Objective: To identify strengths, obstacles, changes in the environment, and capabilities of primary care teams and support units, with the aim of providing high-quality care in an integrated healthcare area.
Design: Mixed methods study based on the SWOT matrix and CAME analysis.
Location: Primary care, Valencian community.
Participants: A total of 271 professionals from different collectives and patient association representatives participated. 99 in the idea generation phase, 154 in the SWOT matrix development phase, and 18 in the CAME analysis development phase.
Interventions: A SWOT-CAME analysis was conducted, from which action lines were established. Information capture was carried out through nominal groups, and the consensus phase involved integrating all professionals through Delphi and consensus conference techniques.
Main Measurements: Prioritization of proposals to maintain strengths, address threats, exploit opportunities, and correct weaknesses within the framework of an integrated healthcare area action plan.
Results: A total of 82 different ideas were proposed (20 strengths; 40 weaknesses; 4 threats; 12 opportunities; 6 threats-opportunities), which, once prioritized, were translated into 7 lines and 33 prioritized actions/interventions (CAME analysis).
Conclusions: Integrated care, seeking collaborative approaches between care levels, redefining roles, digital solutions, staff training, and improvements in equipment and support processes, along with measures to address the aging population and the needs of socio-sanitary centers, constitute the challenges to be addressed.
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http://dx.doi.org/10.1016/j.aprim.2023.102809 | DOI Listing |
J Med Internet Res
January 2025
Faculty of Medicine, University of Geneva, Geneva, Switzerland.
This study examines disparities in research retractions due to misconduct, identifying countries with the highest retraction counts and those disproportionately represented relative to population and publication output. The findings emphasize the need for improved research integrity measures.
View Article and Find Full Text PDFImportance: Fragility fractures result in significant morbidity.
Objective: To review evidence on osteoporosis screening to inform the US Preventive Services Task Force.
Data Sources: PubMed, Embase, Cochrane Library, and trial registries through January 9, 2024; references, experts, and literature surveillance through July 31, 2024.
JAMA Netw Open
January 2025
Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts.
Importance: Nearly all Medicare Advantage (MA) plans offer dental, vision, and hearing benefits not covered by traditional Medicare (TM). However, little is known about MA enrollees' use of those benefits or how much they cost MA insurers or enrollees.
Objective: To estimate use, out-of-pocket (OOP) spending, and insurer payments for dental, hearing, and vision services among Medicare beneficiaries.
J Gen Intern Med
January 2025
Department of Neurology, University of Michigan Medical School, Ann Arbor, MI, USA.
Background: Previous reports suggest patient and caregiver lack of awareness of dementia. Little is known about how this varies by ethnicity and how informal (family) caregiver burden is associated with knowing a dementia diagnosis.
Objective: To investigate whether participants with probable dementia were aware of a diagnosis provided by a physician and how this differed among Mexican American and non-Hispanic White participants; whether having a primary care physician was associated with dementia diagnosis unawareness; and the association of dementia diagnosis unawareness with caregiver burden.
J Med Syst
January 2025
Department of Computing, University of North Florida, 1 UNF Dr., Jacksonville, 32246, FL, USA.
The "no-show" problem in healthcare refers to the prevalent phenomenon where patients schedule appointments with healthcare providers but fail to attend them without prior cancellation or rescheduling. In addressing this issue, our study delves into a multivariate analysis over a five-year period involving 21,969 patients. Our study introduces a predictive model framework that offers a holistic approach to managing the no-show problem in healthcare, incorporating elements into the objective function that address not only the accurate prediction of no-shows but also the management of service capacity, overbooking, and idle resource allocation resulting from mispredictions.
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