Revisiting the washout period in the incident user study design: why 6-12 months may not be sufficient

New data-driven method to predict the therapeutic indication of redeemed prescriptions in secondary data sources: a case study on antiseizure medications users aged ≥65 identified in Danish registries

OBJECTIVES

We aimed to develop a new data-driven method to predict the therapeutic indication of redeemed prescriptions in secondary data sources using antiepileptic drugs among individuals aged ≥65 identified in Danish registries.

DESIGN

This was an incident new-user register-based cohort study using Danish registers.

SETTING

The study setting was Denmark and the study period was 2005-2017.

PARTICIPANTS

Participants included antiepileptic drug users in Denmark aged ≥65 with a confirmed diagnosis of epilepsy.

PRIMARY AND SECONDARY OUTCOME MEASURES

Sensitivity served as the performance measure of the algorithm.

RESULTS

The study population comprised 8609 incident new users of antiepileptic drugs. The sensitivity of the algorithm in correctly predicting the therapeutic indication of antiepileptic drugs in the study population was 65.3% (95% CI 64.4 to 66.2).

CONCLUSIONS

The algorithm demonstrated promising properties in terms of overall sensitivity for predicting the therapeutic indication of redeemed antiepileptic drugs by older individuals with epilepsy, correctly identifying the therapeutic indication for 6 out of 10 individuals using antiepileptic drugs for epilepsy.

New opioid prescription claims and their clinical indications: results from health administrative data in Quebec, Canada, over 14 years

OBJECTIVES

Describe new opioid prescription claims, their clinical indications and annual trends among opioid naïve adults covered by the Quebec's public drug insurance plan (QPDIP) for the fiscal years 2006/2007-2019/2020.

DESIGN AND SETTING

A retrospective observational study was conducted using data collected between 2006/2007 and 2019/2020 within the Quebec Integrated Chronic Disease Surveillance System, a linkage administrative data.

PARTICIPANTS

A cohort of opioid naïve adults and new opioid users was created for each study year (median number=2 263 380 and 168 183, respectively, over study period).

INTERVENTION

No.

MAIN OUTCOME MEASURE AND ANALYSES

A new opioid prescription was defined as the first opioid prescription claimed by an opioid naïve adult during a given fiscal year. The annual incidence proportion for each year was then calculated and standardised for age. A hierarchical algorithm was built to identify the most likely clinical indication for this prescription. Descriptive and trend analyses were performed.

RESULTS

There was a 1.7% decrease of age-standardised annual incidence proportion during the study period, from 7.5% in 2006/2007 to 5.8% in 2019/2020. The decrease was highest after 2016/2017, reaching 5.5% annual percentage change. Median daily dose and days' supply decreased from 27 to 25 morphine milligram equivalent/day and from 5 to 4 days between 2006/2007 and 2019/2020, respectively. Between 2006/2007 and 2019/2020, these prescriptions' most likely clinical indications increased for cancer pain from 34% to 48%, for surgical pain from 31% to 36% and for dental pain from 9% to 11%. Inversely, the musculoskeletal pain decreased from 13% to 2%. There was good consistency between the clinical indications identified by the algorithm and prescriber's specialty or user's characteristics.

CONCLUSIONS

New opioid prescription claims (incidence, dose and days' supply) decreased slightly over the last 14 years among QPDIP enrollees, especially after 2016/2017. Non-surgical and non-cancer pain became less common as their clinical indication.

Buprenorphine dispensing before and after the April 2021 X-Waiver exemptions: An interrupted time series analysis

BACKGROUND

Until the end of 2022, a special registration, known as the X-waiver, was required to prescribe buprenorphine in the US. Before its removal, US federal regulations trialed an X-waiver exemption, initiated on April 28, 2021, which permitted buprenorphine prescribing for up to 30 patients without additional training. We aimed to understand if these regulatory changes impacted buprenorphine dispensing.

METHODS

We conducted an interrupted time series analysis to understand changes in buprenorphine dispensing during the 26 weeks after the X-waiver exemption compared to the expected baseline trend established in the 26 weeks before using the IQVIA Longitudinal Prescription claims database. The primary outcome was number of new buprenorphine prescribers nationwide (defined as no prior buprenorphine prescription dispensed in the last 26 weeks). Segmented regression estimated relative changes in buprenorphine dispensing at 1, 13, and 26 weeks post-X-waiver change.

RESULTS

A total of 15,517,525 prescriptions filled for 1,328,172 patients (43.4 % female) ordered by 62,312 providers were included for analysis. At 26 weeks post-X-waiver change, there was no change in the number of new prescribers compared to the expected baseline trend (-2.7 % [95 % CI:-8.3,2.9]). The number of new (15.2 % [4.6,25.8]) and existing (1.7 % [0.9,2.4]) patients and patients per prescriber (4.3 % [3,5.6]) increased. Buprenorphine prescriptions reimbursed by Medicaid increased (7.5 % [6.6,8.4]) while commercial fills decreased (-3.4 % [-5.3,-1.5]).

CONCLUSIONS

The number of new prescribers did not increase six months post-X-waiver exemption while new patients continued to enter treatment at higher-than-expected rates. These findings suggest that additional interventions beyond the recent X-waiver removal may be needed to increase access to buprenorphine.

