Hospitals collect huge amounts of data from health and patient management records.

Healthcare dashboards turn this raw and complicated data into easy-to-understand metrics, such as patient satisfaction and disease management. You can see these metrics in charts, graphs, and tables.

But you may ask how these metrics help hospitals.

Let me explain. For example, let's take the patient satisfaction metric. This metric helps the admins see whether the patients are happy with the hospital service.

If the dashboard shows that satisfaction levels are low, then it means patients are unhappy with the hospital service.

Admins can make the service better by asking patients for feedback to figure out what needs fixing; then, they can make some changes to keep patients happy.

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Benefits of AI-powered dashboards in healthcare

Here are a few benefits specific to healthcare.

Appointment scheduling:

Suppose you want to book a dental appointment. When you call the doctor's office, AI can assist the receptionist as follows:

It checks the doctor's working hours, days off, and current bookings. The receptionist gathers details like what kind of appointment the patient needs (regular, special, or urgent care).

Combining the doctor's schedule and the patient's requirements, AI can suggest open slots for booking.

This helps the receptionist quickly figure out the best time to fit the patient through the schedule. This saves a lot of time for the patient and the hospital.

Plus, AI can learn from past appointments to determine the best way to schedule patients, making everything more efficient.

Personalized treatment plans:

AI analyzes patient data like medical records, diet, and exercise habits. It can find patterns or similarities in this data to suggest a personalized plan just for you.

‍

For example, AI might find that people with specific lifestyles (people who are physically not active) are likely to develop certain conditions (obesity). Further, it can suggest specific medicines, therapies, or lifestyle changes.

‍

Data visualization and real-time insights:

Real-time analytics and visualizations in healthcare can save people's lives.

‍

For example, doctors can continuously monitor the metric that shows a patient's heart rate. If the heart rate goes down, the doctors can attend to the patient immediately to bring the patient to a normal condition.

‍

This is only possible with an AI-powered dashboard that updates in real time with suitable visualizations.

‍

Predictive analytics:

AI can predict patient outcomes and identify high-risk patients as follows:

1. By analyzing your weight, blood sugar levels, and family history, AI can estimate when the patient might develop diabetes. So, the doctor can recommend preventive measures.
2. Based on age, smoking habits, and medical history, AI can combine this information to find patients at high risk of getting pneumonia.

‍

Revenue cycle improvement:

Processing claims and identifying coding errors by hand takes a lot of time.

‍

But AI can process claims much faster with fewer mistakes. Also, it can verify whether the codes for treatments and procedures are correct. This avoids denial of claims.

Types of healthcare dashboards

Operational dashboards

These dashboards show what's happening every day at a healthcare facility. They give you real-time information like:

Resource use:

1. How many beds are occupied?
2. What equipment is available?
3. When do staff work?

Patient flow:

1. How long are patients waiting?
2. How many are in the emergency department?
3. How many are moving through?

Supply chain:

1. How much inventory is on hand?
2. What medications are available?
3. If equipment needs maintenance.

Clinical dashboards

Clinical dashboards give us a peek into how patients are doing. Some of the important metrics we look at are:

Patient outcomes: 

These include:

1. Readmission rates
2. Mortality rates
3. Complication rates

Disease management:

1. How many people have chronic diseases?
2. How well do they understand their condition?

Quality of care:

1. How happy patients are
2. Rates of infections
3. Errors in medications

Population health:

1. How many people are vaccinated?
2. Using preventive care
3. Are patients getting health check-ups?

Financial dashboards

Financial dashboards in healthcare give a big picture of how well the organization is doing financially.

1. Keeping track of money coming in: This covers how fast payments are collected, managing unpaid invoices, and dealing with denied claims.
2. Watching spending closely: This means keeping a close watch on staff expenses, supply costs, and all the other costs that come with running the place.
3. Figuring out what's making money: This is about understanding which services are pulling in the most revenue, checking out the mix of payers, and comparing costs to how much is charged.
4. Checking financial health: This looks at different numbers to see if the organization is in good shape money-wise, such as how easily it can pay off debts and how profitable it is.

Steps to create an interactive healthcare dashboard

Define purpose and audience

You need to understand why you need this dashboard.

‍

The first step is to identify the primary users of the dashboard and what they need help with. This makes it easy to build dashboards for specific purposes.

‍

For example, doctors and nurses need information about a patient's health status or test results. This specific dashboard might involve metrics such as heart rate, blood test, temperature, etc.

‍

A few metrics for hospital management are how much it costs to run the hospital and how many patients are about to be discharged.

‍

You can either build a specific dashboard that serves certain users or create a generic one to get an overview of your hospital.

