{
  "abstract": "Background Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a high multimorbidity burden. However, existing risk assessment instruments prioritise physiological measures while overlooking systemic comorbidities. We aim to develop and validate an electronic health record (EHR)-embedded artificial intelligence (AI) model—AiRES (AI in patients with RESpiratory disease)—to predict the 30-day, 90-day and 180-day risks of all-cause and index-disease hospitalisations. This model represents a first step towards a clinical decision support tool for personalised multimorbidity management in patients with CRD.Method and analysis Patients aged ≥18 years with a validated case definition of asthma and COPD will be identified from Singapore health administrative data (2012–2020). Candidate predictors will include age, sex, ethnicity, housing type, and comorbidities, measured across multiple care settings as visit frequency, grouped at quarterly intervals in Year 1 and annually for Years 2 and 3 over a 3-year lookback window. We will predict 30-day, 90-day, and 180-day risks of (1) all-cause and (2) asthma/COPD-specific hospital admissions using up to five randomly selected index dates per individual. Three machine learning algorithms—logistic regression (LR) with Lasso regularisation, eXtreme Gradient Boosting, and Categorical Boosting—will be trained using 10-fold cross-validation (CV) with an ensemble feature selection strategy. The optimal model, selected based on performance and feature importance, will be benchmarked against two reference models: a full LR and a Zero-Inflated Negative Binomial regression with hospitalisation history as the sole predictor. Discrimination and calibration will be assessed using internal-external cluster-based and temporal CV. Clinical utility will be evaluated using decision curve analysis.Ethics and dissemination This study obtained ethics approval from the National University of Singapore (NUS-IRB-2024-849). Results will be published in international peer-reviewed journals.",
  "authors": [
    {
      "affiliations": [
        "Saw Swee Hock School of Public Health, National University of Singapore, Singapore"
      ],
      "name": "Wei Ying Tan"
    },
    {
      "affiliations": [
        "Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California, USA"
      ],
      "name": "Tae Yoon Lee"
    },
    {
      "affiliations": [
        "Saw Swee Hock School of Public Health, National University of Singapore, Singapore",
        "Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore",
        "Ministry of Health, Singapore"
      ],
      "name": "Kelvin Bryan Tan"
    },
    {
      "affiliations": [
        "Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore",
        "Duke-NUS Medical School, National University of Singapore, Singapore"
      ],
      "name": "Mariko Siyue Koh"
    },
    {
      "affiliations": [
        "Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore",
        "Health Services and Outcomes Research, National Healthcare Group, Singapore"
      ],
      "name": "John A Abisheganaden"
    },
    {
      "affiliations": [
        "Health Services Research Centre, Singapore Health Services, Singapore"
      ],
      "name": "Sean Shao Wei Lam"
    },
    {
      "affiliations": [
        "Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore",
        "Department of Respiratory and Critical Care Medicine, Tan Tock Seng Hospital, Singapore"
      ],
      "name": "Sanjay H Chotirmall"
    },
    {
      "affiliations": [
        "Pfizer, Chennai, India"
      ],
      "name": "Chandra Prakash Yadav"
    },
    {
      "affiliations": [
        "Department of Respiratory and Critical Care Medicine, Changi General Hospital, Singapore"
      ],
      "name": "Anthony Chau Ang Yii"
    },
    {
      "affiliations": [
        "Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore",
        "Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore",
        "Duke-NUS Medical School, National University of Singapore, Singapore"
      ],
      "name": "Pei Yee Tiew"
    },
    {
      "affiliations": [
        "Division of Respiratory and Critical Care Medicine, Department of Medicine, National University Hospital, National University Health System, Singapore",
        "Division of Respiratory and Critical Care Medicine, National University Health System, Alexandra Hospital, Singapore"
      ],
      "name": "Mei Fong Liew"
    },
    {
      "affiliations": [
        "Saw Swee Hock School of Public Health, National University of Singapore, Singapore"
      ],
      "name": "Qi Sun"
    },
    {
      "affiliations": [
        "Saw Swee Hock School of Public Health, National University of Singapore, Singapore"
      ],
      "name": "Wenjia Chen"
    }
  ],
  "title": "Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol",
  "uid": "34e77571-60f8-58a2-9d4f-7430759cad12"
}