Proper Demographic Data Entry in EHR Can Improve Patient Matching

by | Published on Aug 21, 2019 | Data Entry Services

Today with the entry of the EHR, a greater share of medical records are stored and exchanged electronically. This exchange has increased in recent years and can occur among various types of providers-including hospitals, primary care physicians, specialty physicians, pharmacies, and laboratories. Leading data entry companies now offer medical data entry services that help to streamline their data processing needs and manage the collected data most efficiently. However, entering data into the EHR comes with many challenges and one among them is patient matching. Patient matching involves comparing data from multiple health IT systems to find out whether the data sources match and belong to the same patient. This is important to obtain a complete record of the patient’s health history and medical care received. According to a recent report from the Government Accountability Office (GAO), healthcare organizations should work to adopt proper demographic data entry into the EHR to improve patient matching. It also helps to eliminate duplicate records and confusion.

Data Entry in EHR Can Improve Patient Matching

For delivering the best care, physicians should get hands-on accurate records on each patient’s medical history that includes diagnoses, lab results, imaging, medications, surgeries, and so on. But this interoperability that would link electronic patient medical records across institutions and time requires patient matching on a large scale. This data integration helps the healthcare provider to get a complete picture of a patient’s health and previous care. Moreover, it can also improve future care through this broader shared data, combined with evidence-based medicine.

But as of a 2014 study, GAO cited that only half of records are accurately matched when different organizations exchange information. The main reasons cited for the inconsistencies in demographic data are:

  • Providers collect inaccurate information from patients
  • The patient information isn’t consistently updated
  • Health IT systems allow users to input data (different information collected from patients) differently

It’s very important to have accurate data on EHRs as it ensures that providers have current information about patients’ laboratory or other diagnostic test results; their medications; their diagnosed medical conditions such as allergies; and their family medical histories and they could provide coordinated and effective care. Inaccurate patient record matching can adversely affect treatment and diagnosis decisions, as they might be made in the absence of valuable information, and patients could be subject to adverse events and significant harm.

So, to avoid such issues and to determine how reliable organizations are effectively improving patient matching, GAO reviewed published reports and conducted interviews with physician practices and hospitals and health information exchange (HIE) organizations. From majority reviews, patient demographic data seem to have a significant impact on patient matching accuracy. They also noted that imprecise, imperfect or inconsistently formatted demographic information in patients’ medical records can make it challenging to identify and match all the records belonging to a single patient.

Patient demographic data is the primary resource and the core of the data for any healthcare institution as they allow for the identification of a patient and his categorization into categories for the purpose of statistical analysis. However, first-time entry of patient data is not enough for efficient EHR, updating is necessary. That is, when a patient comes to a healthcare center for an appointment, it is just as important to update patient demographics for existing patients as it is for new patients. For example, if an existing patient has moved from their provided address or changed their phone number, then attempts to send them bills and follow up with phone calls is useless, similarly, if their insurance has changed then claims filed to the old provider may get denied and payments delayed.

Another major thing to keep in mind is ensure that the information is accurately entered without any errors. After validating the patient data entry, the information is entered into the medical billing system. The patient demographic data that all healthcare systems should validate and enter include –

  • Contact Information (Name, Address, Phone number)
  • Family Doctor’s Name
  • Date of Birth
  • Emergency Contact
  • Gender
  • Country, postal code
  • Insurance Provider data
  • Ethnicity
  • Allergies
  • Blood Type
  • Major Diagnoses
  • Medical History

In the above-mentioned study, the interviewees said they implemented these common standards for data collection and formatting to improve the consistency of demographic data. They also mentioned their efforts to boost patients’ ability to share their health information with their providers. Some said they used smartphone apps and other tools to help patients share their demographic data with their various providers.

GAO concluded that “The ability to accurately match patient medical records across different providers is a critical part of effective health information exchange, which can benefit patient care. Quality demographic data is important for effectively matching patients’ medical records.”

However, healthcare providers must just have the best tools in the business for efficient data entry since the quality of the input will determine the kind of knowledge that can be gleaned from the data. A professional data entry company provides a range of data entry solutions catering to organizations in various fields. A reliable medical data entry services provider can increase precision of the data entry as well as lessen the practical implications for the providers.

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