Problem-Oriented Links

Overview

The clinician thought process when evaluating a patient, is to gather information regarding the patient’s illness or problem. This involves asking questions about the patient’s history and current symptoms, to completing a physical exam. The clinician then takes all the data points into consideration to come up with a list of possible diagnoses, then evaluates each one to arrive at the final diagnosis or diagnoses for the visit. The next step is determining what to do about the problem. This may involve medications, lab test, imaging, or patient education or counseling. That is a lot of cognitive processing every 10-15 minutes in an outpatient setting or while managing multiple patient in an inpatient setting.

Quippe supports this thought process by providing diagnostic links between diagnoses and their associated concepts.

How do these diagnostic links work?

This means that for any diagnosis, there is a list of relevant symptoms, history, exam, tests, procedures, medications, imaging studies, education/counseling, and other diagnoses. This list is accessible and useful at multiple points in a patient encounter. In the clinical workflow, these links support:

• Documentation and Completeness of the Note
• Identifying Relevant Clinical Concepts in a Patient Chart
• Guiderails for Ambient Listening
• Compliance and Regulation

At any point in the workflow, Quippe can tell you what other clinical concepts are related to a diagnosis or problem and it can tell what diagnoses any clinical concept belongs to.

Examples:

• I need to get a list of relevant concepts for progeria, a rare disease, because I don’t remember the key concepts from medical school.
• There is a medication in this patient’s chart and I need to know why it was diagnosed.
• I want to review my patient’s chart before seeing them but there is too much information to wade through; I’d like to see just what is related to their main problem.

Diagnostic Links Use Cases

Assisting with Documentation and Completeness

Use Case: Consider an outpatient visit in which a patient reports shortness of breath, cough, wheezing, weakness, and a history of smoking. You may already suspect a respiratory condition, such as bronchitis or COPD, and need a focused list of related clinical concepts to support documentation. By using data points associated with a specific diagnosis, you are presented with relevant concepts that describe the patient’s current condition—without needing to search manually or create a separate template for every diagnosis.

Quippe UI

In the Quippe UI, add any diagnosis to the note via the search. On the entered finding, perform a right mouse click and select DX Prompt.

The concepts related to the selected diagnosis are added to the note, ready for documentation.

In cases where a generic diagnosis is selected, the returned list may be only diagnoses (term type 6), meaning the initial diagnosis is too broad to be helpful. In these cases, you will be asked to select a more specific diagnosis so as to provide a more useable list of findings.

Example: congestive heart failure (MEDCIN ID 33268)

Quippe API

API: /Quippe/NoteBuilder/QuickPrompt

Documentation: GET /Quippe/NoteBuilder/QuickPrompt

Parameters:

• MedcinId: 32890
  • This is the MEDCIN ID for acute bronchitis
• ListSize: small

Response: The code snippet below shows a sample of the output.

