Healthcare Software Development

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

We integrate IoT with healthcare application to drive patient outcomes on a digitally connected healthcare technology solution.

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

With integrate Telemedicine Software with the EHS to improve 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

Patient readmissions result in additional costs for payers, patients and hospitals. AI implementation will help predict and reduce hospital readmissions and enable efficient use of scarce hospital resources while enhancing the quality of care.

Fraudulent claims are costly for every organization and it is inefficient for healthcare institutes to investigate every claim. Our AI engineers help organizations develop accurate predictive models to identify and prioritize fraudulent activity, enabling customer satisfaction and efficient deployment of resources. 

Many patients are sensitive to bloodstream infections during their stay in the hospital. It is an expensive outcome that can result in hospital readmissions. AI technology can help predict which patients are likely to incur CLABSI and sepsis and send alerts to doctors automatically for executing further testing and diagnostics. 

Periodic scarcity of care resources and high costs are two significant reasons why the utilization of ICU should be improved. Automated Machine Learning allows predicting accurately which patients need and don’t need intensive care, saving costs for hospitals. It also helps in understanding the staffing needs for ICU and ED.  

Healthcare providers and payers lose money if members decline to renew their health plan or if patients do not avail of their facilities again. They can leverage the potential of AI and ML to integrate patient retention risks into their workflow, reducing non-renewals and patients not availing further treatments.

People with chronic diseases who do not take their medications regularly lead to over $100 billion in preventable costs every year. Using AI, you can create 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.