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Estimating the Burden of Osteoarthritis to Plan for the Future
Abstract
Background:
With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) are expected to rise in Canada, increasing the demand for health resources. Resource planning to meet this increasing need requires estimates of the anticipated number of OA patients. Using administrative data from Alberta, we estimated OA incidence and prevalence rates and examined their sensitivity to alternative case definitions.
Methods:
We identified cases in a linked dataset spanning 1993 to 2010 (Population Registry, Discharge Abstract Database, Physician Claims, Ambulatory Care Classification System and prescription drug data) using diagnostic codes and drug identification numbers. In the base case, incident cases were captured for patients with an OA diagnostic code for at least two physician visits within two years or any hospital admission. Seven alternative case definitions were applied and compared.
Results:
Age-sex standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases/1000 population, respectively, in the base case. Physician Claims data alone captured 88% of OA cases. Prevalence rate estimates required 15 years of longitudinal data to plateau. Compared to base case, estimates are sensitive to alternative case definitions.
Conclusion:
Administrative databases are a key source for estimating the burden and epidemiological trends of chronic diseases such as OA in Canada. Despite their limitations, these data provide valuable information for estimating disease burden and planning health services. Estimates of OA are mostly defined through Physician Claims data and require a long period of longitudinal data. This article is protected by copyright. All rights reserved.
... Osteoarthritis (OA) is a significant cause of pain and disability affecting 1 in 8 (13%) Canadians [1]. The prevalence of OA is expected to increase, reaching 1 in 4 Canadians by 2040 due to ageing population and increasing prevalence of obesity [2,3]. Although there is no known cure for OA, early treatment and management are critical to slow the disease accessibility is the lack of available empirical data on the actual physician-seeking behavior [28][29][30][31] to verify model assumptions on the choice of reasonable catchment size as well as the distance decay pattern of health care utilization. ...
... In this study, we measured the realized access to three different types of health care providers for people with OA using utilized physician-seeking data. The aim of this study is three-fold: (1) to measure the rural-urban disparities in realized access to three types of health care providers (GPs, Ortho, and PTs); (2) to examine the spatial pattern of realized access at the local geographic area level; (3) to examine how the distance decay pattern of health care utilization varies along the rural-urban continuum. ...
... Cross-sectional study design was applied to examine the rural-urban disparities in realized access to multidisciplinary health care providers for adult people with OA. An adult OA-prevalent cohort (≥ 18 years of age at diagnosis) in fiscal year 2013 (1 April 2012-31 March 2013) was identified using the most current and validated case definition for administrative data [3,14]. ...
Rural Canadians have high health care needs due to high prevalence of osteoarthritis (OA) but lack access to care. Examining realized access to three types of providers (general practitioners (GPs), orthopedic surgeons (Ortho), and physiotherapists (PTs)) simultaneously helps identify gaps in access to needed OA care, inform accessibility assessment, and support health care resource allocation. Travel time from a patient's postal code to the physician's postal code was calculated using origin-destination network analysis. We applied descriptive statistics to summarize differences in travel time, hotspot analysis to explore geospatial patterns, and distance decay function to examine the travel pattern of health care utilization by urbanicity. The median travel time in Alberta was 11.6 min (IQR = 4.3-25.7) to GPs, 28.9 (IQR = 14.8-65.0) to Ortho, and 33.7 (IQR = 23.1-47.3) to PTs. We observed significant rural-urban disparities in realized access to GPs (2.9 and IQR = 0.0-92.1 in rural remote areas vs. 12.6 and IQR = 6.4-21.0 in metropolitan areas), Ortho (233.3 and IQR = 171.3-363.7 in rural remote areas vs. 21.3 and IQR = 14.0-29.3 in metropolitan areas), and PTs (62.4 and IQR = 0.0-232.1 in rural remote areas vs. 32.1 and IQR = 25.2-39.9 in metropolitan areas). We identified hotspots of realized access to all three types of providers in rural remote areas, where patients with OA tend to travel longer for health care. This study may provide insight on the choice of catchment size and the distance decay pattern of health care utilization for further studies on spatial accessibility.
... Rural-urban disparities in the prevalence of osteoarthritis (OA) have been reported at national and provincial levels in Canada, demonstrating significantly higher rates of OA in rural and remote areas compared to urban areas [1][2][3]. The population health burden of OA is expected to increase and reach one in four Canadians by 2040 [4,5] due to an aging population and rising rates of obesity [6,7]. Most importantly, patients suffering the use of non-local PCPs. ...
... We conducted a cross-sectional observational study to examine the spatial pattern of non-local PCP utilization and associated confounding factors using administrative health data. Prevalent OA cohort in the fiscal year 2012/13 (1 April 2012-31 March 2013) were identified using a validated OA case definition [2,7,34]. Exploratory spatial analysis was applied to detect spatial pattern of non-local PCP utilization. ...
... OA cases from 1 April 1994 to 31 March 2013 were identified using data from five AH administrative databases: Alberta Health Care Insurance Plan (AHCIP) population registry, the Physician Claims Database, the Discharge Abstract Database (DAD), and the Ambulatory Care Classification System (ACCS)/National Ambulatory Care Reporting System (NACRS) [7]. The criteria for our case definition included any patients who have at least one OA hospitalization or at least two OA physician claims within two years or at least two OA-related ambulatory care visits [2,7]. ...
The utilization of non-local primary care physicians (PCP) is a key primary care indicator identified by Alberta Health to support evidence-based healthcare planning. This study aims to identify area-level factors that are significantly associated with non-local PCP utilization and to examine if these associations vary between rural and urban areas. We examined rural-urban differences in the associations between non-local PCP utilization and area-level factors using multivariate linear regression and geographically weighted regression (GWR) models. Global Moran's I and Gi* hot spot analyses were applied to identify spatial autocorrelation and hot spots/cold spots of non-local PCP utilization. We observed significant rural-urban differences in the non-local PCP utilization. Both GWR and multivariate linear regression model identified two significant factors (median travel time and percentage of low-income families) with non-local PCP utilization in both rural and urban areas. Discontinuity of care was significantly associated with non-local PCP in the southwest, while the percentage of people having university degree was significant in the north of Alberta. This research will help identify gaps in the utilization of local primary care and provide evidence for health care planning by targeting policies at associated factors to reduce gaps in OA primary care provision.
... Our data sources were five Alberta Health (AH) administrative databases: Alberta Health Care Insurance Plan population registry (AHCIP), Physician Claims, Discharge Abstract Database (DAD), and Ambulatory Care Classification System (ACCS) /National Ambulatory Care Reporting System (NACRS) [4,17,22]. The AHCIP population registry captures individual level data (age, sex, postal code, death, etc.) on all persons who accessed health care services paid for by the provincial health care insurance plan. ...
... Each patient is assigned a unique patient identifier which serves to link datasets prior to deidentification. Members of the Armed Forces and the Royal Canadian Mounted Police, federal penitentiary inmates and Albertans who have opted out of the AHCIP are excluded [22]. Physician Claims captures outpatient feefor-service billing data for publicly funded physician services. ...
... Data from April 1994 through March 2013 were used to identify individuals with OA using the most current and validated case definition for administrative data: at least one OA hospitalization, or at least two OA physician visits or OA-related ambulatory care visits within 2 years, and none of the physicians or ambulatory care visits being on the same day [22,23]. The OA-related records were identified as those with the first 3 digits 715 or M15 to M19 based on the ninth and tenth revisions of the International Classification of Diseases (ICD) codes, respectively [22]. ...
Background
Knowledge of geospatial pattern in comorbidities prevalence is critical to an understanding of the local health needs among people with osteoarthritis (OA). It provides valuable information for targeting optimal OA treatment and management at the local level. However, there is, at present, limited evidence about the geospatial pattern of comorbidity prevalence in Alberta, Canada.
Methods
Five administrative health datasets were linked to identify OA cases and comorbidities using validated case definitions. We explored the geospatial pattern in comorbidity prevalence at two standard geographic areas levels defined by the Alberta Health Services: descriptive analysis at rural-urban continuum level; spatial analysis (global Moran’s I, hot spot analysis, cluster and outlier analysis) at the local geographic area (LGA) level. We compared area-level indicators in comorbidities hotspots to those in the rest of Alberta (non-hotspots).
Results
Among 359,638 OA cases in 2013, approximately 60% of people resided in Metro and Urban areas, compared to 2% in Rural Remote areas. All comorbidity groups exhibited statistically significant spatial autocorrelation (hypertension: Moran’s I index 0.24, z score 4.61). Comorbidity hotspots, except depression, were located primarily in Rural and Rural Remote areas. Depression was more prevalent in Metro (Edmonton-Abbottsfield: 194 cases per 1000 population, 95%CI 192–195) and Urban LGAs (Lethbridge-North: 169, 95%CI 168–171) compared to Rural areas (Fox Creek: 65, 95%CI 63–68). Comorbidities hotspots included a higher percentage of First Nations or Inuit people. People with OA living in hotspots had lower socioeconomic status and less access to care compared to non-hotspots.
Conclusions
The findings highlight notable rural-urban disparities in comorbidities prevalence among people with OA in Alberta, Canada. Our study provides valuable evidence for policy and decision makers to design programs that ensure patients with OA receive optimal health management tailored to their local needs and a reduction in current OA health disparities.
... Incidence estimates are sensitive to the length of run-in period [20,30] and so we repeated the analyses using a 10 year run-in period [20]. General practice membership of CPRD is dynamic (i.e. ...
... Age-standardized incidence rates for physician-diagnosed OA reported in previous studies of health administrative and primary care electronic health record data in Canada [11,12,19,20,30], the Netherlands [2123] and the UK [13] range between 5 and 17 cases per 1000 person-years. It is well-recognized that such rates are sensitive to the specific case definition adopted, the length of run-in period used to exclude prevalent cases, the capture and linkage of hospital data and other databases, population structure and the particular characteristics and incentives for coding behavior within different healthcare systems and databases. ...
