Timeseries Scoring
This endpoint will accept a timeseries of health events, and a list of ages to score on
The time series scoring endpoint extends the default Health Scoring API to support longitudinal analysis for a single user. While the default endpoint generates point-in-time scores for multiple users in a batch, the time series endpoint allows you to submit multiple scoring events each with its own biomarker data and age for a single individual in a single request.
This enables you to construct a continuous trajectory of Volo Scores, Volo Ages, and risk ratios across a user's health history, capturing how health outcomes evolve over time. By analyzing how scores change across events, you can identify trends, measure the impact of health interventions, and support applications that require a longitudinal view of a user's health.
Full details of the endpoint and its definition, along with tools for testing it can be found under the API Reference page.
Request
The request schema closely mirrors the default endpoint, with key differences to accommodate multiple health events for a single user captured at different ages. Each event in the request contains its own set of predictors, allowing biomarker values and the age at which to score to vary across events. The response returns a full set of disease scores, risk ratios, Volo Ages, and predictor attributions for each event, giving you a rich, time-indexed dataset for a single user.
Key objects and field that are different to the default batch scoring request are listed below:
- uid_ext: The ID of the user that's being scored. This is now provided in the main body of the request object and only needed once, as we are scoring for a single user.
- ages_to_score: A list of ages to build scoring bars for and then to score on. Data from health events will be forward/backward imputed to these ages to form as complete a dataset as possible.
- dates_to_score (optional): A list of dates to build scoring bars for and then to score on. Data from health events will be forward/backward imputed to these dates to form as complete a dataset as possible. NOTE: If
dates_to_scoreis present,ages_to_scoremust not be, and eachhealth_eventmust have ahealth_event_date. Additionally,date_of_birthfor the user must be specified. All dates should be in ISO 8601 format (YYYY-MM-DD). - date_of_birth: The date of birth for the user. NOTE: Only used when
dates_to_scoreis present - health_events: The list of health events to build scoring bars from. Each heath event should contain the following data.
- health_event_id: The ID to identify each event with.
- event_age: The age of the user when the event occurred. This should be as granular an age as possible.
- health_event_date: the date when the event occurred, if scoring on dates.
- predictors: The list of biomarkers (as
LOINCs) and their values to be used for scoring. This is the same as the input for the default batch scoring endpoint.
Mode of operation
This endpoint also supports 3 different modes when submitting a request. This is specified in the mode property in the scoring_event_metadata node of the input request object sent to the API. These are:
score- Simply take the input biomarker data and generate scores for the data.validate- This option will only validate the input biomarker data to ensure the values are in the correct range for the given unit for the biomarker, and the gender of the user. No scores will be generated when using this option.validate_and_score- This is a combination of the previous 2 options. This will validate each biomarker and generate scores based on the input data. The validations will be returned alongside each scoring event result for a user.
Example request
Below is a sample request for the timeseries endpoint.
