The pathology and oncology fields are rapidly evolving, presenting exciting opportunities for software development. Building successful solutions requires not just keeping up with technology but anticipating future needs. This article highlights ten key areas where leading developers are excelling, and where you should be focusing your efforts to create truly impactful software.
1. Prioritizing Security from the Foundation: Top developers understand that security isn't an add-on; it's the bedrock of any successful healthcare software. They're integrating security measures into every stage of the development lifecycle, from initial design to ongoing maintenance, ensuring patient data remains protected. This includes robust encryption protocols such as AES-256 and TLS 1.3, granular access controls, and adherence to regulations like HIPAA. With the increasing prevalence of ransomware attacks targeting healthcare organizations, developers are prioritizing robust backup and recovery systems, along with incident response plans. This ensures that even in the event of a successful attack, patient data can be restored, and operations can resume quickly.
2. Leveraging the Full Asset Landscape: Leading software solutions recognize the diverse data sources and tools used in modern labs and clinics. They seamlessly integrate with EMRs, LIMS, imaging platforms, genomic databases, and other relevant systems, maximizing the power of available data for AI and analytics. For instance, build a system that can pull patient history from an EMR, combine it with genomic data from a specialized database, and then feed it into an AI-powered image analysis tool like those developed by Paige and Mindpeak AI. This holistic approach empowers clinicians with a comprehensive view of patient data.
3. Enhancing Product Relevance Through Blended Development: While geographically concentrated teams, such as those solely based in India or Poland, can offer certain efficiencies, leading developers recognize the importance of ensuring product relevance within the US healthcare market. A purely geographically isolated approach can sometimes result in software that lacks the nuanced understanding of US workflows, user expectations, and regulatory intricacies, similar to how a product might lack 'Americanization' in terms of quality and usability. Therefore, developers are adopting blended teams, integrating product managers, developers, and engineers with direct experience in the US healthcare landscape. This strategy facilitates real-time communication, ensures a strong understanding of US healthcare regulations, and ultimately delivers a more effective product. This approach promotes seamless collaboration between the company, the development team, and the medical professionals who will utilize the software.
4. Embracing the Power of AI: Forward-thinking developers are integrating AI into their offerings, not just for basic functions like spell checking, but for advanced applications like image analysis, diagnostic support, personalized treatment recommendations, and predictive analytics. They understand AI's potential to revolutionize patient care. For example, a number of companies use deep learning algorithms to automate the analysis of immunohistochemistry slides, significantly reducing the time required for diagnosis and improving accuracy. This technology demonstrates the power of AI in streamlining workflows and enhancing diagnostic capabilities.
5. Gathering Diverse Feedback: Leading developers understand the importance of diverse perspectives. They're actively seeking feedback not just from individual pathologists or oncologists, but from project managers, designers, lab technicians, administrators, IT professionals, and they're asking about the true impact of the software. What makes the experience frustrating? What aspects make the platform work well? This feedback loop ensures that the software delivers enduring longevity and value.
6. Creating Predictive, Not Just Reactive, Systems: The best software goes beyond simply reacting to user input. It anticipates needs, proactively delivers relevant information, and empowers clinicians to make informed decisions. Build a system that flags potential issues before they become critical, reducing stress and improving patient outcomes. This is the power of predictive analytics. For instance, a system could analyze patient data to predict the likelihood of treatment resistance, allowing clinicians to adjust their approach proactively. This proactive approach contributes to a more positive and empowering user experience.
7. Prioritizing Interoperability: Smart developers recognize that healthcare systems are interconnected. They're prioritizing interoperability by adhering to industry standards like FHIR, ensuring seamless data exchange and collaboration between different platforms. Specifically, developers are focusing on implementing FHIR resources related to diagnostic reports and genomic data, enabling seamless data sharing between labs and clinics.
8. Designing for Intuitive Use: Leading developers understand that user experience (UX) is paramount. They're investing in user research and usability testing to create intuitive interfaces and streamlined workflows. They're also considering the emotional impact of the software, striving to create a positive and even delightful experience. This includes visually appealing interfaces, personalized dashboards, and even gamification where appropriate (and carefully implemented). To measure "happiness" in software use, developers are using metrics like task completion time, error rates, and user satisfaction surveys, focusing on creating a seamless and efficient workflow. Frustrating experiences are avoided through thorough usability testing and continuous feedback loops.
9. Adapting to the Evolving Regulatory Landscape: The healthcare landscape is constantly changing. Smart developers stay ahead of the curve by building in flexibility and adaptability, ensuring their solutions remain compliant with evolving regulations and guidelines. This includes building modular systems that can be easily updated to reflect new requirements.
10. Implementing Robust Data Governance: Handling sensitive patient data requires robust data governance policies. Leading developers are prioritizing data privacy, security, and access control, building trust and ensuring responsible data handling through clear data governance frameworks. This includes implementing data anonymization techniques and strict access control protocols.
Ethical Considerations: When implementing AI, developers must address ethical concerns. This includes mitigating bias in algorithms by using diverse datasets and ensuring transparency in AI decision-making. Data privacy should be your top concern, requiring robust security measures and compliance with regulations at every step of development.
By focusing on these ten key areas, you can create innovative and impactful software solutions that not only meet the needs of the pathology and oncology community but also contribute to a more positive and effective healthcare experience. Start implementing these strategies today to create the next generation of patient-centric tools.
