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Sreeram: What patients are hearing: a large-scale corpus analysis of the most referenced medical conditions and pharmacologic drugs in popular medical television

Abstract

Medical television dramas have a profound impact on the public’s understanding of healthcare. This study conducted a corpus analysis of the subtitles from two long-running medical dramas, Grey’s Anatomy and ER, to identify the top mentioned medical conditions and pharmacologic drugs. Subtitle files for all episodes were obtained, verified for accuracy, and preprocessed. A dictionary-based lexical analysis tallied mentions of medical conditions and drugs. Frequencies of the top 40 terms in each category were temporally analyzed using linear regression models and compared against real-world data. The top mentioned medical conditions across 711 episodes were HIV (216 mentions), stroke (213), heart attack (213), and pneumonia (168). Cardiovascular and nervous organ systems were most mentioned. Temporal trends revealed a decrease in mentions of medical conditions over time in both ER (p < 0.001) and Grey’s Anatomy (p = 0.001). Comparison with real-world incidence indicated an overrepresentation of rare diseases across both shows (p = 0.033). The most mentioned pharmacologic drugs were morphine (303 mentions), atropine (188), and lidocaine (165), and the most represented drug class was analgesics (34% of top 40 drug mentions across shows). These findings may lead to skewed patient perceptions and should be recognized by clinicians during patient interactions.

Introduction

Americans obtain health-related information from the media more than any other source aside from health care professionals (Hesse et al., 2005), and cultivation theory suggests that exposure to television (TV) over time will “cultivate,” or shape, an audience’s ideas of reality (Gerbner et al., 1994). The influence of medical TV dramas on public perception and education of healthcare concepts has thus been a subject of continued interest over the years (Byrne, 2022; Harris & Willoughby, 2009; Hirt et al., 2013). Many of these shows’ viewers, particularly those with no ties to the healthcare field otherwise, assume these shows to be mostly accurate representations of real-world situations and issues (Rideout, 2008; Spadaro, 2003). These shows serve as sources of medical information, with certain storylines leading to increased awareness and knowledge about disease processes among viewers and all having a well-established impact, whether positive or negative, on patients’ medical understanding (Brodie et al., 2001; Cho et al., 2011; Hether et al., 2008; Hoffman et al., 2017; Quick, 2009; Stinson & Heischmidt, 2012). While cultivation theory has been widely applied in media studies, its application to the domain of medical terminology use on television has been limited. For example, repetitions of rare or dramatic medical diagnoses may contribute to skewed beliefs about the prevalence and seriousness of specific conditions. As phenomena such priming and utilization of availability heuristics make certain concepts more accessible (Ellis, 2002), it is reasonable to expect that repeated exposure to certain medical vocabulary may predispose audiences to develop connotations and assumptions about diagnoses and treatments in medicine. That is, even if a term appears in a minor or dramatized context, its repeated presence may make it more cognitively accessible to viewers. This study seeks to extend cultivation theory by identifying the frequency of medical language in popular medical dramas to speculate how viewers’ understandings of healthcare may be shaped. As past studies have even tried to use medical TV shows to teach concepts like patient-provider interaction and pharmacology to medical students (Baños et al., 2019; McNeilly & Wengel, 2001), and with several top medical dramas reaching millions of viewers in the US alone (Brooks & Marsh, 2009), it becomes crucial to examine the medical content they present and their potential impact on audience and patient knowledge of real-world medicine.
The accuracy of medical information presented in these shows has long been a point of concern. While some studies praise certain aspects of medical representation in TV dramas such as appropriate application of pharmacologic agents (Baños et al., 2019), others highlight significant inaccuracies and dramatizations that could lead to misconceptions. A study looking to summarize medical errors in TV examined 6 episodes in each of 8 medical TV dramas and found that compared to data from US hospitals, TV shows depicted more errors in diagnosis, fewer operative errors, higher rates of emotional trauma, and lower rates of temporary injuries (Carney et al., 2020). Ismail and Salama found that rare neurological diagnoses were disproportionately made in Grey’s Anatomy, potentially skewing viewers’ expectations of the nature and incidence of such conditions (Ismail & Salama, 2023). Multiple studies have shown that medical dramas often portray inaccurate details surrounding cardiopulmonary resuscitation, expecting healthcare practitioners to encounter misinformation when dealing with this procedure (Bitter et al., 2021; Diem et al., 1996). More generally, doctors have also been depicted as having elevated confidence (Quick, 2009) and power (Pfau et al., 1995) than may be true to real life.
In the vein of exploring accuracy and suboptimal patient understanding arising from these shows, the medical conditions and treatments to which audiences are frequently exposed is a vital benchmark. Previous research has examined the frequency and context of medical conditions in medical TV (Ye & Ward, 2010), but a large-scale corpus analysis across long-running series is lacking. While the scale of this endeavor limits semantic analyses, the dialogue in medical dramas can itself be a valuable tool used to assess high-level trends and patterns that may generate rich questions for deeper exploration. Frequent encounters with words or phrases can enhance recognition, recall, and understanding (Bisson et al., 2014) and, in the context of medical dramas, even incidental or background mentions of diseases, medications, or medical procedures can contribute to viewers’ medical lexicon and knowledge base. With television having immense potential to promote prosocial, helpful, and tolerant behavior (Mares & Woodard, 2005), and repeated exposure having the potential to increase comprehensive ability (Mares, 2006), elucidating the words belonging to the medical lexicon that audiences most often hear is an important and useful aid with which providers can devise more informed care discussions and practices.
This study aimed to conduct a lexical analysis of the subtitles from two popular medical dramas, Grey’s Anatomy and ER. By examining the corpus of dialogue extracted from both series, spanning 27 years and over 31,000 minutes of television, the most commonly mentioned diseases and medications were identified, temporal trends and real world tie-ins were analyzed for comparative analysis, and potential implications of these findings for patient-provider communication and public health education were discussed. The study aims in question were (a) to identify the most frequently mentioned medical conditions and pharmacologics in contemporary medical television dramas, and (b) to compare these frequencies to the prevalence of these conditions in real-world epidemiological data. In addition to the aforementioned exploratory analyses, it is hypothesized that (a) rarer, more “dramatic” illnesses will be overrepresented in medical TV, and (b) the top referenced diagnoses in medical television shows will not align with the real-world epidemiological prevalence. By leveraging computational analysis of text, this study aims to help providers anticipate potential misconceptions and better guide patients’ understanding of their conditions and treatment plans.

