Duration of effectiveness of the COVID-19 vaccine in Japan: a retrospective cohort study using large-scale population-based registry data.

BACKGROUND: Most evidence of the waning of vaccine effectiveness is limited to a relatively short period after vaccination. METHODS: Data obtained from a linked database of healthcare administrative claims and vaccination records maintained by the municipality of a city in the Kanto region of Japan were used in this study. The study period extended from April 1, 2020, to December 31, 2022. The duration of the effectiveness of the COVID-19 vaccine was analyzed using a time-dependent piecewise Cox proportional hazard model using the age, sex and history of cancer, diabetes, chronic obstructive pulmonary disease, asthma, chronic kidney disease, and cardiovascular disease as covariates. RESULTS: Among the 174,757 eligible individuals, 14,416 (8.3%) were diagnosed with COVID-19 and 936 (0.54%) were hospitalized for COVID-19. Multivariate analysis based on the time-dependent Cox regression model with reference of non-vaccine group revealed a lower incidence of COVID-19 in the one-dose group (hazard ratio, 0.76 [95% confidence interval, 0.63-0.91]), two-dose (0.89 [0.85-0.93]), three-dose (0.80 [0.76-0.85]), four-dose (0.93 [0.88-1.00]), and five-dose (0.72 [0.62-0.84]) groups. A lower incidence of COVID-19-related hospitalization was observed in the one-dose group (0.42 [0.21-0.81]), two-dose (0.44 [0.35-0.56]), three-dose (0.38 [0.30-0.47]), four-dose (0.20 [0.14-0.28]), and five-dose (0.11 [0.014-0.86]) groups. Multivariable analyses based on the time-dependent piecewise Cox proportional hazard model with reference of non-vaccine group revealed significant preventive effects of the vaccine for 4 months for the incidence of COVID-19 and ≥ 6 months for hospitalization. CONCLUSIONS: Vaccine effectiveness showed gradual attenuation with time after vaccination; however, protective effects against the incidence of COVID-19 and hospitalization were maintained for 4 months and ≥ 6 months, respectively. These results may aid in formulating routine vaccination plans after the COVID-19 pandemic.

Inventory of real-world data sources in Japan: Annual survey conducted by the Japanese Society for Pharmacoepidemiology Task Force.

PURPOSE: The Database Task Force of the Japan Society for Pharmacoepidemiology began its annual surveys of databases available for clinico and pharmacoepidemiological studies in 2010. In this report, we summarize the characteristics of the databases available in Japan based on the results of our 2021 survey to illustrate the recent developments in the infrastructure for database research in Japan. METHODS: We included 20 major databases from the academia, government, or industry that were accessible to third parties. We used a web-based questionnaire to ask the database providers about their characteristics, such as their organization, data source(s), numbers of individuals enrolled, age distribution, code(s) used, and average follow-up periods. RESULTS: We received responses from all 20 databases approached: eight hospital-based databases, six insurer-based databases, four pharmacy-based databases, and two in the "other" category. Among them, 17 contained information from medical claims, pharmacy claims, and/or Diagnosis Procedure Combination data. Most insurer databases contained health check-up data that could be attached to the claims component. Some hospital-based databases had data from electronic medical records. Most insurer-based databases collected data from the insurers of working-age employees and therefore had limited coverage of older people. Most databases coded their medication data using the Japanese reimbursement codes, and many provided Anatomical Therapeutic Chemical Classification codes. CONCLUSIONS: The number of databases available for clinico and pharmacoepidemiological research and the proportion of the population they cover are increasing in Japan. The differences in their characteristics mean that the appropriate database must be selected for a particular study purpose.

Investigating the association between metabolic syndrome conditions and perinatal mental illness: a national administrative claims study.

