Data neglect in healthcare: 5 threats to the industry's future
The healthcare industry is inundated with vast amounts of data every day, which is crucial for providing high-quality patient care. While Electronic Medical Records (EMR) and Electronic Health Records (EHR) are the most commonly used tools for collecting and managing healthcare data, other tools, such as data warehouses, health information exchanges, and clinical decision support systems, are used to manage the information. However, the challenge doesn't end with data collection, as the data must also be regularly updated, cleaned, and organized to ensure its accuracy and usefulness. Failure to prioritize data hygiene can severely affect healthcare staff performance and the industry's future. This blog will explore the five major threats healthcare organizations face due to neglecting data hygiene.
5 threats to the industry's future
The healthcare industry is under constant pressure to provide high-quality patient care, and staff are on the front lines of this challenge. However, they are also grappling with a range of data-related challenges that make their jobs even more difficult. These include issues with data silos, data quality, data privacy and security, data integration, and data governance. Neglecting data hygiene can harm patients and healthcare organizations, leading to inaccurate diagnoses, inappropriate treatments, and poor outcomes.
According to recent statistics, dirty data costs the US healthcare industry around $300 billion annually. This is based on figures from the US Attorney, suggesting that around 14% of industry expense disappears through data mismanagement.
These numbers show the significant impact of data hygiene on the healthcare industry and the importance of addressing data-related challenges to improve patient outcomes and reduce costs.
1. Data silos
Healthcare organizations frequently operate in isolated silos, creating a duplication of effort and inconsistent data. This lack of communication and collaboration can pose challenges when building a complete and accurate view of a patient's data or analyzing trends and outcomes. For instance, a patient might visit multiple healthcare providers within the same system. Still, if each provider utilizes a different system, their data will be stored in separate silos, making obtaining a comprehensive picture of the patient's overall health challenging. This can lead to gaps in patient care, as providers might not have access to important information about a patient's medical history or ongoing treatments.
2. Bad data quality
Healthcare data can sometimes be a real headache. It's often incomplete, inaccurate, or inconsistent, making it difficult for staff to provide the best possible care to patients. Picture this: a doctor is trying to determine the best treatment for a patient, but their medical history is scattered across different systems, and important details are missing. It's like trying to solve a puzzle with half the pieces missing. And that's not all - healthcare staff often have to work with poorly structured or hard-to-access data, which can feel like digging through a messy closet to find a specific shirt. But the stakes are much higher in healthcare, as using incorrect data can lead to some serious consequences for patients.
3. Lack of data privacy and security
Healthcare organizations must adhere to strict data privacy and security regulations to safeguard patient health information's confidentiality. This poses a challenge when attempting to share data across departments or organizations, as any breach of privacy can have serious consequences. As a result, healthcare providers may be hesitant to share data, even when it could benefit patient care. Finding a balance between data privacy and sharing is crucial for healthcare organizations to provide high-quality, comprehensive care while maintaining patient trust and confidentiality.
4. Data fragmentation
While data collection is crucial for delivering high-quality patient care, data integration poses a significant challenge for healthcare organizations. This lack of integration hinders a comprehensive understanding of patient health, and meaningful insights are often lost in the process. The challenge of integrating data is particularly evident in situations where a patient's data is stored in separate systems, such as when laboratory and radiology results are stored in different systems, making it difficult to obtain a holistic picture of the patient's health status.
Let's say that a patient, John, has a history of heart disease and is being treated by a primary care physician and a cardiologist. The primary care physician uses an electronic health record system (EHR) to manage John's overall health information, while the cardiologist uses a separate system to manage John's heart-specific information.
John's primary care physician notices that John's blood pressure is elevated and orders a blood test to check his cholesterol levels. The results of the test are automatically added to John's EHR. However, the cardiologist does not have access to John's EHR and instead relies on his system to manage John's health data.
If the cardiologist is unaware of the recent blood test results and prescribes a medication that could interact with John's cholesterol medication, this could lead to harmful consequences. Without a comprehensive view of John's health information, the cardiologist might not be aware of potential risks or make the most informed decisions about John's care.
5. Lack of data governance
Healthcare organizations are held to strict regulatory requirements and ethical standards when managing data. Balancing the need for data access and sharing with data security and privacy can be challenging. For instance, a healthcare organization collaborating with a research partner might need to share sensitive data while ensuring patient privacy. In such cases, de-identification of the data becomes crucial. This process involves removing identifiable information, such as name and social security number, from the data to safeguard patient confidentiality. Healthcare organizations can maintain patients' trust and confidence in their care by ensuring regulatory compliance and ethical data management.
Data Management: a single source of truth
Healthcare organizations must recognize data hygiene's critical role in delivering high-quality patient care. The challenges related to data quality, accessibility, privacy, and security are not impossible. They require a proactive approach prioritizing a complete data management solution, a robust tech stack, and operational staff training in best practices in data hygiene.
By investing in data hygiene, healthcare organizations can unlock the potential of their data to drive insights, optimize operations, and transform the patient experience. The possibilities are endless - from reducing healthcare costs and improving patient outcomes to creating a more connected and coordinated healthcare ecosystem.
The path to data hygiene excellence may not be easy, but delivering patient-centered care in today's complex healthcare landscape is necessary.