scholarly journals Population-based data sources for chronic disease surveillance

2008 ◽  
Vol 29 (1) ◽  
pp. 31-38 ◽  
Author(s):  
L.M. Lix ◽  
M.S. Yogendran ◽  
S. Shaw ◽  
C. Burchill ◽  
C. Metge ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Survey Data ◽  
Administrative Data ◽  
Disease Surveillance ◽  
Canadian Community Health Survey ◽  
Population Based ◽  
Case Definition ◽  
Data Sources ◽  
Case Definitions ◽  
Disease Case

This study estimated agreement between population-based administrative and survey data for ascertaining cases of arthritis, asthma, diabetes, heart disease, hypertension and stroke. Chronic disease case definitions that varied by data source, number of years and number of diagnosis or prescription drug codes were constructed from Manitoba's administrative data. These data were linked to the Canadian Community Health Survey. Agreement between the two data sources, estimated by the κ coefficient, was calculated for each case definition, and differences were tested. Socio-demographic and comorbidity variables associated with agreement were tested using weighted logistic regression. Agreement was strongest for diabetes and hypertension and lowest for arthritis. The case definition elements that contributed to the highest agreement between the two population-based data sources varied across the chronic diseases. Low agreement between administrative and survey data is likely to occur for conditions that are difficult to diagnose, but will be mediated by individual socio-demographic and health status characteristics. Construction of a chronic disease case definition from administrative data should be accompanied by a justification for the choice of each of its elements.

scholarly journals Establishing the Incidence and Prevalence of Multiple Sclerosis in Saskatchewan

2018 ◽  
Vol 45 (3) ◽  
pp. 295-303 ◽  
Author(s):  
Lina H. Al-Sakran ◽  
Ruth Ann Marrie ◽  
David F. Blackburn ◽  
Katherine B. Knox ◽  
Charity D. Evans
Keyword(s):  
Multiple Sclerosis ◽  
Administrative Data ◽  
Predictive Value ◽  
Disease Surveillance ◽  
Population Based ◽  
Case Definition ◽  
Case Definitions ◽  
Health Administrative Data ◽  
Disease Surveillance System ◽  
Definition Of

AbstractObjective: To validate a case definition of multiple sclerosis (MS) using health administrative data and to provide the first province-wide estimates of MS incidence and prevalence for Saskatchewan, Canada. Methods: We used population-based health administrative data between January 1, 1996 and December 31, 2015 to identify individuals with MS using two potential case definitions: (1) ≥3 hospital, physician, or prescription claims (Marrie definition); (2) ≥1 hospitalization or ≥5 physician claims within 2 years (Canadian Chronic Disease Surveillance System [CCDSS] definition). We validated the case definitions using diagnoses from medical records (n=400) as the gold standard. Results: The Marrie definition had a sensitivity of 99.5% (95% confidence interval [CI] 92.3-99.2), specificity of 98.5% (95% CI 97.3-100.0), positive predictive value (PPV) of 99.5% (95% CI 97.2-100.0), and negative predictive value (NPV) of 97.5% (95% CI 94.4-99.2). The CCDSS definition had a sensitivity of 91.0% (95% CI 81.2-94.6), specificity of 99.0% (95% CI 96.4-99.9), PPV of 98.9% (95% CI 96.1-99.9), and NPV of 91.7% (95% CI 87.2-95.0). Using the more sensitive Marrie definition, the average annual adjusted incidence per 100,000 between 2001 and 2013 was 16.5 (95% CI 15.8-17.2), and the age- and sex-standardized prevalence of MS in Saskatchewan in 2013 was 313.6 per 100,000 (95% CI 303.0-324.3). Over the study period, incidence remained stable while prevalence increased slightly. Conclusion: We confirm Saskatchewan has one of the highest rates of MS in the world. Similar to other regions in Canada, incidence has remained stable while prevalence has gradually increased.

scholarly journals How do we enhance linked administrative data based chronic disease surveillance in Canada? Results of an environmental scan.