BACKGROUND: Although the association between mental disorder and metabolic syndrome as a bidirectional relationship has been demonstrated, there is little knowledge of the cumulative and individual effect of these conditions on peripartum mental health. This study aims to investigate the association between metabolic syndrome conditions (MetS-C) and maternal mental illness in the perinatal period, while exploring time to incident mental disorder diagnosis in postpartum women. METHODS: This observational study identified perinatal women continuously enrolled 1 year prior to and 1 year post-delivery using Optum's de-identified Clinformatics® Data Mart Database (CDM) from 2014 to 2019 with MetS-C i.e. obesity, diabetes, high blood pressure, high triglycerides, or low HDL (1-year prior to delivery); perinatal comorbidities (9-months prior to and 4-month postpartum); and mental disorder (1-year prior to and 1-year post-delivery). Additionally, demographics and the number of days until mental disorder diagnosis were evaluated in this cohort. The analysis included descriptive statistics and multivariable logistic regression. MetS-C, perinatal comorbidities, and mental disorder were assessed using the International Classification of Diseases, Ninth, and Tenth Revision diagnosis codes. RESULTS: 372,895 deliveries met inclusion/exclusion criteria. The prevalence of MetS-C was 13.43%. Multivariable logistic regression revealed prenatal prevalence (1.64, CI = 1.59-1.70) and postpartum incident (1.30, CI = 1.25-1.34) diagnosis of mental health disorder were significantly higher in those with at least one MetS-C. Further, the adjusted odds of having postpartum incident mental illness were 1.51 times higher (CI = 1.39-1.66) in those with 2 MetS-C and 2.12 times higher (CI = 1.21-4.01) in those with 3 or more MetS-C. Young women (under the age of 18 years) were more likely to have an incident mental health diagnosis as opposed to other age groups. Lastly, time from hospital discharge to incident mental disorder diagnosis revealed an average of 157 days (SD = 103 days). CONCLUSION: The risk of mental disorder (both prenatal and incident) has a significant association with MetS-C. An incremental relationship between incident mental illness diagnosis and the number of MetS-C, a significant association with younger mothers along with a relatively long period of diagnosis mental illness highlights the need for more screening and treatment during pregnancy and postpartum.

Are breast cancer patients with suboptimal adherence to cardiovascular treatment more likely to discontinue adjuvant endocrine therapy? Competing risk survival analysis in a nationwide cohort of postmenopausal women.

BACKGROUND: High rates of discontinuation undermine the effectiveness of adjuvant endocrine therapy (AET) among hormone-receptive breast cancer patients. Patient prognosis also relies on the successful management of cardiovascular risk, which affects a high proportion of postmenopausal women. As with AET, adherence with cardiovascular drugs is suboptimal. We examined whether patient adherence with cardiovascular drugs was associated with the rate of AET discontinuation in a French nationwide claims database linked with hospitalisation data. METHODS: We identified postmenopausal women starting AET between 01/01/2016 and 31/12/2020 and taking at least two drugs for the primary prevention of cardiovascular disease (antihypertensive drugs, lipid-lowering drugs and platelet aggregation inhibitors) before AET initiation. Adherence was assessed for each drug class by computing the proportion of days covered. Women were categorised as fully adherent, partially adherent or fully non-adherent with their cardiovascular drug regimen based on whether they adhered with all, part or none of their drugs. AET discontinuation was defined as a 90-day gap in AET availability. Time to AET discontinuation according to levels of cardiovascular drug adherence was estimated using cumulative incidence curves, accounting for the competing risks of death and cancer recurrence. Multivariate cause-specific Cox regressions and Fine-and-Gray regressions were used to assess the relative hazards of AET discontinuation. RESULTS: In total, 32,075 women fit the inclusion criteria. Women who were fully adherent with their cardiovascular drugs had the lowest cumulative incidence of AET discontinuation at any point over the 5-year follow-up period. At 5 years, 40.2% of fully non-adherent women had discontinued AET compared with 33.5% of partially adherent women and 28.8% of fully adherent women. Both partial adherence and full non-adherence with cardiovascular drugs were predictors of AET discontinuation in the two models (cause-specific hazard ratios 1.16 [95% CI 1.10-1.22] and 1.49 [95% CI 1.39-1.58]; subdistribution hazard ratios 1.15 [95% CI 1.10-1.21] and 1.47 [95% CI 1.38-1.57]). CONCLUSION: Clinicians should be aware that patients who do not adhere with their entire cardiovascular drug regimen are also more likely to discontinue AET. This stresses the importance of integrated care, as suboptimal adherence with both treatment components poses a threat to achieving ideal patient outcomes.

Patterns of staging, treatment, and mortality in gastric, colorectal, and lung cancer among older adults with and without preexisting dementia: a Japanese multicentre cohort study.