Methods

Show Selection

To appropriately sample shows to which much of the American population would be exposed, the phrase “most popular medical TV shows” was queried across multiple search engines such as Google, Bing, and DuckDuckGo. The aim was to choose shows that had both a substantial episode count (>200) and were favorably popular among the critics and public. Two shows that consistently ranked highly among these criteria were ER (1994) and Grey’s Anatomy (2005), which have both won Golden Globe and Primetime Emmy awards in the past and consistently rank highly in Nielsen television ratings (Brooks & Marsh, 2009). These shows were also the top two noted in a prior systematic review studying exposure to medical television (Hoffman et al., 2017) and were thus chosen for this study.

Data Collection

Subtitle files for episodes of Grey’s Anatomy (seasons 1-17) and ER (seasons 1-15) were obtained from publicly available sources. The accuracy of subtitle files used in this study was verified by cross-referencing by extensive spot-checking against video content for a representative portion of the data (10%). For example, for a 40-minute episode of Grey’s Anatomy, 4 minutes of the episode were selected at random and watched. Subtitle files were verified against spoken dialogue to assess fidelity (>95%) before being used.

Data Preprocessing

The collected subtitle files were initially in SubRip Text (SRT) format, which includes time codes and sequential numbering along with the dialogue text. To prepare the data for analysis, a custom R script was written to perform several preprocessing steps. Firstly, all individual episode subtitle files for each series were merged into two comprehensive files, one for Grey’s Anatomy and one for ER. Each file was maintained in chronological order, with the first episode at the start of the file. The R script then removed all non-textual elements such as time codes, sequence numbers, and formatting tags. Additionally, it standardized text encoding to UTF-8 to ensure consistent character representation. Finally, the cleaned text was tokenized into individual words, with all text converted to lowercase to facilitate uniform analysis.

