Shehzad K. Niazi, M.D., is a consultation-liaison psychiatrist, health care informaticist and outcomes researcher. He cares for the mental health needs of patients with complex care needs in acute and subacute settings. He pursues interdisciplinary and multidisciplinary research and implementation projects to assess how psychiatric comorbidities and social determinants of health factors lead to poorer quality of life, caregiver burden, compliance, increased cost and mortality. He develops risk stratification models and associated care pathways available at the point of care. This approach enables physicians to identify patients at high risk, match each patient with the right level of care, and monitor the progress using patient-reported outcomes.
Dr. Niazi collaborates with experts across Mayo Clinic. In particular, he works closely with Aaron C. Spaulding, Ph.D., C. Burcin Taner, M.D., William V. Bobo, M.D., M.P.H., and Terry D. Schneekloth, M.D.
- Patient-reported outcomes measurement. Regulators, payers and other stakeholders expect and require health care providers to monitor and report outcomes. Without such information, clinicians cannot evaluate the value of care. Dr. Niazi's team has leveraged technology to incorporate patient-reported outcomes (PROs) measurements in routine care delivery to identify the individualized needs of patients. Clinicians collect PROs during synchronous and asynchronous assessments for individual and population-level monitoring.
- Impact of psychosocial comorbidities, including social determinants of health on outcomes. Where people are born, grow up, live and work affects quality of life, life expectancy and outcomes of chronic diseases. Dr. Niazi's research team has been quantifying the impact of social determinants of health factors on surgical outcomes by linking and analyzing large national databases, such as United Network for Organ Sharing (UNOS), American Hospital Association (AHA), SEER-Medicare and OptumLabs, to identify potentially modifiable factors associated with poorer outcomes. Additionally, Dr. Niazi is developing multi-omics disease-specific patient cohorts in patients with cancer or who have undergone a transplant.
- Impact of psychiatric comorbidities on the cost of care. Patients with mental illnesses, especially when unrecognized or untreated, experience more significant physical symptoms, higher comorbidities and more functional impairment. These patients have higher rates of relapses, care utilization, hospitalization, early exit from the workforce and premature mortality. Furthermore, cost studies are critical in assessing cost-benefit and cost-effectiveness. The studies conducted by Dr. Niazi's and his research team have demonstrated how psychiatric comorbidities increase the cost of care. The team has also successfully used that data to develop care pathways and used the cost data to make a business case for adding mental health services to meet the psychosocial needs of these patients.
- Applied clinical informatics (ACI). As a clinical informaticist, Dr. Niazi is developing predictive risk-stratification models using artificial intelligence and fair, accountable and transparent (FAT) machine learning. Development and deployment of these models require a consistent and longitudinal collection of patient-reported outcomes (PROs). However, this process can be challenging to implement and can be burdensome for patients. For such monitoring to be successful, Dr. Niazi is working on ACI projects that aim to:
- Eliminate redundancies to reduce the cognitive and response burden on patients.
- Improve clinicians' effective utilization of PRO information.
- Optimally collect appropriate PROs to document the care value.
- Employee well-being. Dr. Niazi is leading a team to implement and evaluate a stepwise care model that combines behavioral health coaching, psychotherapy and medication management with flexible scheduling and quick access. This model cares for the mental health needs of Mayo Clinic employees and trainees, their spouses, and their dependents 13 years of age and older that live in the southeast portion of the United States.
Significance to patient care
Dr. Niazi's work enables clinicians and care teams to screen, identify and predict individualized patient needs. Further, his work allows clinicians to match patients with the right level of care based on individualized risk factors and monitor treatment outcomes. Dr. Niazi's research uses patient-reported outcomes data to inform and monitor care; uses prevalence and cost data to develop the business case for mental health and psychosocial care of patients with complex health care needs.
- Team lead, In-Room Diagnostics work group, Mayo Clinic Hospital of the Future, Mayo Clinic, 2022-present.
- Peer reviewer, Journal of National Comprehensive Cancer Center Network (JNCCN), 2020-present.
- Member, Patient Clinic Question Approval Group, Mayo Clinic, 2019-present.
- Mayo Clinic representative, Distress Management Panel, National Comprehensive Cancer Network Guideline Panels, 2019-present.
- Site liaison, KERN Applied Clinical Informatics, Mayo Clinic, 2019-present.
- Physician site lead, Office of Information and Knowledge Management, Mayo Clinic, 2018-present.
- Scholar, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 2018-present.
- Writing scholar, Harvard Medical School, 2020-2021.
- Kern Scholar Award in Health Care Services Research, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 2018-2021.
- Georg Haub Career Development Award in Cancer Research, 2017-2021.
- Dorfman Journal Paper Award for Best Article for Original Research, Academy of Consultation-Liaison Psychiatry, 2020.