Merge pull request #99 from Display-Lab/main

mackgalante · web-flow · commit b8f7ba1cf5f1 · 2023-05-30T22:18:53.000-04:00
merge main changes with loss template patch
diff --git a/vignettes/goal_gain_vignette/readme.md b/vignettes/goal_gain_vignette/readme.md
@@ -1,10 +1,10 @@
 # Goal Gain Vignette
 
-## Introduction
-Clinical performance feedback commonly includes peer comparison because it helps providers to understand how their care differs from the norm, and may motivate them to improve the care they provide to align with peers. Peer comparison feedback may also motivate providers to maintain a social status of being a high performer, once they have achieved it. The Social Better Causal Pathway specifies feedback messages that are capable of motivating providers through the delivery of information about high performance, relative to peers. Example messages that uses the social better pathway are "You are a top performer" and "Congratulations, your performance was in the top 10% of providers this month." This vignette serves the purpose of illustrating how a precision feedback system uses the Social Better Causal Pathway to motivate providers. 
+## Introduction 
+Clinical performance feedback commonly includes comparison to goals because it helps providers to understand how their care differs from the norm, and may motivate them to improve the care they provide. Goal comparison feedback may also motivate providers to maintain the status of being a high performer, once they have achieved it by showing performance that became better than that of a goal comparator. The Goal Gain Pathway specifies feedback messages that are capable of motivating providers through the delivery of information about achieving goals. An example messages that uses the goal gain pathway is "You reached the goal." This vignette serves the purpose of illustrating how a precision feedback system uses the Goal Gain Pathway to motivate providers. 
 
 ## Performance Data
-MPOG has received operative case data from last month about Alice and Bob's cases and that of their peers. MPOG calculates the following performance information for the measure SUS-04:
+MPOG has received operative case data from last month about Eugene and Gaile's cases and that of their peers. MPOG calculates the following performance information for the measure [TOC-01: Intraoperative Transfer of Care<sub>(MPOG)</sub>](https://spec.mpog.org/Spec/Public/29). 
 
 ### Healthcare professionals
 Alice has a performance level of 97%.
@@ -14,12 +14,10 @@ Alice's peer benchmarks for last month are 93% for the top 25% peer benchmark (7
 
 ## Preference data
 Preferences for precision feedback are elicited through a preference survey that providers can take. The preference survey produces a preference model for each provider that, with the provider's permission, is shared with MPOG to maintain. MPOG analyses preferences data that is shared to identify population-level preference segments. These are generates as preference profiles that can serve as a default preference model for an organization, or which can be selected by providers who do not take the preference survey, but who identify preferences that are close enough to their own in the settings menu for the precision feedback system.
-
 Alice's preference data: (TODO)
 
 # Precision feedback system
 To generate precision feedback, MPOG sends de-identified performance and preference data to a precision feedback system that processes each provider's data with their peer comparator performance data, to select an optimal precision feedback message. 
-
 The precision feedback system is a knowledge-based system that is comprised of the following parts: 1) A knowledge base, 2) A software pipeline, and 3) A web service.
 
 ## Precision Feedback Knowledge Base
@@ -30,16 +28,13 @@ The causal pathway "social better" describes the influence of feedback intervent
 
 ### Preconditions
 Preconditions for social better are factors that are necessary for the success of the feedback intervention that uses the social better pathway. The social better pathway has the following preconditions:
-
 Information content preconditions:
 1. Social comparator content (http://purl.obolibrary.org/obo/psdo_0000095)
 2. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104)
-
 Message preconditions:
 1. Social comparator element (http://purl.obolibrary.org/obo/psdo_0000045)
 2. Positive performance gap set (http://purl.obolibrary.org/obo/psdo_0000117)
 
-
 ### Moderators
 Moderators are factors that inhibit or promote the influence of the feedback intervention on the recipient. The social better causal pathway has the following moderators:
 1. Habituation: How many times has the recipient previously received this message in the last year?
@@ -55,10 +50,8 @@ Mechanisms are factors that the intervention operates through to influence the f
 ### Outcomes
 The expected outcome of the successful influence of an email that uses the social better pathway is clinical process performance improvement or sustainment.
 
