Positive predictive value of ICD-10 codes for acute myocardial infarction in Japan: a validation study at a single center

Additive association of blood pressure and short stature with stroke incidence in 450,000 Japanese adults: the Shizuoka study

Short stature was suggested to be a risk factor for cardiovascular events. Because short stature increases central blood pressure, this study aimed to investigate a longitudinal association between short stature, blood pressure, and incidence of cardiovascular disease by the analysis of insurance-based real-world dataset. We analyzed data from 463,844 adults aged 40 or older with a mean age of 66.7 enrolled in National Health Insurance, excluding individuals who experienced a stroke or myocardial infarction, or required long-term care. Data from annual health checkups were used to obtain baseline clinical information. Comorbidities and incidences of stroke and myocardial infarction were obtained from the insurance data. During a 5.5-year follow-up period, we observed 11,027 cases of stroke. Adults of a short stature exhibited a higher incidence rate in both men (≤155 cm: 99.7, >175 cm: 24.4) and women (≤140 cm: 85.9, >160 cm: 13.7). Although those in the short stature group had higher blood pressure, and often took antihypertensive drugs, the inverse association between height and stroke incidence was independent of these factors (hazard ratio for 5 cm shorter in height; men: 1.06 [1.03-1.09], women: 1.11 [1.06-1.13]). Short stature and blood pressure showed additive association with stoke incidence (log-rank p < 0.001). No significant association was observed with myocardial infarction (men: 1.01 [0.95-1.06], women: 1.06 [0.98-1.14]). In a longitudinal analysis of a large general Japanese population, short stature was linked to an increased risk of stroke in both genders in any blood pressure range.

Risk of Major Adverse Cardiovascular Events After Emergency Department Visits for Hypertensive Urgency

BACKGROUND

Chronic hypertension is an established long-term risk factor for major adverse cardiovascular events (MACEs). However, little is known about short-term MACE risk after hypertensive urgency, defined as an episode of acute severe hypertension without evidence of target-organ damage. We sought to evaluate the short-term risk of MACE after an emergency department (ED) visit for hypertensive urgency resulting in discharge to home.

METHODS

We performed a case-crossover study using deidentified administrative claims data. Our case periods were 1-week intervals from 0 to 12 weeks before hospitalization for MACE. We compared ED visits for hypertensive urgency during these case periods versus equivalent control periods 1 year earlier. Hypertensive urgency and MACE components were all ascertained using previously validated International Classification of Diseases, Tenth Revision Clinical Modification codes. We used McNemar test for matched data to calculate risk ratios.

RESULTS

Among 2 225 722 patients with MACE, 1 893 401 (85.1%) had a prior diagnosis of hypertension. There were 4644 (0.2%) patients who had at least 1 ED visit for hypertensive urgency during the 12 weeks preceding their MACE hospitalization. An ED visit for hypertensive urgency was significantly more common in the first week before MACE compared with the same chronological week 1 year earlier (risk ratio, 3.5 [95% CI, 2.9-4.2]). The association between hypertensive urgency and MACE decreased in magnitude with increasing temporal distance from MACE and was no longer significant by 11 weeks before MACE (risk ratio, 1.2 [95% CI, 0.99-1.6]).

CONCLUSIONS

ED visits for hypertensive urgency were associated with a substantially increased short-term risk of subsequent MACE.

Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET®) in Japan

BACKGROUND

The Medical Information Database Network (MID-NET®) in Japan is a vast repository providing an essential pharmacovigilance tool. Gastrointestinal perforation (GIP) is a critical adverse drug event, yet no well-established GIP identification algorithm exists in MID-NET®.

METHODS

This study evaluated 12 identification algorithms by combining ICD-10 codes with GIP therapeutic procedures. Two sites contributed 200 inpatients with GIP-suggestive ICD-10 codes (100 inpatients each), while a third site contributed 165 inpatients with GIP-suggestive ICD-10 codes and antimicrobial prescriptions. The positive predictive values (PPVs) of the algorithms were determined, and the relative sensitivity (rSn) among the 165 inpatients at the third institution was evaluated.

RESULTS

A trade-off between PPV and rSn was observed. For instance, ICD-10 code-based definitions yielded PPVs of 59.5%, whereas ICD-10 codes with CT scan and antimicrobial information gave PPVs of 56.0% and an rSn of 97.0%, and ICD-10 codes with CT scan and antimicrobial information as well as three types of operation codes produced PPVs of 84.2% and an rSn of 24.2%. The same algorithms produced statistically significant differences in PPVs among the three institutions. Combining diagnostic and procedure codes improved the PPVs. The algorithm combining ICD-10 codes with CT scan and antimicrobial information and 80 different operation codes offered the optimal balance (PPV: 61.6%, rSn: 92.4%).

CONCLUSION

This study developed valuable GIP identification algorithms for MID-NET®, revealing the trade-offs between accuracy and sensitivity. The algorithm with the most reasonable balance was determined. These findings enhance pharmacovigilance efforts and facilitate further research to optimize adverse event detection algorithms.

Trends and Outcomes of Acute Myocardial Infarction During the Early COVID-19 Pandemic in the United States: A National Inpatient Sample Study

BACKGROUND AND OBJECTIVES

There are limited national data on the trends and outcomes of patients hospitalized with acute myocardial infarction (AMI) during the coronavirus disease 2019 (COVID-19) pandemic. We aimed to evaluate the impact of early COVID-19 pandemic on the trends and outcomes of AMI using the National Inpatient Sample (NIS) database.

METHODS

The NIS database was queried from January 2019 to December 2020 to identify adult (age ≥18 years) AMI hospitalizations and were categorized into ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) based on International Classification of Diseases, Tenth Revision, Clinical Modification codes. In addition, the in-hospital mortality, revascularization, and resource utilization of AMI hospitalizations early in the COVID-19 pandemic (2020) were compared to those in the pre-pandemic period (2019) using multivariate logistic and linear regression analysis.

RESULTS

Amongst 1,709,480 AMI hospitalizations, 209,450 STEMI and 677,355 NSTEMI occurred in 2019 while 196,230 STEMI and 626,445 NSTEMI hospitalizations occurred in 2020. Compared with those in 2019, the AMI hospitalizations in 2020 had higher odds of in-hospital mortality (adjusted odds ratio [aOR], 1.27; 95% confidence interval [CI], [1.23-1.32]; p<0.01) and lower odds of percutaneous coronary intervention (aOR, 0.95 [0.92-0.99]; p=0.02), and coronary artery bypass graft (aOR, 0.90 [0.85-0.97]; p<0.01).

CONCLUSIONS

We found a significant decline in AMI hospitalizations and use of revascularization, with higher in-hospital mortality, during the early COVID-19 pandemic period (2020) compared with the pre-pandemic period (2019). Further research into the factors associated with increased mortality could help with preparedness in future pandemics.

Prognostic Value of Objective Social Isolation and Loneliness in Older Patients With Heart Failure: Subanalysis of FRAGILE-HF and Kitasato Cohort

BACKGROUND

Social factors encompass a broad spectrum of nonmedical factors, including objective (social isolation [SI]) and perceived (loneliness) conditions. Although social factors have attracted considerable research attention, information regarding their impact on patients with heart failure is scarce. We aimed to investigate the prognostic impact of objective SI and loneliness in older patients with heart failure.

METHODS AND RESULTS

This study was conducted using the FRAGILE-HF (Prevalence and Prognostic Value of Physical and Social Frailty in Geriatric Patients Hospitalized for Heart Failure; derivation cohort) and Kitasato cohorts (validation cohort), which included hospitalized patients with heart failure aged ≥65 years. Objective SI and loneliness were defined using the Japanese version of Lubben Social Network Scale-6 and diagnosed when the total score for objective and perceived questions on the Lubben Social Network Scale-6 was below the median in the FRAGILE-HF. The primary outcome was 1-year death. Overall, 1232 and 405 patients in the FRAGILE-HF and Kitasato cohorts, respectively, were analyzed. Objective SI and loneliness were observed in 57.8% and 51.4% of patients in the FRAGILE-HF and 55.4% and 46.2% of those in the Kitasato cohort, respectively. During the 1-year follow-up, 149 and 31 patients died in the FRAGILE-HF and Kitasato cohorts, respectively. Cox proportional hazard analysis revealed that objective SI, but not loneliness, was significantly associated with 1-year death after adjustment for conventional risk factors in the FRAGILE-HF. These findings were consistent with the validation cohort.

CONCLUSIONS

Objective SI assessed using the Lubben Social Network Scale-6 may be a prognostic indicator in older patients with heart failure. Given the lack of established SI assessment methods in this population, further research is required to refine such methods.

Cardiovascular Safety of Romosozumab vs. PTH Analogs for Osteoporosis Treatment: a Propensity Score Matched Cohort Study

CONTEXT

Romosozumab, a monoclonal sclerostin antibody, is a recently approved highly potent anti-osteoporotic agent with osteoanabolic properties. Clinical use of Romosozumab is hindered by the fear of adverse cardiovascular (CV) events raised following the pivotal ARCH-trial.

OBJECTIVE

To assess real-world CV safety of romosozumab vs. alternative osteoanabolic therapies used for treatment of severe osteoporosis.

