STITCHING RELATED HEALTHCARE DATA TOGETHER

1 . A computing system comprising:

one or more processors; and

one or more computer-readable hardware storage devices having stored thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the computing system to perform at least:

access a plurality of healthcare datasets, each of which includes an identifier of a patient, an identifier of a healthcare provider, and an artifact, the artifact including at least one of (1) textual data, (2) image data, (3) audio data, or (4) video data associated with a condition of the patient or care of the patient;

for each of the plurality of healthcare datasets, label the healthcare dataset with one or more explicit designation labels and one or more contextual substitutable labels; and

query the plurality of healthcare datasets to identify a subset of healthcare datasets that share a same explicit designation label or a contextual substitutable label.

2 . The computing system of claim 1 , the computing system further configured to:

generate a visualization presenting the subset of healthcare datasets or data derived from the subset of healthcare datasets; or

store the subset of healthcare datasets that share a same explicit designation label or a contextual substitutable label in a storage.

3 . The computing system of claim 1 , wherein each explicit designation label indicates static information associated with a patient or care of the patient, and each contextual substitutable label indicates substitutable information associated with a condition of the patient or care of the patient.

4 . The computing system of claim 1 , wherein the computing system is further configured to link at least one of the one or more explicit designation labels to one or more contextual substitutable labels.

5 . The computing system of claim 1 , wherein querying the plurality of healthcare datasets includes querying one or more healthcare datasets that share a same particular healthcare provider or a particular patient.

6 . The computing system of claim 5 , wherein the computing system is further configured to:

identify one or more healthcare datasets as related healthcare datasets; and

store the related healthcare datasets together as a link.

7 . The computing system of claim 6 , wherein querying the plurality of healthcare datasets includes querying one or more healthcare datasets in one or more particular links.

8 . The computing system of claim 6 , wherein the computing system is further configured to:

identify one or more links as related links; and

store the related links together as a chain.

9 . The computing system of claim 8 , wherein querying the plurality of healthcare datasets includes querying one or more healthcare datasets in one or more particular chains.

10 . The computing system of claim 8 , wherein a plurality of healthcare datasets associated with a particular chief complaint are stored together in a same link or a same chain, the one or more healthcare datasets associated with the particular chief complaint comprising at least two of: (1) a healthcare dataset associated with an initial healthcare visit generating the particular chief complaint, (2) a healthcare dataset associated with assessment, (3) a healthcare dataset associated with diagnosis, (4) a healthcare dataset associated with prescriptions, (5) a healthcare dataset associated with lab results, (6) a healthcare dataset associated with therapy, or (7) a healthcare dataset associated with behavioral instructions.

11 . The computing system of claim 1 , wherein labeling at least some of the plurality of healthcare datasets with contextual substitutable labels is performed via one or more machine-learning models.

12 . The computing system of claim 11 , wherein the one or more machine-learning models include a machine-learning language model configured to convert audio or video datasets into textual datasets, or an object recognition model configured to identify an affected area based on a healthcare image dataset or a healthcare audiovisual dataset.

13 . The computing system of claim 1 , wherein the computing system is further configured to substitute one or more contextual substitutable labels with a new set of one or more contextual substitutional labels.

14 . The computing system of claim 13 , wherein the computing system is further configured to query the plurality of healthcare datasets based on a contextual substitutional label in the new set of one or more contextual substitutional labels.

15 . The computing system of claim 1 , wherein the computing system further configured to anonymize the healthcare datasets before querying the healthcare datasets.

16 . A method implemented at a computing system for stitching a plurality of related healthcare datasets, the method comprising:

accessing a plurality of healthcare datasets, each of which includes an identifier of a patient, an identifier of a healthcare provider, and an artifact, the artifact including at least one of (1) textual data, (2) image data, (3) audio data, or (4) video data associated with a condition of the patient or care of the patient;

for each of the plurality of healthcare datasets, labeling the healthcare dataset with one or more explicit designation labels and one or more contextual substitutable labels, each explicit designation label indicating static information associated with a patient, and each contextual substitutable label indicating substitutable information associated with a condition of the patient; and

querying the plurality of healthcare datasets to identify a subset of healthcare datasets that share a same explicit designation label or a contextual substitutable label.

17 . The method of claim 16 , the method further comprising:

generating a visualization presenting the subset of healthcare datasets or data derived from the subset of healthcare datasets; or

storing the subset of healthcare datasets that share a same explicit designation label or a contextual substitutable label in a storage.

18 . The method of claim 16 , wherein each explicit designation label indicates static information associated with a patient or care of the patient, and each contextual substitutable label indicates substitutable information associated with a condition of the patient or care of the patient.

19 . The method of claim 15 , wherein the computing system is further configured to link at least one of the one or more explicit designation labels to one or more contextual substitutable labels.

20 . A computer program product comprising one or more hardware storage devices having stored thereon computer-executable instructions that are structured such that, when the computer-executable instructions are executed by one or more processors of a computing system, the computer-executable instructions configure the computing system to perform at least:

access a plurality of healthcare datasets, each of which includes an identifier of a patient, an identifier of a healthcare provider, and an artifact, the artifact including at least one of (1) textual data, (2) image data, (3) audio data, or (4) video data associated with a condition of the patient or care of the patient;

for each of the plurality of healthcare datasets,

label the healthcare dataset with one or more explicit designation labels and one or more contextual substitutable labels, each explicit designation label indicating static information associated with a patient or care of the patient, and each contextual substitutable label indicating substitutable information associated with a condition of the patient or care of the patient;

store related one or more healthcare datasets in a link;

store related one or more links in a chain; and

query the plurality of healthcare datasets in one or more particular links or one or more particular chains to identify a subset of healthcare datasets that share a same contextual substitutable label or a same explicit designation label.