Annual variation of estimated glomerular filtration rate in health check-ups associated with end-stage kidney disease.

Estimated glomerular filtration rate (eGFR) variation is associated with end-stage kidney disease (ESKD) development in patients with chronic kidney disease; whether annual variations in eGFR at health check-ups is associated with ESKD risk in the general population is unclear. We conducted a retrospective cohort study using Japanese national medical insurance claims from 2013 to 2020. Individuals who had their eGFR levels measured three times in annual health check-ups were included (N = 115,191), and the coefficient of variation of eGFR (CVeGFR) was calculated from 3-point eGFR. The end-point was ESKD as reported in the claims data. We analyzed the association between CVeGFR and ESKD incidence after adjusting for conventional ESKD risk factors. The CVeGFR median distribution was 5.7% (interquartile range: 3.5-8.5%). During a median follow-up period of 3.74 years, 164 patients progressed to ESKD. ESKD incidence was significantly higher in the highest quartile group (CVeGFR ≥ 8.5%) than in the other groups (P < 0.0001). After adjusting for risk factors, individuals with CVeGFR ≥ 8.5% had a significantly high ESKD incidence (adjusted hazard ratio: 3.01; 95% CI 2.14-4.30). High CVeGFR in annual health check-ups was associated with high ESKD incidence, independent of its other conventional risk factors, in the general population.

An open repository of real-time COVID-19 indicators.

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Potential Undiagnosed VWD Or Other Mucocutaneous Bleeding Disorder Cases Estimated From Private Medical Insurance Claims.

INTRODUCTION: Von Willebrand disease (VWD) is a common inherited bleeding disorder, but awareness among health care professionals is low. We estimated the number of cases of undiagnosed VWD or other mucocutaneous bleeding disorders among commercially insured patients in the United States with a recent history of bleeding events. METHODS: Patients with a VWD diagnosis who were users of or candidates for von Willebrand factor replacement were identified from the IMS PharMetrics Plus Database (2006-2015). We constructed a unary patient-finding model based on 12 prediagnosis variables that best defined this population, and applied this to undiagnosed patients with recent bleeding events from the same database. Cases of symptomatic undiagnosed VWD or other mucocutaneous bleeding disorders in the commercially insured population were estimated from the "best fit" (positive predictive value [PPV] 83%) and "good fit" (PPV 75%) patients thus identified. RESULTS: Overall, 507,668 undiagnosed patients with recent bleeding events were identified (86% female, 14% male). Application of the VWD model identified 3318 best-fit and 37,163 good-fit patients; 91% of best-fit patients were females aged <46 years, with heavy menstrual bleeding as the most common claim. Projection to the full commercially insured US population suggested that 35,000-387,000 patients may have symptomatic, undiagnosed VWD or other mucocutaneous bleeding disorders. DISCUSSION: Computer modeling suggests there may be a significant number of patients with symptomatic, undiagnosed VWD or other mucocutaneous bleeding disorder in the commercially insured population. Enhanced awareness of VWD symptoms and their impact, and of screening and testing procedures, may improve the diagnosis of VWD and reduce disease burden.

Epidemiology of hyperhidrosis in 2 population-based health care databases.

BACKGROUND: Population-based and clinical case reports of hyperhidrosis (HH) provide prevalence estimates that vary widely across reported studies because of differences in case ascertainment. OBJECTIVE: In this study, we specify diagnostic, symptom, and prescription codes for HH to estimate incidence and prevalence for the United Kingdom and the United States. METHODS: Data from UK and US health care databases were analyzed to ascertain HH cases and estimate incidence and prevalence from health care records during calendar years 2011 through 2013. RESULTS: On the basis of 2013 data for the United States and United Kingdom, between 1.0% and 1.6% of these populations have health care records indicating diagnosis or treatment of HH. Women accounted for approximately 60% of incident and prevalent cases in both databases. LIMITATIONS: Because the case ascertainment methods rely on available data for those seeking health care, we may have underestimated the number of HH cases in both countries. CONCLUSIONS: The findings represent a plausible estimate for incidence and prevalence of HH among persons seeking medical care for excessive sweating. Improved practices for identifying HH in clinical settings may increase the sensitivity and specificity of future studies and improve characterization and quantification of the population burden of this significant disease.

Real-world burden of comorbidities in US patients with psoriasis.

