Diagnostic accuracy of administrative data algorithms in the diagnosis of osteoarthritis: a systematic review

Impact of depressive symptoms on direct medical cost among medicare recipients with knee osteoarthritis

OBJECTIVE

Depressive symptoms are prevalent among knee osteoarthritis (KOA) patients and may lead to additional medical costs. We compared medical costs in Medicare Current Beneficiary Survey (MCBS) respondents with KOA with and without self-reported depressive symptoms.

METHODS

We identified a KOA cohort using ICD-9/10 diagnostic codes in both Part A and Part B claims among community-dwelling MCBS respondents from 2003 to 2019. We determined the presence of depressive symptoms using self-reported data on sadness or anhedonia. We considered three groups: 1) without depressive symptoms, 2) with depressive symptoms, no billable services, and 3) with depressive symptoms and billable services. We used a generalized linear model with log-transformed outcomes to compare annual total direct medical costs among the three groups, adjusting for age, gender, race, history of fall, Total Joint Replacement, comorbidities, and calendar year.

RESULTS

The analysis included 4118 MCBS respondents with KOA. Of them, 27% had self-reported depressive symptoms, and 6% reported depressive symptoms and received depression-related billable services. The adjusted mean direct medical costs were $8598/year for those without depressive symptoms, $9239/year for those who reported depressive symptoms and received no billable services, and $14,229/year for those who reported depressive symptoms and received billable services.

CONCLUSION

While over one quarter of Medicare beneficiaries with KOA self-reported depressive symptoms, only 6% received billable medical services. The presence of depressive symptoms led to higher direct medical costs, even among those who did not receive depression-related billable services.

"Application of five different strategies to define a cohort of patients with knee osteoarthritis in a large primary care database"

BACKGROUND

Electronic health records (EHR) are frequently used for epidemiological research including drug utilisation studies in a defined population such as the population with knee osteoarthritis (KOA). We sought to describe the process of defining a cohort of patients with KOA from a large UK primary care database and estimate the annual incidence of diagnosed KOA between 2000 and 2015.

METHOD

This was a retrospective study using data from the clinical practice research datalink (CPRD). CPRD is a large primary care longitudinal electronic medical records' database that contains anonymous records of patients from general practices across United Kingdom. Five different cohort definition strategies were applied including symptoms-based or diagnosis-based strategies or a combination of both. To validate results, the annual incidence of KOA was estimated and compared to published data.

RESULTS

The study defined 898,690 patients when symptoms-based strategy was applied, 137,541 patients when diagnosis based and 83,294 when a combination of both strategies were applied. The final cohort was defined using a diagnosis-based strategy that avoided overestimation (with symptoms-based definition) or underestimation (with a combination of symptoms and diagnosis). The incidence of KOA ranged from 1.33 per 1000 CPRD registrants in 2000, 1.76 in 2008 and 1.45 patients in 2015.

CONCLUSION

This study logically/sensibly defined a cohort of patients with diagnosed KOA through the application of several strategies. This was an essential step to avoid subsequent over or underestimation of the prevalence of drug utilisation and the associated adverse clinical outcomes within primary care patients with KAO.

Patterns of Comorbidities and Prescribing and Dispensing of Non-steroidal Anti-inflammatory Drugs (NSAIDs) Among Patients with Osteoarthritis in the USA: Real-World Study

BACKGROUND

Osteoarthritis (OA) is a major cause of chronic pain. Non-steroidal anti-inflammatory drugs (NSAIDs) are analgesics commonly used for musculoskeletal pain; however, NSAIDs can increase the risk of certain adverse events, such as gastrointestinal bleeding, edema, heart failure, and hypertension.

OBJECTIVE

The objective of this study was to characterize existing comorbidities among patients with OA. For patients with OA with and without a coexisting medical condition of interest (CMCOI), we estimated the prevalence of prescribing and dispensing NSAIDs pre-OA and post-OA diagnosis.

METHODS

Data from three large administrative claims databases were used to construct an OA retrospective cohort. Databases leveraged were IBM MarketScan Medicare Supplemental Database (MDCR), IBM MarketScan Commercial Database (CCAE), and Optum's de-identified Clinformatics® Data Mart Database (Optum CDM). The OA study population was defined to be those patients who had an OA diagnosis from an inpatient or outpatient visit with at least 365 days of prior observation time in the database during January 2000 through May 2021. Asthma, cardiovascular disorders, renal impairment, and gastrointestinal bleeding risks were the CMCOI of interest. Patients with OA were then classified as having or not having evidence of a CMCOI. For both groups, NSAID dispensing patterns pre-OA and post-OA diagnosis were identified. Descriptive analysis was performed within the Observational Health Data Sciences and Informatics framework.

RESULTS

In each database, the proportion of the OA population with at least one CMCOI was nearly 50% or more (48.0% CCAE; 74.4% MDCR; 68.6% Optum CDM). Cardiovascular disease was the most commonly observed CMCOI in each database, and in two databases, nearly one in four patients with OA had two or more CMCOI (23.2% MDCR; 22.6% Optum CDM). Among the OA population with CMCOI, NSAID utilization post-OA diagnosis ranged from 33.0 to 46.2%. Following diagnosis of OA, an increase in the prescribing and dispensing of NSAIDs was observed in all databases, regardless of patient CMCOI presence.

CONCLUSIONS

This study provides real-world evidence of the pattern of prescribing and dispensing of NSAIDs among patients with OA with and without CMCOI, which indicates that at least half of patients with OA in the USA have a coexisting condition. These conditions may increase the risk of side effects commonly associated with NSAIDs. Yet, at least 32% of these patients were prescribed and dispensed NSAIDs. These data support the importance of shared decision making between healthcare professionals and patients when considering NSAIDs for the treatment of OA in patients with NSAID-relevant coexisting medical conditions.

