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message_templates/test

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{
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"@context": {
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"schema:isBasedOn": {
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"@type": "@id"
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},
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"schema:name": {
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"@type": "xsd:string"
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},
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"schema": "http://schema.org/",
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"pav": "http://purl.org/pav/",
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"xsd": "http://www.w3.org/2001/XMLSchema#",
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"rdfs": "http://www.w3.org/2000/01/rdf-schema#",
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"oslc:modifiedBy": {
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"@type": "@id"
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},
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"rdfs:label": {
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"@type": "xsd:string"
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},
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"skos": "http://www.w3.org/2004/02/skos/core#",
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"pav:derivedFrom": {
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"@type": "@id"
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},
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"pav:lastUpdatedOn": {
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"@type": "xsd:dateTime"
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},
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"oslc": "http://open-services.net/ns/core#",
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"pav:createdOn": {
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"@type": "xsd:dateTime"
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},
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"skos:notation": {
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"@type": "xsd:string"
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},
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"schema:description": {
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"@type": "xsd:string"
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},
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"pav:createdBy": {
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"@type": "@id"
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},
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"is_about": "http://purl.obolibrary.org/obo/IAO_0000136",
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"Name": "https://schema.metadatacenter.org/properties/26450fa6-bb2c-4126-8229-79efda7f863a",
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"Message text": "https://schema.metadatacenter.org/properties/6b9dfdf9-9c8a-4d85-8684-a24bee4b85a8",
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"Display compatibility": "https://schema.metadatacenter.org/properties/537a99db-422e-4916-88b5-f8b188b9f936",
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"Short message ID": "https://schema.metadatacenter.org/properties/cd6dcfc0-9083-4a73-bf7e-fd310b238bd6",
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"Additional message text": "https://schema.metadatacenter.org/properties/df7c7ba0-07dd-4930-aad6-62e1ca9dd6fa",
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"Default display": "https://schema.metadatacenter.org/properties/5b4f16a9-feb7-4724-8741-2739d8808760"
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},
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"@type": "http://data.bioontology.org/ontologies/PSDO/classes/http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FPSDO_0000002",
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"is_about": [
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{
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"@id": "http://purl.obolibrary.org/obo/PSDO_0000129",
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"rdfs:label": "peer 90th percentile benchmark"
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},
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{
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"@id": "http://purl.obolibrary.org/obo/PSDO_0000045",
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"rdfs:label": "social comparator element"
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},
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{
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"@id": "http://purl.obolibrary.org/obo/PSDO_0000116",
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"rdfs:label": "negative performance gap set"
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}
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],
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"Name": {
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"@value": "Opportunity to Improve Top 10 Peer Benchmark"
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},
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"Message text": [
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{
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"@value": "You may have an opportunity to improve for the measure [measure name]. Your performance was [recipient performance level], below the top 10% peer benchmark, which was [comparator performance level] this month."
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}
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],
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"Display compatibility": {
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"@value": "text-only, bar chart, line chart"
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},
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"Short message ID": {
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"@value": "28",
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"@type": "xsd:decimal"
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},
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"Additional message text": {
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"@value": "A case-by-case breakdown of your results are available at your [clinical quality dashboard (link)]. More information about the rationale for the measure [measure name] and how it is calculated is available [here (link to measure spec)]."
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},
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"Default display": {
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"@value": "bar chart"
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},
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"schema:isBasedOn": "https://repo.metadatacenter.org/templates/707d3573-8ac9-4e2c-b53b-2026a795308c",
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"schema:name": "Opportunity to Improve Top 10 Peer Benchmark",
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"schema:description": "specification for a possible precision feedback message",
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"pav:createdOn": "2023-12-06T12:21:12-08:00",
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"pav:createdBy": "https://metadatacenter.org/users/da882240-ad9e-42ea-a48b-215e54161ad3",
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"pav:lastUpdatedOn": "2024-01-27T14:07:00-08:00",
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"oslc:modifiedBy": "https://metadatacenter.org/users/da882240-ad9e-42ea-a48b-215e54161ad3",
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"@id": "https://repo.metadatacenter.org/template-instances/9e71ec9e-26f3-442a-8278-569bcd58e708"
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}
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Causal_pathway,Comparison_size,Trend_slope,Measure_achievement_recency,Loss_recency,Message_recency,Message_received_count,Measure_recency
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Better,0.5,--,--,--,-0.1,-0.1,-0.5
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Worse,0.5,--,--,--,-0.1,-0.5,-0.5
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Improving,--,0.8,--,--,-0.1,-0.1,0
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Worsening,--,0.8,--,--,-0.1,-0.5,0
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Achievement,0.5,0.8,-0.5,--,-0.1,-0.1,-0.5
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Loss,0.5,0.8,--,-0.5,-0.1,-0.5,-0.5
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Approach,0.5,0.8,-0.5,--,-0.1,-0.1,0
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Sustain better,0.5,--,--,--,-0.1,-0.1,-0.5
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Sustain worse,0.5,--,--,--,-0.1,-0.5,-0.5

signal_detectors/readme.md

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1. Improving trend
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2. Worsening trend
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### Performance events
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1. Achievement
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2. Loss
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3) [trend _detect](https://github.com/Display-Lab/precision-feedback-pipeline/blob/main/bitstomach/signals/_trend.py)
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- detects trend signals, where trend equates to the performance level rate of change month over month. This method can detect monotonic positive and negative trends over three months. The method records the slope as a moderator PSDO.performance_trend_content
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In esteemer, the moderator methods reads motivating information identified by signal detectors fro9m teh graph, extracting the values and types of moderators from the motivating information that then affect the score of a message template.
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In esteemer, the moderator methods reads motivating information identified by signal detectors from the graph, extracting the values and types of moderators from the motivating information that then affect the score of a message template.
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