DESIGN

Data was obtained from TriNetX, a global federated health research network including real-time electronic medical records from 113 healthcare organizations with a total of 136,460,930 patients across 16 countries at time of analysis. Inclusion criteria were age ≥ 40 years, a diagnosis of osteoporosis and prescription of romosozumab or a PTH analog (teriparatide/abaloparatide) during 8.2019-8.2022. 1:1 propensity score matched cohorts were created using demographic variables, comorbidities, and medications. Kaplan-Meier analysis was used to estimate the probability of the outcomes.

OUTCOMES

Incident 3-point major adverse CV event or death (3P-MACE) during 1-year of follow-up after the initial prescription.

RESULTS

5,626 and 15,986 patients met the criteria for romosozumab and PTH analog cohorts, respectively, with 5,610 patients per group following propensity score matching. 3P-MACE was significantly less frequent in the romosozumab vs. PTH analog cohort (158 vs 211 patients with an outcome, p=0.003) with reductions in the individual components of the composite outcome: myocardial ischemic events (31 vs 58, p=0.003); cerebrovascular events 56 vs 79, p=0.037; deaths (83 vs 104, p=0.099).

CONCLUSIONS

In a diverse real-world setting, prescription of romosozumab for osteoporosis is associated with less adverse CV events when compared to PTH analog therapy.

Development and validation of claims-based algorithms for identifying hospitalized patients with COVID-19 and their severity in 2020 and 2021

BACKGROUND

This study aimed to develop and validate claims-based algorithms for identifying hospitalized patients with coronavirus disease (COVID-19) and the disease severity.

METHODS

We used claims data including all patients at the National Center for Global and Medicine Hospital between January 1, 2020, and December 31, 2021. The claims-based algorithms for three statuses with COVID-19 (hospitalizations, moderate or higher status, and severe status) were developed using diagnosis codes (ICD-10 code: U07.1, B34.2) and relevant medical procedure code. True cases were determined using the COVID-19 inpatient registry and electronic health records. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each algorithm at 6-month intervals.

RESULTS

Of the 75,711 total patients, number of true cases was 1,192 for hospitalizations, 622 for moderate or higher status, and 55 for severe status. The diagnosis code-only algorithm for hospitalization had sensitivities 90.4% to 94.9% and PPVs 9.3% to 19.4%. Among the algorithms consisting of both diagnosis codes and procedure codes, high sensitivity and PPV were observed during the following periods; 93.9% and 97.1% for hospitalization (January-June 2021), 90.4% and 87.5% for moderate or higher status (July-December 2021), and 92.3% and 85.7% for severe status (July-December 2020), respectively. Almost all algorithms had specificities and NPVs of approximately 99%.

CONCLUSIONS

The diagnosis code-only algorithm for COVID-19 hospitalization showed low validity throughout the study period. The algorithms for hospitalizations, moderate or higher status, and severe status with COVID-19, consisting of both diagnosis codes and procedure codes, showed high validity in some periods.

Dynamic Prognosis Prediction for Patients on DAPT After Drug-Eluting Stent Implantation: Model Development and Validation

BACKGROUND

The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management.

METHODS AND RESULTS

We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI-DAPT model. The AI-DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%-92%] for ischemia and 84% [95% CI, 82%-87%] for bleeding predictions.

CONCLUSIONS

Our AI-DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

Cardiovascular Safety of Atomoxetine and Methylphenidate in Patients With Attention-Deficit/Hyperactivity Disorder in Japan: A Self-Controlled Case Series Study

OBJECTIVE

To investigate the association between atomoxetine or methylphenidate use and arrhythmia, heart failure (HF), stroke, and myocardial infarction (MI) in attention-deficit/hyperactivity disorder (ADHD) patients mainly focused on the people of working age.

METHODS

In a self-controlled case series study using a Japanese claims database, we identified events of arrhythmia, HF, stroke, and MI among 15,472 atomoxetine new users and 12,059 methylphenidate new users. Adjusted incidence rate ratios (aIRRs) of outcome events were estimated using multivariable conditional Poisson regression.

RESULTS

An increased risk of arrhythmia was observed during the first 7 days after the initial atomoxetine exposure (aIRR 6.22, 95% CI [1.90, 20.35]) and in the subsequent exposure (3.23, [1.58, 6.64]). No association was found between methylphenidate exposure and arrhythmia, nor between atomoxetine or methylphenidate exposure and HF. The limited number of stroke and MI cases prevented thorough analysis.

CONCLUSIONS

Clinicians should consider monitoring for arrhythmia after patients initiating or re-initiating atomoxetine.

Associations between metabolic hyperferritinaemia, fibrosis-promoting alleles and clinical outcomes in steatotic liver disease

BACKGROUND & AIMS

Ferritin has been investigated as a biomarker for liver fibrosis and iron in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). However, whether metabolic hyperferritinaemia predicts progression of liver disease remains unknown. In this study, we sought to understand associations between hyperferritinaemia and (1) adverse clinical outcomes and (2) common genetic variants related to iron metabolism and liver fibrosis.

METHODS

This was a retrospective analysis of adults with MASLD seen at the University of Michigan Health System, where MASLD was defined by hepatic steatosis on imaging, biopsy or vibration-controlled transient elastography, plus metabolic risk factors in the absence of chronic liver diseases other than hemochromatosis. The primary predictor was serum ferritin level, which was dichotomized based on a cut-off of 300 or 450 mcg/L for women or men. Primary outcomes included (1) incident cirrhosis, liver-related events, congestive heart failure (CHF), and mortality and (2) distribution of common genetic variants associated with hepatic fibrosis and hereditary hemochromatosis.

RESULTS

Of 7333 patients with MASLD, 1468 (20%) had elevated ferritin. In multivariate analysis, ferritinaemia was associated with increased mortality (HR 1.68 [1.35-2.09], p < .001) and incident liver-related events (HR 1.92 [1.11-3.32], p = .019). Furthermore, elevated ferritin was associated with carriage of cirrhosis-promoting alleles including PNPLA3-rs738409-G allele (p = .0068) and TM6SF2-rs58542926-T allele (p = 0.0083) but not with common HFE mutations.

CONCLUSIONS

In MASLD patients, metabolic hyperferritinaemia was associated with increased mortality and higher incidence of liver-related events, and cirrhosis-promoting alleles but not with iron overload-promoting HFE mutations.

Agreement in All-in-One Dataset between Diagnosis and Prescribed Medication for Common Cardiometabolic Diseases in the NDB-K7Ps

The Japanese National Database (NDB), a useful data source for epidemiological studies, contains information on health checkups, disease diagnoses, and medications, which can be used when investigating common cardiometabolic diseases. However, before the initiation of an integrated analysis, we need to combine several pieces of information prepared separately into an all-in-one dataset (AIOD) and confirm the validation of the dataset for the study. In this study, we aimed to confirm the degree of agreement in data entries between diagnoses and prescribed medications and self-reported pharmacotherapy for common cardiometabolic diseases in newly assembled AIODs. The present study included 10,183,619 people who underwent health checkups from April 2018 to March 2019. Over 95% of patients prescribed antihypertensive and antidiabetic medications were diagnosed with each disease. For dyslipidemia, over 95% of patients prescribed medications were diagnosed with at least one of the following: dyslipidemia, hypercholesterolemia, or hyperlipidemia. Similarly, over 95% of patients prescribed medications for hyperuricemia were diagnosed with either hyperuricemia or gout. Additionally, over 90% of patients with self-reported medications for hypertension, diabetes, and dyslipidemia were diagnosed with each disease, although the proportions differed among age groups. Our study demonstrated high levels of agreement between diagnoses and prescribed medications for common cardiometabolic diseases and self-reported pharmacotherapy in our AIOD.

Studies of Health Insurance Claims Data in Japan: A Scoping Review

BACKGROUND

Health insurance claims data are used in various research fields; however, an overview on how they are used in healthcare research is scarce in Japan. Therefore, we conducted a scoping review to systematically map the relevant studies using Japanese claims data.

METHODS

MEDLINE, EMBASE, and Ichushi-Web were searched up to April 2021 for studies using Japanese healthcare claims data. We abstracted the data on study characteristics and summarized target diseases and research themes by the types of claims database. Moreover, we described the results of studies that aimed to compare health insurance claims data with other data sources narratively.

RESULTS

A total of 1,493 studies were included. Overall, the most common disease classifications were "Diseases of the circulatory system" (18.8%, n = 281), "Endocrine, nutritional, and metabolic diseases" (11.5%, n = 171; mostly diabetes), and "Neoplasms" (10.9%, n = 162), and the most common research themes were "medical treatment status" (30.0%, n = 448), "intervention effect" (29.9%, n = 447), and "clinical epidemiology, course of diseases" (27.9%, n = 417). Frequent diseases and themes varied by type of claims databases. A total of 19 studies aimed to assess the validity of the claims-based definition, and 21 aimed to compare the results of claims data with other data sources. Most studies that assessed the validity of claims data compared to medical records were hospital-based, with a small number of institutions.

CONCLUSIONS

Claims data are used in various research areas and will increasingly provide important evidence for healthcare policy in Japan. It is important to use previous claims database studies and share information on methodology among researchers, including validation studies, while informing policymakers about the applicability of claims data for healthcare planning and management.

Comorbidity in incident osteoarthritis cases and matched controls using electronic health record data

BACKGROUND

Comorbidities are common in patients with osteoarthritis (OA). This study aimed to determine the association of a wide range of previously diagnosed comorbidities in adults with newly diagnosed OA compared with matched controls without OA.