The clinical characteristics, managements, and outcomes of acute myocardial infarction in osteoarthritis patients; a cross-sectional analysis of 6.5 million patients

OBJECTIVES

The prevalence of osteoarthritis (OA) and cardiovascular disease are increasing and both conditions share similar risk factors. We investigated the association between OA and receipt of invasive managements and clinical outcomes in patients with acute myocardial infarction (AMI).

METHODS

Using the National Inpatient Sample, adjusted binary logistic regression determined the association between OA and each outcome variable.

RESULTS

Of 6,561,940 AMI hospitalizations, 6.3% had OA. OA patients were older and more likely to be female. OA was associated with a decreased odds of coronary angiography (adjusted odds ratio 0.91; 95% confidence interval 0.90, 0.92), PCI (0.87; 0.87, 0.88), and coronary artery bypass grafting (0.98; 0.97, 1.00). OA was associated with a decreased odds of adverse outcomes (in-hospital mortality: 0.68; 0.67, 0.69; major acute cardiovascular and cerebrovascular events: 0.71; 0.70, 0.72; all-cause bleeding: 0.76; 0.74, 0.77; and stroke/TIA: 0.84; 0.82, 0.87).

CONCLUSIONS

This study of a representative sample of the US population highlights that OA patients are less likely to be offered invasive interventions following AMI. OA was also associated with better outcomes post-AMI, possibly attributed to a misclassification bias where unwell patients with OA were less likely to receive an OA code because codes for serious illness took precedence.

Increased risk of osteoarthritis in patients with atopic disease

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.

The Association of Body Mass Index and Waist Circumference with the Risk of Achilles Tendon Problems: A Nationwide Population-Based Longitudinal Cohort Study

Background

The purpose of this study was to evaluate the association of body mass index (BMI) and waist circumference (WC) with the risk of Achilles tendinopathy (AT) or Achilles tendon rupture (ATR), using data from a nationwide population-based cohort. We hypothesized that higher BMI and WC would be independently associated with the increased risk of AT or ATR. In addition, a higher WC may potentiate the association between BMI and the risk of Achilles tendon problems.

Methods

We used the National Health Insurance database that covers the entire South Korean population to follow up subjects who participated in the National Health Screening Program (NHSP) from January 2009 to December 2010. The NHSP data include subjects' BMI, WC, blood test results, blood pressure, and information about lifestyle. Among the subjects, those who were newly diagnosed as having AT or ATR before December 31, 2017, were selected. To examine the association of the variables with the risk of AT or ATR and determine whether the effect of higher BMI varied according to WC, multivariate Cox proportional hazards regression was used.

Results

Among a total of 16,830,532 subjects, 125,814 and 31,424 developed AT and ATR, respectively. A higher BMI showed a greater association with the increased risk of ATR than AT (adjusted hazard ratio [HR], 3.49 vs. 1.96). A higher WC was associated with the increased risk of AT (adjusted HR, 1.22), but not ATR. In a separate analysis, the association between BMI and the risk of AT was higher when subjects had higher WC as compared to those with lower WC, being most significant in individuals with both higher BMI and higher WC.

Conclusions

Higher BMI was more associated with the increased risk of ATR than AT. Moreover, a high central fat distribution played an independent and potentiating role in the development of AT. This implies the greater importance of a high central fat distribution contributing to the development of AT in obese people.

Medication use and comorbidities in an increasingly younger osteoarthritis population: an 18-year retrospective open-cohort study

OBJECTIVES

As understanding of the pathogenesis and treatment strategies for osteoarthritis (OA) evolves, it is important to understand how patient factors are also changing. Our goal was to examine demographics and known risk factors of patients with OA over time.

DESIGN

Open-cohort retrospective study using electronic health records.

SETTING

Large US integrated health system with 7 hospitals, 2.6 million outpatient clinic visits and 97 300 hospital admissions annually in a mostly rural geographic region.

PARTICIPANTS

Adult patients with at least two encounters and a diagnosis of OA or OA-relevant surgery between 2001 and 2018. Because of geographic region, over 96% of participants were white/Caucasian.

INTERVENTIONS

None.

PRIMARY AND SECONDARY OUTCOME MEASURES

Descriptive statistics were used to examine age, sex, body mass index (BMI), Charlson Comorbidity Index, major comorbidities and OA-relevant prescribing over time.

RESULTS

We identified 290 897 patients with OA. Prevalence of OA increased significantly from 6.7% to 33.5% and incidence increased 37% (from 3772 to 5142 new cases per 100 000 patients per year) (p<0.0001). Percentage of females declined from 65.3% to 60.8%, and percentage of patients with OA in the youngest age bracket (18-45 years) increased significantly (6.2% to 22.7%, p<0.0001). The percentage of patients with OA with BMI ≥30 remained above 50% over the time period. Patients had low comorbidity overall, but anxiety, depression and gastro-oesophageal reflux disease showed the largest increases in prevalence. Opioid use (tramadol and non-tramadol) showed peaks followed by declines, while most other medications increased slightly in use or remained steady.

CONCLUSIONS

We observe increasing OA prevalence and a greater proportion of younger patients over time. With better understanding of how characteristics of patients with OA are changing over time, we can develop better approaches for managing disease burden in the future.

Prescription Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Incidence of Depression Among Older Cancer Survivors With Osteoarthritis: A Machine Learning Analysis

ObjectiveS

This study examined prescription NSAIDs as one of the leading predictors of incident depression and assessed the direction of the association among older cancer survivors with osteoarthritis.