BACKGROUND: Little is known about dementia's impact on patterns of diagnosis, treatment, and outcomes in cancer patients. This study aimed to elucidate the differences in cancer staging, treatment, and mortality in older cancer patients with and without preexisting dementia. METHODS: Using cancer registry data and administrative data from 30 hospitals in Japan, this multicentre retrospective cohort study examined patients aged 65-99 years who were newly diagnosed with gastric, colorectal, or lung cancer in 2014-2015. Dementia status (none, mild, and moderate-to-severe) at the time of cancer diagnosis was extracted from clinical summaries in administrative data, and set as the exposure of interest. We constructed multivariable logistic regression models to analyse cancer staging and treatment, and multivariable Cox regression models to analyse three-year survival. RESULTS: Among gastric (n = 6016), colorectal (n = 7257), and lung (n = 4502) cancer patients, 5.1%, 5.8%, and 6.4% had dementia, respectively. Patients with dementia were more likely to receive unstaged and advanced-stage cancer diagnoses; less likely to undergo tumour resection for stage I, II, and III gastric cancer and for stage I and II lung cancer; less likely to receive pharmacotherapy for stage III and IV lung cancer; more likely to undergo tumour resection for all-stage colorectal cancer; and more likely to die within three years of cancer diagnosis. The effects of moderate-to-severe dementia were greater than those of mild dementia, with the exception of tumour resection for colorectal cancer. CONCLUSION: Older cancer patients with preexisting dementia are less likely to receive standard cancer treatment and more likely to experience poorer outcomes. Clinicians should be aware of these risks, and would benefit from standardised guidelines to aid their decision-making in diagnosing and treating these patients.

The Medication Possession Ratio as a Predictor of Longitudinal HIV-1 Viral Suppression.

BACKGROUND: Antiretroviral adherence is essential to achieve viral suppression and limit HIV-related morbidity and mortality; however, antiretroviral adherence thresholds to achieve viral suppression in clinical practice have not been fully characterized using administrative claims data. OBJECTIVE: The purpose of this study was to assess the relationship between medication adherence and viral suppression among adult persons with HIV/AIDS (PWH) receiving antiretroviral therapy (ART) for ≥6 months. METHODS: This historical cohort, real-world investigation assessed maintenance of viral load suppression and viral load area-under-the-curve (vAUC) in PWH ≥18 years of age based on ART adherence. A marginal effects model was used to determine the predicted probabilities of final plasma HIV-1 RNA <50 copies/mL or vAUC <1,000 copy-days/mL according to the medication possession ratio (MPR), estimated using a Jackknife model variance estimator and a delta-method for marginal effects standard error. Tests for statistical significance used a Sidák method to correct for multiple comparisons. RESULTS: The mean MPR for ART was 86.7% (95% CI: 85.0%-88.4%) for the 372 PWH included in the study. The marginal effects analysis indicated that an MPR ≥82% was associated with a predicted probability of viral suppression <50 copies/mL (P < 0.05). Significant predicted probabilities for vAUC <1,000 copy-days/mL were observed with an MPR ≥90% (P < 0.05). CONCLUSION AND RELEVANCE: Medication possession ratio as a proxy for drug exposure was significantly and consistently associated with viral suppression using a longitudinal measure of HIV viremia. These findings can aid clinicians in the clinical management of PWH and inform future studies of adherence-viral suppression relationships with contemporary antiretroviral regimens.

High-dimensional propensity scores for empirical covariate selection in secondary database studies: Planning, implementation, and reporting.

Real-world evidence used for regulatory, payer, and clinical decision-making requires principled epidemiology in design and analysis, applying methods to minimize confounding given the lack of randomization. One technique to deal with potential confounding is propensity score (PS) analysis, which allows for the adjustment for measured preexposure covariates. Since its first publication in 2009, the high-dimensional propensity score (hdPS) method has emerged as an approach that extends traditional PS covariate selection to include large numbers of covariates that may reduce confounding bias in the analysis of healthcare databases. hdPS is an automated, data-driven analytic approach for covariate selection that empirically identifies preexposure variables and proxies to include in the PS model. This article provides an overview of the hdPS approach and recommendations on the planning, implementation, and reporting of hdPS used for causal treatment-effect estimations in longitudinal healthcare databases. We supply a checklist with key considerations as a supportive decision tool to aid investigators in the implementation and transparent reporting of hdPS techniques, and to aid decision-makers unfamiliar with hdPS in the understanding and interpretation of studies employing this approach. This article is endorsed by the International Society for Pharmacoepidemiology.

Prescription Trends for the Antidiabetic Agents Used to Treat Type 2 Diabetes Mellitus in Japan from 2012-2020: a Time-Series Analysis.