-
 ## Message templates
 Message templates represent a possible motivational message that a precision feedback system can send. There are two message templates that the precision feedback system can access for this vignette: 
-
 A. The [Top 10 Performer](https://github.com/Display-Lab/knowledge-base/blob/social_better/message_templates/top_10_performer.json) message template contains the following message:
 "Congratulations on your high performance last month! Your performance was above the 90th percentile of [Top 10% Benchmark performance level] for the measure [performance measure name]. Your performance was [recipient performance level]."
 This message template is about a positive performance gap set and a social comparator element (the MPOG Top 10% Benchmark), and is specified to be about (http://purl.obolibrary.org/obo/IAO_0000136) the following metadata:
@@ -71,52 +64,39 @@ This message template is about a positive performance gap set and a social compa
 
 ### Recipient annotations (Bitstomach)
 The first stage of the pipeline analyzes performance to identify features of performance, such as comparisons and trends that are related to motivation. The analysis from this stage results in the following annotations:
-
 Alice's annotations indicate the presence of information content about a social comparator and a positive performance gap for both the Top 10% and Top 25% Benchmarks:
 1. Social comparator content (http://purl.obolibrary.org/obo/psdo_0000095)
 2. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 10% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000129)
 3. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 25% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000128)
-
 ### Candidate Message Generation (Candidate Smasher)
 The second stage of the pipeline creates possible messages by associating the annotations for Alice and Bob with each message template, so that two candidate messages are created for each person.
-
 Alice's candidate messages:
-
 A. Candidate A has the following annotations:
-
 The [Top 10 Performer](https://github.com/Display-Lab/knowledge-base/blob/social_better/message_templates/top_10_performer.json) message template is about:
 1. Social comparator element (http://purl.obolibrary.org/obo/psdo_0000045)
 2. Positive performance gap set (http://purl.obolibrary.org/obo/psdo_0000117)
 3. Top 10% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000129)
 4. Display format compatibility: Line graph (http://purl.obolibrary.org/obo/IAO_0000573), bar chart (http://purl.obolibrary.org/obo/STATO_0000166)
-
 Alice's performance is about:
 1. Social comparator content (http://purl.obolibrary.org/obo/psdo_0000095)
 2. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 10% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000129)
 3. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 25% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000128)
-
 B. Candidate B has the following annotations:
-
 The [Top 25 Performer](https://github.com/Display-Lab/knowledge-base/blob/social_better/message_templates/top_25_performer.json) message template is about:
 1. Social comparator element (http://purl.obolibrary.org/obo/psdo_0000045)
 2. Positive performance gap set (http://purl.obolibrary.org/obo/psdo_0000117)
 3. Top 25% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000128)
 4. Display format compatibility: Line graph (http://purl.obolibrary.org/obo/IAO_0000573), bar chart (http://purl.obolibrary.org/obo/STATO_0000166)
-
 Alice's performance is about:
 1. Social comparator content (http://purl.obolibrary.org/obo/psdo_0000095)
 2. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 10% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000129)
 3. Positive performance gap content (http://purl.obolibrary.org/obo/psdo_0000104) regarding comparator Top 25% Benchmark Comparator (http://purl.obolibrary.org/obo/psdo_0000128)
-
 ### Candidate Message Preconditions Evaluation (Think Pudding)
 For Alice, both candidates have matching preconditions with social better, and are indicated as acceptable for ranking in the next stage of the pipeline:
-
 1. Candidate A acceptable by social better
 2. Candidate B acceptable by social better
-
 ### Candidate Message Moderator Evaluation and Selection (Esteemer)
 TODO
-
 ### Message Generation and Delivery (Pictoralist)
 TODO
 
diff --git a/vignettes/improving_vignette/readme.md b/vignettes/improving_vignette/readme.md
@@ -78,10 +78,10 @@ This pathway describes the influence of feedback interventions that show the mes
 Preconditions for improving are factors that are necessary for the success of the feedback intervention using this pathway. The improving pathway has the following preconditions:
 
