Graduation Year

2021

Document Type

Dissertation

Degree

D.B.A.

Degree Granting Department

Information Systems and Decision Sciences

Major Professor

Shivendu Shivendu, Ph.D.

Co-Major Professor

Manish Agrawal, Ph.D.

Committee Member

Kellas Cameron, Ph.D.

Committee Member

Padmaja Ayyagari, Ph.D.

Keywords

LTPAC, SDOH, EHR, Health IT Adoption, meaningful use, length of stay, Malpractice Claims, organizational performance

Abstract

This dissertation focuses on three key facets of health IT impact on the practice of medicine: (1) Clinical impact on practitioner outcomes through malpractice claims, (2) Socio-economic impact on patient outcomes through the clinical treatment of social determinants of health (SDOH), and (3) Organizational impact on Long-Term Post-Acute Care (LTPAC) Facilities. The first dissertation essay (Chapter 1) investigates the impact of Health IT on the nature and severity of malpractice claims reported in Florida from 2009-2016. The essay empirically examines the treatment effect of federal initiatives, specifically the Meaningful Use program, on medical practitioners enrolled in the Medicare program and actively practicing medicine in Florida during 2009-2016. It further investigates the observed treatment effect in terms of information failures captured in malpractice claim case details using machine learning algorithms. This work provides empirical evidence towards the beneficial impact of Health IT on the provider-outcomes with implications towards policy and operations. The second dissertation essay (Chapter 2) examines whether SDOH factors affect the quality of care a patient receives during initial treatment and whether these variations in quality significantly impact readmission likelihood. The essay demonstrates that even though physicians account for socioeconomic factors when making treatment decisions, these adjustments do not impact long-term health care outcomes. However, SDOH factors still impact long-term patient outcomes in terms of readmission likelihood. The third essay (Chapter 3) examines how and to what extent Health IT and electronic health record (EHR) adoption affect organizational capability configurations of long-term and post-acute care facilities (LTPAC) for high performance in terms of measurable outcomes. The essay provides a configurational perspective accompanied by a fuzzy-set qualitative comparative analysis (fsQCA) to explain complex nonlinear relationships among key digital and non-digital capabilities influencing facility-level measurable outcomes for 18 months [Jan 2016 – Jun 2017]. This shifts attention from individual capabilities to configurations of capabilities to develop a better understanding of the complex role of Health IT in the practice of medicine at the organizational level.

In recent years, the United States healthcare system has been overwhelmed with a technological makeover. Although technology can be attributed to many benefits, assimilation, and use of technology have been synonymous with a double-edged sword. Technology impacts the various stakeholders in the healthcare system as well as public policy. This dissertation proposes to estimate the differential impacts of technology on socio-economic aspects of healthcare delivery, the practice of clinical medicine, and the management of healthcare organizations. Although healthcare technology seems to be a concise term, it’s an amalgamation of components like pharmaceuticals, medical equipment, medical procedures, and health information technology (HIT). In this research project, we particularly focus on the HIT component and its impact and influence on healthcare outcomes.

The first essay investigates the impact of Health IT on the nature and severity of malpractice claims reported against non-hospital-based medical practitioners in Florida from 2009-2016. As the healthcare costs in the US rise at an alarming rate, medical liability claims significantly contribute to it. In addition to economic losses, medical malpractice compromises patient safety and provider reputation. Several federal and state initiatives like Meaningful Use work towards Health IT adoption and use. Our study empirically examines the treatment effect of these state initiatives, specifically the Meaningful Use program, on malpractice risks of the medical practitioners, enrolled in the Medicare program, actively practicing medicine in Florida during 2009-2016. It further investigates the observed treatment effect in terms of information failures captured in malpractice claim case details using machine learning algorithms. The results provide empirical evidence towards the positive role of Health IT on medical practitioners by lowering their risk to malpractice claims. Additionally, an exploratory text analysis of malpractice claims records helps uncover the latent mechanism through which the treatment effect of Health IT shows up in malpractice claims likelihood. We find the practitioners with a higher demonstrated ability of Health IT use in their practice are associated with a reduction in practitioner-based errors in the malpractice claims reported against them. This work has enormous implications for both practice and policy.

The second essay empirically investigates the physician decision-making process and its impact on patient readmission likelihood at a large, academic, urban hospital. Increased complexity of situations encountered by the physicians during their day-to-day practice necessitates technological support from physician decision support systems. These systems focus on clinical condition-based decisions and ignore the impact of patient behaviors on the clinical processes, or provider issues, such as malpractice. The goal of this work is to understand how physicians alter their decision-making process for different patient types during chronic care treatments, and whether these adaptions are purely clinical, or if they include other factors such as socio-economic status, and if so, when should they account for both. This study has important implications for the design and use of decision support systems as part of Health IT systems integrated within the medical practices. The decision support systems are based on clinical markers and provide warnings and suggestions to aid physician’s clinical decision-making process. Some recent debates argue about making these systems sensitive to social and economical attributes and markers of patients to provide holistic healthcare. This study analyses the impact of socio-economic factors perceived by the physician on his/her decision making and then the final impact of this decision’s long-term impact on the healthcare outcomes of the patient in the form of readmission risk. We found although socio-economic factors perceived by the physician during the clinical encounter results in significantly different clinical decisions ceteris paribus, the effect of this difference did not significantly affect the readmission risk of the patient. These findings have important implications for medical education and the design of decision support systems. The paper establishes the clinical treatment of social diagnosis is not useful and needs proper address through policy, education, and designs of decision support systems.

The third essay examines how and to what extent Health IT and electronic health record (EHR) adoption, as well as use, affect organizational capability configurations of long term and post-acute care facilities (LTPAC) for high performance in terms of measurable outcomes. The study adopts a configurational perspective accompanied by a fuzzy-set qualitative comparative analysis (fsQCA) to explain complex nonlinear relationships among key digital and non-digital capabilities influencing facility-level measurable outcomes for 18 months [Jan 2016 – Jun 2017]. This work shifts attention from individual capabilities to configurations of capabilities to develop a better understanding of the complex role of Health IT in the practice of medicine at the organizational level. We find Health IT is necessary but not sufficient condition for the high performance of an LTPAC facility. We find a significant impact of Health IT in clinical and operational performance but not financial performance. Our results indicate the absorption of Health IT impact within financial performance takes longer compared to operational and clinical performance.

This dissertation provides empirical and qualitative evidence of the impact of health IT on various aspects of medical practice. Health IT not only reduces the medical practitioners’ malpractice claim risks but also improves the operational and clinical performance of LTPAC facilities over a short period. We ascertain financial benefits to accrue at a later stage for these facilities. Health IT has been instrumental in emphasizing the role of socioeconomic factors in clinical decisions and the long-term outcomes of patients. We find using Health IT tools efficiently to avoid clinical treatment of social diagnosis potentially saves medical resources and appropriates correct treatment through social interventions and policy.

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