BACKGROUND: Understanding background comorbidity rates in psoriasis can provide perspective for adverse events associated with new therapies. OBJECTIVE: We sought to assess the extent of comorbidities in psoriasis patients by use of the Truven Health Analytics MarketScan database. METHODS: MarketScan, comprising commercial claims representative of a large US-insured population, had 1.22 million patients with ≥1 claim with a psoriasis diagnosis between January 1, 2008, and December 31, 2014. Patients ≥18 years of age who had ≥2 health claims in any diagnosis field for psoriasis (International Classification of Diseases, 9th Revision, Clinical Modification 696.1) with a psoriasis diagnosis (index) date between July 1, 2008, and June 30, 2014, were included to allow follow-up observation time. RESULTS: Prevalence and incidence of 24 comorbidities were assessed in 469,097 psoriasis patients; the most common comorbidities were hyperlipidemia (45.64% and 30.83%, respectively), hypertension (42.19% and 24.19%), depression (17.91% and 12.68%), type 2 diabetes mellitus (17.45% and 8.44%), and obesity (14.38% and 11.57%). LIMITATIONS: A limitation of the study was that only a certain insured population was represented. CONCLUSIONS: Comorbidity rates align with those described in the literature and support the concept that psoriasis patients have high rates of cardiometabolic comorbidities. This analysis highlights the potential utility of very large insurance databases for determining comorbidity prevalence in psoriasis, which may aid health care providers in managing psoriasis.

Sensitivity of Medical Insurance Claims Data Using Population-based Cancer Registry Data / 대한의료정보학회지

Although medical insurance claims data provide an increasingly accessible and widely used source of data for health care research, there are few studies about their sensitivity. This study was conducted to investigate the sensitivity of diagnosed cancers in medical insurance claims data. Every case of Kwangju Cancer Registry registered during 1998-1999 was checked for its status in medical insurance claims. The sensitivity of medical insurance claims was expressed as the proportion of cases who were reported as having cancer among cancer registry cases. The sensitivities of Kwangju and nationwide medical insurance claims data for overall cancer were 87.2% and 92.8%, respectively. For cancer sites, the sensitivity of medical insurance claims data was the highest for breast, followed by thyroid, lymphoma and colorectum, and the lowest for pancreas and kidney. Medical insurance claims data would provide reasonably high sensitivity for the detection of cancer, especially if nationwide medical insurance claims are included. Further studies should examine false positive cases to measure other dimensions of accuracy, such as specificity and predictive value.

The accuracy of myocardial infarction diagnosis in medical insurance claims. Korean Research Group for Cardiovascular Disease Prevention and Control

We attempted to assess the accuracy of the International Classification of Diseases (ICD) codes for myocardial infarction (MI) in medical insurance claims, and to investigate the reasons for any inaccuracy. This study was designed as a preliminary study to establish a surveillance system for cardiovascular diseases in Korea. A sample of 258 male patients who were diagnosed with MI from 1993 to 1997 was selected from the Korea Medical Insurance Corporation cohort (KMIC cohort: 183,461 people). The registered medical record administrators were trained in the survey technique, and gathered data by investigating the medical records of the study subjects from March 1999 to May 1999. The definition of MI for this study included symptoms pursuant to the diagnostic criteria of chest pain, electrocardiogram (ECG) findings, cardiac enzyme and results of coronary angiography or nuclear scan. We asked the record administrators for the reasons of incorrectness for cases where the final diagnosis was 'not MI'. The accuracy rate of the ICD codes for MI in medical insurance claims was 76.0% (196 cases) of the study sample, and 3.9% (ten cases) of the medical records were not available due to hospital closures, non-computerization or missing information. Nineteen cases (7.4%) were classified as insufficient due to insufficient records of chest pain, ECG findings, or cardiac enzymes. The major reason of inaccuracy in the disease code for MI in medical insurance claims was 'to meet the review criteria of medical insurance benefits (45.5%)'. The department responsible for the inaccuracy was the department of inspection for medical insurance benefit of the hospitals.