... We used a stand-alone primary care database and in other health conditions the importance of linked secondary care records for complete capture of cases has been demonstrated [49]. The proportion of cases of OA diagnosed in secondary care and not recorded in the CPRD primary care database is not known but in the Canadian studies, physician claims accounted for 8090% of cases [30] and the general practitioner for 84% of all cases identified from visits to health professionals [11]. A similar contribution from secondary care diagnoses to OA prevalence estimates was seen in Swedish healthcare registry data [26]. ...
Objective:
To determine recent trends in the rate and management of new cases of OA presenting to primary healthcare using UK nationally representative data.
Methods:
Using the Clinical Practice Research Datalink we identified new cases of diagnosed OA and clinical OA (including OA-relevant peripheral joint pain in those aged over 45 years) using established code lists. For both definitions we estimated annual incidence density using exact person-time, and undertook descriptive analysis and age-period-cohort modelling. Demographic characteristics and management were described for incident cases in each calendar year. Sensitivity analyses explored the robustness of the findings to key assumptions.
Results:
Between 1992 and 2013 the annual age-sex standardized incidence rate for clinical OA increased from 29.2 to 40.5/1000 person-years. After controlling for period effects, the consultation incidence of clinical OA was higher for successive cohorts born after the mid-1950s, particularly women. In contrast, with the exception of hand OA, we observed no increase in the incidence of diagnosed OA: 8.6/1000 person-years in 2004 down to 6.3 in 2013. In 2013, 16.4% of clinical OA cases had an X-ray referral. While NSAID prescriptions fell from 2004, the proportion prescribed opioid analgesia rose markedly (0.1% of diagnosed OA in 1992 to 1.9% in 2013).
Conclusion:
Rising rates of clinical OA, continued use of plain radiography and a shift towards opioid analgesic prescription are concerning. Our findings support the search for policies to tackle this common problem that promote joint pain prevention while avoiding excessive and inappropriate health care.
... We used five linked Alberta, Canada provincial administrative databases between 1 April 1994 and 31 March 2013 to identify individuals with OA who accessed healthcare services paid for by the provincial healthcare insurance plan, previously described elsewhere in detail. 6 These databases included the Alberta Health Care Insurance Plan (AHCIP) population registry, the Discharge Abstract Database (DAD), the Physician Claims Database (claims), the Ambulatory Care Classification System (ACCS) and the National Ambulatory Care Reporting System (NACRS). AHCIP population registry captures individual level demographic data on all insured persons as of the last day of each fiscal year (31 March). ...
... 11 In our study, we also included ACCS/NACRS to mitigate the issue of underestimations. 6 Nonetheless, the estimated number of OA cases using this approach is almost certainly an underestimate. Similarly, the algorithms for comorbidities may underestimate the prevalence of these comorbidities; the sensitivity for identifying depression is from 36% to 51%, 19 for PVD is 39% 18 and for COPD is 53% 21 in administrative data (online supplementary appendix 2). ...
Objectives
The purpose of this study is to estimate the prevalence of comorbidities among people with osteoarthritis (OA) using administrative health data.
Design
Retrospective cohort analysis.
Setting
All residents in the province of Alberta, Canada registered with the Alberta Health Care Insurance Plan population registry.
Participants
497 362 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 measures
We 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 χ ² tests of independence with a Bonferroni correction to compare the percentage of comorbid conditions in each age group.
Results
54.6% (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.
Conclusions
Our 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.
... Osteoarthritis is a frequent age-related degenerative joint disease that causes loss in quality of life and functional decline [20,21,27]. It is a progressive, degenerative joint disease with a multi-factorial aetiology and could be considered the result of the interaction between both local and systemic factors [28]. ...
Background:
The identification of synovial fluid (SF) biomarkers that could anticipate the diagnosis of osteoarthritis (OA) is gaining increasing importance in orthopaedic clinical practice. This controlled trial aims to assess the differences between the SF proteome of patients affected by severe OA undergoing Total Knee Replacement (TKR) compared to control subjects (i.e., subjects younger than 35, undergoing knee arthroscopy for acute meniscus injury).
Methods:
The synovial samples were collected from patients with Kellgren Lawrence grade 3 and 4 knee osteoarthritis undergoing THR (study group) and young patients with meniscal tears and no OA signs undergoing arthroscopic surgery (control group). The samples were processed and analyzed following the protocol defined in our previous study. All of the patients underwent clinical evaluation using the International Knee Documentation Committee (IKDC) subjective knee evaluation (main outcome), Knee Society Clinical Rating System (KSS), Knee injury and Osteoarthritis Outcome Score (KOOS), and Visual Analogue Scale (VAS) for pain. The drugs' assumptions and comorbidities were recorded. All patients underwent preoperative serial blood tests, including complete blood count and C-Reactive Protein (CRP).
Results:
The synovial samples' analysis showed a significantly different fibrinogen beta chain (FBG) and alpha-enolase 1 (ENO1) concentration in OA compared to the control samples. A significant correlation between clinical scores, FBG, and ENO1 concentration was observed in osteoarthritic patients.
Conclusions:
Synovial fluid FBG and ENO1 concentrations are significantly different in patients affected by knee OA compared with non-OA subjects.
... The use of two or more codes for OA has a positive predictive value of 0.85, sensitivity of 0.25, and specificity of 0.91 for the presence of knee, hand or hip OA, 21 22 using the American College of Rheumatology classification criteria for OA as the standard, 23 and these criteria have been used in previous OA studies. [24][25][26] As a secondary outcome, we also analysed OA subtypes, including OA of the knee, hip and hands. Patients were followed up until the eligibility end date of the last insurance plan (ie, if there were gaps in coverage, their follow-up time included only the time they were actually in the dataset, and follow-up time ended when the last period of observation in the dataset ended). ...
Objectives
To determine the incidence of osteoarthrits (OA) in patients with atopic disease compared with matched non-exposed patients.
Methods
We conducted a retrospective cohort study with propensity score matching using claims data from Optum’s de-identified Clinformatics Data Mart (CDM) (January 2003 to June 2019) and electronic health record data from the Stanford Research Repository (STARR) (January 2010 to December 2020). We included adult patients without pre-existing OA or inflammatory arthritis who were exposed to atopic disease or who were non-exposed. The primary outcome was the development of incident OA.
Results
In Optum CDM, we identified 117 346 exposed patients with asthma or atopic dermatitis (mean age 52 years; 60% female) and 1 247 196 non-exposed patients (mean age 50 years; 48% female). After propensity score matching (n=1 09 899 per group), OA incidence was higher in patients with asthma or atopic dermatitis (26.9 per 1000 person-years) compared with non-exposed patients (19.1 per 1000 person-years), with an adjusted odds ratio (aOR) of 1.58 (95% CI 1.55 to 1.62) for developing OA. This effect was even more pronounced in patients with both asthma and atopic dermatitis compared with non-exposed patients (aOR=2.15; 95% CI 1.93 to 2.39) and in patients with asthma compared with patients with chronic obstructive pulmonary disease (aOR=1.83; 95% CI 1.73 to 1.95). We replicated our results in an independent dataset (STARR), which provided the added richness of body mass index data. The aOR of developing OA in patients with asthma or atopic dermatitis versus non-exposed patients in STARR was 1.42 (95% CI 1.36 to 1.48).
Conclusions
This study demonstrates an increased incidence of OA in patients with atopic disease. Future interventional studies may consider targeting allergic pathways for the prevention or treatment of OA.
... With regard to (i), it may lead to misdiagnosis, including a variability of diagnoses in the same patient, and unnecessary examinations, with radiation exposure and psychological stress for patients [22]. With regard to (ii), the results of trials are less comparable, with varying rates of incidences, decreased power to detect clinically relevant differences and other issues [23]. ...
Background:
Radiographic knee osteoarthritis (OA) severity and clinical severity are often dissociated. Artificial intelligence (AI) aid was shown to increase inter-rater reliability in radiographic OA diagnosis. Thus, AI-aided radiographic diagnoses were compared against AI-unaided diagnoses with regard to their correlations with clinical severity.
Methods:
Seventy-one DICOMs (m/f = 27:42, mean age: 27.86 ± 6.5) (X-ray format) were used for AI analysis (KOALA software, IB Lab GmbH). Subjects were recruited from a physiotherapy trial (MLKOA). At baseline, each subject received (i) a knee X-ray and (ii) an assessment of five main scores (Tegner Scale (TAS); Knee Injury and Osteoarthritis Outcome Score (KOOS); International Physical Activity Questionnaire; Star Excursion Balance Test; Six-Minute Walk Test). Clinical assessments were repeated three times (weeks 6, 12 and 24). Three physicians analyzed the presented X-rays both with and without AI via KL grading. Analyses of the (i) inter-rater reliability (IRR) and (ii) Spearman's Correlation Test for the overall KL score for each individual rater with clinical score were performed.
Results:
We found that AI-aided diagnostic ratings had a higher association with the overall KL score and the KOOS. The amount of improvement due to AI depended on the individual rater.
Conclusion:
AI-guided systems can improve the ratings of knee radiographs and show a stronger association with clinical severity. These results were shown to be influenced by individual readers. Thus, AI training amongst physicians might need to be increased. KL might be insufficient as a single tool for knee OA diagnosis.
... Due to the high prevalence of osteoarthritis, diagnosis, treatment, and consequences, such as disability, are associated with a heavy financial burden on patients, families, and society. 6 The TKA is one of the most complex and essential procedures in orthopedics that can pose severe risks to patients' health and life. It is necessary to perform it only when the pain and deformity caused by osteoarthritis of the knee cause severe disorders in lifestyle and quality of life. ...