Methods

This study used a retrospective cohort (N = 14, 992) of older adults with incident cancer (breast, prostate, colorectal cancers, or non-Hodgkin's lymphoma) and osteoarthritis. We used the longitudinal data from the linked Surveillance, Epidemiology, and End Results -Medicare data for the study period from 2006 through 2016, with a 12-month baseline and 12-month follow-up period. Cumulative NSAIDs days was assessed during the baseline period and incident depression was assessed during the follow-up period. An eXtreme Gradient Boosting (XGBoost) model was built with 10-fold repeated stratified cross-validation and hyperparameter tuning using the training dataset. The final model selected from the training data demonstrated high performance (Accuracy: 0.82, Recall: 0.75, Precision: 0.75) when applied to the test data. SHapley Additive exPlanations (SHAP) was used to interpret the output from the XGBoost model.

Results

Over 50% of the study cohort had at least one prescption of NSAIDs. Nearly 13% of the cohort were diagnosed with incident depression, with the rates ranging between 7.4% for prostate cancer and 17.0% for colorectal cancer. The highest incident depression rate of 25% was observed at 90 and 120 cumulative NSAIDs days thresholds. Cumulative NSAIDs days was the sixth leading predictor of incident depression among older adults with OA and cancer. Age, education, care fragmentation, polypharmacy, and zip code level poverty were the top 5 predictors of incident depression.

Conclusion

Overall, 1 in 8 older adults with cancer and OA were diagnosed with incident depression. Cumulative NSAIDs days was the sixth leading predictor with an overall positive association with incident depression. However, the association was complex and varied by the cumulative NSAIDs days.

Diagnostic accuracy of linked administrative data for dementia diagnosis in community-dwelling older men in Australia

Background

Routinely collected health administrative data can be used to estimate the prevalence or incidence of dementia at a population level but can be inaccurate. This study aimed to examine the accuracy of hospital and death data for diagnosing dementia compared with a clinical diagnosis in community dwelling older men in Australia.

Methods

We performed a retrospective analysis of the Concord Health and Ageing in Men Project (CHAMP) in Sydney, Australia. Of the 1705 men aged ≥70 years in the CHAMP study, 1400 had available linked administrative data records from 1 year prior to 1 year post the date of clinical dementia diagnosis. The primary outcome was the accuracy of dementia diagnosis using linked administrative data records compared to clinical dementia diagnosis. The linked data diagnosis was based on hospital and death records for the 1 year pre and post the clinical diagnosis. Clinical dementia diagnosis was a two-stage process with initial screening, followed by clinical assessment for those meeting a validated cut-off. A final clinical diagnosis of dementia based on the Diagnostic and Statistical Manual of Mental Disorders (4th edition) criteria was reached by a consensus panel.

Results

Administrative data identified 28 participants as having dementia, compared to 88 identified through clinical assessment. Administrative data had a sensitivity of 20% (95% CI: 13–30%, 18/88), specificity of 99% (95% CI: 99–100%, 1301/1312), positive predictive value (PPV) of 62% (95% CI: 44–77%), negative predictive value of 95% (95% CI: 94–95%), positive likelihood ratio of 24.4 (95% CI: 11.9–50.0) and negative likelihood ratio of 0.80 (0.72–0.89).

Conclusions

Administrative hospital and death data has limited accuracy for dementia diagnosis with poor sensitivity and PPV. The prevalence of dementia is likely underestimated using hospital and deaths data.

Distinct care trajectories among persons living with arthritic conditions: A two-year state sequence analysis

OBJECTIVES

Developing solutions to optimize care trajectories (CareTs) requires examining patient journeys through the health care system. This study aimed to describe CareTs among people living with arthritis and evaluate their association with self-reported health outcomes.

METHODS

Analyses were conducted using the TorSaDE Cohort (n = 102,148), which connects the 2007 to 2016 Canadian Community Health Surveys (CCHS) with Quebec administrative databases (longitudinal claims). CareTs of participants living with arthritis according to CCHS (n = 16,631), over the two years before CCHS completion, were clustered using state sequence analysis (months as a time unit). CareT group membership was then put in association with self-reported outcomes (pain intensity and interference, self-perceived general and mental health).

RESULTS

The analysis revealed five CareT groups characterized predominantly by: (1) arthritis-related visits to a specialist (n = 2,756; 16.6%), (2) arthritis-related emergency department visits (n = 2,928; 17.6%), (3) very high all-cause health care utilization and arthritis-related hospitalizations (n = 1,570; 9.4%), (4) arthritis-related medical visits to general practitioners and specialists (n = 2,708; 16.3%), (5) low all-cause health care utilization (n = 6,669; 40.1%). Multivariable results revealed that CareT group membership was associated with higher levels of pain interference (CareT group #3 vs. #5: OR: 1.4, 95%CI: 1.1-1.8) and fair/poor self-perceived general health (CareT group #1 vs. #5: OR: 1.551, 95%CI: 1.319-1.824; #2 vs. #5: OR: 1.244, 95%CI: 1.062-1.457; #3 vs. #5: OR: 1.771, 95%CI: 1.451-2.162; #4 vs. #5: OR: 1.481, 95%CI: 1.265-1.735).

DISCUSSION

Sate sequence analysis is an innovative method of studying CareTs and valuable for making evidence-based decisions taking into account inter- and intra-individual variability.

Administrative Data Use in National Registry Efforts: Blessing or Curse?

