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GP Research – Looking Beyond the Coded Diagnosis
When it comes to coding GP research, it is vital to look beyond the coded diagnosis. In many cases, GPs do not always code a definite diagnosis on the date it was confirmed. This is especially true for diseases that rely on consultation with hospital consultants. Free text is invaluable in dating the diagnosis, ensuring that a patient’s record accurately matches the information in the coded text, and identifying misclassified cases.
GPs consent to research
If you would like to participate in a research project and want to be part of it, you will need to give your informed consent. This means that you understand what the risks are and that you are empowering the researchers to perform screening tests and study procedures. However, if you have any concerns or problems, you can withdraw your consent at any time. You can discuss these concerns with your GP.
Some GPs declined to participate in the study. This occurred during the postal questionnaire stage of the research. They did so for various reasons. In the first place, they expressed concerns over the contents of the survey and the items on suicidality. They felt that participating in the research would interfere with their clinical practice.
GPs record diagnosis in free text
Free text is the text that GPs do not routinely extract from patient records. It contains huge amounts of additional information about a diagnosis. It can confirm a diagnosis that has been coded, or show that a diagnosis was misclassified. This data can help improve decision-making, reporting, and cost analysis.
GPs record ovarian cancer diagnosis in free text
The free text records are a unique resource in primary care. They provide anonymised information about the diagnosis of ovarian cancer. However, most researchers don’t use this information because it’s difficult to access. This study aims to fill this gap by examining how much information is ‘hidden’ in free text records, as well as the time lag between the diagnosis and the Read code.
The researchers found that family doctors often take up to one month to diagnose ovarian cancer. And in that time, the diagnosis is often misclassified. In fact, 11% of cases of ovarian cancer are classified incorrectly. The study used anonymised data from 500 primary care practices and four million patients.
GPs record misclassified cases in free text
Free text is an important resource that GPs can use to determine if their cases have been misclassified. Free text records are also valuable in determining the date of diagnosis and referral. In the case of cancer, the free text records provide more information than a coded diagnosis.
The data in this dataset was collected from nine general practice practices. Physicians in the nine practices used standardized terms. They were spread across four different cities, with one clinic located in central Auckland. Together, these clinics treated approximately 4.1% of the population of the Auckland region. The GPs who took part in the pilot used a computer system that included standardized terms for data extraction. In addition to making the data extraction process easier, standardized terms increase the specificity of the data.
GPs record cancer diagnosis in free text
Free text documents are a common format in which GPs record cancer diagnosis. These texts are stored on computer systems for easy access. The data contained a range of health-related information, including consultation details, diagnoses, interventions, tests and prescriptions. GPs code diagnoses using structured clinical terminology. A new standard known as SNOMED-CT is expected to be implemented in the next few years.
To conduct the study, researchers analysed anonymised free text records for ovarian cancer diagnosis. They identified 344 women with a Read code for ovarian cancer, and compared the dates of the free text records and the coded diagnosis. They then searched for free text containing words associated with the diagnosis, such as cancer and ovary.
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