Inappropriate laboratory test utilization in outpatient tertiary care: Implications for value-based healthcare.

OBJECTIVES: To assess the rate of inappropriate repetition of laboratory testing and estimate the cost of such testing for thyroid stimulating hormone (TSH), total cholesterol, vitamin D, and vitamin B12 tests. METHODS: A retrospective cohort study was carried out in the Family Medicine and Polyclinic Department at King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia. Clinical and laboratory data were collected between 2018-2021 for the 4 laboratory tests. The inappropriate repetition of tests was defined according to international guidelines and the costs were calculated using the hospital prices. RESULTS: A total of 109,929 laboratory tests carried out on 23,280 patients were included in this study. The percentage of inappropriate tests, as per the study criteria, was estimated to be 6.1% of all repeated tests. Additionally, the estimated total cost wasted amounted to 2,364,410 Saudi Riyals. Age exhibited a weak positive correlation with the total number of inappropriate tests (r=0.196, p=0.001). Furthermore, significant differences were observed in the medians of the total number of inappropriate tests among genders and nationalities (p<0.001). CONCLUSION: The study identified significantly high rates of inadequate repetitions of frequently requested laboratory tests. Urgent action is therefore crucial to overcoming such an issue.

Low-Value Care at the Actionable Level of Individual Health Systems.

Importance: Low-value health care remains prevalent in the US despite decades of work to measure and reduce such care. Efforts have been only modestly effective in part because the measurement of low-value care has largely been restricted to the national or regional level, limiting actionability. Objectives: To measure and report low-value care use across and within individual health systems and identify system characteristics associated with higher use using Medicare administrative data. Design, Setting, and Participants: This retrospective cohort study of health system-attributed Medicare beneficiaries was conducted among 556 health systems in the Agency for Healthcare Research and Quality Compendium of US Health Systems and included system-attributed beneficiaries who were older than 65 years, continuously enrolled in Medicare Parts A and B for at least 12 months in 2016 or 2017, and eligible for specific low-value services. Statistical analysis was conducted from January 26 to July 15, 2021. Main Outcomes and Measures: Use of 41 individual low-value services and a composite measure of the 28 most common services among system-attributed beneficiaries, standardized to distance from the mean value. Measures were based on the Milliman MedInsight Health Waste Calculator and published claims-based definitions. Results: Across 556 health systems serving a total of 11 637 763 beneficiaries, the mean (SD) use of each of the 41 low-value services ranged from 0% (0.01%) to 28% (4%) of eligible beneficiaries. The most common low-value services were preoperative laboratory testing (mean [SD] rate, 28% [4%] of eligible beneficiaries), prostate-specific antigen testing in men older than 70 years (mean [SD] rate, 27% [8%]), and use of antipsychotic medications in patients with dementia (mean [SD] rate, 24% [8%]). In multivariable analysis, the health system characteristics associated with higher use of low-value care were smaller proportion of primary care physicians (adjusted composite score, 0.15 [95% CI, 0.04-0.26] for systems with less than the median percentage of primary care physicians vs -0.16 [95% CI, -0.27 to -0.05] for those with more than the median percentage of primary care physicians; P < .001), no major teaching hospital (adjusted composite, 0.10 [95% CI, -0.01 to 0.20] without a teaching hospital vs -0.18 [95% CI, -0.34 to -0.02] with a teaching hospital; P = .01), larger proportion of non-White patients (adjusted composite, 0.15 [95% CI, -0.02 to 0.32] for systems with >20% of non-White beneficiaries vs -0.06 [95% CI, -0.16 to 0.03] for systems with ≤20% of non-White beneficiaries; P = .04), headquartered in the South or West (adjusted composite, 0.28 [95% CI, 0.14-0.43] for the South and 0.22 [95% CI, 0.02-0.42] for the West compared with -0.09 [95% CI, -0.26 to 0.08] for the Northeast and -0.44 [95% CI, -0.60 to -0.28] for the Midwest; P < .001), and serving areas with more health care spending (adjusted composite, 0.23 [95% CI, 0.11-0.35] for areas above the median level of spending vs -0.24 [95% CI, -0.36 to -0.12] for areas below the median level of spending; P < .001). Conclusions and Relevance: The findings of this large cohort study suggest that system-level measurement and reporting of specific low-value services is feasible, enables cross-system comparisons, and reveals a broad range of low-value care use.

