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A study of factors related to patients’ length of stay using data mining techniques in a general hospital in southern Iran

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Abstract

Purpose

The length of stay (LOS) in hospitals is a widely used indicator for goals such as health care management, quality control, utilizing hospital services and resources, and determining the degree of efficiency. Various methods have been used to identify the factors influencing the LOS. This study adopts a comparative approach of data mining techniques for investigating effective factors and predict the length of stay in Shahid-Mohammadi Hospital, Bandar Abbas, Iran.

Methods

Using a dataset consists of 526 patient records of the Shahid-Mohammadi Hospital from March 2016 to March 2017, factors affecting the LOS were ranked using information gain and correlation indices. In addition, classification models for LOS prediction were created based on nine data mining classifiers applied with and without feature selection technique. Finally, the models were compared.

Results

The most important factors affecting LOS are the number of para-clinical services, counseling frequency, clinical ward, the specialty and the degree of the doctor, and the cause of hospitalization. In addition, regarding to the classifiers created based on the dataset, the best accuracy (83.91%) and sensitivity (80.36%) belongs to the Logistic Regression and Naïve Bayes respectively. In addition, the best AUC (0.896) belongs to the Random Forest and Generalized Linear classifiers.

Conclusion

The results showed that most of the proposed models are suitable for classification of the length of stay, although the Logistic Regression might have a slightly better performance than others in term of accuracy, and this model can be used to determine the patients’ Length of Stay. In general, continuous monitoring of the factors influencing each of the performance indicators based on proper and accurate models in hospitals is important for helping management decisions.

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Acknowledgements

This study is part of a registered research project with the grant number of 9520 and ethical code of HUMS.REC.1395.56 from Deputy of Research and Technology of Hormozgan University of Medical Sciences. We wish to thank the deputy of the university’s research and technology for its supports, also we are sincerely thankful to our counselors in Clinical Research Development Center of Shahid Mohammadi Hospital.

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Authors and Affiliations

  1. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

    Seyed Mohammad Ayyoubzadeh, Marjan Ghazisaeedi & Sharareh Rostam Niakan Kalhori

  2. Students’ Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran

    Seyed Mohammad Ayyoubzadeh

  3. Infectious and Tropical Diseases Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Mehdi Hassaniazad

  4. Department of Health Information Technology, Faculty of Para-Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Tayebeh Baniasadi

  5. Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Keivan Maghooli

  6. Social Determinants in Health Promotion Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Kobra Kahnouji

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  1. Seyed Mohammad Ayyoubzadeh
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Correspondence to Tayebeh Baniasadi.

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Ayyoubzadeh, S.M., Ghazisaeedi, M., Rostam Niakan Kalhori, S. et al. A study of factors related to patients’ length of stay using data mining techniques in a general hospital in southern Iran. Health Inf Sci Syst 8, 9 (2020). https://doi.org/10.1007/s13755-020-0099-8

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