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Raquel Duchen ◽  
Lisa Lix ◽  
Kim Reimer ◽  
Jessica Widdifield ◽  
Debra Butt ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Administrative Data ◽  
Disease Surveillance ◽  
Grey Literature ◽  
Case Definition ◽  
Case Definitions ◽  
Standard Case ◽  
Environmental Scan ◽  
Mesh Terms ◽  
Linked Administrative Data

IntroductionThe Canadian Chronic Disease Surveillance System (CCDSS) is a collaboration of provincial and territorial surveillance systems which generates estimates of chronic diseases using linked population-level administrative health databases and standard case definitions. We conducted an environmental scan of administrative data validation studies and identified opportunities for CCDSS case definition enhancement. Objectives and ApproachThe purpose of this project is to develop a methodology for and conduct an environmental scan, identifying opportunities for enhancing the CCDSS. This multifaceted approach consists of the following elements: 1) key informant interviews and stakeholder consultations to identify new and existing priority conditions for updating/validating within the CCDSS, and new areas of conceptual and methodological relevance for administrative data disease surveillance, 2) a systematic literature review of PubMed, Ovid and Embase from 2013-2017 using MeSH terms and a librarian peer-reviewed search strategy, and 3) a review of the grey literature. ResultsKey stakeholders identified the following priorities for validation work and/or case definition enhancement: diabetes, mood and anxiety disorders, schizophrenia, obesity, hypertension, chronic obstructive pulmonary disease, osteoarthritis, stroke, early-onset dementia, rheumatoid arthritis and gout. Scientific and grey literature reviews of validation work for these conditions examined the following concepts/methods: 1) evaluating validity of disease-specific case definitions over time, and in different ages, sub-populations and settings, 2) defining incidence versus prevalence using linked administrative data, 3) determining opportunities and constraints of using linked administrative data to conduct surveillance on diseases that are chronic versus episodic in nature and defining active versus lifetime prevalence, and 4) assessing the feasibility of using new sources of data for linkage to enhance case definition validity. Conclusion/ImplicationsUtilization of linked administrative databases for chronic disease surveillance has expanded across many jurisdictions since the inception of the CCDSS. As disease estimates generated in this manner are increasingly being relied upon by policy makers working to enhance public health, the methodological opportunities and constraints identified here require consideration.

scholarly journals Validation of a Case Definition for Pediatric Brain Injury Using Administrative Data

2017 ◽  
Vol 44 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Jane McChesney-Corbeil ◽  
Karen Barlow ◽  
Hude Quan ◽  
Guanmin Chen ◽  
Samuel Wiebe ◽  
...  
Keyword(s):  
Brain Injury ◽  
Administrative Data ◽  
Predictive Value ◽  
External Validation ◽  
Secondary Data ◽  
Population Based ◽  
Case Definition ◽  
Case Definitions ◽  
Icd 10 ◽  
Pediatric Tbi

AbstractBackground: Health administrative data are a common population-based data source for traumatic brain injury (TBI) surveillance and research; however, before using these data for surveillance, it is important to develop a validated case definition. The objective of this study was to identify the optimal International Classification of Disease , edition 10 (ICD-10), case definition to ascertain children with TBI in emergency room (ER) or hospital administrative data. We tested multiple case definitions. Methods: Children who visited the ER were identified from the Regional Emergency Department Information System at Alberta Children’s Hospital. Secondary data were collected for children with trauma, musculoskeletal, or central nervous system complaints who visited the ER between October 5, 2005, and June 6, 2007. TBI status was determined based on chart review. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each case definition. Results: Of 6639 patients, 1343 had a TBI. The best case definition was, “1 hospital or 1 ER encounter coded with an ICD-10 code for TBI in 1 year” (sensitivity 69.8% [95% confidence interval (CI), 67.3-72.2], specificity 96.7% [95% CI, 96.2-97.2], PPV 84.2% [95% CI 82.0-86.3], NPV 92.7% [95% CI, 92.0-93.3]). The nonspecific code S09.9 identified >80% of TBI cases in our study. Conclusions: The optimal ICD-10–based case definition for pediatric TBI in this study is valid and should be considered for future pediatric TBI surveillance studies. However, external validation is recommended before use in other jurisdictions, particularly because it is plausible that a larger proportion of patients in our cohort had milder injuries.

scholarly journals The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Lisa Lix ◽  
James Ayles ◽  
Sharon Bartholomew ◽  
Charmaine Cooke ◽  
Joellyn Ellison ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Health Agency ◽  
Population Based ◽  
Population Characteristics ◽  
Administrative Databases ◽  
Distributed Model ◽  
Case Definitions ◽  
Disease Surveillance System

Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities.

scholarly journals The Canadian Chronic Disease Surveillance System: A Distributed Surveillance Model

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Lisa Lix ◽  
Kim Reimer
Keyword(s):  
Health Insurance ◽  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Feasibility Studies ◽  
Mental Illnesses ◽  
Population Characteristics ◽  
Case Definitions ◽  
Disease Surveillance System ◽  
Disease Case