{
"scoring_event_metadata": {
"event_id": "550e8400-e29b-41d4-a716-446655440000",
"event_asof_dtutc": "2024-02-05T14:30:00Z",
"mode": "validate_and_score"
},
"ages_to_score": [
45,
46,
47,
48
],
"uid_ext": "HSJDU721WDHQH",
"health_events": [
{
"health_event_id": "evt_001",
"event_age": 45.3,
"predictors": [
{
"id": "6b0ca208-86a7-440d-b0c1-0818ad53002e",
"observation_code": "30525-0",
"value": "28",
"unit": "a"
},
{
"id": "aa653593-7071-4266-b010-953cefff9eb3",
"observation_code": "46098-0",
"value": "male",
"unit": ""
},
{
"id": "c40aa00e-2e3d-4e7e-9718-95a25c2df8e9",
"observation_code": "8302-2",
"value": "78",
"unit": "inches"
},
{
"id": "1f796753-f375-494a-8539-b0f140ff4f56",
"observation_code": "29463-7",
"value": "210",
"unit": "lbs"
},
{
"id": "8835a752-bc03-473c-a4ba-37387c045f14",
"observation_code": "64219-9",
"value": "0",
"unit": "pack/years"
},
{
"id": "0dd946b0-d10a-477a-8a43-dc313e0ef0a9",
"observation_code": "4548-4",
"value": "5.4",
"unit": "%"
},
{
"id": "a624e601-d519-40d9-b972-b45e15d2a43e",
"observation_code": "2885-2",
"value": "8.1",
"unit": "g/dL"
},
{
"id": "3197ae19-9438-40d5-aded-67228b498a9e",
"observation_code": "2571-8",
"value": "40",
"unit": "mg/dL"
},
{
"id": "3d9b1dcd-3c70-4c36-9f7b-fc8e2e57bd49",
"observation_code": "10835-7",
"value": "6.2",
"unit": "mg/dL"
},
{
"id": "29ebacd2-baf0-4b86-b66d-92ece13264e3",
"observation_code": "1751-7",
"value": "4.8",
"unit": "g/dL"
},
{
"id": "f644ac87-420c-4656-8f07-daa6350bca0c",
"observation_code": "17861-6",
"value": "9.6",
"unit": "mg/dL"
},
{
"id": "0dfe36d5-a8d3-4a36-9d6d-7dcec20e647d",
"observation_code": "2160-0",
"value": "0.83",
"unit": "mg/dL"
},
{
"id": "c6f4d776-d8e8-486a-9ed0-2d6260c0a583",
"observation_code": "2498-4",
"value": "106",
"unit": "ug/dL"
},
{
"id": "bd9d03b9-1be7-4e51-a3c9-5fd7dee92ea8",
"observation_code": "2086-7",
"value": "76",
"unit": "mg/dL"
},
{
"id": "852a0141-90a0-4397-9480-081786fedc54",
"observation_code": "1975-2",
"value": "0.7",
"unit": "mg/dL"
},
{
"id": "120c6aff-1613-4a14-9a29-88803c8eef71",
"observation_code": "77147-7",
"value": "117.25",
"unit": "mL/min/1.73m^2"
},
{
"id": "aed5cd82-513a-47d8-b8ae-7109dc8a8065",
"observation_code": "13457-7",
"value": "80",
"unit": "mg/dL"
},
{
"id": "199bd4d3-07ac-494f-93e4-d96979f86824",
"observation_code": "2276-4",
"value": "89.6",
"unit": "ng/mL"
}
]
},
{
"health_event_id": "evt_002",
"event_age": 47.8,
"predictors": [
{
"id": "6b0ca208-86a7-440d-b0c1-0818ad53002f",
"observation_code": "30525-0",
"value": "28",
"unit": "a"
},
{
"id": "aa653593-7071-4266-b010-953cefff9eb4",
"observation_code": "46098-0",
"value": "male",
"unit": ""
},
{
"id": "c40aa00e-2e3d-4e7e-9718-95a25c2df8e0",
"observation_code": "8302-2",
"value": "78",
"unit": "inches"
},
{
"id": "1f796753-f375-494a-8539-b0f140ff4f57",
"observation_code": "29463-7",
"value": "210",
"unit": "lbs"
},
{
"id": "8835a752-bc03-473c-a4ba-37387c045f15",
"observation_code": "64219-9",
"value": "0",
"unit": "pack/years"
},
{
"id": "0dd946b0-d10a-477a-8a43-dc313e0ef0a0",
"observation_code": "4548-4",
"value": "5.4",
"unit": "%"
},
{
"id": "a624e601-d519-40d9-b972-b45e15d2a43f",
"observation_code": "2885-2",
"value": "8.1",
"unit": "g/dL"
},
{
"id": "3197ae19-9438-40d5-aded-67228b498a9f",
"observation_code": "2571-8",
"value": "40",
"unit": "mg/dL"
},
{
