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\"A bold call to reexamine how our government operates-and sometimes fails to-from President Obama's former deputy chief technology officer and the founder of Code for America. Just when we most need our government to work-to decarbonize our infrastructure and economy, to help the vulnerable through a pandemic, to defend ourselves against global threats-it is faltering. Government at all levels has limped into the digital age, offering online services that can feel even more cumbersome than the paperwork that preceded them and widening the gap between the policy outcomes we intend and what we get. But it's not more money or more tech we need. Government is hamstrung by a rigid, industrial-era culture, in which elites dictate policy from on high, disconnected from and too often disdainful of the details of implementation. Lofty goals morph unrecognizably as they cascade through a complex hierarchy. But there is an approach taking hold that keeps pace with today's world and reclaims government for the people it is supposed to serve. Jennifer Pahlka shows why we must stop trying to move the government we have today onto new technology and instead consider what it would mean to truly recode American government\"-- Provided by publisher.

It is well documented that earnings inequalities have risen in many high-income countries. Less clear are the linkages between rising income inequality and workplace dynamics, how within- and between-workplace inequality varies across countries, and to what extent these inequalities are moderated by national labor market institutions. In order to describe changes in the initial between- and within-firm market income distribution we analyze administrative records for 2,000,000,000+ job years nested within 50,000,000+ workplace years for 14 high-income countries in North America, Scandinavia, Continental and Eastern Europe, the Middle East, and East Asia. We find that countries vary a great deal in their levels and trends in earnings inequality but that the between-workplace share of wage inequality is growing in almost all countries examined and is in no country declining. We also find that earnings inequalities and the share of between-workplace inequalities are lower and grew less strongly in countries with stronger institutional employment protections and rose faster when these labor market protections weakened. Our findings suggest that firm-level restructuring and increasing wage inequalities between workplaces are more central contributors to rising income inequality than previously recognized.

(1) Background: Several smaller studies have shown that COVID-19 patients with cancer are at a significantly higher risk of death. Our objective was to compare patients hospitalized for COVID-19 with cancer to those without cancer using national data and to study the effect of cancer on the risk of hospital death and intensive care unit (ICU) admission. (2) Methods: All patients hospitalized in France for COVID-19 in March–April 2020 were included from the French national administrative database, which contains discharge summaries for all hospital admissions in France. Cancer patients were identified within this population. The effect of cancer was estimated with logistic regression, adjusting for age, sex and comorbidities. (3) Results: Among the 89,530 COVID-19 patients, we identified 6201 cancer patients (6.9%). These patients were older and were more likely to be men and to have complications (acute respiratory and kidney failure, venous thrombosis, atrial fibrillation) than those without cancer. In patients with hematological cancer, admission to ICU was significantly more frequent (24.8%) than patients without cancer (16.4%) (p < 0.01). Solid cancer patients without metastasis had a significantly higher mortality risk than patients without cancer (aOR = 1.4[1.3–1.5]), and the difference was even more marked for metastatic solid cancer patients (aOR = 3.6[3.2–4.0]). Compared to patients with colorectal cancer, patients with lung cancer, digestive cancer (excluding colorectal cancer) and hematological cancer had a higher mortality risk (aOR = 2.0[1.6–2.6], 1.6[1.3–2.1] and 1.4[1.1–1.8], respectively). (4) Conclusions: This study shows that, in France, patients with COVID-19 and cancer have a two-fold risk of death when compared to COVID-19 patients without cancer. We suggest the need to reorganize facilities to prevent the contamination of patients being treated for cancer, similar to what is already being done in some countries.