Author
Scott Kilcoyne
DigitCells Cofounder & COO
1. Prioritizing Security from the Foundation: Top developers understand that security isn't an add-on; it's the bedrock of any successful healthcare software. They're integrating security measures into every stage of the development lifecycle, from initial design to ongoing maintenance, ensuring patient data remains protected. This includes robust encryption protocols such as AES-256 and TLS 1.3, granular access controls, and adherence to regulations like HIPAA. With the increasing prevalence of ransomware attacks targeting healthcare organizations, developers are prioritizing robust backup and recovery systems, along with incident response plans. This ensures that even in the event of a successful attack, patient data can be restored, and operations can resume quickly.
2. Leveraging the Full Asset Landscape: Leading software solutions recognize the diverse data sources and tools used in modern labs and clinics. They seamlessly integrate with EMRs, LIMS, imaging platforms, genomic databases, and other relevant systems, maximizing the power of available data for AI and analytics. For instance, build a system that can pull patient history from an EMR, combine it with genomic data from a specialized database, and then feed it into an AI-powered image analysis tool like those developed by Paige and Mindpeak AI. This holistic approach empowers clinicians with a comprehensive view of patient data.
3. Enhancing Product Relevance Through Blended Development: While geographically concentrated teams, such as those solely based in India or Poland, can offer certain efficiencies, leading developers recognize the importance of ensuring product relevance within the US healthcare market. A purely geographically isolated approach can sometimes result in software that lacks the nuanced understanding of US workflows, user expectations, and regulatory intricacies, similar to how a product might lack 'Americanization' in terms of quality and usability. Therefore, developers are adopting blended teams, integrating product managers, developers, and engineers with direct experience in the US healthcare landscape. This strategy facilitates real-time communication, ensures a strong understanding of US healthcare regulations, and ultimately delivers a more effective product. This approach promotes seamless collaboration between the company, the development team, and the medical professionals who will utilize the software.
4. Embracing the Power of AI: Forward-thinking developers are integrating AI into their offerings, not just for basic functions like spell checking, but for advanced applications like image analysis, diagnostic support, personalized treatment recommendations, and predictive analytics. They understand AI's potential to revolutionize patient care. For example, a number of companies use deep learning algorithms to automate the analysis of immunohistochemistry slides, significantly reducing the time required for diagnosis and improving accuracy. This technology demonstrates the power of AI in streamlining workflows and enhancing diagnostic capabilities.
5. Gathering Diverse Feedback: Leading developers understand the importance of diverse perspectives. They're actively seeking feedback not just from individual pathologists or oncologists, but from project managers, designers, lab technicians, administrators, IT professionals, and they're asking about the true impact of the software. What makes the experience frustrating? What aspects make the platform work well? This feedback loop ensures that the software delivers enduring longevity and value.
6. Creating Predictive, Not Just Reactive, Systems: The best software goes beyond simply reacting to user input. It anticipates needs, proactively delivers relevant information, and empowers clinicians to make informed decisions. Build a system that flags potential issues before they become critical, reducing stress and improving patient outcomes. This is the power of predictive analytics. For instance, a system could analyze patient data to predict the likelihood of treatment resistance, allowing clinicians to adjust their approach proactively. This proactive approach contributes to a more positive and empowering user experience.
7. Prioritizing Interoperability: Smart developers recognize that healthcare systems are interconnected. They're prioritizing interoperability by adhering to industry standards like FHIR, ensuring seamless data exchange and collaboration between different platforms. Specifically, developers are focusing on implementing FHIR resources related to diagnostic reports and genomic data, enabling seamless data sharing between labs and clinics.
8. Designing for Intuitive Use: Leading developers understand that user experience (UX) is paramount. They're investing in user research and usability testing to create intuitive interfaces and streamlined workflows. They're also considering the emotional impact of the software, striving to create a positive and even delightful experience. This includes visually appealing interfaces, personalized dashboards, and even gamification where appropriate (and carefully implemented). To measure "happiness" in software use, developers are using metrics like task completion time, error rates, and user satisfaction surveys, focusing on creating a seamless and efficient workflow. Frustrating experiences are avoided through thorough usability testing and continuous feedback loops.
9. Adapting to the Evolving Regulatory Landscape: The healthcare landscape is constantly changing. Smart developers stay ahead of the curve by building in flexibility and adaptability, ensuring their solutions remain compliant with evolving regulations and guidelines. This includes building modular systems that can be easily updated to reflect new requirements.
10. Implementing Robust Data Governance: Handling sensitive patient data requires robust data governance policies. Leading developers are prioritizing data privacy, security, and access control, building trust and ensuring responsible data handling through clear data governance frameworks. This includes implementing data anonymization techniques and strict access control protocols.
Ethical Considerations: When implementing AI, developers must address ethical concerns. This includes mitigating bias in algorithms by using diverse datasets and ensuring transparency in AI decision-making. Data privacy should be your top concern, requiring robust security measures and compliance with regulations at every step of development.
By focusing on these ten key areas, you can create innovative and impactful software solutions that not only meet the needs of the pathology and oncology community but also contribute to a more positive and effective healthcare experience. Start implementing these strategies today to create the next generation of patient-centric tools.
Author
Scott Kilcoyne
DigitCells Cofounder & COO