Lifestyle affects health and life expectations and care training programs are attempts to change patients' lifestyles. The study aims to evaluate the effects of educational intervention on the lifestyle of patients with knee osteoarthritis. In this clinical trial, 60 patients with knee osteoarthritis were studied before and after total knee arthroplasty. Before surgery, health-promoting lifestyle profile II (HPLP II) was completed for all patients. Then the patients attended educational programs about aspects of lifestyle before undergoing total knee arthroplasty (TKA). Three months after the surgery, the questionnaire was again completed for all patients. Finally, the obtained data were analyzed statistically. The mean score of the components of health responsibility (vs.), physical activity (vs.), nutrition (vs.), self-actualization (vs.), interpersonal support (vs.), and total mean of HPLP II questionnaires (vs.) significantly increased after the training (p<0.05). However, the education program did not improve the mental stress management component (vs. p=0.479). Educational intervention can improve the lifestyle of patients with knee osteoarthritis after total knee arthroplasty. These training programs are ineffective in improving stress management components and should be further investigated by future studies. The present study provided significant findings on education and improving lifestyle. The findings of this study provide a new vision for policymakers to reduce health problems by refining lifestyles.
... Administrative health data are healthcare information systematically collected by the publicly funded healthcare systems in each province and territory in Canada, often including data on health services, diagnosis, medications and costs. Many studies have shown that administrative health data, with diagnostic information coded by International Classification of Diseases (ICD) codes, is a promising and reliable tool to identify patients with chronic conditions [2][3][4][5][6][7][8]. Quan et al. (2005Quan et al. ( , 2008 and 2009) have shown that using ICD codes in Alberta Health (AH) administrative data has acceptable (56.2-86.5%) ...
Introduction
Alberta's Tomorrow Project (ATP) is the largest population-based prospective cohort study of cancer and chronic diseases in Alberta, Canada. The ATP cohort data were primarily self-reported by participants on lifestyle behaviors and disease risk factors at the enrollment, which lacks sufficient and accurate data on chronic disease diagnosis for longer-term follow-up.
Objectives
To characterize the occurrence rate and trend of chronic diseases in the ATP cohort by linking with administrative healthcare data.
Methods
A set of validated algorithms using ICD codes were applied to Alberta Health (AH) administrative data (October 2000-March 2018) linked to the ATP cohort to determine the prevalence and incidence of common chronic diseases.
Results
There were 52,770 ATP participants (51.2± 9.4 years old at enrollment and 63.7% females) linked to the AH data with average follow-up of 10.1± 4.4 years. In the ATP cohort, hypertension (18.5%), depression (18.1%), chronic pain (12.8%), osteoarthritis (10.1%) and cardiovascular diseases (8.7%) were the most prevalent chronic conditions. The incidence rates varied across diseases, with the highest rates for hypertension (22.1 per 1000 person-year), osteoarthritis (16.2 per 1000 person-year) and ischemic heart diseases (13.0 per 1000 person-year). All chronic conditions had increased prevalence over time (p
... At the macro level, PROMs data can be used to evaluate the performance of the healthcare system to compare outcomes across different jurisdictions or over time and support health policy decision making. Combined with administrative databases as a key source for estimating the burden and epidemiologic trends of chronic diseases such as osteoarthritis [26], and simulation models that reflect how patients transition through the continuum of care from disease onset through end-stage care [27], PROMs data can provide insight into the magnitude of the patient population and burden of disease, healthcare resource requirements and associated healthcare costs. Such tools can be used for estimating how many patients will need care, the nature of that care, and when the care will be needed. ...
PROMs are part of routine measurement for hip and knee replacement in Alberta, Canada. We provide an overview of how PROMs are implemented in routine care, and how we use PROMs data for decision-making at different levels within the health system. The Alberta Bone and Joint Health Institute (ABJHI) ran a randomized controlled trial to determine the effectiveness and cost-effectiveness of an evidence-based care pathway for hip and knee arthroplasty in 2004. The study included several PROMs questionnaires: Western Ontario and McMaster Universities Osteoarthritis Index, Health Utility Index, Short Form 36 and the EQ-5D-3L. Subsequently, the focus shifted to spread and scale of the care pathway provincially. WOMAC and EQ-5D-3L and a patient experience survey were selected for provincial adoption - captured before surgery, three-months post-surgery, and 12-months post-surgery. These PROMs data were integrated into research and routine clinical practice at the micro, meso and macro levels. At the micro level, PROMs data are used at the individual patient and provider level for patients to provide input on their care and as a tool to communicate with their healthcare providers. We examined the relationship of appropriateness and patient reported outcomes in a prospective cohort study. We evaluated whether routinely collected PROMs could be integrated into a patient decision aid to better inform shared decision making. At the meso level, continuous quality improvement reports are provided routinely to individual health care providers, hospitals and clinics on their performance against the measurement framework and standard key performance indicators. At the macro level, PROMs data are used to evaluate system performance by comparing outcomes across different jurisdictions or over time and support health policy decision making. Combined with administrative databases, we have used simulation models to reflect transition through the continuum of care from disease onset through end-stage care regarding the burden of disease, healthcare resource requirements and associated healthcare costs. The addition of PROMs data in clinical repositories and analyses enables the system to identify and address issues of continuous quality improvement against a measurement framework of performance indicators and to explicitly recognize the trade-offs that are inherent in any resource-constrained system.
... Various case definitions of OA (symptomatic, radiographic, self-reported, or doctordiagnosed) [2][3][4][5][6] have been used across different clinical studies. Similarly, epidemiological studies using health administrative and electronic medical record (EMR) data have used various OA algorithms [7][8][9][10][11][12][13][14][15], which may contribute to varying disease estimates across studies. ...
Objective
To estimate the 1) accuracy of algorithms for identifying osteoarthritis (OA) using health administrative data; and 2) population-level OA prevalence and incidence over time in Ontario, Canada.
Method
We performed a retrospective chart abstraction study to identify OA patients in a random sample of 7500 primary care patients from electronic medical records. The validation sample was linked with several administrative data sources. Accuracy of administrative data algorithms for identifying OA was tested against two reference standard definitions by estimating the sensitivity, specificity and predictive values. The validated algorithms were then applied to the Ontario population to estimate and compare population-level prevalence and incidence from 2000 to 2017.
Results
OA prevalence within the validation sample ranged from 10% to 23% across the two reference standards. Algorithms varied in accuracy depending on the reference standard, with the sensitivity highest (77%) for patients with OA documented in medical problem lists. Using the top performing administrative data algorithms, the crude population-level OA prevalence ranged from 11% to 25% and standardized prevalence ranged from 9 to 22% in 2017. Over time, prevalence increased whereas incidence remained stable (~1% annually).
Conclusion
Health administrative data have limited sensitivity in adequately identifying all OA patients and appear to be more sensitive at detecting OA patients for whom their physician formally documented their diagnosis in medical problem lists than individuals who have their diagnosis documented outside of problem lists. Irrespective of the algorithm used, OA prevalence has increased over the past decade while annual incidence has been stable.
... Osteoarthritis (OA) is a progressive joint disease due to bone and cartilage degeneration, with a significant personal and societal impact. Costs associated with OA management involve not only direct treatment strategies (clinic assessments, medications, orthotics, surgery), but also significant indirect costs (loss of productivity of patient and caregivers through both physical and mental burden) [1][2][3][4][5][6]. Approximately one in four Canadians suffer from osteoarthritis, with a growing economic burden estimated, through direct and indirect costs associated with this disease, in 2010 at $27.5 Billion and increasing by 2040 to almost $1.5 trillion [1]. ...
Objective
To evaluate the management and costs of osteoarthritis of the knee (OAK), a progressive joint disease due to bone and cartilage degeneration, with significant personal and societal impact.
Methods
We prospectively analyzed the clinical outcomes and quantifiable cumulative direct costs of patients with OAK referred to our multidisciplinary OA program over a two year time period. One hundred thirty-one subjects were assessed. All demonstrated radiographic criteria for moderate to severe OAK. Western Ontario McMaster Osteoarthritis Index (WOMAC), Minimal Clinically Important Improvement (MCII), and change in BMI were recorded and analyzed. Total medical and surgical direct costs for all subjects during the two year time period were determined.
Results
Five patients underwent total joint replacement during the two years of study. Among the group as a whole, a significant overall improvement in WOMAC scores was noted at the two year time point follow-up. After dividing the group into tertiles by baseline WOMAC scores, 46% achieved MCII. Significant weight loss was noted for individuals with baseline BMI of > 30. As all patients were considered “de facto” surgical candidates at referral, an average net savings of $9551.10 of direct costs per patient, or a potential total of $1,203,438.60 for the entire group, could be inferred as a result of medical as opposed to surgical management.
Conclusion
These findings support the benefits of multidisciplinary medical management for patients with significant OAK. This approach is clinically beneficial and may provide significant cost savings. Such models of care can substantially improve the long-term outcome of this highly prevalent condition and reduce societal and financial burdens.
... According to the World Health Organisation, the prevalence of OA is 18% in elderly women, whereas this is 9.6 % in elderly men [3]. Following the current rise in obesity and concomitant increase in life expectancy, prevalence of OA is expected to increase [4]. This poses OA as an increasing future health problem. ...
Osteoarthritis is one of the major causes of immobility and its current prevalence in elderly (>60 years) is 18% in women and 9.6% in men. Patients with osteoarthritis display altered movement patterns to avoid pain and overcome movement limitations in activities of daily life, such as sit-to-stand transfers. Currently, there is a lack of evidence that distinguishes effects of knee osteoarthritis on sit-to-stand performance in patients with and without obesity. The purpose of this study was therefore to investigate differences in knee and hip kinetics during sit-to-stand movement between healthy controls and lean and obese knee osteoarthritis patients. Fifty-five subjects were included in this study, distributed over three groups: healthy controls (n=22), lean knee osteoarthritis (n=14), and obese knee OA patients (n=19). All subjects were instructed to perform sit-to-stand transfers at self-selected, comfortable speed. A three-dimensional movement analysis was performed to investigate compensatory mechanisms and knee and hip kinetics during sit-to-stand movement. No difference in sit-to-stand speed was found between lean knee OA patients and healthy controls. Obese knee osteoarthritis patients, however, have reduced hip and knee range of motion, which is associated with reduced peak hip and knee moments. Reduced vertical ground reaction force in terms of body weight and increased medial ground reaction forces indicates use of compensatory mechanisms to unload the affected knee in the obese knee osteoarthritis patients. We believe that an interplay between obesity and knee osteoarthritis leads to altered biomechanics during sit-to-stand movement, rather than knee osteoarthritis alone. From this perspective, obesity might be an important target to restore healthy sit-to-stand biomechanics in obese knee OA patients.