IncidencePrevalence: An R package to calculate population-level incidence rates and prevalence using the OMOP common data model

PURPOSE

Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM).

MATERIALS AND METHODS

We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases.

RESULTS

IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic.

CONCLUSION

For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner.

New cases of dementia are rising in elderly populations in Wales, UK

Dementia is one of the most common diseases in elderly populations, and older populations are one of the fastest growing groups globally. Consequently, the number of people developing and living with dementia is likely to grow. Using longitudinal medical records from Wales, UK between 1999 and 2018, diagnoses of overall dementia and common subtypes were combined with demographic data to assess numbers of new and existing cases per year. Data extraction resulted in 161,186 diagnoses from 116,645 individuals. Mean age at diagnosis of dementia increased over this period, resulting in fewer younger people with the disease. New cases of dementia have risen, as has the number of people living with dementia. Individuals with dementia are also living longer, even accounting for their older age. This may present a challenge for healthcare systems as the number of elderly people living with dementia is expected to continue to grow.

Examining Real-World Adherence to Nusinersen for the Treatment of Spinal Muscular Atrophy Using Two Large US Data Sources

INTRODUCTION

Spinal muscular atrophy (SMA) is a rare neuromuscular disease characterized by progressive muscular atrophy and weakness. Nusinersen was the first treatment approved for SMA. Per the US label, the nusinersen administration schedule consists of three loading doses at 14-day intervals, a fourth loading dose 30 days later, and maintenance doses every 4 months thereafter. Using two large US databases, we evaluated real-world adherence to nusinersen with its unique dosing schedule among generalizable populations of patients with SMA.

METHODS

Patients with SMA treated with nusinersen, likely to have complete information on date of treatment initiation, were identified in the Optum^® de-identified electronic health records (EHR) database (7/2017-9/2019), and in the Merative™ MarketScan^® Research Databases from commercial (1/2017-6/2020) and Medicaid claims (1/2017-12/2019). Baseline demographics, number of nusinersen administrations on time, and distribution of inter-dose intervals were summarized.

RESULTS

Totals of 67 and 291 patients were identified in the EHR and claims databases, respectively. Most nusinersen doses were received on time (93.9% EHR, 80.5% claims). Adherence was higher during the maintenance phase (90.6%) than the loading phase (71.1%) in the claims analysis, in contrast with the EHR analysis (95.5% and 92.6%, respectively), suggesting that not all loading doses of nusinersen may be accurately captured in claims. Inter-dose intervals captured in both databases aligned with the expected dosing schedule.

CONCLUSION

Most nusinersen doses were received on time, consistent with the recommended schedule. Our findings also highlight the importance of careful methodological approaches when using real-world administrative databases for evaluation of nusinersen treatment patterns.

Novel Algorithm for the Estimation of Cancer Incidence Using Claims Data in Japan: A Feasibility Study

PURPOSE

We developed algorithms to identify patients with newly diagnosed cancer from a Japanese claims database to identify the patients with newly diagnosed cancer of the sample population, which were compared with the nationwide cancer incidence in Japan to assess the validity of the novel algorithms.

METHODS

We developed two algorithms to identify patients with stomach, lung, colorectal, breast, and cervical cancers: diagnosis only (algorithm 1), and combining diagnosis, treatments, and medicines (algorithm 2). Patients with newly diagnosed cancer were identified from an anonymized commercial claims database (JMDC Claims Database) in 2017 with two inclusions/exclusion criteria: selecting all patients with cancer (extract 1) and excluding patients who had received cancer treatments in 2015 or 2016 (extract 2). We estimated the cancer incidence of the five cancer sites and compared it with the Japan National Cancer Registry incidence (calculated standardized incidence ratio with 95% CIs).

RESULTS

The number of patients with newly diagnosed cancer ranged from 219 to 17,840 by the sites, algorithms, and exclusion criteria. Standardized incidence ratios were significantly higher in the JMDC Claims Database than in the national registry data for extract 1 and algorithm 1, extract 1 and algorithm 2, and extract 2 and algorithm 1. In extract 2 and algorithm 2, colorectal cancer in male and stomach, lung, and cervical cancers in females showed similar cancer incidence in the JMDC and national registry data.

CONCLUSION

The novel algorithms are effective for extracting information about patients with cancer from claims data by using the combined information on diagnosis, procedures, and medicines (algorithm 2), with 2-year cancer-treatment history as an exclusion criterion (extract 2).

Incidence of major depressive disorder over time in patients with liver cirrhosis: A nationwide population-based study in Korea

There is yet to be a large-scale longitudinal study on the course of depression incidence within the duration of cirrhosis. The aim of this study is to analyze the incidence of depression from before to after diagnosis of cirrhosis over time. Incidence Rate (IR) was defined as the number of newly diagnosed patients with MDD divided by the sum of observation periods by using claims database in Korea. Incidence Rate Ratio (IRR) was defined as the IR in the specific interest period divided by the IR in the control period. The control period was defied as 1 to 2 years before diagnosis of cirrhosis. The IRs before and after cirrhosis diagnosis were 3.56 and 7.54 per 100 person-year, respectively. The IRR was 2.12 (95% confidence Interval: 2.06-2.18). The IRR of developing depression mildly increased before diagnosis of cirrhosis (-360 days to -181 days, IRR 1.14, p < 0.001; -180 days to -90 days, IRR 1.24, p < 0.001; -90 days to -31 days, IRR 1.56, p < 0.001) and rapidly increased immediately after diagnosis of cirrhosis (+30 days to +89 days, IRR 2.12, 95% confidence interval: 2.06-2.18, p < 0.001). The pattern of increasing depression immediately after the diagnosis of cirrhosis was observed equally in all sexes and ages. Thus, clinicians must pay close attention to screening for depression within the first three months of liver cirrhosis diagnosis.