In April 2014, sodium-glucose cotransporter 2 inhibitor (SGLT-2i) was introduced in Japan. In May 2015, the prescription limitation for SGLT-2i was lifted. Subsequently, SGLT-2i was shown to reduce cardiovascular events in patients with type 2 diabetes mellitus (T2DM). SGLT-2i prescription is expected to increase and consequently affect the prescription trends for other antidiabetic agents. Therefore, we evaluated the trends for antidiabetic agent prescriptions in Japan from April 2012 to March 2020. In this study, a dynamic cohort consisting of patients with T2DM derived from the Japan Medical Data Center health insurance database and with at least one antidiabetic agent prescription was investigated. The prescription rates were calculated monthly (/1000 person-months) for each class of antidiabetic agent. The eligible cohort comprised 34333 patients. The prescription rate for dipeptidyl peptidase-4 inhibitor increased from 424.0 in April 2012 to 656.3 in May 2015, and slightly decreased to 635.4 in March 2020. The prescription rate for biguanide consistently increased from 347.2 in April 2012 to 500.1 in March 2020. The prescription rate for sulfonylurea consistently decreased from 393.8 in April 2012 to 172.5 in March 2020. The prescription rate for SGLT-2i consistently increased from 4.1 in April 2014 to 363.1 in March 2020. SGLT-2i prescription increased and may affect the prescription trends for dipeptidyl peptidase-4 inhibitor and sulfonylurea after May 2015, when the prescription limitation for SGLT-2i was lifted. Biguanide prescriptions increased regardless of the introduction of SGLT-2i. The treatment of T2DM in Japan is clearly changing, with a focus on SGLT-2i and biguanide.

Routine treatment pathways in a cohort of patients with major depression and suicidality in Italy: the ARIANNA observational study.

BACKGROUND: Major Depressive Disorder (MDD) with suicidal ideation, intent, or behavior is a psychiatric emergency with controversial care management. Our study describes the comprehensive treatment pathways of this population in Italian routine clinical practice. METHODS: ARIANNA [NCT04463108] is an observational prospective and retrospective cohort study involving both primary data collection and secondary data extract. A total of 137 adult MDD patients with suicidality were enrolled from 24 Italian care sites and followed for 90 days. Other than the description of treatment patterns, the impact of treatment on depressive symptoms and suicidality, the burden on the patient's and caregiver's quality of life, healthcare resource utilization and costs were described. RESULTS: Of the 133 eligible patients, 68.4% were female, and the median age was 47. Approximately half of the study population had a current severe major depressive episode. Treatment strategies at the time of active suicidal ideation with intent definition/confirmation (t0) were heterogeneous, increasing in complexity during observation. According to the MADRS, patients with remission at t0+1 day were 2.6%, with the mean total score decreasing from 37.2 at t0 to 32.3. LIMITATIONS: The study sites were not randomly selected. CONCLUSIONS: To the best of our knowledge, this is the first cohort study that prospectively describes the characteristics of patients with MDD and suicide risk in Italy, and how they are treated in clinical practice. The study confirms this is a difficult-to-treat population. In addition, a lack of rapid, effective treatment for reducing depressive symptoms and suicidality is observed.

Validation of algorithms to identify colorectal cancer patients from administrative claims data of a Japanese hospital.

BACKGROUND: Administrative claims data are a valuable source for clinical studies; however, the use of validated algorithms to identify patients is essential to minimize bias. We evaluated the validity of diagnostic coding algorithms for identifying patients with colorectal cancer from a hospital's administrative claims data. METHODS: This validation study used administrative claims data from a Japanese university hospital between April 2017 and March 2019. We developed diagnostic coding algorithms, basically based on the International Classification of Disease (ICD) 10th codes of C18-20 and Japanese disease codes, to identify patients with colorectal cancer. For random samples of patients identified using our algorithms, case ascertainment was performed using chart review as the gold standard. The positive predictive value (PPV) was calculated to evaluate the accuracy of the algorithms. RESULTS: Of 249 random samples of patients identified as having colorectal cancer by our coding algorithms, 215 were confirmed cases, yielding a PPV of 86.3% (95% confidence interval [CI], 81.5-90.1%). When the diagnostic codes were restricted to site-specific (right colon, left colon, transverse colon, or rectum) cancer codes, 94 of the 100 random samples were true cases of colorectal cancer. Consequently, the PPV increased to 94.0% (95% CI, 87.2-97.4%). CONCLUSION: Our diagnostic coding algorithms based on ICD-10 codes and Japanese disease codes were highly accurate in detecting patients with colorectal cancer from this hospital's claims data. The exclusive use of site-specific cancer codes further improved the PPV from 86.3 to 94.0%, suggesting their desirability in identifying these patients more precisely.

Association between early childhood lower respiratory tract infections and subsequent asthma.