"id": "3d9b1dcd-3c70-4c36-9f7b-fc8e2e57bd40",
"observation_code": "10835-7",
"value": "6.2",
"unit": "mg/dL"
},
{
"id": "29ebacd2-baf0-4b86-b66d-92ece13264e4",
"observation_code": "1751-7",
"value": "4.8",
"unit": "g/dL"
},
{
"id": "f644ac87-420c-4656-8f07-daa6350bca0d",
"observation_code": "17861-6",
"value": "9.6",
"unit": "mg/dL"
},
{
"id": "0dfe36d5-a8d3-4a36-9d6d-7dcec20e647e",
"observation_code": "2160-0",
"value": "0.83",
"unit": "mg/dL"
},
{
"id": "c6f4d776-d8e8-486a-9ed0-2d6260c0a584",
"observation_code": "2498-4",
"value": "106",
"unit": "ug/dL"
},
{
"id": "bd9d03b9-1be7-4e51-a3c9-5fd7dee92ea9",
"observation_code": "2086-7",
"value": "76",
"unit": "mg/dL"
},
{
"id": "852a0141-90a0-4397-9480-081786fedc55",
"observation_code": "1975-2",
"value": "0.7",
"unit": "mg/dL"
},
{
"id": "120c6aff-1613-4a14-9a29-88803c8eef72",
"observation_code": "77147-7",
"value": "117.25",
"unit": "mL/min/1.73m^2"
},
{
"id": "aed5cd82-513a-47d8-b8ae-7109dc8a8066",
"observation_code": "13457-7",
"value": "80",
"unit": "mg/dL"
},
{
"id": "199bd4d3-07ac-494f-93e4-d96979f86825",
"observation_code": "2276-4",
"value": "89.6",
"unit": "ng/mL"
}
]
}
]
}Response
The response schema closely matches the output from default batch scoring endpoint, with some minor differences to support the timeseries scores.
The differences in the response are outlined below:
- scoring_events: As with the batch scoring response, this contains an array of scores at the different ages requested. Below are the new fields included as part of the object.
- scoring_event_age: The age of the user at this scoring event
- scoring_event_date: the date of this scoring event, if
dates_to_scorewas passed. - scoring_predictors: As with the batch scoring response, this contains an array of predictor metadata objects used to score upon. This will be returned every time and includes both the given predictors and the sideways imputed predictors. The only change to a predictor object is:
- health_event_id: The
health_event_idthat this predictor was taken from, if it wasGIVEN,FORWARD, orBACKWARDimputed.
- health_event_id: The
The remaining output for each scoring event remains the same as the batch scoring response.
Example response
Below is a sample response based on the request above.
{
"scoring_event_metadata": {
"event_id": "550e8400-e29b-41d4-a716-446655440000",
"event_asof_dtutc": "2024-02-05T14:30:00Z",
"product_version": "4.3.0"
},
"uid_ext": "HSJDU721WDHQH",
"scoring_results": [
{
"scoring_event_age": 45,
"scoring_predictors": [
{
"predictor_code": "4548-4",
"value": 5.4,
"imputation_code": "BACKWARD",
"percentile": 69.72225630956763,
"health_event_id": "evt_001"
},
{
"predictor_code": "6768-6",
"value": 76.5865653375151,
"imputation_code": "SIDEWAYS",
"percentile": 47.41791649777058,
"health_event_id": null
},
{
"predictor_code": "1742-6",
"value": 23.063663357300165,
"imputation_code": "SIDEWAYS",
"percentile": 39.33760857212436,
"health_event_id": null
},
{
"predictor_code": "1920-8",
"value": 25.836784497054293,
"imputation_code": "SIDEWAYS",
"percentile": 45.98778004073319,
"health_event_id": null
},
{
"predictor_code": "bl__AST_ALT_Ratio",
"value": 1.120237669826913,
"imputation_code": "SIDEWAYS",
"percentile": 62.05997392438071,
"health_event_id": null
},
{
"predictor_code": "1751-7",
"value": 4.8,
"imputation_code": "BACKWARD",
