How to create an aggregate based on unique elements as fields?
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I am trying to aggregate documents based on diagnosisType, and at a higher level patientKey and encounterKey. This is what the documents look like:
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "medical_history",
"diagnosisCode" : "Z87.81",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "problem_list",
"diagnosisCode" : "2x.2",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "D21.01",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "X2.31",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "problem_list",
"diagnosisCode" : "p.2342",
}
This is what I would like the aggregate to look like:
{
"patientKey": 1,
"encounters":[{
encounterKey: 2,
medical_history: [Z87.81],
problem_list: [2x.2]
},
{
encounterKey: 3,
medical_history: [D21.01, X2.31],
problem_list: [p.2342]
}]
}
Any ideas how I could approach this?
I have tried the following for medical history and then problem list, my initial thought is to first aggregate on Problem List and then on Medical History, then combine the collections, afterwards do another aggregate based on encounters, and then finally another aggregate on patientid.
But it's a problem combining heterogeous documents.
db.collections.aggregate([
{$match:{diagnosisType:"Problem List"}},
{$group:{_id:"$encounterKey",
"ProblemList": {$push:{$concat:"$diagnosisCode"}},
"durableKey":{$first:"$durableKey"}}},
{$project:{_id:0,
encounterKey:"$_id",
ProblemList:1,
durableKey:1}},
{$out:"output"}
],{
allowDiskUse: true
})
mongodb aggregation-framework
edited Jan 4 at 17:20
mickl
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
add a comment |
I am trying to aggregate documents based on diagnosisType, and at a higher level patientKey and encounterKey. This is what the documents look like:
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "medical_history",
"diagnosisCode" : "Z87.81",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "problem_list",
"diagnosisCode" : "2x.2",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "D21.01",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "X2.31",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "problem_list",
"diagnosisCode" : "p.2342",
}
This is what I would like the aggregate to look like:
{
"patientKey": 1,
"encounters":[{
encounterKey: 2,
medical_history: [Z87.81],
problem_list: [2x.2]
},
{
encounterKey: 3,
medical_history: [D21.01, X2.31],
problem_list: [p.2342]
}]
}
Any ideas how I could approach this?
I have tried the following for medical history and then problem list, my initial thought is to first aggregate on Problem List and then on Medical History, then combine the collections, afterwards do another aggregate based on encounters, and then finally another aggregate on patientid.
But it's a problem combining heterogeous documents.
db.collections.aggregate([
{$match:{diagnosisType:"Problem List"}},
{$group:{_id:"$encounterKey",
"ProblemList": {$push:{$concat:"$diagnosisCode"}},
"durableKey":{$first:"$durableKey"}}},
{$project:{_id:0,
encounterKey:"$_id",
ProblemList:1,
durableKey:1}},
{$out:"output"}
],{
allowDiskUse: true
})
mongodb aggregation-framework
edited Jan 4 at 17:20
mickl
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
add a comment |
I am trying to aggregate documents based on diagnosisType, and at a higher level patientKey and encounterKey. This is what the documents look like:
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "medical_history",
"diagnosisCode" : "Z87.81",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "problem_list",
"diagnosisCode" : "2x.2",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "D21.01",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "X2.31",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "problem_list",
"diagnosisCode" : "p.2342",
}
This is what I would like the aggregate to look like:
{
"patientKey": 1,
"encounters":[{
encounterKey: 2,
medical_history: [Z87.81],
problem_list: [2x.2]
},
{
encounterKey: 3,
medical_history: [D21.01, X2.31],
problem_list: [p.2342]
}]
}
Any ideas how I could approach this?
I have tried the following for medical history and then problem list, my initial thought is to first aggregate on Problem List and then on Medical History, then combine the collections, afterwards do another aggregate based on encounters, and then finally another aggregate on patientid.
But it's a problem combining heterogeous documents.
db.collections.aggregate([
{$match:{diagnosisType:"Problem List"}},
{$group:{_id:"$encounterKey",
"ProblemList": {$push:{$concat:"$diagnosisCode"}},
"durableKey":{$first:"$durableKey"}}},
{$project:{_id:0,
encounterKey:"$_id",
ProblemList:1,
durableKey:1}},
{$out:"output"}
],{
allowDiskUse: true
})
mongodb aggregation-framework
edited Jan 4 at 17:20
mickl
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
I am trying to aggregate documents based on diagnosisType, and at a higher level patientKey and encounterKey. This is what the documents look like:
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "medical_history",
"diagnosisCode" : "Z87.81",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 2,
"diagnosisType" : "problem_list",
"diagnosisCode" : "2x.2",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "D21.01",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "medical_history",
"diagnosisCode" : "X2.31",
}
{
"_id" : ObjectId("...."),
"patientKey" : 1,
"encounterKey" : 3,
"diagnosisType" : "problem_list",
"diagnosisCode" : "p.2342",
}
This is what I would like the aggregate to look like:
{
"patientKey": 1,
"encounters":[{
encounterKey: 2,
medical_history: [Z87.81],
problem_list: [2x.2]
},
{
encounterKey: 3,
medical_history: [D21.01, X2.31],
problem_list: [p.2342]
}]
}
Any ideas how I could approach this?
