Predictors of hospital readmissions in internal medicine patients: Application of Andersen's Model

Kaya, Sıdıka; Güven, Gülay Sain; Aydan, Seda; Toka, Onur

doi:10.1002/hpm.2648

Cited by 17 publications

(16 citation statements)

References 29 publications

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“…We also found that longer LOS within the index admission puts patients at risk of multiple and longer readmission events. This result is partially consistent with some other studies on internal medicine patients conducted in civilian settings (4,17,20), which examined a much shorter post-discharge period than the present study. Still, a longer LOS seems to be an important factor for predicting the risk of repeated future readmissions.…”

Section: Discussionsupporting

confidence: 93%

“…This approach also enabled the identification of high-risk patients who are the most appropriate target group for reducing the overall number of readmission events. To date, numerous studies have examined 30-day readmission for various severe diseases and suggested that it is associated with the male sex (OR=1.83, P=0.02), ICU stay (OR=2.5, P=0.049), LOS (4), comorbidity score (17), and different socioeconomic factors (18), although similar studies are rare in military settings.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment Rates and Causes of Readmissions in Military Casualties

Gharehchahi¹,

Mahmoudi²,

Khoshmohabat³

et al. 2021

Preprint

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Introduction: Military medical care encompasses domains such as the long-term prognosis, morbidity, and quality of life of survivors after discharge from the hospital. The identification factors affecting hospitalization and readmissions are crucial in military settings. The study aimed to assess rates and causes of readmissions in military casualties.Methods: We included 775 military personnel with combat-related injuries from September 2014 to October 2019. We determined readmissions if they occurred within one year since the date of discharge from the index admission. The data was included regarding the pattern and mechanism of injury, Abbreviated Injury Scale (AIS), injury severity score (ISS), primary and subsequent treatments and procedures, experienced side effects, source of admission, hospital care unit, and the length of stay in the hospital. Results: The mean age of the patients was 27.99±7.55 years. The great majority of the investigated combat-related injuries were penetrating (N=639, 82.5%), followed by blunt (N=97, 12.5%). The most injured part of the body was the extremities (N=360, 46.5%), followed by the head and neck (N=175, 22.6%) and the abdomen and pelvis (N=106, 13.7%). The most common reason for the readmission event number 1-7 was overall wound infection. The average length of hospitalization during the index admission was 9.48±12.07 days. There was a significant relationship between multiple readmissions and total readmission days and LOS, max AIS, ISS, side effects, and blood transfusion(P<0.001 for all the variables). Among the variables influencing multiple readmissions, ISS>24 led to the highest risk. Conclusion: A longer LOS within the index admission and its associated factors put patients at risk of multiple and longer readmission events in the future. The outcomes imply that patients with more severe injuries may require high-quality care for longer durations as part of the initial hospital inpatient stay, and this may motivate more effective management of combat-related injuries and the associated medical costs.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Assessment Rates and Causes of Readmissions in Military Casualties

Gharehchahi¹,

Mahmoudi²,

Khoshmohabat³

et al. 2021

Preprint

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“…Within the scope of other studies, between 50.6% and 61.7% of women used health care (Dhingra et al, 2010;Hong et al, 2019;Conner, 2012;Jin et al, 2019;Roh et al, 2017;Liu et al, 2019). However, some studies determine that men (around 53%) receive more health services (Holtzman et al, 2015;Kaya et al, 2019).…”

Section: Discussion and Limitationsmentioning

confidence: 99%

“…In this study, it was revealed that the most married people (72.7%) used a family medicine. If we look at similar studies on the subject, it was determined that 52.9% to 84% of the married people use health service (Heider et al, 2014;Hong et al, 2019;Jin et al, 2019;Ogunsanya et al, 2016;Kaya et al, 2019;Franck et al, 2020;Liu et al, 2019). Some studies determine that those who receive health services (66% and 84.6%) are not married (single, divorced and widows) Hirshfield et al, 2018;Lee et al, 2020).…”

Section: Discussion and Limitationsmentioning

confidence: 99%

Aile Hekimliğine Olan Talebi Etkileyen Faktörler: Davranışsal Model İçin Türkiye Verilerinden Kanıtlar

Kurutkan

Yıldız

ARSLAN

et al. 2021

İzmir İktisat Dergisi

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This study aims to investigate the effects of chronic diseases and socio-economic factors on the demand for family medicine. The basic approach used is Andersen's behavioral health model. The variables used in the analysis were obtained from the “TurkStat Health Survey” micro data set for 2016. Three models were established to determine the degree of chronic disease data and socio-economic variables affecting health demand. Binary Logit regression analysis was used in the analysis of models. The variables such as gender, age, employment status, learning difficulties, concentration problems, treatment costs covered by the Social Security Institution (SGK), having a reliable relative, receiving help from neighbors, delaying health care appointments, having chronic hypertension and diabetes are the variables that influence the condition of receiving service from the family medicine (p

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“…3,6 Previous studies have identified factors associated with hospital admissions in older populations. [7][8][9] However, there is a paucity of research that reports predictors of urgency-specific (planned and unplanned) hospital admission.…”

Section: Introductionmentioning

confidence: 99%

Estimating unplanned and planned hospitalization incidents among older Australian women aged 75 years and over: The presence of death as a competing risk

Shebeshi

Dolja‐Gore

Byles

2020

Health Planning & Management

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Summary Objectives To estimate the incidence of unplanned and planned hospitalization and identify associated factors among older women aged 75 years and over. Methods This study is a prospective longitudinal cohort study (over the period 2001‐2016). Women born between 1921 and 1926 were included from the Australian Longitudinal Study on Women's Health (ALSWH). ALSWH self‐reported data were linked with New South Wales's state Admitted Patient Data Collection. A competing risk analysis was performed using SAS v 9.4. Results Overall, during the 15‐year observation period, 86.7% of women experienced at least one unplanned admission and 60.3% experienced at least one planned admission. The complement of Kaplan‐Meier survival function overestimates hospitalization incidence compared to cumulative incidence function in the presence of a competing risk, that is, “death.” Predisposing factors (older age and not partnered) and need factors (hospital doctor visit, GP or family doctor visit, poor perceived general health, and having at least one chronic disease) were associated with increased unplanned admission. First language other than English and not having private health insurance showed a negative association with planned admission; specialist doctor visits had a positive association. Conclusions Hospital admission was influenced by predisposing and enabling factors, as well as need. Intervention aiming to support older people who do not have private health insurance may be required to improve the goal of equal access to healthcare through planned admissions people with equal need.

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Predictors of hospital readmissions in internal medicine patients: Application of Andersen's Model

Cited by 17 publications

References 29 publications

Assessment Rates and Causes of Readmissions in Military Casualties

Assessment Rates and Causes of Readmissions in Military Casualties

Aile Hekimliğine Olan Talebi Etkileyen Faktörler: Davranışsal Model İçin Türkiye Verilerinden Kanıtlar

Estimating unplanned and planned hospitalization incidents among older Australian women aged 75 years and over: The presence of death as a competing risk

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