... We present the findings for 3-and 10-year look-back periods in the main results, as we have shown previously that the 3-year is the minimum period needed to pick up recorded OA in CPRD 15 and 10-year is the reasonable maximum period to capture existing diagnosis of OA as shown in previous studies. 2,15,16 The full set of findings is provided in the Supplementary materials. ...
Purpose: Primary care electronic health records are increasingly used to estimate the occurrence of osteoarthritis (OA). We aimed to estimate the extent and trend over time of underrecording of severe OA patients in UK primary care electronic health records using first primary total hip and knee replacements (THR/TKR) – >90% of which are performed for OA – as the reference population.
Patients and methods: We identified patients with a first primary THR or TKR recorded in the UK Clinical Practice Research Datalink between 2000 and 2015. We then searched for a diagnostic/problem code for OA up to 10 years prior to THR/TKR using 3 definitions: “diagnosed OA (joint-specific),” “diagnosed OA (any joint),” “clinical OA” (diagnosed OA or relevant peripheral joint pain symptom code).
Results: Among 34,299 THR patients identified, 28.1%, 53.4%, and 74.4% had a prior record
of diagnosed OA (hip), diagnosed OA (any), and clinical OA, respectively. Among 47,588 TKR
patients, the corresponding figures were, 25.5% (diagnosed OA [knee]), 43.7%, and 74.8%. In
the UK Clinical Practice Research Datalink, the proportion of patients with prior recorded OA
decreased between 2000 and 2015.
Conclusion: An increasing trend of underrecording of OA or joint pain among patients with
THR or TKR (severe OA patients) between 2000 and 2015 was identified. An underestimate
health care demand could be derived based on consultation incidence and prevalence of OA
from electronic health record data that relies on osteoarthritis diagnostic codes. Further studies are warranted to investigate the validity of OA or joint pain recorded in primary care settings, which might be used to correct the consultation incidence and prevalence of OA.
... Despite these limitations, these data provide valuable information for estimating disease burden and planning health services, and are being increasingly used for epidemiologic and outcomes research, health care quality measurement and management, and health services' population-based research. [25] Widdifield et al. demonstrated in their study that administrative data can be used to identify RA patients with a high degree of accuracy. [26] RA diagnosis date and disease duration are fairly well estimated from administrative data in jurisdictions of universal health-care insurance. ...
Introduction: Arthritis is a leading cause of functional impairment and health care utilization in Canada and in the Western world. The aim of this investigation is to quantify the frequency, severity, and magnitude of arthritis in Ontario, Canada, using recognized databases supplemented with comprehensive, population-based survey data to facilitate informed, evidence-based planning. Materials and Methods: Data from Vital Statistics (2011, mortality), Canadian Institute for Health Information (2013, Discharge Abstract Database), Census (2011, demographic information), National Ambulatory Care Reporting System (2013, emergency department visits), and the Canadian Community Health Survey (2011/12) were used to construct an arthritis pyramid for residents of Ontario aged 15 years and older. Results and Discussion: Although arthritis is not a common cause of death, it is an important reason for hospitalizations and emergency room visits. Its greatest impact lies in the prevalence of individuals who are affected; approximately 1.8 million individuals in Ontario, and the resulting negative impact on functional ability, health care utilization, and health-care costs. The impact on society is immense and is expected to worsen as the population ages. Conclusion: A nationwide health care strategy to prevent and manage all forms of arthritis is crucial. In order to do this, we must first understand its prevalence and impact on society. This study provides a detailed information on the iceberg effect for arthritis and offers valid information for regional planning, provincial comparisons and an illustration for similar analyses nationally and internationally.
... Osteoarthritis (OA) is a chronic inflammatory disease that affects middle aged and older people worldwide [1]. This disease also affects horses and other animal species, which causes economic losses by diminishing the athletic potential of the affected animals and through the chronic use of anti-inflammatory drugs and nutraceuticals [2][3][4]. ...
Background:
Platelet-rich plasma (PRP) preparations are a common treatment in equine osteoarthritis (OA). However, there are controversies regarding the ideal concentration of platelets and leukocytes in these biological substances necessary to induce an adequate anti-inflammatory and anabolic response in articular cartilage. The aims were to study the influence of leukocyte- and platelet-rich gel (L-PRG) and pure platelet-rich gel (P-PRG) supernatants on the histological changes of cartilage, the degree of chondrocyte apoptosis, the production of hyaluronan (HA) and the gene expression of nuclear factor kappa beta (NFkβ), matrix metalloproteinase 13 (MMP-13), a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), collagen type I alpha 1 (COL1A1), collagen type II alpha 1 (COL2A1) and cartilage oligomeric matrix protein (COMP) in normal cartilage explants (CEs) challenged with lipopolysaccharide (LPS).
Results:
Overall, 25 % L-PRG supernatant (followed in order of importance by, 50 % P-PRG, 25 % P-PRG and 50 % L-PRG) represented the substance with the most important anti-inflammatory and anabolic effect. 25 % P-PRG supernatant presented important anabolic effects, but it induced a more severe chondrocyte apoptosis than the other evaluated substances.
Conclusions:
25 % L-PRG supernatant presented the best therapeutic profile. Our results demonstrate that the biological variability of PRP preparations makes their application rather challenging. Additional in vivo research is necessary to know the effect of PRP preparations at different concentrations.
... Estudos retrospectivos revelaram que os sujeitos acometidos tendem a procurar os serviços de saúde quando a dor limita suas atividades diárias. (21) Quando a dor se cronifica ocorre o envolvimento central na AO denominado de sensibilização central. (22) Neste caso ocorre uma desregulação da percepção álgica que interfere no funcionamento das vias corticoespinais e intracorticais. ...
Objetivo: Esta revisão fornece evidências sobre exercício e exercício combinado com a estimulação elétrica em indivíduos com OA do joelho. Método: Uma revisão narrativa foi realizada com termos de estratégias não-farmacológicas, particularmente exercício, estimulação transcraniana por corrente contínua (ETCC) e estimulação elétrica neuromuscular (EEN). As variáveis analisadas foram dor, função, qualidade de vida e excitabilidade cortical. Resultados: Os resultados mostraram que o exercício foi benéfico para melhorar a dor e função em pessoas com OA do joelho. Exercício associados os ETCC pode melhorar os benefícios terapêuticos. As evidências na OA são raras, porém promissoras. Achados semelhantes foram encontrados com o EEN. Estudos sugerem que a combinação é melhor do que isolado exercício. Conclusões: Ambos os estímulos eléctricos pode ser envolvido no exercício com aumento do tamanho do efeito. Isto é devido à melhoria da plasticidade cerebral que ocorre de forma diferente nas duas técnicas. Os efeitos da interação entre os estímulos voluntários (exercício) e exógenos (elétrica) na plasticidade cerebral nos pacientes com OA do joelho requerem maior detalhamento. Informações sobre a intensidade, frequência e duração dos programas de intervenção são divergentes. Revisões sistemáticas com meta-análises podem ser desenvolvidas para identificar a combinação mais efetiva na dor, função e qualidade de vida desses indivíduos.
The objective of this review is to provide an overview of the current status of osteoarthritis (OA) as one of the most common joint disorders worldwide. Despite being the 11th cause of disability globally, there has been an increase in the prevalence, annual incidence, and years lived with disability of OA, particularly in developed and developing countries. Erosive hand OA, which affects approximately 10% of the general population, has been associated with a higher clinical burden compared to non-erosive hand OA. Patients with knee and hip OA, but not hand OA, are also at an increased risk of cardiovascular disease and all-cause mortality. Furthermore, OA has a significant contribution to healthcare costs in most countries. The recent COVID-19 pandemic has further exacerbated the disease burden of OA patients due to limited access to medical and surgical treatment. With increasing life expectancy and the aging of the global population, the burden of OA is expected to worsen. Therefore, this review highlights the importance of improving population and policymaker awareness of risk factors, such as obesity and injury, as well as early intervention and management of OA to control the future burden of the disease.
Introduction
The wait times crisis for hip and knee arthroplasty has been a significant health care issue in Alberta and across Canada. Significant resource and financial efforts have been put forward to reduce wait times for surgical consults and surgeries as a means of treating patients with osteoarthritis, but after an initial shortening of wait times, they were not sustained and have expanded.
Objective
To effectively address wait times issues, an alternative perspective on this problem is presented – that the wait times are not the central problem, but rather wait times are a symptom of the much bigger issue of an inability of health care systems to accommodate the large number of patients with recently diagnosed OA or moderate OA who are not being effectively managed conservatively.
Discussion
In considering this alternative perspective, encapsulated by the concept of an “osteoarthritis funnel”, being continually filled with new patients and arthroplasty capacity being a bottleneck, we outline potential approaches for a solution on a systemic level that integrates services delivery, health care resource allocation and conceptualization of OA in on-going scientific activities. It also emphasizes the need for a more effective and relevant program of research to address this complex problem with its attendant potential for multiple etiologies for OA that may require unique solutions.
Conclusions
New approaches and understanding are needed to address development of effective conservative treatment of newly diagnosed osteoarthritis to prevent the constant and expanding demand for arthroplasty.
Introduction: Since its introduction by the World Health Organization (WHO), the concept of burden of disease has been evolving. The current method uses life expectancy projected to 2050 and does not consider age-weighting and time-discounting. Our aim is to estimate the burden of disease due to hip, knee, and unspecified osteoarthritis using this new method in the Peruvian Social Health Insurance System (EsSalud) during 2016.
Methods: We followed the original 1994 WHO study and the current 2015 Global Burden of Disease (GBD) methods to estimate disability adjusted life years (DALY) due to osteoarthritis, categorized by sex, age, osteoarthritis type, and geographical area. We used disability weights employed by the Peruvian Ministry of Health, and the last update issued by WHO.