Background Acute Care Surgery (ACS) was developed as a structured, team-based approach to providing round-the-clock emergency general surgery (EGS) care for adult patients needing treatment for diseases such as cholecystitis, gastrointestinal perforation, and necrotizing fasciitis. Lacking any prior evidence on optimizing outcomes for EGS patients, current implementation of ACS models has been idiosyncratic. We sought to use a Donabedian approach to elucidate potential EGS structures and processes that might be associated with improved outcomes as an initial step in designing the optimal model of ACS care for EGS patients. Methods We developed and implemented a national survey of hospital-level EGS structures and processes by surveying surgeons or chief medical officers regarding hospital-level structures and processes that directly or indirectly impacted EGS care delivery in 2015. These responses were then anonymously linked to 2015 data from the American Hospital Association (AHA) annual survey, Medicare Provider Analysis and Review claims (MedPAR), 17 State Inpatient Databases (SIDs) using AHA unique identifiers (AHAID). This allowed us to combine hospital-level data, as reported in our survey or to the AHA, to patient-level data in an effort to further examine the role of EGS structures and processes on EGS outcomes. We describe the multi-step, iterative process utilizing the Donabedian framework for quality measurement that serves as a foundation for later work in this project. Results Hospitals that responded to the survey were primarily non-governmental and located in urban settings. A plurality of respondent hospitals had fewer than 100 inpatient beds. A minority of the hospitals had medical school affiliations. Discussion Our results will enable us to develop a measure of preparedness for delivering EGS care in the US, provide guidance for regionalized care models for EGS care, tiering of ACS programs based on the robustness of their EGS structures and processes and the quality of their outcomes, and formulate triage guidelines based on patient risk factors and severity of EGS disease. Conclusions Our work provides a template for team science applicable to research efforts combining primary data collection (i.e., that derived from our survey) with existing national data sources (i.e., SIDs and MedPAR).

Few developments have had broader consequences for the public sector than the introduction of the Internet and digital technology. In this book, Darrell West discusses how new technology is altering governmental performance, the political process, and democracy itself by improving government responsiveness and increasing information available to citizens. Using multiple methods--case studies, content analysis of over 17,000 government Web sites, public and bureaucrat opinion survey data, an e-mail responsiveness test, budget data, and aggregate analysis--the author presents the most comprehensive study of electronic government ever undertaken. Among other topics, he looks at how much change has taken place in the public sector, what determines the speed and breadth of e-government adoption, and what the consequences of digital technology are for the public sector. Written in a clear and analytical manner, this book outlines the variety of factors that have restricted the ability of policy makers to make effective use of new technology. Although digital government offers the potential for revolutionary change, social, political, and economic forces constrain the scope of transformation and prevent government officials from realizing the full benefits of interactive technology.

The Public Health Agency of Canada's Canadian Chronic Disease Surveillance System (CCDSS) produces population-based estimates of chronic disease prevalence and incidence using administrative health data. Our aim was to assess trends in incidence rates over time, trends are essential to understand changes in population risk and to inform policy development. Incident cases of diagnosed asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, ischemic heart disease (IHD), and stroke were obtained from the CCDSS online infobase for 1999 to 2012. Trends in national and regional incidence estimates were tested using a negative binomial regression model with year as a linear predictor. Subsequently, models with year as a restricted cubic spline were used to test for departures from linearity using the likelihood ratio test. Age and sex were covariates in all models. Based on the models with year as a linear predictor, national incidence rates were estimated to have decreased over time for all diseases, except diabetes; regional incidence rates for most diseases and regions were also estimated to have decreased. However, likelihood ratio tests revealed statistically significant departures from a linear year effect for many diseases and regions, particularly for hypertension. Chronic disease incidence estimates based on CCDSS data are decreasing over time, but not at a constant rate. Further investigations are needed to assess if this decrease is associated with changes in health status, data quality, or physician practices. As well, population characteristics that may influence changing incidence trends also require exploration.

The French Breast Cancer Screening Program (DOCS) was created to detect early Breast Cancer (BC). Key performance indicators for digital mammography include sensitivity (SE), positive predictive value (PPV), interval cancer rate (ICR) and cancer detection rate (CDR). Calculating these metrics requires a linkage between screening data and BC registries; however, registries are scarce in France and often inaccessible for research. We therefore used medico-administrative data as an alternative. We linked regional screening data to the French National Health Data System (SNDS) between 2011 and 2020. Women were followed for 24 months post-screening. Screen-detected cancers and those identified with the SNDS were included. Performance metrics were calculated based on these linked datasets. A total of 252,786 screening exams were analyzed, covering 29,661–33,447 screenings annually, with a mean age of 61 years. SE was 77.9% (95% CI 76.3–79.3), indicating that approximately four in five cancers were detected through mammography. PPV was 19.8% (95% CI 19–20.5), meaning that one in five women with a positive screening test were confirmed with cancer within 24 months. CDR was 10.9 per 1000 exams (95% CI 10.5–11.3), equating to one detected case per 100 screenings. ICR was 2.4 per 1000 exams (95% CI 2.2–2.6), meaning that more than two interval cancers were detected per 1000 screenings. This identification approach using medico-administrative data offers a reproducible alternative for regions where cancer registries are unavailable. A future study applying this methodology in a registry-covered region could further validate the effectiveness of linking screenings to SNDS data for systematic cancer identification.