"Big data" refers to a growing field of large database research. Administrative data, a subset of big data, includes information from insurance claims, electronic medical records, and registries that can be useful for investigating novel research questions. While its use provides salient advantages, potential researchers relying on big data would benefit from knowing about how these databases are coded, common errors they may encounter, and how to best use large data to address various research questions. In the first section of this paper, Dr. Nicholas A. Bedard addresses the four major pitfalls to avoid with diagnosis and procedure codes in administrative data. In the next section, Dr. Jeffrey N. Katz et al. focus on the strengths and limitations of administrative data, suggesting methods to mitigate these limitations. Lastly, Dr. Elena Losina et al. review the uses and misuses of large databases for cost-effectiveness research, detailing methods for careful economic evaluations.

Validation of Operational Definition to Identify Patients with Osteoporotic Hip Fractures in Administrative Claims Data

As incidences of osteoporotic hip fractures (OHFs) have increased, identifying OHFs has become important to establishing the medical guidelines for their management. This study was conducted to develop an operational definition to identify patients with OHFs using two diagnosis codes and eight procedure codes from health insurance claims data and to assess the operational definition’s validity through a chart review. The study extracted data on OHFs from 522 patients who underwent hip surgeries based on diagnosis codes. Orthopedic surgeons then reviewed these patients’ medical records and radiographs to identify those with true OHFs. The validities of nine different algorithms of operational definitions, developed using a combination of three levels of diagnosis codes and eight procedure codes, were assessed using various statistics. The developed operational definition showed an accuracy above 0.97 and an area under the receiver operating characteristic curve above 0.97, indicating excellent discriminative power. This study demonstrated that the operational definition that combines diagnosis and procedure codes shows a high validity in detecting OHFs and can be used as a valid tool to detect OHFs from big health claims data.

Operational Definition Identifying Osteoporotic Vertebral Fractures in the Claims Database

BACKGROUND

We analyzed the International Classification of Diseases, 10th edition (ICD-10) diagnostic codes, procedure codes, and radiographic image codes for vertebral fracture (VF) used in the database of Health Insurance Review and Assessment Service (HIRA) of Korea to establish a validated operational definition for identifying patients with osteoporotic VF in claims data.

METHODS

We developed three operational definitions for detecting VFs using 9 diagnostic codes, 5 procedure codes and 4 imaging codes. Medical records and radiographs of 2,819 patients, who had primary and subordinated codes of VF between January 2016 and December 2016 at two institutions, were reviewed to detect true vertebral fractures. We evaluated the sensitivity and positive predictive value (PPV) of the operational definition in detecting true osteoporotic VF and obtained the receiver operating characteristic (ROC) curve.

RESULTS

Among the 2,819 patients who had primary or secondary diagnosis codes for VF, 995 patients satisfied at least one of the criteria for the operational definition of osteoporotic VF. Of these patients, 594 were judged as having true fractures based on medical records and radiographic examinations. The sensitivity and PPV were 62.5 (95% confidence interval [CI], 59.4-65.6) and 59.7(95% CI, 56.6-62.8) respectively. In the receiver operating characteristic analysis, area under the curve (AUC) was 0.706 (95% CI, 0.688-0.724).

CONCLUSION

Our findings demonstrate the validity of our operational definitions to identify VFs more accurately using claims data. This algorithm to identify VF is likely to be useful in future studies for diagnosing osteoporotic VF.

Estimating incidence and prevalence of hip osteoarthritis using electronic health records: a population-based cohort study

OBJECTIVE

To determine the incidence and prevalence of hip osteoarthritis (OA) in electronic health records (EHRs) of Dutch general practices by using narrative and codified data.

METHOD

A retrospective cohort study was conducted using the Integrated Primary Care Information database. An algorithm was developed to identify patients with narratively diagnosed hip OA in addition to patients with codified hip OA. Incidence and prevalence estimates among people aged ≥30 were assessed from 2008 to 2019. The association of comorbidities with codified hip OA diagnosis was analysed using multivariable logistic regression.

RESULTS

Using the hip OA narrative data algorithm (positive predicted value = 72%) in addition to codified hip OA showed a prevalence of 1.76-1.95 times higher and increased from 4.03% in 2008 to 7.34% in 2019. The incidence was 1.83-2.41 times higher and increased from 6.83 to 7.78 per 1000 person-years from 2008 to 2019. Among codified hip OA patients, 39.4% had a previous record of narratively diagnosed hip OA, on average approximately 1.93 years earlier. Hip OA patients with a previous record of spinal OA, knee OA, hypertension, and hyperlipidaemia were more likely to be recorded with a hip OA code.

CONCLUSION

This study using Dutch EHRs showed that epidemiological estimates of hip OA are likely to be an underestimation. Using our algorithm, narrative data can be added to codified data for more realistic epidemiological estimates based on routine healthcare data. However, developing a valid algorithm remains a challenge, possibly due to the diagnostic complexity of hip pain in general practice.

Trends in the Annual Consultation Incidence and Prevalence of Low Back Pain and Osteoarthritis in England from 2000 to 2019: Comparative Estimates from Two Clinical Practice Databases

Purpose

To compare estimates of annual person-consulting incidence and prevalence of low back pain (LBP) and osteoarthritis for two national English electronic health record databases (Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD).

Patients and Methods

Retrospective, population-based, longitudinal cohort study. LBP and osteoarthritis cases were defined using established codelists in people aged ≥15 and ≥45 years, respectively. Incident cases were new recorded cases in a given calendar year with no relevant consultation in the previous 3 years (denominator = exact person-time in the same calendar year for the at-risk population). Prevalent cases were individuals with ≥1 consultation for the condition of interest recorded in a given calendar year, irrespective of prior consultations for the same condition (denominator = all patients with complete registration history in the previous 3 years). We estimated age-sex standardised incidence and annual (12-month period) prevalence for both conditions in 2000–2019, overall, and by sex, age group, and region.