"percentile": 70.74458722055977,
"health_event_id": "evt_001"
},
{
"predictor_code": "1869-7",
"value": 176.75924873530673,
"imputation_code": "SIDEWAYS",
"percentile": 95.21878993522232,
"health_event_id": null
},
{
"predictor_code": "1884-6",
"value": 53.46169347833242,
"imputation_code": "SIDEWAYS",
"percentile": 0.765703054622881,
"health_event_id": null
},
{
"predictor_code": "bl__BUN_creat_ratio",
"value": 17.974449347980762,
"imputation_code": "SIDEWAYS",
"percentile": 70.94221717253693,
"health_event_id": null
},
{
"predictor_code": "1975-2",
"value": 0.7,
"imputation_code": "BACKWARD",
"percentile": 75.76276019389792,
"health_event_id": "evt_001"
},
{
"predictor_code": "1988-5",
"value": 1.0385466995410038,
"imputation_code": "SIDEWAYS",
"percentile": 49.72355476054964,
"health_event_id": null
},
{
"predictor_code": "17861-6",
"value": 9.6,
"imputation_code": "BACKWARD",
"percentile": 53.590770992030286,
"health_event_id": "evt_001"
},
{
"predictor_code": "2160-0",
"value": 0.83,
"imputation_code": "BACKWARD",
"percentile": 30.266039419255414,
"health_event_id": "evt_001"
},
{
"predictor_code": "33863-2",
"value": 0.8819953452808293,
"imputation_code": "SIDEWAYS",
"percentile": 58.94920338914339,
"health_event_id": null
},
{
"predictor_code": "2324-2",
"value": 25.867899445274492,
"imputation_code": "SIDEWAYS",
"percentile": 35.701533717438934,
"health_event_id": null
},
{
"predictor_code": "2339-0",
"value": 85.69720545733948,
"imputation_code": "SIDEWAYS",
"percentile": 44.265256664463536,
"health_event_id": null
},
{
"predictor_code": "2086-7",
"value": 76.0,
"imputation_code": "BACKWARD",
"percentile": 98.06573845611561,
"health_event_id": "evt_001"
},
{
"predictor_code": "2484-4",
"value": 186.69851587084227,
"imputation_code": "SIDEWAYS",
"percentile": 53.79189431623583,
"health_event_id": null
},
{
"predictor_code": "13457-7",
"value": 80.0,
"imputation_code": "BACKWARD",
"percentile": 2.2886178861788617,
"health_event_id": "evt_001"
},
{
"predictor_code": "bl__LDL_ApoB_ratio",
"value": 1.496398538748559,
"imputation_code": "SIDEWAYS",
"percentile": 97.48399277622723,
"health_event_id": null
},
{
"predictor_code": "43583-4",
"value": 38.958673898554075,
"imputation_code": "SIDEWAYS",
"percentile": 64.92955612785941,
"health_event_id": null
},
{
"predictor_code": "2885-2",
"value": 8.1,
"imputation_code": "BACKWARD",
"percentile": 95.93725213712875,
"health_event_id": "evt_001"
},
{
"predictor_code": "13967-5",
"value": 42.13665250800349,
"imputation_code": "SIDEWAYS",
"percentile": 79.65245145846262,
"health_event_id": null
},
{
"predictor_code": "2986-8",
"value": 558.8281447910819,
"imputation_code": "SIDEWAYS",
"percentile": 73.0539656582175,
"health_event_id": null
},
{
"predictor_code": "2571-8",
"value": 40.0,
"imputation_code": "BACKWARD",
"percentile": 0.40196516301920504,
"health_event_id": "evt_001"
},
{
"predictor_code": "3084-1",
"value": 5.213999228254566,
"imputation_code": "SIDEWAYS",
"percentile": 28.64851706089991,
"health_event_id": null
},
{
"predictor_code": "3094-0",
"value": 14.918792958824033,
"imputation_code": "SIDEWAYS",
"percentile": 58.18218705619801,
"health_event_id": null
},
{
"predictor_code": "14635-7",
"value": 39.178919864309236,
"imputation_code": "SIDEWAYS",
"percentile": 66.88005390835579,
"health_event_id": null
},
{
"predictor_code": "704-7",