OBJECTIVE: We examined the relationship between recurrent lower respiratory tract infections (LRTI) in young children and subsequent childhood asthma outcomes. METHODS: Retrospective cohort study using 2009-2017 Colorado All Payer Claims Database to assess 0- to 2-year-old children with visits due to LRTI and acute gastroenteritis (AGE). The primary exposure was number of LRTI visits prior to 2 years of age. Children with AGE served as the no LRTI comparator group. The primary outcome was incident asthma, defined by ICD-9 (490.XX) or ICD-10 (J45.9XX) codes, in the same children between 3 and 9 years of age. Multivariable accelerated failure time (AFT) models were used to estimate the effect of LRTI visits on median time to asthma diagnosis. Sensitivity analyses were performed using more conservative asthma diagnostic criteria and with hospitalized children only. RESULTS: Of 38,441 eligible subjects, 32,729 had ≥1 LRTI and 5,712 had AGE (no LRTI) between 0 and 2 years of age. Children with ≥3 LRTI visits had an 80% decrease in median time to asthma diagnosis relative to those with AGE visits only (time ratio [TR] 0.2; 95% CI 0.16, 0.24). Children with ≥3 LRTI hospitalizations had a 98% reduction in median time to asthma diagnosis relative to those with AGE hospitalizations only (TR 0.02; 95% CI 0.01, 0.07). History of atopy, wheezing, and family history of asthma documented prior to 2 years of age were also associated with earlier asthma diagnosis. CONCLUSIONS: Recurrent LRTIs, especially LRTI hospitalizations, before 2 years of age are associated with earlier diagnosis of pediatric asthma.

Assessment of coding-based frailty algorithms for long-term outcome prediction among older people in community settings: a cohort study from the Shizuoka Kokuho Database.

OBJECTIVES: To assess the applicability of Electronic Frailty Index (eFI) and Hospital Frailty Risk Score (HFRS) algorithms to Japanese administrative claims data and to evaluate their association with long-term outcomes. STUDY DESIGN AND SETTING: A cohort study using a regional government administrative healthcare and long-term care (LTC) claims database in Japan 2014-18. PARTICIPANTS: Plan enrollees aged ≥50 years. METHODS: We applied the two algorithms to the cohort and assessed the scores' distributions alongside enrollees' 4-year mortality and initiation of government-supported LTC. Using Cox regression and Fine-Gray models, we evaluated the association between frailty scores and outcomes as well as the models' discriminatory ability. RESULTS: Among 827,744 enrollees, 42.8% were categorised by eFI as fit, 31.2% mild, 17.5% moderate and 8.5% severe. For HFRS, 73.0% were low, 24.3% intermediate and 2.7% high risk; 35 of 36 predictors for eFI, and 92 of 109 codes originally used for HFRS were available in the Japanese system. Relative to the lowest frailty group, the highest frailty group had hazard ratios [95% confidence interval (CI)] of 2.09 (1.98-2.21) for mortality and 2.45 (2.28-2.63) for LTC for eFI; those for HFRS were 3.79 (3.56-4.03) and 3.31 (2.87-3.82), respectively. The area under the receiver operating characteristics curves for the unadjusted model at 48 months was 0.68 for death and 0.68 for LTC for eFI, and 0.73 and 0.70, respectively, for HFRS. CONCLUSIONS: The frailty algorithms were applicable to the Japanese system and could contribute to the identifications of enrollees at risk of long-term mortality or LTC use.

Impact of breakthrough trials on prescription trends of sodium-glucose cotransporter-2 inhibitors in Japan: An interrupted time-series analysis.

WHAT IS KNOWN AND OBJECTIVE: Sodium-glucose cotransporter-2 inhibitors (SGLT-2is) have been increasingly prescribed for the treatment of type 2 diabetes mellitus (T2DM). We aimed to investigate the impact of clinical trials presenting remarkable results on the prescription of SGLT-2is and the relationship between the impact and generalisability of the breakthrough trials on SGLT-2is. METHODS: This retrospective cohort study involved 32,949 patients with T2DM who were prescribed at least one antidiabetic agent in the Japan Medical Data Center health insurance database. Prescription rates of SGLT-2is were calculated monthly from April 2014 to March 2020. We evaluated the impact of the EMPA-REG OUTCOME study for an Asian subgroup on the prescription rate of empagliflozin and the impact of the CANVAS/CANVAS-R study on the prescription rate of canagliflozin. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were estimated using the quasi-Poisson regression model in the overall population, subgroup with a history of cardiovascular disease (high-risk group), and subgroup without a history and risk factors of cardiovascular disease (low-risk group). RESULTS AND DISCUSSION: The EMPA-REG OUTCOME study for the Asian subgroup led to increased prescription rates of empagliflozin 3 months after its publication in the overall population and high-risk group but not in low-risk group (IRR [95% CI]: 1.40 [1.17-1.66], 1.39 [1.05-1.84], and 1.00 [0.79-1.27], respectively). The increase in high-risk group may be appropriate because this study included patients with a history of cardiovascular disease only. The CANVAS/CANVAS-R study led to increased prescription rates of canagliflozin 3 months after its publication in the overall population, high-risk group, and low-risk group (IRR [95% CI]: 1.52 [1.06-2.19], 1.39 [1.06-1.83], and 1.81 [1.20-2.75], respectively). The increase in low-risk group may not be appropriate because this study did not include patients without a history or risk factors of cardiovascular disease. WHAT IS NEW AND CONCLUSION: The breakthrough trials increased prescription rates not only for patients to whom the trial results could be extrapolated but also for those in whom trial benefits were not certain. Our findings suggest that information about breakthrough trials may need to be provided along with data on trial result generalisability.