Bidirectionality of antiseizure and antipsychotic treatment: A population-based study

PURPOSE

To study the prevalence and directionality of comorbid epilepsy and psychosis in Norway.

METHODS

The Norwegian Prescription Database (NorPD) provided individual-based information on all antiseizure medications (ASMs) and antipsychotic drugs (APDs) dispensed during 2004-2017. Subjects were ≥18 years of age at the end of the study period. Diagnosis-specific reimbursement codes from the 10th revision of the International Classification of Diseases/2nd edition of the International Classification of Primary Care (ICD-10/ICPC-2) combined with ATC codes were used as indicators of diagnosis. Subjects had collected ASMs for epilepsy or APDs for psychosis at least four times, at least once issued with an ICD-10 code from the specialist healthcare service. Directionality was analyzed in subjects receiving both treatments. To reduce prevalent comorbidity bias, we employed a four-year comorbidity-free period (2004-2007). The use of specific ASMs and APDs was analyzed.

RESULTS

A total of 31,289 subjects had collected an ASM for epilepsy at least four times, 28,889 an APD for psychosis. Both the prevalence of treatment for epilepsy and of treatment for psychosis was 0.8%. Further, 891 subjects had been treated for both conditions; 2.8% with epilepsy had been treated for psychosis, and 3.1% with psychosis had been treated for epilepsy. Among 558 subjects included in the analyses of directionality, 56% had collected the first APD before an ASM, whereas 41% had collected an ASM first. During the last year prior to comorbidity onset, levetiracetam, topiramate, or zonisamide had been used for epilepsy by approximately 40%, whereas olanzapine and quetiapine were most used in patients with psychosis, and clozapine in 13%.

CONCLUSION

The proportion of patients with prior antipsychotic treatment at onset of epilepsy is higher than previously acknowledged, as demonstrated in this nation-wide study. Apart from a shared neurobiological susceptibility, the bidirectionality of epilepsy and psychosis may be influenced by various environmental factors, including the interaction of pharmacodynamic effects. APDs may facilitate seizures; ASMs may induce psychiatric symptoms. In patients with combined treatment, these potential drug effects should receive ample attention, along with the psychosocial consequences of the disorders. A prudent multi-professional approach is required.

Pharmacoepidemiological Research on N-Nitrosodimethylamine-Contaminated Ranitidine Use and Long-Term Cancer Risk: A Population-Based Longitudinal Cohort Study

N-Nitrosodimethylamine (NDMA), a carcinogenic chemical, has recently been identified in ranitidine. We conducted a population-based study to explore ranitidine use and cancer emergence over time. Using the Taiwan National Health Insurance Research Database, a population-based cohort study was conducted. A total of 55,110 eligible patients who received ranitidine between January 2000 and December 2018 were enrolled in the treated cohort. We conducted a 1:1 propensity-score-matching procedure to match the ranitidine-treated group with the ranitidine-untreated group and famotidine controls for a longitudinal study. The association of ranitidine exposure with cancer outcomes was assessed. A multivariable Cox regression analysis that compared cancer risk with the untreated groups revealed that ranitidine increased the risk of liver (hazard ratio (HR): 1.22, 95% confidence interval (CI): 1.09-1.36, p < 0.001), lung (HR: 1.17, CI: 1.05-1.31, p = 0.005), gastric (HR: 1.26, CI: 1.05-1.52, p = 0.012), and pancreatic cancers (HR 1.35, CI: 1.03-1.77, p = 0.030). Our real-world observational study strongly supports the pathogenic role of NDMA contamination, given that long-term ranitidine use is associated with a higher likelihood of liver cancer development in ranitidine users compared with the control groups of non-ranitidine users treated with famotidine or proton-pump inhibitors.

Incidence in pharmacoepidemiology-Basic definitions and types of misclassification

The definition of a new case is a vital step in incidence studies in both epidemiology and pharmacoepidemiology, although with significant differences in methodology between the fields. We define and apply a framework for two different types of new cases of drug use, first-ever and recurrent, and show how the associated misclassifications related to length of run-in period can be expressed by the positive predictive value (PPV). In the study, we consider individual-level dispensations of statins 2006-2019 for 1,017,058 individuals with at least one dispensation in 2019 in Sweden. The incidence proportion for statins for both sexes of all ages in Sweden 2019 varied from 17.4/1000 with a run-in of 8 months, 9.45/1000 with 5 years and 8.4/1000 with 10 years. The PPV was 49% with 8 months and 89% for 5 years using 10 years as gold standard. We conclude that the interpretation of incidence and thus the selection of an appropriate run-in period, in pharmacoepidemiology, depends on whether first-ever use, recurrent treatment or both together (new cases) is the focus of the research question studied. At least five different misclassifications can be introduced depending on how incidence is defined.