"value": 26.19850408073086,
"imputation_code": "SIDEWAYS",
"percentile": 72.21290528669542,
"health_event_id": null
},
{
"predictor_code": "30180-4",
"value": 0.5166194918495685,
"imputation_code": "SIDEWAYS",
"percentile": 67.21370388116914,
"health_event_id": null
},
{
"predictor_code": "26449-9",
"value": 170.7283078070493,
"imputation_code": "SIDEWAYS",
"percentile": 54.74365117393387,
"health_event_id": null
},
{
"predictor_code": "26450-7",
"value": 2.8884005379766635,
"imputation_code": "SIDEWAYS",
"percentile": 61.58361284139914,
"health_event_id": null
},
{
"predictor_code": "20570-8",
"value": 43.26961029603254,
"imputation_code": "SIDEWAYS",
"percentile": 44.39440436810011,
"health_event_id": null
},
{
"predictor_code": "30350-3",
"value": 14.988846088536413,
"imputation_code": "SIDEWAYS",
"percentile": 42.85201865210633,
"health_event_id": null
},
{
"predictor_code": "731-0",
"value": 1708.6385159550919,
"imputation_code": "SIDEWAYS",
"percentile": 41.03977000479156,
"health_event_id": null
},
{
"predictor_code": "736-9",
"value": 28.875396396938022,
"imputation_code": "SIDEWAYS",
"percentile": 48.88196773678326,
"health_event_id": null
},
{
"predictor_code": "785-6",
"value": 31.14523285182164,
"imputation_code": "SIDEWAYS",
"percentile": 45.23932884301144,
"health_event_id": null
},
{
"predictor_code": "28540-3",
"value": 34.66152871708674,
"imputation_code": "SIDEWAYS",
"percentile": 50.88677214937627,
"health_event_id": null
},
{
"predictor_code": "30428-7",
"value": 89.91536906548255,
"imputation_code": "SIDEWAYS",
"percentile": 47.28388665258459,
"health_event_id": null
},
{
"predictor_code": "742-7",
"value": 444.4276289429064,
"imputation_code": "SIDEWAYS",
"percentile": 47.45647660118192,
"health_event_id": null
},
{
"predictor_code": "5905-5",
"value": 7.408054867111466,
"imputation_code": "SIDEWAYS",
"percentile": 55.757866155566205,
"health_event_id": null
},
{
"predictor_code": "751-8",
"value": 3560.331659787946,
"imputation_code": "SIDEWAYS",
"percentile": 41.407123462705634,
"health_event_id": null
},
{
"predictor_code": "23761-0",
"value": 60.171349698340634,
"imputation_code": "SIDEWAYS",
"percentile": 51.249800351381566,
"health_event_id": null
},
{
"predictor_code": "777-3",
"value": 226.00885677530286,
"imputation_code": "SIDEWAYS",
"percentile": 39.292973576182696,
"health_event_id": null
},
{
"predictor_code": "788-0",
"value": 13.212217280389027,
"imputation_code": "SIDEWAYS",
"percentile": 54.6690048224463,
"health_event_id": null
},
{
"predictor_code": "789-8",
"value": 4.819153506056094,
"imputation_code": "SIDEWAYS",
"percentile": 46.82555497987326,
"health_event_id": null
},
{
"predictor_code": "6690-2",
"value": 5.858383688044959,
"imputation_code": "SIDEWAYS",
"percentile": 35.94914511179307,
"health_event_id": null
},
{
"predictor_code": "8302-2",
"value": 198.12,
"imputation_code": "GIVEN",
"percentile": 99.58784918333079,
"health_event_id": "evt_001"
},
{
"predictor_code": "29463-7",
"value": 95.25431999999999,
"imputation_code": "GIVEN",
"percentile": 76.60280873149138,
"health_event_id": "evt_001"
},
{
"predictor_code": "41909-3",
"value": 24.265285996055226,
"imputation_code": "SIDEWAYS",
"percentile": 21.901236452450007,
"health_event_id": null
},
{
"predictor_code": "8462-4",
"value": 71.65463436822071,
