Trends in the Quality of Primary Care and Acute Care in Korea From 2008 to 2020: A Cross-sectional Study.

OBJECTIVES: Measuring the quality of care is paramount to inform policies for healthcare services. Nevertheless, little is known about the quality of primary care and acute care provided in Korea. This study investigated trends in the quality of primary care and acute care. METHODS: Case-fatality rates and avoidable hospitalization rates were used as performance indicators to assess the quality of primary care and acute care. Admission data for the period 2008 to 2020 were extracted from the National Health Insurance Claims Database. Case-fatality rates and avoidable hospitalization rates were standardized by age and sex to adjust for patients' characteristics over time, and significant changes in the rates were identified by joinpoint regression. RESULTS: The average annual percent change in age-/sex-standardized case-fatality rates for acute myocardial infarction was -2.3% (95% confidence interval, -4.6 to 0.0). For hemorrhagic and ischemic stroke, the age-/sex-standardized case-fatality rates were 21.8% and 5.9%, respectively in 2020; these rates decreased since 2008 (27.1 and 8.7%, respectively). The average annual percent change in age-/sex-standardized avoidable hospitalization rates ranged from -9.4% to -3.0%, with statistically significant changes between 2008 and 2020. In 2020, the avoidable hospitalization rates decreased considerably compared with the 2019 rate because of the coronavirus disease 2019 pandemic. CONCLUSIONS: The avoidable hospitalization rates and case-fatality rates decreased overall during the past decade, but they were relatively high compared with other countries. Strengthening primary care is an essential requirement to improve patient health outcomes in the rapidly aging Korean population.

Disability Evaluations: Common Questions and Answers

Disability is a physical or mental impairment that substantially limits at least one major life activity. Family physicians are often asked to assess patients with disabling conditions that can impact insurance benefits, employment, and ability to access needed accommodations. Disability evaluations are needed for short-term work restrictions following a simple injury or illness and for more complex cases involving Social Security Disability Insurance, Supplemental Security Income, Family and Medical Leave Act, workers' compensation, and personal/private disability insurance claims. Using a stepwise approach built on awareness of the biologic, psychological, and social elements of disability assessment may facilitate this evaluation. Step 1 establishes the role of the physician in the disability evaluation process and the context of the request. In Step 2, the physician assesses impairments and establishes a diagnosis based on findings from an examination and validated diagnostic tools. In Step 3, the physician identifies specific participation restrictions by assessing the patient's ability to perform specific movements or activities and reviewing the employment environment and tasks. Steps 4 and 5 ensure proper documentation, billing, and coding. In complex cases, consultants such as psychiatrists and physical therapists may assist by providing insight into a patient's mental and physical impairments, activity limitations, and response to treatment. (Am Fam Physician. 2023;107(5):490–498. Copyright © 2023 American Academy of Family Physicians.)

Changes in the Characteristics and Outcomes of COVID-19 Patients from the Early Pandemic to the Delta Variant Epidemic: A Nationwide Population-based Study.

The coronavirus disease 2019 (COVID-19) pandemic has dramatically changed because of virus mutations, vaccine dissemination, treatment development and policies, among other factors. These factors have a dynamic and complex effect on the characteristics and outcomes of patients. Therefore, there is an urgent need to understand those changes and update the evidence. We used a large-scale real-world data set of 937,758 patients with COVID-19 from a nationwide claims database that included outpatients and inpatients in Japan to investigate the changes in their characteristics, outcomes and risk factors for severity/mortality from the early pandemic to the delta variant-predominant waves. The severity of COVID-19 was defined according to the modified World Health Organization clinical-progression ordinal scale. With changing waves, mean patient age decreased, and proportion of patients with comorbidities decreased. The incidences of "severe COVID-19 or death (i.e. ≥severe COVID-19)" and "death" markedly declined (5.0% and 2.9%, wild-type-predominant; 4.6% and 2.2%, alpha variant-predominant and 1.4% and 0.4%, delta variant-predominant waves, respectively). Across the wave shift, risk factors for ≥severe COVID-19 and death, including older age, male, malignancy, congestive heart failure and chronic obstructive pulmonary disease, were largely consistent. The significance of some factors, such as liver disease, varied as per the wave. This study, one of the largest population-based studies on COVID-19, showed that patient characteristics and outcomes changed during the waves. Risk factors for severity/mortality were similar across all waves, but some factors were inconsistent. These data suggest that the clinical status of COVID-19 will change further with the coming epidemic wave.