METHODS

A case-control study was conducted. The data were derived from an electronic health record database that contains the medical records of patients from general practices throughout the Netherlands. Incident OA cases were defined as patients with one or more diagnostic codes recorded in their medical records that correspond to knee, hip, or other/peripheral OA. Additionally, the first OA code had to be recorded between January 1, 2006, and December 31, 2019. The date of cases' first OA diagnosis was defined as the index date. Cases were matched (by age, sex, and general practice) to up to 4 controls without a recorded OA diagnosis. Odds ratios were derived for each 58 comorbidities separately by dividing the comorbidity prevalence of cases by that of their matched controls at the index date.

RESULTS

80,099 incident OA patients were identified of whom 79,937 (99.8%) were successfully matched with 318,206 controls. OA cases had higher odds for 42 of the 58 studied comorbidities compared with matched controls. Musculoskeletal diseases and obesity showed large associations with incident OA.

CONCLUSIONS

Most of the comorbidities under study had higher odds in patients with incident OA at the index date. While previously known associations were confirmed in this study, some associations were not described earlier.

Validation studies of Japanese administrative health care data: A scoping review

PURPOSE

Large-scale administrative health care databases are increasingly being utilized for research. However, there has not been much literature that validated administrative data in Japan; a previous review identified six validation studies published between 2011 and 2017. We conducted a literature review of studies that assessed the validity of Japanese administrative health care data.

METHODS

We searched for studies published by March 2022 that compared individual-level administrative data with a reference standard from another data source, as well as studies that validated administrative data using other data within the same database. The eligible studies were also summarized based on characteristics which included data types, settings, reference standard used, numbers of patients, and conditions validated.

RESULTS

There were 36 eligible studies, including 29 that used external reference standard and seven that validated administrative data using other data within the same database. Chart review was the reference standard in 21 studies (range of the numbers of patients, 72-1674; 11 studies conducted in single institutions and nine studies in 2-5 institutions). Five studies used a disease registry as the reference standard. Diagnoses of cardiovascular diseases, cancer, and diabetes were frequently evaluated.

CONCLUSIONS

Validation studies are being conducted at an increasing rate in Japan, although most of them are small scale. Further large-scale comprehensive validation studies are necessary to effectively utilize the databases for research.

Higher mortality among lean patients with non-alcoholic fatty liver disease despite fewer metabolic comorbidities

BACKGROUND & AIMS

Non-alcoholic fatty liver disease (NAFLD) can develop in individuals who are not overweight. Whether lean persons with NAFLD have lower mortality and lower incidence of cirrhosis, cardiovascular diseases (CVD), diabetes mellitus (DM) and cancer than overweight/obese persons with NAFLD remains inconclusive. We compared mortality and incidence of cirrhosis, CVD, DM and cancer between lean versus non-lean persons with NAFLD.

METHODS

This is a retrospective study of adults with NAFLD in a single centre from 2012 to 2021. Primary outcomes were mortality and new diagnosis of cirrhosis, CVD, DM and cancer. Outcomes were modelled using competing risk analysis and Cox proportional hazards regression analysis.

RESULTS

A total of 18,594 and 13,420 patients were identified for cross-sectional and longitudinal analysis respectively: approximately 11% lean, 25% overweight, 28% class 1 obesity and 35% class 2-3 obesity. The median age was 51.0 years, 54.6% were women. The median follow-up was 49.3 months. Lean patients had lower prevalence of metabolic diseases at baseline and lower incidence of cirrhosis and DM than non-lean patients and no difference in CVD, any cancer or obesity-related cancer during follow-up. However, lean patients had significantly higher mortality with incidence per 1000 person-years of 16.67, 10.11, 7.37 and 8.99, respectively, in lean, overweight, obesity class 1 and obesity class 2-3 groups respectively.

CONCLUSIONS

Lean patients with NAFLD had higher mortality despite lower incidence of cirrhosis and DM, and similar incidence of CVD and cancer and merit similar if not more attention as non-lean patients with NAFLD.

Occurrence of comorbidity following osteoarthritis diagnosis: a cohort study in the Netherlands

OBJECTIVE

To determine the risk of comorbidity following diagnosis of knee or hip osteoarthritis (OA).

DESIGN

A cohort study was conducted using the Integrated Primary Care Information database, containing electronic health records of 2.5 million patients from the Netherlands. Adults at risk for OA were included. Diagnosis of knee or hip OA (=exposure) and 58 long-term comorbidities (=outcome) were defined by diagnostic codes following the International Classification of Primary Care coding system. Time between the start of follow-up and incident diagnosis of OA was defined as unexposed, and between diagnosis of OA and the end of follow-up as exposed. Age and sex adjusted hazard ratios (HRs) comparing comorbidity rates in exposed and unexposed patient time were estimated with 99.9% confidence intervals (CI).

RESULTS

The study population consisted of 1,890,712 patients. For 30 of the 58 studied comorbidities, exposure to knee OA showed a HR larger than 1. Largest positive associations (HR with (99.9% CIs)) were found for obesity 2.55 (2.29-2.84) and fibromyalgia 2.06 (1.53-2.77). For two conditions a HR < 1 was found, other comorbidities showed no association with exposure to knee OA. For 26 comorbidities, exposure to hip OA showed a HR larger than 1. The largest were found for polymyalgia rheumatica 1.81 (1.41-2.32) and fibromyalgia 1.70 (1.10-2.63). All other comorbidities showed no associations with hip OA.

CONCLUSION

This study showed that many comorbidities were diagnosed more often in patients with knee or hip OA. This suggests that the management of OA should consider the risk of other long-term-conditions.

Association of pneumococcal vaccination with cardiovascular diseases in older adults: The vaccine effectiveness, networking, and universal safety (VENUS) study

The protective effect of the 23-valent pneumococcal polysaccharide vaccine (PPSV23) against cardiovascular disease has been investigated in the United States and Europe; however, its effect has not been fully established. This study aimed to investigate the protective effect of PPSV23 on cardiovascular events in adults aged ≥ 65 years. This population-based nested case-control study was conducted using the claims data and vaccine records between April 2015 and March 2020 from the Vaccine Effectiveness, Networking, and Universal Safety (VENUS) Study. PPSV23 vaccination was identified using vaccination records in each municipality. The primary outcome was acute myocardial infarction (AMI) or stroke. The adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for PPSV23 vaccination were calculated using conditional logistic regression. Among 383,781 individuals aged ≥ 65 years, 5,356 and 25,730 individuals with AMI or stroke were matched with 26,753 and 128,397 event-free controls, respectively. Individuals who were PPSV23 vaccinated, compared with the unvaccinated individuals, had significantly lower odds of AMI or stroke events (aOR, 0.70 [95% CI, 0.62-0.80] and aOR, 0.81 [95% CI, 0.77-0.86], respectively). More recent PPSV23 vaccination was associated with lower odds ratios (AMI, aOR 0.55 [95% CI, 0.42-0.72] for 1-180 days and aOR 1.11 [95% CI, 0.84-1.47] for 720 days or longer; stroke, aOR 0.83 [95% CI, 0.74-0.93] for 1-180 days and aOR 0.90 [95% CI, 0.78-1.03] for 720 days or longer). Among Japanese older adults, individuals who were PPSV23 vaccinated, compared with unvaccinated individuals, had significantly lower odds of AMI or stroke events.

Prevalence of neurological complaints among emergency department patients with severe hypertension

OBJECTIVE

Severe hypertension can accompany neurological symptoms without obvious signs of target organ damage. However, acute cerebrovascular events can also be a cause and consequence of severe hypertension. We therefore use US population-level data to determine prevalence and clinical characteristics of patients with severe hypertension and neurological complaints.

METHODS

We used nationally representative data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) collected in 2016-2019 to identify adult ED patients with severely elevated blood pressure (BP) defined as systolic BP ≥ 180 mmHg and/or diastolic BP ≥120 mmHg. We used ED reason for visit data fields to define neurological complaints and used diagnosis data fields to define acute target organ damage. We applied survey visit weights to obtain national estimates.

RESULTS

Based on 5083 observations, an estimated 40.4 million patients (95% CI: 37.5-43.0 million) in EDs nationwide from 2016 to 2019 had severe hypertension, equating to 6.1% (95% CI: 5.7-6.5%) of all ED visits. Only 2.8% (95% CI: 2.0-3.9%) of ED patients with severe hypertension were diagnosed with acute cerebrovascular disease; hypertensive urgency was diagnosed in 92.0% (95% CI: 90.3-93.4%). Neurological complaints were frequent in both patients with (75.6%) and without (19.9%) cerebrovascular diagnoses. Hypertensive urgency patients with neurological complaints were more often older, female, had prior stroke/TIA, and had neuroimaging than patients without these complaints. Non-migraine headache and vertigo were the most common neurological complaints recorded.

CONCLUSION

In a nationally representative survey, one-in-sixteen ED patients had severely elevated BP and one-fifth of those patients had neurological complaints.

