The data that healthcare organizations hold is incredibly valuable – it’s perhaps the most valuable asset they have. At an individual level, patient data often contains the key to understanding illness and potential recovery. Viewed more broadly, the data associated with a patient’s engagement with a healthcare provider – for example, admissions records and procedures performed – can provide insights into what the future strategy of the organization should be.
Understanding the data issues healthcare faces
Yet, data can also be one of the most challenging aspects of a healthcare organization’s operations. Usually, patient data sits in individual silos, which are unable to communicate with each other. Many individuals who have been hospitalized will recall having to repeatedly fill out paper forms giving their name, address, and other basic details. Usually, these details are input manually, and sometimes mistakes are made.
Silos create other challenges, too. Often there is no agreed data, infrastructure or security standards between technology systems. There can be inconsistencies in the way data is stored, or shared – data models of technology tools can vary widely. As well as having manual processes for collecting data, there are often also manual processes for finding and linking data too. Lastly, data can be stored in spreadsheets, PDFs – or even still on paper! Basic operational issues like these can lead to low data quality, or an inability to create a holistic picture of an individual patient’s care.
Healthcare organizations face other challenges, too. They operate in a highly regulated industry, which often has standards or regulations around data privacy and data security. There are more general rules too – for example, within the EU there is the General Data Protection Regulation (GDPR), and in the US there is the new California Consumer Privacy Act (CCPA). As well, healthcare organizations are at an elevated level of risk when it comes to cyber threats. Concerns about risk and compliance can make it daunting to consider more advanced approaches to managing data – will patient data be safe, and will the organization remain compliant?
The good news is that a robust data governance program can help solve many of these challenges. It’s important for health-related organizations to consider the positive reasons for embracing data governance and understand the change that data governance is capable of enabling.
Being open to data opportunities
Healthcare is one of the most rapidly changing industries in the world. New illnesses emerge, or old illnesses reappear. Treatments – often technology-based – are constantly evolving. Due to the well-being aspect of healthcare, the industry is often the subject of intense scrutiny, and so finds itself adapting to new laws, regulations, or social perceptions. Good data governance can transform organizations so they are able to overcome the challenges they face and embrace the opportunities these changes create, providing improved patient outcomes. Five key opportunities for healthcare organizations include:
- Improving operational efficiencies – Individuals are able to look across silos find the data they need to do their jobs much more quickly and easily. They are able to understand the quality of the data and its source(s) at a glance. As a result, individuals will be able to spend less time struggling with data and can refocus their efforts on providing patient care.
- Building more collaboration – Robust data governance enables healthcare teams to collaborate more efficiently and effectively, greatly enhancing patient care. For example, pieces of patient information scattered across silos can be brought together in a regulatorily compliant way, helping to create a more holistic view of the patient’s health that care teams can leverage to drive better outcomes.
- Enhancing quality of data – Data governance helps healthcare organizations understand issues with data quality and establish and monitor programs to remediate future data quality issues. It’s important for doctors to be able to trust the patient data they are working with, and for administrators to be able to trust the data they are using to make strategic decisions.
- Assuring regulatory compliance – Healthcare organizations need to comply with data privacy and protection rules such as HIPAA as well as GDPR or the CCPA. A strong data governance approach enables healthcare organizations to know where personal health information is stored, and what is stored, and who has access – making compliance much easier to achieve and evidence. Formal workflow processes for requirements such as data breach notification help ensure compliance processes are adhered to.
- Fostering innovation – Technology is revolutionizing healthcare, and high-quality data is essential for engagement with artificial intelligence (AI), Big Data, the Internet of Things (IoT) and other uses. For example, using AI techniques to develop predictive models for outcomes requires training data sets that are well understood and accurately reflect real-world data sets. High-quality data is also essential for the kinds of advanced analytics that healthcare administrations are beginning to use as best practice.
Getting data governance right can help healthcare organizations tackle the challenges they face, embrace the changing nature of their industry, and transform themselves by responding in new ways to opportunities.
After almost 15 years in Healthcare data management with IBM, Oracle, and Informatica, Chris joined the Collibra team to help Healthcare organizations get more out of their data-driven initiatives by focusing on data governance as a tool for engaging the business and clinical organizations. Chris is responsible for the Collibra Healthcare Sales and Strategy in the United States — a mission that aligns with his core belief that data and transparency are critical to providing the best healthcare.