Faculty Research Projects

The Healthcare Business Institute will produce high quality research that creates an impact in healthcare and in the larger community of research scholars in business disciplines by adding to the body of knowledge at the intersection of traditional business disciplines and healthcare. Academic business scholars in the disciplines of leadership, marketing, operations management, information systems, finance, organizational behavior, and entrepreneurship have all addressed problems in healthcare from a disciplinary standpoint and have applied theoretical business tenets and conceptual frameworks from their disciplines to the understanding of healthcare problems. Similarly, there is a large cohort of healthcare specialists, clinical and non-clinical, working to address healthcare delivery issues.

The Healthcare Business Institute research will bring together a diverse community of business and healthcare research scholars and practicing clinicians to collaborate on producing original and insightful research that addresses important contemporary problems in healthcare with theory, methodological rigor, and practical applications.

Hospitals Operations: Metrics, KPIs, Technologies

  • Hospital Operations & Supply Chains: Using ML-based prediction models to predict consumption of medical supplies in high volatility medical supply chains.
  • Medical Billing & Reimbursements: Organizing Billing Processes for Optimizing Revenues: using precision metrics.
  • Precision costing models for Hospital Operations: Linking costs to clinical metrics.
  • ER Functioning Optimization: Increasing ER Throughput, Using in situ metrics and prediction models.
  • Precision Metrics & KPIs: Linking technologies to processes and operational outcomes.

Healthcare Technologies: Platforms, Processes and People

  • Medical Error Prevention: Investigating the role that information and communication technologies play in preventing and minimizing medical errors.
  • Case Study: A Study of Platforms, Processes, and People in Clinical Excellence.
  • Telemedicine for Chronic Care: An investigation of factors that lead to successful care delivery via telemedicine platforms by identifying the telemedicine architectures that are optimal for delivering chronic care.
  • Modeling the impact of virtual reality-based treatments for chronic pain (this research led to the FDA approval of a VR-based device/program for treatment of chronic pain).
  • Consumer health information technologies for remote monitoring and management of chronic health problems.

AI & Machine Learning in Hospital Contexts

  • Using AI in Data Intensive Contexts: combing AI-based prediction models with statistical techniques to analyze hospital rankings.
  • Using AI in Clinical Contexts: Predicting the state transition in disease progression using ML-based techniques.
  • Readmission of Heart Disease Patients: Predicting the clinical trajectory of patients with heart disease post discharge: modeling clinical trajectories as sequential prediction states, using ML techniques.
  • Use of ML – based Models to predict discontinuities in patient medical adherence.

Electronic Health Records: EHRs and EMRs:

  • Electronic health record systems and their links to Medicare reimbursement.
  • Linking social determinants of health to electronic patient records: Bridging the gaps in population health equity.
  • Automation & Productivity: Optimal ways to automate highly interconnected set of clinical and non-clinical processes.
  • Electronic Health Record Systems: Differential impacts of technology-network structures on cost efficiency: Knowledge spillovers in healthcare.

Emerging Financial Models in Healthcare

  • New Pricing Models for Devices: Tracking medical devices using IoT sensors can lead to new pricing strategies where providers pay for usage rather than purchase.
  • Valuation and Venture Capital: New valuation models for healthcare startups.
  • Valuation Models: Valuing service-based healthcare startups; the role of business adjacencies as revenue multipliers.

Leadership & Management

  • Talent Management: Antecedents and consequences of gender bias in the healthcare industry – an exploration of how gender bias relates to talent management and succession, patient care experiences, executive development, and reputation management in the healthcare context.
  • Leadership & Management: How leader narcissism, humility, and competence affect decision making and outcomes.
  • Implementing Health Information Technologies in Precision Medicine Practice: Examining the barriers and facilitators for health services organizations.
  • Healthcare Leadership in the Digital Era: Exploring the scope of leadership competencies, organizational barriers and enablers, and strategic approaches to improve practices.

Patient Decision-making

  • Understanding customer preferences for low-cost alternatives in healthcare access.
  • Understanding customer valuation of treatment attributes for chronic pain.
  • Modeling health-seeking (STI detection and prevention) behavior among sex-workers in India.
  • Understanding the impact of cognitive and motivational interventions to help chronic pain patients taper off opioid medications.
  • Understanding and modeling barriers to vaccination among vulnerable populations.
  • Assessing relative preferences for vaccine features in vaccination choice.
  • Information consumption and decision making by patients: the role of patient perceptions of risk on patient choice of hospital in invasive surgical procedures.
  • Implications of Hospital Care-Compare: A natural experiment of displaying clinical hospital quality on crowdsourced review platforms.
  • Factors influencing vulnerability to online health misinformation and disinformation in patients with chronic diseases.
  • Omnichannel in Healthcare: Spillover or cannibalization effect of online-offline channel integration in online health consultation platforms?