Clinical Decision Support Software Development: A Full Guide

Last updated on August 26th, 2024

Clinical decision support systems (CDSS) act as intelligent allies for healthcare professionals. These software applications leverage patient information, established medical guidelines, and the latest research to assist providers in making informed and timely decisions. Picture having a well-informed colleague by your side, providing expert insights as decisions unfold—that is the essence of what clinical decision support software development strives for.

The global market for CDSS was valued at approximately $5.30 billion in 2023 and is anticipated to expand at a compound annual growth rate (CAGR) of 10.79% from 2024 to 2030. This growth highlights a significant demand for CDSS and presents lucrative opportunities for businesses looking to invest in this field. If you are considering developing clinical decision support software, continue reading this blog, which will guide you through essential features, development steps, benefits, and associated costs to effectively create your CDSS. Let’s get started!

What is Clinical Decision Support Software?

A clinical decision support system (CDSS) is a software tool that integrates data, medical knowledge, and patient information to aid physicians in making informed healthcare decisions. By synthesizing extensive medical knowledge with specific details about a patient’s health, the system provides recommendations, alerts, and vital insights that support providers in their decision-making processes.

The primary goal of developing custom clinical decision support software is to enhance the quality of healthcare delivery by equipping healthcare professionals with evidence-based data at the point of care.

Also Read: A Brief Guide for Healthcare App Development

Future Predictions And Projections

• It is estimated that by 2028, approximately 47% of the market for clinical decision support systems will be focused on preventive care.
• The AI medical software service market was projected to reach nearly 7.2 billion yuan by 2022, reflecting an increase of about 94% compared to 2018 figures.
• A survey conducted in 2023 revealed that just under 20% of healthcare decisions within the Asia-Pacific region relied on AI tools like ChatGPT and similar technologies.
• The global market value for clinical decision support systems stood at USD 5.30 billion in 2023, with expectations of a yearly growth rate of 10.79% from 2024 to 2030.

Types of Clinical Decision Support Software

The primary aim of Clinical Decision Support Software (CDSS) is to provide healthcare professionals with timely information and recommendations to enhance patient care. There are primarily two key types of CDSS solutions:

1. Knowledge-Based CDSS

This software product development employs specific medical expertise, often through guidelines or policies, to generate recommendations by comparing patient data against established rules. Examples include:

• Diagnostic Support Systems: Assist healthcare providers in determining potential diagnoses by analyzing symptoms and test results.
• Treatment Support Systems: Offer guidance on appropriate medications, dosages, or treatment strategies tailored to individual patient needs.
• Guideline-Based Systems: Ensure adherence to clinical practice standards and protocols in patient care.

2. Non-Knowledge-Based CDSS

These systems analyse trends within patient data through advanced algorithms and statistical models, frequently leveraging AI and machine learning technologies. Examples include:

• Predictive Modeling Systems: These systems forecast the progression of a disease or predict a patient’s likely outcomes.
• Risk Assessment Tools: Designed to identify individuals at higher risk for certain diseases.
• Natural Language Processing-Based Decision Support Systems: These systems examine clinical notes to extract valuable insights and generate innovative ideas.

How Does Clinical Decision Support Software Work?

Healthcare professionals can utilise Clinical Decision Support Software (CDSS) to assist in making informed decisions regarding patient care. Here’s a simplified overview of its functionality:

1. Data Collection

Clinical Decision Support (CDS) software obtains valuable patient data from various sources, including electronic health records (EHRs), medical devices, and external databases. This information can encompass a range of details such as medical history, vital signs, laboratory results, and demographic information, among other relevant factors.

2. Knowledge Base

The software relies on an extensive information repository that includes medical guidelines, protocols, evidence-based best practices, and expert insights. This database is continually updated to reflect the latest advancements and developments in the field of medicine.

3. Data Analysis

To evaluate the gathered patient data against the knowledge base, the software employs sophisticated algorithms. By considering the patient’s condition and medical history, it identifies patterns, trends, and potential risks.

4. Decision Support

Based on the results of the data analysis, the software provides decision support to healthcare professionals. It presents recommendations, alerts, and warnings to assist in making informed decisions about patient care.

5. Integration

The CDS software seamlessly integrates into the healthcare provider’s workflow, functioning smoothly without interruptions. It typically appears as pop-up alerts, embedded within the EHR system, or through other user-friendly interfaces. This design enables healthcare professionals to receive timely and valuable assistance while making decisions at the point of care.