"imputation_code": "SIDEWAYS",
"percentile": 44.38513568576318,
"health_event_id": null
},
{
"predictor_code": "pm__grip_strength_mean_lbs",
"value": 104.43633671255158,
"imputation_code": "SIDEWAYS",
"percentile": 68.78127028988274,
"health_event_id": null
},
{
"predictor_code": "40443-4",
"value": 65.00582850802952,
"imputation_code": "SIDEWAYS",
"percentile": 45.11449759595795,
"health_event_id": null
},
{
"predictor_code": "8480-6",
"value": 119.65686289902435,
"imputation_code": "SIDEWAYS",
"percentile": 49.92054113524306,
"health_event_id": null
},
{
"predictor_code": "srSmoke__Pack_years_of_smoking",
"value": 0.0,
"imputation_code": "SIDEWAYS",
"percentile": 59.60410557184751,
"health_event_id": null
}
],
"disease_scores": [
{
"disease_code": "ARD",
"age_to_score": 55.0,
"info_ratio": 0.0,
"score_percentile": 34.67010407715077,
"health_score": {
"health_score": 210.32962607579353,
"max_score": 245.0
},
"risk_ratios": {
"your_risk_frac": 0.005236156319934303,
"peer_risk_frac": 0.007490123319709001,
"risk_ratio": 0.6990747810728613
},
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"risk_attribution": -0.04194407126934931,
"multiplier": 0.957415893344419
},
{
"predictor_code": "8480-6",
"score_attribution": 1.6817018501921477,
"risk_attribution": -0.03795275095844231,
"multiplier": 0.7237458476014214
},
{
"predictor_code": "56117-5",
"score_attribution": -1.050125483371767,
"risk_attribution": 0.023699296603002944,
"multiplier": 0.7383335458300179
},
{
"predictor_code": "srSmoke__Pack_years_of_smoking",
"score_attribution": -0.18587157772511823,
"risk_attribution": 0.0041947612169470775,
"multiplier": 0.7853199633694548
},
{
"predictor_code": "63632-4",
"score_attribution": -0.0,
"risk_attribution": 0.0,
"multiplier": null
}
]
},
{
"disease_code": "Thyroid",
"age_to_score": 0.0,
"info_ratio": 0.0,
"score_percentile": 24.647548862544056,
"health_score": {
"health_score": 206.11503220932036,
"max_score": 245.0
},
"risk_ratios": {
"your_risk_frac": 0.06514105327478496,
"peer_risk_frac": 0.08051840854541706,
"risk_ratio": 0.8090206258614963
},
"disease_age": {
"disease_age": 46.5,
"disease_age_delta": -1.5
},
"predictor_attributions": null
}
]
}
],
"validations": [
[
{
"code": "30525-0",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'age' (resolved from '30525-0')",
"return_code": "no_threshold_data",
"id": "6b0ca208-86a7-440d-b0c1-0818ad53002e",
"validated_value": null,
"validated_unit": null
},
{
"code": "8302-2",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Unit mismatch and conversion failed: expected 'cm', received 'inches'. Conversion error: ['Invalid source unit: inches', 'Unable to create unit from: inches']",
"return_code": "invalid_unit_dimension",
"id": "c40aa00e-2e3d-4e7e-9718-95a25c2df8e9",
"validated_value": null,
"validated_unit": null
},
{
"code": "29463-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Unit mismatch and conversion failed: expected 'kg', received 'lbs'. Conversion error: ['Invalid source unit: lbs', 'Unable to create unit from: lbs']",
"return_code": "invalid_unit_dimension",
"id": "1f796753-f375-494a-8539-b0f140ff4f56",
"validated_value": null,
"validated_unit": null
},
{
"code": "64219-9",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'srSmoke__Cigarette_packs_per_day' (resolved from '64219-9')",
"return_code": "no_threshold_data",