Establishing a National Cardiovascular Disease Surveillance System in the United States Using Electronic Health Record Data: Key Strengths and Limitations

Cardiovascular disease surveillance involves quantifying the evolving population-level burden of cardiovascular outcomes and risk factors as a data-driven initial step followed by the implementation of interventional strategies designed to alleviate this burden in the target population. Despite widespread acknowledgement of its potential value, a national surveillance system dedicated specifically to cardiovascular disease does not currently exist in the United States. Routinely collected health care data such as from electronic health records (EHRs) are a possible means of achieving national surveillance. Accordingly, this article elaborates on some key strengths and limitations of using EHR data for establishing a national cardiovascular disease surveillance system. Key strengths discussed include the: (1) ubiquity of EHRs and consequent ability to create a more "national" surveillance system, (2) existence of a common data infrastructure underlying the health care enterprise with respect to data domains and the nomenclature by which these data are expressed, (3) longitudinal length and detail that define EHR data when individuals repeatedly patronize a health care organization, and (4) breadth of outcomes capable of being surveilled with EHRs. Key limitations discussed include the: (1) incomplete ascertainment of health information related to health care-seeking behavior and the disconnect of health care data generated at separate health care organizations, (2) suspect data quality resulting from the default information-gathering processes within the clinical enterprise, (3) questionable ability to surveil patients through EHRs in the absence of documented interactions, and (4) the challenge in interpreting temporal trends in health metrics, which can be obscured by changing clinical and administrative processes.

Exemption from informed consent: When it is possible in investigational product and drug trials?

One of the most important ethical step in conducting investigational product trials or drug trials is obtaining informed consent from the participants. Although consent from the participants regarding participation is of prime importance but is not always practical or feasible. There may be several instances where it is practically impossible to obtain informed consent, whereas in some cases, obtaining informed consent from the trial participants adversely affects the quality and validity of the study data. Obtaining informed consent is a highly complex and technical process if the participants are not literate or suffering from a terminal illness, Also in some instances obtaining informed consent regarding the washout of prior prescribed medicine which may affect the trial outcomes. Although many guidelines exist for obtaining proper informed consent while very scarce literature exists on the instances where it can be waived off. Therefore, this brief narrative review aims to provide insight into currently available knowledge about when to obtain informed consent during testing of investigational product trials and drug trials and other possible scenarios where it can be waived off considering the effects of the washout period.

New-user and prevalent-user designs and the definition of study time origin in pharmacoepidemiology: A review of reporting practices

BACKGROUND

Guidance reports for observational comparative effectiveness and drug safety research recommend implementing a new-user design whenever possible, since it reduces the risk of selection bias in exposure effect estimation compared to a prevalent-user design. The uptake of this guidance has not been studied extensively.

METHODS

We reviewed 89 observational effectiveness and safety cohort studies published in six pharmacoepidemiological journals in 2018 and 2019. We developed an extraction tool to assess how frequently new-user and prevalent-user designs were reported to be implemented. For studies that implemented a new-user design in both treatment arms, we extracted information about the extent to which the moment of meeting eligibility criteria, treatment initiation, and start of follow-up were reported to be aligned.

RESULTS

Of the 89 studies included, 40% reported implementing a new-user design for both the study exposure arm and the comparator arm, while 13% reported implementing a prevalent-user design in both arms. The moment of meeting eligibility criteria, treatment initiation, and start of follow-up were reported to be aligned in both treatment arms in 53% of studies that reported implementing a new-user design. We provided examples of studies that minimized the risk of introducing bias due to unclear definition of time origin in unexposed participants, immortal time, or a time lag.

CONCLUSIONS

Almost half of the included studies reported implementing a new-user design. Implications of misalignment of study design origin were difficult to assess because it would require explicit reporting of the target estimand in original studies. We recommend that the choice for a particular study time origin is explicitly motivated to enable assessment of validity of the study.

Estimating the disease burden of Korean type 2 diabetes mellitus patients considering its complications

BACKGROUND

The burden of diabetes is considerable not only globally but also nationally within Korea. The Global Burden of Disease study derived the disability-adjusted life years (DALYs) of diabetes depending on its complications as individual severity using prevalence-based approach from 2017. Conversely, the Korean National Burden of Disease study based on an incidence-based approach does not incorporate the severity of diseases. This study aimed to simulate incidence-based DALYs of type 2 diabetes mellitus (T2DM), given diabetic complications as disease severity using a Markov model.

METHODS

We developed a model with six Markov states, including incident and existing prevalent cases of diabetes and its complications and death. We assumed that diabetes and its complications would not be cured. The cycle length was one year, and the endpoint of the simulation was 100 years. A 5% discount rate was adopted in the analysis. Transition cases were counted by 5-year age groups above 30 years of age. Age- and sex-specific transition probabilities were calculated based on the incident rate.

RESULTS

The total DALY estimates of T2DM were 5,417 and 3,934 per 100,000 population in men and women, respectively. The years of life lost in men were relatively higher than those in women in most age groups except the 80-84 age group. The distribution of years lived with disability by gender and age group showed a bell shape, peaking in the 55-59 age group in men and 65-69 age group in women.