1
{
2
  "list": {
3
    "id": "IPrompt_32890_1_0",
4
    "medcinId": 32890,
5
    "type": "list",
6
    "text": "Acute Bronchitis",
7
    "listType": "Prompt",
8
    "count": 154,
9
    "item": [
10
      {
11
        "type": "term",
12
        "medcinId": 283159,
13
        "nodeKey": "-A-NCF",
14
        "termType": 1,
15
        "text": "medication reconciliation performed",
16
        "specialty": "*",
17
        "sectionId": "S16",
18
        "groupId": "G2900",
19
        "phrasing": {
20
          "ip": "medication reconciliation performed",
21
          "in": "~2.0 not"
22
        }
23
      },
24
      {
25
        "type": "term",
26
        "medcinId": 7,
27
        "nodeKey": "-A-RGL",
28
        "termType": 1,
29
        "text": "chills [as a symptom]",
30
        "subs": "+",
31
        "specialty": "I",
32
        "sectionId": "S16",
33
        "groupId": "G1878",
34
        "phrasing": {
35
          "ip": "chills",
36
          "in": "~< no",
37
          "startContext": "-A-RGL"
38
        }
39
      },
40
      {
41
        "type": "term",
42
        "medcinId": 281327,
43
        "nodeKey": "-AAJGOIH-J",
44
        "termType": 1,
45
        "text": "chest pain made worse by breathing",
46
        "specialty": "CIOPA",
47
        "sectionId": "S16",
48
        "groupId": "G1881",
49
        "phrasing": {
50
          "ctnk": "-AAJGOIH",
51
          "ip": "chest pain ~L worsened by breathing",
52
          "in": "~2.1 not",
53
          "dp": "~L by breathing",
54
          "dn": "~0.1 not"
55
        }
56
      },
57
      {
58
        "type": "term",
59
        "medcinId": 281328,
60
        "nodeKey": "-AAJGOIH-R",
61
        "termType": 1,
62
        "text": "chest pain made worse by coughing",
63
        "subs": "+",
64
        "specialty": "CIOPA",
65
        "sectionId": "S16",
66
        "groupId": "G1881",
67
        "phrasing": {
68
          "ctnk": "-AAJGOIH",
69
          "ip": "chest pain ~L worsened by coughing",
70
          "in": "~2.1 not",
71
          "dp": "~L by coughing",
72
          "dn": "~0.1 not"
73
        }
74
      },
75
      {
76
        "type": "term",
77
        "medcinId": 353,
78
        "nodeKey": "-AALDD",
79
        "termType": 1,
80
        "text": "difficulty breathing (dyspnea)",
81
        "subs": "+",
82
        "specialty": "CIOP",
83
        "sectionId": "S16",
84
        "groupId": "G1880",
85
        "phrasing": {
86
          "ip": "difficulty breathing",
87
          "in": "~< no",
88
          "startContext": "-AALDD"
89
        }
90
      }
91
    ]
92
  }
93
}

Identifying Relevant Clinical Concepts in a Patient Chart

Use Case: With the onslaught of data in a patient’s chart, it is difficult and time consuming for a clinician to find relevant information. The patient is here for a diabetes follow-up. Great, how do you quickly identify the current state of the disease? What and when were the last A1C or glucose level? What medication is the patient taking?

The clinician requires a quick snapshot of the items relevant to diabetes and does not need to worry about the cold the patient had last year. With the diagnostic links, the clinician can see the clinical concepts related to the patient’s diabetes.

Quippe UI

Open Clinical Lens and select Seymour Patients - he has a more complete sample chart - which provides a summary of the patient’s chart. The first tab includes the most recent instance of every finding. To view the findings related to a specific diagnosis or problem, simply click on one in the Filter by Problem task pane on the right side of the window. The related findings will be highlighted in yellow.

Example view of diabetes mellitus type 2 (MEDCIN ID 30480) for Seymour Patients:

Quippe APIs

There are multiple steps in this process. One to retrieve the list of concepts related to the selected diagnosis and their node keys and one to identify findings in the chart that have similar node keys. A node key defines a concept’s place in the MEDCIN hierarchy. With the node key, we can identify (and then highlight) all the findings that start with that same node key.

For example, blood hemoglobin A1C (MEDCIN ID 12736) is related to type 2 diabetes. Its node key is -DDD-P-E-E. When looking through the patient’s chart to find concepts related to diabetes type 2, we will highlight all concepts that start with this node key. This would include not only blood hemoglobin A1C, but also is subs. This ensures that all A1C concepts are identified.

Step 1: Identify the node keys of the concepts related to the selected disease. In this use case, we want to identify findings related to diabetes mellitus, type 2, MEDCIN ID 30480.

API: /Quippe/ClinicalLens/Prompt

Documentation: GET /Quippe/ClinicalLens/Prompt

Parameters:

• SourceId: 30480
  • This is the MEDCIN ID for diabetes mellitus type 2
• SourceType: term
• ListSize: medListSmall

Response: Partial list of the associated node keys.

