ecqm.measure

CMS249v1 - Appropriate Use of DXA Scans in Women Under 65 Years Who Do Not Meet the Risk Factor Profile for Osteoporotic Fracture

Rationale:

Appropriate Use of DXA Scans in Women Under 65 Years Who Do Not Meet the Risk Factor Profile for Osteoporotic Fracture. This measure is expected to increase recording of patient risk for fracture data and decrease the amount of inappropriate DXA scans. Current osteoporosis guidelines underscore the importance of screening women for osteoporosis if they are 1) 65 years or older or 2) younger than 65 if they have a fracture risk 'equal to or greater than that of a 65-year-old white woman who has no additional risk factors.' Clinical information, such as age, body mass index (BMI), parental fracture history, and tobacco and alcohol use, can be used to determine a woman's fracture risk (USPSTF, 2011). Additionally, there are potentially avoidable harms associated with screening for osteoporosis in general, including exposure to radiation, false positive exams, and resulting side effects from unnecessary osteoporosis medications, which add costs to an already burdened health care system (Lim, 2009).

Data Elements

AverageNumberOfDrinksPerDrinkingDayPerformed

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

Subject constrained to the Average Number of Drinks per Drinking Day

AssessmentPerformed: Data elements that meet criteria using this datatype should document completion of the assessment indicated by the QDM category and its corresponding value set. Timing: The time the assessment is completed; Author dateTime.

DataType

Cardinality

AverageNumberOfDrinksPerDrinkingDayPerformed

0..*

HistoryOfHipFractureInParentPerformed

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

Subject constrained to the History of hip fracture in parent

AssessmentPerformed: Data elements that meet criteria using this datatype should document completion of the assessment indicated by the QDM category and its corresponding value set. Timing: The time the assessment is completed; Author dateTime.

DataType

Cardinality

HistoryOfHipFractureInParentPerformed

0..*

TenYearProbabilityOfAllMajorOsteoporosisRelatedFracturePerformed

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

Subject constrained to the Ten-year probability of all major osteoporosis related fracture

AssessmentPerformed: Data elements that meet criteria using this datatype should document completion of the assessment indicated by the QDM category and its corresponding value set. Timing: The time the assessment is completed; Author dateTime.

DataType

Cardinality

TenYearProbabilityOfAllMajorOsteoporosisRelatedFracturePerformed

0..*

TobaccoUseScreeningPerformed

Clinical Focus: Under Development

Data Element Scope: Under Development

Inclusion Criteria: Under Development

Exclusion Criteria: Under Development

Subject constrained to the Tobacco Use Screening

AssessmentPerformed: Data elements that meet criteria using this datatype should document completion of the assessment indicated by the QDM category and its corresponding value set. Timing: The time the assessment is completed; Author dateTime.

DataType

Cardinality

TobaccoUseScreeningPerformed

0..*

CurrentTobaccoSmokerResult

Clinical Focus: This set of values is used to distinguish that a patient is a current smoker whether light, heavy, or occasional; the patient has a current history of cigarette, cigar, or pipe smoking as communicated to and documented by the health care provider.

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

Result: The final consequences or data collected from the datatype. Results can be used in five ways, to express: That a result is present in the electronic record but any entry is acceptable. A numerical result is reported directly as a value. Values may be integers or decimal numbers without units, or as a quantity with a value and units – examples: 100 mg/dL for a lab test, 140 mmHg for blood pressure, as a percentage (actually a quantity with % as units), as a ratio (e.g., 1:4, 1:80). Beginning with QDM 5.3 measures use CQL logic to express the mathematical operators to constrain desired results to those above or below a certain threshold. A result that matches one of a specific set of coded concepts in a value set or a code that matches a direct referenced code. A result as a dateTime (Assessment, Performed and components).

DataType

Cardinality

CurrentTobaccoSmokerResult

0..*

Type1DiabetesDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of type 1 diabetes mellitus and distinguishes these patients from patients with other types of diabetes mellitus, including gestational, drug-induced or type 2 diabetes mellitus.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes associated with type 1 diabetes mellitus , with or without reference to complications and comorbidities.

Exclusion Criteria: Exclude all diagnosis codes associated with gestational, drug-induced and type 2 diabetes mellitus without mention of type 1 diabetes mellitus.