CONCLUSIONS

The burden of T2DM considering its complications was larger compared to the outcomes from previous studies, with more precise morbid duration using the Markov model.

Association Between Angiotensin II Receptor Blockers and the Risk of Lung Cancer Among Patients With Hypertension From the Korean National Health Insurance Service-National Health Screening Cohort

Objectives:

The objective of this study was to estimate the risk of lung cancer in relation to angiotensin II receptor blocker (ARB) use among patients with hypertension from the Korean National Health Insurance Service-National Health Screening Cohort.

Methods:

We conducted a retrospective cohort study of patients with hypertension who started to take antihypertensive medications and had a treatment period of at least 6 months. We calculated the weighted hazard ratios (HRs) and their 95% confidence intervals (CIs) of lung cancer associated with ARB use compared with calcium channel blocker (CCB) use using inverse probability treatment weighting.

Results:

Among a total of 60 469 subjects with a median follow-up time of 7.8 years, 476 cases of lung cancer were identified. ARB use had a protective effect on lung cancer compared with CCB use (HR, 0.75; 95% CI, 0.59 to 0.96). Consistent findings were found in analyses considering patients who changed or discontinued their medication (HR, 0.50; 95% CI, 0.32 to 0.77), as well as for women (HR, 0.56; 95% CI, 0.34 to 0.93), patients without chronic obstructive pulmonary disease (HR, 0.75; 95% CI, 0.56 to 1.00), never-smokers (HR, 0.64; 95% CI, 0.42 to 0.99), and non-drinkers (HR, 0.69; 95% CI, 0.49 to 0.97). In analyses with different comparison antihypertensive medications, the overall protective effects of ARBs on lung cancer risk remained consistent.

Conclusions:

The results of the present study suggest that ARBs could decrease the risk of lung cancer. More evidence is needed to establish the causal effect of ARBs on the incidence of lung cancer.

The effects of different lookback periods on the sociodemographic structure of the study population and on the estimation of incidence rates: analyses with German claims data

BACKGROUND

Defining incident cases has always been a challenging issue for researchers working with routine data. Lookback periods should enable researchers to identify and exclude recurrent cases and increase the accuracy of the incidence estimation. There are different recommendations for lookback periods depending on a disease entity of up to 10 years. Well-known drawbacks of the application of lookback periods are shorter remaining observation period in the dataset or smaller number of cases. The problem of selectivity of the remaining population after introducing lookback periods has not been considered in the literature until now.

METHODS

The analyses were performed with pseudonymized claims data of a German statutory health insurance fund with annual case numbers of about 2,1 million insured persons. Proportions of study population excluded due to the application of lookback periods are shown according to age, occupational qualification and income. Myocardial infarction and stroke were used to demonstrate changes in incidence rates after applying lookback periods of up to 5 years.

RESULTS

Younger individuals show substantial dropouts after the application of lookback periods. Furthermore, there are selectivities regarding occupational qualification and income, which cannot be handled by age standardization. Due to selective dropouts of younger individuals, crude incidence rates of myocardial infarction and stroke increase after applying lookback periods. Depending on the income group, age-standardized incidence rates changed differentially, leading to a decrease and possible underestimation of the social gradient after applying lookback periods.

CONCLUSIONS

Selectivity analyses regarding age and sociodemographic structure should be performed for the study population after applying lookback periods since the selectivity can affect the outcome especially in health care research. The selectivity effects might occur not only in claims data of one health insurance fund, but also in other longitudinal data with left- or right-censoring not covering the whole population. The effects may also apply to health care systems with a mix of public and private health insurance. A trade-off has to be considered between selectivity effects and eliminating recurrent events for more accuracy in the definition of incidence.

Rethinking morbidity compression

Studies of morbidity compression routinely report the average number of years spent in an unhealthy state but do not report variation in age at morbidity onset. Variation was highlighted by Fries (1980) as crucial for identifying disease postponement. Using incidence of first hospitalization after age 60, as one working example, we estimate variation in morbidity onset over a 27-year period in Denmark. Annual estimates of first hospitalization and the population at risk for 1987 to 2014 were identified using population-based registers. Sex-specific life tables were constructed, and the average age, the threshold age, and the coefficient of variation in age at first hospitalization were calculated. On average, first admissions lasting two or more days shifted towards older ages between 1987 and 2014. The average age at hospitalization increased from 67.8 years (95% CI 67.7-67.9) to 69.5 years (95% CI 69.4-69.6) in men, and 69.1 (95% CI 69.1-69.2) to 70.5 years (95% CI 70.4-70.6) in women. Variation in age at first admission increased slightly as the coefficient of variation increased from 9.1 (95% CI 9.0-9.1) to 9.9% (95% CI 9.8-10.0) among men, and from 10.3% (95% CI 10.2-10.4) to 10.6% (95% CI 10.5-10.6) among women. Our results suggest populations are ageing with better health today than in the past, but experience increasing diversity in healthy ageing. Pensions, social care, and health services will have to adapt to increasingly heterogeneous ageing populations, a phenomenon that average measures of morbidity do not capture.

