Patient-Reported Data's Accuracy Upheld in MS Study
Claims data is valuable for research, but patient-reports have been seen as unreliable. A study of MS patients found such data is accurate.
Patients can be trusted to self-report data about their illness correctly.
A recent study showed that self-reported data from multiple sclerosis (MS) patients can be successfully matched with billing claims data, making for a powerful tool for research and quality improvement. The study was conducted by Gabriel Eichler, PhD, of PatientsLikeMe, and colleagues, and was published in the Journal of Medical Internet Research on May 12, 2016.
The researchers state the aim of the study as being to explore “the linking of 2 disparate sources of real-world data: patient-reported data from a patient-powered research network (PatientsLikeMe) and insurance claims.” They anonymously matched patient-reported data to the insurance claims and found a high degree of concordance between them.
There were 603 participants in this study, all of whom had self-reported a diagnosis of either MS or Parkinson’s disease (PD), with MS being “the condition of primary interest” and the “PD patients were included as non-MS controls as a comparator to evaluate the accuracy of MS diagnosis reporting” according to the authors. There were 414 participants with MS and 188 had PD, while 1 person reported having both conditions.
The researchers report, “Overall, 567 of the 603 consenting patients (94%) were found in the claims dataset and were, therefore, revealed to be real patients with confirmed identities for the purposes of this study.” Additionally, the researchers were able to demonstrate concordance of a diagnosis in 93% of the patients, and importantly, between 74% and 100% there was agreement about specific disease modifying therapies (DMTs).
Claims data has long been used in research, but is an imperfect source of information for several reasons, including time lag and the lack of explanation as to why services are provided or tests administered. Being able to combine real-time, self-reported data from patients with claims data could “provide an opportunity to capture an entirely new dimension of the patient’s health care experience, that is, their account of what happened, although these are of course subject to self-reporting biases,” say the researchers.