Results : Overall, EsSalud reported 17.9 new cases of osteoarthritis per 1000 patients per year. Annual incidence was 23.7/1000 among women, and 72.6/1000 in people above 60 years old. Incidence was 5.6/1000 for knee osteoarthritis and 1.1/1000 for hip. According to the 1994 WHO method, there were 399,884 DALYs or 36.6 DALYs/1000 patients per year due to osteoarthritis. 12.4 and 2.2 DALYs/1000 patients per-year were estimated for knee and hip osteoarthritis, respectively. Using the 2015 GBD method, there were 1,037,865 DALYs or 94.9 DALYs/1000 patients per year. 31.4 and 5.3 DALYs/1000 patients per year were calculated for knee and hip osteoarthritis, respectively.
Conclusions: In the Peruvian social health insurance subsystem, hip, knee, and unspecified osteoarthritis produced a high burden of disease, especially among women and patients over 60. The 2015 GBD methodology yields values almost three times higher than the original recommendations.
Introduction: Since its introduction by the World Health Organization (WHO), the concept of burden of disease has been evolving. The current method uses life expectancy projected to 2050 and does not consider age-weighting and time-discounting. Our aim is to estimate the burden of disease due to hip, knee, and unspecified osteoarthritis using this new method in the Peruvian Social Health Insurance System (EsSalud) during 2016.
Methods: We followed the original 1994 WHO study and the current 2015 Global Burden of Disease (GBD) methods to estimate disability adjusted life years (DALY) due to osteoarthritis, categorized by sex, age, osteoarthritis type, and geographical area. We used disability weights employed by the Peruvian Ministry of Health, and the last update issued by WHO.
Results : Overall, EsSalud reported 17.9 new cases of osteoarthritis per 1000 patients per year. Annual incidence was 23.7/1000 among women, and 72.6/1000 in people above 60 years old. Incidence was 5.6/1000 for knee osteoarthritis and 1.1/1000 for hip. According to the 1994 WHO method, there were 399,884 DALYs or 36.6 DALYs/1000 patients per year due to osteoarthritis. 12.4 and 2.2 DALYs/1000 patients per-year were estimated for knee and hip osteoarthritis, respectively. Using the 2015 GBD method, there were 1,037,865 DALYs or 94.9 DALYs/1000 patients per year. 31.4 and 5.3 DALYs/1000 patients per year were calculated for knee and hip osteoarthritis, respectively.
Conclusions: In the Peruvian social health insurance subsystem, hip, knee, and unspecified osteoarthritis produced a high burden of disease, especially among women and patients over 60. The 2015 GBD methodology yields values almost three times higher than the original recommendations.
Objective. To assess the impact of a computerized system on physicians’ accuracy and agreement rate, as compared with unaided diagnosis. Methods. A set of 124 unilateral knee radiographs from the Osteoarthritis Initiative (OAI) study were analyzed by a computerized method with regard to Kellgren-Lawrence (KL) grade, as well as joint space narrowing, osteophytes, and sclerosis Osteoarthritis Research Society International (OARSI) grades. Physicians scored all images, with regard to osteophytes, sclerosis, joint space narrowing OARSI grades and KL grade, in 2 modalities: through a plain radiograph ( unaided) and a radiograph presented together with the report from the computer assisted detection system ( aided). Intraclass correlation between the physicians was calculated for both modalities. Furthermore, physicians’ performance was compared with the grading of the OAI study, and accuracy, sensitivity, and specificity were calculated in both modalities for each of the scored features. Results. Agreement rates for KL grade, sclerosis, and osteophyte OARSI grades, were statistically increased in the aided versus the unaided modality. Readings for joint space narrowing OARSI grade did not show a statistically difference between the 2 modalities. Readers’ accuracy and specificity for KL grade >0, KL >1, sclerosis OARSI grade >0, and osteophyte OARSI grade >0 was significantly increased in the aided modality. Reader sensitivity was high in both modalities. Conclusions. These results show that the use of an automated knee OA software increases consistency between physicians when grading radiographic features of OA. The use of the software also increased accuracy measures as compared with the OAI study, mostly through increases in specificity.
There is limited evidence on the geographical variation in the prevalence of comorbidities in people with osteoarthritis in Alberta. Our study explores the spatial pattern of osteoarthritis comorbidities along the rural-urban continuum. The results showed a pattern of higher age-sex standardized prevalence rate of osteoarthritis comorbidities in the north and rural areas compared to the south and urban areas, respectively. Hot spots were identified in the north remote area for osteoarthritis with two or more comorbidities, and osteoarthritis with chronic obstructive pulmonary disease. This study provides information for health care planning to support access to health care services.
Background
To identify knee osteoarthritis (OA) patients among OA patients in the claims database.
Methods
All patients with OA diagnostic codes for any sites (M15 to M19) in 2014 were recruited from a single academic referral hospital. After excluding patients who had inflammatory arthritis or were less than 50 years of age, we identified data for the overall OA population. Radiographic knee OA of Kellgren and Lawrence grades ≥2 is considered the gold standard for knee OA, and we evaluated the sensitivity, specificity, and positive predictive value (PPV) of three operational definitions using the diagnostic codes in the claims database. The operational definitions were: (1) gonarthrosis (M17); (2) any site of OA (M15 to M19) with knee X‐ray; and (3) (1) or (2).
Results
A total of 7959 OA patients were included in this study of whom 74.5% were women. The PPV of gonarthrosis (M17) was 0.67 (95% CI 0.65‐0.69), and sensitivity was 0.44 (95% CI 0.42‐0.46). The PPV and sensitivity of any OA site (M15 to M19) with knee X‐ray were 0.65 (95% CI 0.62‐0.67), and 0.37 (95% CI 0.35‐0.39), respectively. When knee OA was defined as satisfying either of the two above definitions, PPV was 0.63 (95% CI 0.62‐0.65) and sensitivity 0.55 (95% CI 0.53‐0.57).
Conclusions
Knee OA patients can be identified in a claims database using the algorithms of gonarthrosis (M17) or any site of OA (M15 to M19) with a performed knee X‐ray.
There is limited evidence on the geographic distribution of osteoarthritis (OA) in Alberta to inform planning of equitable access to health care services. This research aimed to explore the geographic variation in age-sex standardized OA prevalence rates by geographic areas across the rural-urban continuum, and by six-digit postal codes using global Moran's I and hot spot analysis. The results demonstrated a substantially higher OA prevalence rate in Rural Remote (134.7 cases per 1000 population) and Rural (128.5), compared to Metro (107.4) and Urban areas (107.3). Metro-Edmonton had a substantially higher OA prevalence rate (124.4) compared to Metro-Calgary (94.4). OA hot spots were identified in north rural communities and Metro-Edmonton. These variations should be considered when planning programs for health promotion and prevention of osteoarthritis and access to associated health care services. Further research is needed to identify the underlying factors contributing to this geographic variation.
Systematic reviews of self-management programs for osteoarthritis suggest minimal evidence of benefit and indicate substantial heterogeneity in interventions. The purpose of this scoping review was to describe the nature of self-management interventions provided to patients with osteoarthritis focusing on the inclusion and type of education and social support components. We searched PsycINFO, EMBASE, MEDLINE, and Cochrane Library databases from 1990 to 2016 to identify studies addressing community-based management strategies for osteoarthritis that included aspects of disease-specific education and ongoing social support. Results are presented as a narrative synthesis to facilitate integration of diverse evidence. Data were extracted from 23 studies that met our inclusion and exclusion criteria, describing complex, multicomponent interventions for osteoarthritis. All studies included education components, and 18 of these were osteoarthritis-specific. Social support was most often offered through peers and health care professionals, but also through exercise trainers/instructors and researchers, and lasted between 5 and 52 weeks. We charted positive social interaction offered by peers in group settings and emotional/informational support offered by health care professionals. Overall, descriptions of self-management provided limited documentation of the rationale or content of the programs. This suggests that more precise definitions of the theoretical underpinnings, components, and mechanisms would be useful for greater insight into best practices for osteoarthritis self-management programs.
Background/aims:
Osteoarthritis (OA), the commonest joint disorder, is a leading cause of disability. Symptomatic slow-acting drugs for OA (SYSADOA), particularly glucosamine plus chondroitin sulphate (GS/CS), are effective for symptom relief, protect joint cartilage and delay OA progression, with a good safety profile. D-002, a mixture of beeswax alcohols that inhibits both cyclooxygenase and 5-lipoxygenase activities, has been effective in experimental and clinical OA studies, showing also a chondroprotective effect.
Objectives:
To compare the effects of D-002 and GS/SC administered for 12 weeks on OA symptoms.
Methods:
Participants were randomized to GS/CS (375/300 mg) or 50 mg D-002 once daily for 12 weeks. Symptoms were assessed by the Western Ontario and McMaster Individual Osteoarthritis Index (WOMAC) and the Visual Analogy Scale (VAS) scores. The primary outcome was the reduction of the total WOMAC score. Secondary outcomes included WOMAC pain, stiffness and function scores, VAS score and rescue medication consumption.
Results:
Of 60 randomized patients, 59 completed the study. D-002 and GS/SC reduced significantly total WOMAC score (72.1% and 78.5%, respectively), and pain, joint stiffness and physical function scores versus baseline. VAS scores decreased significantly with D-002 (76.6%) and GS/SC (76.8%). The reductions, significant from the second week, were enhanced over the trial. Rescue medications were consumed by 3/30 D-002 and 4/30 GS/SC patients. No differences between groups were found. Treatments were well tolerated.
Conclusions:
D-002 (50 mg/day) administered for 12 weeks was safe and comparable to GS/SC for alleviating OA symptoms (pain, stiffness, and functional limitation) (RPCEC00000180).
