Dean Health Systems

Abstract Background Venous thromboembolism (VTE) remains a leading cause of mortality following metabolic and bariatric surgery. Although D-dimer is a widely used biomarker of fibrinolysis and thrombosis, postoperative D-dimer kinetics after MBS have not been systematically characterized. Objectives To describe the temporal pattern of perioperative D-dimer changes after MBS and assess the relationship with procedural invasiveness and detected VTE events. Methods We conducted a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines. MEDLINE, Embase, Web of Science, Scopus, and Cochrane Central were searched from inception to 30 October 2025. We included cohort studies and randomized controlled trials reporting D-dimer levels in adults undergoing MBS. Two reviewers independently screened studies, extracted data, and assessed quality using the Cochrane Risk of Bias 2.0 tool and the Newcastle-Ottawa Scale. Results Eight studies (522 patients) were included. The majority of studies demonstrated postoperative D-dimer elevation (86.6% to 496% above baseline), with four distinct temporal patterns: early peak within 24 hours (2 studies, up to 496% increase), delayed peak at days 1–2 with subsequent decline (2 studies), sustained elevation at 1 month (2 studies), and long-term decline below baseline at follow-up (2 studies). Despite marked elevations, VTE incidence was low (0.38%, 2/522 patients). One study documented persistent thromboelastography hypercoagulability at 6 months despite D-dimer normalization. Conclusions D-dimer elevations are common after metabolic and bariatric surgery, but may has limited clinical utility for VTE. Conventional markers may underestimate prolonged hypercoagulability. Clinical evaluation should guide thromboprophylaxis rather than routine D-dimer monitoring.

The authors examined the relationship between mother and child activity. The authors compared moderate-vigorous physical activity (MVPA) and sedentary time of low-income mothers with obesity and their 6- to 12-year-old children on week (WD) and weekend (WE) days. A total of 196 mother-child pairs wore accelerometers simultaneously for a week. Mothers completed questionnaires. Spearman correlation and multivariate regression were used. WE MVPA (accelerometry) was significantly correlated between mothers with children aged 6-7 (rs = .35) and daughters (rs = .27). Self-reported maternal PA time spent with one of their children was significantly correlated with the WE MVPA of all children (rs = .21) and children aged 8-10 (rs = .22) and with the WD MVPA of all children (rs = .15), children aged 8-10 (rs = .23), aged 11-12 (rs = .52), and daughters (rs = .37), and inversely correlated to the WD sedentary time of all children (rs = -.21), children aged 8-10 (rs = -.30), aged 11-12 (rs = -.34), daughters (rs = -.26), and sons (rs = -.22). In multivariate regression, significant associations were identified between reported child-mother PA time together and child MVPA and sedentary time (accelerometry). Mothers may influence the PA levels of their children with the strongest associations found in children aged 6-7 and daughters. Mother-child coparticipation in PA may lead to increased child MVPA and decreased sedentary behavior.

A patient's stay at a hospital may encompass various departments or units. Since many critical and complex problems occur at the interfaces of healthcare delivery systems, safe and efficient transitions between the departments within a hospital has significant importance. This paper presents a Markov chain-based model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward in small and medium-sized community hospitals. To make the analytical study tractable, an iteration method is introduced to approximate the system performance during transitions, including direct transferring probabilities without waiting, average patient occupancy in each department, and average patient length of stay. In addition, system properties, such as monotonicity and sensitivity, are analyzed. It is shown that such a method has a high accuracy in performance estimation and can be used to study and improve patient transitions in small or medium-sized hospitals.

Primary care is the backbone of the U.S. healthcare delivery system. In primary care clinics, teams led by providers play a central role in care delivery. A care service task typically requires joint efforts among the care providers and support staff in the team. Thus, communications within a team are critical to ensure effective collaboration and coordination between team members to provide high quality of care. Due to such an importance, team communication and collaboration have received a considerable amount of research attention. However, most research is qualitative or based on empirical studies. This paper introduces an analytical framework of modeling, analysis, and improvement of team communication and collaboration process in primary care clinics. Specifically, using a queueing network model, the physicians, nurses, and medical assistants are modeled as servers and the communication and collaboration tasks are viewed as customers. The team members interact with each other multiple times to accomplish a task. The efficiency of the team communication and collaboration process is characterized by task throughput, task completion time, and the number of iterations to finish a task. Analytical formulas to evaluate such performances are derived and system properties are investigated. In addition, bottleneck analysis is carried out to identify the constraint that impedes the system performance in the strongest manner. Finally, a case study at a primary care clinic is presented to illustrate the applicability of the model. Note to Practitioners —In primary care clinics, care delivery activities are carried out by a team of care providers and support staff, such as physicians, nurses, and medical assistants. An activity or a task may need to be carried out by more than one team member multiple times. Thus, communication and collaboration between team members are critical to ensure safety and high quality of care services. Modeling, analysis, and improvement in the team communication and collaboration process are of significant importance. Although numerous studies have been found regarding team communication and collaboration issues, quantitative and analytical models to address the efficiency of such processes are not available. The goal of this paper is to present an analytical framework using queueing network models. Using this framework, the efficiency of the process can be evaluated and system properties can be investigated. In addition, the most critical constraints, i.e., bottlenecks, can be identified to improve process performance.