Validity of Diagnostic Algorithms for Cardiovascular Diseases in Japanese Health Insurance Claims

BACKGROUND

We aimed to validate a claims-based diagnostic algorithm to identify hospitalized patients with acute major cardiovascular diseases (CVDs) from health insurance claims in Japan.Methods and Results: This retrospective multicenter validation study was conducted at 4 institutes, including Japanese Circulation Society-certified and uncertified hospitals in Japan. Data on patients with CVDs in departmental lists or with International Classification of Diseases, 10th Revision (ICD-10) codes for CVDs hospitalized between April 2018 and March 2019 were extracted. We examined the sensitivity and positive predictive value of a diagnostic algorithm using ICD-10 codes, medical examinations, and treatments for acute coronary syndrome (ACS), acute heart failure (HF), and acute aortic disease (AAD). We identified 409 patients with ACS (mean age 70.6 years; 24.7% female), 615 patients with acute HF (mean age 77.3 years; 46.2% female), and 122 patients with AAD (mean age 73.4 years; 36.1% female). The respective sensitivity and positive predictive value for the algorithm were 0.86 (95% confidence interval [CI] 0.82-0.89) and 0.95 (95% CI 0.92-0.97) for ACS; 0.74 (95% CI 0.70-0.77) and 0.79 (95% CI 0.76-0.83) for acute HF; and 0.86 (95% CI 0.79-0.92) and 0.83 (95% CI 0.76-0.89) for AAD.

CONCLUSIONS

The validity of the diagnostic algorithm for Japanese claims data was acceptable. Our results serve as a foundation for future studies on CVDs using nationwide administrative data.

Validation study on definition of cause of death in Japanese claims data

Identifying the cause of death is important for the study of end-of-life patients using claims data in Japan. However, the validity of how cause of death is identified using claims data remains unknown. Therefore, this study aimed to verify the validity of the method used to identify the cause of death based on Japanese claims data. Our study population included patients who died at two institutions between January 1, 2018 and December 31, 2019. Claims data consisted of medical data and Diagnosis Procedure Combination (DPC) data, and five definitions developed from disease classification in each dataset were compared with death certificates. Nine causes of death, including cancer, were included in the study. The definition with the highest positive predictive values (PPVs) and sensitivities in this study was the combination of "main disease" in both medical and DPC data. For cancer, these definitions had PPVs and sensitivities of > 90%. For heart disease, these definitions had PPVs of > 50% and sensitivities of > 70%. For cerebrovascular disease, these definitions had PPVs of > 80% and sensitivities of> 70%. For other causes of death, PPVs and sensitivities were < 50% for most definitions. Based on these results, we recommend definitions with a combination of "main disease" in both medical and DPC data for cancer and cerebrovascular disease. However, a clear argument cannot be made for other causes of death because of the small sample size. Therefore, the results of this study can be used with confidence for cancer and cerebrovascular disease but should be used with caution for other causes of death.

Short-term associations of ambient air pollution with hospital admissions for ischemic stroke in 97 Japanese cities

The short-term association between ambient air pollution and hospital admissions for ischemic stroke is not fully understood. We examined the association between four regularly measured major ambient air pollutants, i.e., sulfur dioxide (SO₂), nitrogen dioxide (NO₂), photochemical oxidants (O_x), and particulate matter with aerodynamic diameters ≤ 2.5 μm (PM_2.5), and hospital admissions for ischemic stroke by analyzing 3 years of nationwide claims data from 97 cities in Japan. We first estimated city-specific results by using generalized additive models with a quasi-Poisson regression, and we obtained the national average by combining city-specific results with the use of random-effect models. We identified a total of 335,248 hospital admissions for ischemic stroke during the 3-year period. Our analysis results demonstrated that interquartile range increases in the following four ambient air pollutants were significantly associated with hospital admissions for ischemic stroke on the same day: SO₂ (1.05 ppb), 1.05% (95% CI: 0.59-1.50%); NO₂ (6.40 ppb), 1.10% (95% CI: 0.61-1.59%); O_x (18.32 ppb), 1.43% (95% CI: 0.81-2.06%); and PM_2.5 (7.86 μg/m³), 0.90% (95% CI: 0.35-1.45%). When the data were stratified by the hospital admittees' medication use, we observed stronger associations with SO₂, NO₂, and PM_2.5 among the patients who were taking antihypertensive drugs and weaker associations with SO₂, NO₂, and O_x among those taking antiplatelet drugs. Short-term exposure to ambient air pollution was associated with increased hospital admissions for ischemic stroke, and medication use and season may modify the association.

Systematic approach to outcome assessment from coded electronic healthcare records in the DaRe2THINK NHS-embedded randomized trial. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2022;3:426-436. [PMID: 36712153 PMCID: PMC9708037 DOI: 10.1093/ehjdh/ztac046]

Aims

Improving the efficiency of clinical trials is key to their continued importance in directing evidence-based patient care. Digital innovations, in particular the use of electronic healthcare records (EHRs), allow for large-scale screening and follow up of participants. However, it is critical these developments are accompanied by robust and transparent methods that can support high-quality and high clinical value research.

Methods and results

The DaRe2THINK trial includes a series of novel processes, including nationwide pseudonymized pre screening of the primary-care EHR across England, digital enrolment, remote e-consent, and 'no-visit' follow up by linking all primary- and secondary-care health data with patient-reported outcomes. DaRe2THINK is a pragmatic, healthcare-embedded randomized trial testing whether earlier use of direct oral anticoagulants in patients with prior or current atrial fibrillation can prevent thromboembolic events and cognitive decline (www.birmingham.ac.uk/dare2think). This study outlines the systematic approach and methodology employed to define patient information and outcome events. This includes transparency on all medical code lists and phenotypes used in the trial across a variety of national data sources, including Clinical Practice Research Datalink Aurum (primary care), Hospital Episode Statistics (secondary care), and the Office for National Statistics (mortality).

Conclusion

Co-designed by a patient and public involvement team, DaRe2THINK presents an opportunity to transform the approach to randomized trials in the setting of routine healthcare, providing high-quality evidence generation in populations representative of the community at risk.

Association between psoriasis and short-term outcomes of acute myocardial infarction: A matched-pair cohort study using a nationwide inpatient database in Japan

Background

Objective

Methods

Results

Limitations

Conclusion

Comparative cardiovascular effectiveness of glucagon-like peptide-1 receptor agonists versus sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes: A population-based cohort study

AIMS

To examine the comparative effectiveness of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 (SGLT2) inhibitors for select cardiovascular outcomes and to examine whether the relative risks varied across different patient subgroups in patients with type 2 diabetes.

MATERIALS AND METHODS

We conducted a nationwide cohort study of patients with type 2 diabetes who initiated GLP-1RAs or SGLT2 inhibitors between 2012 and 2018 in Taiwan. The study outcomes included myocardial infarction and total stroke, further classified into ischaemic or haemorrhagic stroke. We estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) for each outcome, comparing GLP-1RAs with SGLT2 inhibitors using Cox proportional hazards models after 1:1 propensity-score (PS) matching. We also examined if there was effect modification by age, underlying chronic kidney disease, or coexisting cardiovascular disease in prespecified subgroup analyses.

RESULTS

Among 26 032 PS-matched patients, GLP-1RA initiators and SGLT2 inhibitor initiators showed similar risks of myocardial infarction (HR 0.99, 95% CI 0.65-1.52), total stroke (HR 0.90, 95% CI 0.69-1.17), ischaemic stroke (HR 0.86, 95% CI 0.65-1.14) and haemorrhagic stroke (HR 0.88, 95% CI 0.63-1.25). However, GLP-1RA treatment was associated with an increased risk of total stroke (HR 1.76, 95% CI 1.06-2.94) and ischaemic stroke (HR 1.88, 95% CI 1.09-3.23) among patients with chronic kidney disease, but not among patients without chronic kidney disease. GLP-1RA therapy seemed to have a lower risk of haemorrhagic stroke among patients with cardiovascular disease (HR 0.64, 95% CI 0.43-0.97), but not in patients without cardiovascular disease.

CONCLUSIONS

Glucagon-like peptide-1 receptor agonists and SGLT2 inhibitors appeared to have comparable effectiveness with regard to several cardiovascular outcomes overall, but their comparative effectiveness may vary in certain patient subgroups.

Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan

OBJECTIVES

Validation studies in oncology are limited in Japan. This study was conducted to evaluate the accuracy of diagnosis and adverse event (AE) definitions for specific cancers in a Japanese health administrative real-world database (RWD).

DESIGN AND SETTING

Retrospective observational validation study to assess the diagnostic accuracy of electronic medical records (EMRs) and claim coding regarding oncology diagnosis and AEs based on medical record review in the RWD. The sensitivity and positive predictive value (PPV) with 95% CIs were calculated.

PARTICIPANTS

The validation cohort included patients with lung (n=2257), breast (n=1121), colorectal (n=1773), ovarian (n=216) and bladder (n=575) cancer who visited the hospital between January 2014 and December 2018, and those with prostate cancer (n=3491) visiting between January 2009 and December 2018, who were identified using EMRs.

OUTCOMES

Key outcomes included primary diagnosis, deaths and AEs.

RESULTS

For primary diagnosis, sensitivity and PPV for the respective cancers were as follows: lung, 100.0% (96.6 to 100.0) and 81.0% (74.9 to 86.2); breast, 100.0% (96.3 to 100.0) and 74.0% (67.3 to 79.9); colorectal, 100.0% (96.6 to 100.0) and 80.5% (74.3 to 85.8); ovarian, 89.8% (77.8 to 96.6) and 75.9% (62.8 to 86.1); bladder, 78.6% (63.2 to 89.7) and 67.3% (52.5 to 0.1); prostate, 100.0% (93.2 to 100.0) and 79.0% (69.7 to 86.5). Sensitivity and PPV for death were as follows: lung, 97.0% (84.2 to 99.9) and 100.0% (84.2 to 100.0); breast, 100.0% (1.3 to 100.0) and 100.0% (1.3 to 100.0); colorectal, 100.0% (28.4 to 100.0) and 100.0% (28.4 to 100.0); ovarian, 100.0% (35.9 to 100.0) and 100.0% (35.9 to 100.0); bladder, 100.0% (9.4-100.0) and 100.0% (9.4 to 100.0); prostate, 75.0% (19.4 to 99.4) and 100.0% (19.4 to 100.0). Overall, PPV tended to be low, with the definition based on International Classification of Diseases, 10th revision alone for AEs.

