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Patterns of Social Needs Predict Quality-of-Life and Healthcare Utilization Outcomes in Patients from a Large Hospital System

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Abstract

Background

Unmet social needs (SNs) often coexist in distinct patterns within specific population subgroups, yet these patterns are understudied.

Objective

To identify patterns of social needs (PSNs) and characterize their associations with health-related quality-of-life (HRQoL) and healthcare utilization (HCU).

Design

Observational study using data on SNs screening, HRQoL (i.e., low mental and physical health), and 90-day HCU (i.e., emergency visits and hospital admission). Among patients with any SNs, latent class analysis was conducted to identify unique PSNs. For all patients and by race and age subgroups, compared with no SNs, we calculated the risks of poor HRQoL and time to first HCU following SNs screening for each PSN.

Patients

Adult patients undergoing SNs screening at the Mass General Brigham healthcare system in Massachusetts, United States, between March 2018 and January 2023.

Main Measures

SNs included: education, employment, family care, food, housing, medication, transportation, and ability to pay for household utilities. HRQoL was assessed using the Patient-Reported Outcomes Measurement Information System Global-10.

Key Results

Six unique PSNs were identified: “high number of social needs,” “food and utility access,” “employment needs,” “interested in education,” “housing instability,” and “transportation barriers.” In 14,230 patients with HRQoL data, PSNs increased the risks of poor mental health, with risk ratios ranging from 1.07(95%CI:1.01–1.13) to 1.80(95%CI:1.74–1.86). Analysis of poor physical health yielded similar findings, except that the “interested in education” showed a mild protective effect (0.97[95%CI:0.94–1.00]). In 105,110 patients, PSNs increased the risk of 90-day HCU, with hazard ratios ranging from 1.09(95%CI:0.99–1.21) to 1.70(95%CI:1.52–1.90). Findings were generally consistent in subgroup analyses by race and age.

Conclusions

Certain SNs coexist in distinct patterns and result in poorer HRQoL and more HCU. Understanding PSNs allows policymakers, public health practitioners, and social workers to identify at-risk patients and implement integrated, system-wide, and community-based interventions.

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Acknowledgements

The authors thank the clinicians and program staff for their support on the successful implementation of the social needs screening initiative. This study was presented at the International Society for Quality of Life Research 30th Annual Conference in Calgary, Alberta, Canada, 18-21 October, 2023.

Author information

Authors and Affiliations

  1. Patient-Reported Outcomes, Value and Experience (PROVE) Center, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, USA

    Chengbo Zeng PhD, Manraj N. Kaur PhD, Sri Harshini Malapati BS, Jason B. Liu MD, Andrea L. Pusic MD & Maria O. Edelen PhD

  2. Harvard Medical School, Boston, MA, USA

    Chengbo Zeng PhD, Manraj N. Kaur PhD, Sri Harshini Malapati BS, Jason B. Liu MD, Allison S. Bryant MD, David W. Bates MD, Nadine J. McCleary MD, Andrea L. Pusic MD & Maria O. Edelen PhD

  3. Division of Surgical Oncology, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, USA

    Jason B. Liu MD

  4. Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA

    Allison S. Bryant MD

  5. Office of the Chief Medical Officer, Mass General Brigham, Boston, MA, USA

    Allison S. Bryant MD & Peter M. Meyers BS

  6. Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA, USA

    David W. Bates MD

  7. Clinical and Quality Analysis, Information Systems, Mass General Brigham, Boston, MA, USA

    David W. Bates MD

  8. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Nadine J. McCleary MD

  9. Division of Plastic and Reconstructive Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, USA

    Andrea L. Pusic MD

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  1. Chengbo Zeng PhD
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  3. Sri Harshini Malapati BS
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  7. David W. Bates MD
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  8. Nadine J. McCleary MD
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  9. Andrea L. Pusic MD
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  10. Maria O. Edelen PhD
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Corresponding author

Correspondence to Chengbo Zeng PhD.

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Conflict of Interest

Dr. Bates reported receiving a grant from IBM Watson and personal fees from FeelBetter, CORE, NORC, Kaiser Permanente, Early Sense, AESOP, Statista, and having equity in Clew, MDClone, ValeraHealth, FeelBetter, and Guided Clinical Solutions outside the submitted work; additionally, Dr. Bates received honoraria from Industrial Technology Research Institute (Taiwan), Vanderbilt University, and University of Utah; and finally, Dr. Bates has a patent for PHC-028654 on intraoperative clinical decision support. No other conflicts of interest were reported.

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Zeng, C., Kaur, M.N., Malapati, S.H. et al. Patterns of Social Needs Predict Quality-of-Life and Healthcare Utilization Outcomes in Patients from a Large Hospital System. J GEN INTERN MED (2024). https://doi.org/10.1007/s11606-024-08788-6

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  • DOI: https://doi.org/10.1007/s11606-024-08788-6

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