An exploratory, retrospective evaluation of Ambulatory Integration of the Medical and Social (AIMS), a care coordination model designed to integrate medical and non-medical needs of patients and delivered exclusively by social workers was conducted to examine mean utilization of costly health care services for older adult patients. Results reveal mean utilization of 30-day hospital readmissions, emergency department (ED) visits, and hospital admissions are significantly lower for the study sample compared to the larger patient population. Comparisons with national population statistics reveal significantly lower mean utilization of 30-day admissions and ED visits for the study sample. The findings offer preliminary support regarding the value of AIMS.

Download full-text PDF

Source
http://dx.doi.org/10.1080/00981389.2016.1164269DOI Listing

Publication Analysis

Top Keywords

ambulatory integration
8
integration medical
8
medical social
8
social aims
8
retrospective evaluation
8
utilization 30-day
8
study sample
8
aims model
4
model retrospective
4
evaluation exploratory
4

Similar Publications

Background: Remote patient monitoring (RPM) aims to improve patient access to care and communication with clinical providers. Overall, understanding the usability of RPM applications and their influence on clinical care workflows is limited from the perspectives of clinician end users at a cancer center in the Northeastern United States.

Objective: This study aims to explore the usability and functionality of RPM and elicit the perceptions and experiences of oncology clinicians using RPM for oncology patients after hospital discharge.

View Article and Find Full Text PDF

Background: Individuals with metabolic syndrome (MetS) are at a higher risk of developing depressive symptoms, with inflammation hypothesized to mediate this association. This study used data from the National Health and Nutrition Examination Survey (NHANES) (2015-2020) to investigate the relationship between MetS and depression and assess the mediating role of inflammatory markers.

Methods: This cross-sectional study included 20,520 participants.

View Article and Find Full Text PDF

Age Self Care-Resilience, a medical group visit program targeting pre-frailty: A mixed methods pilot clinical trial.

J Frailty Aging

February 2025

Division of Geriatrics and Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.

Background: Pre-frailty is highly prevalent and multimodal lifestyle interventions are effective for preventing transition to frailty. However, little is known about the potential for medical group visits (MGV) to prevent frailty progression.

Objectives: To assess the feasibility and acceptability of the MGV Age Self Care-Resilience.

View Article and Find Full Text PDF

Purpose: We aimed to determine whether implementation of clinical decision support (CDS) tool integrated into the electronic health record (EHR) of a multi-site academic medical center increased the proportion of patients with American Urological Association (AUA) "high risk" microscopic hematuria (MH) who receive guideline concordant evaluations.

Materials And Methods: We conducted a two-arm cluster randomized quality improvement project in which 202 ambulatory sites from a large health system were randomized to either have their physicians receive at time of test results an automated CDS alert for patients with 'high-risk' MH with associated recommendations for imaging and cystoscopy (intervention) or usual care (control). Primary outcome was met if a patient underwent both imaging and cystoscopy within 180 days from MH result.

View Article and Find Full Text PDF

Recognizing human body motions opens possibilities for real-time observation of users' daily activities, revolutionizing continuous human healthcare and rehabilitation. While some wearable sensors show their capabilities in detecting movements, no prior work could detect full-body motions with wireless devices. Here, we introduce a soft electronic textile-integrated system, including nanomaterials and flexible sensors, which enables real-time detection of various full-body movements using the combination of a wireless sensor suit and deep-learning-based cloud computing.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!