Patient health status key component of capitation fee

1996 ◽  
Vol 86 (1) ◽  
pp. 5-5
Keyword(s):  
Health Status ◽  
Patient Health Status ◽  
Patient Health ◽  
Capitation Fee

PATIENT HEALTH STATUS TRAJECTORIES IN HEART FAILURE WITH RECOVERED EJECTION FRACTION

2019 ◽  
Vol 73 (9) ◽  
pp. 970
Author(s):  
Peter Wohlfahrt ◽  
Jose Nativi-Nicolau ◽  
Mingyuan Zhang ◽  
Craig Selzman ◽  
Tom Greene ◽  
...  
Keyword(s):  
Heart Failure ◽  
Health Status ◽  
Ejection Fraction ◽  
Patient Health Status ◽  
Patient Health

scholarly journals Chronic non-specific abdominal complaints in general practice: a prospective study on management, patient health status and course of complaints

2006 ◽  
Vol 7 (1) ◽  
Author(s):  
Henriëtte AM van den Heuvel-Janssen ◽  
Jeroen AJ Borghouts ◽  
Jean WM Muris ◽  
Bart W Koes ◽  
Lex M Bouter ◽  
...  
Keyword(s):  
General Practice ◽  
Health Status ◽  
Prospective Study ◽  
Patient Health Status ◽  
Patient Health ◽  
A Prospective Study

scholarly journals Factors Affecting Treatment with Life-Saving Interventions, Computed Tomography Scans and Specialist Consultations

2020 ◽  
Vol 17 (8) ◽  
pp. 2914
Author(s):  
Chu-Chieh Chen ◽  
Chin-Yi Chen ◽  
Ming-Chung Ko ◽  
Yi-Chun Chien ◽  
Emily Chia-Yu Su ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Health Status ◽  
Ambulatory Care ◽  
Patient Characteristics ◽  
Multivariate Logistic Regression Model ◽  
Medical Institutions ◽  
Patient Health Status ◽  
Life Saving ◽  
Patient Health ◽  
The Impact

Background: Emergency treatments determined by emergency physicians may affect mortality and patient satisfaction. This paper attempts to examine the impact of patient characteristics, health status, the accredited level of hospitals, and triaged levels on the following emergency treatments: immediate life-saving interventions (LSIs), computed tomography (CT) scans, and specialist consultations (SCs). Methods: A multivariate logistic regression model was employed to analyze the impact of patient characteristics, including sex, age, income and the urbanization degree of the patient’s residence; patient health status, including records of hospitalization and the number of instances of ambulatory care in the previous year; the Charlson Comorbidity Index (CCI) score; the accredited level of hospitals; and the triaged level of emergency treatments. Results: All the patient characteristics were found to impact receiving LSI, CT and SC, except for income. Furthermore, a better health status was associated with a decreased probability of receiving LSI, CT and SC, but the number of instances of ambulatory care was not found to have a significant impact on receiving CT or SC. This study also found no evidence to support impact of CCI on SC. Hospitals with higher accredited levels were associated with a greater chance of patients receiving emergency treatments of LSI, CT and SC. A higher assigned severity (lower triaged level) led to an increased probability of receiving CT and SC. In terms of LSI, patients assigned to level 4 were found to have a lower chance of treatment than those assigned to level 5. Conclusions: This study found that several patient characteristics, patient health status, the accredited level of medical institutions and the triaged level, were associated with a higher likelihood of receiving emergency treatments. This study suggests that the inequality of medical resources among medical institutions with different accredited levels may yield a crowding-out effect.

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