Improving Clinical Performance in Healthcare: Technology & Innovation Utilization
Kevin Lewis
30+ Year Healthcare Performance Improvement Leader | Resilient Healthcare | United Nations Speaker | White House Advisor | 100+ Written Articles | 25+ Publications including TIME, The N.Y. Times & The Wharton School
The intersection of technology, innovation and clinical performance has never been more critical. The ongoing challenges, from managing patient care to ensuring operational efficiency, demand a resilient approach. This resilience not only helps in weathering the storms of unpredictability but also in driving forward the continuous improvement of healthcare services. As healthcare organizations, from sprawling enterprises to individual hospitals and non-acute facilities, look towards the future, integrating technology and innovation with a resilient mindset is key to unlocking unprecedented levels of clinical performance improvement.
Invest in Predictive Analytics and Big Data
Investing in predictive analytics and Big Data enables healthcare organizations, both acute and non-acute, to significantly improve clinical performance by making data-driven decisions. For entry-level healthcare facilities, a practical first step is to use predictive analytics with their existing electronic health records (EHRs) to forecast patient admissions, helping to optimize staffing and resources. This can be achieved by implementing simple predictive models that analyze trends in admission rates and patient flow. Advanced healthcare organizations can take this a step further by employing sophisticated machine learning algorithms to sift through vast amounts of Big Data from EHRs. This approach not only predicts patient admissions but also enhances the accuracy of diagnoses and personalizes treatment plans based on the analysis of patient data over time. Such predictive capabilities enable healthcare providers to anticipate and mitigate potential health crises, improve the allocation of resources and tailor care to individual patient needs more effectively. For both basic and advanced level organizations, the key is to start with what data is available, focus on specific clinical outcomes to improve and progressively adopt more complex analytics techniques as their data infrastructure and analytics capabilities evolve.
Implement Telehealth and Remote Patient Monitoring Solutions
Implementing telehealth and remote patient monitoring solutions significantly improves clinical performance across healthcare organizations by facilitating continuous care and enabling real-time interventions. For basic-level healthcare facilities, a practical step is to introduce telehealth consultations, which can be particularly useful for managing routine follow-ups or conducting initial patient assessments remotely, thus reducing the need for physical visits. These facilities can gradually incorporate simple wearable devices that monitor vital signs like heart rate and blood pressure, assisting in the management of patients with chronic conditions. Advanced healthcare organizations, on the other hand, can deploy more sophisticated remote patient monitoring technologies, such as glucose monitors for diabetic patients or advanced wearables that track multiple physiological parameters. This enables healthcare providers to monitor patients' health status in real-time and intervene promptly when anomalies are detected, potentially preventing hospital readmissions or emergencies. By integrating these technologies, healthcare facilities can maintain a high level of patient care even during external disruptions like pandemics, ensuring that patients receive the necessary support without the need to visit a healthcare facility, thereby streamlining resource allocation and enhancing patient outcomes.
Embrace Artificial Intelligence (AI) and Machine Learning (ML) for Clinical Decision Support
Artificial intelligence (AI) and machine learning (ML) are transforming clinical decision support in healthcare organizations, leading to improved clinical performance. At a basic level, healthcare facilities can start by employing AI algorithms to analyze electronic health records (EHR) for identifying at-risk patients. For instance, AI can help predict which patients are more likely to be readmitted after discharge, allowing healthcare providers to intervene earlier. Advanced healthcare organizations might implement ML models to assist in diagnosing diseases early and accurately. For example, convolutional neural networks (CNNs), a class of deep learning, can be used to analyze X-rays and MRIs to detect abnormalities such as fractures or tumors with high precision. In practice, the use of AI and ML in healthcare has led to remarkable outcomes. Mayo Clinic, for instance, collaborated with Google Health to develop an AI algorithm that can detect heart conditions from ECG results faster and more accurately than traditional methods. Another example is the AI system developed by researchers at MIT, which can predict the onset of sepsis up to 12 hours before the occurrence, giving doctors a critical time window for intervention. Additionally, PathAI is utilizing ML to assist pathologists in diagnosing diseases like cancer more accurately by analyzing pathology slides for patterns missed by the human eye. These examples highlight how AI and ML are not just theoretical concepts but are being actively implemented to improve clinical outcomes, demonstrating their potential to revolutionize healthcare delivery and patient care.
