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ABSTRACT BACKGROUND Rehospitalizations within 30 days of discharge are responsible for a large portion of healthcare spending. One approach to preventing rehospitalizations is early follow-up, usually defined as an office visit with a primary care physician within 7 days of discharge—an approach that is being incentivized by health plans. However, evidence regarding its effectiveness is limited. OBJECTIVE We aimed to determine whether an office visit with a primary care physician within 7 days after discharge is associated with 30-day rehospitalization. DESIGN This was an observational study set within a randomized trial. PARTICIPANTS The study included patients age 65 and older receiving care from a multi-specialty group practice and discharged from hospital to home between 26 August 2010 and 25 August 2011. To control for confounding, we identified characteristics of patients and hospital stays that are predictive of rehospitalization, and also developed high-dimensional propensity scores. Analyses used Cox proportional hazards models and took into account varying amounts of opportunity time for office visits. MAIN MEASURES We looked at 30-day rehospitalizations at any hospital. KEY RESULTS Of 3,661 patients discharged to home during the study year, 707 (19.3 %) were rehospitalized within 30 days. Patients receiving an office visit within 7 days numbered 1,808 (49.4 %), and of these, 1,000 (27.3 %) were with a primary care physician. In models predicting rehospitalization, stratified on deciles of propensity score and controlling for additional confounders, the hazard ratios associated with office visits with a primary care physician within 7 days were 0.98 (95 % CI 0.80, 1.21); for visits with any physician, the hazard ratio was HR 1.04, (95 % CI 0.87, 1.25). CONCLUSIONS We found no protective effect for office visits within 7 days. Such visits may need to be specifically focused on a range of issues related to the specific reasons why patients are rehospitalized. It is likely that outpatient visits will need to be set within comprehensive transition programs.

Abstract Objective. To improve pain management practices, we developed an online interactive continuing education (CE) program for primary care providers (PCPs). This program follows the flow of clinical decision-making through simulated cases at critical pain treatment points along the pain treatment continuum. Design. A randomized controlled trial was conducted to test the efficacy of this program. Participants were randomized to either the experimental condition or the control condition (online, text-based CE program). Subjects. A total of 238 primary care providers were recruited through hospitals, professional newsletters, and pain conferences. Results. Participants in both conditions reported significantly improved scores on knowledge (KNOW-PAIN 50), attitudes (CAOS), and pain practice behaviors (PPBS) scales over the four-month study. The experimental condition showed significantly greater change over time on the tamper-resistant formulations (TRFs) of opioids and dosing CAOS subscale compared with the control condition. Post hoc comparisons suggested that participants in the experimental condition were less likely to endorse use of opioid TRFs over time compared with the control condition. Exploratory analyses for potential moderators indicated a significant three-way interaction with time, condition, and discipline (i.e., physician vs other) for the impediments and concerns attitudes subscale and the early refill behaviors subscale. Post hoc comparisons indicated that physicians in the experimental condition exhibited the greatest change in attitudes and the nonphysicians exhibited the greatest change in reported behaviors in response to requests for early refills. Conclusions. Findings suggest online CE programs may positively impact PCPs’ knowledge, attitudes, and pain practice behaviors but provide minimal evidence for the value of including interactivity.

INTRODUCTION: Indigenous peoples’ rights include the right to self-determine one’s identity. For Māori, this includes self-assignment of ethnicity, and traditional identities such as Iwi (tribe). New Zealand’s Ministry of Health requires health services to collect ethnicity data using standard protocols. Iwi data are also collected by some health services; however, with no health-specific protocols, little is known about Iwi data collection and quality. The National Hauora Coalition (NHC) Primary Healthcare Organisation (PHO) sought to understand Iwi data collection across its network of primary care providers.AIM: To understand Iwi data collection at the NHC PHO; specifically, is it being routinely collected, how is it being collected and what are the results?METHODS: In 2017, NHC’s general practice clinics were invited to submit their enrolment forms, which capture ethnicity and potentially Iwi information, by e-mail to the audit team. Forms were reviewed to determine whether Iwi information was being collected and if so, what question was being used. Iwi numbers were collated from the annual data extract.RESULTS: Thirty-three of a total of 35 clinics (94%) submitted their enrolment forms to the audit team. Nine of the 33 clinics (27%) sought Iwi name/s with a specific question on their enrolment form. Six different ‘Iwi’ questions were used by the nine clinics. The data extract revealed that the NHC had Iwi data for 13% (2672/20,814) of its Māori enrolments. Ngāpuhi were the largest Iwi group at the NHC.DISCUSSION: This is the first study to describe the quantity and quality of Iwi data collection in NZ primary care. Standard procedures for collecting, recording and using Iwi data are being developed by the NHC PHO. These could inform national protocols to optimise the quality of Iwi data.

