploying a multi-device strategy that silos data and data access time frames. The Sickbay Clinical Platform stands alone as the only FDA-cleared platform to aggregate time-series waveform data across disparate devices at native resolution. Current bedside devices delete data on average after 72 hours, while Sickbay saves the data indefinitely. Sickbay provides a portal through which care providers can review aggregated, time-synchronized data, annotate it, and collaborate to create algorithms (including ML & AI) and evaluate post-event care. Those algorithms and care models can then be reintroduced into the platform to advance care and innovation. Simply put, Sickbay provides the hospital teams their data from anywhere, anytime, to optimize workflows, analysis, and risk stratification across the patient care spectrum. The diverse team at MIC is fundamentally unlocking a blue ocean of new patient monitoring capabilities for ourselves, our partners, and our clients. MIC’s Sickbay saves lives, improves outcomes, streamlines strategy and technologies, and reduces the overall caring cost for hospital patients nationwide.

Compatibility level

Select which hospital or health system you work at and see a personalized compatibility level.

Clients

Select which hospital or health system you work at and see the client list

Product Capabilities

Sickbay collects, integrates, & displays time-aligned medical device data for over 30k signals. Information is displayed to end users in near real-time (~25ms) on local and mobile devices.

Sickbay's Patient Monitor (PatMon) displays per patient waveform and EHR data alerting clinical end users based on parameters defined by the hospital. Sickbay's Multiple Patient Monitor (MultiMon) displays that same information for up to 100 patients on a single screen to support virtual monitoring at scale. Sickbay's Risk Stratification module displays risk score data customized per hospital to improve awareness of patient risk in higher acuity beds. Sickbay's Alert Queue module displays alerts for telemetry patients that have been newly admitted, shift changes, dietary requirements, and rhythm validation.

Sickbay integrates EHRs using interfaces for ADT information, staffing assignments, meds, & labs. Sickbay integrates directly into the EHR to automate the capture and storage of ECG strips on the patient's record without additional, time-consuming, error-prone manual steps.

Sickbay simplifies the clinical theater by centralizing patient monitoring data from devices, EHRs, camera-enabled technology, and 3rd party analytics into a single screen. This enhances the readability and interpretation required to reduce the time-to-treat a deteriorating patient. Sickbay's interface is shared between bedside and remote care teams to drive scale and efficiency. This approach reduces the risk associated with new nursing team members on staff and improves the training / onboarding by using a single platform for patient monitoring. Sickbay's analytics workbench directly connects clinical researchers with bedside teams to develop and implement custom algorithms for specific patient cohorts in near real-time.

Sickbay integrates camera-enabled technology into a single interface alongside near real-time physiological data to provide remote care teams with video support to reduce patient risk and improve the time-to-treat for patients that are deteriorating.

Use Cases

Description:

Provider Systems: Epic

Payer Portals: OnBase, Epic

Challenge:

A large Mid-West Healthcare provider with fifteen hospitals across two states had a large document processing problem: importing Patient Consent Forms into OnBase. This is generally not an issue for most DU (Document Understanding) tools because most of the data is structured. In this case these particular documents included a stamp or label of patient demographics added by hand and placed on the document with both structured and unstructured data. This information on these labels then needed to be read and indexed into Epic. The challenge was that these labels were being placed on the documents by clinicians and in most cases were not always positioned in a way that was effectively “read” by most DU tools.

Solution:

As a trusted adviser to the client, CampTek Software brought in several DU vendors to perform a proof of concept for the provider so they could evaluate the ability of several tools to effectively read the skewed labels. Document Understanding solutions such as ABBYY, UiPath and Indico were among those reviewed.

Each product was given a sample set of documents as part of a proof of concept. From there, CampTek would analyze the ability and percentage results to present back to the client. The findings were overwhelmingly positive for Indico. Even upside down, the labels could be read immediately. For others, the test proved that if the label was more than 10% out of alignment, they had poor results. Indico immediately showed a 90% accuracy result. Indico also did not require the use of templates, like some of the other tools did.

