Systems and methods for reducing data collection burden
A system for reducing data collection burden, comprising: one or more programs including instructions for: receiving a first set of metrics for a plurality of facilities; receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities; determining one or more anomalies in the received data; removing the determined one or more anomalies from the received data; selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.
1. A system for reducing data collection burden, comprising:
one or more processors;
memory;
one or more programs configured for execution by the one or more processors, the one or more programs including instructions for:
receiving a first set of metrics for a plurality of facilities, the plurality of facilities having a total number of facilities;
receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities;
determining one or more anomalies in the received data;
removing the determined one or more anomalies from the received data;
selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and
outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.
2. The system of claim 1 , wherein the one or more anomalies are determined by Robust Principal Component Analysis (RPCA).
3. The system of claim 2 , wherein the one or more anomalies determined by RPCA are interpreted as a guidance for selecting the second set of metrics.
4. The system of claim 1 , wherein the one or more programs includes instructions for inserting anomalies into the received data and determining a value of a parameter associated with a protocol, the value configured to enable the protocol to detect the inserted anomalies and select the second set of metrics.
5. The system of claim 1 , wherein the one or more programs includes instructions for determining an accuracy of the recommendation.
6. The system of claim 1 , wherein the second set of metrics is selected by Sparse Principal Component Analysis (SPCA).
7. The system of claim 1 , wherein the one or more programs includes instructions for computing a variable configured to infer non-selected metrics of the first set of metrics that are not included in the second set of metrics.
8. The system of claim 7 , wherein the one or more programs includes instructions for inferring the non-selected metrics of the first set of metrics that are not included in the second set of metrics based on the computed variable.
9. The system of claim 1 , wherein the recommendation is configured to recommend the second set of metrics for reducing a data processing burden of the received data without appreciable loss of information.
10. The system of claim 1 , wherein the received data includes one or more of real data and synthetic data.
11. The system of claim 1 , wherein selecting the second set of metrics includes selecting metrics from the first set of metrics that are less expensive to measure than non-selected metrics of the first set of metrics, the non-selected metrics are not included in the second set of metrics.
12. The system of claim 1 , wherein selecting the second set of metrics includes selecting metrics in which a probability of one or more anomalies in the received data associated with the second set of metrics is smaller than a probability of one or more anomalies in the received data associated with the first set of metrics, the non-selected metrics are not included in the second set of metrics.
13. The system of claim 1 , wherein the recommendation includes guidance, the guidance comprising one or more of: avoiding data points identified to be associated with the one or more anomalies and using the second set of metrics.
14. The system of claim 1 , wherein the data is associated with one or more metrics from one or more of Group Practice Reporting Option Features, Consumer Assessment of Healthcare Providers Survey Features, and Electronic Health Record Features.
15. A method for reducing data collection burden, comprising:
receiving a first set of metrics for a plurality of facilities, the plurality of facilities having a total number of facilities;
receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities;
determining one or more anomalies in the received data;
removing the determined one or more anomalies from the received data;
selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and
outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.
16. The method of claim 15 , wherein the one or more anomalies are determined by Robust Principal Component Analysis (RPCA).
17. The method of claim 15 , wherein the one or more anomalies determined by RPCA are interpreted as a guidance for selecting the second set of metrics.
18. The method of claim 15 , comprising inserting anomalies into the received data and determining a value of a parameter associated with a protocol, the value configured to enable the protocol to detect the inserted anomalies and select the second set of metrics.
19. The method of claim 15 , comprising determining an accuracy of the recommendation.
20. The method of claim 15 , wherein the second set of metrics is selected by Sparse Principal Component Analysis (SPCA).
21. The method of claim 15 , comprising computing a variable configured to infer non-selected metrics of the first set of metrics that are not included in the second set of metrics.
22. The method of claim 21 , comprising inferring the non-selected metrics of the first set of metrics that are not included in the second set of metrics based on the computed variable.
23. The method of claim 15 , wherein the recommendation is configured to recommend the second set of metrics for reducing a data processing burden of the received data without appreciable loss of information.