"id": "8835a752-bc03-473c-a4ba-37387c045f14",
"validated_value": null,
"validated_unit": null
},
{
"code": "4548-4",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "0dd946b0-d10a-477a-8a43-dc313e0ef0a9",
"validated_value": 5.4,
"validated_unit": "%"
},
{
"code": "2885-2",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "a624e601-d519-40d9-b972-b45e15d2a43e",
"validated_value": 8.1,
"validated_unit": "g/dL"
},
{
"code": "2571-8",
"qa_status": "FLAGGED",
"severity": "UNUSUAL",
"message": "Value 40.0 under unusual lower trim threshold 44.728",
"return_code": "value_under_unusual_minimum",
"id": "3197ae19-9438-40d5-aded-67228b498a9e",
"validated_value": 40.0,
"validated_unit": "mg/dL"
},
{
"code": "10835-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Code '10835-7' could not be resolved (as LOINC or obs_code)",
"return_code": "invalid_code",
"id": "3d9b1dcd-3c70-4c36-9f7b-fc8e2e57bd49",
"validated_value": null,
"validated_unit": null
},
{
"code": "1751-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "29ebacd2-baf0-4b86-b66d-92ece13264e3",
"validated_value": 4.8,
"validated_unit": "g/dL"
},
{
"code": "17861-6",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "f644ac87-420c-4656-8f07-daa6350bca0c",
"validated_value": 9.6,
"validated_unit": "mg/dL"
},
{
"code": "2160-0",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "0dfe36d5-a8d3-4a36-9d6d-7dcec20e647d",
"validated_value": 0.83,
"validated_unit": "mg/dL"
},
{
"code": "2498-4",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'bl__Iron' (resolved from '2498-4')",
"return_code": "no_threshold_data",
"id": "c6f4d776-d8e8-486a-9ed0-2d6260c0a583",
"validated_value": null,
"validated_unit": null
},
{
"code": "2086-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "bd9d03b9-1be7-4e51-a3c9-5fd7dee92ea8",
"validated_value": 76.0,
"validated_unit": "mg/dL"
},
{
"code": "1975-2",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "852a0141-90a0-4397-9480-081786fedc54",
"validated_value": 0.7,
"validated_unit": "mg/dL"
},
{
"code": "77147-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Code '77147-7' could not be resolved (as LOINC or obs_code)",
"return_code": "invalid_code",
"id": "120c6aff-1613-4a14-9a29-88803c8eef71",
"validated_value": null,
"validated_unit": null
},
{
"code": "13457-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "aed5cd82-513a-47d8-b8ae-7109dc8a8065",
"validated_value": 80.0,
"validated_unit": "mg/dL"
},
{
"code": "2276-4",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'bl__Ferritin' (resolved from '2276-4')",
"return_code": "no_threshold_data",
"id": "199bd4d3-07ac-494f-93e4-d96979f86824",
"validated_value": null,
"validated_unit": null
}
],
[
{
"code": "30525-0",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'age' (resolved from '30525-0')",
"return_code": "no_threshold_data",
"id": "6b0ca208-86a7-440d-b0c1-0818ad53002f",
"validated_value": null,
"validated_unit": null
},
{
"code": "8302-2",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Unit mismatch and conversion failed: expected 'cm', received 'inches'. Conversion error: ['Invalid source unit: inches', 'Unable to create unit from: inches']",
"return_code": "invalid_unit_dimension",
"id": "c40aa00e-2e3d-4e7e-9718-95a25c2df8e0",
"validated_value": null,
"validated_unit": null
},
{
