Background/Purpose: Rising rates of total knee arthroplasty (TKA) in younger adults with knee osteoarthritis (OA) has prompted concern about surgical appropriateness. We compared patient appropriateness for TKA, using previously validated criteria, and surgeons’ recommendations for TKA, by patient age.
Methods: This cross-sectional study recruited patients with knee OA referred for TKA consultation to two centralized provincial arthroplasty intake centers in Alberta, Canada. Patients aged 30 years or older and determined by the surgeon to have primary knee OA on physical examination and imaging were eligible. Individuals with inflammatory arthritis were excluded. To examine age effects, recruitment continued until there was at least 200 individuals aged 30-59, 60-69 and ≥ 70 years. A pre-consult questionnaire assessed measures of patients’ TKA appropriateness (need: knee symptoms, prior OA treatment; readiness/willingness to undergo TKA; health status; expectations) and contextual factors. Post-consultation, surgeons reported if TKA had been recommended and if not, why. Using multivariable logistic regression, we assessed the relationships between patient age (< 60 versus ≥ 60) and TKA appropriateness and receipt of surgeon recommendation for TKA.
Results: Of 2,064 participants, 26.0% were < 60 years of age, 68.0% female, 35.6% employed. Compared to older participants, younger participants reported significantly worse knee symptoms, higher use of OA therapies and similar TKA readiness/willingness. They were also more likely to have BMI >40 kg/m2, smoke and endorse return to exercise/sports as a very important TKA outcome. TKA was offered to 1,525 individuals (73.9%). In multivariable analyses, controlling for TKA appropriateness, we found no relationship between patient age and surgeons’ recommendations for TKA (OR, odds ratio, 0.81; 95% CI, confidence interval, 0.59 to 1.10). Surgeons were significantly more likely to recommend TKA to those with TKA need, willingness and for whom improved ability to perform daily activities was very important. They were less likely to recommend surgery to smokers and for whom return to exercise/sport was important.
Conclusion: Among individuals referred for surgical consultation regarding TKA for knee OA, we found that younger patients (< 60 years old) had comparable TKA need, readiness and willingness as those aged 60 years or older. However, younger individuals were more likely to be obese, smoke, and desire to return to sport after TKA, which may increase risk for complications, including early revision. Incorporation of TKA appropriateness criteria into patient referral and patient-surgeon decision-making regarding TKA has potential to facilitate a balanced consideration of TKA benefits alongside the risks in a growing population of young, obese individuals with knee OA.
Authors: Lisa Lix, James Ayles, Sharon Bartholomew, Charmaine Cooke, Joellyn Ellison, Valerie Emond, Naomi Hamm, Heather Hannah, Sonia Jean, Shannon LeBlanc, J. Michael Paterson, Catherine Pelletier, Karen Phillips, Rolf Puchtinger, Kim Reimer, Cynthia Robitaille, Mark Smith, Lawrence Svenson, Karen Tu, Linda VanTil, Sean Waits, Louise Pelletier [Canadian Chronic Disease Surveillance System (CCDSS)]
The Canadian Chronic Disease Surveillance System (CCDSS) uses administrative data to estimate prevalence of multiple chronic diseases, including arthritis.
Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data.
Using a bilingual online survey, we ascertained Canadians’ views about using administrative databases and other publicly-collected data for health research. Respondents were generally supportive (by the end of the survey, 93% felt positively about this work), but wanted to learn more about the data access and security measures, including the role of data stewards. Our findings suggest that more education may increase public trust and support for this important research.
Document Link: https://acrabstracts.org/abstract/canadians-views-about-using-big-data-in-health-research-from-a-national-online-survey-a-partnership-of-patient-consumers-and-researchers/
More than 6 million Canadians suffer from arthritis; more than half of them are under the age of 65. Health reporter Pauline Chan of CTV interviews Dr. Jessica Widdifield to learn about what it is like to live with arthritis (simulation of arthritis in a bodysuit) and to gain insight on access to care, discussing the lack of medical specialists to provide treatment to patients with arthritis.
Abstract
Purpose of Review
One justification for using expensive biologic therapy in rheumatoid arthritis (RA) has been that it can reduce future healthcare utilization such as joint surgeries and physician visits. However, the evidence to support this assertion is unclear. We conducted a review of the literature for studies which have analyzed the trends in resource use of RA patients, and then undertook a retrospective observational analysis of a Canadian administrative database using instrumental variable methods.
Recent Findings
Our review found a trend in reduced resource utilization prior to the introduction of biologics and no evidence that biologic therapies have specifically contributed to this reduction. Our observational analysis, which overcame some of the epidemiological challenges with determining the influence of biologics on resource utilization, found a possible reduction in other medications but possible increases rather than decreases in physician visits and hospitalizations. However, our sample was not sufficiently large to make definitive conclusions.
Summary
Over 15 years since the introduction of biologics for RA, no evidence exists supporting the assumption that biologic therapies reduce future healthcare utilization. While such a question is challenging to generate evidence for, and so an absence of evidence does not suggest that the hypothesis is incorrect, an instrumental variable analysis using sufficient data could provide definitive evidence.
Administrative databases: can they be used for pediatric rheumatic disease surveillance? a survey of Canadian pediatric rheumatologists
Poster
Abstract
Objectives: To conduct a systematic review of studies reporting on the development or validation of comorbidity indices using administrative health data and compare their ability to predict outcomes related to comorbidity (ie, construct validity).