The findings were presented to the customer and within a short time the project was approved. Also, it was stated by the project lead that once this first project was implemented, there will be additional opportunities for expansion of the Indico/CampTek managed services solution. For example, the ability to pull data and documents from Legacy systems like CPSI and replacing expensive point solutions like Edco Solarity as next projects.

  • 7.4m documents first year requirements
  • Hospital 1: 600/hour average (Tuesdays are the heaviest day week).
  • Hospital 2: 320/hour (Tuesdays are the heaviest day week). 500-400 documents per hour per process (4 processes)
  • Average file size, twenty pages or less
Pediatric use cases:

None provided

Users:

Any Healthcare provider

Description:
  • Patient Monitoring
  • Remote Patient Monitoring
  • Virtual Care Models: Virtual Nursing, Central Telemetry Monitoring
  • Rounding
  • Vent Management
  • Patient Risk Stratification
  • Interdepartmental Transfers
  • Automation: ECG Strip Automation, Data Management
  • Revenue: CDI, Denials Management
  • Analytics: Compliance, Billing, Cohort Management
  • Research: Algorithm Development
  • Legal: Litigation Support
Pediatric use cases:

Same as use case descriptions above.

Users:
  • Nurses
  • Respiratory Therapists
  • Doctors
  • Anesthesioligists
  • Surgeons
  • CDI
  • Revenue Cycle
  • Research
  • Analytics
  • Quality
  • Compliance
  • Legal

EHR Integrations

Integrations:

Acute care EMR, Ambulatory EMR, Ancillary EMR, ERP system, Patient portal, Pop health platform, Home health, Behavioral health, Community based organizations, ADT, Access +/or revenue cycle, Credentialing, Website / public online sources, Other

EMR Integration & Relevant Hardware:

None provided

EMRs Supported:

Epic, Cerner, Meditech, Allscripts, NextGen, athena, GE, eClinicalWorks, McKesson, Other, Allscripts/Eclipsys, Athenahealth, Azalea Health/Prognosis, CPSI, Evident, Healthland, MEDHOST, MedWorx, QuadraMed, Self-developed, Would prefer not to disclose, Point Click Care

Hardware Compatibility:

None provided

Integrations:

Acute care EMR, ADT, Access +/or revenue cycle, Other

EMR Integration & Relevant Hardware:

Required

EMRs Supported:

Epic, Cerner, Allscripts

Hardware Compatibility:

Desktop, Mobile / Tablet (web optimized), Other

Client Types

None provided

Awards

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Differentiators

Differentiators vs EHR Functionality:

We offer Intelligent Automation as a Managed Service and have successfully built automations for every major EHR.

Differentiators vs Competitors:

We not only focus on development but also full support of bots once they are in production. Each bot has its own custom dashboard view so that our customers are continuously informed of its daily trransaction metrics and KPIs.

Differentiators vs EHR Functionality:

The EHR is intended to be a point of care reference to support billing. Traditionally, only documenting discreet vitals from patient monitoring devices at single points.

Sickbay Clinical Platform:

  • captures consolidated, persistent, time-series waveform data from networked and non-networked bedside devices at its native resolution
  • re-displays near real-time, time aligned signals at an average latency of <25 mSec
  • integration of risk scores and analytics
Differentiators vs Competitors:

Sickbay is a single, interconnected platform that is designed to support dozens of use cases, therefore competition is dependent upon the use case. In addition to the data agggregation, consolidation, and visualilzation differences referenced under EHR functionality, key differentiators in patient monitoring & virtual care include: 

  • vendor neutral device integration
  • web-based to support monitoring on any PC, tablet, phone or embedded EHR workflow
  • flexible, modular design to enable ability to monitor 50+ patients across units, facilities, and vendors
  • unlimited retrospective data, from one second to one year+, to support building and sharing of trends, CDI documentation support, quality reporting
  • integration, development and deployment of near real-time risk scores and analytics into established workflows
  • automated documentation of vitals, ECG strips, and event trends into the EHR

Health Equity

Keywords

Images

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CampTek Methodology.jpg

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Sickbay on Multiple Devices

Videos

1 of 4

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Podcast: The Importance of Managed Services

No videos provided

Downloads

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HIM-dex Case Study.pdf
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Use Case: Comprehensive Case Review

Alternatives

Company Details

Founded in 2018

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