"code": "29463-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Unit mismatch and conversion failed: expected 'kg', received 'lbs'. Conversion error: ['Invalid source unit: lbs', 'Unable to create unit from: lbs']",
"return_code": "invalid_unit_dimension",
"id": "1f796753-f375-494a-8539-b0f140ff4f57",
"validated_value": null,
"validated_unit": null
},
{
"code": "64219-9",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'srSmoke__Cigarette_packs_per_day' (resolved from '64219-9')",
"return_code": "no_threshold_data",
"id": "8835a752-bc03-473c-a4ba-37387c045f15",
"validated_value": null,
"validated_unit": null
},
{
"code": "4548-4",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "0dd946b0-d10a-477a-8a43-dc313e0ef0a0",
"validated_value": 5.4,
"validated_unit": "%"
},
{
"code": "2885-2",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "a624e601-d519-40d9-b972-b45e15d2a43f",
"validated_value": 8.1,
"validated_unit": "g/dL"
},
{
"code": "2571-8",
"qa_status": "FLAGGED",
"severity": "UNUSUAL",
"message": "Value 40.0 under unusual lower trim threshold 44.728",
"return_code": "value_under_unusual_minimum",
"id": "3197ae19-9438-40d5-aded-67228b498a9f",
"validated_value": 40.0,
"validated_unit": "mg/dL"
},
{
"code": "10835-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Code '10835-7' could not be resolved (as LOINC or obs_code)",
"return_code": "invalid_code",
"id": "3d9b1dcd-3c70-4c36-9f7b-fc8e2e57bd40",
"validated_value": null,
"validated_unit": null
},
{
"code": "1751-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "29ebacd2-baf0-4b86-b66d-92ece13264e4",
"validated_value": 4.8,
"validated_unit": "g/dL"
},
{
"code": "17861-6",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "f644ac87-420c-4656-8f07-daa6350bca0d",
"validated_value": 9.6,
"validated_unit": "mg/dL"
},
{
"code": "2160-0",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "0dfe36d5-a8d3-4a36-9d6d-7dcec20e647e",
"validated_value": 0.83,
"validated_unit": "mg/dL"
},
{
"code": "2498-4",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'bl__Iron' (resolved from '2498-4')",
"return_code": "no_threshold_data",
"id": "c6f4d776-d8e8-486a-9ed0-2d6260c0a584",
"validated_value": null,
"validated_unit": null
},
{
"code": "2086-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "bd9d03b9-1be7-4e51-a3c9-5fd7dee92ea9",
"validated_value": 76.0,
"validated_unit": "mg/dL"
},
{
"code": "1975-2",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "852a0141-90a0-4397-9480-081786fedc55",
"validated_value": 0.7,
"validated_unit": "mg/dL"
},
{
"code": "77147-7",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "Code '77147-7' could not be resolved (as LOINC or obs_code)",
"return_code": "invalid_code",
"id": "120c6aff-1613-4a14-9a29-88803c8eef72",
"validated_value": null,
"validated_unit": null
},
{
"code": "13457-7",
"qa_status": "PASS",
"severity": null,
"message": "Valid entry",
"return_code": "valid_entry",
"id": "aed5cd82-513a-47d8-b8ae-7109dc8a8066",
"validated_value": 80.0,
"validated_unit": "mg/dL"
},
{
"code": "2276-4",
"qa_status": "FAIL",
"severity": "IMPLAUSIBLE",
"message": "No threshold data for predictor code 'bl__Ferritin' (resolved from '2276-4')",
"return_code": "no_threshold_data",
"id": "199bd4d3-07ac-494f-93e4-d96979f86825",
"validated_value": null,
"validated_unit": null
}
]
]
}Updated 6 days ago