Assessment of the Prescriptions of Systemic Antibiotics in Primary Dental Care in Germany from 2017 to 2021: A Longitudinal Drug Utilization Study.

(1) Background: Due to increasing antibiotic resistance, the frequency of antibiotic use should be questioned in dentistry and attention paid to the choice of the best suited substance according to guidelines. In Germany, overprescribing of clindamycin was noteworthy in the past. Therefore, the aim of our study was to determine the trend of antibiotic prescriptions in primary dental care. (2) Methods: Prescriptions of antibiotics in German primary dental care from 2017 to 2021 were analysed using dispensing data from community pharmacies, claimed to the statutory health insurance (SHI) funds, and compared with all antibiotic prescriptions in primary care. Prescriptions were analysed based on defined daily doses per 1000 SHI-insured persons per day (DID). (3) Results: Amoxicillin was the most frequently prescribed antibiotic (0.505 DID in 2017, 0.627 in 2021, +24.2%) in primary dental care, followed by clindamycin (0.374 DID in 2017, 0.294 in 2021, -21.4%). Dental prescriptions still made up 56% of all clindamycin prescriptions in primary care in 2021. (4) Conclusions: Our study suggests that the problem of overuse of clindamycin in German dentistry has improved, but still persists.

Characterizing Thrombotic Complication Risk Factors Associated With COVID-19 via Heterogeneous Patient Data: Retrospective Observational Study.

BACKGROUND: COVID-19 has been observed to be associated with venous and arterial thrombosis. The inflammatory disease prolongs hospitalization, and preexisting comorbidities can intensity the thrombotic burden in patients with COVID-19. However, venous thromboembolism, arterial thrombosis, and other vascular complications may go unnoticed in critical care settings. Early risk stratification is paramount in the COVID-19 patient population for proactive monitoring of thrombotic complications. OBJECTIVE: The aim of this exploratory research was to characterize thrombotic complication risk factors associated with COVID-19 using information from electronic health record (EHR) and insurance claims databases. The goal is to develop an approach for analysis using real-world data evidence that can be generalized to characterize thrombotic complications and additional conditions in other clinical settings as well, such as pneumonia or acute respiratory distress syndrome in COVID-19 patients or in the intensive care unit. METHODS: We extracted deidentified patient data from the insurance claims database IBM MarketScan, and formulated hypotheses on thrombotic complications in patients with COVID-19 with respect to patient demographic and clinical factors using logistic regression. The hypotheses were then verified with analysis of deidentified patient data from the Research Patient Data Registry (RPDR) Mass General Brigham (MGB) patient EHR database. Data were analyzed according to odds ratios, 95% CIs, and P values. RESULTS: The analysis identified significant predictors (P<.001) for thrombotic complications in 184,831 COVID-19 patients out of the millions of records from IBM MarketScan and the MGB RPDR. With respect to age groups, patients 60 years and older had higher odds (4.866 in MarketScan and 6.357 in RPDR) to have thrombotic complications than those under 60 years old. In terms of gender, men were more likely (odds ratio of 1.245 in MarketScan and 1.693 in RPDR) to have thrombotic complications than women. Among the preexisting comorbidities, patients with heart disease, cerebrovascular diseases, hypertension, and personal history of thrombosis all had significantly higher odds of developing a thrombotic complication. Cancer and obesity were also associated with odds>1. The results from RPDR validated the IBM MarketScan findings, as they were largely consistent and afford mutual enrichment. CONCLUSIONS: The analysis approach adopted in this study can work across heterogeneous databases from diverse organizations and thus facilitates collaboration. Searching through millions of patient records, the analysis helped to identify factors influencing a phenotype. Use of thrombotic complications in COVID-19 patients represents only a case study; however, the same design can be used across other disease areas by extracting corresponding disease-specific patient data from available databases.