Major Steps of Clinical Decision Support Software Development

Clinical Decision Support Software (CDSS) development necessitates a systematic and precise strategy to ensure that the software effectively aids healthcare professionals in making sound clinical decisions. Below, our expert developers outline the key phases involved in the creation of CDSS:

Step 1 – Define Your Target Audience

When initiating the development of clinical decision support software, it’s crucial to understand the specific audience for whom it is being created and their requirements. By taking into account the desires and necessities of the target users, both clients and developers can visualize a coherent solution for the future. This clarity makes it easier to determine which technologies and features, such as virtual reality, cloud computing, and the Internet of Things, should be integrated. Additionally, strong relationships between software developers and potential clients can lead to the creation of superior products that effectively meet user needs.

Step 2 – Collect Information About Your Product Idea

Before embarking on the development of Clinical Decision Support software, it is essential to accumulate all necessary information related to creating a medical product, such as EMR software. This thorough understanding will guide you in identifying the specific requirements and features essential for successful software development. Having a clear framework at the outset will significantly enhance the decision-making process as you move forward in the development journey.

Step 3 – Design A Prototype   

Whether you are embarking on the development of clinical decision support software or a hospital administration system, creating a functional prototype that users can engage with is vital. Your prototype should incorporate a wireframe that allows for user interaction with the product. In the realm of medical device software development, prototyping holds significant importance for several reasons. It allows for testing of the product before its full-scale production, and you can also seek assistance from a software testing services provider. This approach enables you to gather feedback and ensure that you are aligned with user needs before investing substantial time and resources into the clinical decision support software. By making iterative changes throughout the project, you can mitigate potential issues and resolve them before they escalate.

Step 4 – Develop Your Final Prototype

Once you have effectively planned the project using various prototyping tools and technologies, it’s time to create the final version of the Clinical Decision Support software prototype. Understanding the intricacies of software development within the healthcare sector and staying abreast of technological advancements is crucial. The most essential aspect is to have a clear vision of how your software should ultimately appear and function upon completion.

Step 5 – Create Code to Write Your Software 

In the realm of medical device software development, crafting Clinical Decision Support Software from the ground up requires significant time and effort; however, it doesn’t necessitate spending excessive time coding every component. Leveraging a software development kit or integrating third-party solutions can streamline the process, potentially reducing the time to market. It’s essential to have a deep understanding of your audience’s needs and preferences for the successful development of a CDSS. By actively soliciting customer feedback, you can determine the most suitable programming languages for their requirements, ensuring their satisfaction with the final outcome of the Clinical Decision Support Software.

Step 6 – Collect Feedback from Users and Deliver To Client

It’s crucial not to release your Clinical Decision Support software before it has been thoroughly assessed by users. Gather reviews from those who will use your medical software and compile a list of potential improvements. Ensure the project reaches completion in the most effective manner possible by delivering the software alongside all necessary updates and documentation. Even when facing time constraints to launch the product, it’s important to allow adequate opportunity for users to test the software and provide valuable feedback.

Read More: 10 Best Healthcare Apps for iPhone and Android Devices

Key Features of Clinical Decision Support Software Development 

To guarantee the success of the software, incorporating essential features is vital. If you’re planning to develop a Clinical Decision Support System (CDSS) for your healthcare organisation, it’s imperative to consult with an IT consulting services provider to ensure these elements are included. Let’s explore the various functions that Clinical Decision Support Software should offer:

Best 5 Clinical Decision Support Software

Clinical Decision Support Software aids healthcare professionals by delivering timely and relevant information, enabling them to make more informed decisions. Here are five widely-used alternatives to consider for enhancing clinical practices:

1.   Epic 

• What it does: A popular platform that equips healthcare providers with various tools for managing aspects like drug interactions and treatment guidelines.
• How it helps: By facilitating swift access to patient data and recommending optimal treatment pathways, Epic enhances efficiency for doctors and boosts the quality of patient care.

2.   Oracle Cerner 

• What it does: An advanced system that provides comprehensive clinical decision support, including predictive analytics and real-time updates on patient conditions.
• How it helps: By leveraging AI technology, Oracle Cerner can identify potential health risks and suggest appropriate interventions, leading to better patient outcomes.

3.   IBM Watson Health  

• What it does: A powerful tool that leverages natural language processing and machine learning to assist in medical decision-making.
• How it helps: By analyzing vast amounts of patient data, IBM Watson Health can provide personalized treatment recommendations and identify potential complications, improving accuracy and efficiency in care.