ObjectiveTo describe the process, benefits, and challenges of implementinga distributed model for chronic disease surveillance across thirteenCanadian jurisdictions.IntroductionThe Public Health Agency of Canada (PHAC) established theCanadian Chronic Disease Surveillance System (CCDSS) in 2009 tofacilitate national estimates of chronic disease prevalence, incidence,and health outcomes. The CCDSS uses population-based linkedhealth administrative databases from all provinces/territories (P/Ts)and a distributed analytic protocol to produce standardized diseaseestimates.MethodsThe CCDSS is founded on deterministic linkage of threeadministrative health databases in each Canadian P/T: health insuranceregistration files, physician billing claims, and hospital dischargeabstracts. Data on all residents who are eligible for provincial orterritorial health insurance (about 97% of the Canadian population) arecaptured in the health insurance registration files. Thus, the CCDSScoverage is near-universal. Disease case definitions are developed byexpert Working Groups after literature reviews are completed andvalidation studies are undertaken. Feasibility studies are initiatedin selected P/Ts to identify challenges when implementing thedisease case definitions. Analytic code developed by PHAC is thendistributed to all P/Ts. Data quality surveys are routinely conductedto identify database characteristics that may bias disease estimatesover time or across P/Ts or affect implementation of the analytic code.The summary data produced in each P/T are approved by ScientificCommittee and Technical Committee members and then submitted toPHAC for further analysis and reporting.ResultsNational surveillance or feasibility studies are currently ongoing fordiabetes, hypertension, selected mental illnesses, chronic respiratorydiseases, heart disease, neurological conditions, musculoskeletalconditions, and stroke. The advantages of the distributed analyticprotocol are (Figure 1): (a) changes in methodology can be easilymade, and (b) technical expertise to implement the methodology is notrequired in each P/T. Challenges in the use of the distributed analyticprotocol are: (a) heterogeneity in healthcare databases across P/Tsand over time, (b) the requirement that each P/T use the minimum setof data elements common to all jurisdictions when producing diseaseestimates, and (c) balancing disclosure guidelines to ensure dataconfidentiality with comprehensive reporting. Additional challenges,which include incomplete data capture for some databases and poormeasurement validity of disease diagnosis codes for some chronicconditions, must be continually addressed to ensure the scientificrigor of the CCDSS methodology.ConclusionsThe CCDSS distributed analytic protocol offers one model fornational chronic disease surveillance that has been successfullyimplemented and sustained by PHAC and its P/T partners. Manylessons have been learned about national chronic disease surveillanceinvolving jurisdictions that are heterogeneous with respect tohealthcare databases, expertise, and population characteristics.

Incidence and prevalence of MS in children

Neurology ◽  
2018 ◽  
Vol 91 (17) ◽  
pp. e1579-e1590 ◽  
Author(s):  
Ruth Ann Marrie ◽  
Julia O'Mahony ◽  
Colleen Maxwell ◽  
Vicki Ling ◽  
E. Ann Yeh ◽  
...  
Keyword(s):  
Administrative Data ◽  
Predictive Value ◽  
Disease Surveillance ◽  
Pediatric Population ◽  
Case Definition ◽  
Health Claims ◽  
Healthy Children ◽  
Case Definitions ◽  
Health Claims Data ◽  
Definition Of

ObjectiveTo validate a case definition of multiple sclerosis (MS) in the pediatric population using administrative (health claims) data, and to estimate the incidence and prevalence of MS in the pediatric population for Ontario, Canada.MethodsWe used population-based administrative data to identify persons aged ≤18 years with MS. We assessed the performance of multiple administrative case definitions using a clinical reference cohort including children with MS, children with monophasic demyelinating syndromes, and healthy children; we report sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We applied 2 preferred case definitions to estimate the incidence and prevalence of MS from 2003 to 2014.ResultsThe Canadian Chronic Disease Surveillance System definition of ≥1 hospitalization or ≥5 physician claims for MS within 2 years had a sensitivity of 81.1%, specificity of 100%, PPV of 100%, and NPV of 86%. The Marrie definition of ≥3 hospital or physician claims for MS ever had a sensitivity of 89.2%, specificity of 100%, PPV of 100%, and NPV of 91.5%. Depending on the administrative case definition used, in 2014, the annual age-standardized annual incidence of MS in the pediatric population ranged from 0.99 to 1.24 per 100,000 population, and the age-standardized prevalence ranged from 4.03 to 6.8 per 100,000 population. The prevalence of MS rose over time.ConclusionAdministrative data provide a feasible, valid means of estimating the incidence and prevalence of MS in the pediatric population. MS prevalence in the Ontario pediatric population is among the highest reported in pediatric populations worldwide.