Measuring prevalence and incidence of chronic conditions in claims and electronic health record databases

Background

Health care databases are natural sources for estimating prevalence and incidence of chronic conditions, but substantial variation in estimates limits their interpretability and utility. We evaluated the effects of design choices when estimating prevalence and incidence in claims and electronic health record databases.

Methods

Prevalence and incidence for five chronic diseases at increasing levels of expected frequencies, from cystic fibrosis to COPD, were estimated in the Clinical Practice Research Datalink (CPRD) and MarketScan databases from 2011 to 2014. Estimates were compared using different definitions of lookback time and contributed person-time.

Results

Variation in lookback time substantially affected estimates. In 2014, for CPRD, use of an all-time vs a 1-year lookback window resulted in 4.3–8.3 times higher prevalence (depending on disease), reducing incidence by 1.9–3.3 times. All-time lookback resulted in strong temporal trends. COPD prevalence between 2011 and 2014 in MarketScan increased by 25% with an all-time lookback but stayed relatively constant with a 1-year lookback. Varying observability did not substantially affect estimates.

Conclusion

This framework draws attention to the underrecognized potential for widely varying incidence and prevalence estimates, with implications for care planning and drug development. Though prevalence and incidence are seemingly straightforward concepts, careful consideration of methodology is required to obtain meaningful estimates from health care databases.

Estimating Adherence Based on Prescription or Dispensation Information: Impact on Thresholds and Outcomes. A Real-World Study With Atrial Fibrillation Patients Treated With Oral Anticoagulants in Spain

Objective: To estimate drug exposure, Proportion of Days Covered (PDC) and percentage of patients with PDC ≥ 80% from a cohort of atrial fibrillation patients initiating oral anticoagulant (OAC) treatment. We employed three different approaches to estimate PDC, using either data from prescription and dispensing (PD cohort) or two common designs based on dispensing information only, requiring at least one (D1) or at least two (D2) refills for inclusion in the cohorts. Finally, we assessed the impact of adherence on health outcomes according to each method. Methods: Population-based retrospective cohort of all patients with Non Valvular Atrial Fibrillation (NVAF), who were newly prescribed acenocoumarol, apixaban, dabigatran or rivaroxaban from November 2011 to December 2015 in the region of Valencia (Spain). Patients were followed for 12 months to assess adherence using three different approaches (PD, D1 and D2 cohorts). To analyze the relationship between adherence (PDC ≥ 80) defined according to each method of calculation and health outcomes (death for any cause, stroke or bleeding) Cox regression models were used. For the identification of clinical events patients were followed from the end of the adherence assessment period to the end of the available follow-up period. Results: PD cohort included all patients with an OAC prescription (n = 38,802), D1 cohort excluded fully non-adherent patients (n = 265) and D2 cohort also excluded patients without two refills separated by 180 days (n = 2,614). PDC ≥ 80% ranged from 94% in the PD cohort to 75% in the D1 cohort. Drug exposure among adherent (PDC ≥ 80%) and non-adherent (PDC < 80%) patients was different between cohorts. In adjusted analysis, high adherence was associated with a reduced risk of death [Hazard Ratio (HR): from 0.82 to 0.86] and (except in the PD cohort) the risk for ischemic stroke (HR: from 0.61 to 0.64) without increasing the risk of bleeding. Conclusion: Common approaches to assess adherence using measures based on days' supply exclude groups of non-adherent patients and, also, misattribute periods of doctors' discontinuation to patient non-adherence, misestimating adherence overall. Physician-initiated discontinuation is a major contributor to reduced OAC exposure. When using the PDC80 threshold, very different groups of patients may be classified as adherent or non-adherent depending on the method used for the calculation of days' supply measures. High adherence and high exposure to OAC treatment in NVAF patients is associated with better health outcomes.

Timing of physical therapy consultation on 1-year healthcare utilization and costs in patients seeking care for neck pain: a retrospective cohort

BACKGROUND

Patients seek care from physical therapists for neck pain but it is unclear what the association of the timing of physical therapy (PT) consultation is on 1-year healthcare utilization and costs. The purpose of this study was to compare the 1-year healthcare utilization and costs between three PT timing groups: patients who consulted a physical therapist (PT) for neck pain within 14 days (early PT consultation), between 15 and 90 days (delayed PT consultation) or between 91 and 364 days (late PT consultation).

METHODS

A retrospective cohort of 308 patients (69.2% female, ages 48.7[±14.5] years) were categorized into PT timing groups. Descriptive statistics were calculated for each group. In adjusted regression models, 1-year healthcare utilization of injections, imaging, opioids and costs were compared between groups.

RESULTS

Compared to early PT consultation, the odds of receiving an opioid prescription (aOR = 2.79, 95%CI: 1.35-5.79), spinal injection (aOR = 4.36, 95%CI:2.26-8.45), undergoing an MRI (aOR = 4.68, 95%CI:2.25-9.74), X-ray (aOR = 2.97, 95%CI:1.61-5.47) or CT scan (aOR = 3.36, 95%CI: 1.14-9.97) were increased in patients in the late PT consultation group. Similar increases in risk were found in the delayed group (except CT and Opioids). Compared to the early PT consultation group, mean costs were $2172 ($557, $3786) higher in the late PT contact group and $1063 (95%CI: $ 138 - $1988) higher in the delayed PT consultation group.