Recently, there have been major changes in the understanding of the occurrence and pattern of adverse reactions in the gastrointestinal tract attributed to the antirheumatic drugs. Major changes among these include: (1) the increasing awareness of the multiorgan system toxicity of nonsteroidal antiinflammatory drugs (NSAIDs) and the disease-modifying antirheumatic drugs (DMARDs); (2) comorbidities from the occurrence of different rheumatic diseases especially cardiovascular disease; (3) the widespread use of aspirin and other antithrombotic drugs to control cardiovascular complications with consequent increase in the incidence of gastrointestinal (GI) complications; (4) the increasing use of antiacid secretory agents proton-pump inhibitors, H2-receptor antagonists alone or in fixed combinations with NSAIDs to reduce the occurrence of serious GI reactions (upper GI bleeding and ulceration), but with apparently profound consequences for the intestinal microbiome in the form of dysbiosis and intestinal inflammation; and (5) the changing pattern of use of NSAIDs and DMARDs especially in patients with rheumatoid arthritis (RA). The complications in the form of iatrogenic disease that occur in the GI tract from use of agents to protect the GI tract from NSAIDs are of particular concern.
Objective:
To estimate and project the productivity costs of work loss (PCWL) associated with osteoarthritis (OA) in Canada using a population-based health microsimulation model (POHEM).
Design:
We integrated an employment module based on 2006 Canadian Census into the previously developed microsimulation model of OA. The Canadian Community Health Survey (CCHS) Cycle 2.1 with an OA sample aged 25-64 (n=7,067) was used to calibrate the results of the employment module and to estimate the fraction of non-employment associated with OA. Probabilities of non-employment together with attributable fractions were then implemented in POHEM to estimate PCWL associated with OA from 2010 to 2031.
Results:
Among the OA population, 44.4% and 59.4% of non-employment due to illness was associated with OA for those not working full-year and part-year, respectively. According to POHEM projections, the size of the working age population with OA increased from 1.5 million in 2010 to 1.7 million in 2031. The PCWL associated with OA increased from $12 billion to $17.5 billion in constant 2008 Canadian dollars. Around 38% of this increase was due to the increase in OA prevalence and changes in demographics, while the rest was due to increase in real wage growth. Male and female OA patients between 55-64 years of age had the highest total projected PCWL, respectively.
Conclusions:
The total PCWL associated with OA in Canada is estimated to be substantial and increasing in future years. Results of this study could be used to inform policies aiming to increase employment sustainability among individuals with OA.
http://mchp-appserv.cpe.umanitoba.ca/deliverablesList.html
Estimating how many patients will require care, the nature of the care they require, and when and where they will require it, is critical when planning resources for a sustainable health-care system. Resource planning must consider how quickly patients move among stages of care, the various different pathways they may take and the resources required at each stage. This research presents a preliminary long-term, population-driven system dynamics simulation developed to support resource planning and policy development relating to osteoarthritis care. The simulation models osteoarthritis patients as they transition through the continuum of care from disease onset through end-stage care, and provides insight into the size and characteristics of the patient population, their resource requirements and associated health-care costs. Although the model presented is specific to the osteoarthritis care system in the Province of Alberta, Canada, similar methods could be applied to develop simulations relating to other chronic conditions.
Background:
The time between symptom onset and physician diagnosis is a period when people with osteoarthritis can make lifestyle changes to reduce pain, improve function and delay disability.
Data and methods:
This study analyses data for a nationally representative sample of 4,565 Canadians aged 20 or older who responded to the Arthritis component of the 2009 Survey on Living with Chronic Diseases in Canada. Descriptive statistics are used to report the prevalence of hip and knee osteoarthritis; the mean age of symptom onset and diagnosis; medication use; and contacts with health professionals during the previous year.
Results:
Among people with a physician diagnosis of arthritis, 37% reported osteoarthritis. Of these, 70% experienced pain in the hip(s), knee(s), or hip(s) and knee(s). Close to half (48%) of these people experienced symptoms the same year that they were diagnosed; 42% experienced symptoms at least a year before the diagnosis; and 10% experienced symptoms after the diagnosis. Among those who had symptoms before diagnosis, the average time between symptom onset and diagnosis was 7.7 years.
Interpretation:
Individuals with osteoarthritis may experience symptoms for several years before they obtain a physician diagnosis.
To estimate the global burden of hip and knee osteoarthritis (OA) as part of the Global Burden of Disease 2010 study and to explore how the burden of hip and knee OA compares with other conditions.
Systematic reviews were conducted to source age-specific and sex-specific epidemiological data for hip and knee OA prevalence, incidence and mortality risk. The prevalence and incidence of symptomatic, radiographic and self-reported hip or knee OA were included. Three levels of severity were defined to derive disability weights (DWs) and severity distribution (proportion with mild, moderate and severe OA). The prevalence by country and region was multiplied by the severity distribution and the appropriate disability weight to calculate years of life lived with disability (YLDs). As there are no deaths directly attributed to OA, YLDs equate disability-adjusted life years (DALYs).
Globally, of the 291 conditions, hip and knee OA was ranked as the 11th highest contributor to global disability and 38th highest in DALYs. The global age-standardised prevalence of knee OA was 3.8% (95% uncertainty interval (UI) 3.6% to 4.1%) and hip OA was 0.85% (95% UI 0.74% to 1.02%), with no discernible change from 1990 to 2010. Prevalence was higher in females than males. YLDs for hip and knee OA increased from 10.5 million in 1990 (0.42% of total DALYs) to 17.1 million in 2010 (0.69% of total DALYs).
Hip and knee OA is one of the leading causes of global disability. Methodological issues within this study make it highly likely that the real burden of OA has been underestimated. With the aging and increasing obesity of the world's population, health professions need to prepare for a large increase in the demand for health services to treat hip and knee OA.
"Arthritis" describes more than 100 conditions that affect the joints, the tissues that surround joints and other connective tissue. These conditions range from relatively mild forms of tendonitis and bursitis to systemic illnesses, such as rheumatoid arthritis. Life with arthritis in Canada: a personal and public health challenge presents the latest knowledge about arthritis in the Canadian population and its wide-ranging impact. It provides an overview of the impact of arthritis, and is designed to increase public awareness of the importance of prevention and timely management. Although progress has been made on interventions, arthritis remains common, disabling and costly. Increasing participation in physical activity and maintaining a healthy body weight may help to mitigate the effects of arthritis.
Traditionally, the determination of the occurrence of hypertension in patients has relied on costly and time-consuming survey methods that do not allow patients to be followed over time.
To determine the accuracy of using administrative claims data to identify rates of hypertension in a large population living in a single-payer health care system.
Various definitions for hypertension using administrative claims databases were compared with 2 other reference standards: (1) data obtained from a random sample of primary care physician offices throughout the province, and (2) self-reported survey data from a national census.
A case-definition algorithm employing 2 outpatient physician billing claims for hypertension over a 3-year period had a sensitivity of 73% (95% confidence interval [CI] 69%-77%), a specificity of 95% (CI 93%-96%), a positive predictive value of 87% (CI 84%-90%), and a negative predictive value of 88% (CI 86%-90%) for detecting hypertensive adults compared with physician-assigned diagnoses. Compared with self-reported survey data, the algorithm had a sensitivity of 64% (CI 63%-66%), a specificity of 94%(CI 93%-94%), a positive predictive value of 77% (76%-78%), and negative predictive value of 89% (CI 88%-89%). When this algorithm was applied to the entire province of Ontario, the age- and sex-standardized prevalence of hypertension in adults older than 35 years increased from 20% in 1994 to 29% in 2002.
It is possible to use administrative data to accurately identify from a population sample those patients who have been diagnosed with hypertension. Given that administrative data are already routinely collected, their use is likely to be substantially less expensive compared with serial cross-sectional or cohort studies for surveillance of hypertension occurrence and outcomes over time in a large population.
Asthma imposes a heavy and expensive burden on individuals and populations. A population-based surveillance and research program based on health administrative data could measure and study the burden of asthma; however, the validity of a health administrative data diagnosis of asthma must first be confirmed.
To evaluate the accuracy of population-based provincial health administrative data in identifying adult patients with asthma for ongoing surveillance and research.
Patients from randomly selected primary care practices were assigned to four categories according to their previous diagnoses: asthma, chronic obstructive pulmonary disease, related respiratory conditions and nonasthma conditions. In each practice, 10 charts from each category were randomly selected, abstracted, then reviewed by a blinded expert panel who identified them as asthma or nonasthma. These reference standard diagnoses were then linked to the patients' provincial records and compared with health administrative algorithms designed to identify asthma. Analyses were performed using the concepts of diagnostic test evaluation.
A total of 518 charts, including 160 from individuals with asthma, were reviewed. The algorithm of two or more ambulatory care visits and/or one or more hospitalization(s) for asthma in two years had a sensitivity of 83.8% (95% CI 77.1% to 89.1%) and a specificity of 76.5% (95% CI 71.8% to 80.8%).
Definitions of adult asthma using health administrative data are sensitive and specific for identifying adults with asthma. Using these definitions, cohorts of adults with asthma for ongoing population-based surveillance and research can be developed.
Osteoarthritis is the most common form of arthritis, affecting millions of people in the United States. It is a complex disease whose etiology bridges biomechanics and biochemistry. Evidence is growing for the role of systemic factors (such as genetics, dietary intake, estrogen use, and bone density) and of local biomechanical factors (such as muscle weakness, obesity, and joint laxity). These risk factors are particularly important in weight-bearing joints, and modifying them may present opportunities for prevention of osteoarthritis-related pain and disability. Major advances in management to reduce pain and disability are yielding a panoply of available treatments ranging from nutriceuticals to chondrocyte transplantation, new oral anti-inflammatory medications, and health education. This article is part 1 of a two-part summary of a National Institutes of Health conference. The conference brought together experts on osteoarthritis from diverse backgrounds and provided a multidisciplinary and comprehensive summary of recent advances in the prevention of osteoarthritis onset, progression, and disability. Part 1 focuses on a new understanding of what osteoarthritis is and on risk factors that predispose to disease occurrence. It concludes with a discussion of the impact of osteoarthritis on disability.