ResultValue constrained to codes in the Type 1 Diabetes valueset (2.16.840.1.113883.3.464.1003.103.12.1020)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

Type1DiabetesDiagnosis

0..*

RheumatoidArthritisDiagnosis

Clinical Focus: This set of values contains diagnosis codes that are used to identify patients with Rheumatoid arthritis.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes rheumatoid arthritis and felty's syndrome. Includes comorbidities occuring with rheumatoid arthritis, such as rheumatoid polyneuropathy, rheumatoid myopathy, rheumatoid heart disease, rheumatoid vasculitis, and rheumatoid lung disease.

Exclusion Criteria: Exclude codes for Juvenile chronic polyarthritis, Chronic postrheumatic arthropathy, or inflammatory polyarhtropathy.

ResultValue constrained to codes in the Rheumatoid Arthritis valueset (2.16.840.1.113883.3.464.1003.113.12.1005)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

RheumatoidArthritisDiagnosis

0..*

OsteoporosisDiagnosis

Clinical Focus: This value set contains codes to identify osteoporosis.

Data Element Scope: This value set was intended to identify patients who had osteoporosis.

Inclusion Criteria: Include diagnosis codes for idiopathic, senile, disuse, and other/unspecified osteoporosis. Includes localized, transient, and regional migrating osteoporosis.

Exclusion Criteria: Exclude diagnosis codes for osteoporosis due to cystic fibrosis.

ResultValue constrained to codes in the Osteoporosis valueset (2.16.840.1.113883.3.464.1003.113.12.1038)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

OsteoporosisDiagnosis

0..*

OsteogenesisImperfectaDiagnosis

Clinical Focus: This value set identifies patients with a diagnosis of osteogenesis imperfecta.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for osteogenesis imperfecta disease classifications 1-4. Does include diagnoses in perinatal population.

Exclusion Criteria: Excludes diagnosis of osteoporosis with pseudoglioma.

ResultValue constrained to codes in the Osteogenesis Imperfecta valueset (2.16.840.1.113883.3.464.1003.113.12.1044)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

OsteogenesisImperfectaDiagnosis

0..*

AnkylosingSpondylitisDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of ankylosing spondylitis.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes associated with ankylosing spondylitis with comorbidities and associated system involvement.

Exclusion Criteria: Exclude all diagnosis codes associated with juvenile ankylosing spondylitis.

ResultValue constrained to codes in the Ankylosing Spondylitis valueset (2.16.840.1.113883.3.464.1003.113.12.1045)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

AnkylosingSpondylitisDiagnosis

0..*

PsoriaticArthritisDiagnosis

Clinical Focus: This value set identifies patients with a diagnosis of psoriatic arthritis.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for psoriatic arthritis, arthritis mutilans, psoriatic spondylitis, and other unspecified psoriatic arthropathy.

Exclusion Criteria: Excludes diagnosis codes for juvenile psoriatic arthritis and dactylitis.

ResultValue constrained to codes in the Psoriatic Arthritis valueset (2.16.840.1.113883.3.464.1003.113.12.1046)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

PsoriaticArthritisDiagnosis

0..*

EhlersDanlosSyndromeDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of Ehlers Danlos Syndrome.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes for Ehlers-Danlos Syndrome.

Exclusion Criteria: N/A

ResultValue constrained to codes in the Ehlers Danlos Syndrome valueset (2.16.840.1.113883.3.464.1003.113.12.1047)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

EhlersDanlosSyndromeDiagnosis

0..*

MarfansSyndromeDiagnosis

Clinical Focus: This value set identifies patients with a diagnosis of marfan's syndrome.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for marfan's syndome with or without cardiovascular, occular, skeletal, or epithelial manifestations.

Exclusion Criteria: N/A

ResultValue constrained to codes in the Marfan's Syndrome valueset (2.16.840.1.113883.3.464.1003.113.12.1048)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

MarfansSyndromeDiagnosis

0..*

OsteopeniaDiagnosis

Clinical Focus: This value set identifies patients with a diagnosis of osteopenia.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for specified and unspecified disorder of bones and cartilage. Includes osteopenia of prematurity, drug-induced osteopenia, and senile osteopenia.

Exclusion Criteria: Excludes diagnosis of arrest of bone development or growth, chondromalacia, or stress fracture of bone.

