Corpus ID: 80514905

Strategies Clinic Managers Use to Reduce Missed Medical Appointments

@inproceedings{Skym2017StrategiesCM,
  title={Strategies Clinic Managers Use to Reduce Missed Medical Appointments},
  author={Sophea Ey Skym},
  year={2017}
}
Strategies Clinic Managers Use to Reduce Missed Medical Appointments by Sophea Ey Skym MBA, University of Phoenix, 2011 MSN, University of Phoenix, 2011 BSN, Medical College of Virginia. [...] Key Method Change management theory guided the scope and analysis.Expand
1 Citations
Increasing Uninsured Patients' Compliance with Return Primary Care Visits
TLDR
The findings of this project have potential to create social change in clinics for uninsured in the community by addressing food insecurity and providing patients an incentive to return for care every 6 months. Expand

References

SHOWING 1-10 OF 191 REFERENCES
A Model Program to Reduce Patient Failure to Keep Scheduled Medical Appointments
TLDR
A model intervention program developed by a quality improvement committee at a Northwest Ohio community health center is credited with significantly reducing rates of patient failure to keep scheduled medical and dental clinic appointments. Expand
Implementing shared medical appointments for heart failure patients in a community cardiology practice: a pilot study.
TLDR
Satisfaction was high among patients and office staff, and billing charges were not significantly different for SMAs versus usual appointments, suggesting SMAs are a feasible option in a community cardiology practice. Expand
Getting patients in the door: medical appointment reminder preferences
TLDR
The number of missed appointments and reasons for missing appointments are consistent with prior research, and patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients’ needs. Expand
REASONS FOR MISSING APPOINTMENTS IN GENERAL CLINICS OF PRIMARY HEALTH CARE CENTER IN RIYADH MILITARY HOSPITAL, SAUDI ARABIA
TLDR
Knowing the factors that are associated with missed appointments facilitates the prospective identification of patients at risk of missing appointment and helps the continuous quality improvement for future planning which may include program modifications, and formulation of strategies to reduce the risk and rate of non-attendance. Expand
Appointment keeping for medical review among patients with selected chronic diseases in an urban area of Uganda
TLDR
Patients missed appointments mainly due to: financial and health system barriers, conflicting commitments with appointments, and perceptions of the disease condition. Expand
Influence of Shared Medical Appointments on Patient Satisfaction: A Retrospective 3-Year Study
TLDR
Overall, SMA patients appear more satisfied with their care relative to patients receiving usual care, and this model of care may also improve access to care and deliver care that patients find to be sensitive to their needs. Expand
No-Show to Primary Care Appointments
TLDR
Interventions designed to target reasons for no- show are needed to help reduce the no-show rate, improve access and decrease health disparities in underserved patient populations. Expand
Patients' and providers' satisfaction with shared medical appointments.
TLDR
Patients' and providers' attitude and satisfaction with SMAs after attending at least two are measured, and the most appropriate form of SMA suited to Australian conditions is considered. Expand
Appointment system design with interruptions and physician lateness
TLDR
It is shown that, in general, appointment slots should be shorter and pushed later in the session as lateness increases and, as interruptions rise, appointments in the middle of the session should be longer. Expand
Risk factor model to predict a missed clinic appointment in an urban, academic, and underserved setting.
TLDR
The aim of this study was to identify predictors of a missed appointment and develop a model to predict an individual's likelihood of missing an appointment and the strongest predictors were percentage of previously missed appointments and wait time. Expand
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