scholarly journals Quebec Integrated Chronic Disease Surveillance System (QICDSS), an innovative approach

2014 ◽  
Vol 34 (4) ◽  
pp. 226-235 ◽  
Author(s):  
C Blais ◽  
S Jean ◽  
C Sirois ◽  
L Rochette ◽  
C Plante ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Chronic Diseases ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Selection Criterion ◽  
Population Based ◽  
Administrative Databases ◽  
Case Definitions ◽  
Public Health Decision ◽  
Disease Surveillance System

Introduction With the growing burden of chronic diseases, surveillance will play an essential role in improving their prevention and control. The Institut national de santé publique du Québec has developed an innovative chronic disease surveillance system, the Quebec Integrated Chronic Disease Surveillance System (QICDSS). We discuss the primary features, strengths and limitations of this system in this report. Methodology The QICDSS was created by linking five health administrative databases. Updated annually, it currently covers the period from January 1, 1996, to March 31, 2012. The operational model comprises three steps: (1) extraction and linkage of health administrative data according to specific selection criteria; (2) analysis (validation of case definitions essentially) and production of surveillance measures; and (3) data interpretation, submission and dissemination of information. The QICDSS allows the surveillance of the following chronic diseases: diabetes, cardiovascular diseases, respiratory diseases, osteoporosis, osteoarticular diseases, mental disorders, Alzheimer's disease and related disorders. The system also lends itself to the analysis of multimorbidity and polypharmacy. Results For 2011–2012, the QICDSS contained information on 7 995 963 Quebecers with an average age of 40.8 years. Of these, 95.3% met at least one selection criterion allowing the application of case definitions for chronic disease surveillance. The actual proportion varied with age, from 90.1% for those aged 19 years or less to 99.3% for those aged 65 years or over. Conclusion The QICDSS provides a way of producing population-based data on the chronic disease burden, health services and prescription drug uses. The system facilitates the integrated study of several diseases in combination, an approach rarely implemented until now in the context of population surveillance. The QICDSS possesses all the essential features of a surveillance system and supports the dissemination of information to public health decision-makers for future actions.

scholarly journals The Canadian Chronic Disease Surveillance System: The Benefits and Challenges of a Distributed Model for National Disease Surveillance

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Lisa Lix ◽  
Kim Reimer
Keyword(s):  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Feasibility Studies ◽  
Population Characteristics ◽  
Distributed Model ◽  
Case Definitions ◽  
Disease Surveillance System ◽  
Disease Case ◽  
Over Time

ABSTRACT ObjectivesThe Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate national estimates of chronic disease prevalence, incidence, and health outcomes. The CCDSS uses population-based linked health administrative databases from all provinces/territories (P/Ts) and a distributed analytic protocol to produce standardized disease estimates. Our purpose is to describe the process, benefits, and challenges of implementing a distributed model for disease surveillance across thirteen jurisdictions with unique healthcare databases. ApproachThe CCDSS is founded on deterministic linkage of three administrative health databases in each Canadian P/T: health insurance registration files, physician billing claims, and hospital discharge abstracts. Disease case definitions are developed by expert Working Groups after literature reviews are completed and validation studies are undertaken. Feasibility studies are initiated in selected P/Ts to identify challenges when implementing the disease case definitions. Analytic code developed by PHAC is then distributed to all P/Ts. Data quality surveys are routinely conducted to identify database characteristics that may bias disease estimates over time or across P/Ts or affect implementation of the analytic code. The summary data produced in each P/T are approved by Scientific Committee and Technical Committee members and then submitted to PHAC for further analysis and reporting. ResultsNational surveillance or feasibility studies are currently ongoing for diabetes, hypertension, selected mental illnesses, chronic respiratory diseases, heart disease, neurological conditions, musculoskeletal conditions, and stroke. The advantages of the distributed analytic protocol are: (a) changes in methodology can be easily made, and (b) technical expertise to implement the methodology is not required in each P/T. Challenges in the use of the distributed analytic protocol are: (a) heterogeneity in healthcare databases across P/Ts and over time, (b) the requirement that each P/T use the minimum set of data elements common to all jurisdictions when producing disease estimates, and (c) balancing disclosure guidelines to ensure data confidentiality with comprehensive reporting. Additional challenges, which include incomplete data capture for some databases and poor measurement validity of disease diagnosis codes for some chronic conditions, must be continually addressed to ensure the scientific rigor of the CCDSS methodology. ConclusionsThe CCDSS distributed analytic protocol offers one model for national chronic disease surveillance that has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national chronic disease surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise, and population characteristics.