Results

Standardised incidence and prevalence of LBP from Aurum were lower than those from GOLD until 2014, after which estimates were similar. Both databases showed recent declines in incidence and prevalence of LBP: declines began earlier in GOLD (after 2012–2014) than Aurum (after 2014–2015). Standardised incidence (after 2011) and prevalence of osteoarthritis (after 2003) were higher in Aurum than GOLD and showed different trends: incidence and prevalence were stable or increasing in Aurum, decreasing in GOLD. Stratified estimates in CPRD Aurum suggested consistently higher occurrence among women, older age groups, and those living in the north of England.

Conclusion

Comparative analyses of two English databases produced conflicting estimates and trends for two common musculoskeletal conditions. Aurum estimates appeared more consistent with external sources and may be useful for monitoring population musculoskeletal health and healthcare demand, but they remain sensitive to analytic decisions and data quality.

Incidence and prevalence of knee osteoarthritis using codified and narrative data from electronic health records: a population-based study

OBJECTIVE

This study aimed to determine the incidence and prevalence of knee osteoarthritis (OA) using codified and narrative data from general practices throughout the Netherlands.

METHODS

A retrospective cohort study was conducted using the Integrated Primary Care Information database. Patients with codified knee OA were selected and an algorithm was developed to identify patients with narratively diagnosed knee OA only. Point prevalence proportions and incidence rates among people aged ≥30 were assessed from 2008 to 2019. The association of comorbidities with codified knee OA was analysed using multivariable logistic regression.

RESULTS

The positive predicted value of narratively diagnosed knee OA only was 94.0% (95%CI 87.4%-100%) and for codified knee OA 96.0% (95%CI 90.6%-100%). Including narrative data in addition to codified data resulted in a prevalence of 1.83 to 2.01 times higher (over the study years); prevalence increased from 5.8% to 11.8% between 2008 and 2019. The incidence rate was on 1.93 to 2.28 times higher and increased from 9.98 per 1000 person-years to 13.8 per 1000 person-years between 2008 and 2019. Among patients with codified knee OA, 39.4% were previously diagnosed narratively with knee OA, on average approximately three years earlier. Comorbidities influenced the likelihood of being recorded with codified knee OA.

CONCLUSION

Our study of a Dutch primary care database showed that current incidence and prevalence estimates based on codified data alone from electronic health records are underestimated. Narrative data can be incorporated in addition to codified data to identify knee OA patients more accurately.

Validation of an Operational Definition to Identify Distal Radius Fractures in a National Health Insurance Database

PURPOSE

To develop and validate identification criteria for distal radius fractures (DRFs) and their treatment using a national health insurance database.

METHODS

Patients who had at least 1 wrist radiograph taken in 2018 were recruited from a single academic referral hospital. After excluding patients who lacked immobilization code for wrist pathology, we collected data on the overall population. Because some patients might have undergone wrist radiography at another institution or had DRFs without an immobilization code, we additionally included patients who had a DRF diagnosis code at our institution. Reviews of medical records and wrist radiographs were considered for the diagnosis of DRF. We evaluated the sensitivity, specificity, and positive predictive value (PPV) of 3 operational definitions of fractures that were based on a single primary or secondary diagnosis code; all diagnosis codes, including primary and secondary codes; and all diagnosis and procedure codes.

RESULTS

Among 768 patients included in the study, true DRFs were confirmed in 305. The sensitivity, specificity, and PPV for definition 1 were 91.5% (95% CI, 88.3%-94.6%), 97.5% (95% CI, 95.9%-99.1%), and 96.9% (95% CI, 94.9%-98.9%), respectively. Although the sensitivity of definition 2 was higher (92.1%; 95% CI, 89.1%-95.2%), its specificity and PPV were lower (96.4% [95% CI, 94.4%-98.3%] and 95.6% [95% CI, 93.2%-97.9%], respectively). The sensitivity of definition 3 was the lowest (88.2%; 95% CI, 84.6%-91.8%), but its specificity and PPV were the highest among the 3 definitions (98.6% [95% CI, 97.4%-98.8%] and 98.2% [95% CI, 96.6%-99.8%], respectively).

CONCLUSIONS

Patients with DRFs can be identified from claims databases with high accuracy using an operational definition based on DRF diagnosis and procedure codes, including codes for surgical and nonoperative methods.

CLINICAL RELEVANCE

Verified operational definitions will increase the consistency of results in future national health insurance database studies related to DRFs.

Impact of reported NSAID "allergies" on opioid use disorder in back pain

BACKGROUND

It is crucial to identify patients at highest risk for opioid use disorder (OUD) and to address challenges in reducing opioid use. Reported nonsteroidal anti-inflammatory drug (NSAID) allergies may predispose to use of stronger pain medications and potentially to OUD.

OBJECTIVE

We sought to investigate the clinical impact of reported NSAID allergy on OUD in patients with chronic back pain.

METHODS

We conducted a retrospective study of adults receiving care at a tertiary health care system from January 1, 2013, to December 31, 2018. Back pain and OUD were identified using administrative data algorithms. We used propensity score matching and logistic regression to estimate the impact of self-reported NSAID adverse drug reactions (ADRs) on risk of OUD, adjusting for other relevant clinical information.