Musculoskeletal conditions are a major burden on individuals, health systems, and social care systems, with indirect costs being predominant. This burden has been recognized by the United Nations and WHO, by endorsing the Bone and Joint Decade 2000-2010. This paper describes the burden of four major musculoskeletal conditions: osteoarthritis, rheumatoid arthritis, osteoporosis, and low back pain. Osteoarthritis, which is characterized by loss of joint cartilage that leads to pain and loss of function primarily in the knees and hips, affects 9.6% of men and 18% of women aged > 60 years. Increases in life expectancy and ageing populations are expected to make osteoarthritis the fourth leading cause of disability by the year 2020. Joint replacement surgery, where available, provides effective relief. Rheumatoid arthritis is an inflammatory condition that usually affects multiple joints. It affects 0.3-1.0% of the general population and is more prevalent among women and in developed countries. Persistent inflammation leads to joint destruction, but the disease can be controlled with drugs. The incidence may be on the decline, but the increase in the number of older people in some regions makes it difficult to estimate future prevalence. Osteoporosis, which is characterized by low bone mass and microarchitectural deterioration, is a major risk factor for fractures of the hip, vertebrae, and distal forearm. Hip fracture is the most detrimental fracture, being associated with 20% mortality and 50% permanent loss in function. Low back pain is the most prevalent of musculoskeletal conditions; it affects nearly everyone at some point in time and about 4-33% of the population at any given point. Cultural factors greatly influence the prevalence and prognosis of low back pain.
Large health care utilization databases are frequently used in variety of settings to study the use and outcomes of therapeutics. Their size allows the study of infrequent events, their representativeness of routine clinical care makes it possible to study real-world effectiveness and utilization patterns, and their availability at relatively low cost without long delays makes them accessible to many researchers. However, concerns about database studies include data validity, lack of detailed clinical information, and a limited ability to control confounding.
We consider the strengths, limitations, and appropriate applications of health care utilization databases in epidemiology and health services research, with particular reference to the study of medications.
Progress has been made on many methodologic issues related to the use of health care utilization databases in recent years, but important areas persist and merit scrutiny.
Osteoarthritis is the most common form of arthritis, affecting millions of people in the United States. It is a complex disease whose etiology bridges biomechanics and biochemistry. Evidence is growing for the role of systemic factors (such as genetics, dietary intake, estrogen use, and bone density) and of local biomechanical factors (such as muscle weakness, obesity, and joint laxity). These risk factors are particularly important in weightbearing joints, and modifying them may present opportunities for prevention of osteoarthritis-related pain and disability. Major advances in management to reduce pain and disability are yielding a panoply of available treatments ranging from nutriceuticals to chondrocyte transplantation, new oral anti-inflammatory medications, and health education. This article is part 1 of a two-part summary of a National Institutes of Health conference. The conference brought together experts on osteoarthritis from diverse backgrounds and provided a multidisciplinary and comprehensive summary of recent advances in the prevention of osteoarthritis onset, progression, and disability. Part 1 focuses on a new understanding of what osteoarthritis is and on risk factors that predispose to disease occurrence. It concludes with a discussion of the impact of osteoarthritis on disability. Ann Intern Med. 2000;133:635-646. www.annals.org For author affiliations and current addresses, see end of text.
Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications.
Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Evolving definitions of osteoarthritis and improvements in risk factor measurement that use advanced imaging, systemic and local biomarkers, and improved methods for measuring symptoms and their impact can help elucidate mechanisms and identify potential areas for intervention or prevention.
Objective:
To evaluate the quality of the methods and reporting of published studies that validate administrative database algorithms for rheumatic disease case ascertainment.
Methods:
We systematically searched MEDLINE, Embase, and the reference lists of articles published from 1980 to 2011. We included studies that validated administrative data algorithms for rheumatic disease case ascertainment using medical record or patient-reported diagnoses as the reference standard. Each study was evaluated using published standards for the reporting and quality assessment of diagnostic accuracy, which informed the development of a methodologic framework to help critically appraise and guide research in this area.
Results:
Twenty-three studies met the inclusion criteria. Administrative database algorithms to identify cases were most frequently validated against diagnoses in medical records (83%). Almost two-thirds of the studies (61%) used diagnosis codes in administrative data to identify potential cases and then reviewed medical records to confirm the diagnoses. The remaining studies did the reverse, identifying patients using a reference standard and then testing algorithms to identify cases in administrative data. Many authors (61%) described the patient population, but few (26%) reported key measures of diagnostic accuracy (sensitivity, specificity, and positive and negative predictive values). Only one-third of studies reported disease prevalence in the validation study sample.
Conclusion:
The methods used in administrative data validation studies of rheumatic diseases are highly variable. Few studies reported key measures of diagnostic accuracy despite their importance for drawing conclusions about the validity of administrative database algorithms. We developed a methodologic framework and recommendations for validation study conduct and reporting.
Musculoskeletal conditions are common in men and women of all ages across all socio-demographic strata of society. They are the most common cause of severe long-term pain and physical disability and affect hundreds of millions of people around the world. They impact on all aspects of life through pain and by limiting activities of daily living typically by affecting dexterity and mobility. They affect one in four adults across Europe [1]. Musculoskeletal conditions have an enormous economic impact on society through both direct health expenditure related to treating the sequelae of the conditions and indirectly through loss of productivity. The prevalence of many of these conditions increases markedly with age, and many are affected by lifestyle factors, such as obesity and lack of physical activity. The burden of these conditions is therefore predicted to increase, in particular in developing countries. The impact on individuals and society of the major musculoskeletal conditions is reviewed and effective prevention, treatment and rehabilitation considered. The need to recognise musculoskeletal conditions as a global public health priority is discussed.
Obesity and knee osteoarthritis are among the most frequent chronic conditions affecting Americans aged 50 to 84 years.
To estimate quality-adjusted life-years lost due to obesity and knee osteoarthritis and health benefits of reducing obesity prevalence to levels observed a decade ago.
The U.S. Census and obesity data from national data sources were combined with estimated prevalence of symptomatic knee osteoarthritis to assign persons aged 50 to 84 years to 4 subpopulations: nonobese without knee osteoarthritis (reference group), nonobese with knee osteoarthritis, obese without knee osteoarthritis, and obese with knee osteoarthritis. The Osteoarthritis Policy Model, a computer simulation model of knee osteoarthritis and obesity, was used to estimate quality-adjusted life-year losses due to knee osteoarthritis and obesity in comparison with the reference group.
United States.
U.S. population aged 50 to 84 years.
Quality-adjusted life-years lost owing to knee osteoarthritis and obesity.
Estimated total losses of per-person quality-adjusted life-years ranged from 1.857 in nonobese persons with knee osteoarthritis to 3.501 for persons affected by both conditions, resulting in a total of 86.0 million quality-adjusted life-years lost due to obesity, knee osteoarthritis, or both. Quality-adjusted life-years lost due to knee osteoarthritis and/or obesity represent 10% to 25% of the remaining quality-adjusted survival of persons aged 50 to 84 years. Hispanic and black women had disproportionately high losses. Model findings suggested that reversing obesity prevalence to levels seen 10 years ago would avert 178,071 cases of coronary heart disease, 889,872 cases of diabetes, and 111,206 total knee replacements. Such a reduction in obesity would increase the quantity of life by 6,318,030 years and improve life expectancy by 7,812,120 quality-adjusted years in U.S. adults aged 50 to 84 years.
Comorbidity incidences were derived from prevalence estimates on the basis of life expectancy of the general population, potentially resulting in conservative underestimates. Calibration analyses were conducted to ensure comparability of model-based projections and data from external sources.
The number of quality-adjusted life-years lost owing to knee osteoarthritis and obesity seems to be substantial, with black and Hispanic women experiencing disproportionate losses. Reducing mean body mass index to the levels observed a decade ago in this population would yield substantial health benefits.
The National Institutes of Health and the Arthritis Foundation.
Osteoarthritis (OA) is the most common joint disorder in the United States. Symptomatic knee OA occurs in 10% men and 13% in women aged 60 years or older. The number of people affected with symptomatic OA is likely to increase due to the aging of the population and the obesity epidemic. OA has a multifactorial etiology, and can be considered the product of an interplay between systemic and local factors. Old age, female gender, overweight and obesity, knee injury, repetitive use of joints, bone density, muscle weakness, and joint laxity all play roles in the development of joint OA, particularly in the weight-bearing joints. Modifying these factors may reduce the risk of OA and prevent subsequent pain and disability.
To assess validity of diabetes International Classification of Disease (ICD) 9 and 10 coding algorithms from administrative data using physicians' charts as the 'gold standard' across time periods and geographic regions.
From 48 urban and 16 rural general practitioners' clinics in Alberta and British Columbia, Canada, we randomly selected 50patient charts/clinic for those who visited the clinic in either 2001 or 2004. Reviewed chart data were linked with inpatient discharge abstract and physician claims administrative data. We identified patients with diabetes in the administrative databases using ICD-9 code 250.xx and ICD-10 codes E10.x-E14.x.
The prevalence of diabetes was 8.1% among clinic charts. The coding algorithm of "2 physician claims within 2 years or 1 hospitalization with the relevant diabetes ICD codes" had higher validity than other 7 algorithms assessed (sensitivity 92.3%, specificity 96.9%, positive predictive value 77.2%, and negative predictive value 99.3%). After adjustment for age, sex, and comorbid conditions, sensitivity and positive predictive values were not significantly different between time periods and regions.
Diabetes could be accurately identified in administrative data using the following case definition "2 physician claims within 2 years or 1 hospital discharge abstract record with diagnosis codes 250.xx or E10.x-E14.x".
Although older age is the greatest risk factor for osteoarthritis (OA), OA is not an inevitable consequence of growing old. Radiographic changes of OA, particularly osteophytes, are common in the aged population, but symptoms of joint pain may be independent of radiographic severity in many older adults. Ageing changes in the musculoskeletal system increase the propensity to OA but the joints affected and the severity of disease are most closely related to other OA risk factors such as joint injury, obesity, genetics and anatomical factors that affect joint mechanics. The ageing changes in joint tissues that contribute to the development of OA include cell senescence that results in development of the senescent secretory phenotype and ageing changes in the matrix including formation of advanced glycation end-products that affect the mechanical properties of joint tissues. An improved mechanistic understanding of joint ageing will likely reveal new therapeutic targets to slow or halt disease progression. The ability to slow progression of OA in older adults will have enormous public health implications given the ageing of our population and the increase in other OA risk factors such as obesity.
