Healthcare Software Development

We build healthcare software applications that integrate with the EHR systems to improve clinical workflows.

The IoT system integrators at LeewayHertz integrate the existing healthcare application with IoT to drive patient outcomes on a digitally connected healthcare technology solution.

With our healthcare software development, maintenance planners and equipment operators gets comprehensive insight into asset risk and enable them to maintain higher levels of asset availability.

• Track, benchmark, and rank performance
• Enable asset-level diagnostics and projections

The Sensor Health Detection software determines the Optimal Deployment and Operational Health of IoT Sensor Devices.

• Sensor deployment
• Sensor device reconciliation
• Reporting and ad hoc analysis

We build patient engagemnet solutions to communicate with patients, provide educational resources, or manage the patient-provider relationship.

By integrating Telemedicine Software with the EHS, medical software development companies are improving the clinical workflows.

We build medical inventory applications that order, track, and maintain medical equipment, Control stock levels, manage locations, and monitor expiry dates with ease.

We consult and develop the enterprises across the technologies and delivery models for:

• Clinical applications
• Medical imaging solutions
• Cloud applications
• BI/ analytics solutions
• Patient portals and consumer/ mobile applications

We aim to reduce the readmission costs of hospitals and enable efficient use of scarce hospital resources while enhancing the quality of patient care with AI, IoT implemented smart digital software.

With our AI and IoT expertise, we develop predictive models to identify and prioritize fraudulent activity, enabling customer satisfaction and efficient deployment of hospital resources.

With AI Predictive model integrated software, doctors will receive alerts about patient’s sensitive environmental conditions and suggests respective tests and diagnoses.

Automated Machine Learning enabled software are giving predictions about patient’s needs around intensive care, allocation of staff, which is saving costs for hospitals.

Healthcare providers and payors are integrating patient retention risks into their workflow, by reducing non-renewals with the potential of AI and ML and reducing operational costs.

AI is providing models to identify people who do not adhere to prescribed medication and to predict their behavior. It helps create the right plan to increase medication adherence.

No-show appointments are not only expensive for payers and providers, but also patients because not showing up for a medical appointment can result in adverse health conditions and untreated medical conditions. AI can help reduce these no-shows by equipping decision-makers with the information they require for rescheduling, engaging patients proactively and crafting interventions. 

The length of stay significantly predicts the cost. Staying for long not only places patients at risk of hospital-acquired conditions, but it also constrains physician time and hospital bed availability. AI technology can help payers and providers predict the length of stay, creating scheduling flexibility, enabling targeted interventions for patients at risks and reducing costs.