HIT-It or Quit It: Heparin-Induced Thrombocytopenia Testing Appropriateness Using 4T Scoring and Inappropriate Testing Cost Analysis.

OBJECTIVES: The American Society of Hematology's 4T scoring system is a validated tool to assess a patient's probability of having heparin-induced thrombocytopenia (HIT) before testing is performed. There is no benefit to testing patients with a low probability 4T score for HIT. This study aimed to assess for inappropriate HIT testing at our institution based on 4T scoring. METHODS: We retrospectively reviewed 201 patient charts and calculated 4T scores and testing costs to assess for inappropriate testing and the economic impact of such testing. RESULTS: HIT testing often occurred in the least appropriate patients and resulted in tens of thousands of dollars of waste for unnecessary testing. CONCLUSIONS: Inappropriate testing for HIT is still a prevalent issue despite literature supporting the 4T score for guidance in testing appropriateness.

Medical Practice Variation Among Primary Care Physicians: 1 Decade, 14 Health Services, and 3,238,498 Patient-Years.

PURPOSE: Variation in medical practice is associated with poorer health outcomes, increased costs, disparities in care, and increased burden on the public health system. In the present study, we sought to describe and assess inter- and intra-primary care physician variation, adjusted for patient and clinic characteristics, over a decade of practice and across a broad range of health services. METHODS: We assessed practice patterns of 251 primary care physicians in southern Israel. For each of 14 health services (imaging tests, cardiac tests, laboratory tests, and specialist visits) we described interphysician and intraphysician variation, adjusted for patient case mix and clinic characteristics, using the coefficient of variation. The adjusted rates were assessed by generalized linear negative-binomial mixed models. RESULTS: The variation between physicians was on average 3-fold greater than the variation of individual physician practice over the years. Services with low utilization were associated with greater inter- and intraphysician variation: rs = (-0.58), P = .03 and rs = (-0.39), P = .17, respectively. In addition, physician utilization ranks averaged over all health services were consistent across the 14 health services (intraclass correlation coefficient, 0.94; 95% CI, 0.93-0.95). CONCLUSIONS: Our results show greater variation in practice patterns between physicians than for individual physicians over the years. It appears that the variation remains high even after adjustment for patient and clinic characteristics and that the individual physician utilization patterns are stable across health services. We propose that personal behavioral characteristics of medical practitioners might explain this variation.

Preoperative laboratory testing among low-risk patients prior to elective ambulatory endocrine surgeries: A review of the 2015-2018 NSQIP cohorts.

BACKGROUND: Preoperative laboratory tests (PLTs) are not associated with complications among healthy patients in various ambulatory procedures. This association has not been studied in ambulatory endocrine surgery. METHODS: The 2015-2018 NSQIP datasets were queried for elective outpatient thyroid and parathyroid procedures in ASA class 1 and 2 patients. Outcomes were compared between those with and without PLTs. Multivariate regression examined factors predictive of receiving PLTs. Testing costs were calculated. RESULTS: 58.7% of the cohort received PLTs. There were no differences in outcomes between those who were and those who were not tested. Non-white ethnicity, dyspnea, and non-general anesthesia were strongly predictive of receiving PLTs. Over $2.6 million is spent annually on PLTs in this population. CONCLUSIONS: Over half of healthy patients undergoing elective thyroid and parathyroid surgery receive PLTs. Complication rates did not differ between those with and without PLTs. Preoperative testing should be used more judiciously in these patients, which may lead to cost savings.

COVID-19 case-fatality rate and demographic and socioeconomic influencers: worldwide spatial regression analysis based on country-level data.