ResultValue constrained to codes in the Osteopenia valueset (2.16.840.1.113883.3.464.1003.113.12.1049)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

OsteopeniaDiagnosis

0..*

OsteoporoticFracturesDiagnosis

Clinical Focus: This set of values contains codes that are used to identify patients with a diagnosis of pathological fracture with or without occurrence of osteoporosis.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes associated with pathological fracture, with or without reference to osteoporosis.

Exclusion Criteria: Exclude all diagnosis codes for fractures that are not pathological.

ResultValue constrained to codes in the Osteoporotic Fractures valueset (2.16.840.1.113883.3.464.1003.113.12.1050)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

OsteoporoticFracturesDiagnosis

0..*

CushingsSyndromeDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of cushings syndrome.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes for hypercortiosolism, pituitary ACTH hypersecretion, and cushings syndrome. Also Include syndrome induced by tumors, alcohol, and depression.

Exclusion Criteria: N/A

ResultValue constrained to codes in the Cushings Syndrome valueset (2.16.840.1.113883.3.464.1003.117.12.1009)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

CushingsSyndromeDiagnosis

0..*

LupusDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of lupus (lupus erythematosus).

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for systemic, discoid, and drug-induced lupus erythematosus.

Exclusion Criteria: Excludes diagnosis codes for systemic lupus erythematosus in childhood or in remission.

ResultValue constrained to codes in the Lupus valueset (2.16.840.1.113883.3.464.1003.117.12.1010)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

LupusDiagnosis

0..*

HyperthyroidismDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of Hyperthyroidism.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes diagnosis codes for thyrotoxicosis, both with and without thyrotoxic crisis or storm, and with and without presence of goiter.

Exclusion Criteria: Excludes diagnosis codes for neonatal thyrotoxicosis.

ResultValue constrained to codes in the Hyperthyroidism valueset (2.16.840.1.113883.3.464.1003.117.12.1015)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

HyperthyroidismDiagnosis

0..*

HyperparathyroidismDiagnosis

Clinical Focus: This set of values contains codes that are used to identify patients with a diagnosis of primary, secondary, tertiary, and all other types of hyperparathyroidism.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes associated with hyperparathyroidism, with or without reference to complications and comorbidities.

Exclusion Criteria: Excludes diagnoses of autonomous thyroid function, Iatrogenic thyrotoxicosis factitia, neonatal thyrotoxicosis, and thyrotoxic crisis.

ResultValue constrained to codes in the Hyperparathyroidism valueset (2.16.840.1.113883.3.464.1003.117.12.1016)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

HyperparathyroidismDiagnosis

0..*

ChronicLiverDiseaseDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of chronic liver disease.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes associated with chronic liver disease that are not substance-induced.

Exclusion Criteria: N/A

ResultValue constrained to codes in the Chronic Liver Disease valueset (2.16.840.1.113883.3.464.1003.199.12.1035)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

ChronicLiverDiseaseDiagnosis

0..*

ChronicMalnutritionDiagnosis

Clinical Focus: This set of values contains codes that identify patients with a diagnosis of chronic malnutrition.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include all diagnosis codes for specified and unspecified eating disorders.

Exclusion Criteria: Exclude all diagnosis codes for feeding disorders of infancy or childhood. These include feeding disturbances, developmental delays, loss of appetite, & rumination. Also avoide restrictive food intake disorders, and pica.

ResultValue constrained to codes in the Chronic Malnutrition valueset (2.16.840.1.113883.3.464.1003.199.12.1036)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

ChronicMalnutritionDiagnosis

0..*

MalabsorptionSyndromesDiagnosis

Clinical Focus: This set of values contains codes that are used to identify patients with a diagnosis of chronic intestinal malabsorption.

Data Element Scope: This value set is developed for the diagnosis QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Includes regional enteritis, ulcerative enterocolitis, celiac disease, tropical sprue, blind loop syndrome, Pancreatic steatorrhea, and other specified or unspecified intestinal malabsorption disorders.

