Browsing by Author "Ubel, Peter A"

Patients with early stage prostate cancer face a difficult preference-sensitive decision. There are multiple treatment options, each of which is associated with a unique set of benefits and risks. For example, surgery may cure the cancer but also come with the risk of serious side effects, such as impotence and incontinence. Alternatively, active surveillance avoids those side effects but requires patients to live with an untreated cancer inside their body. The optimal treatment for each patient will thus depend not only on his medical characteristics but also on how he personally values those risks and benefits. Ideally, patients and their physicians would partner together in a process of shared decision making (SDM) to ensure that patients receive treatments that reflect their personal preferences (i.e., preference-concordant treatments). In this dissertation, I use both qualitative and quantitative methods to examine patients’ decision-making processes in the context of early stage prostate cancer, focusing on if and how patients and physicians work together in the decision-making process to incorporate patients’ preferences into their treatment choices.

Essay 1 examines patients’ decision making processes within the context of a larger trial that was designed to assess the impact of a novel patient-centered (vs. standard) decision aid (DA) on patients’ decision making processes. The patient-centered DA increased patients’ desire to participate in the decision-making process and interest in active surveillance (Fagerlin et al., unpublished). However, regardless of which DA patients received, their treatment choices were primarily driven by physicians’ recommendation which, in turn, were driven by patients’ medical characteristics (e.g., cancer severity) and not their personal preferences (e.g., interest in sexual activity). Qualitative analyses of clinical appointments revealed relatively passive patients regardless of condition, suggesting that patients may not have known how to participate in clinical appointments and would benefit from pre-appointment communication skills training.

Essay 2 examines the effect of a novel patient communication skills intervention plus a patient-centered DA (vs. a patient-centered DA only) on several measures of patient empowerment using a randomized controlled trial. The intervention was a video (DVD) that modeled specific communication skills patients could use to participate in their upcoming appointments. The intervention increased patients’ intentions to use four process skills (e.g., taking notes) and sense of self-efficacy regarding their ability to ask for referrals and express personal concerns during their upcoming clinical appointments. It did not increase patients’ sense of self-efficacy regarding their ability to seek information or make assertive utterances.

Essay 3 examines focuses on a specific moment in clinical appointments: patients’ requests for treatment recommendations (data from Essay 1). Patient requests for recommendations are a pivotal and powerful moment in clinical appointments, yet no existing studies have examined how patients actually request recommendations nor what patient characteristics are associated with requests for recommendations. Patients or their companions requested recommendations in approximately 20% of appointments. Patients who requested recommendations had higher prostate cancer anxiety, placed increased importance on sex in their lives, preferred shared (vs. patient-led) decision making, and were more likely to prefer active treatment prior to appointments. When requesting recommendations, patients discussed physicians’ expertise and the role of their recommendations, asked physicians to engage in self-disclosure (e.g., “What would you do?”) and repeated their requests.

Truly empowering patients as decision makers in the context of early stage prostate cancer is difficult, and both patients and physicians may be uncertain how to behave in this new paradigm of patient empowerment. Patient communication skills interventions show promise, but continued research is needed to truly transform clinical medicine into a domain in which patients are empowered to fully participate in the medical decision-making process.

In three essays, this dissertation examines how patients judge their physicians in online physician reviews and whether those judgements align with traditional gender stereotypes. Specifically, I qualitatively explore patients’ judgments of their physicians’ interpersonal manner and technical competence, and the predominant factors within the two dimensions. I then train a machine-learning algorithm to code patients’ judgments in online physician reviews at scale. Finally, I use the machine-coded sample to analyze physician gender differences in judgments received from patients and how those judgments affect physicians’ review star ratings. In Essay 1, I propose an elaborated theoretical framework to identify the predominant factors underlying patients’ interpersonal manner and technical competence judgments of their physicians. This framework expands on prior grounded theory work by Lopez et al. (2012) and uses findings from a qualitative content analysis of 2,000 reviews received by distinct physicians. For this framework, I draw on a larger, new dataset of physician reviews from Healthgrades.com, one of the leading physician review websites, and use a balanced sample of reviews representing primary care physicians and surgeons, male and female physicians, and low- and high-rated reviews. I provide rich descriptions and illustrative quotations of the factors comprising interpersonal manner and technical competence, and describe factors added to and removed from Lopez et al.’s original framework. This framework from Essay 1 demonstrates that patients value their physicians on a wide array of interpersonal manner and technical competence factors, including but not limited to bedside manner, going above and beyond, availability, knowledge, diagnostic skill, and open-mindedness about treatment. In Essay 2, I train, test, and validate an advanced natural language processing algorithm called Robustly Optimized BERT Pre-Training Approach (i.e., RoBERTa) for classifying the presence and positive or negative valence of patients’ interpersonal manner and technical competence judgments in online physician reviews. I use the 2,000 manually coded physician reviews from Essay 1 to train and test two classification models, one for interpersonal manner and one for technical competence. Both models perform with 90% accuracy, with high precision, recall, and weighted F1 scores. I validate the models using the full sample of 345,053 RoBERTa-coded reviews for 167,150 physicians by testing associations between the valence-coded judgments and review star ratings and by comparing review rating and gender analyses with extant results in the literature. The fine-tuned algorithm from Essay 2 allows us to code a large dataset of unstructured textual review data with high efficiency and accuracy, enabling subsequent large-scale text analysis. In Essay 3, I analyze whether patients’ judgments of their physicians’ interpersonal manner and technical competence align with traditional gender stereotypes. Drawing on the Stereotype Content Model, I hypothesize that patients’ judgments will conform with gender stereotypes, such that female physicians will be more likely to receive reviews with interpersonal manner judgments whereas male physicians will be more likely to receive reviews with technical competence judgments. Using the full sample of machine-coded reviews from Essay 2, I estimate multilevel logistic regressions to identify gender differences in interpersonal manner and technical competence judgments of physicians. Results from Essay 3 suggest that patients’ judgments partly align with traditional gender stereotypes: Female physicians are more likely to receive interpersonal manner judgments, but male physicians are not more likely to receive technical competence judgments. Whether female physicians are relatively more likely to receive praise or criticism for their interpersonal manner depends on their specialty. In stereotypically warm specialties, like primary care, females are penalized for seeming cold, whereas in stereotypically technical specialties, like surgery, females are advantaged for appearing warm. Last, female physicians, in some cases, are either not rewarded as much or penalized more than their male counterparts in their star ratings when receiving positive or negative interpersonal manner and technical competence judgments.