1
{
2
  "list": {
3
    "sourceId": 30480,
4
    "count": 135,
5
    "keys": [
6
      "-A-REX-H",
7
      "-A-RIT-D-D",
8
      "-A-RIT-D-H",
9
      "-AAA-L",
10
      "-AAD-NCN",
11
      "-AAF-PPD",
12
      "-AAN-H-H-I",
13
      "-AAP-JBL-D-P-H",
14
      "-AAP-JBL-D-T",
15
      "-AAR-F",
16
      "-AAVTNCN-C-Q-N",
17
      "-AAY-C-D",
18
      "-AAYEP-RBH-H",
19
      "-B-L-N-H-L",
20
      "-B-L-N-H-P",
21
      "-B-L-XMX-H",
22
      "-B-L-XTJ-P",
23
      "-B-L-XTN-P",
24
      "-B-S-F-P-J-H-F",
25
      "-B-SEL-L-H-C",
26
      "-C-I-H",
27
      "-C-I-P",
28
      "-C-I-T",
29
      "-C-IAA-F",
30
      "-C-IAA-H",
31
      "-C-K-D",
32
      "-C-K-L",
33
      "-C-UBNAN",
34
      "-C-UDD-L",
35
      "-C-UDDAPAW",
36
      "-C-UDDAPBA",
37
      "-C-UDDBH",
38
      "-C-X-L-H-B",
39
      "-CAZ-G-N",
40
      "-CBA-J-H-D-U",
41
      "-CBABT-L-BRD",
42
      "-CBABT-L-BRH",
43
      "-CBABT-L-BTD",
44
      "-CBABT-L-BTH",
45
      "-CBABTED",
46
      "-CCWRD",
47
      "-CDAAD-B",
48
      "-CDAAD-GBP"
49
    ]
50
  }
51
}

Step 2: Next, we need to gather the node keys of the findings in the patient’s chart.

API: /Quippe/NoteBuilder/ResolveTerms

Documentation: GET /Quippe/NoteBuilder/ResolveTerms

Parameters:

• MedcinIds: pass in all the MEDCIN IDs from the patient’s chart.

Response: Partial list of the findings in the patient chart. One of the properties provided is the nodeKey.

1
{
2
  "list": {
3
    "type": "list",
4
    "listType": "Prompt",
5
    "item": [
6
      {
7
        "medcinId": 5,
8
        "nodeKey": "-A-RGH",
9
        "termType": 1,
10
        "subs": "+",
11
        "specialty": "I",
12
        "text": "fever [as symptom]",
13
        "sectionId": "S16",
14
        "groupId": "G1878",
15
        "hasHistory": true,
16
        "phrasing": {
17
          "ip": "fever",
18
          "in": "~< no",
19
          "startContext": "-A-RGH"
20
        }
21
      },
22
      {
23
        "medcinId": 10,
24
        "nodeKey": "-AAA-L",
25
        "termType": 1,
26
        "subs": "+",
27
        "specialty": "N",
28
        "text": "headache",
29
        "sectionId": "S16",
30
        "groupId": "G1879",
31
        "hasHistory": true,
32
        "phrasing": {
33
          "ip": "headache",
34
          "in": "~< no",
35
          "startContext": "-AAA-L"
36
        }
37
      },
38
      {
39
        "medcinId": 134,
40
        "nodeKey": "-AAD-N-DED",
41
        "termType": 1,
42
        "specialty": "CNV",
43
        "text": "eye strain (asthenopia)",
44
        "sectionId": "S16",
45
        "groupId": "G2901",
46
        "hasHistory": true,
47
        "phrasing": {
48
          "ctnk": "-AAD-N-D",
49
          "ip": "eye strain",
50
          "in": "~< no"
51
        }
52
      },
53
      {
54
        "medcinId": 141,
55
        "nodeKey": "-AAF-DBY",
56
        "termType": 1,
57
        "subs": "+",
58
        "specialty": "TINOP",
59
        "text": "loss of hearing",
60
        "sectionId": "S16",
61
        "groupId": "G2902",
62
        "hasHistory": true,
63
        "phrasing": {
64
          "ctnk": "-AAF-D",
65
          "ip": "hearing loss",
66
          "in": "~< no",
67
          "startContext": "-AAF-DBY"
68
        }
69
      },
70
      {
71
        "medcinId": 147,
72
        "nodeKey": "-AAF-DED",
73
        "termType": 1,
74
        "subs": "+",
75
        "specialty": "TNOBP",
76
        "text": "earache",
77
        "sectionId": "S16",
78
        "groupId": "G2902",
79
        "hasHistory": true,
80
        "phrasing": {
81
          "ctnk": "-AAF-D",
82
          "ip": "earache",
83
          "in": "~< no",
84
          "startContext": "-AAF-DED"
85
        }
86
      },
87
      {
88
        "medcinId": 162,
89
        "nodeKey": "-AAF-HHR",
90
        "termType": 1,
91
        "subs": "+",
92
        "specialty": "TP",
93
        "text": "nasal discharge",
94
        "sectionId": "S16",
95
        "groupId": "G2902",
96
        "hasHistory": true,
97
        "phrasing": {
98
          "ctnk": "-AAF-H",
99
          "ip": "nasal discharge",
100
          "in": "~< no",
101
          "dp": "discharge",
102
          "dn": "~< no",
103
          "startContext": "-AAF-HHR"
104
        }
105
      },
106
      {
107
        "medcinId": 207,
108
        "nodeKey": "-AAR-F",
109
        "termType": 1,
110
        "subs": "+",
111
        "specialty": "CEV",
112
        "text": "excessive thirst / fluid intake (polydipsia)",
113
        "sectionId": "S16",
114
        "groupId": "G1887",
115
        "hasHistory": true,
116
        "phrasing": {
117
          "ip": "polydipsia",
118
          "in": "~< no",
119
          "startContext": "-AAR-F"
120
        }
121
      },
122
      {
123
        "medcinId": 217,
124
        "nodeKey": "-AAF-L-H",
125
        "termType": 1,
126
        "subs": "+",
127
        "specialty": "ETOP",
128
        "text": "hoarseness",
129
        "sectionId": "S16",
130
        "groupId": "G2902",
131
        "hasHistory": true,
132
        "phrasing": {
133
          "ctnk": "-AAF-L",
134
          "ip": "hoarseness",
135
          "in": "~< no",
136
          "startContext": "-AAF-L-H"
137
        }
138
      }
139
    ]
140
  }
141
}

