Fracture profiles of a 4-year cohort of 266,324 first incident upper extremity fractures from population health data in Ontario

Background Understanding the profiles of different upper extremity fractures, particularly those presenting as a 1st incident can inform prevention and management strategies. The purpose of this population-level study was to describe first incident fractures of the upper extremity in terms of fracture characteristics and demographics. Methods Cases with a first adult upper extremity (UE) fracture from the years 2013 to 2017 were extracted from administrative data in Ontario. Fracture locations (ICD-10 codes) and associated characteristics (open/closed, associated hospitalization within 1-day, associated nerve, or tendon injury) were described by fracture type, age category and sex. Standardized mean differences of at least 10% (clinical significance) and statistical significance (p < 0.01) in ANOVA were used to identify group differences (age/sex). Results We identified 266,324 first incident UE fractures occurring over 4 years. The most commonly affected regions were the hand (93 K), wrist/forearm(80 K), shoulder (48 K) or elbow (35 K). The highest number of specific fractures were: distal radius (DRF, 47.4 K), metacarpal (30.4 K), phalangeal (29.9 K), distal phalangeal (24.4 K), proximal humerus (PHF, 21.7 K), clavicle (15.1 K), radial head (13.9 K), and scaphoid fractures (13.2 K). The most prevalent multiple fractures included: multiple radius and ulna fractures (11.8 K), fractures occurring in multiple regions of the upper extremity (8.7 K), or multiple regions in the forearm (8.4 K). Tendon (0.6% overall; 8.2% in multiple finger fractures) or nerve injuries were rarely reported (0.3% overall, 1.5% in distal humerus). Fractures were reported as being open in 4.7% of cases, most commonly for distal phalanx (23%). A similar proportion of females (51.5%) and males were present in this fracture cohort, but there were highly variant age-sex profiles across fracture subtypes. Fractures most common in 18–40-year-old males included metacarpal and finger fractures. Fractures common in older females were: DRF, PHF and radial head, which exhibited a dramatic increase in the over-50 age group. Conclusions UE fracture profiles vary widely by fracture type. Fracture specific prevention and management should consider fracture profiles that are highly variable according to age and sex. Supplementary Information The online version contains supplementary material available at 10.1186/s12891-021-04849-7.

The CCRS-LTC database is compiled by the Canadian Institute for Health Information (CIHI) and comprises all mandatory, clinical assessments performed on nursing home residents in Ontario. In Ontario nursing homes, full assessments are completed on admission, annually, and following any significant change in health status; briefer assessments occur on a quarterly basis. Nursing home assessments are made using the Resident Assessment Instrument Minimum Data Set (RAI-MDS) version 2.0 which are administered by trained healthcare professionals. The instrument captures data on the physical, functional, cognitive, and social domains of health. In a large-scale international study of the reliability of RAI instruments, agreement (average weighted kappa statistics) for the 19 information domains in the long-term care facility instrument ranged from 0.63 to 0.93, with a median value of 0.83. (1) Discharge Abstract Database (DAD) The DAD is compiled by the Canadian Institute for Health Information (CIHI) and contains administrative, clinical (diagnoses and procedures/interventions), demographic, and administrative information for all admissions to acute care hospitals in Ontario. At ICES, consecutive DAD records are linked together to form 'episodes of care' among the hospitals to which patients have been transferred after their initial admission.
Prior to April 1, 2002, diagnoses (up to 16 on a given DAD record) are captured using the International Statistical Classification of Diseases, Injuries, and Causes of Death, 9 th Revision (ICD-9) coding system and procedures (up to 10 on a given DAD record) are captured using the Canadian Classification of Diagnostic, Therapeutic, and Surgical Procedures (CCP) coding system. Prior to April 1, 2002, diagnoses (up to 6 on a given NACRS record) are captured using the ICD-9 coding system and procedures (up to 10 on a given NACRS record) are captured using the CCP coding system. Following April 1, 2002, diagnoses (up to 10 on a given NACRS record) are captured using the ICD-10-CA coding system and interventions (up to 10 on a given NACRS record) are captured using the CCI coding system. NACRS emergency department diagnosis codes have been extensively validated. Ontario Drug Benefit (ODB) program database The ODB database contains prescription medication claims for those covered under the provincial drug program, mainly: those aged 65 years and older, nursing home residents, patients receiving services under the Ontario Home Care program, those receiving social assistance, and residents eligible for specialized drug programs (e.g., programs which cover the costs of medications for individuals whose medication costs exceed 4% of their net household income and for individuals with rare, serious conditions such as Cystic Fibrosis).
Each medication claim has an associated prescriber identifier which indicates the health practitioner who wrote the prescription, as well as fields that identify the type and quantity of medication and duration of treatment. A special flag in the ODB database indicates whether the prescription was dispensed to a nursing home resident.
An audit of 100 randomly selected prescriptions dispensed from 50 Ontario pharmacies determined that the ODB had an error rate of 0.7% and none of the pharmacy characteristics examined (locations, owner affiliation, productivity) were associated with coding errors. The OHIP claims database contains information on inpatient and outpatient services provided to Ontario residents eligible for the province's publicly funded health insurance system by fee-forservice health care practitioners (primarily physicians) and "shadow billings" for those paid through non-fee-for-service payment plans.
Billing codes on the claims (OHIP fee codes) identify the care provider, their area of specialization and the type and location of service. OHIP billing claims also contain a 3-digit diagnosis codethe main reason for the service -captured using a modified version of the ICD, 8 th revision coding system. OHIP claims are well completed, but the validity of the diagnosis coding is highly variable.(4) Ontario Mental Health Reporting System (OMHRS) The OMHRS is compiled by the Canadian Institute for Health Information (CIHI) and contains administrative, clinical (diagnoses and procedures), demographic, and administrative information for all admissions to adult designated inpatient mental health beds. This includes beds in general hospitals, provincial psychiatric facilities, and specialty psychiatric facilities. Clinical assessment data is ascertained using the Resident Assessment Instrument for Mental Health (RAI-MH), but different amounts of information are collected using this instrument depending on the length of stay in the mental health bed. Multiple assessments may occur during the length of a mental health admission.
Psychiatric diagnoses are captured using the Diagnostic and Statistical Manual of Mental Disorders, 4 th Edition, Text Revision (DSM-IV-TR) coding system. Non-psychiatric diagnoses are captured using the ICD-10-CA coding system.