DISCUSSION

There was an association with the timing of physical therapy consultation on healthcare utilization and costs, where later consultation was associated with increases costs and healthcare utilization. This study examined the association of timing of physical therapy consultation on costs and healthcare utilization, but not the association of increased access to physical therapy consultation. Therefore, the findings warrant further investigation to explore the effects of increased access to physical therapy consultation on healthcare utilization and costs in a prospective study.

Influence of Initial Provider on Health Care Utilization in Patients Seeking Care for Neck Pain

Objective

To examine patients seeking care for neck pain to determine associations between the type of provider initially consulted and 1-year health care utilization.

Patients and Methods

A retrospective cohort of 1702 patients (69.25% women, average age, 45.32±14.75 years) with a new episode of neck pain who consulted a primary care provider, physical therapist (PT), chiropractor (DC), or specialist from January 1, 2012, to June 30, 2013, was analyzed. Descriptive statistics were calculated for each group, and subsequent 1-year health care utilization of imaging, opioids, surgery, and injections was compared between groups.

Results

Compared with initial primary care provider consultation, patients consulting with a DC or PT had decreased odds of being prescribed opioids within 1 year from the index visit (DC: adjusted odds ratio [aOR], 0.54; 95% CI, 0.39-0.76; PT: aOR, 0.59; 95% CI, 0.44-0.78). Patients consulting with a DC additionally demonstrated decreased odds of advanced imaging (aOR, 0.43; 95% CI, 0.15-0.76) and injections (aOR, 0.34; 95% CI, 0.19-0.56). Initiating care with a specialist or PT increased the odds of advanced imaging (specialist: aOR, 2.96; 95% CI, 2.01-4.38; PT: aOR, 1.57; 95% CI, 1.01-2.46), but only initiating care with a specialist increased the odds of injections (aOR, 3.21; 95% CI, 2.31-4.47).

Conclusion

Initially consulting with a nonpharmacological provider may decrease opioid exposure (PT and DC) over the next year and also decrease advanced imaging and injections (DC only). These data provide an initial indication of how following recent practice guidelines may influence health care utilization in patients with a new episode of neck pain.

The impact of the lookback period and definition of confirmatory events on the identification of incident cancer cases in administrative data

Background

This cohort study examined the impact of the lengths of lookback and confirmation periods as well as the definition of confirmatory events on the number of incident cancer cases identified and age-standardized cumulative incidences (ACI) estimated in administrative data using German cancer registry data as a benchmark.

Methods

ACI per 100,000 insured persons for breast, prostate and colorectal cancer were estimated using BARMER Statutory Health Insurance claims data. Incident cancer cases were defined as having an in- or outpatient diagnosis in 2013, no diagnosis in a lookback period of 1 year and a second diagnosis (or death) in a confirmation period of 1 quarter. We varied lookback periods from 1 to 7 years, confirmation periods from 1 to 4 quarters as well as the definition of confirmatory events and compared ACI estimates to cancer registry data.

Results

ACI were higher for breast (138.7) and prostate (103.6) but lower for colorectal cancer (42.1) when compared to cancer registries (119.3, 98.0 and 45.5, respectively). Extending the lookback period to 7 years reduced ACI to 129.0, 95.1 and 38.3. An extended confirmation period of 4 quarters increased ACI to 151.3, 114.9 and 46.8. Including breast and colorectal surgeries as a confirmatory event reduced ACI to 114.9 and 37.1, respectively.

Conclusions

The choice of lookback and confirmation periods and the definition of confirmatory events have considerable impact on the number of incident cancer cases identified and ACI estimated. Researchers need to be aware of potential misclassification when identifying incident cancer cases in administrative data. Further validation studies as well as studies using administrative data to estimate cancer incidences should consider several choices of the lookback and confirmation periods and the definition of confirmatory events to show how these parameters impact the validity and robustness of their results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-017-0407-4) contains supplementary material, which is available to authorized users.

Minimizing Attrition for Multisite Emergency Care Research

Loss to follow-up of enrolled patients (a.k.a. attrition) is a major threat to study validity and power. Minimizing attrition can be challenging even under ideal research conditions, including the presence of adequate funding, experienced study personnel, and a refined research infrastructure. Emergency care research is shifting toward enrollment through multisite networks, but there have been limited descriptions of approaches to minimize attrition for these multicenter emergency care studies. This concept paper describes a stepwise approach to minimize attrition, using a case example of a multisite emergency department prospective cohort of over 3,000 patients that has achieved a 30-day direct phone follow-up attrition rate of <3%. The seven areas of approach to minimize attrition in this study focused on patient selection, baseline contact data collection, patient incentives, patient tracking, central phone banks, local enrollment site assistance, and continuous performance monitoring. Appropriate study design, including consideration of these methods to reduce attrition, will be time well spent and may improve study validity.

Trajectories of Diabetes Medication Adherence and Hospitalization Risk: A Retrospective Cohort Study in a Large State Medicaid Program

BACKGROUND

Numerous interventions are available to boost medication adherence, but the targeting of these interventions often relies on crude measures of poor adherence. Group-based trajectory models identify individuals with similar longitudinal prescription filling patterns. Identifying distinct adherence trajectories may be more useful for targeting interventions, although the association between adherence trajectories and clinical outcomes is unknown.