CONCLUSION

Diagnostic accuracy was not so high, and therefore needs to be further investigated.

TRIAL REGISTRATION NUMBER

University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000039345).

Validity of operative information in Japanese administrative data: a chart review-based analysis of 1221 cases at a single institution

PURPOSE

To evaluate the validity of operative information recorded in the Diagnosis Procedure Combination (DPC) database, a national inpatient database including administrative claims data.

METHODS

We reviewed the medical charts of 1221 patients who underwent one of six surgeries (breast, esophageal, gastric, thyroid cancer surgery, appendectomy, or inguinal hernia repair) at a surgery department of a university hospital from April 2016 to March 2019. We compared operative information (type, date, laterality of procedure; type of anesthesia; transfusion; and duration of anesthesia) recorded in the DPC database with the information recorded in the medical charts.

RESULTS

The DPC data for type, date, laterality of surgery, and type of anesthesia were accurate in 99% of the reviewed patients. The sensitivity and specificity for identifying whether a patient received a transfusion procedure were 97.5% and 99.6%, respectively. Data regarding the duration of anesthesia in the DPC database were identical to those in medical chart records in 1114 of 1216 cases that received general or spinal anesthesia (91.5%). The duration of anesthesia in the DPC data was 53 min longer on average than the recorded operative time in the medical charts.

CONCLUSION

The DPC database had high validity for operative information.

Impact of telemedicine on clinical practice patterns for patients with chest pain in the emergency department

Background

The outbreak of the COVID-19 pandemic has led to the rapid adoption of novel telemedicine programs within the emergency department (ED) to minimize provider exposure and conserve personal protective equipment (PPE). In this study, we sought to assess how the adoption of telemedicine in the ED impacted clinical order patterns for patients with chest pain. We hypothesize that clinicians would rely more on imaging and laboratory workup for patients receiving telemedicine due to limitation in physical exams.

Methods

A single-center, retrospective, propensity score matched study was designed for patients presenting with chest pain at an ED. The study period was defined between April 1st, 2020 and September 30th, 2020. The frequency of the most frequent lab, imaging, and medication orders were compared. In addition, poisson regression analysis was performed to compare the overall number of orders between the two groups.

Results

455 patients with chest pain who received telemedicine were matched to 455 similar patients without telemedicine with standardized mean difference < 0.1 for all matched covariates. The proportion of frequent lab, imaging, and medication orders were similar between the two groups. However, telemedicine patients received more orders overall (RR, 1.19, 95% CI, 1.11, 1.28, p-value < 0.001) as well as more imaging, lab, and nursing orders. The number of medication orders between the two groups remained similar.

Conclusions

Frequent labs, imaging, and medications were ordered in similar proportions between the two cohorts. However, telemedicine patients had more orders placed overall. This study is an important objective assessment of the impact that telemedicine has upon clinical practice patterns and can guide future telemedicine implementation after the COVID-19 pandemic.

Effectiveness and Safety of Reduced and Standard Daily Doses of Direct Oral Anticoagulants in Patients with Nonvalvular Atrial Fibrillation: A Cohort Study Using National Database Representing the Japanese Population

Purpose

To compare the effectiveness and safety of reduced or standard daily doses of direct oral anticoagulants (DOACs) with warfarin in Japanese patients with nonvalvular atrial fibrillation (NVAF). We used post-hoc analyses to identify patient groups that could benefit from reduced-dose DOACs.

Patients and Methods

Using the National Database of Health Insurance Claims and Specific Health Checkups of Japan, we identified 944,776 patients with NVAF who had started an oral anticoagulant after at least one year of non-use between April 2011 and March 2016. We matched patients taking any, reduced, or standard doses of DOACs 1:1 with those taking warfarin. We measured treatment effectiveness based on admission due to stroke or systemic embolism (S/SE) and safety based on admission due to any bleeding (defined as major bleeding, MB). We compared both outcomes between DOACs and warfarin using the Cox proportional hazards model. We used post-hoc analysis to match patients receiving reduced-dose DOACs to those receiving standard-dose DOACs and compared treatment effectiveness and safety.

Results

More than half of patients receiving DOACs used a reduced dose. The occurrences of S/SE and MB in patients receiving any, reduced, or standard doses of DOACs were equal to or lower than those receiving warfarin. In the post-hoc analysis, the risk of S/SE and MB was similar between reduced and standard doses of DOACs except for those with a history of cerebral infarction and CHA₂DS₂-VASc score ≥3, where the risk of S/SE was lower for reduced doses of any and individual DOACs.

Conclusion

Findings from the current study are consistent with recent Asian and global studies but different from most studies conducted in North America and Europe, where patients receiving a reduced dose of DOACs had an increased risk of S/SE. Future studies should test the reproducibility of results from the current study.

Long-Term Outcomes for Patients With Acute Coronary Syndrome and Nonvalvular Atrial Fibrillation

Short-term outcomes are worse for patients with acute coronary syndrome (ACS) with a history of nonvalvular atrial fibrillation (NVAF). However, long-term prognosis remains unclear. We linked administrative health databases to identify patients hospitalized with ACS (ST-elevation myocardial infarction [STEMI], non-STEMI [NSTEMI], and unstable angina) between 2008 and 2019 in Alberta, Canada. Patients were stratified according to history of NVAF before hospitalization. The primary outcome was a composite of all-cause mortality, hospitalization for myocardial infarction, or stroke at 3 years. Cox models were constructed to estimate the association between ACS, NVAF, and outcomes. Of 54,309 ACS hospitalizations, 6,351 patients (11.7%) had a history of NVAF. Compared with patients without NVAF, patients with previous NVAF were older (75.6 ± 11.6 vs 64.9 ± 13.4 years), women (35.1% vs 30.0%), had higher comorbid burden (Charlson co-morbidity index 3.0 vs 1.0), and more often presented with NSTEMI (57.5% vs 49.0%). The primary outcome occurred in 37.0% of patients with previous NVAF and 17.4% without (p <0.001). In the multivariable analysis, there was a 1.14-fold (95% confidence interval [CI] 1.09 to 1.20) higher risk of the primary outcome in patients with previous NVAF. There was a significant association with STEMI (adjusted harazard ratio [aHR] 1.24, 95% CI 1.12 to 1.36) and NSTEMI (aHR 1.12, 95% CI 1.06 to 1.19) but not with unstable angina (aHR 1.04, 95% CI 0.90 to 1.22). In conclusion, in this population-based study, we identified that a history of NVAF at ACS presentation is associated with worse long-term prognosis, particularly for STEMI and NSTEMI.

Validity of Methods to Identify Individuals With Lower Extremity Amputation Using Department of Veterans Affairs Electronic Medical Records

Objectives

To determine the positive predictive value (PPV) of algorithms to identify patients with major (at the ankle or more proximal) lower extremity amputation (LEA) using Department of Veterans Affairs electronic medical records (EMR) and to evaluate whether PPV varies by sex, age, and race.

Design

We conducted a validation study comparing EMR determined LEA status to self-reported LEA (criterion standard).

Setting

Veterans who receive care at the Department of Veterans Affairs.

Participants

We invited a national sample of patients (N=699) with at least 1 procedure or diagnosis code for major LEA to participate. We oversampled women, Black men, and men ≤40 years of age.

Interventions

Not applicable.

Main Outcome Measure

We calculated PPV estimates and false negative percentages for 7 algorithms using EMR LEA procedure and diagnosis codes relative to self-reported major LEA.

Results

A total of 466 veterans self-reported their LEA status (68%). PPVs for the 7 algorithms ranged from 89% to 100%. The algorithm that required a single diagnosis or procedure code had the lowest PPV (89%). The algorithm that required at least 1 procedure code had the highest PPV (100%) but also had the highest proportion of false negatives (66%). Algorithms that required at least 1 procedure code or 2 or more diagnosis codes 1 month to 1 year apart had high PPVs (98%-99%) but varied in terms of false negative percentages. PPV estimates were higher among men than women but did not differ meaningfully by age or race, after accounting for sex.

Conclusion

PPVs were higher if 1 procedure or at least 2 diagnosis codes were required; the difference between algorithms was marked by sex. Investigators should consider trade-offs between PPV and false negatives to identify patients with LEA using EMRs.

Validation Study of Algorithms to Identify Malignant Tumors and Serious Infections in a Japanese Administrative Healthcare Database

BACKGROUND

This retrospective observational study validated case-finding algorithms for malignant tumors and serious infections in a Japanese administrative healthcare database.

METHODS

Random samples of possible cases of each disease (January 2015-January 2018) from two hospitals participating in the Medical Data Vision Co., Ltd. (MDV) database were identified using combinations of ICD-10 diagnostic codes and other procedural/billing codes. For each disease, two physicians identified true cases among the random samples of possible cases by medical record review; a third physician made the final decision in cases where the two physicians disagreed. The accuracy of case-finding algorithms was assessed using positive predictive value (PPV) and sensitivity.

