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In-House Health

Company Overview

In-House Health is a healthcare technology company focused on developing AI-driven scheduling and management solutions for nursing teams. Founded to address challenges in hospital nurse employment, In-House aims to help hospitals become the employer of choice for nurses again by providing modern, transformative technology.

The company was founded by Ari Brenner (CEO), Sergey Vasilenko (CNO), and Shachar Har Zvi (VP of Engineering). Their mission is to “restore sustainability to nursing by providing modern, transformative technology.”

In-House Health is headquartered in Denver, Colorado, with a hybrid work model. They also have a presence in Tel Aviv, Israel.

Products Overview

In-House Health’s core product is an AI-powered predictive scheduling and management platform for nursing teams. Key features include:

  1. Predictive Insights: An AI algorithm that predicts shift-level staffing requirements 1-3 weeks in advance. It uses a proprietary Workload Score that factors in patient-specific work requirements and adjusts unit predictions based on average patient status per shift.

  2. Recommendation Engine: Combines predictive census and current staffing in a summary dashboard. It can suggest automatic updates via AI while allowing manual overrides.

  3. Team Management: Tracks nurse preferences, experience by unit, training, and certifications. It automatically reflects these in schedule recommendations.

  4. Mobile App: Allows pushing out swaps, adds, and other requests via mobile app or text message.

The platform aims to save nurse managers time, reduce labor costs, and improve shift efficiency. In-House claims their system can save nurse managers 5+ hours per week and save hospitals over 10% in labor costs (about $800K for an average single facility).

Founding Team

  1. Ari Brenner - Founder & CEO Previously founded Stellar Health, a digital health unicorn.

  2. Sergey Vasilenko - Founder & CNO

  3. Shachar Har Zvi - Founder & VP of Engineering

The founding team brings experience from companies like Stellar Health, McKinsey & Company, and others in the healthcare and technology sectors.

Problem and Market Fit

In-House Health addresses several key challenges in hospital nurse employment:

  1. Nurses wanting more control and flexibility in their schedules
  2. Hospitals struggling to shift from traditional full-time workforce models
  3. Increased use of agencies to fill staffing gaps, leading to margin pressure
  4. Manual, time-consuming scheduling processes for nurse managers

The company’s AI-driven platform aims to solve these issues by providing more efficient, flexible, and data-driven scheduling solutions tailored to both hospital and nurse needs.

Business Model

In-House Health operates a B2B model, selling their software platform to hospitals and healthcare systems. They likely use a subscription-based pricing model, common in enterprise software, though specific pricing details are not provided.

Funding and Runway

The company has raised at least $4 million in funding, as reported in a July 2023 article. No information about their current runway is provided in the available material.

Competitive Landscape

While specific competitors are not mentioned, In-House Health operates in the healthcare workforce management and scheduling software market. This space likely includes both legacy healthcare IT providers and other startups focusing on nurse scheduling and management solutions.

Customers

No specific customers are mentioned in the provided material. However, the company targets hospitals and healthcare systems as their primary customers.

Relevant News

  1. July 23, 2023: In-House Health raised $4 million to build out their AI-enabled scheduling platform for nursing teams.

  2. July 26, 2024: The company published a blog post discussing new inter-facility float (IFF) programs being implemented by hospitals to combat nurse shortages and burnout. This highlights In-House Health’s ongoing engagement with emerging trends in nurse staffing and management.

Classification: AI Tier 2

  1. Core AI: Create fundamental AI technologies/base models
  2. AI-Enabled: Core offerings rely on recent AI advances
  3. AI Adopters: Use AI to enhance existing products/services
  4. Non-AI: No AI in products/services

In-House Health’s main product depends on AI-powered predictive and management features, classifying it as Tier 2 - AI-Enabled.