OBJECTIVE

To examine the association between adherence trajectories for oral hypoglycemics and subsequent hospitalizations among diabetes patients.

DESIGN

Retrospective cohort study.

PATIENTS

A total of 16,256 Pennsylvania Medicaid enrollees, non-dually eligible for Medicare, initiating oral hypoglycemics between 2007 and 2009.

MAIN MEASURES

We used group-based trajectory models to identify trajectories of oral hypoglycemics in the 12 months post-treatment initiation, using monthly proportion of days covered (PDC) as the adherence measure. Multivariable Cox proportional hazard models were used to examine the association between trajectories and time to first diabetes-related hospitalization/emergency department (ED) visits in the following year. We used the C-index to compare prediction performance between adherence trajectories and dichotomous cutpoints (annual PDC <80 vs. ≥80 %).

RESULTS

The mean annual PDC was 0.58 (SD 0.32). Seven trajectories were identified: perfect adherers (9 % of the cohort), nearly perfect adherers (31.4 %), moderate adherers (21.0 %), low adherers (11.0 %), late discontinuers (6.8 %), early discontinuers (9.7 %), and non-adherers with only one fill (11.1 %). Compared to perfect adherers, trajectories of moderate adherers (HR = 1.48, 95 % CI 1.25, 1.75), low adherers (HR = 1.51, 95 % CI 1.25, 1.83), and non-adherers with only one fill (HR = 1.35, 95 % CI 1.09, 1.67) had greater risk of diabetes-related hospitalizations/ED visits. Predictive accuracy was improved using trajectories compared to dichotomized cutpoints (C-index = 0.714 vs. 0.652).

CONCLUSIONS

Oral hypoglycemic treatment trajectories were highly variable in this large Medicaid cohort. Low and moderate adherers and those filling only one prescription had a modestly higher risk of hospitalizations/ED visits compared to perfect adherers. Trajectory models may be valuable in identifying specific non-adherence patterns for targeting interventions.

Cohort restriction based on prior enrollment: Examining potential biases in estimating cancer and mortality risk

Electronic health records and administrative databases provide rich, longitudinal data for health-related research. These data cover large, diverse populations creating excellent research opportunities, but have limitations. In particular, information is available only for individuals who are enrolled in a particular health system; thus, studies often exclude individual's with short enrollment history. Such cohort restriction may cause selection bias in absolute risk estimates for the full enrollee population. We use hazard ratios (HRs) to estimate the association between length of prior enrollment and cancer and all-cause mortality risk. HRs different from one indicate restricted cohorts would produce biased risk estimates for the full enrollee population. Our study sample included 170,708 enrollees of a Western Washington healthcare delivery system. Unadjusted models found individuals with 10 or more years of prior enrollment had higher risk of cancer and death compared to those with less than 5 years prior enrollment (HRs ranged from 1.29 - 3.01). Age- and sex-adjusted models accounted for much of this difference (HRs: 0.93 - 1.24). Models adjusting for additional covariates had similar results (HRs: 0.91 - 1.14). After evaluating potential selection bias, we conclude that, in this setting, age- and sex-standardizing risk estimates can remove most of the bias due to lengthy, prior-enrollment cohort restrictions. Before generalizing estimates based on a selected sample of patients meeting prior enrollment criteria, researchers should assess the potential for selection bias.

Association between trajectories of buprenorphine treatment and emergency department and in-patient utilization

BACKGROUND AND AIMS

Uncertainty about optimal treatment duration for buprenorphine opioid agonist therapy may lead to substantial variation in provider and payer decision-making regarding treatment course. We aimed to identify distinct trajectories of buprenorphine use and examine outcomes associated with these trajectories to guide health system interventions regarding treatment length.

DESIGN

Retrospective cohort study.

SETTING

US Pennsylvania Medicaid.

PATIENTS

A total of 10 945 enrollees aged 18-64 years initiating buprenorphine treatment between 2007 and 2012.

MEASUREMENTS

Group-based trajectory models were used to identify trajectories based on monthly proportion of days covered with buprenorphine in the 12 months post-treatment initiation. We used separate multivariable Cox proportional hazard models to examine associations between trajectories and time to first all-cause hospitalization and emergency department (ED) visit within 12 months after the first-year treatment.

FINDINGS

Six trajectories [Bayesian information criterion (BIC) = -86 246.70] were identified: 24.9% discontinued buprenorphine < 3 months, 18.7% discontinued between 3 and 5 months, 12.4% discontinued between 5 and 8 months, 13.3% discontinued > 8 months, 9.5% refilled intermittently and 21.2% refilled persistently for 12 months. Persistent refill trajectories were associated with an 18% lower risk of all-cause hospitalizations [hazard ratio (HR) = 0.82, 95% confidence interval (CI) = 0.70-0.95] and 14% lower risk of ED visits (HR = 0.86, 95% CI = 0.78-0.95) in the subsequent year, compared with those discontinuing between 3 and 5 months.

CONCLUSIONS

Six distinct buprenorphine treatment trajectories were identified in this population-based low-income Medicaid cohort in Pennsylvania, USA. There appears to be an association between persistent use of buprenorphine for 12 months and lower risk of all-cause hospitalizations/emergency department visits.