Identification of individuals benefiting from the kakaritsuke-yakuzaishi (family pharmacist) system in Japan: a retrospective cohort study using an employment-based health insurance claims database.

BACKGROUND: The kakaritsuke-yakuzaishi system (henceforth, the family pharmacist system) which provides more health services than those by general pharmaceutical practice, was implemented in Japan in April 2016. To distribute medical resources and medical care expenditures appropriately, identifying the possible major beneficiaries of this system is essential. By analyzing administrative claims data through this retrospective cohort study, we identified modifiers of the potential benefits of the system. Further, we integrated the identified modifiers into a scoring system that indicates the possible benefitting subpopulations. METHODS: We obtained data about individuals under 75 years old routinely using community pharmacies in Japan from the JMDC database. We classified the individuals as users or non-users. We used claims related to "choufukutouyaku-sougosayoutou-boushi-kasan (additional therapeutic duplication and drug interaction [TDDI] prevention fees)" filed between April 2018 and March 2020, which indicate that individuals' prescriptions were modified to adjust leftover drugs or to avoid TDDI as indicators of potential benefit. We estimated adjusted absolute risk differences and 95% confidence intervals for product terms using multiple generalized linear regression models. We included the factors whose 95% confidence interval lower limits did not reach 0 in the multiple logistic regression models for developing a scoring system. RESULTS: The eligible cohort included 162,340 individuals (1,214 users and 161,126 non-users). The leftover drugs adjustment significantly increased for individuals prescribed antidepressants. However, as only one modifier was identified, we did not develop a scoring system for the leftover drugs adjustment. For TDDI prevention, the following factors were included in the scoring system: being female, being prescribed ≥ 6 drug types, using ≥ 2 medical institutions, and being prescribed proton pump inhibitors, antibiotics, probiotics, or traditional Japanese herbal medicines. The developed scoring system for TDDI prevention scored "female" and "traditional Japanese herbal medicines prescription" factors higher than other factors. CONCLUSIONS: Individuals who are female or prescribed traditional Japanese herbal medicines, or antidepressants may benefit significantly from the family pharmacist system.

Patient characteristics, pain treatment patterns, and incidence of total joint replacement in a US population with osteoarthritis.

BACKGROUND: Currently available medications for chronic osteoarthritis pain are only moderately effective, and their use is limited in many patients because of serious adverse effects and contraindications. The primary surgical option for osteoarthritis is total joint replacement (TJR). The objectives of this study were to describe the treatment history of patients with osteoarthritis receiving prescription pain medications and/or intra-articular corticosteroid injections, and to estimate the incidence of TJR in these patients. METHODS: This retrospective, multicenter, cohort study utilized health plan administrative claims data (January 1, 2013, through December 31, 2019) of adult patients with osteoarthritis in the Innovation in Medical Evidence Development and Surveillance Distributed Database, a subset of the US FDA Sentinel Distributed Database. Patients were analyzed in two cohorts: those with prevalent use of "any pain medication" (prescription non-steroidal anti-inflammatory drugs [NSAIDs], opioids, and/or intra-articular corticosteroid injections) using only the first qualifying dispensing (index date); and those with prevalent use of "each specific pain medication class" with all qualifying treatment episodes identified. RESULTS: Among 1 992 670 prevalent users of "any pain medication", pain medications prescribed on the index date were NSAIDs (596 624 [29.9%] patients), opioids (1 161 806 [58.3%]), and intra-articular corticosteroids (323 459 [16.2%]). Further, 92 026 patients received multiple pain medications on the index date, including 71 632 (3.6%) receiving both NSAIDs and opioids. Altogether, 20.6% of patients used an NSAID at any time following an opioid index dispensing and 17.2% used an opioid following an NSAID index dispensing. The TJR incidence rates per 100 person-years (95% confidence interval [CI]) were 3.21 (95% CI: 3.20-3.23) in the "any pain medication" user cohort, and among those receiving "each specific pain medication class" were NSAIDs, 4.63 (95% CI: 4.58-4.67); opioids, 7.45 (95% CI: 7.40-7.49); and intra-articular corticosteroids, 8.05 (95% CI: 7.97-8.13). CONCLUSIONS: In patients treated with prescription medications for osteoarthritis pain, opioids were more commonly prescribed at index than NSAIDs and intra-articular corticosteroid injections. Of the pain medication classes examined, the incidence of TJR was highest in patients receiving intra-articular corticosteroids and lowest in patients receiving NSAIDs.

