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How and where patients with advanced cancer facing limited survival spend their time is critical. Healthcare contact days (days with healthcare contact outside the home) offer a patient-centered and practical measure of how much of a person's life is consumed by healthcare. We retrospectively analyzed contact days among decedent veterans with stage IV gastrointestinal cancer at the Minneapolis Veterans Affairs Healthcare System from 2010 to 2021. Among 468 decedents, the median overall survival was 4 months. Patients spent 1 in 3 days with healthcare contact. Over the course of illness, the percentage of contact days followed a "U-shaped" pattern, with an initial post-diagnosis peak, a lower middle trough, and an eventual rise as patients neared the end-of-life. Contact days varied by clinical factors and by sociodemographics. These data have important implications for improving care delivery, such as through care coordination and communicating expected burdens to and supporting patients and care partners., (© The Author(s) 2023. Published by Oxford University Press.)

Objective: This study was to determine the racial disparities in incidence, clinicopathological features and prognosis of hypopharyngeal squamous cell carcinoma (HPSCC) in the US., Methods: The National Program of Cancer Registries and Surveillance, Epidemiology, and End Results (SEER) database was used to determine racial disparity in age adjusted incidence rate (AAIR) of HPSCC and its temporal trend during 2004-2019. Using the separate SEER 17 database, we further evaluated racial disparity in clinicopathological features, and in prognosis using Kaplan-Meier curves and Cox proportional hazard models., Results: HPSCC accounted for 95.8% of all hypopharyngeal cancers and occurred much more frequently in males. Its incidence decreased in both male and females, in male non-Hispanic white (NHW), non-Hispanic black (NHB) and Hispanic as well as female NHW and NHB during the study period. NHB had the highest, whereas non-Hispanic Asian or Pacific Islanders (API) had comparable and the lowest incidence in both males and females. Among 6,172 HPSCC patients obtained from SEER 17 database, 80.6% were males and 83.9% were at the advanced stages III/IV. Five-year cancer specific and overall survival rates were 41.2% and 28.9%, respectively. NHB patients were more likely to be younger, unmarried, from the Southern region, larger sized tumor, and at the stage IV, but less likely to receive surgery. They also had higher proportions of dying from HPSCC and all causes. Multivariate analyses revealed that NHB with HPSCC at the locally advanced stage had both significantly worse cancer specific and overall survival compared with NHW, but not at early stage (I/II) or distant metastatic stage. Hispanic patients had significantly better prognosis than NHW at locally advanced and metastatic stages. NHW and API had comparable prognoses., Conclusions: HPSCC displays continuously decreased incidence and racial disparity. The majority of the disease is diagnosed at the advanced stage. NHB have the highest burden of HPSCC and a worse prognosis. More studies are needed to curtail racial disparity and improve early detection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Liang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The Centers for Disease Control and Prevention (CDC) uses standardized antimicrobial administration ratios (SAARs)-that is, observed-to-predicted ratios-to compare antibiotic use across facilities. CDC models adjust for facility characteristics when predicting antibiotic use but do not include patient diagnoses and comorbidities that may also affect utilization. This study aimed to identify comorbidities causally related to appropriate antibiotic use and to compare models that include these comorbidities and other patient-level claims variables to a facility model for risk-adjusting inpatient antibiotic utilization., Methods: The study included adults discharged from Premier Database hospitals in 2016-2017. For each admission, we extracted facility, claims, and antibiotic data. We evaluated 7 models to predict an admission's antibiotic days of therapy (DOTs): a CDC facility model, models that added patient clinical constructs in varying layers of complexity, and an external validation of a published patient-variable model. We calculated hospital-specific SAARs to quantify effects on hospital rankings. Separately, we used Delphi Consensus methodology to identify Elixhauser comorbidities associated with appropriate antibiotic use., Results: The study included 11 701 326 admissions across 576 hospitals. Compared to a CDC-facility model, a model that added Delphi-selected comorbidities and a bacterial infection indicator was more accurate for all antibiotic outcomes. For total antibiotic use, it was 24% more accurate (respective mean absolute errors: 3.11 vs 2.35 DOTs), resulting in 31-33% more hospitals moving into bottom or top usage quartiles postadjustment., Conclusions: Adding electronically available patient claims data to facility models consistently improved antibiotic utilization predictions and yielded substantial movement in hospitals' utilization rankings., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.)