Complementing Nielsen and colleagues’ (2020) analysis of methodological trends in the Journal of International Business Studies over the past 50 years, we examine similar data on methods published in a wider range of leading international business (IB) journals. Our analysis shows a clear decline of studies based on primary data relative to secondary data, and a persistently low level of individual-level studies among the growing body of research using secondary data across all IB journals considered. We discuss the main mechanisms driving these trends and identify the problems of IB’s increasing exposure to the risks inherent in secondary data. We also discuss the implications related to neglecting individual-level data for theory advancement in IB, such as a disregard for novel secondary data opportunities at the individual level and the risk of reduced theoretical pluralism. In doing so, we substantially extend the debate initiated by Nielsen and colleagues (2020).

Ethics in social science experimentation and data collection are often discussed but rarely articulated in writing as part of research outputs. Although papers typically reference human subjects research approvals from relevant institutional review boards, most recognize that such boards do not carry out comprehensive ethical assessments. We propose a structured ethics appendix to provide details on the following: policy equipoise, role of the researcher, potential harms to participants and nonparticipants, conflicts of interest, intellectual freedom, feedback to participants, and foreseeable misuse of research results. We discuss each of these and some of the norms and challenging situations of each. We believe that discussing such issues explicitly in appendices of papers, even if briefly, will serve two purposes: more complete communication of ethics can improve discussions of papers and can clarify and improve the norms themselves.

Irrational prescription of drugs in children is reported to be widespread. There are scarce studies on the pediatric prescribing pattern especially at primary health care (PHC) level. To determine the physicians' prescribing patterns for children under five years, to explore completeness of prescriptions' recorded information, and to analyze the core indicators of drug prescribing at primary health care centers (PHCC) in Qassim. This cross-sectional study was conducted on 25 randomly selected PHCCs. All prescriptions, for the first week of first six months of the year 1437 Hijrah (October 2015 to April 2016), were reviewed. Among 25 012 prescriptions, 4125 (16.5%) were for children under five years. We randomly selected 1212 prescriptions for the study. World Health Organization (WHO) specified drug use indicators, and index of rational drug prescribing (IRDP) with a maximum value of 5, were calculated. The physicians and pharmacists of sampled PHCCs were also surveyed to explore prescribing issues. The completeness of recorded date, patient age, and gender was more than 90%. The diagnosis was legibly written in 842 (69.5%), while the patient weight was recorded in 307 (25.3%) prescriptions. The least commonly recorded instruction was the drug strength (26.8%), while the dose and frequency of use were stated for 91.3% and 90.8% of the drugs, respectively. The average number of drugs per prescription was 2.35 ± 0.89; 72.97% drugs were prescribed by generic name; in 65.98% patient encounters, antibiotics were prescribed. The overall IRDP was 3.56. Most of the physicians and pharmacists reported availability of the drug list and Saudi PHC formulary in their PHCCs. PHC physicians' drug prescribing was not at the optimal level of rational use, especially regarding prescription of antibiotics. Creating awareness about rational drug use and hazards of overuse of antibiotics is needed.