Scope-of-Practice for Nurse Practitioners and Adherence to Medications for Chronic Illness in Primary Care.

BACKGROUND: Nonadherence to medications is costly and improving adherence is difficult, requiring multifactorial solutions, including policy solutions. OBJECTIVE: The purpose of this study is to evaluate the effect of one policy strategy on medication adherence. Specifically, we examine the effect on adherence of expanding scope-of-practice regulations for nurse practitioners (NPs) to practice and prescribe without physician supervision. DESIGN: We conducted three difference-in-difference multivariable analyses of commercial insurance claims. PARTICIPANTS: Patients who filled at least two prescriptions in one of three chronic therapeutic medications: anti-diabetics (n = 514,255), renin angiotensin system antagonists (RASA) (n = 1,679,957), and anti-lipidemics (n = 1,613,692). MAIN MEASURES: Medication adherence was measured as the proportion of days covered (PDC). We used one continuous (PDC 0-1) and one binary outcome (PDC of > .8), the latter indicating good adherence. KEY RESULTS: Patients taking anti-diabetic medications had a 1.9 percentage point higher medication adherence rate (p < 0.05) and a 2.7 percentage point higher probability of good adherence (p < 0.001) in states that expanded NP scope-of-practice. Medication adherence for patients taking RASA was higher by 2.3 percentage points (p < 0.001) and 3.4 percentage points (p < 0.01) for both measures, respectively. Patients taking anti-lipidemics saw a smaller, but statistically insignificant, improvement in adherence. CONCLUSIONS: Results indicate that scope-of-practice regulations that allow NPs to practice and prescribe without physician oversight are associated with improved medication adherence. We postulate that the mechanism for this effect is increased access to health care services, which in turn increases access to prescriptions. Our results suggest that policies allowing NPs to maximally use their skills can be beneficial to patients.

Validation of a claims-based algorithm for identifying non-infectious pneumonitis in patients diagnosed with lung cancer.

PURPOSE: Non-infectious pneumonitis (NIP) is a common complication of treatments for lung cancer. We know of no existing validated algorithm for identifying NIP in claims databases, limiting our ability to understand the morbidity and mortality of this toxicity in real-world data. METHODS: Electronic health records (EHR), cancer registry, and administrative data from a National Cancer Institute-designated comprehensive cancer center were queried for patients diagnosed with lung cancer between 10/01/2015-12/31/2020. Health insurance claims were searched for ICD-10-CM codes that indicate an inpatient or outpatient diagnosis with possible NIP. A 20-code (Algorithm A) and 11-code (Algorithm B) algorithm were tested with and without requiring prescription with corticosteroids. Cases with a diagnosis of possible NIP in the 6 months before their first lung cancer diagnosis were excluded. The algorithms were validated by reviewing the EHR. The positive predictive value (PPV) for each algorithm was computed with 95% confidence intervals (CI). RESULTS: Seventy patients with lung cancer had a diagnosis code compatible with NIP: 36 (51.4%) inpatients and 34 (48.6%) outpatients. The PPV of Algorithm A was 77.1% (95% CI: 65.6-86.3). The PPV of Algorithm B was 86.9% (95% CI: 75.8-94.2). Requiring a documented prescription for a systemic corticosteroid improved the PPV of both Algorithm A and Algorithm B: 92.5% (95% CI: 79.6-98.4) and 100.0% (95% CI: 90.0-100.0), respectively. CONCLUSIONS: This study validated ICD-10-CM and prescription-claims-based definitions of NIP in lung cancer patients. All algorithms have at least reasonable performance. Enriching the algorithm with corticosteroid prescription records results in excellent performance.

Validating a novel algorithm to identify patients with autoimmune hepatitis in an administrative database.