OBJECTIVE: To investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally. DESIGN: Publicly available register-based ecological study. SETTING: Two hundred and nine countries/territories in the world. PARTICIPANTS: Aggregated data including 10 445 656 confirmed COVID-19 cases. PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website. RESULTS: The average of country/territory-specific COVID-19 CFR is about 2%-3% worldwide and higher than previously reported at 0.7%-1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR. CONCLUSION: The association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.

The Utility of Preoperative Labs in Predicting Postoperative Complications Following Primary Total Hip and Knee Arthroplasty.

BACKGROUND: Preoperative testing costs billions of dollars despite little evidence supporting its utility. The purpose of this study was to determine the relationship between abnormal preoperative laboratory tests and postoperative complications following total joint arthroplasty. METHODS: The NSQIP database was used to identify 45,936 primary total hip arthroplasty (THA) and 76,041 pri-mary total knee arthroplasty (TKA) cases performed between 2006 and 2013. Complications within 30 days of surgery were collected and multivariable regression modeling was performed incorporating all significant laboratory values as well as demographics and preoperative comorbidities. RESULTS: For THA patients, abnormal sodium (p = 0.016, OR = 1.89), white count (p = 0.043, OR = 1.73), and partial thromboplastin time (p = 0.028, OR = 1.43) were significantly associated with complications. For TKA patients, abnormal alkaline phosphatase (p = 0.04, OR = 2.12), creatinine (p = 0.003, OR = 1.56), and INR (p = 0.008, OR = 1.99) were significantly predictive of complications. CONCLUSION: Of the 13 laboratory values, only six were significantly associated with complications. These findings may have implications for risk stratification in the inpatient setting.

Unmet clinical needs for COVID-19 tests in UK health and social care settings.

There is an urgent requirement to identify which clinical settings are in most need of COVID-19 tests and the priority role(s) for tests in these settings to accelerate the development of tests fit for purpose in health and social care across the UK. This study sought to identify and prioritize unmet clinical needs for COVID-19 tests across different settings within the UK health and social care sector via an online survey of health and social care professionals and policymakers. Four hundred and forty-seven responses were received between 22nd May and 15th June 2020. Hospitals and care homes were recognized as the settings with the greatest unmet clinical need for COVID-19 diagnostics, despite reporting more access to laboratory molecular testing than other settings. Hospital staff identified a need for diagnostic tests for symptomatic workers and patients. In contrast, care home staff expressed an urgency for screening at the front door to protect high-risk residents and limit transmission. The length of time to test result was considered a widespread problem with current testing across all settings. Rapid tests for staff were regarded as an area of need across general practice and dental settings alongside tests to limit antibiotics use.

Assessment of early mitigation measures against COVID-19 in Puerto Rico: March 15-May 15, 2020.

On March 15, 2020 Puerto Rico implemented non-pharmaceutical interventions (NPIs), including a mandatory curfew, as part of a state of emergency declaration to prevent the community transmission of the SARS-CoV-2 virus. The strict enforcement of this curfew was extended through May 25, with a gradual relaxation beginning on May 1. This report summarizes an assessment of these early mitigation measures on the progression of the COVID-19 pandemic in the island. From March 15 to May 15, 2020, 70,656 results of molecular (RT-PCR) tests were reported to the Puerto Rico Department of Health. Of these, 1,704 were positive, corresponding to 1,311 individuals with COVID-19 included in the study. We derived the epidemic growth rates (r) and the corresponding reproductive numbers (R) from the epidemic curve of these 1,311 individuals with laboratory-confirmed diagnosis of COVID-19 using their date of test collection as a proxy for symptoms onset. Through May 31, 2020, there were 143 COVID-19 associated deaths in Puerto Rico, for a case fatality risk of 10.9%. We compared the observed cases and deaths with Gompertz model projections had the mitigation measures not been implemented. The number of daily RT-PCR-confirmed cases peaked on March 30 (85 cases), showing a weekly cyclical trend, with lower counts on weekends and a decreasing secular trend since March 30. The initial exponential growth rate (r) was 15.87% (95% CI: 7.59%, 24.15%), corresponding to R of 1.82 (95% CI:1.37, 2.30). After March 30, the r value reverted to an exponential decay rate (negative) of -2.95% (95% CI: -4.99%, -0.92%), corresponding to R of 0.93 (95% CI: 0.86, 0.98). We estimate that, had the initial growth rate been maintained, a total of 6,155 additional COVID-19 cases would have occurred by May 15, with 211 additional COVID-19 deaths by May 31. These findings are consistent with very effective implementation of early NPIs as mitigation measures in Puerto Rico. These results also provide a baseline to assess the impact of the transition from mitigation to subsequent containment stages in Puerto Rico.