24. The method of claim 15 , wherein the received data includes one or more of real data and synthetic data.
25. The method of claim 15 , wherein selecting the second set of metrics includes selecting metrics that are less expensive to measure than non-selected metrics of the first set of metrics, the non-selected metrics are not included in the second set of metrics.
26. The method of claim 15 , wherein selecting the second set of metrics includes selecting metrics in which a probability of one or more anomalies in the received data associated with the second set of metrics is smaller than a probability of one or more anomalies in the received data associated with the first set of metrics, the non-selected metrics are not included in the second set of metrics.
27. The method of claim 15 , wherein the recommendation includes guidance, the guidance comprising one or more of: avoiding data points identified to be associated with the one or more anomalies and using the second set of metrics.
28. The method of claim 15 , wherein the data is associated with one or more metrics from one or more of Group Practice Reporting Option Features, Consumer Assessment of Healthcare Providers Survey Features, and Electronic Health Record Features.
29. A non-transitory computer readable storage medium storing one or more programs, the one or more programs configured to reduce a data processing burden, the one or more programs comprising instructions, which when executed by an electronic device, cause the device to:
receive a first set of metrics for a plurality of facilities, the plurality of facilities having a total number of facilities;
receive data associated with the first set of metrics from one or more facilities of the plurality of facilities;
determine one or more anomalies in the received data;
remove the determined one or more anomalies from the received data;
select a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and
output a recommendation applicable to the plurality of facilities based on the second set of metrics.
30. The non-transitory computer readable storage medium of claim 29 , wherein the plurality of anomalies are determined by Robust Principal Component Analysis (RPCA).
31. The non-transitory computer readable storage medium of claim 30 , wherein the one or more anomalies determined by RPCA are interpreted as a guidance for selecting the second set of metrics.
32. The non-transitory computer readable storage medium of claim 29 , wherein the one or more programs includes instructions for inserting anomalies into the received data and determining a value of a parameter associated with a protocol, the value configured to enable the protocol to detect the inserted anomalies and select the second set of metrics.
33. The non-transitory computer readable storage medium of claim 29 , wherein the one or more programs includes instructions for determining an accuracy of the recommendation.
34. The non-transitory computer readable storage medium of claim 29 , wherein the second set of metrics is selected by Sparse Principal Component Analysis (SPCA).
35. The non-transitory computer readable storage medium of claim 29 , wherein the one or more programs includes instructions for computing a variable configured to infer non-selected metrics of the first set of metrics that are not included in the second set of metrics.
36. The non-transitory computer readable storage medium of claim 35 , wherein the one or more programs includes instructions for inferring the non-selected metrics of the first set of metrics that are not included in the second set of metrics based on the computed variable.
37. The non-transitory computer readable storage medium of claim 29 , wherein the recommendation is configured to recommend the second set of metrics for reducing a data processing burden of the received data without appreciable loss of information.
38. The non-transitory computer readable storage medium of claim 29 , wherein the received data includes one or more of real data and synthetic data.
39. The non-transitory computer readable storage medium of claim 29 , wherein selection of the second set of metrics includes selection of metrics that are less expensive to measure than non-selected metrics of the first set of metrics, the non-selected metrics are not included in the second set of metrics.
40. The non-transitory computer readable storage medium of claim 29 , wherein selection of the second set of metrics includes selection of metrics in which a probability of one or more anomalies in the received data associated with the second set of metrics is smaller than a probability of one or more anomalies in the received data associated with the first set of metrics, the non-selected metrics are not included in the second set of metrics.
41. The non-transitory computer readable storage medium of claim 29 , wherein the recommendation includes guidance, the guidance comprising one or more of: avoiding data points identified to be associated with the one or more anomalies and using the second set of metrics.
42. The non-transitory computer readable storage medium of claim 29 , wherein the data is associated with one or more metrics from one or more of Group Practice Reporting Option Features, Consumer Assessment of Healthcare Providers Survey Features, and Electronic Health Record Features.