The adoption of the European Health Data Space (EHDS) regulation has made integrating health data critical for both primary and secondary applications. Primary use cases include patient diagnosis, prognosis, and treatment, while secondary applications support research, innovation, and regulatory decision-making. Additionally, leveraging large datasets improves training quality for artificial intelligence (AI) models, particularly in cancer prevention, prediction, and treatment personalization. The European Union (EU) has recently funded multiple projects under Europe’s Beating Cancer Plan. However, these projects face challenges related to fragmentation and the lack of standardization in metadata, data storage, access, and processing. This paper examines interoperability standards used in six EU-funded cancer-related projects: IDERHA (Integration of Heterogeneous Data and Evidence Towards Regulatory and Health Technology Assessments Acceptance), EUCAIM (European Cancer Imaging Initiative), ASCAPE (Artificial Intelligence Supporting Cancer Patients Across Europe), iHelp, BigPicture, and the HealthData@EU pilot. These initiatives aim to enhance the analysis of heterogeneous health data while aligning with EHDS implementation, specifically for the EHDS for the secondary use of data (EHDS2). Between October 2023 and July 2024, we organized meetings and workshops among these projects to assess how they adopt health standards and apply Internet of Things (IoT) semantic interoperability. The discussions focused on interoperability standards for health data, knowledge graphs, the data quality framework, patient-generated health data, AI reasoning, federated approaches, security, and privacy. Based on our findings, we developed a template for designing the EHDS2 interoperability framework in alignment with the new European Interoperability Framework (EIF) and EHDS governance standards. This template maps EHDS2-recommended standards to the EIF model and principles, linking the proposed EHDS2 data quality framework to relevant International Organization for Standardization (ISO) standards. Using this template, we analyzed and compared how the recommended EHDS2 standards were implemented across the studied projects. During workshops, project teams shared insights on overcoming interoperability challenges and their innovative approaches to bridging gaps in standardization. With support from HSbooster.eu, we facilitated collaboration among these projects to exchange knowledge on standards, legal implementation, project sustainability, and harmonization with EHDS2. The findings from this work, including the created template and lessons learned, will be compiled into an interactive toolkit for the EHDS2 interoperability framework. This toolkit will help existing and future projects align with EHDS2 technical and legal requirements, serving as a foundation for a common EHDS2 interoperability framework. Additionally, standardization efforts include participation in the development of ISO/IEC 21823-3:2021—Semantic Interoperability for IoT Systems. Since no ISO standard currently exists for digital pathology and AI-based image analysis for medical diagnostics, the BigPicture project is contributing to ISO/PWI 24051-2, which focuses on digital pathology and AI-based, whole-slide image analysis. Integrating these efforts with ongoing ISO initiatives can enhance global standardization and facilitate widespread adoption across health care systems.

Record linkage is increasingly used to expand the information available for public health research. An understanding of record linkage methods and the relevant strengths and limitations is important for robust analysis and interpretation of linked data. Here, we describe the approach used by Clinical Practice Research Datalink (CPRD) to link primary care data to other patient level datasets, and the potential implications of this approach for CPRD data analysis. General practice electronic health record software providers separately submit de-identified data to CPRD and patient identifiers to NHS Digital, excluding patients who have opted-out from contributing data. Data custodians for external datasets also send patient identifiers to NHS Digital. NHS Digital uses identifiers to link the datasets using an 8-stage deterministic methodology. CPRD subsequently receives a de-identified linked cohort file and provides researchers with anonymised linked data and metadata detailing the linkage process. This methodology has been used to generate routine primary care linked datasets, including data from Hospital Episode Statistics, Office for National Statistics and National Cancer Registration and Analysis Service. 10.6 million (M) patients from 411 English general practices were included in record linkage in June 2018. 9.1M (86 %) patients were of research quality, of which 8.0M (88 %) had a valid NHS number and were eligible for linkage in the CPRD standard linked dataset release. Linking CPRD data to other sources improves the range and validity of research studies. This manuscript, together with metadata generated on match strength and linkage eligibility, can be used to inform study design and explore potential linkage-related selection and misclassification biases.

The coronavirus disease 2019 (COVID-19) pandemic forced health systems to offer video and telephone visits as in-person visit alternatives. Although video visits offer some benefits compared with telephone visits, they require complex setup, which may disadvantage some patients due to the \"digital divide.\" Our objective was to determine patient and neighborhood characteristics associated with visit modality. This was a cross-sectional study across 1652 primary care and specialty care practices of adult patients at an integrated health system from April 23 to June 1, 2020. We used electronic health record and administrative data. Our primary outcome was visit modality (in-person, video, or telephone), which was captured using billing codes. We assessed predictors of using video vs telephone using multivariable logistic regression. We used hierarchical logistic regression to determine the contribution of patient-, physician-, and practice-level components of variance in the choice of video or telephone visits. We analyzed 231,596 visits by 162,102 patients. Sixty-five percent of the visits were virtual (31.7% telephone, 33.5% video). Patients who were older than 65 years (adjusted odds ratio [AOR], 0.41; 95% CI, 0.40-0.43), Black (AOR, 0.60; 95% CI, 0.57-0.63), Hispanic (AOR, 0.76; 95% CI, 0.73-0.80), Spanish-speaking (AOR, 0.57; 95% CI, 0.52-0.61), and from areas with low broadband access (AOR, 0.93; 95% CI, 0.88-0.98) were less likely to use video visits. Practices (38%) and clinicians (26%) drove more of the variation in video visit use than patients (9%). Telemedicine access differences may compound disparities in chronic disease and COVID-19 outcomes. Institutions should monitor video visit use across demographics and equip patients, clinicians, and practices to promote telemedicine equity.