Outcome Disparities Among Men and Women With COVID-19: An Analysis of the New York City Population Cohort.

BACKGROUND: Growing evidence suggests a possible sex disparity in COVID-19 disease related outcomes. OBJECTIVE: To explore the sex disparity in COVID-19 cases and outcomes using New York City (NYC) population level data. SETTING: NYC surveillance data from February 29 to June 12, 2020. PARTICIPANTS: Individuals tested for COVID-19 in metropolitan NYC.Outcome Measurements and Statistical Analysis: Outcomes of interest included rates of COVID-19 case positivity, hospitalization and death. Relative risks and case fatality rates were computed for all outcomes based on sex and were stratified by age groups. RESULTS AND LIMITATIONS: 911,310 individuals were included, of whom 434,273 (47.65%) were male and 477,037 (52.35%) were female. Men represented the majority of positive cases (n=106,275, 51.36%), a majority of hospitalizations (n=29,847, 56.44%), and a majority of deaths (n=13,054, 59.23%). Following population level adjustments for age and sex, testing rates of men and women were equivalent. The majority of positive cases and hospitalizations occurred in men for all age groups except age >75 years, and death was more likely in men of all age groups. Men were at a statistically significant greater relative risk of case positivity, hospitalization, and death across all age groups except those <18 years of age. The most significant difference for case positivity was observed in the 65–74 age group (RR 1.22, 95%CI 1.19–1.24), for hospitalization in the 45–65 age group (RR 1.85, 95% 1.80–1.90), and for death in the 18–44 age group (RR 3.30, 95% CI 2.82–3.87). Case fatality rates were greater for men in all age-matched comparisons to women. Limitations include the use of an evolving surveillance data set and absence of further demographic characteristics such as ethnographic data. CONCLUSION: Men have higher rates of COVID-19 positivity, hospitalization, and death despite greater testing of women; this trend remains after stratification by age. J Drugs Dermatol. 2020;19(10):960-967. doi:10.36849/JDD.2020.5590.

Impact of COVID-19 epidemic curtailment strategies in selected Indian states: An analysis by reproduction number and doubling time with incidence modelling.

The Government of India in-network with the state governments has implemented the epidemic curtailment strategies inclusive of case-isolation, quarantine and lockdown in response to ongoing novel coronavirus (COVID-19) outbreak. In this manuscript, we attempt to estimate the impact of these steps across ten selected Indian states using crowd-sourced data. The trajectory of the outbreak was parameterized by the reproduction number (R0), doubling time, and growth rate. These parameters were estimated at two time-periods after the enforcement of the lockdown on 24th March 2020, i.e. 15 days into lockdown and 30 days into lockdown. The authors used a crowd sourced database which is available in the public domain. After preparing the data for analysis, R0 was estimated using maximum likelihood (ML) method which is based on the expectation minimum algorithm where the distribution probability of secondary cases is maximized using the serial interval discretization. The doubling time and growth rate were estimated by the natural log transformation of the exponential growth equation. The overall analysis shows decreasing trends in time-varying reproduction numbers (R(t)) and growth rate (with a few exceptions) and increasing trends in doubling time. The curtailment strategies employed by the Indian government seem to be effective in reducing the transmission parameters of the COVID-19 epidemic. The estimated R(t) are still above the threshold of 1, and the resultant absolute case numbers show an increase with time. Future curtailment and mitigation strategies thus may take into account these findings while formulating further course of action.

Optimising triage procedures for patients with cancer needing active anticancer treatment in the COVID-19 era.