Exclusion Criteria: Excludes diagnoses of specified disorders of the intestine, including fistula of intesting, ulceration of intesting, performation of intestine, angiodysplasia (with or without hemmorrhage

ResultValue constrained to codes in the Malabsorption Syndromes valueset (2.16.840.1.113883.3.464.1003.199.12.1050)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

MalabsorptionSyndromesDiagnosis

0..*

EndStageRenalDiseaseDiagnosis

Clinical Focus: Under Development

Data Element Scope: Under Development

Inclusion Criteria: Under Development

Exclusion Criteria: Under Development

ResultValue constrained to codes in the End Stage Renal Disease valueset (2.16.840.1.113883.3.526.3.353)

Diagnosis: Condition/Diagnosis/Problem represents a practitioner’s identification of a patient’s disease, illness, injury, or condition. This category contains a single datatype to represent all of these concepts: Diagnosis. A practitioner determines the diagnosis by means of examination, diagnostic test results, patient history, and/or family history. Diagnoses are usually considered unfavorable, but may also represent neutral or favorable conditions that affect a patient’s plan of care (e.g., pregnancy). The QDM does not prescribe the source of diagnosis data in the EHR. Diagnoses may be found in a patient’s problem list, encounter diagnosis list, claims data, or other sources within the EHR. The preferred terminology for diagnoses is SNOMED-CT, but diagnoses may also be encoded using ICD-9/10. The Diagnosis datatype should not be used for differential diagnoses or rule-out diagnoses (neither of which are currently supported by the QDM).

DataType

Cardinality

EndStageRenalDiseaseDiagnosis

0..*

DxaDualEnergyXrayAbsorptiometryScanOrder

Clinical Focus: This value set identifies patients with a DXA scan.

Data Element Scope: This value set was intended to map to the QDM data type of Diagnostic Study, but has the potential to be used in additional ways.

Inclusion Criteria: Includes scans of the general body, spine, and the limbs.

Exclusion Criteria: Excludes codes specific to DXA scans of the hip.

Subject constrained to the DXA (Dual energy Xray Absorptiometry) Scan

DiagnosticStudyOrder: Data elements that meet criteria using this datatype should document a request by a clinician or appropriately licensed care provider to an appropriate provider or organization to perform the diagnostic study indicated by the QDM category and its corresponding value set. The request may be in the form of a consultation or a direct order to the organization that performs the diagnostic study. Diagnostic studies are those that are not performed in the clinical laboratory. Such studies include but are not limited to imaging studies, cardiology studies (electrocardiogram, treadmill stress testing), pulmonary function testing, vascular laboratory testing, and others. Timing: The time the order is signed; Author dateTime.

DataType

Cardinality

DxaDualEnergyXrayAbsorptiometryScanOrder

0..*

OfficeVisit1Performed

Clinical Focus: This value set identifies patients who have had an office or other outpatient visit.

Data Element Scope: This value set was intended to map to the QDM data type of encounter.

Inclusion Criteria: Includes comprehensive history, evaluation, and management of a patient in an office or outpatient facility. Patient can be presenting with problems that are minor to high severity.

Exclusion Criteria: Excludes non-office visits, including telehealth services.

Subject constrained to the Office Visit1

EncounterPerformed: Data elements that meet criteria using this datatype should document that the encounter indicated by the QDM category and its corresponding value set is in progress or has been completed. Timing: The Relevant Period addresses: startTime – The time the encounter began (admission time) stopTime – The time the encounter ended (discharge time). The Author dateTime addresses when an Encounter is documented. Documentation can occur at the beginning, during, at the end or subsequent to the end of an Encounter. The Author dateTime should be used only if the Relevant Period cannot be obtained. The Location Period is an attribute of the attribute facility location addresses: startTime = the time the patient arrived at the location; stopTime = the time the patient departed from the location

DataType

Cardinality

OfficeVisit1Performed

0..*

OutpatientConsultationPerformed

Clinical Focus: This value set indentifies patients who have had an outpatient interaction at an office with a member of their medical care team.

Data Element Scope: This value set was intended to map to the QDM data type of encounter.

Inclusion Criteria: Includes comprehensive history, evaluation, and management of a patient in an office or outpatient facility. Patient can be presenting with problems that are minor to high severity.

Exclusion Criteria: Excludes non-office visits, including telehealth services.

Subject constrained to the Outpatient Consultation

EncounterPerformed: Data elements that meet criteria using this datatype should document that the encounter indicated by the QDM category and its corresponding value set is in progress or has been completed. Timing: The Relevant Period addresses: startTime – The time the encounter began (admission time) stopTime – The time the encounter ended (discharge time). The Author dateTime addresses when an Encounter is documented. Documentation can occur at the beginning, during, at the end or subsequent to the end of an Encounter. The Author dateTime should be used only if the Relevant Period cannot be obtained. The Location Period is an attribute of the attribute facility location addresses: startTime = the time the patient arrived at the location; stopTime = the time the patient departed from the location

DataType

Cardinality

OutpatientConsultationPerformed

0..*

PreventiveCareServicesInitialOfficeVisit18AndUp1Performed

Clinical Focus: This value set identifies patients over the age of 18 who have had an initial preventive care office visit.