I have tried the following for medical history and then problem list, my initial thought is to first aggregate on Problem List and then on Medical History, then combine the collections, afterwards do another aggregate based on encounters, and then finally another aggregate on patientid.
But it's a problem combining heterogeous documents.
db.collections.aggregate([
{$match:{diagnosisType:"Problem List"}},
{$group:{_id:"$encounterKey",
"ProblemList": {$push:{$concat:"$diagnosisCode"}},
"durableKey":{$first:"$durableKey"}}},
{$project:{_id:0,
encounterKey:"$_id",
ProblemList:1,
durableKey:1}},
{$out:"output"}
],{
allowDiskUse: true
})
mongodb aggregation-framework
mongodb aggregation-framework
edited Jan 4 at 17:20
mickl
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
edited Jan 4 at 17:20
mickl
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
edited Jan 4 at 17:20
mickl
16.3k61741
edited Jan 4 at 17:20
mickl
16.3k61741
edited Jan 4 at 17:20
mickl
16.3k61741
16.3k61741
asked Jan 4 at 16:56
user252046user252046
6318
asked Jan 4 at 16:56
user252046user252046
6318
asked Jan 4 at 16:56
user252046user252046
6318
6318
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
You can use below aggregation:
db.col.aggregate([
{
$group: {
_id: { patientKey: "$patientKey", encounterKey: "$encounterKey", diagnosisType: "$diagnosisType" },
problem_list: { $push: "$diagnosisCode" }
}
},
{
$group: {
_id: { patientKey: "$_id.patientKey", encounterKey: "$_id.encounterKey" },
encounters: { $push: { k: "$_id.diagnosisType", v: "$problem_list" } }
}
},
{
$project: {
encounters: { $arrayToObject: "$encounters" }
}
},
{
$group: {
_id: "$_id.patientKey",
encounters: {
$push: {
encounterKey: "$_id.encounterKey",
problem_list: "$encounters.problem_list",
medical_history: "$encounters.medical_history"
}
}
}
},
{
$project: {
patientKey: "$_id",
_id: 0,
encounters: 1
}
}
])
Basically you need few $group stages to accumulate the data. Additionally you have to use $arrayToObject to build your JSON keys dynamically.
Outputs:
{
"patientKey" : 1,
"encounters" : [
{
"encounterKey" : 2,
"problem_list" : [
"2x.2"
],
"medical_history" : [
"Z87.81"
]
},
{
"encounterKey" : 3,
"problem_list" : [
"p.2342"
],
"medical_history" : [
"D21.01",
"X2.31"
]
}
]
}
answered Jan 4 at 17:14
micklmickl
16.3k61741
add a comment |
Your Answer
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can use below aggregation:
db.col.aggregate([
{
$group: {
_id: { patientKey: "$patientKey", encounterKey: "$encounterKey", diagnosisType: "$diagnosisType" },
problem_list: { $push: "$diagnosisCode" }
}
},
{
$group: {
_id: { patientKey: "$_id.patientKey", encounterKey: "$_id.encounterKey" },
encounters: { $push: { k: "$_id.diagnosisType", v: "$problem_list" } }
}
},
{
$project: {
encounters: { $arrayToObject: "$encounters" }
}
},
{
$group: {
_id: "$_id.patientKey",
encounters: {
$push: {
encounterKey: "$_id.encounterKey",
problem_list: "$encounters.problem_list",
medical_history: "$encounters.medical_history"
}
}
}
},
{
$project: {
patientKey: "$_id",
_id: 0,
encounters: 1
}
}
])
Basically you need few $group stages to accumulate the data. Additionally you have to use $arrayToObject to build your JSON keys dynamically.
