{
  "abstract": "Objectives Unplanned hospital revisits (UHR) among older adults are common and contribute to adverse clinical outcomes, caregiver burden and increased healthcare costs. We aimed to develop and validate a risk prediction model for UHR in older adults to support early identification.Methods We conducted a retrospective cohort study, following the TRIPOD statement, using a Flemish linked database combining primary care and national health insurance data. Adults aged ≥75 years with an all-cause hospital admission in 2014 were included. The primary outcome was UHR, defined as emergency department visits or unplanned hospital admissions within 6 months post-discharge. We used multivariable logistic regression to identify predictors for UHR and develop a risk prediction model. Model performance was assessed using balanced accuracy. Missing data were handled using multiple imputation by chained equations. The model was validated on a held-out test set and a k-nearest neighbour classifier was used to cross-validate risk categories.Results Among 3133 patients, 309 (10%) experienced UHR. The best-performing model had a balanced accuracy of 0.56, with a sensitivity of 58% and a specificity of 54%. Predictors were polypharmacy, male sex, haemoglobin level, number of general practitioner contacts and multimorbidity. Excessive polypharmacy (>9 medications) was associated with a 55% increase in UHR odds. Three UHR risk groups were identified: low-risk (5.1%), medium-risk (8.8%) and high-risk (11.6%).Conclusions UHR are common in older adults, with excessive polypharmacy emerging as a key predictor. The pragmatic model described here provides a valuable tool to stratify older adults into distinct risk groups, identifying a high-risk group that may benefit from targeted interventions.",
  "authors": [
    {
      "affiliations": [
        "Hospital Pharmacy Department, University Hospitals Leuven, Leuven, Belgium"
      ],
      "name": "Julie Hias"
    },
    {
      "affiliations": [
        "Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), KU Leuven, Leuven, Belgium"
      ],
      "name": "Nicolas Saud"
    },
    {
      "affiliations": [
        "Faculty of Medicine, KU Leuven, Leuven, Belgium"
      ],
      "name": "Lotte Blocquiaux"
    },
    {
      "affiliations": [
        "Hospital Pharmacy Department, University Hospitals Leuven, Leuven, Belgium",
        "Department of Pharmaceutical and Pharmacological Sciences, KU Leuven Biomedical Sciences Group, Leuven, Belgium"
      ],
      "name": "Laura Hellemans"
    },
    {
      "affiliations": [
        "Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), KU Leuven, Leuven, Belgium",
        "Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium"
      ],
      "name": "Geert Molenberghs"
    },
    {
      "affiliations": [
        "Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium"
      ],
      "name": "Bert Vaes"
    },
    {
      "affiliations": [
        "InterMutualistic Agency (IMA), Brussels, Belgium"
      ],
      "name": "Xavier Rygaert"
    },
    {
      "affiliations": [
        "Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium",
        "Department of Chronic Diseases, Metabolism and Ageing, KU Leuven, Leuven, Belgium"
      ],
      "name": "Jos Tournoy"
    },
    {
      "affiliations": [
        "Hospital Pharmacy Department, University Hospitals Leuven, Leuven, Belgium",
        "Department of Pharmaceutical and Pharmacological Sciences, KU Leuven Biomedical Sciences Group, Leuven, Belgium"
      ],
      "name": "Lorenz Roger Van der Linden"
    }
  ],
  "title": "Predicting unplanned hospital revisits among community-dwelling older adults: a dynamic cohort study",
  "uid": "517b4876-c7ab-55da-b729-469d44a424de"
}