However, the audience and the purpose are the first steps to building either of these dashboards.

Data collection and preparation

Collect all the relevant data from health records, billing systems, and patient registries.

‍

Make sure the data is of high quality, has a consistent format, and is complete. After that, prepare it into a suitable format for analysis.

Select key performance indicators

Just like we discussed earlier, choosing the right KPIs is easier when you have a clear purpose and know who your dashboard is for.

Choose a visualization tool

Visualization tools make it easy to convert data into clear and beautiful charts.

‍

But, not all tools are created equally, and they are not suitable for your specific needs. So, pick a tool that has great data visualization, allows for interaction, and can be integrated easily.

‍

DataBrain is an excellent choice for its user-friendly interface and powerful features.

Design dashboard layout

1. Design a layout that looks great and is easy to understand.
2. Put the important stuff first and make sure everything is clearly labeled.
3. Organize the information into logical sections and use color and hierarchy effectively.

Incorporate interactivity

Let users explore data with features like drill-down, filtering, and zooming. It makes discovering hidden information more fun and interactive.

Testing and refinement

Test the dashboard thoroughly with the end users to get their feedback.

‍

This will help you find ways to improve it and make necessary changes to ensure the data is accurate. The visualizations should be clear, and the overall user experience should be excellent.

Deployment and maintenance

Make sure to put the dashboard in a secure and easy-to-reach spot.

‍

Give users clear instructions and support. Also, set up a regular maintenance schedule to update data, fix errors, and add new features.

Additional considerations

• Data security and privacy: Keep patient information safe by establishing strong security measures and following data privacy rules like the HIPAA and GDPR.
• Accessibility: Make sure the dashboard is easy for people with disabilities and meets accessibility standards (e.g., WCAG).
• Mobile optimization: Ensure the dashboard looks good and works well on all devices.
• User training: Provide comprehensive training to help users understand the dashboard's functionalities and extract maximum value.

How DataBrain simplifies AI dashboard creation

DataBrain is a tool that makes it easy to create dashboards with its AI technology. It lets healthcare workers focus on their data instead of getting stuck on complex steps.

‍

It has an interface where you just drag and drop to build your dashboards. This means you don't need to know coding to make something that looks good. Just pick your data and how you want it to show up.

‍

You can also change your dashboards any way you want. You can pick different colors and fonts and add buttons and filters to make it work for you.

‍

Dashboards from DataBrain are important for healthcare because they use natural language processing and machine learning to understand your questions and respond with answers within minutes. This helps make better choices and be more efficient.

If you think DataBrain could help your healthcare facility work better, reach out to see it in action.

Benefits of AI-powered dashboards in healthcare

Here are a few benefits specific to healthcare.

Appointment scheduling:

Suppose you want to book a dental appointment. When you call the doctor's office, AI can assist the receptionist as follows:

‍

It checks the doctor's working hours, days off, and current bookings. The receptionist gathers details like what kind of appointment the patient needs (regular, special, or urgent care).

‍

Combining the doctor's schedule and the patient's requirements, AI can suggest open slots for booking.

‍

This helps the receptionist quickly figure out the best time to fit the patient through the schedule. This saves a lot of time for the patient and the hospital.

‍

Plus, AI can learn from past appointments to determine the best way to schedule patients, making everything more efficient.

‍

Personalized treatment plans:

AI analyzes patient data like medical records, diet, and exercise habits. It can find patterns or similarities in this data to suggest a personalized plan just for you.

‍

For example, AI might find that people with specific lifestyles (people who are physically not active) are likely to develop certain conditions (obesity). Further, it can suggest specific medicines, therapies, or lifestyle changes.

‍

Data visualization and real-time insights:

Real-time analytics and visualizations in healthcare can save people's lives.

‍

For example, doctors can continuously monitor the metric that shows a patient's heart rate. If the heart rate goes down, the doctors can attend to the patient immediately to bring the patient to a normal condition.

‍

This is only possible with an AI-powered dashboard that updates in real time with suitable visualizations.

‍

Predictive analytics:

AI can predict patient outcomes and identify high-risk patients as follows:

1. By analyzing your weight, blood sugar levels, and family history, AI can estimate when the patient might develop diabetes. So, the doctor can recommend preventive measures.
2. Based on age, smoking habits, and medical history, AI can combine this information to find patients at high risk of getting pneumonia.

‍

Revenue cycle improvement:

Processing claims and identifying coding errors by hand takes a lot of time.

‍

But AI can process claims much faster with fewer mistakes. Also, it can verify whether the codes for treatments and procedures are correct. This avoids denial of claims.