Outputs:
{
"patientKey" : 1,
"encounters" : [
{
"encounterKey" : 2,
"problem_list" : [
"2x.2"
],
"medical_history" : [
"Z87.81"
]
},
{
"encounterKey" : 3,
"problem_list" : [
"p.2342"
],
"medical_history" : [
"D21.01",
"X2.31"
]
}
]
}
answered Jan 4 at 17:14
micklmickl
16.3k61741
add a comment |
You can use below aggregation:
db.col.aggregate([
{
$group: {
_id: { patientKey: "$patientKey", encounterKey: "$encounterKey", diagnosisType: "$diagnosisType" },
problem_list: { $push: "$diagnosisCode" }
}
},
{
$group: {
_id: { patientKey: "$_id.patientKey", encounterKey: "$_id.encounterKey" },
encounters: { $push: { k: "$_id.diagnosisType", v: "$problem_list" } }
}
},
{
$project: {
encounters: { $arrayToObject: "$encounters" }
}
},
{
$group: {
_id: "$_id.patientKey",
encounters: {
$push: {
encounterKey: "$_id.encounterKey",
problem_list: "$encounters.problem_list",
medical_history: "$encounters.medical_history"
}
}
}
},
{
$project: {
patientKey: "$_id",
_id: 0,
encounters: 1
}
}
])
Basically you need few $group stages to accumulate the data. Additionally you have to use $arrayToObject to build your JSON keys dynamically.
Outputs:
{
"patientKey" : 1,
"encounters" : [
{
"encounterKey" : 2,
"problem_list" : [
"2x.2"
],
"medical_history" : [
"Z87.81"
]
},
{
"encounterKey" : 3,
"problem_list" : [
"p.2342"
],
"medical_history" : [
"D21.01",
"X2.31"
]
}
]
}
answered Jan 4 at 17:14
micklmickl
16.3k61741
add a comment |
You can use below aggregation:
db.col.aggregate([
{
$group: {
_id: { patientKey: "$patientKey", encounterKey: "$encounterKey", diagnosisType: "$diagnosisType" },
problem_list: { $push: "$diagnosisCode" }
}
},
{
$group: {
_id: { patientKey: "$_id.patientKey", encounterKey: "$_id.encounterKey" },
encounters: { $push: { k: "$_id.diagnosisType", v: "$problem_list" } }
}
},
{
$project: {
encounters: { $arrayToObject: "$encounters" }
}
},
{
$group: {
_id: "$_id.patientKey",
encounters: {
$push: {
encounterKey: "$_id.encounterKey",
problem_list: "$encounters.problem_list",
medical_history: "$encounters.medical_history"
}
}
}
},
{
$project: {
patientKey: "$_id",
_id: 0,
encounters: 1
}
}
])
Basically you need few $group stages to accumulate the data. Additionally you have to use $arrayToObject to build your JSON keys dynamically.
Outputs:
{
"patientKey" : 1,
"encounters" : [
{
"encounterKey" : 2,
"problem_list" : [
"2x.2"
],
"medical_history" : [
"Z87.81"
]
},
{
"encounterKey" : 3,
"problem_list" : [
"p.2342"
],
"medical_history" : [
"D21.01",
"X2.31"
]
}
]
}
answered Jan 4 at 17:14
micklmickl
16.3k61741
You can use below aggregation:
db.col.aggregate([
{
$group: {
_id: { patientKey: "$patientKey", encounterKey: "$encounterKey", diagnosisType: "$diagnosisType" },
problem_list: { $push: "$diagnosisCode" }
}
},
{
$group: {
_id: { patientKey: "$_id.patientKey", encounterKey: "$_id.encounterKey" },
encounters: { $push: { k: "$_id.diagnosisType", v: "$problem_list" } }
}
},
{
$project: {
encounters: { $arrayToObject: "$encounters" }
}
},
{
$group: {
_id: "$_id.patientKey",
encounters: {
$push: {
encounterKey: "$_id.encounterKey",
problem_list: "$encounters.problem_list",
medical_history: "$encounters.medical_history"
}
}
}
},
{
$project: {
patientKey: "$_id",
_id: 0,
encounters: 1
}
}
])
Basically you need few $group stages to accumulate the data. Additionally you have to use $arrayToObject to build your JSON keys dynamically.
Outputs:
{
"patientKey" : 1,
"encounters" : [
{
"encounterKey" : 2,
"problem_list" : [
"2x.2"
],
"medical_history" : [
"Z87.81"
]
},
{
"encounterKey" : 3,
"problem_list" : [
"p.2342"
],
"medical_history" : [
"D21.01",
"X2.31"
]
}
]
}
answered Jan 4 at 17:14
micklmickl
16.3k61741
answered Jan 4 at 17:14
micklmickl
16.3k61741
answered Jan 4 at 17:14
micklmickl
16.3k61741
answered Jan 4 at 17:14
micklmickl
16.3k61741
16.3k61741
add a comment |
add a comment |
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