The purpose of the study was to develop a population-based simulation model of osteoarthritis (OA) in Canada that can be used to quantify the future health and economic burden of OA under a range of scenarios for changes in the OA risk factors and treatments. In this article we describe the overall structure of the model, sources of data, derivation of key input parameters for the epidemiological component of the model, and preliminary validation studies.
We used the Population Health Model (POHEM) platform to develop a stochastic continuous-time microsimulation model of physician-diagnosed OA. Incidence rates were calibrated to agree with administrative data for the province of British Columbia, Canada. The effect of obesity on OA incidence and the impact of OA on health-related quality of life (HRQL) were modeled using Canadian national surveys.
Incidence rates of OA in the model increase approximately linearly with age in both sexes between the ages of 50 and 80 and plateau in the very old. In those aged 50+, the rates are substantially higher in women. At baseline, the prevalence of OA is 11.5%, 13.6% in women and 9.3% in men. The OA hazard ratios for obesity are 2.0 in women and 1.7 in men. The effect of OA diagnosis on HRQL, as measured by the Health Utilities Index Mark 3 (HUI3), is to reduce it by 0.10 in women and 0.14 in men.
We describe the development of the first population-based microsimulation model of OA. Strengths of this model include the use of large population databases to derive the key parameters and the application of modern microsimulation technology. Limitations of the model reflect the limitations of administrative and survey data and gaps in the epidemiological and HRQL literature.
We validated the accuracy of case definitions for hypertension derived from administrative data across time periods (year 2001 versus 2004) and geographic regions using physician charts. Physician charts were randomly selected in rural and urban areas from Alberta and British Columbia, Canada, during years 2001 and 2004. Physician charts were linked with administrative data through unique personal health number. We reviewed charts of approximately 50 randomly selected patients >35 years of age from each clinic within 48 urban and 16 rural family physician clinics to identify physician diagnoses of hypertension during the years 2001 and 2004. The validity indices were estimated for diagnosed hypertension using 3 years of administrative data for the 8 case-definition combinations. Of the 3,362 patient charts reviewed, the prevalence of hypertension ranged from 18.8% to 33.3%, depending on the year and region studied. The administrative data hypertension definition of "2 claims within 2 years or 1 hospitalization" had the highest validity relative to the other definitions evaluated (sensitivity 75%, specificity 94%, positive predictive value 81%, negative predictive value 92%, and kappa 0.71). After adjustment for age, sex, and comorbid conditions, the sensitivities between regions, years, and provinces were not significantly different, but the positive predictive value varied slightly across geographic regions. These results provide evidence that administrative data can be used as a relatively valid source of data to define cases of hypertension for surveillance and research purposes.
Billing or claims data, commonly referred to as administrative data, can be a valuable tool as the first step in a continuous quality improvement process. It is an inexpensive source of information which allows providers to identify opportunities for improvement in the process and the outcomes of health care delivery. The All Patient Refined/Diagnosis-Related Group case mix or severity-adjusted data represents one tool. The Practice Review System of Value Health Sciences is another. Comparative information is the first step, and the first step only in the quality improvement process. As such, to meet the needs of all continuous quality improvement customers, it is necessary to make this first step as reliable, yet inexpensive, as possible. Completing all the steps requires the use of a several measures over time.
To assess the positive and negative predictive values of osteoarthritis (OA) diagnoses contained in an administrative database.
We identified all members (> or =18 years of age) of a Massachusetts health maintenance organization with documentation of at least one health care encounter associated with an OA diagnosis during the period 1994-1996. From this population, we randomly selected 350 subjects. In addition, we randomly selected 250 enrollees (proportionally by the age and sex of the 350 subjects) who did not have a health care encounter associated with an OA diagnosis. Trained nurse reviewers abstracted OA-related clinical, laboratory, and radiologic data from the medical records of both study groups (all but 1 chart was available for review). Pairs of physician reviewers evaluated the abstracted information for both groups of subjects and rated the evidence for the presence of OA according to 3 levels: definite, possible, and unlikely.
Among the group of patients with an administrative diagnosis of OA, 215 (62%) were rated as having definite OA, 36 (10%) possible OA, and 98 (28%) unlikely OA, according to information contained in the medical record. The positive predictive value of an OA diagnosis was 62%. In those without an administrative OA diagnosis, 44 (18%) were assigned a rating of definite OA. The negative predictive value of the absence of an administrative OA diagnosis was 78%.
Use of administrative data in epidemiologic and health services research on OA may lead to both case misclassification and under ascertainment.
To resolve uncertainty regarding sex differences in osteoarthritis (OA) by performing a meta-analysis of sex differences in OA prevalence, incidence and severity.
Standard search strategies for population-based studies of OA providing sex-specific data. Random effects meta-analysis to provide pooled male vs female risk and rate ratios for prevalent and incident OA, and standardized mean differences (SMD) for OA severity. Meta-regression was used to investigate sources of heterogeneity.
Males had a significantly reduced risk for prevalent OA in the knee [Risk Ratio (RR) 0.63, 95% CI 0.53-0.75] and hand [RR 0.81, 95% CI 0.73-0.90] but not for other sites. Males aged <55 years had a greater risk of prevalent cervical spine OA [RR 1.29, 95% CI 1.18-1.41]. Males also had significantly reduced rates of incident OA in the knee [Incidence Rate Ratio (IRR) 0.55, 95% CI 0.32-0.94] and hip [IRR 0.64, 95% CI 0.48-0.86], with a trend for hand [IRR 0.65, 95% confidence interval (CI) 0.35-1.20]. Females, particularly those > or = 55 years, tended to have more severe OA in the knee but not other sites. Heterogeneity in the estimates of sex differences in prevalence was substantially explained by age and other study design factors including method of OA definition.
The results demonstrate the presence of sex differences in OA prevalence and incidence, with females generally at a higher risk. Females also tend to have more severe knee OA, particularly after menopausal age. The site differences indicate the need for further studies to explore mechanisms underlying OA.
The aim of the study is to develop a method to estimate osteoarthritis (OA) incidence by using administrative health care databases.
Using actual counts of OA diagnoses in different periods, we generated an equation that estimated the number of new OA diagnoses based on the length of time used for excluding prevalent OA cases. Physicians billing files from 1983 to 2002 maintained at Alberta Health and Wellness were used to verify the proposed method. Age- and sex-specific and crude OA incidences in 2002 were calculated by using this method.
Women aged 50 to 59 years had the greatest incidence. For men, the greatest incidence was in the 60- to 69-year age category. Crude incidences for women and men were 1103 and 934 per 100,000 person-years, respectively. The overall crude rate was 1040 per 100,000 person-years.
Modified power function accurately summarizes the relationship between number of first OA diagnoses and length of the clearance period and thus provides an effective model to estimate OA incidence. Not restricted to OA, this model also can be implemented to estimate incidences of other chronic conditions.
Osteoarthritis (OA) is a highly prevalent and often disabling disease. Data on the incidence of OA in the general population are limited. Our objectives were (1) to estimate OA prevalence and incidence rates by age and sex in a geographically defined population of 4 million people [British Columbia (BC), Canada] using an administrative database; and (2) to determine the effects of different administrative definitions of OA and observation (run-in) time on such estimates.
We used data on all visits to health professionals and hospital admissions covered by the Medical Services Plan (MSP) of BC for the fiscal years 1991-92 through 2000-01. OA was defined based on International Classification of Diseases, 9th Revision, diagnostic codes required for administrative purposes.
The overall prevalence of OA in 2001 was 10.8%: 8.9% in men and 12.6% in women. Prevalence was higher in women in all age groups. By age 70-74 years, about one-third of men and 40% of women had OA. Incidence rates in 2000-01 were 11.7 per 1000 person-years in the total population, 10.0 in men and 13.4 in women. Rates increased linearly with age between 50 and 80 years. Both prevalence and incidence depended strongly on the definition of OA and the run-in period.
Prevalence of physician-diagnosed OA in BC was slightly lower than self-reported prevalence of arthritis in population surveys. Routinely collected administrative data could be a valuable source of information for OA surveillance, but more research is needed on the validity of OA diagnosis in administrative databases.
Prevalence of osteoarthritis (OA) is expected to increase due to population aging. However, there is little information on the trends in the incidence of OA over time. The purpose of this study was to describe changes in physician-diagnosed OA incidence rates between 1996-1997 and 2003-2004 in British Columbia (BC), Canada.
We used data on all visits to health professionals and hospital admissions covered by the Medical Services Plan of BC (population approximately 4 million) for the fiscal years 1991-1992 through 2003-2004. Rates were standardized to the BC population in 2000. We used 2 definitions of OA: 1) at least 1 visit or hospitalization with a diagnostic code for OA, and 2) at least 2 visits or 1 hospitalization with a code for OA. Incidence rates were calculated with a 5-year run-in period to exclude prevalent cases.
Between 1996-1997 and 2003-2004, crude incidence rates of OA based on definition 1 increased from 10.5 to 12.2 per 1,000 in men and from 13.9 to 17.4 per 1,000 in women. The age-standardized rates did not change in men and increased from 14.7 to 16.7 per 1,000 in women. Incidence rates based on definition 2 were almost 50% lower, but the trends were similar.
We observed an increase in the incidence of OA in both men and women due to population aging and an additional increase in women beyond the effect of aging. These trends have important implications for public health and provision of health services to this very large group of patients.
Burden of major musculoskeletal conditions: World Health 2005 76.2 72.6 82.6 (82.2, 82.9) 72.7 68
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2005
76.2
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68.5
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136.3
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74.6
--
74.7
70.7
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2007
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