The Accuracy of ICD codes for Cerebrovascular Diseases in Medical Insurance Claims / 예방의학회지

OBJECTIVES: We attempted to assess the accuracy of ICD codes for cerebrovascular diseases in medical insurance claims (ICMIC) and to investigate the reasons for error. This study was designed as a preliminary study to establish a nationwide surveillance system. METHODS: A total of 626 patients with medical insurance claims who indicated a diagnosis of cerebrovascular diseases during the period from 1993 to 1997 was selected from the Korea Medical Insurance Corporation cohort (KMIC cohort: 115,600 persons). The KMIC cohort was 10% of those insured who had taken health examinations in 1990 and 1992 consecutively. The registered medical record administrators were trained in the survey technique and gathered data from March to May 1999. The definition of cerebrovascular diseases in this study included cases which met one of two criteria (Minnesota, WHO) or 'definite stroke' in CT/MRI finding. We questioned the medical record administrators to explain the error if the final diagnoses were not coded as stroke. RESULTS: The accuracy rate of the ICMIC was 83.0% (425 cases). Medical records were not available for 8.2% (51 cases) due to the closing of hospitals, the absence of a computer system or omission of medical record, etc. Sixty-three cases (10.0%) were classified as impossible to interpret due to insufficient records in 'major clinical symptoms' or 'neurological deficits'. The most common reason was 'to meet review criteria of medical insurance benefits (52.9%)'. The department where errors in the ICMIC occurred most frequently was the department for medical insurance claims in the hospital. CONCLUSION: The accuracy rate of the ICMIC was 83.0%.

Impacts of DRG Payment System on Behavior of Medical Insurance Claimants / 예방의학회지

OBJECTIVES: To evaluate the impacts of the DRG payment system on the behavior of medical insurance claimants. Specifically, we evaluated the case-mix index, the numbers of diagnosis and procedure codes utilized, and the corresponding rate of diagnosis codes before, during and after implementation of the DRG payment system. METHODS: In order to evaluate the case-mix index, the number of diagnosis and procedure codes utilized, we used medical insurance claim data from all medical facilities that participated in the DRG-based Prospective Payment Demonstration Program. This medical insurance claim data consisted of both pre-demonstration program data (fee-for-service, from November, 1998 to January, 1999) and post-demonstration program data (DRG-based Prospective Payment, from February, 1999 to April, 1999). And in order to evaluate the corresponding rate of diagnosis codes utilized, we reviewed 820 medical records from 20 medical institutes that were selected by random sampling methods. RESULTS: The case-mix index rate decreased after the DRG-based Prospective Payment Demonstration Program was introduced. The average numbers of different claim diagnosis codes used decreased (new DRGs from 2.22 to 1.24, and previous DRGs from 1.69 to 1.21), as did the average number of claim procedure codes used (new DRGs from 3.02 to 2.16, and previous DRGs from 2.97 to 2.43). With respect to the time of participation in the program, the change in number of claim procedure codes was significant, but the change in number of claim diagnosis codes was not. The corresponding rate of claim diagnosis codes increased (from 57.9% to 82.6%), as did the exclusion rate of claim diagnosis codes (from 16.5% to 25.1%). CONCLUSIONS: After the implementation of the DRG payment system, the corresponding rate of insurance claim codes and the corresponding exclusion rate of claim diagnosis codes both increased, because the inducement system for entering the codes for claim review was changed.

Incorrect Disease Coding in Medical Insurance Claims and the Effect of Official Intervention: Based on Medical Insurance Claims of 6 Notifiable Acute Communicable Diseases / 한국역학회지

BACKGROUND: Because of their large size and excellent computerized records of illness and services rendered, the importance of national insurance program is getting much attentions from the public health researchers and the national and local health authorities. In reality, however, most health records from medical insurance program suffer very much from inaccurate disease coding, and therefore, they are practically in no use. METHODS: Pattern of incorrect disease coding of 6 Notifiable Acute Communicable Diseases that believed not to have been occurred in Korea lately was reviewed. The reasons of such incorrect codings in different level of medical institutions were studied. This study also attempted to see how an official intervention asking the medical institutions to correct their coding behavior works by comparing the frequencies of incorrect disease coding before and after the intervention. RESULTS: Study results showed that more incorrect disease codings came from clinics than hospitals, and non-physician personnel in clinics and hospitals seemed to be responsible for most of the incorrect disease codings. Most frequent diseases coded incorrectly such as cholera and poliomyelitis were the ones that physicians and non-physician personnel in the clinics and hospitals had been familiar with for a long time period. CONCLUSION: Even a simple official intervention asking the clinics and hospitals to correct their coding behavior was very effective : total number of incorrect disease codings before intervention (398 cases from 144 institutions) dramatically decreased (14 cases from 8 institutions) after intervention. Significant decrease in incorrect disease coding was found more in small institutions such as clinics and public health facilities than large institutions.