Data Element Scope: This value set was intended to map to the QDM data type of encounter.

Inclusion Criteria: Includes comprehensive preventive medicine reevaluation and management of an individual over the age of 18.

Exclusion Criteria: Excludes non-office visits, including telehealth services.

Subject constrained to the Preventive Care Services-Initial Office Visit, 18 and Up1

EncounterPerformed: Data elements that meet criteria using this datatype should document that the encounter indicated by the QDM category and its corresponding value set is in progress or has been completed. Timing: The Relevant Period addresses: startTime – The time the encounter began (admission time) stopTime – The time the encounter ended (discharge time). The Author dateTime addresses when an Encounter is documented. Documentation can occur at the beginning, during, at the end or subsequent to the end of an Encounter. The Author dateTime should be used only if the Relevant Period cannot be obtained. The Location Period is an attribute of the attribute facility location addresses: startTime = the time the patient arrived at the location; stopTime = the time the patient departed from the location

DataType

Cardinality

PreventiveCareServicesInitialOfficeVisit18AndUp1Performed

0..*

PreventiveCareServicesEstablishedOfficeVisit18AndUp1Performed

Clinical Focus: This value set identifies patients over the age of 18 who have had an established preventive care office visit.

Data Element Scope: This value set was intended to map to the QDM data type of encounter.

Inclusion Criteria: Includes comprehensive preventive medicine reevaluation and management of an individual over the age of 18.

Exclusion Criteria: Excludes non-office visits, including telehealth services.

Subject constrained to the Preventive Care Services - Established Office Visit, 18 and Up1

EncounterPerformed: Data elements that meet criteria using this datatype should document that the encounter indicated by the QDM category and its corresponding value set is in progress or has been completed. Timing: The Relevant Period addresses: startTime – The time the encounter began (admission time) stopTime – The time the encounter ended (discharge time). The Author dateTime addresses when an Encounter is documented. Documentation can occur at the beginning, during, at the end or subsequent to the end of an Encounter. The Author dateTime should be used only if the Relevant Period cannot be obtained. The Location Period is an attribute of the attribute facility location addresses: startTime = the time the patient arrived at the location; stopTime = the time the patient departed from the location

DataType

Cardinality

PreventiveCareServicesEstablishedOfficeVisit18AndUp1Performed

0..*

PreventiveCareServicesOtherPerformed

Clinical Focus: This value set identifies patients who patients who had an unlisted preventive medicine service. Inclusion: Includes unlisted preventive medicine services

Data Element Scope: This value set was intended to map to the QDM data type of encounter.

Inclusion Criteria: Includes unlisted preventive medicine services.

Exclusion Criteria: Excludes visits that are not performed in-person, including telehealth services.

Subject constrained to the Preventive Care Services - Other

EncounterPerformed: Data elements that meet criteria using this datatype should document that the encounter indicated by the QDM category and its corresponding value set is in progress or has been completed. Timing: The Relevant Period addresses: startTime – The time the encounter began (admission time) stopTime – The time the encounter ended (discharge time). The Author dateTime addresses when an Encounter is documented. Documentation can occur at the beginning, during, at the end or subsequent to the end of an Encounter. The Author dateTime should be used only if the Relevant Period cannot be obtained. The Location Period is an attribute of the attribute facility location addresses: startTime = the time the patient arrived at the location; stopTime = the time the patient departed from the location

DataType

Cardinality

PreventiveCareServicesOtherPerformed

0..*

AromataseInhibitorsActive

Clinical Focus: This value set identifies patients who were prescribed a aromatase inhibitor.

Data Element Scope: This value set was intended to map to the QDM data type of Medication, but has the potential to be used in additional ways.

Inclusion Criteria: Includes both steroidal and non-steroidal inhibitors. Includes non-selective and selective inhibitors.

Exclusion Criteria: Excludes selective inhibitors vorozole, formestane, and fadrozole.