RESULTS

Of 47,114 patients with chronic back pain, 3,620 (7.7%) had a reported NSAID ADR. In an adjusted propensity score-matched analysis, patients with NSAID ADRs had higher odds (odds ratio, 1.34; 95% CI, 1.07-1.67) of developing OUD as compared with those without NSAID ADRs. Additional risk factors for OUD included younger age, male sex, Medicaid insurance, Medicare insurance, higher number of inpatient and outpatient visits in the previous year, and comorbid anxiety and depression. Patients with listed NSAID ADRs also had higher odds of a documented opioid prescription during the study period (odds ratio, 1.22; 95% CI, 1.11-1.34).

CONCLUSIONS

Adults with chronic back pain and reported NSAID ADRs are at a higher risk of developing OUD and receiving opioid analgesics, even after accounting for comorbidities and health care utilization. Allergy evaluation is critical for potential delabeling of patients with reported NSAID allergies and chronic pain.

A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis

Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no such study has been carried out in the United States. Therefore, we sought to examine the prevalence and predictors of potentially inappropriate NSAIDs use in older adults (age > 65) with OA using machine learning with real-world data from Optum De-identified Clinformatics^® Data Mart. We identified a retrospective cohort of eligible individuals using data from 2015 (baseline) and 2016 (follow-up). Potentially inappropriate NSAIDs use was identified using the type (COX-2 selective vs. non-selective) and length of NSAIDs use and an individual's CV and GI risk. Predictors of potentially inappropriate NSAIDs use were identified using eXtreme Gradient Boosting. Our study cohort comprised of 44,990 individuals (mean age 75.9 years). We found that 12.8% individuals had potentially inappropriate NSAIDs use, but the rate was disproportionately higher (44.5%) in individuals at low CV/high GI risk. Longer duration of NSAIDs use during baseline (AOR 1.02; 95% CI:1.02-1.02 for both non-selective and selective NSAIDs) was associated with a higher risk of potentially inappropriate NSAIDs use. Additionally, individuals with low CV/high GI (AOR 1.34; 95% CI:1.20-1.50) and high CV/low GI risk (AOR 1.61; 95% CI:1.34-1.93) were also more likely to have potentially inappropriate NSAIDs use. Heightened surveillance of older adults with OA requiring NSAIDs is warranted.

Performance of Administrative Algorithms to Identify Interstitial Lung Disease in Rheumatoid Arthritis

OBJECTIVE

To determine the performance of administrative-based algorithms for classifying interstitial lung disease (ILD) complicating rheumatoid arthritis (RA).

METHODS

Participants in a large, multicenter RA registry were screened for ILD using codes from the International Classification of Diseases, Ninth Revision (ICD-9) and the ICD-10. Medical record review confirmed ILD among participants screening positive and a random sample of those screening negative. ICD and procedure codes, provider specialty, and dates were extracted from Veterans Affairs administrative data to construct ILD algorithms. Performance of these algorithms against medical record review was assessed by sensitivity, specificity, positive predictive value (PPV), negative predictive value, and kappa using inverse probability weighting to account for sampling methods.

RESULTS

Medical records of 536 RA patients were reviewed, confirming 182 (stringent definition) and 203 (relaxed definition) cases of ILD. Initially, we identified ≥2 ICD codes from inpatient or outpatient encounters as optimal discriminating factors (specificity 96.0%, PPV 65.5%; κ = 0.70). Subsequently, we constructed a set of ICD-9 and ICD-10 codes that improved algorithm specificity (specificity 96.8%, PPV 69.5%; κ = 0.72). Algorithms that included a pulmonologist diagnosis or chest computed tomography plus pulmonary function testing or lung biopsy had improved performance (specificity 98.0%, PPV 77.4%; κ = 0.75). PPV increased with exclusion of other ILD causes (78.5%) in comparison with the relaxed ILD definition (82.4%) and in sensitivity analyses (83.4-86.3%). Gains in specificity and PPV with greater algorithm requirements were accompanied by declines in sensitivity.

CONCLUSION

Administrative algorithms with optimal combinations of ICD codes, provider specialty, diagnostic testing, and exclusion of other ILD causes accurately classify ILD in RA.

Validity of Algorithms for Identification of Individuals Suffering from Chronic Noncancer Pain in Administrative Databases: A Systematic Review

BACKGROUND

Secondary analysis of health administrative databases is indispensable to enriching our understanding of health trajectories, health care utilization, and real-world risks and benefits of drugs among large populations.

OBJECTIVES

This systematic review aimed at assessing evidence about the validity of algorithms for the identification of individuals suffering from nonarthritic chronic noncancer pain (CNCP) in administrative databases.

METHODS

Studies reporting measures of diagnostic accuracy of such algorithms and published in English or French were searched in the Medline, Embase, CINAHL, AgeLine, PsycINFO, and Abstracts in Social Gerontology electronic databases without any dates of coverage restrictions up to March 1, 2018. Reference lists of included studies were also screened for additional publications.

RESULTS

Only six studies focused on commonly studied CNCP conditions and were included in the review. Some algorithms showed a ≥60% combination of sensitivity and specificity values (back pain disorders in general, fibromyalgia, low back pain, migraine, neck/back problems studied together). Only algorithms designed to identify fibromyalgia cases reached a ≥80% combination (without replication of findings in other studies/databases).

CONCLUSIONS

In summary, the present investigation informs us about the limited amount of literature available to guide and support the use of administrative databases as valid sources of data for research on CNCP. Considering the added value of such data sources, the important research gaps identified in this innovative review provide important directions for future research. The review protocol was registered with PROSPERO (CRD42018086402).