Leverage Robotic Process Automation (RPA) for Efficiency and Accuracy
Identify and automate repetitive, manual tasks within clinical and administrative processes using RPA . This can range from patient scheduling to billing to supply chain processes. Use RPA bots to streamline data entry, processing and migration tasks. This reduces human error and frees up staff to focus on more critical, patient-centric activities. RPA introduces a layer of operational resilience by ensuring that key processes continue smoothly, even in the face of staffing challenges or increased demand. Automation not only increases efficiency but also maintains a high level of accuracy and consistency in tasks that are crucial for patient care and organizational operations. By incorporating RPA into their technological arsenal, healthcare organizations can achieve significant improvements in workflow efficiency, data accuracy and overall patient and staff satisfaction. This strategic move not only enhances current operational capabilities but also builds a solid foundation for embracing further innovation and adapting to future challenges in the healthcare sector. is increasingly being deployed in healthcare settings to streamline operations and enhance clinical performance. At Sheba Medical Center in Israel, RPA is used to automate the monitoring of patient vital signs. The system automatically alerts medical staff if it detects any abnormalities, ensuring prompt intervention and potentially saving lives by reducing response times in critical situations. In the United Kingdom, the National Health Service (NHS) has implemented RPA to automate the patient appointment scheduling process. This has not only reduced the administrative burden on staff but also decreased patient waiting times, making healthcare access more efficient. The Cleveland Clinic in the United States has applied RPA to patient registration and billing processes. This automation has led to a significant reduction in manual errors and has streamlined administrative workflows, allowing healthcare professionals to allocate more time to direct patient care. These instances demonstrate how RPA can enhance clinical performance by automating routine tasks, optimizing operational efficiencies and ultimately improving patient care outcomes.
Strengthen & Test Cybersecurity
Strengthening cybersecurity in healthcare organizations is essential to protect patient data and ensure uninterrupted clinical services. Basic-level healthcare facilities should start by conducting bi-annual risk assessments to identify potential vulnerabilities within their IT systems. Remediation plans can then be developed to address these vulnerabilities, minimizing the risk of cyberattacks. Additionally, implementing mandatory cybersecurity training for all employees upon hire and annually thereafter, can significantly reduce the likelihood of data breaches caused by human error. For advanced healthcare organizations, adopting more sophisticated cybersecurity measures is advisable. This could include deploying intrusion detection systems that monitor network traffic for suspicious activity in real time and hiring a dedicated cybersecurity team responsible for overseeing the organization's cybersecurity posture and responding to incidents as they occur. By prioritizing cybersecurity, healthcare organizations can protect sensitive patient information from unauthorized access and ensure the availability of critical healthcare services, ultimately supporting high-quality patient care.
Foster a Culture of Continuous Learning and Innovation
To improve clinical performance, healthcare organizations must embrace a culture of continuous learning and innovation. At the basic level, healthcare facilities can start by organizing monthly interdisciplinary workshops where clinicians, IT professionals and administrative staff come together to share knowledge and brainstorm improvements in patient care processes. These facilities should also allocate a portion of their budget to provide staff with subscriptions to online healthcare education platforms (i.e., Coursera, LinkedIn Learning, Khan Academy, edX, Udacity, FutureLearn, Harvard Online Learning, Stanford Online, Medscape and BMJ Learning), enabling employees to stay updated on the latest in healthcare technology and best practices. For more advanced healthcare organizations, creating partnerships with tech companies or universities can be a strategic move. This allows them to access cutting-edge research and pilot innovative technologies in a clinical setting. Further, establishing an innovation lab within the organization can serve as a dedicated space for staff to experiment with new ideas, technologies and processes, with the support of a small fund to prototype promising projects. This approach ensures that all levels of the organization are engaged in ongoing education and are prepared to adapt and implement new solutions, leading to improved clinical outcomes and patient care efficiency.
In conclusion, the path to enhanced clinical performance in healthcare is paved with resilience, technology and innovation. By focusing on predictive analytics, telehealth, AI , ML , RPA , cybersecurity and fostering a culture of continuous improvement, healthcare organizations can build a more adaptable, efficient and patient-centered care model. The integration of these elements not only enhances clinical outcomes but also ensures that healthcare organizations are well-equipped to face future challenges and disruptions to care head-on.
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