Background: In recent years, there has been a growing interest in outcomes of patients with acute myocardial infarction (AMI) using large administrative datasets. The present study was designed to compare the characteristics, management strategies and acute outcomes between patients with primary and secondary AMI diagnoses in a national cohort of patients., Methods: All hospitalisations of adults (≥18 years) with a discharge diagnosis of AMI in the US National Inpatient Sample from January 2004 to September 2015 were included, stratified by primary or secondary AMI. The International Classification of Diseases, ninth revision and Clinical Classification Software codes were used to identify patient comorbidities, procedures and clinical outcomes., Results: A total of 10 864 598 weighted AMI hospitalisations were analysed, of which 7 186 261 (66.1%) were primary AMIs and 3 678 337 (33.9%) were secondary AMI. Patients with primary AMI diagnoses were younger (median 68 vs 74 years, P < .001) and less likely to be female (39.6% vs 48.5%, P < .001). Secondary AMI was associated with lower odds of receipt of coronary angiography (aOR 0.19; 95%CI 0.18-0.19) and percutaneous coronary intervention (0.24; 0.23-0.24). Secondary AMI was associated with increased odds of MACCE (1.73; 1.73-1.74), mortality (1.71; 1.70-1.72), major bleeding (1.64; 1.62-1.65), cardiac complications (1.69; 1.65-1.73) and stroke (1.68; 1.67-1.70) (P < .001 for all)., Conclusions: Secondary AMI diagnoses account for one-third of AMI admissions. Patients with secondary AMI are older, less likely to receive invasive care and have worse outcomes than patients with a primary diagnosis code of AMI. Future studies should consider both primary and secondary AMI diagnoses codes in order to accurately inform clinical decision-making and health planning., (© 2021 John Wiley & Sons Ltd.)

Background: Subclinical hypothyroidism (SCH) is the most common thyroid dysfunction, and its relationship with blood pressure (BP) has been controversial. The aim of the study was to analyze the association between SCH and newly-diagnosed hypertension., Methods: Based on data from the Thyroid disease, Iodine nutrition and Diabetes Epidemiology (TIDE) study, 49,433 euthyroid individuals and 7,719 SCH patients aged ≥18 years were enrolled. Patients with a history of hypertension or thyroid disease were excluded. SCH was determined by manufacturer reference range. Overall hypertension and stage 1 and 2 hypertension were diagnosed according to the guidelines issued by the American College of Cardiology/American Heart Association in 2017., Results: The prevalence of overall hypertension (48.7%), including stage 1 (28.9%) and 2 (19.8%) hypertension, increased significantly in SCH patients compared with euthyroid subjects. With elevated serum thyroid stimulating hormone (TSH) level, the hypertension prevalence also increased significantly from the euthyroid to different SCH subgroups, which was more profound in females or subjects aged <65 years. The age- and sex-specific regression analysis further demonstrated the same trends in the general population and in the 1:1 propensity matched population. Similarly, several BP components (i.e., systolic, diastolic, and mean arterial BP) were positively associated with TSH elevation, and regression analysis also confirmed that all BP components were closely related with SCH in female subjects aged <65 years., Conclusion: The prevalence of hypertension increases for patients with SCH. SCH tends to be associated with hypertension and BP components in females younger than 65 years.

Background: Quantifying the amount and diversity of antibiotic use in United States hospitals assists antibiotic stewardship efforts but is hampered by limited national surveillance. Our study aimed to address this knowledge gap by examining adult antibiotic use across 576 hospitals and nearly 12 million encounters in 2016-2017., Methods: We conducted a retrospective study of patients aged ≥ 18 years discharged from hospitals in the Premier Healthcare Database between 1 January 2016 and 31 December 2017. Using daily antibiotic charge data, we mapped antibiotics to mutually exclusive classes and to spectrum of activity categories. We evaluated relationships between facility and case-mix characteristics and antibiotic use in negative binomial regression models., Results: The study included 11 701 326 admissions, totaling 64 064 632 patient-days, across 576 hospitals. Overall, patients received antibiotics in 65% of hospitalizations, at a crude rate of 870 days of therapy (DOT) per 1000 patient-days. By class, use was highest among β-lactam/β-lactamase inhibitor combinations, third- and fourth-generation cephalosporins, and glycopeptides. Teaching hospitals averaged lower rates of total antibiotic use than nonteaching hospitals (834 vs 957 DOT per 1000 patient-days; P < .001). In adjusted models, teaching hospitals remained associated with lower use of third- and fourth-generation cephalosporins and antipseudomonal agents (adjusted incidence rate ratio [95% confidence interval], 0.92 [.86-.97] and 0.91 [.85-.98], respectively). Significant regional differences in total and class-specific antibiotic use also persisted in adjusted models., Conclusions: Adult inpatient antibiotic use remains high, driven predominantly by broad-spectrum agents. Better understanding reasons for interhospital usage differences, including by region and teaching status, may inform efforts to reduce inappropriate antibiotic prescribing., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.)