Validation of an electronic coding algorithm to identify the primary indication of orthopedic surgeries from administrative data

Background

Determining the primary indication of a surgical procedure can be useful in identifying patients undergoing elective surgery where shared decision-making is recommended. The purpose of this study was to develop and validate an algorithm to identify patients receiving the following combinations of surgical procedure and primary indication as part of a study to promote shared decision-making: (1) knee arthroplasty to treat knee osteoarthritis (KOA); (2) hip arthroplasty to treat hip osteoarthritis (HOA); (3) spinal surgery to treat lumbar spinal stenosis (SpS); and (4) spinal surgery to treat lumbar herniated disc (HD).

Methods

Consecutive surgical procedures performed by participating spine, hip, and knee surgeons at four sites within an integrated care network were included. Study staff reviewed electronic medical records to ascertain a “gold standard” determination of the procedure and primary indication status. Electronic algorithms consisting of ICD-10 and CPT codes for each combination of procedure and indication were then applied to records for each case. The primary measures of validity for the algorithms were the sensitivity and specificity relative to the gold standard review.

Results

Participating surgeons performed 790 procedures included in this study. The sensitivity of the algorithms in determining whether a surgical case represented one of the combinations of procedure and primary indication ranged from 0.70 (HD) to 0.92 (KOA). The specificity ranged from 0.94 (SpS) to 0.99 (HOA, KOA).

Conclusion

The electronic algorithm was able to identify all four procedure/primary indication combinations of interest with high specificity. Additionally, the sensitivity for the KOA cases was reasonably high. For HOA and the spine conditions, additional work is needed to improve the sensitivity of the algorithm to identify the primary indication for each case.

The prevalence of type 2 diabetes and associated risk factors with generalized osteoarthritis: a retrospective study using ICD codes for clinical data repository system

OBJECTIVE

Type 2 diabetes mellitus (T2DM) has been associated with osteoarthritis (OA). T2DM may be associated with generalized OA (GOA ≥ 3 joints) rather than localized OA (LOA < 3 joints). The purpose of this study was to examine the prevalence of T2DM in people with GOA compared with LOA and to investigate the association between demographic risk factors and chronic diseases (i.e., T2DM, hypertension, dyslipidemia, neuropathy, and body mass index (BMI)) with GOA compared with LOA.

METHODS

A retrospective review of data was performed, and patients with diagnostic codes for OA were selected. Identified codes included primary GOA, primary LOA, T2DM, hypertension, dyslipidemia, neuropathy, depression, anxiety, and sleep disorders. Information about BMI and medication list was obtained. Chi-square and logistic regression were performed to examine the prevalence and risk factors, respectively.

RESULTS

Data from 3855 patients (mean age = 66.43 ± 11.02, 60.9% women) included patients with GOA (n = 1265) and LOA (n = 2590). The prevalence of T2DM was significantly greater among patients with GOA (25.8%) compared with those with LOA (12.0%); however, the GOA group were older. Based on age groups, T2DM was prevalent in 17.8% of GOA compared with 7.2% in LOA for younger adults (aged 45-64 years) and was prevalent in 28.8% of GOA compared with 15.7% in LOA for older adults (aged 65 years or older). The odds ratio of GOA increased in people with chronic diseases compared with those without including T2DM (odds ratio (OR) 1.37, 95% confidence interval (CI) 1.05-1.78, p = 0.02), hypertension (OR 1.99, CI 1.63-2.43, p < 0.001), and dyslipidemia (OR 3.46, CI 2.86-4.19, p < 0.001), adjusting for covariates.

CONCLUSION

Higher prevalence of T2DM was found in people with GOA when compared with LOA across both age groups. T2DM, hypertension, and dyslipidemia were associated with GOA. Future research with longitudinal designs is needed to test the causality of this association.Key Points• The prevalence of type 2 diabetes in people with generalized osteoarthritis was almost double compared with localized osteoarthritis, although generalized osteoarthritis group were older.• Among people with osteoarthritis, the risk of generalized osteoarthritis is increased by 37% when people had type 2 diabetes, by 99% when people had hypertension, and by 246% when people had dyslipidemia.

Racial differences in skeletal fragility but not osteoarthritis among women and men with cerebral palsy

Background

Adults with cerebral palsy (CP) have increased risk for skeletal fragility and osteoarthritis. However, racial differences in these outcomes have not been examined. Such knowledge could improve patient-specific clinical care for the prevention and management of these conditions. The purpose of this study was to determine if there were racial differences in the prevalence of osteoporosis, all-cause fracture, and osteoarthritis among young and middle-aged adults with CP.

Methods

Data from 2016 were extracted from a random 20% sample of the Medicare fee-for-service database. International Classification of Diseases, Tenth Revision, Clinical Modification codes were used to identify 18-64 year olds with CP, as well as osteoporosis, all-cause fracture, osteoarthritis, and neurodevelopmental and noncommunicable disease comorbidities.

Results

Of the 16,488 adults with CP, 13,334 were White, 2477 were Black, and 677 were Hispanic. The age-standardized prevalence of osteoporosis (women: 12.9%, 9.0%, 8.3%, respectively; men: 9.2%, 4.8%, 7.9%, respectively) and fracture (women: 7.4%, 4.2%, 9.9%; men: 6.0%, 2.3%, 6.0%) was lower for Black adults with CP compared to White adults with CP (all p < 0.005). No racial differences were observed for age-standardized prevalence of osteoarthritis (women: 13.6%, 14.4%, 9.6%; men: 10.7%, 10.4%, 12.7%). The racial differences between Black and White adults with CP remained even after adjusting for age, U.S. region, neurodevelopmental comorbidities, and several noncommunicable diseases for osteoporosis (women: OR = 0.66, 99.5% CI = 0.48-0.91; men: OR = 0.51, 99.5% CI = 0.35-0.75) and fracture (women: OR = 0.57, 99.5% CI = 0.37-0.89; men: OR = 0.39, 99.5% CI = 0.23-0.68).