Medical visits and health-care expenditures of patients attending orthopedic clinics during the COVID-19 pandemic in Japan: LIFE Study.

BACKGROUND: The first state of emergency for coronavirus disease 2019 (COVID-19) in Japan was imposed from April to May 2020. During that period, people were urged to avoid non-essential outings, which may have reduced their access to health care. METHODS: Using health-care claims data from a city in Fukuoka prefecture, Japan, we conducted a retrospective cohort study of the state of emergency's impact on patients' medical visits to orthopedic clinics and their associated health-care expenditures. These measures were compared between 2019 and 2020 using a year-over-year analysis and unpaired t-tests. RESULTS: The analysis showed that medical visits in 2020 significantly decreased by 23.7% in April (P < 0.01) and 17.6% in May (P < 0.01) when compared with the previous year. Similarly, monthly outpatient health-care expenditure significantly decreased by 2.4% (P < 0.01) in April 2020 when compared with April 2019. In contrast, the health-care expenditure per capita per visit significantly increased by 1.5% (P < 0.01) in June 2020 (after the state of emergency was lifted) when compared with June 2019. CONCLUSION: As orthopedic clinics in Japan are reimbursed using a fee-for-service system, the increases in per capita expenditures after the state of emergency may be indicative of physician-induced demand. However, we posit that it is more likely that a post-emergency increase in anti-inflammatory and analgesic treatments for spondylopathies, low back pain and sciatica induced a temporary rise in these expenditures.

Breast cancer diagnosis and treatment during the COVID-19 pandemic in a nationwide, insured population.

PURPOSE: The early months of the COVID-19 pandemic led to reduced cancer screenings and delayed cancer surgeries. We used insurance claims data to understand how breast cancer incidence and treatment after diagnosis changed nationwide over the course of the pandemic. METHODS: Using the Optum Research Database from January 2017 to March 2021, including approximately 19 million US adults with commercial health insurance, we identified new breast cancer diagnoses and first treatment after diagnosis. We compared breast cancer incidence and proportion of newly diagnosed patients receiving pre-operative systemic therapy pre-COVID, in the first 2 months of the COVID pandemic and in the later part of the COVID pandemic. RESULTS: Average monthly breast cancer incidence was 19.3 (95% CI 19.1-19.5) cases per 100,000 women and men pre-COVID, 11.6 (95% CI 10.8-12.4) per 100,000 in April-May 2020, and 19.7 (95% CI 19.3-20.1) per 100,000 in June 2020-February 2021. Use of pre-operative systemic therapy was 12.0% (11.7-12.4) pre-COVID, 37.7% (34.9-40.7) for patients diagnosed March-April 2020, and 14.8% (14.0-15.7) for patients diagnosed May 2020-January 2021. The changes in breast cancer incidence across the pandemic did not vary by demographic factors. Use of pre-operative systemic therapy across the pandemic varied by geographic region, but not by area socioeconomic deprivation or race/ethnicity. CONCLUSION: In this US-insured population, the dramatic changes in breast cancer incidence and the use of pre-operative systemic therapy experienced in the first 2 months of the pandemic did not persist, although a modest change in the initial management of breast cancer continued.

The association between statin and COVID-19 adverse outcomes: national COVID-19 cohort in South Korea.