BACKGROUND: Immunosuppression induced by anticancer therapy in a COVID-19-positive asymptomatic patient with cancer may have a devastating effect and, eventually, be lethal. To identify asymptomatic cases among patients receiving active cancer treatment, the Federico II University Hospital in Naples performs rapid serological tests in addition to hospital standard clinical triage for COVID-19 infection. METHODS: From 6 to 17 April 2020, all candidates for chemotherapy, radiotherapy or target/immunotherapy, if negative at the standard clinical triage on the day scheduled for anticancer treatment, received a rapid serological test on peripheral blood for COVID-19 IgM and IgG detection. In case of COVID-19 IgM and/or IgG positivity, patients underwent a real-time PCR (RT-PCR) SARS-CoV-2 test to confirm infection, and active cancer treatment was delayed. RESULTS: Overall 466 patients, negative for COVID-19 symptoms, underwent serological testing in addition to standard clinical triage. The average age was 61 years (range 25-88 years). Most patients (190, 40.8%) had breast cancer, and chemotherapy with or without immunotherapy was administered in 323 (69.3%) patients. Overall 433 (92.9%) patients were IgG-negative and IgM-negative, and 33 (7.1%) were IgM-positive and/or IgG-positive. Among the latter patients, 18 (3.9%), 11 (2.4%) and 4 (0.9%) were IgM-negative/IgG-positive, IgM-positive/IgG-negative and IgM-positive/IgG-positive, respectively. All 33 patients with a positive serological test, tested negative for RT-PCR SARS-CoV-2 test. No patient in our cohort developed symptoms suggestive of active COVID-19 infection. CONCLUSION: Rapid serological testing at hospital admission failed to detect active asymptomatic COVID-19 infection. Moreover, it entailed additional economic and human resources, delayed therapy administrationand increased hospital accesses.

Disparities in COVID-19 Incidence, Hospitalizations, and Testing, by Area-Level Deprivation - Utah, March 3-July 9, 2020.

Coronavirus disease 2019 (COVID-19) has had a substantial impact on racial and ethnic minority populations and essential workers in the United States, but the role of geographic social and economic inequities (i.e., deprivation) in these disparities has not been examined (1,2). As of July 9, 2020, Utah had reported 27,356 confirmed COVID-19 cases. To better understand how area-level deprivation might reinforce ethnic, racial, and workplace-based COVID-19 inequities (3), the Utah Department of Health (UDOH) analyzed confirmed cases of infection with SARS-CoV-2 (the virus that causes COVID-19), COVID-19 hospitalizations, and SARS-CoV-2 testing rates in relation to deprivation as measured by Utah's Health Improvement Index (HII) (4). Age-weighted odds ratios (weighted ORs) were calculated by weighting rates for four age groups (≤24, 25-44, 45-64, and ≥65 years) to a 2000 U.S. Census age-standardized population. Odds of infection increased with level of deprivation and were two times greater in high-deprivation areas (weighted OR = 2.08; 95% confidence interval [CI] = 1.99-2.17) and three times greater (weighted OR = 3.11; 95% CI = 2.98-3.24) in very high-deprivation areas, compared with those in very low-deprivation areas. Odds of hospitalization and testing also increased with deprivation, but to a lesser extent. Local jurisdictions should use measures of deprivation and other social determinants of health to enhance transmission reduction strategies (e.g., increasing availability and accessibility of SARS-CoV-2 testing and distributing prevention guidance) to areas with greatest need. These strategies might include increasing availability and accessibility of SARS-CoV-2 testing, contact tracing, isolation options, preventive care, disease management, and prevention guidance to facilities (e.g., clinics, community centers, and businesses) in areas with high levels of deprivation.

Utility-Based Multicriteria Model for Screening Patients under the COVID-19 Pandemic.

