This article was submitted to Healthcare Weekly by Salman Rashid @ RightPatient.
Providing optimal healthcare services to patients depends on several factors. Identifying the problem accurately at the right time, providing proper treatment, ensuring that the patient is engaged throughout the journey, and following up to detect any subsequent issues are just some of them. Hospitals and health systems have to ensure that all the cogs in the machine are working well with one another, otherwise, it will impact healthcare outcomes down the line. One of the growing concerns is healthcare data quality issues – something which can make or break patient outcomes.
That being said, let’s take a look at what healthcare data quality is, why it’s so crucial for caregivers and patients alike, and some potential ways to ensure and maintain high-quality patient data.
First of all, healthcare data quality is quite simple, even though maintaining it can be a herculean task. It refers to how accurate, relevant, consistent, and useful the data in question is. Whenever healthcare data quality is mentioned, it typically refers to EHRs, or electronic health records. These EHRs basically contain all the information about patients – medical history, vitals, immunization dates, address, medications, conditions, lab test results, and more.
Preventing healthcare data quality issues, as a result, ensures that physicians have access to accurate, consistent, relevant, and timely information for making informed decisions – improving healthcare outcomes, preventing patient safety incidents, and reducing unwanted readmissions.
Unfortunately, as mentioned, it’s easier said than done, and most care providers suffer from healthcare data quality issues.
Ensuring high-quality healthcare data is impeded by many problems – the most prominent ones are poor data quality right from the start, medical record errors that need to be rectified, medical record mix-ups, and inaccurate patient identification. But what are the major consequences of low-quality healthcare data?
Quite understandably, healthcare data quality issues not only cause problems for hospitals and health systems but the consequences are suffered by patients as well. That being said, let’s take a look at the major consequences caused by patient data integrity issues.
This is an obvious consequence – if the patient data is corrupt, inaccurate, or fragmented, it can lead to a plethora of issues for the patient. For starters, it will start an inaccurate treatment, will lead to redundant lab tests, will lead to performing surgery on the wrong patient – all of which can be detrimental for the patients. In fortunate cases, the treatment might get delayed, but if it’s a critical case, delays can be quite costly. All in all, poor quality data leads to patient harm, detrimental healthcare outcomes, hospital readmissions, and worse.
When patient data is corrupt in EHR systems, it leads to confusion among the EHR users, and leads to medical record errors such as duplicates or overlays, especially if the hospital isn’t using a robust patient identification system.
For instance, when a patient comes for a visit, the EHR user needs to assign the correct medical record for proceeding to the next stage. However, due to poor data quality and the lack of proper patient identification, the EHR user will find it quite difficult to identify the appropriate medical record – there might be hundreds of them with similar names or characteristics.
The EHR user will either:
This will most likely cause overlays down the line, that is, merging medical records of different patients – something that is extremely dangerous. Even if actual duplicates are merged, the results won’t be as good as that of a patient record that is immaculate, consistent, and unfragmented.
Well, if the patient is assigned with the wrong medical record, it’s a given that the healthcare provider will face issues after submitting the claim to the payer. Even if the patient is Since wrong information leads to billing and coding errors, these inconsistencies are picked up by the insurance provider, after which the claim is either denied or rejected – something that hits the hospital’s bottom line quite hard.
While those were some of the common consequences of poor patient data quality, are there ways to ensure patient data integrity?
It’s quite simple – these audits can identify the gaps a hospital might have that lead to patient data integrity issues. Conducting them proactively rather than reactively is also the wiser choice – it’s better to be safe than sorry as data integrity issues are interconnected and might lead to more down the line.
The biggest issue that can lead to data integrity issues is if the medical records aren’t following the standards properly. One EHR might have used all the name fields for a patient (first, middle, and last), whereas another one might use only the first and last names. This is just a simple example but can lead to integrity issues down the line. Can you imagine what occurs when data quality standards aren’t followed for more complex fields?
Training and reminding EHR users, physicians, and anyone else who can edit EHRs to comply with data standards strictly is a must to ensure high-quality data.
One of the best ways to prevent data quality issues is to prevent them right from the start – the registration process. Preventing duplicate medical records, overlays, and data integrity issues is quite possible if hospitals are ensuring positive patient identification. Doing so ensures that the EHR user, physician, or registrar is identifying the accurate medical record and inputting the right information in the right medical record – ensuring high-data quality.
You may also want to read Doctor MacKoul’s suspension article of medical licenses among Ambulatory Surgery Centers here.