Data Analytics Development

Tired of your healthcare data just sitting there, collecting dust?

Data is useless if it doesn't help improve patient care

Data isn’t just about numbers—it’s about improving patient care and making smarter decisions in healthcare. You have patient records, treatment plans, and lab results—valuable data. But is it helping you make better decisions, spot risks, or improvise care?

Codewave makes all of that possible. We use AWS Cloud and real-time data pipelines to connect your systems and provide instant access to critical information. Natural Language Processing (NLP) tools convert unstructured data, like doctor’s notes, into insights that improve diagnoses and care decisions.

We also apply predictive analytics to spot risks early, helping you act faster and prevent complications. These AI-driven insights optimize resources, reduce inefficiencies, and ultimately improve patient outcomes.

With Codewave’s Data strategy intervention, you achieve

100%

Realtime monitoring

3X

Faster data processing

~3 Weeks

Time saved per month in manual work

25%

Reduction in operational costs

Why you'll love us?

We’re 10x thinkers and change makers, driving extreme-value innovation through human-centric design and emerging tech, defying the traditional. With a track record of serving 300+ businesses globally, collaborating with VC firms, startups, SMEs, and governments, while also developing our own GenAI products – we’re obsessed with building high-impact products, ready for scale.

Healthcare Deep Data Analytics

We help you make sense of your healthcare data. Here’s how we can help:

Custom Analytics

Know what data is worth tracking, and track it clearly with custom dashboards. For instance, Tableau visualizes recovery rates after surgery, showing clear trends. Power BI tracks daily ER patient volume with interactive reports, giving you actionable insights at a glance.

AWS QuickSight will make data quickly accessible–for tracking bed availability during peak hours or monitoring ICU occupancy trends. Python processes data fast, and SQL ensures accurate insights so you can make informed decisions instantly.

Patient Journey Mapping

Visualize patient journeys from discovery to onboarding to active ongoing engagement. Understand highs and lows on the patient journey, transform touchpoints to maximize value and delight. Microsoft Visio helps visualize each step, from appointment booking to follow-ups. For example, you can pinpoint exactly where delays happen—maybe it’s in the waiting room or during post-care instructions.

Smaply integrates EHR data to map the patient experience. Python and R help you spot issues, like delays in prescription delivery, and suggest improvements for better care and satisfaction.

Operational Efficiency

Spot inefficiencies on the patient journeys and fix them. AI-powered Workforce Management Software helps you adjust staffing in real time based on patient needs. Tableau and Power BI provide live data on staff performance, patient flow, and costs so you can act fast and make operations run smoother.

For example, if patient onboarding is slow, use data from your EHRs and CRMs to see where the delays happen. With UiPath, processes such as patient check-ins and discharge are automated.

Cloud Integration

Get all your data in one place. Integrate your EHR, lab, and patient management systems onto a cloud platform like AWS or Microsoft Azure. Set up real-time data pipelines with Apache Kafka and AWS Lambda so departments can access patient data instantly.

For example, a doctor in the ER can pull up lab results while talking to a patient, speeding up decisions and improving care.

Data Vision & Strategy

Bring all your scattered data together from multiple platforms. We use Azure Synapse and AWS to integrate your systems and create a central hub for data–turn that data into “value” that helps you make smarter decisions.

For example, AI-driven predictive models can be used to forecast patient needs and allocate resources where they’re needed most. This strategy helps reduce waste, improve care, and keep operations running flawlessly.

AI/ML Powered Insights

Get deeper insights from your healthcare data. TensorFlow and Azure Machine Learning analyze patient information to predict outcomes, such as spotting patients at high risk for readmission. This helps doctors act fast with the right treatment.

For example, AI can flag early signs of complications, giving doctors a head start on care. This lets you make decisions quickly, improving care while cutting down on errors.

Data ROI

Make the most of your data. Store it securely with AWS, and manage it easily with Kubernetes for smooth, automated handling. Apache Spark and Python tools are useful to process large amounts of data quickly.

Tableau and Power BI turn that data into clear, visual reports you can use to simplify decision-making. For example, AI can predict patient volume for the coming days, helping you adjust staffing levels before a rush hits.

Embedded Technology Innovation

Get real time data from connected devices and turn data into insights that give you a strategic advantage over your competitors. Raspberry Pi connects devices affordably while sensors track usage in real-time. For instance, real-time monitoring of ventilators helps healthcare teams respond quickly when needed.

Bluetooth LE ensures smooth communication between devices, making workflows quicker and more efficient. This tech directly embeds insights into operations, improving care and resource management.

Predictive Healthcare Modeling

Predictive tools like decision trees and regression analysis analyze past patient data to identify trends. For example, track a patient's history of respiratory issues and forecast when they might need intensive care due to declining lung function.

AWS SageMaker automates this process, enabling real-time predictions that help allocate resources proactively, reducing the risk of emergencies. This leads to faster and fewer crises and more efficient use of healthcare resources.

IoT Solutions

AWS IoT Core connects medical devices to a centralized system, providing real-time data. For instance, if a patient's heart rate spikes on a monitor, an automatic alert is sent to the medical team, allowing them to respond immediately.

Simultaneously, EMR integration ensures patient data is updated in real-time, so doctors have the latest information. This reduces delays in treatment, prevents errors, and improves overall patient care by enabling faster, data-driven decisions.

Looking to improve how you use your data?
Our Data Strategy Consulting simplifies the process and helps you see better insights. Find out how we can assist!

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Why Codewave, for Data Analytics Development?