In this paper, a utility-based multicriteria model is proposed to support the physicians to deal with an important medical decision-the screening decision problem-given the squeeze put on resources due to the COVID-19 pandemic. Since the COVID-19 emerged, the number of patients with an acute respiratory failure has increased in the health units. This chaotic situation has led to a deficiency in health resources. Thus, this study, using the concepts of the multiattribute utility theory (MAUT), puts forward a mathematical model to aid physicians in the screening decision problem. The model is used to generate which of the three alternatives is the best one for where patients with suspected COVID-19 should be treated, namely, an intensive care unit (ICU), a hospital ward, or at home in isolation. Also, a decision information system, called SIDTriagem, is constructed and illustrated to operate the mathematical model proposed.

Business Closures, Stay-at-Home Restrictions, and COVID-19 Testing Outcomes in New York City.

INTRODUCTION: In response to the coronavirus disease 2019 (COVID-19) pandemic, New York City closed all nonessential businesses and restricted the out-of-home activities of residents as of March 22, 2020. This order affected different neighborhoods differently, as stores and workplaces are not randomly distributed across the city, and different populations may have responded differently to the out-of-home restrictions. This study examines how the business closures and activity restrictions affected COVID-19 testing results. An evaluation of whether such actions slowed the spread of the pandemic is a crucial step in designing effective public health policies. METHODS: Daily data on the fraction of COVID-19 tests yielding a positive result at the zip code level were analyzed in relation to the number of visits to local businesses (based on smartphone location) and the number of smartphones that stayed fixed at their home location. The regression model also included vectors of fixed effects for the day of the week, the calendar date, and the zip code of residence. RESULTS: A large number of visits to local businesses increased the positivity rate of COVID-19 tests, while a large number of smartphones that stayed at home decreased it. A doubling in the relative number of visits increases the positivity rate by about 12.4 percentage points (95% CI, 5.3 to 19.6). A doubling in the relative number of stay-at-home devices lowered it by 2.0 percentage points (95% CI, -2.9 to -1.2). The business closures and out-of-home activity restrictions decreased the positivity rate, accounting for approximately 25% of the decline observed in April and May 2020. CONCLUSION: Policy measures decreased the likelihood of positive results in COVID-19 tests. These specific policy tools may be successfully used when comparable health crises arise in the future.

Cost-Effectiveness Analysis of Point-of-Care Rapid Testing Versus Laboratory-Based Testing for Antenatal Screening of Syphilis in Brazil.

OBJECTIVES: Severe consequences of mother-to-child transmission of syphilis and high increasing incidence of congenital syphilis remains an important public health problem in Brazil. Our objective was to assess the cost-effectiveness of a rapid point-of-care test (RT) and treatment of positive mothers immediately compared with a laboratory-based standard test (ST) with treatment at next follow-up visit. METHODS: A decision analytic model was developed to estimate the incremental cost-effectiveness ratio (ICER) between antenatal syphilis screening strategies. The model was built with lifetime horizon from Brazilian health system perspective using 3% and 5% discount rates. A hypothetical cohort of pregnant women at reproductive age were used in the model. Health outcomes: low birth weight, stillbirths, neonatal deaths and congenital syphilis were estimated in disability-adjusted life-years (DALYs) lost. Microcosting study and secondary data provided parameters of direct medical costs. Probabilistic sensitivity analysis was undertaken. RESULTS: For base case, the mean cost per pregnant woman screened was $2.63 (RT) and $2.48 (ST), respectively. Maternal syphilis was associated with a loss of 0.0043 DALYs (RT) and 0.0048 DALYs (ST) per mother screened. Expected value of incremental cost per DALY averted was $298.08. After 10 000 probabilistic sensitivity analysis model runs, incremental cost and health benefits were $0.15 (95% credible interval -1.56 to 1.92) and 0.00042 DALYs (95% credible interval -0.0036 to 0.0044), respectively, with a mean ICER of $357.44 per DALY. Screening with RT has a 58% chance of being the optimal strategy at a threshold of $3,200 per DALY. CONCLUSIONS: In Brazil, antenatal screening with syphilis RT and immediate treatment is likely to be cost-effective compared with standard screening and must be prioritized in local settings.

Transmission dynamics of Covid-19 in Italy, Germany and Turkey considering social distancing, testing and quarantine.