 Information content preconditions:
-1. Positive performance trend content (http://purl.obolibrary.org/obo/PSDO_0000099)
+1. [Positive performance trend content<sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/PSDO/?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FPSDO_0000099)
 
 Message preconditions:
-1. Positive performance trend set (http://purl.obolibrary.org/obo/PSDO_0000120)
+1. [Positive performance trend set<sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/PSDO/?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FPSDO_0000120)
  
 ### Moderators 
 Moderators are factors that inhibit or promote the influence of the feedback intervention on the recipient. The social loss causal pathway has the following moderators:
@@ -101,14 +101,17 @@ The expected outcome of the successful influence of an email that uses the impro
 ## Message templates (TODO)
 Message templates represent a possible motivational message that a precision feedback system can send. There are two message templates that the precision feedback system can access for this vignette: 
 
-A. The [Performance Improving](https://github.com/Display-Lab/knowledge-base/...json TODO) message template contains the following message: "Your performance is improving this month for the measure [measure name].". This message template [is about] (http://purl.obolibrary.org/obo/IAO_0000136) the following features of performance data:
-1. Positive performance trend set (http://purl.obolibrary.org/obo/PSDO_0000120)
-2. Display format compatibility: Line graph (http://purl.obolibrary.org/obo/IAO_0000573), bar chart (http://purl.obolibrary.org/obo/STATO_0000166), text only (TODO ?)
+A. The [Performance Improving](https://github.com/Display-Lab/knowledge-base/...json TODO) message template contains the following message: "Your performance is improving this month for the measure [measure name].". This message template [is about<sub>(OB)</sub>](http://purl.obolibrary.org/obo/IAO_0000136) the following features of performance data:
 
-B. The [Congrats Improved Performance](https://github.com/Display-Lab/knowledge-base/blob/...json TODO) message template contains the following message: "Congratulations on your improved performance this month for the measure [measure name]." This message template [is about] (http://purl.obolibrary.org/obo/IAO_0000136) the following features of performance data:
+1. [Positive performance trend set<sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/PSDO/?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FPSDO_0000120)
 
-1. Positive performance trend set (http://purl.obolibrary.org/obo/PSDO_0000120)
-2. Display format compatibility: Line graph (http://purl.obolibrary.org/obo/IAO_0000573), bar chart (http://purl.obolibrary.org/obo/STATO_0000166), text only (TODO ?)
+2. Display format compatibility: [Line Graph <sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/IAO?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FIAO_0000573), [Bar Chart <sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/STATO?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FSTATO_0000166), text only (TODO ?)
+
+B. The [Congrats Improved Performance](https://github.com/Display-Lab/knowledge-base/blob/...json TODO) message template contains the following message: "Congratulations on your improved performance this month for the measure [measure name]." This message template [is about<sub>(BP)</sub>](http://purl.obolibrary.org/obo/IAO_0000136) the following features of performance data:
+
+1. [Positive performance trend set<sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/PSDO/?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FPSDO_0000120)
+
+2. Display format compatibility: [Line Graph <sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/IAO?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FIAO_0000573), [Bar Chart <sub>(BP)</sub>](https://bioportal.bioontology.org/ontologies/STATO?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FSTATO_0000166), text only (TODO ?)
 
