Remote clinical study site monitoring and data quality scoring
First Claim
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1. A computer-implemented method, comprising:
- receiving site data from one or more clinical sites, the site data including clinical monitoring data;
converting, by a processor, the site data into a site-level data quality score using at least one single-sided or double-sided metric risk profile, wherein;
the site-level data quality score is based on at least two metrics; and
the at least one metric risk profile is based on at least clinical study data and historic clinical study data, the clinical study data being received from a plurality of clinical sites and the historic clinical study data having a statistical distribution and a benchmark related to a metric;
calculating a risk indicator based on the site-level data quality score; and
generating, by a processor, the at least one metric risk profile in at least substantially real-time by;
calculating a clinical study benchmark for at least one of the metrics based on the clinical study data;
automatically scaling the historic clinical study data statistical distribution by a ratio of the clinical study benchmark to the historic clinical study data benchmark; and
assigning risk regions, utilizing measures of statistical significance, to the scaled statistical distribution; and
outputting at least one of said risk indicator and said site-level data quality score.
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Abstract
A method for remote site monitoring includes receiving data from a data site, converting those data into a site-level quality score using a metric risk profile, and calculating a risk indicator based on the site-level quality score. The metric risk profile may be based on historic data and study data, where the study data is received from a plurality of data sites. In some embodiments, converting the data includes normalizing a value of a metric by applying to it the metric risk profile and aggregating the normalized metric values to calculate the site-level quality score. An apparatus for remote site monitoring is also described.
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Citations
29 Claims
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1. A computer-implemented method, comprising:
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receiving site data from one or more clinical sites, the site data including clinical monitoring data; converting, by a processor, the site data into a site-level data quality score using at least one single-sided or double-sided metric risk profile, wherein; the site-level data quality score is based on at least two metrics; and the at least one metric risk profile is based on at least clinical study data and historic clinical study data, the clinical study data being received from a plurality of clinical sites and the historic clinical study data having a statistical distribution and a benchmark related to a metric; calculating a risk indicator based on the site-level data quality score; and generating, by a processor, the at least one metric risk profile in at least substantially real-time by; calculating a clinical study benchmark for at least one of the metrics based on the clinical study data; automatically scaling the historic clinical study data statistical distribution by a ratio of the clinical study benchmark to the historic clinical study data benchmark; and assigning risk regions, utilizing measures of statistical significance, to the scaled statistical distribution; and outputting at least one of said risk indicator and said site-level data quality score. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An apparatus, comprising:
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a site data filter configured to receive site data from one or more clinical sites, the site data including clinical monitoring data; a processor configured to; convert the site data into a site-level data quality score using at least one single-sided or double-sided metric risk profile, wherein; the site-level data quality score is based on at least two metrics; and the at least one metric risk profile is based on at least clinical study data and historic clinical study data, the clinical study data being received from a plurality of clinical sites and the historic clinical study data having a statistical distribution and a benchmark related to a metric; calculate a risk indicator based on the site-level data quality score; and generate the at least one metric risk profile in at least substantially real-time by; calculating a clinical study benchmark for at least one of the metrics based on the clinical study data; automatically scaling the historic clinical study data statistical distribution by a ratio of the clinical study benchmark to the historic clinical study data benchmark; and assigning risk regions, utilizing measures of statistical significance, to the scaled statistical distribution; and a component configured to output at least one of said risk indicator and said site-level data quality score. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A computer readable storage medium, comprising computer executable instructions embodied therein, to be executed by a computer, for:
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receiving site data from one or more clinical sites, the site data including clinical monitoring data; converting, by a processor, the site data into a site-level data quality score using at least one single-sided or double-sided metric risk profile, wherein; the site-level data quality score is based on at least two metrics; and the at least one metric risk profile is based on at least clinical study data and historic clinical study data, the clinical study data being received from a plurality of clinical sites and the historic clinical study data having a statistical distribution and a benchmark related to a metric; calculating a risk indicator based on the site-level data quality score; and generating, by a processor, the at least one metric risk profile in at least substantially real-time by; calculating a clinical study benchmark for at least one of the metrics based on the clinical study data; automatically scaling the historic clinical study data statistical distribution by a ratio of the clinical study benchmark to the historic clinical study data benchmark; and assigning risk regions, utilizing measures of statistical significance, to the scaled statistical distribution; and outputting at least one of said risk indicator and said site-level data quality score. - View Dependent Claims (25, 26, 27, 28, 29)
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Specification