Background: Diagnoses recorded in administrative databases have limited utility for accurate identification of severe sepsis and disseminated intravascular coagulation (DIC). We evaluated the performance of alternative identification methods that use procedure records. Methods: We obtained data for adult patients admitted to intensive care units in three hospitals during a 1-year period. Severe sepsis and DIC were identified by three means: laboratory data, diagnoses, and procedures. Using laboratory data as a reference, the sensitivity and specificity of procedure-based methods and diagnosis-based methods were compared. Results: Of 595 intensive care unit admissions, 212 (35.6%) and 81 (13.6%) were identified as severe sepsis and DIC, respectively, using laboratory data. The sensitivity of procedure-based methods for identifying severe sepsis was 64.2%, and the specificity was 65.3%. Two diagnosis-based methods -the Angus and Martin algorithms- exhibited sensitivities of 21.7% and 14.6% and specificities of 98.7% and 99.5%, respectively, for severe sepsis. For DIC, the sensitivity of procedure-based methods was 55.6%, and the specificity was 67.1%, and the sensitivity and specificity of diagnosis-based methods were 35.8% and 98.2%, respectively. Conclusions: Procedure-based methods were more sensitive and less specific than diagnosis-based methods in identifying severe sepsis and DIC. Procedure records could improve disease identification in administrative databases.

Discharge to home is considered appropriate as a treatment goal for diseases that often leave disabilities such as cerebral infarction. Previous studies showed differences in risk-adjusted in-hospital mortality and readmission rates; however, studies assessing the rate of hospital-to-home transition are limited. We developed and calculated the hospital standardized home-transition ratio (HSHR) using Japanese administrative claims data from 2016–2020 to measure the quality of in-hospital care for cerebral infarction. Overall, 24,529 inpatients at 35 hospitals were included. All variables used in the analyses were associated with transition to another hospital or facility for inpatients, and evaluation of the HSHR model showed good predictive ability with c-statistics (area under curve, 0.73 standard deviation; 95% confidence interval, 0.72–0.73). All HSHRs of each consecutive year were significantly correlated. HSHRs for cerebral infarction can be calculated using Japanese administrative claims data. It was found that there is a need for support for low HSHR hospitals because hospitals with high/low HSHR were likely to produce the same results in the following year. HSHRs can be used as a new quality indicator of in-hospital care and may contribute to assessing and improving the quality of care.

Introduction Medico‐administrative databases are increasingly used to study the epidemiology of status epilepticus (SE), targeting hospitalizations with the SE G41 ICD‐10 code. However, the positive predictive value (PPV) of the G41 code, which measures the percentage of true cases among those identified by the code, is unknown. Methods We identified all hospitalizations with a primary or secondary diagnosis coded as G41 in five different hospitals. Medical reports for each hospitalization were reviewed to classify the stays as really related to SE or not, using two distinct approaches (sensitive and specific). The clinical characteristics of SE cases were also extracted. Results Among the 797 hospitalizations identified, the PPV ranged from 85.7% using the sensitive approach to 70.6% with the specific approach. Hospitalizations coded with G41 as the main diagnosis had the highest PPV, whereas codes G411 and G418 showed the lowest PPV. Of the 400 hospitalizations with a G410 (generalized convulsive SE) code, 72.7% were classified as generalized convulsive SE, while 76.5% of the 149 hospitalizations with a G412 (focal SE) code were classified as focal SE. Conclusion Our findings highlight that PPV varies by G41 subtype and diagnostic position. Studies requiring a higher PPV should exclude certain codes or hospitalizations with G41 code only as an associated diagnosis. Further studies are needed to estimate the sensitivity and specificity of G41 code. Sorbonne University Hospitals (5 hospitals, 1.1% of hospitalizations in France Extraction of all hospitalizations with a G41 discharge code (n = 797). Review of medical reports and labeling of hospitalizations using a sensitive and a specific approach. True positive (TP): hospitalization with a G41 code that corresponds to a hospitalization for Status Epilepticus. False positive (FP): hospitalization with a G41 code without Status Epilepticus Positive Predictive Value (PPV) : TP / (TP + FP). The Positive Predictive Value (PPV) of the G41 discharge code for Status Epilepticus ranges from 70.6% to 85.7%. The PPV is higher when the G41 code is the main diagnosis or when the patient is hospitalized in a neurology unit.