Why good data management is the key to quality patient care
If you work in health care, you will know how essential your customer relationship management (CRM) system is in ensuring you deliver high-quality patient care that’s personalised, safe and meets the specific needs of the individual. But your CRM system is only as good as the patient data you capture and store.
Having accurate data is arguably the most critical concern for those who work in the healthcare sector; however, staying on top of this is not always an easy task. Providers deal with an abundance of information, patients and other providers on a daily basis. Therefore, capturing accurate client data is a responsibility that needs to fall to everyone in the organisation who interacts with the CRM — including reception and administrative staff, healthcare practitioners, managers, and sales and marketing teams at times. Duplicate information and invalid entries compromise data quality and can result in poor decision-making and inappropriate or inadequate care with potentially serious consequences, not to mention an inefficient use of resources, decreased patient retention and ultimately revenue loss.
To ensure you’re practising good data management and providing your clients with best practice care, take note of these three simple steps: assessment, prevention and remediation.
Start with a thorough assessment of your patient data quality. Before you can tackle any potential data quality issues, you need to understand the specific areas that need to be addressed as well as the size of the problem. A good assessment tool should show specific data-quality issues, how they are affecting your day-to-day business functions like sales and marketing, and just as importantly, what needs to be done to fix them.
Common data-quality issues that have significant treatment implications include duplicate data, incorrect data, invalid data, incomplete or inconsistent data or poorly defined data (which means that data is sectioned in the wrong category).
You can prevent bad data from becoming a recurring issue by looking at how data enters the system initially. This means educating all employees that interact with the CRM on how to correctly input and manage data, as well as establishing protocols for keeping data complete and accurate or ‘clean’.
A list of rules for all people adding data should include:
- Using standardised naming conventions and formats, including abbreviations.
- Inputting all required fields for a record. For example, identifying that it’s a patient’s first visit or that they need to schedule a follow-up.
- Double-checking each patient’s info every time you interact with them, whether they be making a new appointment or filling a new prescription.
Prevention should also include evaluating third-party tools that can help ensure data quality. Examples include email list verification services, email verification application programming interfaces (APIs) for web forms, and scanners and blockers designed to find duplicate data and prevent it from being entered. In addition, making manual data entry and corrections as easy as possible for your end users will significantly help in preventing data issues by saving them time and stress, Validity Inc.’s Grid Buddy being one example.
Data that started out as ‘clean’ can become compromised. A patient’s medical and contact information can change over time, as can their treatment needs. Therefore, the information and incentives that you offer them need to evolve, too. Implementing frequent data cleansing processes to regularly remove or merge duplicates, standardise content and verify contact information is key. Third-party software can make staying on top of your data simple by automating these processes for you.
Poor-quality data often goes undetected until it becomes obvious that it’s negatively affecting patient care, impacting on revenue or resulting in overspending. Don’t wait until then — investing in good data-quality processes and tools is critical to removing obstacles to best practice care and business success. Some accessible examples include data management tools that, in addition to correcting specific data issues like duplicates or incomplete datasets, also help you implement an entire data governance regime to ensure you maintain data integrity and prevent further issues from arising. Your chosen CRM system may even have some native tools you could use depending on the capabilities you require.
Using data to ensure you stay on top of patients’ personal information, appointments and treatment can be the difference between seeing someone once or twice and having a loyal, trusting patient for years to come. Once you’ve got the right processes and tools in place, you can use your patient data to provide the highest quality care, ensuring your patients always feel assured, safe and supported.
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