Types of healthcare dashboards

Operational dashboards

These dashboards show what's happening every day at a healthcare facility. They give you real-time information like:

Resource use:

1. How many beds are occupied?
2. What equipment is available?
3. When do staff work?

Patient flow:

1. How long are patients waiting?
2. How many are in the emergency department?
3. How many are moving through?

Supply chain:

1. How much inventory is on hand?
2. What medications are available?
3. If equipment needs maintenance.

Clinical dashboards

Clinical dashboards give us a peek into how patients are doing. Some of the important metrics we look at are:

Patient outcomes: 

These include:

1. Readmission rates
2. Mortality rates
3. Complication rates

Disease management:

1. How many people have chronic diseases?
2. How well do they understand their condition?

Quality of care:

1. How happy patients are
2. Rates of infections
3. Errors in medications

Population health:

1. How many people are vaccinated?
2. Using preventive care
3. Are patients getting health check-ups?

Financial dashboards

Financial dashboards in healthcare give a big picture of how well the organization is doing financially.

1. Keeping track of money coming in: This covers how fast payments are collected, managing unpaid invoices, and dealing with denied claims.
2. Watching spending closely: This means keeping a close watch on staff expenses, supply costs, and all the other costs that come with running the place.
3. Figuring out what's making money: This is about understanding which services are pulling in the most revenue, checking out the mix of payers, and comparing costs to how much is charged.
4. Checking financial health: This looks at different numbers to see if the organization is in good shape money-wise, such as how easily it can pay off debts and how profitable it is.

Steps to create an interactive healthcare dashboard

Define purpose and audience

You need to understand why you need this dashboard.

‍

The first step is to identify the primary users of the dashboard and what they need help with. This makes it easy to build dashboards for specific purposes.

‍

For example, doctors and nurses need information about a patient's health status or test results. This specific dashboard might involve metrics such as heart rate, blood test, temperature, etc.

‍

A few metrics for hospital management are how much it costs to run the hospital and how many patients are about to be discharged.

‍

You can either build a specific dashboard that serves certain users or create a generic one to get an overview of your hospital.

However, the audience and the purpose are the first steps to building either of these dashboards.

Data collection and preparation

Collect all the relevant data from health records, billing systems, and patient registries.

‍

Make sure the data is of high quality, has a consistent format, and is complete. After that, prepare it into a suitable format for analysis.

Select key performance indicators

Just like we discussed earlier, choosing the right KPIs is easier when you have a clear purpose and know who your dashboard is for.

Choose a visualization tool

Visualization tools make it easy to convert data into clear and beautiful charts.

‍

But, not all tools are created equally, and they are not suitable for your specific needs. So, pick a tool that has great data visualization, allows for interaction, and can be integrated easily.

‍

DataBrain is an excellent choice for its user-friendly interface and powerful features.

Design dashboard layout

1. Design a layout that looks great and is easy to understand.
2. Put the important stuff first and make sure everything is clearly labeled.
3. Organize the information into logical sections and use color and hierarchy effectively.

Incorporate interactivity

Let users explore data with features like drill-down, filtering, and zooming. It makes discovering hidden information more fun and interactive.

Testing and refinement

Test the dashboard thoroughly with the end users to get their feedback.

‍

This will help you find ways to improve it and make necessary changes to ensure the data is accurate. The visualizations should be clear, and the overall user experience should be excellent.

Deployment and maintenance

Make sure to put the dashboard in a secure and easy-to-reach spot.

‍

Give users clear instructions and support. Also, set up a regular maintenance schedule to update data, fix errors, and add new features.

Additional considerations

• Data security and privacy: Keep patient information safe by establishing strong security measures and following data privacy rules like the HIPAA and GDPR.
• Accessibility: Make sure the dashboard is easy for people with disabilities and meets accessibility standards (e.g., WCAG).
• Mobile optimization: Ensure the dashboard looks good and works well on all devices.
• User training: Provide comprehensive training to help users understand the dashboard's functionalities and extract maximum value.

How DataBrain simplifies AI dashboard creation

DataBrain is a tool that makes it easy to create dashboards with its AI technology. It lets healthcare workers focus on their data instead of getting stuck on complex steps.

‍

It has an interface where you just drag and drop to build your dashboards. This means you don't need to know coding to make something that looks good. Just pick your data and how you want it to show up.

‍

You can also change your dashboards any way you want. You can pick different colors and fonts and add buttons and filters to make it work for you.

‍

Dashboards from DataBrain are important for healthcare because they use natural language processing and machine learning to understand your questions and respond with answers within minutes. This helps make better choices and be more efficient.

If you think DataBrain could help your healthcare facility work better, reach out to see it in action.