This letter introduces a causal Bayesian network model to study readmissions reduction for chronic obstructive pulmonary disease (COPD) patients. The model employs a Bayesian network learning method and adopts domain knowledge. Using this model, we analyze the impacts of critical variables on a patient's readmission risk by the manipulation of such variables. Through this analysis, effective intervention options to reduce readmission can be identified, which can provide a quantitative tool for designing personalized interventions to reduce COPD readmissions.

This paper studies the post-surgery care process for total joint replacement (TJR) patients. First, factors affecting readmission risks are identified and a multivariate logistic regression model is introduced to predict a patient's readmission probability from the patient profile. Based on readmission risk and patient eligibility, different intervention processes can be carried out. Specifically, three intervention options are considered: nursing home, home care service, and self-care. A discrete-event simulation model is introduced to illustrate how intervention process moves along the 90 day post discharge phase. Finally, the models are used to identify the best intervention strategy to reduce overall readmission rate with minimal cost.

Health information technology, i.e. secure messaging, can support high-quality, efficient care. Secure messaging – encrypted communication between patient and clinician or staff, similar to email – can facilitate patient-reported information and communication, but its fit with clinical workflow is not understood. Fifteen primary care clinicians and staff were interviewed and observed over 35 hours to understand the impact of secure messaging on ambiguity within the care delivery workflow. We developed a general workflow diagram for secure messaging, and identified three types of ambiguity relating to workflow, content of communication, and multiple points of data entry. While the use of secure messaging can help to clarify and document patient information, it can also increase ambiguity, particularly relating to the organization of work and workflow. Understanding how to design and implement technology to support multiple stakeholders, including patients, while considering the work system is a major area for future research.

Few smokers receive evidence-based tobacco treatment during healthcare visits. Electronic health records (EHRs) present an opportunity to efficiently identify and refer smokers to state tobacco quitlines. The purpose of this case study is to develop and evaluate a secure, closed-loop EHR referral system linking patients visiting healthcare clinics with a state tobacco quitline. A regional health system, EHR vendor, tobacco cessation telephone quitline vendor, and university research center collaborated to modify a health system's EHR to create an eReferral system. Modifications included the following: clinic workflow adjustments, EHR prompts, and return of treatment delivery information from the quitline to the patient's EHR. A markedly higher percentage of adult tobacco users were referred to the quitline using eReferral than using the previous paper fax referral (14 vs. 0.3%). The eReferral system increased the referral of tobacco users to quitline treatment. This case study suggests the feasibility and effectiveness of a secure, closed-loop EHR-based eReferral system.

Macrolides have antimicrobial and anti-inflammatory properties that may be useful in the treatment of chronic asthma. We performed a randomized, placebo-controlled, double-blinded effectiveness trial of 12 weekly doses of adjunctive azithromycin, with follow-up to 1 year after randomization, in adults with persistent asthma. Measurements included overall asthma symptoms, asthma quality of life (AQL), and asthma control. Eligible subjects who declined to participate in randomization were offered enrollment into a parallel open-label (OL) azithromycin treatment arm. Of 304 adult asthma patients screened, 97 (32%) were enrolled: 38 were randomized to azithromycin, 37 were randomized to placebo, and 22 opted in as OL subjects. OL subjects had higher rates of severe persistent asthma compared with randomized subjects (32% vs 8%, respectively; P = .012). At 1 year, compared with the placebo arm, subjects randomized to azithromycin were more likely to have an AQL score ≥1 unit increase compared with baseline, but this difference was not statistically significant (36% vs 21% for placebo; P = .335). Compared with placebo, OL subjects had significant improvements in overall asthma symptoms from baseline (P = .0196), AQL (P = .0006), and asthma control (P = .0148). Adults with asthma who were randomized to azithromycin did not show statistically significant improvement in asthma outcomes, although the study was underpowered to detect clinical improvement in 15% (number needed to treat = 7). Adults with severe persistent asthma who elected OL treatment documented clinical improvements in asthma symptoms, AQL, and asthma control that persisted after completion of OL azithromycin (number needed to treat = 2).

There is no consensus on the ideal gastrojejunostomy anastomosis (GJA) technique in laparoscopic Roux-en-Y gastric bypass (LRYGB). We reviewed our experience with three GJA techniques (hand-sewn (HSA), linear-stapled (LSA), and 25-mm circular-stapled (CSA)) to determine which anastomosis technique is associated with the lowest early (60-day) anastomotic complication rates. From November 2004 through December 2009, 882 consecutive patients underwent LRYGB using three GJA techniques: HSA, LSA, and CSA. All patients had a minimum of 2months follow-up. Records were reviewed for postoperative gastrojejunostomy leak, stricture, and marginal ulcer, and these early complications were classified according to anastomosis technique. Multivariate analysis was performed to determine associations between complications and anastomosis technique. Preoperative demographics, length of hospital stay, and postoperative follow-up did not differ between the three groups. The majority of patients underwent LSA (n = 514, 61.6%) followed by HSA (n = 180, 21.6%) and CSA (n = 140, 16.8%). Using multivariate analysis, there were no statistically significant differences in the rates of leak (LSA 1.0%, HSA 1.1%, CSA 0.0%, p = 0.480), stricture (LSA 6.0%, HSA 6.1%, CSA 4.3%, p = 0.657), or marginal ulcer (LSA 8.0%, HSA 7.7%, CSA 3.6%, p = 0.180). The three techniques can be used safely with a low complication rate. Our data do not identify a superior anastomosis technique.