Step 3: Compare the node keys in the patient chart with the node keys from the findings related to type 2 diabetes.

There is no specific Quippe API to accomplish this simple comparison. If a chart finding node key starts with any of the node keys in the diagnosis list, then it is related to the diagnosis. In JavaScript, this might looks something like:

1
chartFindings.filter(f => {
2
    return diagnosisNodeKeys.some(k => f.nodeKey.startsWith(k));
3
})

Guiderails for Ambient Listening

Use Case: The trend in EHR documentation now is to use ambient listening to capture the transcript of a conversation between a clinician and a patient and then translate it to a text clinical note. The unknown in this equation is the accuracy - did the tool capture the conversation and subsequent clinical concepts correctly? Did it differentiate a family history of breast cancer versus a patient history of breast cancer?

With the Quippe APIs, that clinical text note can be translated into structured Medcin findings. Once you have the structured clinical data points, the diagnostic links can be used to validate the accuracy of the note. Say the note includes diabetes and acute bronchitis as the diagnoses. The links can be used to verify that the other clinical data points in the note are associated with one of those diagnosis and alert the clinician of the outliers. If biopsy showed Bowen’s disease turned up in the note because the patient’s last name is Bowen, the clinician would be alerted and could easily remove the finding.

Quippe UI

Quippe APIs

API: /Quippe/ChartReview/ScoreNote

Documentation: POST /Quippe/ChartReview/ScoreNote

Parameters:

• Sample XML Input:

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<Chart xmlns="http://schemas.medicomp.com/V3/Chart.xsd">
2
  <Patient id="17095000" Sex="M" Race="H" BirthDate="1970-02-01T00:00:00.000">
3
    <Encounters>
4
      <Encounter EncounterTime="2026-07-27T19:16:00.000Z" id="CURRENT" Description="Basic Note_CT">
5
        <Records>
6
          <Record id="Q1" MedcinId="32998" Result="A" Text="emphysema">
7
            <CodeMaps>
8
              <Map Vocab="icd10" Code="J43.9" Description="Emphysema, unspecified" AutoMapped="true" />
9
            </CodeMaps>
10
          </Record>
11
          <Record id="Q5" MedcinId="5" Result="A" Text="fever" />
12
          <Record id="Q6" MedcinId="71911" Prefix="O" Result="A" Text="metformin HCl" />
13
          <Record id="Q2" MedcinId="41470" Prefix="O" Result="A" Text="albuterol" />
14
          <Record id="Q3" MedcinId="12194" Prefix="O" Result="A" Text="ABG panel" />
15
          <Record id="Q4" MedcinId="105598" Prefix="O" Result="A" Unit="%" Text="oxygen saturation" RangeNormalLow="93" RangeNormalHigh="100" />
16
        </Records>
17
      </Encounter>
18
    </Encounters>
19
  </Patient>
20
</Chart>