Same-Day Surgery (SDS) database
The SDS is compiled by the Canadian Institute for Health Information (CIHI) and contains administrative, clinical (diagnoses and procedures), demographic, and administrative information for all patient visits made to day surgery institutions in Ontario.
Prior to April 1, 2002, diagnoses (up to 16 on a given SDS record) were captured using the ICD-9 coding system and procedures (up to 10 on a given SDS record) were captured using the CCP coding system. Since April 1, 2002, diagnoses (up to 25 on a given SDS record) are captured using the ICD-10-CA coding system and interventions (up to 16 on a given SDS record) are captured using the CCI coding system.

ICES-derived cohorts Ontario Asthma Database
The Ontario Asthma Database is created using a definition of ≥2 physician billing claims with a diagnosis of asthma (OHIP diagnosis code: 493) and/or ≥1 inpatient hospitalization or same day surgery record with a diagnosis of asthma (ICD-9 diagnosis code: 493; ICD-10 diagnosis codes: J45, J46; in any diagnostic code space) in a two-year period applied to hospitalization (DAD), same day surgery (SDS), and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of asthma in Ontario.
For those aged 18 years and older, the above definition, when using primary care chart abstraction as the reference standard, has been demonstrated to have the following performance characteristics: Sensitivity (80.6%), Specificity (81.4%), Positive Predictive Value (72.5%), and Negative Predictive Value (87.3%).(5) Ontario Congestive Heart Failure (CHF) Database The Ontario CHF Database is created using a definition of ≥2 physician billing claims with a diagnosis of CHF (OHIP diagnosis code: 428) and/or ≥1 inpatient hospitalization or same day surgery record with a diagnosis of CHF (ICD-9 diagnosis code: 428; ICD-two-year period applied to hospitalization (DAD), same day surgery (SDS), and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of CHF in Ontario.
When using electronic medical record data abstraction as the reference standard, the above definition has been demonstrated to have the following performance characteristics: Sensitivity (84.8%), Specificity (97.0%), and Positive Predictive Value (55.3%). (6) Ontario Chronic Obstructive Pulmonary Disease (COPD) Database The Ontario COPD Database is created using two separate algorithms applied to inpatient hospitalization (DAD), same day surgery (SDS) records, and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of COPD in Ontario.
In an algorithm which maximizes sensitivity, the definition for COPD is any physician billing claim with a diagnosis for COPD (OHIP diagnosis codes: 491, 492, 496) or any inpatient hospitalization or same day surgery record with a diagnosis for COPD (ICD-9 diagnosis codes: 491, 492, 496; ICD-10 diagnosis codes: J41-J44; in any diagnostic code space). When using expert panel review of primary care charts as the reference standard, this definition has been shown to have the following performance characteristics: Sensitivity (85.0%), Specificity (78.4%), Positive Predictive Value (57.5%), and Negative Predictive Value (93.8%). (7) In an algorithm which maximizes specificity, the definition for COPD is ≥3 physician billing claims with a diagnosis for COPD (OHIP diagnosis codes: 491, 492, 496) or ≥1 inpatient hospitalization or same day surgery record with a diagnosis for COPD (ICD-9 diagnosis codes: 491, 492, 496; ICD-10 diagnosis codes: J41, J42, J43, J44; in any diagnostic code space) in a twoyear period. When using expert panel review of primary care charts as the reference standard, this definition has been shown to have the following performance characteristics: Sensitivity The ODD is created using algorithms applied to inpatient hospitalization (DAD) records, same day surgery (SDS) records, and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of diabetes in Ontario.
For adults aged 19 years and greater, the definition for diabetes is 2 physician billing claims with a diagnosis for diabetes (OHIP diagnosis code: 250) or 1 inpatient hospitalization or same day surgery record with a diagnosis for diabetes (ICD-9 diagnosis code: 250; ICD-10 diagnosis codes: E10, E11, E13, E14; in any diagnostic code space) within a 2 year period. Physician claims and hospitalizations with a diagnosis of diabetes occurring within 120 prior to and 180 days after a gestational hospitalization record were excluded. When using primary care chart abstraction as the reference standard, this definition has been shown to have the following performance characteristics: When using primary care chart abstraction as the reference standard, the above definition has been demonstrated to have the following performance characteristics: Sensitivity (96.2%) and Specificity (99.6%).