Published in:
01-08-2015 | Original Article
Web-Based Assessment of Outcomes After Subarachnoid and Intracerebral Hemorrhage: A New Patient Centered Option for Outcomes Assessment
Authors:
Andrew M. Naidech, Jennifer L. Beaumont, Michael Berman, Eric Liotta, Matthew B. Maas, Shyam Prabhakaran, Konrad Kording, Jane Holl, David Cella
Published in:
Neurocritical Care
|
Issue 1/2015
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Abstract
Background
Clinical outcomes are typically assessed by trained staff. We tested the hypothesis that outcomes reported by the patient or a caregiver on the web would be correlated with a validated interview.
Methods
We assessed surviving patients with intracerebral and subarachnoid hemorrhage at 1- , 3- , and 12-month follow-up with a validated interview for the modified Rankin Scale (mRS, a validated ordinal scale from 0, no symptoms to 5, severe disability). Health-related quality of life (HRQoL) was assessed on the web with NIH Patient-Reported Outcomes Measurement Information System (PROMIS) and Neuro-QOL using computer adaptive testing by the patient, proxy reporting by a caregiver, or proxy entry by study staff.
Results
A coincident mRS and HRQoL assessment was available for 149 (71 %) of 209 patients at one, three, or 12 months. There were 89 assessments with proxy entry by study staff, 89 by the patient on the web, and 58 with proxy report by a caregiver on the web. PROMIS physical function assessments were completed in median of 4 questions, and T scores were associated with the mRS (P < 0.001), regardless of respondent. Mean T scores in every category of the mRS were different from every other category (P ≤ 0.003 for all). Results were similar for Neuro-QOL mobility.
Conclusions
Web-based HRQoL assessment with NIH PROMIS and Neuro-QOL is feasible and correlated with a validated interview for the mRS. T scores distinguished between individual categories of the mRS, detecting modest differences in physical function and mobility HRQoL that are difficult to detect with the mRS. PROMIS and Neuro-QOL provide powerful and sensitive outcomes for potentially large cohorts.