Estimating the incidence of first-episode psychosis using population-based health administrative data to inform early psychosis intervention services

2018 ◽  
Vol 49 (12) ◽  
pp. 2091-2099 ◽  
Author(s):  
Kelly K. Anderson ◽  
Ross Norman ◽  
Arlene G. MacDougall ◽  
Jordan Edwards ◽  
Lena Palaniyappan ◽  
...  
Keyword(s):  
Psychotic Disorder ◽  
Administrative Data ◽  
Catchment Area ◽  
Population Based ◽  
First Episode Psychosis ◽  
Case Definition ◽  
First Episode ◽  
Affective Psychosis ◽  
Health Administrative Data ◽  
Episode Psychosis

AbstractBackgroundDiscrepancies between population-based estimates of the incidence of psychotic disorder and the treated incidence reported by early psychosis intervention (EPI) programs suggest additional cases may be receiving services elsewhere in the health system. Our objective was to estimate the incidence of non-affective psychotic disorder in the catchment area of an EPI program, and compare this to EPI-treated incidence estimates.MethodsWe constructed a retrospective cohort (1997–2015) of incident cases of non-affective psychosis aged 16–50 years in an EPI program catchment using population-based linked health administrative data. Cases were identified by either one hospitalization or two outpatient physician billings within a 12-month period with a diagnosis of non-affective psychosis. We estimated the cumulative incidence and EPI-treated incidence of non-affective psychosis using denominator data from the census. We also estimated the incidence of first-episode psychosis (people who would meet the case definition for an EPI program) using a novel approach.ResultsOur case definition identified 3245 cases of incident non-affective psychosis over the 17-year period. We estimate that the incidence of first-episode non-affective psychosis in the program catchment area is 33.3 per 100 000 per year (95% CI 31.4–35.1), which is more than twice as high as the EPI-treated incidence of 18.8 per 100 000 per year (95% CI 17.4–20.3).ConclusionsCase ascertainment strategies limited to specialized psychiatric services may substantially underestimate the incidence of non-affective psychotic disorders, relative to population-based estimates. Accurate information on the epidemiology of first-episode psychosis will enable us to more effectively resource EPI services and evaluate their coverage.

scholarly journals Existing comorbidities in people with osteoarthritis: a retrospective analysis of a population-based cohort in Alberta, Canada

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e033334 ◽  
Author(s):  
Deborah A Marshall ◽  
Xiaoxiao Liu ◽  
Cheryl Barnabe ◽  
Karen Yee ◽  
Peter D Faris ◽  
...  
Keyword(s):  
Cohort Analysis ◽  
Age Groups ◽  
Population Based ◽  
Case Definition ◽  
Chronic Obstructive ◽  
Age Group ◽  
Case Definitions ◽  
Obstructive Pulmonary Disease ◽  
Physician Visits ◽  
Significant Difference

ObjectivesThe purpose of this study is to estimate the prevalence of comorbidities among people with osteoarthritis (OA) using administrative health data.DesignRetrospective cohort analysis.SettingAll residents in the province of Alberta, Canada registered with the Alberta Health Care Insurance Plan population registry.Participants497 362 people with OA as defined by ‘having at least one OA-related hospitalization, or at least two OA-related physician visits or two ambulatory care visits within two years’.Primary outcome measuresWe selected eight comorbidities based on literature review, clinical consultation and the availability of validated case definitions to estimate their frequencies at the time of diagnosis of OA. Sex-stratified age-standardised prevalence rates per 1000 population of eight clinically relevant comorbidities were calculated using direct standardisation with 95% CIs. We applied χ2 tests of independence with a Bonferroni correction to compare the percentage of comorbid conditions in each age group.Results54.6% (n=2 71 794) of people meeting the OA case definition had at least one of the eight selected comorbidities. Females had a significantly higher rate of comorbidities compared with males (standardised rates ratio=1.26, 95% CI 1.25 to 1.28). Depression, chronic obstructive pulmonary disease (COPD) and hypertension were the most prevalent in both females and males after age-standardisation, with 40% of all cases having any combination of these comorbidities. We observed a significant difference in the percentage of comorbidities among age groups, illustrated by the youngest age group (<45 years) having the highest percentage of cases with depression (24.6%), compared with a frequency of 16.1% in those >65 years.ConclusionsOur findings highlight the high frequency of comorbidity in people with OA, with depression having the highest age-standardised prevalence rate. Comorbidities differentially affect females, and vary by age. These factors should inform healthcare programme and delivery.

Sign in / Sign up

Export Citation Format

Share Document