Codewave's Analytics Approach: Enhance Patient Care

At Codewave, we take a patient centric approach to Data. Here’s what we do:

Data Collection

All healthcare data—ranging from patient records to medical device data—are gathered in one system. This removes the need to navigate between multiple platforms and gives a comprehensive view of the information at hand.

Data Integration

Patient records, test results, and operational data are automatically synchronized. This ensures all data is up-to-date, accurate, and ready for immediate use, eliminating the risk of missing or incorrect information.

Data Organization

Raw data is cleaned, structured, and organized for easy analysis. This step ensures that key metrics, such as patient recovery and resource usage, are clearly defined, so decisions are based on consistent, reliable data.

Predictive Analysis

Historical and real-time data are analyzed to identify potential trends and risks. Predictions about patient outcomes or resource needs are made, enabling proactive actions that prevent issues before they arise.

Continuous Monitoring

Patient data is continuously monitored to detect changes. Alerts are triggered when significant shifts in health conditions or equipment performance are detected, allowing for immediate response to prevent complications.

Actionable Insights

Complex data is transformed into clear insights, such as patient progress or hospital efficiency metrics. These insights enable quick, well-informed decisions that improve care and operations.

Your data should work for you, not the other way around.
Our Data Strategy Consulting helps you align your analytics with your business goals! Let’s talk about your data challenges!

Codewave: Success Stories in Healthcare Analytics

Over the years, we have partnered with global VC firms, governments, startups, and SMEs to build scalable digital businesses.

In healthcare analytics, the focus is on using data to improve patient outcomes using advanced analytics and machine learning–make data-driven decisions that lead to better care.

Here are some of our impactful projects in healthcare:

Twin Health: Generating More Leads

Twin Health needed a way to connect with diabetes patients and doctors in India. Our user-friendly website with CRM integration helped increase patient inquiries and made it easier for people to find the right care.

M Square: Automating Critical Reports

M Square uses GenAI to generate morbidity and mortality (M&M) reports in minutes which otherwise would take days. We simplified the report generation for doctors helping them focus better on patient care and reduce time spent on administrative tasks.

HaploCare: Building a Supportive Community

HaploCare creates a safe space for women to talk about their mental health and depression issues, before, during and after pregnancy. We developed an app with appointment booking, video consultations, and a social feed, offering a blend of expert help and community support for users.

InstaLife: Bringing Medical Diagnosis Home

InstaLife wanted to help busy users manage their health from home. We built a platform for booking lab tests, setting reminders, and receiving personalized health insights, making it easier for users to stay on top of their wellness, from the convenience of their homes.

Nexus Ventures: Investment ROI Tracking

Nexus needed a better way to manage financial data for healthcare portfolios. We created an app to track investments, valuations, and transactions, making reporting faster and more accurate for investors and decision-makers.

Driving Real Business Impact

Machine learning and AI technologies provide ongoing, refined insights that help optimize resource use, reduce readmissions, and improve patient outcomes. Over time, these models get smarter, continuously supporting better decision-making and operational efficiency.

What to expect

What to expect working with us.

Tired of stagnation?

It doesn’t take much to get unstuck. Codewave isn’t just a software development company – we’re your design thinking partner to drive innovation and growth.

Frequently asked questions

.01 /What makes Codewave's healthcare solutions stand out?

At Codewave, we combine design thinking with advanced tech to create user-friendly healthcare analytics. By focusing on the needs of both healthcare pros and patients, we deliver insights that are clear, relevant, and actionable.

.02 /How does design thinking help in healthcare analytics?

Design thinking puts the user at the center. We start by understanding users’ challenges, define specific issues, brainstorm ideas, and test prototypes to make sure the final tool is both data-rich and easy to use. This process helps us create solutions that fit seamlessly into healthcare workflows.

.03 /Which healthcare organizations can benefit from Codewave's solutions?

Our solutions work well across the board—from hospitals and clinics to research centers, pharma companies, and insurers. With our global experience, we tailor each solution to meet the needs and regulations of different healthcare systems.

.04 /How does Codewave ensure data security in healthcare?

We make data security a priority. Our team follows global regulations like HIPAA and GDPR, using strong encryption, access controls, and regular audits to keep data safe and compliant.

.05 /Can Codewave solutions integrate with existing healthcare systems?

Absolutely. We design solutions that connect smoothly with current healthcare systems, like EHRs and medical devices. Our cloud and edge solutions make integration easy and flexible for different setups.

.06 /How long does it take to implement a healthcare analytics solution?

Timelines vary by project, but a basic solution usually takes 2-3 months, while more comprehensive systems may take 6-12 months. Our agile approach lets us roll out initial modules quickly, adding improvements based on your feedback.

.07 /How does Codewave's global reach benefit clients?

With experience in various healthcare systems worldwide, we bring a unique perspective that combines global best practices with local insights in our healthcare analytics services. This lets us create adaptable solutions that meet regional needs while staying innovative.

.08 /What support does Codewave provide after implementation?

We’re with you post-launch, offering updates, performance tweaks, user training, and ongoing technical help. We also work with you to keep evolving the solution as new needs and trends emerge in healthcare.

.09 /How does Codewave ensure compliance with healthcare regulations?

Codewave ensures all solutions comply with regional and global healthcare regulations, including HIPAA, GDPR, and local privacy laws. We implement secure data management practices, regularly conduct audits, and adapt solutions to meet the latest compliance standards.

.10 /What challenges are faced in Data Analytics Development?

.11 /How scalable are Codewave’s healthcare analytics solutions?

Codewave’s healthcare solutions are highly scalable, allowing organizations to expand as needed. Whether handling growing data volumes or adding new functionalities, our flexible architecture supports seamless scaling to meet evolving healthcare demands.