(10) Ontario Hypertension Database The Ontario Hypertension Database is created using a definition of ≥2 physician billing claims with a diagnosis of hypertension (OHIP diagnosis codes: 401-405) and/or ≥1 inpatient hospitalization or same day surgery record with a diagnosis of hypertension (ICD-9 diagnosis codes: 401-405; ICD-10 diagnosis codes: I10-I13, I15; in any diagnostic code space) in a two-year period applied to hospitalization (DAD), same day surgery (SDS), and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of hypertension in Ontario. Physician claims and hospitalizations with a diagnosis of hypertension occurring within 120 prior to and 180 days after a gestational hospitalization record are excluded.
When using electronic medical record data abstraction as the reference standard, the above definition has been demonstrated to have the following performance characteristics: Sensitivity (72%), Specificity (95%), Positive Predictive Value (87%), and Negative Predictive Value (88%).(11) Ontario Myocardial Infarction Database (OMID) The OMID contains records of all inpatient hospital admissions for acute myocardial infarctions (ICD-9 diagnosis code: 410; ICD-10 diagnosis code: I21; in the primary diagnostic code space) in Ontario since 1991. These admissions are ascertained using the DAD and exclude in-hospital events and admissions where there had been a previous discharge for acute myocardial infarction in the previous year. This cohort of patients with acute myocardial infarction hospital admissions is linked with hospitalization (DAD), same day surgery (SDS), and physician billing claims data (OHIP) to create indicators of hospital readmission after discharge and receipt of cardiac procedures during and after the initial hospital admission.
When using a clinical registry of acute coronary syndromes from 58 cardiac care units in Ontario as the reference standard, the above definition has been demonstrated to have the following performance characteristics: Sensitivity (92.8%), Specificity (88.9%), and Positive Predictive Value (88.5%). (12) Ontario Rheumatoid Arthritis Database (ORAD) The ORAD is created using a definition of ≥3 physician billing claims, and at least 1 claim billed by a musculoskeletal specialist, with a diagnosis of rheumatoid arthritis (OHIP diagnosis code: 714) and/or ≥1 inpatient hospitalization or same day surgery record with a diagnosis of rheumatoid arthritis (ICD-9 diagnosis code: 714; ICD-10 diagnosis codes: M05, M06; in any diagnostic code space) in a two-year period applied to hospitalization (DAD), same day surgery (SDS), and physician billing claims (OHIP) data to determine the diagnosis date for incident cases of rheumatoid arthritis in Ontario.

Population and demographics Client Agency Program Enrollment (CAPE) Database
The CAPE Database is a registry of all patients who have ever been rostered to receive care from a particular physician in Ontario and documents the time period in which a patient was rostered to a specific physician. Immigration, Refugees, and Citizenship Canada's (IRCC) Permanent Resident Database The Ontario portion of the IRCC Permanent Resident Database includes immigration application records for people who initially applied to land in Ontario since 1985. The dataset contains permanent residents' demographic information such as country of citizenship, level of education, mother tongue, and landing date. New immigrants who are currently residing in Ontario but originally landed in another province are not captured in this dataset. Office of the Registrar General (ORGD) Vital Statistics Database The ORGD Vital Statistics Database contains information on all deaths registered in Ontario starting on January 1, 1990. Information on the causes of death (immediate, antecedent, and underlying) recorded on the death certificate are captured. At ICES, we derive a single cause of death variable based on the underlying cause of death if available and, otherwise, the immediate cause of death using the ICD-9 coding system. OHIP Registered Persons Database (RPDB) The OHIP RPDB provides basic demographic information (age, sex, location of residence, date of birth, and date of death for deceased individuals) for those issued an Ontario health insurance number. The RPDB also indicates the time periods for which an individual was eligible to receive publicly funded health insurance benefits and the best known postal code for each registrant on July 1 st of each year.