Subject constrained to the Aromatase Inhibitors

MedicationActive: Data elements that meet criteria using this datatype should document that the medication indicated by the QDM category and its corresponding value set is being taken by the patient. Keep in mind that when this datatype is used with timing relationships, the criterion is looking for a medication being taken for the time frame indicated by the timing relationships. Timing: The Relevant Period addresses: StartTime = when the medication is first known to be used (generally the time of entry on the medication list); StopTime = when the medication is discontinued (generally, the time discontinuation is recorded on the medication list)

DataType

Cardinality

AromataseInhibitorsActive

0..*

AromataseInhibitorsOrder

Clinical Focus: This value set identifies patients who were prescribed a aromatase inhibitor.

Data Element Scope: This value set was intended to map to the QDM data type of Medication, but has the potential to be used in additional ways.

Inclusion Criteria: Includes both steroidal and non-steroidal inhibitors. Includes non-selective and selective inhibitors.

Exclusion Criteria: Excludes selective inhibitors vorozole, formestane, and fadrozole.

Subject constrained to the Aromatase Inhibitors

MedicationOrder: Data elements that meet criteria using this datatype should document a request to a pharmacy to provide the medication indicated by the QDM category and its corresponding value set. Timing: The Author dateTime is the time the order is signed. Timing: The Relevant Period addresses: startTime = when the first administration of the medication is expected. The first administration may be expected at the time of the order or at a specified future date (i.e., the active time for the order); such information should be identified in the medication order. If the startTime is not specified in the order, the startTime defaults to the Author dateTime (the time the order is signed). stopTime = when the medication supply provided by the medication order is expected to be completed, including all fulfillments covered by the number of refills. Note that when calculating cumulative medication duration, the stopTime may be present directly in the medication order. If the stopTime is not available, the duration in days is the difference between the Relevant Period start and stop times multiplied by (1 + the number of refills). Refer to Special Cases in Appendix A (Section A.3) for scenarios to consider in calculating cumulative medication duration.

DataType

Cardinality

AromataseInhibitorsOrder

0..*

GlucocorticoidsOralOnlyActive

Clinical Focus: This set of values contains codes that are used to identify medications used as oral steroids.

Data Element Scope: This value set is developed for the medication QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include cortisone, dexamethasone, hydrocortisone, predenisone, methyprednisone, triamcinolone, betamethasone, dexamethasone, fludrocortisone and triamcinolone. Include only glucocorticoids taken orally, i.e., through an tablet, capsule, or oral solution.

Exclusion Criteria: Exclude all glucocorticoids taken non-orally, i.e., as a nasal inhalant or injectable solution.

Subject constrained to the Glucocorticoids (oral only)

MedicationActive: Data elements that meet criteria using this datatype should document that the medication indicated by the QDM category and its corresponding value set is being taken by the patient. Keep in mind that when this datatype is used with timing relationships, the criterion is looking for a medication being taken for the time frame indicated by the timing relationships. Timing: The Relevant Period addresses: StartTime = when the medication is first known to be used (generally the time of entry on the medication list); StopTime = when the medication is discontinued (generally, the time discontinuation is recorded on the medication list)

DataType

Cardinality

GlucocorticoidsOralOnlyActive

0..*

EthnicityPatientCharacteristicEthnicity

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

ResultValue constrained to codes in the Ethnicity valueset (2.16.840.1.114222.4.11.837)

PatientCharacteristicEthnicity: Data elements that meet criteria using this datatype should document that the patient has one or more of the ethnicities indicated by the QDM category and its corresponding value set. Timing: Ethnicity does not have a specific timing. Measures using Patient Characteristic, Ethnicity should address the most recent entry in the clinical record.

DataType

Cardinality

EthnicityPatientCharacteristicEthnicity

0..*

OncAdministrativeSexPatientCharacteristicGender

Clinical Focus: Gender identity restricted to only Male and Female used in administrative situations requiring a restriction to these two categories.

Data Element Scope: Gender

Inclusion Criteria: Male and Female only.

Exclusion Criteria: Any gender identity that is not male or female.

ResultValue constrained to codes in the ONC Administrative Sex valueset (2.16.840.1.113762.1.4.1)

PatientCharacteristicGender: Data elements that meet criteria using this datatype should document that the patient's sex matches the QDM category and its corresponding value set. Timing: Birth (administrative) sex does not have a specific timing.