PURPOSE: Population-level studies on the treatment practices and comparative effectiveness of therapies in autoimmune hepatitis (AIH) are lacking due to the absence of validated methods to identify patients with AIH in large databases, such as administrative claims or electronic health records. This study ascertained the performance of International Classification of Diseases (ICD) codes for AIH, and developed and validated a novel algorithm that reliably identifies patients with AIH in health administrative data and claims. METHODS: This was a cross-sectional study of patients with ≥1 inpatient or ≥2 outpatient ICD codes for AIH between 2008 and 2019 at a single health system. In a random sample of 250 patients, definite or probable AIH was determined using the Simplified AIH score, Revised AIH score or expert adjudication. The positive predictive value (PPV) was obtained. Variations of this base algorithm were evaluated using additional criteria to increase its performance. RESULTS: Of the 250 patients, 143 (57.2%) patients had sufficient records available for review. The PPV of the base algorithm was 77.6% (95% CI: 69.9-84.2%). Exclusion of patients with ≥1 ICD code for primary biliary cholangitis or primary sclerosing cholangitis yielded a PPV of 89.7% (95% CI: 82.8-94.6%). Further exclusion of patients with recent immune checkpoint inhibitor therapy increased the PPV to 92.9% (95% CI: 86.5-96.9%). CONCLUSIONS: The use of ICD codes for AIH alone are insufficient to reliably identify patients with AIH in health administrative data and claims. Our proposed algorithm that includes additional diagnostic and medication-related coding criteria demonstrates excellent performance.

Validation of claims-based algorithms to identify patients with psoriasis.

PURPOSE: Accurately identifying patients with psoriasis (PsO) is crucial for generating real-world evidence on PsO disease course and treatment utilization. METHODS: We developed nine claims-based algorithms for PsO using a combination of the International Classification of Diseases (ICD)-9 codes, specialist visit, and medication dispensing using Medicare linked to electronic health records data (2013-2014) in two healthcare provider networks in Boston, Massachusetts. We calculated positive predictive value (PPV) and 95% confidence interval (CI) for each algorithm using the treating physician's diagnosis of PsO via chart review as the gold standard. Among the confirmed PsO cases, we assessed their PsO disease activity. RESULTS: The nine claims-based algorithms identified 990 unique patient records. Of those, 918 (92.7%) with adequate information were reviewed. The PPV of the algorithms ranged from 65.1 to 82.9%. An algorithm defined as ≥1 ICD-9 diagnosis code for PsO and ≥1 prescription claim for topical vitamin D agents showed the highest PPV (82.9%). The PPV of the algorithm requiring ≥2 ICD-9 diagnosis codes and ≥1 prescription claim for PsO treatment excluding topical steroids was 81.1% but higher (82.5%) when ≥1 diagnosis was from a dermatologist. Among 411 PsO patients with adequate information on PsO disease activity in EHRs, 1.5-5.8% had no disease activity, 31.3-36.8% mild, and 26.9-35.1% moderate-to-severe across the algorithms. CONCLUSIONS: Claims-based algorithms based on a combination of PsO diagnosis codes and dispensing for PsO-specific treatments had a moderate-to-high PPV. These algorithms can serve as a useful tool to identify patients with PsO in future real-world data pharmacoepidemiologic studies.

Accuracy of diagnoses of inflammatory arthritis in administrative hospitalization databases.

PURPOSE: Studies using administrative hospitalization data often classify patients as having inflammatory arthritis based on diagnoses recorded at the hospitalization. We examined the agreement of these diagnoses with patients' prior medical histories. METHODS: We identified Medicare beneficiaries hospitalized in 2011 to 2015 for total hip arthroplasty (THA), total knee arthroplasty (TKA), acute myocardial infarction (AMI), or sepsis. We compared diagnoses of rheumatoid arthritis (RA) or ankylosing spondylitis (AS) at the index hospitalization to diagnoses over prior inpatient and outpatient claims. To assess the impact of potential misclassification, we compared hospital outcomes using the alternative methods of detecting beneficiaries with arthritis. Analyses were repeated using Medicaid data. RESULTS: Among 506 781 Medicare beneficiaries with THA, 18282 had RA and 571 had AS at the arthroplasty hospitalization, while 13 212 had RA and 1519 had AS based on claims history. Diagnoses at the hospitalization were highly specific (0.98-0.99), but sensitivities (0.65 for RA; 0.31 for AS) and positive predictive values (PPV) (0.47 for RA; 0.83 for AS) were lower. For TKA, AMI, and sepsis, specificities were 0.97 to 0.99, sensitivities 0.60 to 0.66 for RA and 0.18 to 0.22 for AS, and PPVs 0.43 to 0.47 for RA and 0.73 to 0.77 for AS. In Medicaid, sensitivities were 0.21 to 0.67 for RA and 0.07 to 0.49 for AS. Frequencies of some hospital outcomes differed when arthritis was classified by the index hospitalization or claims history. CONCLUSION: Diagnoses of RA and AS in hospitalization databases are highly specific but fail to identify large proportions of patients with these diagnoses.