Question: Are there ways to mitigate the challenges associated with imperfect data validity in Patient Safety Indicator (PSI) report cards?, Findings: Applying a methodological framework on simulated PSI report card data, we compare the adjusted PSI rates of three hospitals with variable quality of data and coding. This framework combines (i) a measure of PSI rates using existing algorithms; (ii) a medical record review on a small random sample of charts to produce a measure of hospital-specific data validity and (iii) a simple Bayesian calculation to derive estimated true PSI rates. For example, the estimated true PSI rate, for a theoretical hospital with a moderately good quality of coding, could be three times as high as the measured rate (for example, 1.4% rather than 0.5%). For a theoretical hospital with relatively poor quality of coding, the difference could be 50-fold (for example, 5.0% rather than 0.1%)., Meaning: Combining a medical chart review on a limited number of medical charts at the hospital level creates an approach to producing health system report cards with estimates of true hospital-level adverse event rates., (© The Author(s) 2021. Published by Oxford University Press on behalf of International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The Food and Drug Administration (FDA) guidance for evaluating cardiovascular (CV) risk in new antidiabetic therapies to treat type 2 diabetes released in December 2008 recommends that sponsors conduct appropriate data analysis to rule out CV safety concerns for drugs treating type 2 diabetes. CV trials of antidiabetic drugs and drugs of other indications for chronic conditions are usually large-scale/long-term trials and can be designed as adaptive noninferiority/superiority trials. In these trials, treatment effect may not manifest immediately after patients take study medication and there will be a dilution in treatment effect after treatment discontinuation. These factors should be taken into account for more precise planning of study sample size and timeline. In this paper, we first derive closed-form formulas for the number of events and total exposure as functions of many other trial parameters. We then outline some considerations for the design of an adaptive noninferiority/superiority CV trial based on ideas of other authors. We also use an example to illustrate the application of the methods.

Background: The electronic medical record (EMR)/electronic health record (EHR) is becoming an integral component of many primary-care outpatient practices. Before implementing an EMR/EHR system, primary-care practices should have an understanding of the potential benefits and limitations., Objective: The objective of this study was to systematically review the recent literature around the impact of the EMR/EHR within primary-care outpatient practices., Materials and Methods: Searches of Medline, EMBASE, CINAHL, ABI Inform, and Cochrane Library were conducted to identify articles published between January 1998 and January 2010. The gray literature and reference lists of included articles were also searched. 30 studies met inclusion criteria., Results and Discussion: The EMR/EHR appears to have structural and process benefits, but the impact on clinical outcomes is less clear. Using Donabedian's framework, five articles focused on the impact on healthcare structure, 21 explored healthcare process issues, and four focused on health-related outcomes.

Background: In the United States, the Agency for Healthcare Research and Quality (AHRQ) has developed 20 Patient Safety Indicators (PSIs) to measure the occurrence of hospital adverse events from medico-administrative data coded according to the ninth revision of the international classification of disease (ICD-9-CM). The adaptation of these PSIs to the WHO version of ICD-10 was carried out by an international consortium., Methods: Two independent teams transcoded ICD-9-CM diagnosis codes proposed by the AHRQ into ICD-10-WHO. Using a Delphi process, experts from six countries evaluated each code independently, stating whether it was "included", "excluded" or "uncertain". During a two-day meeting, the experts then discussed the codes that had not obtained a consensus, and the additional codes proposed., Results: Fifteen PSIs were adapted. Among the 2569 proposed diagnosis codes, 1775 were unanimously adopted straightaway. The 794 remaining codes and 2541 additional codes were discussed. Three documents were prepared: (1) a list of ICD-10-WHO codes for the 15 adapted PSIs; (2) recommendations to the AHRQ for the improvement of the nosological frame and the coding of PSI with ICD-9-CM; (3) recommendations to the WHO to improve ICD-10., Conclusions: This work allows international comparisons of PSIs among the countries using ICD-10. Nevertheless, these PSIs must still be evaluated further before being broadly used., (Copyright © 2011 Elsevier Masson SAS. All rights reserved.)