Study Design and Setting: We conducted a comprehensive literature search of MEDLINE and EMBASE, until September 2012. After title and abstract screen, relevant articles were selected for review by two independent investigators. Predictive validity and model fit were measured using c-statistic for dichotomous outcomes and R2 for continuous outcomes.
Results: Our review includes 76 articles. Two categories of comorbidity indices were identified: those identifying comorbidities based on diagnoses, using International Classification of Disease codes from hospitalization or outpatient data, and based on medications, using pharmacy data. The ability of indices studied to predict morbidity-related outcomes ranged from poor (C statistic 0.69) to excellent (C statisticO0.80) depending on the specific index, outcome measured, and study population. Diagnosis-based measures, particularly the Elixhauser Index and the Romano adaptation of the Charlson Index, resulted in higher ability to predict mortality outcomes. Medication-based indices, such as the Chronic Disease Score, demonstrated better performance for predicting health care utilization.
Conclusion: A number of valid comorbidity indices derived from administrative data are available. Selection of an appropriate index should take into account the type of data available, study population, and specific outcome of interest. 2015 Elsevier Inc. All rights reserved.
Abstract
Introduction: Use of disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) may prevent joint damage and potentially reduce joint replacement surgeries. We assessed the association between RA drug use and joint replacement in Quebec, Canada.
Methods: A cohort of new-onset RA patients was identified from Quebec’s physician billing and hospitalization databases from 2002–2011. The outcome was defined using procedure codes submitted by orthopedic surgeons. Medication use was obtained from pharmacy databases. We used alternative Cox regression models with
time-dependent variables measuring the cumulative effects of past use during different time windows (one model focussing on the first year after cohort entry) for methotrexate (MTX), and other DMARDs. Models were adjusted for baseline sociodemographics, co-morbidity and prior health service use, time-dependent cumulative use of other drugs (anti-tumor necrosis factor [anti-TNF] agents, other biologics, cyclooxygenase-2 inhibitors [COXIBs], nonselective nonsteroidal antiinflammatory drugs [NSAIDs], and systemic steroids), and markers of disease severity.
Results: During follow-up, 608 joint replacements occurred among 11,333 patients (median follow-up: 4.6 years). The best-fitting model relied on the cumulative early use (within the first year after cohort entry) of MTX and of other DMARDs, with an interaction between MTX and other DMARDs. In this model, greater exposure within the first year, to either MTX (adjusted hazard ratio, HR = 0.95 per 1 month, 95 % confidence interval, 95 % CI 0.93-0.97) or other DMARDs (HR = 0.97, 95 % CI 0.95-0.99) was associated with longer time to joint replacement.
Conclusions: Our results suggest that longer exposure to either methotrexate (MTX) or other DMARDs within the first year after RA diagnosis is associated with longer time to joint replacement surgery.
Authors:Cristiano S. Moura, Michal Abrahamowicz, Marie-Eve Beauchamp, Diane Lacaille, Yishu Wang, Gilles Boire, Paul R. Fortin, Louis Bessette, Claire Bombardier, Jessica Widdifield, John G. Hanly, Debbie Feldman, Walter Maksymowych, Christine Peschken, Cheryl Barnabe, Steve Edworthy, Sasha Bernatsky and CAN-AIM
Abstract
Background: Though administrative databases are increasingly being used for research related to myocardial infarction (MI),
the validity of MI diagnoses in these databases has never been synthesized on a large scale.
Objective: To conduct the first systematic review of studies reporting on the validity of diagnostic codes for identifying MI
in administrative data.
Methods: MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to
identify MI; or (b) Evaluating the validity of MI codes in administrative data; and (c) Reporting validation statistics (sensitivity,
specificity, positive predictive value (PPV), negative predictive value, or Kappa scores) for MI, or data sufficient for their
calculation. Additonal articles were located by handsearch (up to February 2011) of original papers. Data were extracted by
two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool.
Results: Thirty studies published from 1984–2010 were included; most assessed codes from the International Classification
of Diseases (ICD)-9th revision. Sensitivity and specificity of hospitalization data for identifying MI in most [$50%] studies was
$86%, and PPV in most studies was $93%. The PPV was higher in the more-recent studies, and lower when criteria that do
not incorporate cardiac troponin levels (such as the MONICA) were employed as the gold standard. MI as a cause-of-death
on death certificates also demonstrated lower accuracy, with maximum PPV of 60% (for definite MI).
Conclusions: Hospitalization data has higher validity and hence can be used to identify MI, but the accuracy of MI as a
cause-of-death on death certificates is suboptimal, and more studies are needed on the validity of ICD-10 codes. When
using administrative data for research purposes, authors should recognize these factors and avoid using vital statistics data
if hospitalization data is not available to confirm deaths from MI.
Received September 29, 2013; Accepted February 20, 2014; Published March 28, 2014
Citation: McCormick N, Lacaille D, Bhole V, Avina-Zubieta JA (2014) Validity of Myocardial Infarction Diagnoses in Administrative Databases: A Systematic
Review. PLoS ONE 9(3): e92286. doi:10.1371/journal.pone.0092286
Abstract
Background
Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0.
Methods
Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen’s κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement.
Results
The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen’s κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics.
Conclusions
Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations.
BMC Geriatrics 2015, 15:24 (11 March 2015).