INTRODUCTION: There are significant differences in the active cases and fatality rates of Covid-19 for different European countries. METHODOLOGY: The present study employs Monte Carlo based transmission growth simulations for Italy, Germany and Turkey. The probabilities of transmission at home, work and social networks and the number of initial cases have been calibrated to match the basic reproduction number and the reported fatality curves. Parametric studies were conducted to observe the effect of social distancing, work closure, testing and quarantine of the family and colleagues of positively tested individuals. RESULTS: It is observed that estimates of the number of initial cases in Italy compared to Turkey and Germany are higher. Turkey will probably experience about 30% less number of fatalities than Germany due its smaller elderly population. If social distancing and work contacts are limited to 25% of daily routines, Germany and Turkey may limit the number of fatalities to a few thousands as the reproduction number decreases to about 1.3 from 2.8. Random testing may reduce the number of fatalities by 10% upon testing least 5/1000 of the population. Quarantining of family and workmates of positively tested individuals may reduce the total number of fatalities by about 50%. CONCLUSIONS: The fatality rate of Covid-19 is estimated to be about 1.5% based on the simulation results. This may further be reduced by limiting the number of non-family contacts to two, conducting tests more than 0.5% of the population and immediate quarantine of the contacts for positively tested individuals.

Evaluation and cost estimation of laboratory test overuse in 43 commonly ordered parameters through a Computerized Clinical Decision Support System (CCDSS) in a large university hospital.

BACKGROUND: Computerized Clinical Decision Support Systems (CCDSS) have become increasingly important in ensuring patient safety and supporting all phases of clinical decision making. The aim of this study is to evaluate, through a CCDSS, the rate of the laboratory tests overuse and to estimate the cost of the inappropriate requests in a large university hospital. METHOD: In this observational study, hospital physicians submitted the examination requests for the inpatients through a Computerized Physician Order Entry. Violations of the rules in tests requests were intercepted and counted by a CCDSS, over a period of 20 months. Descriptive and inferential statistics (Student's t-test and ANOVA) were made. Finally, the monthly comprehensive cost of the laboratory tests was calculated. RESULTS: During the observation period a total of 5,716,370 requests were analyzed and 809,245 violations were counted. The global rate of overuse was 14.2% ± 3.0%. The most inappropriate exams were Alpha Fetoprotein (85.8% ± 30.5%), Chlamydia trachomatis Nucleic Acid Amplification (48.7% ± 8.8%) and Alkaline Phosphatase (20.3% ± 6.5%). The monthly cost of over-utilization was 56,534€ for basic panel, 14,421€ for coagulation, 4,758€ for microbiology, 432€ for immunology exams. All the exams, generated an estimated avoidable cost of 1,719,337€ (85,967€ per month) for the hospital. CONCLUSIONS: The study confirms the wide variability in over-utilization rates of laboratory tests. For these reasons, the real impact of inappropriateness is difficult to assess, but the generated costs for patients, hospitals and health systems are certainly high and not negligible. It would be desirable for international medical communities to produce a complete panel of prescriptive rules for all the most common laboratory exams that is useful not only to reduce costs, but also to ensure standardization and high-quality care.

Spatial analysis of COVID-19 clusters and contextual factors in New York City.

Identifying areas with low access to testing and high case burden is necessary to understand risk and allocate resources in the COVID-19 pandemic. Using zip code level data for New York City, we analyzed testing rates, positivity rates, and proportion positive. A spatial scan statistic identified clusters of high and low testing rates, high positivity rates, and high proportion positive. Boxplots and Pearson correlations determined associations between outcomes, clusters, and contextual factors. Clusters with less testing and low proportion positive tests had higher income, education, and white population, whereas clusters with high testing rates and high proportion positive tests were disproportionately black and without health insurance. Correlations showed inverse associations of white race, education, and income with proportion positive tests, and positive associations with black race, Hispanic ethnicity, and poverty. We recommend testing and health care resources be directed to eastern Brooklyn, which has low testing and high proportion positives.