Management method and system for implementation, execution, data collection, and data analysis of a structured collection procedure which runs on a collection device

Abstract

Method embodiments for performing a structured collection protocol by utilizing a collection device comprise collecting one or more sampling sets of biomarker data, wherein each sampling set comprises a sufficient plurality of sampling instances recorded over a collection period. The methods further include determining compliance with adherence criteria for the sampling instances, wherein noncompliance with adherence criteria is recorded as an adherence event, classifying sampling instances as primary samples or secondary samples, wherein primary samples, which do not have corresponding recorded adherence events, are sampling instances utilized in the calculations performed by the processor that yield therapy results for a diabetic person, and secondary samples are sampling instances not utilized in the calculations, unless one or more secondary samples are promoted to primary samples, and performing at least one additional task if one or more sampling instances is a primary sample with a corresponding recorded adherence event.

1 . A method of performing a structured collection protocol by utilizing a collection device comprising a processor, wherein the method comprises:
 collecting one or more sampling sets of biomarker data using the collection device, wherein each sampling set comprises a sufficient plurality of sampling instances recorded over a collection period, wherein each sampling instance comprises a biomarker reading;   determining compliance with adherence criteria for the sampling instances of the sampling set via the processor, wherein noncompliance with adherence criteria is recorded as an adherence event;   classifying sampling instances as primary samples or secondary samples via the processor, wherein
 primary samples, which do not have corresponding recorded adherence events, are sampling instances utilized in calculations performed by the processor that yield therapy results for a diabetic person, and 
 secondary samples are sampling instances not utilized in calculations performed by the processor that yield therapy results for a diabetic person, unless one or more secondary samples, which do not have corresponding recorded adherence events, are promoted to primary samples; and 
   performing via the processor at least one additional task if one or more sampling instances is a primary sample with a corresponding recorded adherence event.   
     
     
         2 . The method of  claim 1  wherein the sampling instances are non-adverse sampling instances. 
     
     
         3 . The method of  claim 1  wherein the adherence criteria comprises acceptance criteria, wherein the acceptance criteria require a biomarker reading to be within an expected range. 
     
     
         4 . The method of  claim 3  wherein a biomarker reading outside of the expected range is indicative of an adverse event. 
     
     
         5 . The method of  claim 1  further comprising classifying sampling instances as tertiary samples for sampling instances which are not utilized in the calculations of the structured collection protocol and cannot be promoted to primary samples. 
     
     
         6 . The method of  claim 1  wherein the at least one additional task comprises collecting at least one additional primary sample. 
     
     
         7 . The method of  claim 1  wherein the at least one additional task comprises replacing via the processor one or more primary samples with corresponding recorded adherence events with one or more secondary samples if the secondary samples have no corresponding recorded adherence events. 
     
     
         8 . The method of  claim 7  wherein the replacement of the primary samples is performed automatically via the processor. 
     
     
         9 . The method of  claim 1  wherein the at least one additional task comprises ignoring primary samples with corresponding recorded adherence events and performing the calculations to yield therapy results to the diabetic person based on primary samples in the sampling set, which do not include corresponding recorded adherence events. 
     
     
         10 . The method of  claim 1  wherein the additional task comprises restarting the sampling set. 
     
     
         11 . The method of  claim 1  wherein the additional task comprises terminating the structured collection protocol. 
     
     
         12 . The method of  claim 1  wherein the additional task comprises contacting a healthcare provider. 
     
     
         13 . A method of performing a structured collection protocol by utilizing a collection device comprising a processor, wherein the method comprises:
 collecting a plurality of samples of biomarker data using the collection device;   classifying samples as critical if they are utilized in calculations performed by the processor that yield therapy results for a diabetic person,   determining whether critical samples were collected during a desired time window, wherein failure to collect a sample during the time window is recorded as a missed sample; and   replacing missed critical samples with other samples recorded during the desired time window.   
     