RESULTS

There were 2,940 possible cases of malignant tumor; 180 were randomly selected and 108 were identified as true cases after medical record review. One case-finding algorithm gave a high PPV (64.1%) without substantial loss in sensitivity (90.7%) and included ICD-10 codes for malignancy and photographing/imaging. There were 3,559 possible cases of serious infection; 200 were randomly selected and 167 were identified as true cases after medical record review. Two case-finding algorithms gave a high PPV (85.6%) with no loss in sensitivity (100%). Both case-finding algorithms included the relevant diagnostic code and immunological infection test/other related test and, of these, one also included pathological diagnosis within 1 month of hospitalization.

CONCLUSIONS

The case-finding algorithms in this study showed good PPV and sensitivity for identification of cases of malignant tumors and serious infections from an administrative healthcare database in Japan.

Medication based machine learning to identify subpopulations of pediatric hemodialysis patients in an electronic health record database

Electronic health records (EHRs) have given rise to large and complex databases of medical information that have the potential to become powerful tools for clinical research. However, differences in coding systems and the detail and accuracy of the information within EHRs can vary across institutions. This makes it challenging to identify subpopulations of patients and limits the widespread use of multi-institutional databases. In this study, we leveraged machine learning to identify patterns in medication usage among hospitalized pediatric patients receiving renal replacement therapy and created a predictive model that successfully differentiated between intermittent (iHD) and continuous renal replacement therapy (CRRT) hemodialysis patients. We trained six machine learning algorithms (logistical regression, Naïve Bayes, k-nearest neighbor, support vector machine, random forest, and gradient boosted trees) using patient records from a multi-center database (n = 533) and prescribed medication ingredients (n = 228) as features to discriminate between the two hemodialysis types. Predictive skill was assessed using a 5-fold cross-validation, and the algorithms showed a range of performance from 0.7 balanced accuracy (logistical regression) to 0.86 (random forest). The two best performing models were further tested using an independent single-center dataset and achieved 84–87% balanced accuracy. This model overcomes issues inherent within large databases and will allow us to utilize and combine historical records, significantly increasing population size and diversity within both iHD and CRRT populations for future clinical studies. Our work demonstrates the utility of using medications alone to accurately differentiate subpopulations of patients in large datasets, allowing codes to be transferred between different coding systems. This framework has the potential to be used to distinguish other subpopulations of patients where discriminatory ICD codes are not available, permitting more detailed insights and new lines of research.

Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratification

Diagnosis and appropriate intervention for myocardial infarction (MI) are time-sensitive but rely on clinical measures that can be progressive and initially inconclusive, underscoring the need for an accurate and early predictor of MI to support diagnostic and clinical management decisions. The objective of this study was to develop a machine learning algorithm (MLA) to predict MI diagnosis based on electronic health record data (EHR) readily available during Emergency Department assessment. An MLA was developed using retrospective patient data. The MLA used patient data as they became available in the first 3 h of care to predict MI diagnosis (defined by International Classification of Diseases, 10th revision code) at any time during the encounter. The MLA obtained an area under the receiver operating characteristic curve of 0.87, sensitivity of 87% and specificity of 70%, outperforming the comparator scoring systems TIMI and GRACE on all metrics. An MLA can synthesize complex EHR data to serve as a clinically relevant risk stratification tool for MI.

Major adverse cardiovascular event definitions used in observational analysis of administrative databases: a systematic review

Background

Major adverse cardiovascular events (MACE) are increasingly used as composite outcomes in randomized controlled trials (RCTs) and observational studies. However, it is unclear how observational studies most commonly define MACE in the literature when using administrative data.

Methods

We identified peer-reviewed articles published in MEDLINE and EMBASE between January 1, 2010 to October 9, 2020. Studies utilizing administrative data to assess the MACE composite outcome using International Classification of Diseases 9th or 10th Revision diagnosis codes were included. Reviews, abstracts, and studies not providing outcome code definitions were excluded. Data extracted included data source, timeframe, MACE components, code definitions, code positions, and outcome validation.

Results

A total of 920 articles were screened, 412 were retained for full-text review, and 58 were included. Only 8.6% (n = 5/58) matched the traditional three-point MACE RCT definition of acute myocardial infarction (AMI), stroke, or cardiovascular death. None matched four-point (+unstable angina) or five-point MACE (+unstable angina and heart failure). The most common MACE components were: AMI and stroke, 15.5% (n = 9/58); AMI, stroke, and all-cause death, 13.8% (n = 8/58); and AMI, stroke and cardiovascular death 8.6% (n = 5/58). Further, 67% (n = 39/58) did not validate outcomes or cite validation studies. Additionally, 70.7% (n = 41/58) did not report code positions of endpoints, 20.7% (n = 12/58) used the primary position, and 8.6% (n = 5/58) used any position.

Conclusions

Components of MACE endpoints and diagnostic codes used varied widely across observational studies. Variability in the MACE definitions used and information reported across observational studies prohibit the comparison, replication, and aggregation of findings. Studies should transparently report the administrative codes used and code positions, as well as utilize validated outcome definitions when possible.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01440-5.

Development of algorithms for identifying patients with Crohn's disease in the Japanese health insurance claims database

Background

Real-world big data studies using health insurance claims databases require extraction algorithms to accurately identify target population and outcome. However, no algorithm for Crohn’s disease (CD) has yet been validated. In this study we aim to develop an algorithm for identifying CD using the claims data of the insurance system.

Methods

A single-center retrospective study to develop a CD extraction algorithm from insurance claims data was conducted. Patients visiting the Kitasato University Kitasato Institute Hospital between January 2015–February 2019 were enrolled, and data were extracted according to inclusion criteria combining the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) diagnosis codes with or without prescription or surgical codes. Hundred cases that met each inclusion criterion were randomly sampled and positive predictive values (PPVs) were calculated according to the diagnosis in the medical chart. Of all cases, 20% were reviewed in duplicate, and the inter-observer agreement (Kappa) was also calculated.

Results

From the 82,898 enrolled, 255 cases were extracted by diagnosis code alone, 197 by the combination of diagnosis and prescription codes, and 197 by the combination of diagnosis codes and prescription or surgical codes. The PPV for confirmed CD cases was 83% by diagnosis codes alone, but improved to 97% by combining with prescription codes. The inter-observer agreement was 0.9903.

Conclusions

Single ICD-code alone was insufficient to define CD; however, the algorithm that combined diagnosis codes with prescription codes indicated a sufficiently high PPV and will enable outcome-based research on CD using the Japanese claims database.

Lifestyle behaviors associated with the initiation of renal replacement therapy in Japanese patients with chronic kidney disease: a retrospective cohort study using a claims database linked with specific health checkup results

Background

Chronic kidney disease (CKD) is an independent risk factor for progression to an end-stage renal disease requiring dialysis or kidney transplantation. We investigated the association of lifestyle behaviors with the initiation of renal replacement therapy (RRT) among CKD patients using an employment-based health insurance claims database linked with specific health checkup (SHC) data.

Methods

This retrospective cohort study included 149,620 CKD patients aged 40–74 years who underwent a SHC between April 2008 and March 2016. CKD patients were identified using ICD-10 diagnostic codes and SHC results. We investigated lifestyle behaviors recorded at SHC. Initiation of RRT was defined by medical procedure claims. Lifestyle behaviors related to the initiation of RRT were identified using a Cox proportional hazards regression model with recency-weighted cumulative exposure as a time-dependent covariate.

Results

During 384,042 patient-years of follow-up by the end of March 2016, 295 dialysis and no kidney transplantation cases were identified. Current smoking (hazard ratio: 1.87, 95% confidence interval, 1.04─3.36), skipping breakfast (4.80, 1.98─11.62), and taking sufficient rest along with sleep (2.09, 1.14─3.85) were associated with the initiation of RRT.

Conclusions

Among CKD patients, the lifestyle behaviors of smoking, skipping breakfast, and sufficient rest along with sleep were independently associated with the initiation of RRT. Our study strengthens the importance of monitoring lifestyle behaviors to delay the progression of mild CKD to RRT in the Japanese working generation. A substantial portion of subjects had missing data for eGFR and drinking frequency, warranting verification of these results in prospective studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-021-01022-3.

Association between topical β-blocker use and asthma attacks in glaucoma patients with asthma: a cohort study using a claims database

PURPOSE

To investigate the association between the use of topical β-blockers and subsequent asthma attacks in glaucoma patients with asthma.

METHODS

This was a retrospective longitudinal cohort study using an administrative claims database. All patients aged 20 years or older who were registered in the health insurance claims database updated and managed by JMDC Inc. (Tokyo, Japan). Patients who were newly prescribed eye drops for glaucoma treatment were identified between 2011 and 2017. The patients with glaucoma were divided into two groups: β-blocker users and non-β-blocker users, based on the presence of a β-blocker in the prescribed eye drops. We investigated whether the incidence of asthma attacks in patients with previously treated asthma differed between the two groups.

RESULTS

We categorized 17,666 patients in the β-blocker-user group and 12,609 patients in the non-β-blocker-user group. A total of 580 patients in the β-blocker group (3.28%) and 847 in the non-β-blocker group (6.72%) underwent asthma treatment before the prescription of anti-glaucoma eye drops (P < 0.001). Furthermore, 94 patients in the β-blocker-user group (0.53%) and 278 in the non-β-blocker user group (2.20%) were undergoing current treatment for asthma (P < 0.001). The adjusted hazard ratios of asthma attacks were 0.73 (95% confidence interval, 0.46-1.16, P = 0.18) in patients with a history of asthma treatment and 1.22 (95% confidence interval, 0.56-2.70, P = 0.62) in patients with current asthma treatment, compared to the non-β-blocker-user group.