BACKGROUND: There currently exist limited and conflicting clinical data on the use of statins in coronavirus disease 2019 (COVID-19) patients. The aim of this paper was to compare hospitalized patients with COVID-19 who did and did not receive statins. METHODS: We performed a population-based retrospective cohort study using South Korea's nationwide healthcare claim database. We identified consecutive patients hospitalized with COVID-19 and aged 40 years or older. Statin users were individuals with inpatient and outpatient prescription records of statins in the 240 days before cohort entry to capture patients who are chronic statin users and, therefore, receive statin prescriptions as infrequently as every 8 months. Our primary endpoint was a composite of all-cause death, intensive care unit (ICU) admission, mechanical ventilation use and cardiovascular outcomes [myocardial infarction (MI), transient cerebral ischemic attacks (TIA) or stroke]. We compared the risk of outcomes between statin users and non-users using logistic regression models after inverse probability of treatment weighting (IPTW) adjustment. RESULTS: Of 234,427 subjects in the database, 4,349 patients were hospitalized with COVID-19 and aged 40+ years. In total, 1,115 patients were statin users (mean age =65.9 years; 60% female), and 3,234 were non-users (mean age =58.3 years; 64% female). Pre-hospitalization statin use was not significantly associated with increased risk of the primary endpoint [IPTW odds ratio (OR) 0.82; 95% confidence interval (CI): 0.60-1.11]. Subgroup analysis showed a protective role of antecedent statin use for individuals with hypertension (IPTW OR 0.40; 95% CI: 0.23-0.69, P for interaction: 0.0087). CONCLUSIONS: Pre-hospitalization statin use is not detrimental and may be beneficial amongst hypertensive COVID-19 patients. Further investigation into statin is needed for more conclusive effects of statins for treatment of COVID-19.

Delivering Unemployment Assistance in Times of Crisis: Scalable Cloud Solutions Can Keep Essential Government Programs Running and Supporting Those in Need

The COVID-19 public health emergency caused widespread economic shutdown and unemployment. The resulting surge in Unemployment Insurance claims threatened to overwhelm the legacy systems state workforce agencies rely on to collect, process, and pay claims. In Rhode Island, we developed a scalable cloud solution to collect Pandemic Unemployment Assistance claims as part of a new program created under the Coronavirus Aid, Relief and Economic Security Act to extend unemployment benefits to independent contractors and gig-economy workers not covered by traditional Unemployment Insurance. Our new system was developed, tested, and deployed within 10 days following the passage of the Coronavirus Aid, Relief and Economic Security Act, making Rhode Island the first state in the nation to collect, validate, and pay Pandemic Unemployment Assistance claims. A cloud-enhanced interactive voice response system was deployed a week later to handle the corresponding surge in weekly certifications for continuing unemployment benefits. Cloud solutions can augment legacy systems by offloading processes that are more efficiently handled in modern scalable systems, reserving the limited resources of legacy systems for what they were originally designed. This agile use of combined technologies allowed Rhode Island to deliver timely Pandemic Unemployment Assistance benefits with an estimated cost savings of $502,000 (representing a 411% return on investment). © 2020 Owner/Author.

How regulatory changes are driven by a need for control in reputational scandals: a case study in the German insurance industry

PurposeThis paper aims to contribute to the understanding of the mechanisms that evolve during reputational scandals and lead to changes in industry regulation. It explores the processes by which a demand for external industry regulation evolves, also addressing the consequences of firms’ competitive behaviors which lead to substantial misbehavior and the destruction of reputational capital. The authors are interested in whether and how regulatory activities – in the case analyzed here, changes in insurance regulation regarding sales commissions for insurance brokers – are used as a costly, external behavioral control mechanism (third-loop learning) to terminate a reputational scandal that cannot be stopped by internal controls at a firm level (first-loop and second-loop learning) anymore.Design/methodology/approachThe paper explores a real-life case in the German insurance industry that peaked in 2012 and has been well documented by broad media coverage, complemented by interviews with leading industry representatives. Using causal process tracing as a methodology, the authors study the factors in the case that led to an industry scandal. The authors further analyze why the insurance firms involved were not able to limit the scandal’s impact by internally controlling their behaviors, but had to call for external regulation, thus imposing costly restrictions on sales and contract processes. To identify the mechanisms underlying this result, theories from the fields of economics (game theory) and sociology (vicious cycle of bureaucracies), as well as organizational learning theory, are used.FindingsThe authors find that individual rationality does not suffice to prevent insurance firms from scandalous business practices, e.g. via implementing appropriate internal behavioral control measures within their organizations. If, as a result, misbehavior leads to reputational scandals, and the destruction of reputational capital spills over to the whole industry, a vicious cycle is set in motion which can be terminated by regulation as an externally enforced control mechanism.Research limitations/implicationsThis study is limited to the analysis of a single case study, combining published materials, e.g. broad media coverage, with interviews from representatives of the insurance industry. Nevertheless, the underlying mechanisms that have been identified can be used in other case studies as well.Practical implicationsThe paper shows that if firms want to avoid increasing regulation, they must implement strong reputational risk management (RRM) to counteract short-term profit pressure and to avoid restrictive regulation imposed on the industry as a whole. Furthermore, it sheds light on the relevance of spillover effects for RRM, as not only employee behavior within an organization might lead to the destruction of reputational capital but also that from other firms, e.g. from elsewhere within an industry.Originality/valueThe paper contributes by emphasizing a direct causal link between corporate scandals, loss of reputation and regulatory change within the insurance industry. Furthermore, the paper contributes by combining economic theories with organizational theories to understand real-life phenomena.