4.   DynaMed

• What it does: A comprehensive database of evidence-based clinical content that offers point-of-care decision support for healthcare providers.
• How it helps: By providing quick access to the latest and most relevant medical knowledge, DynaMed enables doctors to make well-informed decisions at the point of care, leading to improved patient outcomes.

5.   Micromedex

• What it does: A trusted source of medication information and clinical support tools for healthcare professionals.
• How it helps: By providing accurate drug information, dosing guidelines, and potential interactions, Micromedex ensures safe prescribing practices and reduces the risk of adverse events for patients. Additionally, its advanced features such as drug comparison and compatibility checker aid in optimizing treatment plans for complex cases.

Benefits of Clinical Decision Support Software Development 

Clinical Decision Support (CDS) software development has become essential in contemporary healthcare. It empowers healthcare professionals to make informed decisions, ultimately leading to improved patient outcomes. If you’re considering developing software akin to CDS, it’s important to understand its advantages:

1. Enhanced Patient Safety 

• Reduced medical errors: Clinical Decision Support (CDS) systems significantly decrease the likelihood of adverse events by actively monitoring for harmful drug interactions, allergies, and dosage errors.
• Impact on health outcomes: According to a study published in the Journal of the American Medical Association (JAMA), CDS interventions have the potential to prevent up to 88,000 harmful drug-related incidents annually in the United States.

2. Improved Quality of Care 

• Efficient diagnosis: CDS systems assist healthcare professionals in reaching accurate diagnoses by providing access to the latest evidence-based guidelines and clinical decision-making tools.
• Optimized treatment plans: With the help of CDS, clinicians can create personalized treatment plans that consider patient-specific factors such as medical history, allergies, and drug interactions.

3. Increased Efficiency 

• Time-saving: CDS software automates manual tasks such as data entry, drug interaction checking, and guideline adherence, freeing up time for healthcare professionals to focus on providing quality care.
• Cost-effective: By reducing medical errors and improving patient outcomes, CDS can ultimately reduce overall healthcare costs in the long run.

4. Reduced Healthcare Costs 

• Avoiding unnecessary tests and procedures: CDS systems can assist in avoiding unnecessary medical tests and procedures, resulting in cost savings for both patients and healthcare providers.
• Lower rates of hospital readmission: By providing timely and effective care, CDS systems can help prevent avoidable readmissions, which can be costly for patients and healthcare facilities alike.

5. Enhanced Diagnostic Accuracy

• Support for decision-making: CDS systems empower clinicians to improve diagnostic precision by providing essential patient information, diagnostic resources, and expert insights. Research indicates that these systems can enhance diagnostic accuracy by 5 to 10%.

6. Improved Patient Engagement

• Tailored care plans: CDS systems equip individuals with essential knowledge and self-management tools, empowering them to take an active role in their healthcare.
• Enhanced patient involvement: Increased engagement through CDS is associated with improved health outcomes and greater patient satisfaction.

Challenges and Limitations in Traditional Clinical Decision Support

Even though traditional clinical decision support systems (CDSS) offer significant advantages, they face several challenges and limitations that AI-driven systems aim to address. According to insights from a Clinical Decision Support Software development services provider, key issues include:

• Lack of Integration

Traditional clinical decision support systems often struggle to seamlessly integrate with existing healthcare workflows and electronic health records (EHR). This lack of compatibility can lead to communication barriers and hinder overall efficiency within healthcare settings.

• Limited Scalability and Adaptability

As the volume and diversity of patient data continue to expand, certain clinical decision support systems may struggle to keep pace. These systems might lack the flexibility to adapt to emerging medical knowledge and evolving healthcare requirements, which can diminish their effectiveness in facilitating timely and accurate decision-making for healthcare providers.

• Data Quality and Interoperability

Ensuring the accuracy, completeness, and shareability of data within clinical decision support systems can be quite challenging. According to a SAAS application development provider, inconsistencies or gaps in the data, along with a lack of interoperability between systems, can undermine the reliability and effectiveness of decision-support tools. When the data cannot effectively communicate across different platforms, it compromises the overall utility of these systems for healthcare providers.

• Alert Fatigue

Traditional clinical decision support systems can generate an overwhelming number of alerts, leading to a phenomenon known as “alert fatigue.” This situation presents a challenge for healthcare providers, as the excessive flow of information can desensitize them or contribute to feelings of being overwhelmed. Furthermore, sorting and prioritizing these notifications according to each patient’s unique circumstances and the urgency of their clinical needs becomes increasingly difficult.