Background: The United States is about to make a major nationwide transition from ICD-9-CM coding of hospital discharges to ICD-10-CM, a country-specific modification of the World Health Organization's ICD-10. As this transition occurs, the WHO is already in the midst of developing ICD-11. Given this context, we undertook this review to discuss: (1) the history of the International Classification of Diseases (a core information "building block" for health systems everywhere) from its introduction to the current era of ICD-11 development; (2) differences across country-specific ICD-10 clinical modifications and the challenges that these differences pose to the international comparability of morbidity data; (3) potential strategic approaches to achieving better international ICD-11 comparability., Literature Review and Discussion: A literature review and stakeholder consultation was carried out. The various ICD-10 clinical modifications (ICD-10-AM [Australia], ICD-10-CA [Canada], ICD-10-GM [Germany], ICD-10-TM [Thailand], ICD-10-CM [United States]) were compared. These ICD-10 modifications differ in their number of codes, chapters, and subcategories. Specific conditions are present in some but not all of the modifications. ICD-11, with a similar structure to ICD-10, will function in an electronic health records environment and also provide disease descriptive characteristics (eg, causal properties, functional impact, and treatment)., Conclusion: The threat to the comparability of international clinical morbidity is growing with the development of many country-specific ICD-10 versions. One solution to this threat is to develop a meta-database including all country-specific modifications to ensure more efficient use of people and resources, decrease omissions and errors but most importantly provide a platform for future ICD updates.

Composite endpoints are often used in clinical trials in order to increase the overall event rates, reduce the sizes of the trials and achieve desired power. For example, in a trial to study the effect of a treatment on the prevention of venous thromboembolic events after a major orthopaedic surgery of the lower limbs, the primary endpoint is usually a composite endpoint consisting of any deep vein thrombosis identified by systematic venography of lower limbs, symptomatic and well-documented non-fatal pulmonary embolism, and death from all causes. Just as any endpoints, missing data can occur in the components of the composite endpoint. If a patient has missing data on some of the components but not all the components, this patient may not have complete data but partial data for the composite endpoint. To be consistent with the intention-to-treat principle, the patient should not be discarded from the analysis. In this research, we propose an approach for the analysis of a composite endpoint with missing data in components. The main idea is to first derive the probabilities of all possible study outcomes based on the appropriate model and then to construct the overall rate for the composite endpoint. Simulations are conducted to compare the approach with several naïve methods. A data example is used to illustrate the application of the approach.

In active controlled trials without a placebo arm, there are usually two study objectives: to test a superiority hypothesis that the experimental treatment is more effective than the active control therapy, and to test a non-inferiority hypothesis that the experimental treatment is therapeutically no worse than the active control within a defined margin. For a two-stage adaptive design, it is not necessary to give a fixed sample size calculation at the planning stage of the study when treatment effect information is often insufficient. Instead, decision and estimation of the design specifications can be made more reliably after the first stage when interim results are available. We propose the use of conditional power approach to determine the sample size and critical values for testing the superiority and non-inferiority hypotheses for the second stage based on the observed result of the first stage. The proposed adaptive procedure preserves the overall type I error rate for both superiority and non-inferiority, and has the flexibility of early termination of the study (for futility or efficacy) or extending the study by appropriate sample size., (Copyright 2004 John Wiley & Sons, Ltd.)

The U.S. Food and Drug Administration (FDA) Modernization Act of 1997 has a Section (No. 112) entitled 'Expediting Study and Approval of Fast Track Drugs' (the Act). In 1998, the FDA issued a 'Guidance for Industry: the Fast Track Drug Development Programs' (the FTDD programmes) to meet the requirement of the Act. The purpose of FTDD programmes is to 'facilitate the development and expedite the review of new drugs that are intended to treat serious or life-threatening conditions and that demonstrate the potential to address unmet medical needs'. Since then many health products have reached patients who suffered from AIDS, cancer, osteoporosis, and many other diseases, sooner by utilizing the Fast Track Act and the FTDD programmes. In the meantime several scientific issues have also surfaced when following the FTDD programmes. In this paper we will discuss the concept of two kinds of type I errors, namely, the 'conditional approval' and the 'final approval' type I errors, and propose statistical methods for controlling them in a new drug submission process., (Copyright 2003 John Wiley & Sons, Ltd.)

In this paper we explore the possible reasons why medical papers reporting clinical trials sponsored by the pharmaceutical industry often analyse repeated measures data at certain key time-points instead of employing sophisticated models of repeated measures proposed by many statisticians. A survey indicated that the priority reason in the industry for having repeated measures in clinical trials is to monitor the trial and to utilize the early results for strategic decision making. We discuss what the common statistical methods do and do not offer for analysis of repeated measures in such clinical trials. We advocate the need to improve the understanding of the medical interest in conducting longitudinal trials in the industry, and to plan and analyse the repeated measures accordingly. We address the medical interest by formulating the problem and give illustrative examples for both phases II and III trials.