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.

The Impact of COVID-19 on Hospital Admissions for Twelve High-Burden Diseases and Five Common Procedures in the Philippines: A National Health Insurance Database Study 2019-2020.

BACKGROUND: The Philippines has the highest cumulative COVID-19 cases and deaths in the Western-Pacific. To explore the broader health impacts of the pandemic, we assessed the magnitude and duration of changes in hospital admissions for 12 high-burden diseases and the utilization of five common procedures by lockdown stringency, hospital level, and equity in patient access. METHODS: Our analysis used Philippine social health insurance data filed by 1,295 hospitals in 2019 and 2020. We calculated three descriptive statistics of percent change comparing 2020 to the same periods in 2019: (1) year-on-year, (2) same-month-prior-year, and (3) lockdown periods. FINDINGS: Disease admissions declined (-54%) while procedures increased (13%) in 2020 versus 2019. The increase in procedures was caused by hemodialysis surpassing its 2019 utilization levels in 2020 by 25%, overshadowing declines for C-section (-5%) and vaginal delivery (-18%). Comparing months in 2020 to the same months in 2019, the declines in admissions and procedures occurred at pandemic onset (March-April 2020), with some recovery starting May, but were generally not reversed by the end of 2020. Non-urgent procedures and respiratory diseases faced the largest declines in April 2020 versus April 2019 (range: -60% to -70%), followed by diseases requiring regular follow-up (-50% to -56%), then urgent conditions (-4% to -40%). During the strictest (April-May 2020) and relaxed (May-December 2020) lockdown periods compared to the same periods in 2019, the declines among the poorest (-21%, -39%) were three-times greater than in direct contributors (-7%, -12%) and two-times more in the south (-16%, -32%) than the richer north (-8%, -10%). Year-on-year admission declines across the 12 diseases and procedures (except for hemodialysis) was highest for level three hospitals. Compared to public hospitals, private hospitals had smaller year-on-year declines for procedures, because of increases in utilization in lower level private hospitals. INTERPRETATION: COVID-19's prolonged impact on the utilization of hospital services in the Philippines suggests a looming public health crisis in countries with frail health systems. Through the periodic waves of COVID-19 and lockdowns, policymakers must employ a whole-of-health strategy considering all conditions, service delivery networks, and access for the most vulnerable. FUNDING: Open Philanthropy.

Unemployment insurance claims and COVID-19.

We explore the effect of various factors on interstate differences in weekly unemployment insurance claims, focusing specifically on the determinants over the initial period of the pandemic in the U.S. We consider the effects of COVID-19 cases, state policies enacted in response to COVID-19, relevant provisions of Federal Coronavirus Aid, Relief and Economic Security (CARES) legislation, and the nature of state economies. We find that during the initial weeks of the pandemic, unemployment claims were driven by consumer reactions to the coronavirus. We find that over the March 21-April 25 period states with greater employment in industries most affected by the virus and which issued orders closing nonessential businesses experienced greater weekly unemployment claims. We find mixed evidence that unemployment benefits affect the number of unemployment claims. However, we find no evidence that the ability to work at home mitigated the increase in unemployment rates during this period, nor evidence that the CARES Act's Payroll Protection Program influenced the level of new unemployment claims.