• Dependency on Manual Processes

Many clinical decision support systems still rely heavily on manual data entry and paperwork, which can result in errors, inefficiencies, and delays in the decision-making process. By implementing standardized communication protocols and automating data entry, these processes can be streamlined, enhancing the overall functionality and effectiveness of the decision support systems.

How Much Does Clinical Decision Support Software Development Cost?   

Ultimately, the financial aspect is vital when it comes to creating an optimal healthcare decision support system while maintaining budget constraints. You may wonder, “What is the cost of developing Clinical Decision Support Software?” The typical price range generally falls between $10,000 and $30,000, with the possibility of exceeding this amount depending on your project’s specific needs. If you’re also considering healthcare app development, the costs for creating a healthcare website will likely align with this same range. Additionally, the expenses associated with building Clinical Decision Support Software (CDSS) can vary significantly due to factors such as software complexity, desired features, and the chosen technology stack. For a clearer insight into the potential costs, let’s explore the table below:

Suggested: How Much Does it Cost to Create An App

Ready to Build Clinical Decision Support Software by iTechnolabs

At iTechnolabs, we understand that cost is a crucial factor when it comes to developing Clinical Decision Support Software. Our team of dedicated developers and healthcare experts work closely with our clients to create customized solutions that meet their unique needs while staying within budget constraints. With our expertise in advanced analytics, integration, and AI, we can help you build a CDSS that goes beyond the basic features and incorporates cutting-edge technology for optimal decision-making support.

We also offer ongoing maintenance and updates to ensure your CDSS stays up-to-date with the latest advancements in the healthcare industry. Our team will work with you to integrate necessary compliance measures, such as HIPAA regulations, into your system to ensure patient data remains secure and protected.

In addition to development and maintenance, we provide user training and support to ensure your staff is equipped with the knowledge and skills to effectively use the new system. Our goal is to not only create a high-quality CDSS for our clients but also empower them to utilize it to its full potential.

With iTechnolabs, you can rest assured that your CDSS will be built with precision, expertise, and cost-effectiveness in mind. Contact us today to learn more about how we can help bring your CDSS vision to life.

FAQs             

1. How Much Does It Cost To Develop Clinical Decision Support Software?

The cost of developing Clinical Decision Support Software can vary significantly due to multiple factors. Typically, expenses may range from $10,000 to $30,000, depending on the complexity of your project. It is worth noting that if you’re focusing on creating a healthcare app, the overall costs might be relatively lower.

2. How Long Will Clinical Decision Support Software Development Take?

The development timeline for a Clinical Decision Support Software (CDSS) can range from 2 to 4 months for basic systems. However, more intricate CDSS solutions may require over 8 months to complete. Therefore, it is recommended to consult with a CDSS development company for guidance on the best approach for your specific project needs.

3. How To Monetize Clinical Decision Support Software?

There are several effective strategies to consider for monetizing your Clinical Decision Support Software (CDSS).

• Subscription Model: Implement a recurring fee structure that allows healthcare providers to access the software and its features regularly.
• Per-User Licensing: Offer licensing options that cater to individual clinicians or specific departments within healthcare facilities.
• Value-Based Pricing: Establish a pricing model that correlates costs with improved patient outcomes, such as fewer medical errors or overall cost reductions in healthcare delivery.
• Data Licensing: Explore opportunities to generate income by licensing anonymized patient data for research or analytical purposes.

4. What Are the Benefits of Clinical Decision Support Software Development? 

• Enhanced Patient Outcomes: Clinical Decision Support Software contributes to more effective treatments and improved health results for patients.
• Increased Patient Safety: By providing critical information and alerts, CDSS reduces the likelihood of errors in clinical decision-making.
• Boosted Efficiency: The software streamlines workflows, allowing healthcare providers to devote more time to patient care.
• Reduced Healthcare Costs: Implementing CDSS can lead to significant savings by decreasing the incidence of costly medical errors and unnecessary procedures.
• Informed Decision-Making: Healthcare professionals can rely on accurate data and insights to make better-informed clinical choices.

5. What are Popular Clinical Decision Support Software?

We have listed some of the best CDSS systems for your reference:

• Hearst
• Elsevier
• Cerner Corporation
• McKesson
• Epic