Conclusions

Study findings suggest racial differences in skeletal fragility among young and middle-aged adults with CP, with White women and men with CP having greater risk compared to Black women and men with CP. This study found no evidence of racial differences in the prevalence of osteoarthritis.

Green tea polyphenols attenuate LPS-induced inflammation through upregulating microRNA-9 in murine chondrogenic ATDC5 cells

BACKGROUND

Osteoarthritis (OA), a universal chronic musculoskeletal disorder, is closely related to inflammation. More effective drugs for improving OA outcome are definitely needed. Herein, we attempted to verify the protective role of green tea polyphenols (GTP) after treatment with murine in ATDC5 cells to reveal the regulatory mechanism.

METHODS

ATDC5 cells were stimulated with lipopolysaccharide (LPS) to mimic an inflammatory response during OA. Cell activity, apoptosis, levels of relative proteins, and prophlogistic factors were tested via a Cell Counting Kit-8 experiment, a flow cytometry experiment, western blot, and RT-qPCR (ELISA and Western blot), separately. miR-9 level was detected by RT-qPCR and altered via miR-9 mimic and inhibitor transfection. We finally studied MAPK and NF-κB pathways in GTP-related modulations using western blot.

RESULTS

LPS caused inflammatory cell damage in ATDC5 cells, showing decreased cell activity, enhanced apoptosis, and increased levels of pro-inflammatory cytokines. GTP pretreatments could significantly attenuate LPS-induced alterations. In addition, LPS-induced miR-9 upregulation was further positively regulated in ATDC5 cells. The effects of GTP pretreatments in LPS-caused ATDC5 cells were enhanced via miR-9 upregulation, whereas they were reduced via miR-9 suppression. Finally, we found that GTP pretreatments could suppress the MAPK and NF-κB pathways through miR-9 regulation.

CONCLUSION

GTP pretreatments attenuated LPS-induced inflammatory response accompanied by the suppression of the MAPK and NF-κB pathways via positively regulating miR-9 in ATDC5 cells.

Validation of algorithms to identify knee osteoarthritis patients in the claims database

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.

Prevalence and treatment of hip and knee osteoarthritis in people aged 60 years or older in Germany: an analysis based on health insurance claims data

Objective

Osteoarthritis (OA) is highly prevalent throughout the world, especially in the elderly population, and is strongly associated with patients’ frailty. However, little is known about the prevalence and treatment of OA in elderly patients in routine clinical care in Germany.

Materials and methods

As a part of Linking Patient-Reported Outcomes with CLAIms Data for Health Services Research in Rheumatology (PROCLAIR), a cross-sectional study using claims data from a large Germany statutory health insurance (BARMER) was conducted. We included people aged 60 years or older and assessed the prevalence of OA of the hip or knee, defined as having outpatient diagnoses (ICD: M16 or M17) in at least two quarters of 2014. The use of conservative treatment, including analgesics and physical therapy, and total joint replacement was studied. Analyses were stratified by age, sex, comorbidities, and level of care dependency defined by social law.

Results

A total of 595,754 patients (mean age: 74.9 years; 69.8% female) were diagnosed with OA (21.8%), with the highest prevalence in those between 80 and 89 years (31.0%) and in females compared to males (23.9% vs 18.3%). Prevalence decreased with increasing level of care dependency from 30.5% in patients with a low level (0/1) to 18.7% in the highest level of care dependency. A total of 63.4% of the patients with OA received analgesics, with higher use with increasing age. Physical therapy was prescribed to 43.1% of the patients, but use decreased with age. In all, 5.3% of the patients received total joint replacement in 2014.

Conclusion

The lower frequency of coded OA with increasing level of care dependency may reflect underdiagnosis, and patients with many other medical problems seem to be at risk for inadequate recognition and treatment of their OA.

Underrecording of osteoarthritis in United Kingdom primary care electronic health record data

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.

Population trends in the incidence and initial management of osteoarthritis: age-period-cohort analysis of the Clinical Practice Research Datalink, 1992-2013

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.

Needles in the haystack: Using open-text fields to identify persons with intellectual and developmental disabilities in administrative home care data

BACKGROUND

Use of administrative health data to study populations of interest is becoming more common. Identifying individuals with intellectual and developmental disabilities (IDD) in existing databases can be challenging due to inconsistent definitions and terminologies of IDD over time and across sectors, and the inability to rely on etiologies of IDD as they are frequently unknown.

AIMS

To identify diagnoses related to IDD in an administrative database and create a cohort of persons with IDD.

METHODS

Open-text diagnostic entries related to IDD were identified in an Ontario home care database (2003-2015) and coded as being either acceptable (e.g. Down syndrome) or ambiguous (e.g. intellectually challenged). The cognitive and functional skills of the resulting groups were compared using logistic regressions and standardized differences, and their age distributions were compared to that of the general home care population.

RESULTS

Just under 1% of the home care population had a diagnostic entry related to IDD. Ambiguous terms were most commonly used (61%), and this group tended to be older and less impaired than the group with more acceptable terms used to describe their IDD.

CONCLUSIONS

Open-text diagnostic variables in administrative health records can be used to identify and study individuals with IDD.

IMPLICATIONS

Future work is needed to educate assessors on the importance of using standard, accepted terminology when recording diagnoses related to IDD.