My dissertation research offers insights about the effects of Medicaid managed care (MMC) programs from Kentucky’s statewide market-based program. Kentucky’s significant reforms to introduce a comprehensive MMC program just one year after the passage of the ACA can provide valuable lessons for other rural states with substantial poor populations.

In the first study, I explore Kentucky’s 2011 introduction of MMC and the quality of hospitals used by Medicaid recipients. Kentucky’s MMC program is a post-Affordable Care Act (ACA) market-based program that uses a small set of competing managed-care organizations (MCOs) to administer Medicaid benefits. Using a quasi-experimental research design, I explore whether the introduction of MMC changes the hospitals used by pregnant Medicaid-insured mothers for their deliveries and whether the quality of these hospitals is different compared to the hospitals used before the policy change. I also test whether the changes in hospitals used by pregnant Medicaid-insured mothers for their deliveries differ in smaller counties with fewer hospitals and Medicaid recipients compared to those in larger counties with more hospitals and Medicaid recipients. My analysis uses hospital quality measures designed by the Agency for Healthcare Research and Quality to measure hospital quality. I find that Medicaid-insured pregnant women from nonmetropolitan counties have an increased probability of delivering in the highest quality local hospitals as opposed to the lowest quality local hospitals. In contrast, I find that Medicaid-insured pregnant women from metropolitan counties have a decreased probability of delivering in the highest quality local hospitals and increased probability of delivering in lower quality local hospitals. Since Kentucky’s metropolitan counties have high quality hospitals and its nonmetropolitan counties have some of the poorest quality hospitals in the state, these findings may be positive for patient outcomes and program costs. Additional research evaluating patient outcomes and identifying the causal mechanisms responsible for changes in the hospitals used by Medicaid recipients is needed.

Motivated by my findings in the first chapter, in my second chapter I exploit Kentucky’s reforms to explore potential mechanisms that link MMC to changes in the hospitals used by Medicaid-insured pregnant women for their deliveries. I focus on hospital network status and physician-hospital arrangements, which are the terms by which physicians practice in hospitals. These arrangements can affect the hospital ultimately used by physicians’ patients and may be designed specifically for the purposes of joint contracting with insurers. After using reduced form hospital choice models to estimate the change in the hospitals used by pregnant women in Kentucky in response to the introduction of MMC, I introduce measures of hospital network status and physician-hospital arrangements to my analysis. The primary policy effects on the hospitals used by Medicaid-insured women for deliveries remain unchanged, including the two covariates that suggest that other mechanisms with opposing effects to hospital-network status and physician-hospital arrangements are responsible for the changes in hospitals used by Medicaid-insured women. Future research should consider the role of information in provider choice after the introduction of MMC.

In the third chapter, I shift my focus to considering how well Kentucky’s MMC program navigated expanding Medicaid eligibility. Specifically, I explore the impact of the ACA on disparities in access to medical providers in MMC programs. In states expanding Medicaid eligibility, low-income communities with pre-existing elevated numbers of uninsured people experienced larger gains in coverage from the ACA than other communities. While researchers have reported that there is increased physician participation in states that expanded Medicaid, researchers have yet to explore whether increases in physician participation coincided with areas experiencing the greatest increases in Medicaid coverage or inadequate access to medical services. In these programs, Medicaid recipients access care from provider networks created by the health maintenance organizations (HMOs) selected by states to administer Medicaid benefits. Using an original dataset on Kentucky’s Medicaid HMO networks, I use a difference-in-differences framework to compare provider network participation before and after the implementation of the ACA across counties. Specifically, I compare counties with differing levels of pre-ACA uninsured rates, medically underserved populations and poverty. I find provider network participation is greater in counties experiencing smaller increases in Medicaid coverage but subtly larger participation in counties with medically underserved areas or high poverty.

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Judgment and decision-making in a healthcare context often involve complex information and difficult tradeoffs. In order to understand key concepts and receive help with difficult decisions, patients may turn to written materials, like informed consent forms. Unfortunately, these materials can actually increase confusion. This dissertation explores the relationship between written health materials and cognitive processes, specifically comprehension, memory, judgment, and decision-making. The first goal was to investigate how language and design affect cognition for informed consent forms. We developed a Standard informed consent form and two Enhanced versions that had simplified language and modified design, and compared comprehension and memory between the three versions. As written health materials undergo changes to make their content more accessible to readers, they also become more fluent. The second goal was to explore how this fluency affects judgments and decision-making, especially for materials that have a negative valence. This question was studied in the context of two competing fluency theories, the Hedonic Fluency Model and the Fluency Amplification Model. We manipulated the fluency of various materials, including medications, diseases, and risks, and asked participants to make several judgments about the fluent and disfluent materials. Our results highlight the complexities and nuances that characterize fluency’s effects.