CONCLUSION

Our results clarified that several patients with asthma were prescribed topical β-blockers for glaucoma treatment. However, asthma attacks may not be significantly attributed to topical β-blockers, even in glaucoma patients under current asthma treatment. The administration of topical β-blockers to asthma patients could be a treatment option in the absence of other treatment options, if adequate informed consent is obtained. Further studies are needed to draw a firm conclusion on this clinical question.

Validation study on diabetes definitions using Japanese Diagnosis Procedure Combination data among hospitalized patients

BackgroundValidation studies on diabetes definitions using nationwide healthcare databases are scarce. We evaluated the validity of diabetes definitions using disease codes and antidiabetic drug prescriptions in the Japanese Diagnosis Procedure Combination (DPC) data via medical chart review.MethodsWe randomly selected 500 records among 15,334 patients who participated in the Japan Public Health Center-Based Prospective Study for the Next Generation in Yokote City and who had visited a general hospital in Akita between October 2011 and August 2018. Of the 500 patients, 98 were linked to DPC data; however, only 72 had sufficient information in the medical chart. Gold standard confirmation was performed by board-certified diabetologists. DPC-based diabetes definitions were based on the International Classification of Diseases, 10th Revision codes, and antidiabetic prescriptions. Sensitivity, specificity, and the positive and negative predictive values (PPV and NPV, respectively) of DPC-based diabetes definitions were evaluated.ResultsOf 72 patients, 23 were diagnosed with diabetes by chart review; 19 had a diabetes code, and 13 had both a diabetes code and antidiabetic prescriptions. The sensitivity, specificity, PPV, and NPV were 89.5% (95% confidence interval: 66.9-98.7), 96.2% (87.0-99.5), 89.5% (66.9-98.7), and 96.2% (87.0-99.5), respectively, for (i) diabetes codes alone; 89.5% (66.9-98.7), 94.3% (84.3-98.8), 85.0% (62.1-96.8), and 96.2 (86.8-99.5) for (ii) diabetes codes and/or prescriptions; 68.4% (43.4-87.4), 100% (93.3-100), 100% (75.3-100), and 89.8% (79.2-96.2) for (iii) both diabetes codes and prescriptions.ConclusionsOur results suggest that DPC data can accurately identify diabetes among inpatients using (i) diabetes codes alone or (ii) diabetes codes and/or prescriptions.

Acute myocardial infarction: Development and application of an ICD-10-CM-based algorithm to a large U.S. healthcare claims-based database

Background

Healthcare administrative claims data hold value for monitoring drug safety and assessing drug effectiveness. The U.S. Food and Drug Administration Biologics Effectiveness and Safety Initiative (BEST) is expanding its analytical capacity by developing claims-based definitions—referred to as algorithms—for populations and outcomes of interest. Acute myocardial infarction (AMI) was of interest due to its potential association with select biologics and the lack of an externally validated International Classification of Diseases, 10^th Revision, Clinical Modification (ICD-10-CM) algorithm.

Objective

Develop and apply an ICD-10-CM-based algorithm in a U.S. administrative claims database to identify and characterize AMI populations.

Methods

A comprehensive literature review was conducted to identify validated AMI algorithms. Building on prior published methodology and consistent application of ICD-9-CM codes, an ICD-10-CM algorithm was developed via forward-backward mapping using General Equivalence Mappings and refined with clinical input. An AMI population was then identified in the IBM^® MarketScan^® Research Databases and characterized using descriptive statistics.

Results and discussion

Between 2014–2017, 2.83–3.16 individuals/1,000 enrollees/year received ≥1 AMI diagnosis in any healthcare setting. The 2015 transition to ICD-10-CM did not result in a substantial change in the proportion of patients identified. Average patient age at first AMI diagnosis was 64.9 years, and 61.4% of individuals were male. Unspecified chest pain, hypertension, and coronary atherosclerosis of native coronary vessel/artery were most commonly reported within one day of AMI diagnosis. Electrocardiograms were the most common medical procedure and beta-blockers were the most commonly ordered cardiac medication in the one day before to 14 days following AMI diagnosis. The mean length of inpatient stay was 5.6 days (median 3 days; standard deviation 7.9 days). Findings from this ICD-10-CM-based AMI study were internally consistent with ICD-9-CM-based findings and externally consistent with ICD-9-CM-based studies, suggesting that this algorithm is ready for validation in future studies.

Validity of claims-based algorithms for selected cancers in Japan: Results from the VALIDATE-J study

Purpose

Real‐world data from large administrative claims databases in Japan have recently become available, but limited evidence exists to support their validity. VALIDATE‐J validated claims‐based algorithms for selected cancers in Japan.

Methods

VALIDATE‐J was a multicenter, cross‐sectional, retrospective study. Disease‐identifying algorithms were used to identify cancers diagnosed between January or March 2012 and December 2016 using claims data from two hospitals in Japan. Positive predictive values (PPVs), specificity, and sensitivity were calculated for prevalent (regardless of baseline cancer‐free period) and incident (12‐month cancer‐free period; with claims and registry periods in the same month) cases, using hospital cancer registry data as gold standard.

Results

22 108 cancers were identified in the hospital claims databases. PPVs (number of registry cases) for prevalent/incident cases were: any malignancy 79.0% (25 934)/73.1% (18 119); colorectal 84.4% (3519)/65.6% (2340); gastric 87.4% (3534)/76.8% (2279); lung 88.1% (2066)/79.9% (1636); breast 86.4% (4959)/59.9% (3185); pancreatic 87.1% (582)/80.4% (508); melanoma 48.7% (46)/42.9% (36); and lymphoma 83.6% (1457)/77.8% (1035). Specificity ranged from 98.3% to 100% (prevalent)/99.5% to 100% (incident); sensitivity ranged from 39.1% to 67.6% (prevalent)/12.5% to 31.4% (incident). PPVs of claims‐based algorithms for several cancers in patients ≥66 years of age were slightly higher than those in a US Medicare population.

Conclusions

VALIDATE‐J demonstrated high specificity and modest‐to‐moderate sensitivity for claims‐based algorithms of most malignancies using Japanese claims data. Use of claims‐based algorithms will enable identification of patient populations from claims databases, while avoiding direct patient identification. Further research is needed to confirm the generalizability of our results and applicability to specific subgroups of patient populations.

The validity of the claims-based definition of rheumatoid arthritis evaluated in 64 hospitals in Japan

BACKGROUND

An administrative database covering a whole population such as the national database in Japan may be used to estimate the nationwide prevalence of diseases including rheumatoid arthritis (RA) when a well-validated definition of the disease is available. In Japan, the record linkage between the administrative database and medical charts in hospitals is strictly prohibited. A "hospital-based" validation study is one of few possible validation studies where claims kept inside the study hospital are rearranged into the database structure.

METHODS

We selected random samples of 19,734 patients from approximately 1.6 million patients who received medical care between February 2018 and January 2019 in one of the 64 hospitals of the Tokushukai Medical Group. We excluded patients whose observation period was less than 365 days and identified 334 patients who met the definition of "possible cases of RA" whose medical charts were then independently evaluated by two rheumatologists. In a sensitivity analysis, we assessed bias due to misclassifying some patients with RA who did not meet the definition of "possible cases of RA" as a patient with no RA.

RESULTS

The kappa coefficient between the two rheumatologists was 0.80. The prevalence of RA in the study population was estimated to be 0.56%. We found that [condition code of RA] and ([any disease-modifying antirheumatic drug] or [oral corticosteroid with no systemic autoimmune diseases (other than RA) and no polymyalgia rheumatica]) had a relatively high sensitivity (approximately 73%) and a high positive predictive value (approximately 80%). In a sensitivity analysis, we found that when some patients with RA who did not meet the definition of "possible cases of RA" were misclassified as a patient with no RA, then this would lead to underestimation of the prevalence of the definition-positive patients and the adjusted prevalence.

CONCLUSIONS

We recommend using the claims-based definition of RA (found in the current validation study) to estimate the prevalence of RA in Japan. We also suggest estimating the adjusted prevalence using the quantitative bias analysis method, since the prevalence of the disease in the "hospital-based" validation study is different from that in the administrative database.

TRIAL REGISTRATION

The current study is not a clinical trial and hence not subject to trial registration.

Use of Post-Acute Care Services and Readmissions After Acute Myocardial Infarction Complicated by Cardiac Arrest and Cardiogenic Shock

OBJECTIVE

To evaluate post-acute care utilization and readmissions after cardiac arrest (CA) and cardiogenic shock (CS) complicating acute myocardial infarction (AMI).

METHODS

With use of an administrative claims database, AMI patients from January 1, 2010, to May 31, 2018, were stratified into CA+CS, CA only, CS only, and AMI alone. Outcomes included 90-day post-acute care (inpatient rehabilitation or skilled nursing facility) utilization and 1-year emergency department visits and readmissions.