     
         14 . A collection device configured to guide a diabetic person through a structured collection protocol, comprising:
 a meter configured to measure one or more selected biomarkers;   a processor disposed inside the meter and coupled to memory, wherein the memory comprises collection procedures; and   software having instructions that when executed by the processor causes the processor to:
 instruct the diabetic person to collect one or more sampling sets of biomarker data using the collection device, wherein each sampling set comprises a sufficient plurality of sampling instances recorded over a collection period, wherein each sampling instance comprises a biomarker reading; 
 determine compliance with adherence criteria for the sampling instances of the sampling set via the processor, wherein noncompliance with adherence criteria is recorded as an adherence event; 
 classify sampling instances as primary samples or secondary samples via the processor, wherein
 primary samples, which do not have corresponding recorded adherence events, are sampling instances utilized in calculations performed by the processor that yield therapy results for a diabetic person, and 
 secondary samples are sampling instances not utilized in calculations performed by the processor that yield therapy results for a diabetic person, unless one or more secondary samples, which do not have corresponding recorded adherence events, are promoted to primary samples; and 
 
 perform via the processor at least one additional task if one or more sampling instances is a primary sample with a corresponding recorded adherence event 
   
     
     
         15 . The collection device of  claim 14  wherein the sampling instances are non-adverse sampling instances. 
     
     
         16 . The collection device of  claim 14  wherein the adherence criteria comprises acceptance criteria, wherein the acceptance criteria require a biomarker reading to be within an expected range. 
     
     
         17 . The collection device of  claim 14  wherein a biomarker reading outside of the expected range is indicative of an adverse event. 
     
     
         18 . The collection device of  claim 14  wherein sampling instances are classified as tertiary samples for sampling instances which are not utilized in the calculations of the structured collection protocol and cannot be promoted to primary samples. 
     
     
         19 . The collection device of  claim 14  wherein the at least one additional task is the collection of at least one additional primary sample. 
     
     
         20 . The collection device of  claim 14  wherein the at least one additional task is the replacement of one or more primary samples with corresponding recorded adherence events with one or more secondary samples if the secondary samples have no corresponding recorded adherence events. 
     
     
         21 . The collection device of  claim 20  wherein the replacement of the primary samples is automatic. 
     
     
         22 . The collection device of  claim 14  wherein the additional task is the termination of the structured collection protocol. 
     
     
         23 . A method of performing a structured collection protocol by utilizing a collection device comprising a processor, wherein the method comprises:
 collecting one or more sampling sets of biomarker data using the collection device, wherein each sampling set comprises a sufficient plurality of sampling instances recorded over a collection period, wherein each sampling instance comprises a biomarker reading;   determining compliance with adherence criteria for the sampling instances of the sampling set via the processor, wherein noncompliance with adherence criteria is recorded as an adherence event;   classifying sampling instances as primary samples or secondary samples via the processor; and   performing via the processor at least one additional task if one or more primary samples is recorded with a corresponding recorded adherence event, wherein the at least one additional task is calculated by the processor based on the adherence event as well as on the classification of the sampling instance.   
     
     
         24 . The method of  claim 23  wherein primary samples, which do not have corresponding recorded adherence events, are sampling instances utilized in an assessment of the structured collection protocol and secondary samples are sampling instances not utilized for the assessment performed by the processor, unless one or more secondary samples, which do not have corresponding recorded adherence events, are promoted to primary samples. 
     
     
         25 . The method of  claim 23  wherein the calculations of the structured collection protocol performed by the processor yield therapy results for a diabetic person. 
     
     
         26 . The method of  claim 23  wherein sampling instances comprising the same contextual data belong to the same sampling set. 
     
     
         27 . The method of  claim 26  wherein the contextualized data of the primary sample, which is replaced by the secondary sample, at least partially identical with the contextualized data of the secondary sample 
     
     
         28 . The method of  claim 23  wherein primary samples, which have corresponding recorded adherence events are replaced by secondary samples, which do not have corresponding recorded adherence events, and are promoted to primary samples. 
     
     
         29 . The method of  claim 23  wherein the contextualized data of the primary sample, which is replaced by the secondary sample, is at least partially identical with the contextualized data of the secondary sample