DataType

Cardinality

OncAdministrativeSexPatientCharacteristicGender

0..*

FemalePatientCharacteristicGender

Clinical Focus: Concepts that represent Female when assessing quality measures

Data Element Scope: Gender

Inclusion Criteria: Appropriate female gender concepts

Exclusion Criteria: Concepts representing Male gender

ResultValue constrained to codes in the Female valueset (2.16.840.1.113883.3.560.100.2)

PatientCharacteristicGender: Data elements that meet criteria using this datatype should document that the patient's sex matches the QDM category and its corresponding value set. Timing: Birth (administrative) sex does not have a specific timing.

DataType

Cardinality

FemalePatientCharacteristicGender

0..*

PayerPatientCharacteristicPayer

Clinical Focus: Categories of types of health care payor entities as defined by the US Public Health Data Consortium SOP code system

Data Element Scope: @code in CCDA r2.1 template Planned Coverage [act: identifier urn:oid:2.16.840.1.113883.10.20.22.4.129 (open)] DYNAMIC

Inclusion Criteria: All codes in the code system

Exclusion Criteria: none

ResultValue constrained to codes in the Payer valueset (2.16.840.1.114222.4.11.3591)

PatientCharacteristicPayer: Data elements that meet criteria using this datatype should document that the patient has one or more of the payers indicated by the QDM category and its corresponding value set. Timing: The Relevant Period addresses: startTime – The first day of insurance coverage with the referenced payer stopTime – The last day of insurance coverage with the referenced payer

DataType

Cardinality

PayerPatientCharacteristicPayer

0..*

WhitePatientCharacteristicRace

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

ResultValue constrained to codes in the White valueset (2.16.840.1.113883.3.464.1003.123.12.1007)

PatientCharacteristicRace: Data elements that meet criteria using this datatype should document the patient’s race. Timing: Race does not have a specific timing. Measures using Patient Characteristic, Race should address the most recent entry in the clinical record.

DataType

Cardinality

WhitePatientCharacteristicRace

0..*

RacePatientCharacteristicRace

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

ResultValue constrained to codes in the Race valueset (2.16.840.1.114222.4.11.836)

PatientCharacteristicRace: Data elements that meet criteria using this datatype should document the patient’s race. Timing: Race does not have a specific timing. Measures using Patient Characteristic, Race should address the most recent entry in the clinical record.

DataType

Cardinality

RacePatientCharacteristicRace

0..*

BmiRatioPerformed

Clinical Focus:

Data Element Scope:

Inclusion Criteria:

Exclusion Criteria:

Subject constrained to the BMI Ratio

PhysicalExamPerformed: Data elements that meet criteria using this datatype should document the completion of the physical exam indicated by the QDM category and its corresponding value set. Timing: The Relevant Period addresses: startTime – The time the physical examination activity begins. stopTime – The time the physical examination activity ends. NOTE - timing refers to a single instance of a physical examination activity. If a measure seeks to evaluate multiple physical examination activities over a period of time, the measure developer should use CQL logic to represent the query request.

DataType

Cardinality

BmiRatioPerformed

0..*

GastricBypassSurgeryPerformed

Clinical Focus: This set of values contains codes that can be used to identify patients who have undergone a partial or total removeal of the stomach by either a laparoscopic or open method.

Data Element Scope: This value set is developed for the procedure QDM datatype. It can potentially be used for other datatypes as well.

Inclusion Criteria: Include codes that identify procedures for repair or removal of digestive system organs that include a partial or total removal of the stomach.

Exclusion Criteria: Exclude endoscopic excision of tissue of stomach, excision/laparoscopic wedge resection of lesion of stomach, and incisional biopsy of stomach.

Subject constrained to the Gastric Bypass Surgery

ProcedurePerformed: Data elements that meet criteria using this datatype should document the completion of the procedure indicated by the QDM category and its corresponding value set. Timing: The Relevant Period addresses: StartTime = the time the procedure begins; StopTime = the time the procedure is completed NOTE: 1) Timing refers to a single instance of a procedure. If a measure seeks to evaluate multiple procedures over a period of time, the measure developer should use CQL logic to represent the query request. 2) The Incision dateTime is a single point in time available from the Operating Room and/or Anesthesia Record.

DataType

Cardinality

GastricBypassSurgeryPerformed

0..*