RESULTS

Of 163,071 AMI patients, CA+CS, CA only, and CS only were noted in 3965 (2.4%), 8221 (5.0%), and 6559 (4.0%), respectively. In-hospital mortality was noted in 10,686 (6.6%) patients: CA+CS, 1935 (48.8%); CA only, 2948 (35.9%); CS only, 1578 (24.1%); and AMI alone, 4225 (2.9%) (P<.001). Among survivors, post-acute care services were used in 67,799 (44.5%), with higher use in the CS+CA cohort (1310 [64.6%]; hazard ratio [HR], 1.19; 95% CI, 1.06 to 1.33; P=.003) and CA cohort (2738 [51.9%]; HR, 1.27; 95% CI, 1.20 to 1.35; P<.001) but not in the CS cohort (3048 [61.2%]; HR, 1.03; 95% CI, 0.97 to 1.11; P=.35) compared with the AMI cohort (60,703 [43.3%]). Compared with the AMI cohort (48,990 [35.0%]), patients with CS only (2,085 [41.9%]; HR, 1.16; 95% CI, 1.10 to 1.22; P<.001) but not those with CA+CS (724 [35.7%]; HR, 1.07; 95% CI, 0.98 to 1.17; P=.14) had higher rates of readmissions (P=.03). Readmissions were lower in those with CA (1,590 [30.2%]; HR, 0.94; 95% CI, 0.89 to 0.99). Repeated AMI, coronary artery disease, and heart failure were the most common readmission reasons. There were no differences for emergency department visits.

CONCLUSION

CA is associated with increased post-acute care use, whereas CS is associated with increased readmission risk in AMI survivors.

Validation study of the claims-based definition for age-related macular degeneration at a single university hospital in Japan

PURPOSE

To evaluate the efficacy of the claims'-based definition of age-related macular degeneration (AMD) in detecting clinically-diagnosed AMD.

STUDY DESIGN

A validation study using cross-sectional data.

METHODS

Seven hundred clinically-diagnosed AMD patients and seven hundred non-AMD individuals were randomly selected from patients at the Kyoto University Hospital's ophthalmology outpatient clinic between January 2011 and December 2017. We evaluated the sensitivity, specificity, and positive/negative likelihood ratio of eight different claims'-based definitions of AMD for detecting clinically-diagnosed AMD. These definitions consist of the diagnosis name (AMD) in combination with (1) fluorescent fundus angiography, and/or (2) treatment of AMD, and (3) the exclusion of patients who had a diagnosis of central serous chorioretinopathy (CSC) or myopic choroidal neovascularization.

RESULTS

Defining by the diagnosis name AMD in the claims' data showed the highest accuracy (sensitivity 94.9%, specificity 92.6%, accuracy 93.7%). Combining the diagnosis name AMD with fluorescence fundus angiography and/or anti-vascular endothelial growth factor (anti VEGF) treatment increased the specificity at the expense of sensitivity. Notably, the combination with AMD treatment achieved a specificity of 98.3%.

CONCLUSION

The current validation study elucidated the high accuracy of the disease name (AMD) in the claims' data for identifying clinically-diagnosed AMD at a single university hospital. Although drawing wider conclusions may be limited, the results of this study contribute to creating real-world evidence in ophthalmology, based on the National Database of Health Insurance Claims in Japan.

Accuracy of Japanese claims data in identifying diabetes-related complications

PURPOSE

To evaluate the accuracy of various claims-based definitions of diabetes-related complications (coronary artery disease [CAD], heart failure, cerebrovascular disease and dialysis).

METHODS

We evaluated data on 1379 inpatients who received care at the Niigata University Medical & Dental Hospital in September 2018. Manual electronic medical chart reviews were conducted for all patients with regard to diabetes-related complications and were used as the gold standard. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each claims-based definition associated with diabetes-related complications based on Diagnosis Procedure Combination (DPC), International Classification of Diseases, Tenth Revision (ICD-10) codes, procedure codes and medication codes were calculated.

RESULTS

DPC-based definitions had higher sensitivity, specificity, and PPV than ICD-10 code definitions for CAD and cerebrovascular disease, with sensitivity of 0.963-1.000 and 0.905-0.952, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. Sensitivity, specificity, and PPV were high using procedure codes for CAD and dialysis, with sensitivity of 0.963 and 1.000, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. DPC and/or ICD-10 codes + medication were better for heart failure than the ICD-10 code definition, with sensitivity of 0.933, specificity of 1.000, and PPV of 1.000. The PPVs were lower than 60% for all diabetes-related complications using ICD-10 codes only.

CONCLUSION

The DPC-based definitions for CAD and cerebrovascular disease, procedure codes for CAD and dialysis, and DPC or ICD-10 codes with medication codes for heart failure could accurately identify these diabetes-related complications from claims databases.

Validation of Acute Myocardial Infarction and Heart Failure Diagnoses in Hospitalized Patients With the Nationwide Claim-Based JROAD-DPC Database

Background: Big data systems such as diagnosis procedure combination (DPC) datasets have recently been used for research purposes. However, there have been few validation studies to determine the accuracy of diagnoses. The aim of this study was to validate and evaluate 2 diagnoses, namely acute myocardial infarction (AMI) and heart failure (HF), using International Classification of Diseases, 10th revision (ICD-10) codes in the Japanese Registry Of All cardiac and vascular Disease (JROAD)-DPC database.

Methods and Results: ICD-10 codes I21.0–I21.9 and I50.0–I50.9 were used to identify AMI and HF, respectively, in the JROAD-DPC database. Diagnoses of AMI and HF were validated in clinical datasets assessing sensitivity and positive predictive value (PPV). Over 1–2 years, 742 patients hospitalized for AMI and 1,368 patients hospitalized for HF were identified in the DPC dataset. Sensitivity and PPV for AMI were 78.9% and 78.8%, respectively. When emergency hospitalization was included as a criterion, PPV increased to 84.9%. For HF, sensitivity and PPV were 84.7% and 57.0%, respectively. When emergency hospitalization and acute HF were included as criteria, PPV increased to 83.0%.

Conclusions: Using ICD-10 codes for AMI and HF diagnoses among hospitalized patients, the DPC dataset showed acceptable concordance with clinical datasets. PPV increased when any conditions of hospitalization were included, especially in HF.

Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review

Background

Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.

Objective

This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.

Methods

A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.

Results

A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.

Conclusions

Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

Differences in aggressive treatments during the actively dying phase in patients with cancer and heart disease: an exploratory study using the sampling dataset of the National Database of Health Insurance Claims

Despite the recent attention given to palliative care for patients with heart disease, data about the treatments in their actively dying phase are not sufficiently elaborated. In this study, we used the sampling dataset of a national database to compare the aggressive treatments performed in patients with cancer and those with heart disease. We only included patients deceased in January or July from 2011 to 2015, using the Diagnosis Procedure Combination sampling dataset of the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB). Patients who were discharged within the first 10 days of each month were excluded. We explored and compared aggressive treatments such as cardiopulmonary resuscitation and intensive care utilization, performed within seven days before death in cancer patients. We used 10,637 (0.4% of the dataset) deceased target population (40.0% female), with 7844 (73.7%) and 2793 (26.3%) being the proportion of cancer and heart disease patients, respectively. Aggressive treatments and procedures such as cardiopulmonary resuscitation (18.4%), intensive care utilization (5.4%), use of inotropes (43.4%), use of respirators (29.1%), and dialysis (4.5%) were frequently observed in heart disease patients. These associations remained after adjusting for age, sex, and disease severity. This study indicates the possible use of an NDB sampling dataset to evaluate the aggressive treatments and procedures in the actively dying phase in both heart disease and cancer patients. Our results showed the differences in aggressive treatment strategies in the actively dying phase between patients with cancer and those with heart disease.

Long-Term Outcomes of Acute Myocardial Infarction With Concomitant Cardiogenic Shock and Cardiac Arrest

This study sought to evaluate long-term mortality and major adverse cardiac and cerebrovascular events (MACCE) in patients with cardiac arrest (CA) and cardiogenic shock (CS) complicating acute myocardial infarction (AMI). This was a retrospective cohort study using an administrative claims database. AMI patients from January 1, 2010 to May 31, 2018 were stratified into CA + CS, CA only, CS only, and AMI alone cohorts. Outcomes of interest were long-term mortality and MACCE (death, AMI, cerebrovascular accident, unplanned revascularization) in AMI survivors. A total 163,071 AMI patients were included with CA + CS, CA only, and CS only in 2.4%, 5.0%, and 4.0%, respectively. The CA + CS cohort had higher rates of multiorgan failure, mechanical circulatory support use and less frequent coronary angiography use. In-hospital mortality was noted in 10,686 (6.6%) patients - CA + CS (48.8%), CA only (35.9%), CS only (24.1%), and AMI alone (2.9%; p < 0.001). Over 23.5 ± 21.7 months follow-up after hospital discharge, patients with CA + CS (hazard ratio [HR] 1.36 [95% confidence interval {CI} 1.19 to 1.55]), CA only (HR 1.16 [95% CI 1.08 to 1.25]), CS only (HR 1.39 [95% CI 1.29 to 1.50]) had higher all-cause mortality compared with AMI alone (all p < 0.001). Presence of CS, either alone (HR 1.22 [95% CI 1.16 to 1.29]; p < 0.001) or with CA (HR 1.18 [95% CI 1.07 to 1.29]; p < 0.001), was associated with higher MACCE compared with AMI alone. In conclusion, CA + CS, CA, and CS were associated with worse long-term survival. CA and CS continue to influence outcomes beyond the index hospitalization in AMI survivors.