 ## Software Pipeline (Precision Feedback Pipeline) TODO
 
diff --git a/vignettes/social_approach_vignette/readme.md b/vignettes/social_approach_vignette/readme.md
@@ -15,23 +15,23 @@ Bob, a nurse anesthetist (CRNA) at Max Commuity Hospital, has the following perf
 
 |Month|Performance Level|Top 10% Benchmark|Peer Average|
 |-----|-----------------|-----------------|------------|
-|Oct  |              xx%|               xx|          xx|
-|Nov  |              85%|               95|          87|
-|Dec  |              85%|               93|          85|
-|Jan  |              87%|               96|          88|
-|Feb  |              88%|               97|          87|
-|Mar  |              91%|               95|          86|
+|Oct  |              84%|               90|          85|
+|Nov  |              85%|               92|          86|
+|Dec  |              85%|               93|          87|
+|Jan  |              83%|               92|          86|
+|Feb  |              81%|               92|          86|
+|Mar  |              83%|               91|          85|
 
 Deepa, another CRNA at Midwest Medicine, a medical-school affiliated hospital, has the following performance data over the last 6 months for the FLUID-01-NC measure:
 
 |Month|Performance Level|Top 10% Benchmark|Peer Average|
 |-----|-----------------|-----------------|------------|
-|Oct  |              xx%|               xx|          xx|
-|Nov  |              95%|               95|          87|
-|Dec  |              94%|               93|          85|
-|Jan  |              92%|               96|          88|
-|Feb  |              94%|               97|          87|
-|Mar  |              97%|               95|          86|
+|Oct  |              83%|               93|          85|
+|Nov  |              84%|               95|          87|
+|Dec  |              85%|               93|          85|
+|Jan  |              84%|               92|          88|
+|Feb  |              84%|               93|          87|
+|Mar  |              85%|               91|          86|
 
 ## Preference data
 Preferences for precision feedback are elicited through a preference survey that providers can take. The preference survey produces a preference model for each provider that, with the provider's permission, is shared with MPOG to maintain. MPOG analyses preferences data that is shared to identify population-level preference segments. These are generates as preference profiles that can serve as a default preference model for an organization, or which can be selected by providers who do not take the preference survey, but who identify preferences that are close enough to their own in the settings menu for the precision feedback system.
diff --git a/vignettes/social_better_vignette/readme.md b/vignettes/social_better_vignette/readme.md
@@ -16,23 +16,23 @@ Alice, an attending anesthesiologist at Midwest Medicine, has the following perf
 
 |Month|Performance Level|Top 10% Benchmark|Peer Average|
 |-----|-----------------|-----------------|------------|
-|Aug  |              6/7|               94|          88|
-|sep  |              16/19|               99|          91|
-|Oct  |              xx%|               95|          88|
+|Aug  |              86%|               94|          88|
+|sep  |              84%|               99|          91|
+|Oct  |              86%|               95|          88|
 |Nov  |              89%|               98|          93|
-|Dec  |              87%|               98|          94|
-|Jan  |              86%|               96|          90|
+|Dec  |              90%|               98|          94|
+|Jan  |              92%|               96|          90|
 
 Gaile, a resident anesthesiologist at Midwest Medicine, has the following performance data over the last 6 months for SUS-04:
 
 |Month|Performance Level|Top 10% Benchmark|Peer Average|
 |-----|-----------------|-----------------|------------|
-|Aug  |              6/7|               94|          88|
-|sep  |              16/19|               99|          91|
-|Oct  |              xx%|               95|          88|
-|Nov  |              89%|               98|          93|
-|Dec  |              87%|               98|          94|
-|Jan  |              86%|               96|          90|
+|Aug  |              88%|               94|          91|
+|sep  |              89%|               99|          92|
+|Oct  |              90%|               95|          89|
+|Nov  |              90%|               98|          91|
+|Dec  |              91%|               98|          92|
+|Jan  |              93%|               96|          91|
 
 ## Preference data
 Preferences for precision feedback are elicited through a preference survey that providers can take. The preference survey produces a preference model for each provider that, with the provider's permission, is shared with MPOG to maintain. MPOG analyses preferences data that is shared to identify population-level preference segments. These are generates as preference profiles that can serve as a default preference model for an organization, or which can be selected by providers who do not take the preference survey, but who identify preferences that are close enough to their own in the settings menu for the precision feedback system.
diff --git a/vignettes/worsening_vignette/readme.md b/vignettes/worsening_vignette/readme.md