Response:

1
{
2
  "noteScores": [
3
    {
4
      "medcinId": 32998,
5
      "text": "emphysema",
6
      "score": 1,
7
      "targetIds": "Q1,Q2,Q3,Q4"
8
    }
9
  ]
10
}

In the above example, emphysema is the documented diagnosis. The related entries are Q1 (emphysema) , Q2 (albuterol), Q3 (ABG panel), and Q4 (oxygen saturation), excluding Q5 (fever) and Q6 (metformin).

Compliance and Regulation

These diagnostic links can also support the data compliance regulations. For example, when submitting E&M or HCC claims data, the requirement states the note must contain an appropriate history and physical. What does that mean and how does a clinician know if their note is compliant?

Quippe uses the diagnostic links along with coding guidelines to provide the clinician with a level of confidence that their note is compliant, at the point of care. If it is not, the diagnostic links can be used to suggest related clinical concepts to add to the note to ensure completeness. This group of APIs is the Documentation Scoring capability.

Quippe UI

The easiest way to see this in action is to add a diagnosis and some documentation to a note. The Documentation Scoring task pane is visible by default. If it is not visible, click the Settings icon in the bottom right of the window and select Documentation Scoring.

Once a diagnosis has been entered into the note (marked red, positive), it is scored and displayed in the task pane.

• Score 1 - Hazard sign with exclamation mark: The note does not support the diagnosis.
• Score 2 - Question mark: The note may or may not support the diagnosis.
• Score 3 - Green checkmark: The note is not incomplete.

For more information, see the Documentation Scoring topic.

Quippe APIs

API: /Quippe/ChartReview/ScoreNote

Documentation: POST /Quippe/ChartReview/ScoreNote

Parameters:

• Sample XML Input:

1
<Chart xmlns="http://schemas.medicomp.com/V3/Chart.xsd">
2
  <Patient id="150290" Sex="M" BirthDate="1960-05-19T00:00:00.000">
3
    <Encounters>
4
      <Encounter EncounterTime="2026-06-22T20:30:00.000Z" id="CURRENT" Description="Basic Note_CT">
5
        <Records>
6
          <Record id="Q7" MedcinId="390" Result="A" Unit="lbs" Text="recent weight loss" />
7
          <Record id="Q4" MedcinId="10" Result="A" Text="headache" />
8
          <Record id="Q5" MedcinId="113" Result="N" Text="no blurry vision" />
9
          <Record id="Q8" MedcinId="392" Result="A" Text="increased appetite" />
10
          <Record id="Q6" MedcinId="549" Result="A" Text="nocturia" />
11
          <Record id="Q9" MedcinId="303099" Result="N" Text="no dilated retinal eye exam" />
12
          <Record id="Q10" MedcinId="206255" Result="A" Text="tachycardia by auscultation" />
13
          <Record id="Q2" MedcinId="296219" Result="A" Text="decreased sensation on monofilament wire test of foot" />
14
          <Record id="Q3" MedcinId="163501" Result="A" Unit="cm" Text="ulcer on feet" />
15
          <Record id="Q1" MedcinId="30480" Result="A" Text="type 2 diabetes mellitus" />
16
          <Record id="Q38" MedcinId="194714" Prefix="O" Result="A" Text="sulfonylureas" />
17
        </Records>
18
      </Encounter>
19
    </Encounters>
20
  </Patient>
21
</Chart>

Response:

1
{
2
  "noteScores": [
3
    {
4
      "medcinId": 30480,
5
      "text": "type 2 diabetes mellitus",
6
      "score": 2,
7
      "targetIds": "Q7,Q4,Q5,Q8,Q6,Q9,Q10,Q2,Q3,Q1,Q38"
8
    }
9
  ]
10
}

Resources

Help Library > End Users:

• Prompt

• Clinical Lens

• Documentation Scoring