Lexical Analysis

To identify and tally mentions of conditions and drugs, a dictionary-based approach was employed. Two comprehensive dictionaries were created, one containing a wide range of medical conditions, syndromes, and diagnoses, and the other containing generic and brand names of drugs, pharmacologics, and medications. These dictionaries were created by aggregating information from reputable medical databases and standardized medical terminology resources such as SNOMED CT (Chang & Mostafa, 2021) and RxNorm (Liu et al., 2005). Entries were kept in a conservative fashion so as to mitigate the risk of excluding real terms, and were instead manually checked for extraneous or inappropriate terms during data analysis. Importantly, this analysis checked for all medical conditions, including and on top of those conventionally defined as diseases. Conversely, categories of both diseases (e.g. “cancer”) and pharmacologics (e.g. “anesthetic”) were excluded.
An internal R script was written to perform a matching of each tokenized word and multi-word phrase against the curated disease and pharmacologic dictionaries. For each matched term, the script maintained a running tally of occurrences.

Data Analysis

After the initial tallying, disease and drug frequencies were combined across the two shows. The 40 most frequently mentioned diseases and the 40 most frequently mentioned drugs were subsequently identified.
A graph visualizing the frequency of these words was created with a bin size of 0.002 (500 bins total), with positions normalized to range from 0 to 1 across the entire corpus for each show. The frequency of the mentioned terms over the course of each series across the years was then analyzed by fitting a linear regression model to the data, with the normalized position as the predictor variable (x) and the frequency of keyword occurrences as the response variable (y). Coefficients were estimated using the ordinary least squares method, and the significance of the regression coefficients was tested using t-tests. To assess the overall significance of the linear regression model, an F-test was conducted to compare the fit of the full model (including the predictor) against a reduced model (excluding the predictor), determining if the predictor explained a significant amount of variance in the response variable.
Comparison to real-world data was performed using a 2018 report from the National Inpatient Sample (NIS), which listed the top 20 principal diagnoses for hospital admissions nationwide (Most Frequent Principal Diagnoses for Inpatient Stays in U.S. Hospitals, 2018 #277, 2021). For all conditions, their yearly incidence in the United States was researched and categorized into one of 4 categories based on yearly incidence information from the Centers for Disease Control and Prevention (CDC, 2024): common (>1 million cases), uncommon (200,000-1 million cases), rare (50-200,000 cases), and extremely rare (<50 cases). These categorizations were then applied to the top 40 conditions mentioned across the two medical TV shows as well as the top 20 conditions noted on the NIS. A chi-squared analysis was conducted to test for statistically significant distribution across the two groups.

Results

In total, 711 episodes were analyzed (380 Grey’s Anatomy, 331 ER). Parsing of subtitle data identified the 2,415 mentions of the top 40 medical conditions and 1,333 mentions of the top 40 pharmacologics across both shows. On average, each episode contained 3.4 mentions of a medical condition and 1.9 mentions of a medication.

Most Common Medical Conditions

Figure 1 illustrates the top 40 mentioned medical diseases across both shows. The most common disease mentioned was HIV, with 216 occurrences (33 in Grey’s Anatomy and 183 in ER), followed by heart attack and stroke, with 213 occurrences each.
Each show’s occurrences of these top 40 diseases was assessed over time, revealing significant temporal changes (Figure 2). A marked decrease in mentions of top medical conditions was observed in later seasons as compared to earlier ones in both ER (p < 0.001) and Grey’s Anatomy (p = 0.001). As a validation, temporal trends over time for all disease and medical conditions (i.e. not just the top 40) were also analyzed, and statistically significant reductions in frequency were observed over time for both ER (p < 0.001) and Grey’s Anatomy (p < 0.001).
Each medical condition was also sorted by the primary affected organ system. Categorization of these top 40 conditions revealed that the cardiovascular and nervous systems had conditions mentioned most frequently in TV shows, collectively accounting for 42% of all mentions. With regards to variety, the cardiovascular system, followed by the nervous and digestive systems, had the most number of conditions mentioned in the top 40 (8 and tied for 7, respectively). It was deemed that HIV, sepsis, ischemia, and the plague were not limited primarily to one organ system. These results are summarized in Table 1.

Comparison with Real-World Incidence

Out of the top 40 mentioned conditions across both shows, it was found that only 40% were considered common, and 30% fell into either the rare or extremely rare categories. Thirty percent of diseases were categorized as uncommon. There was a statistically significant difference in the distributions of the two datasets, with medical TV holding substantially more entries in rare categories compared to the NIS data (p = 0.033). A comparison of top diseases across the NIS versus TV shows, in relation to their nationwide incidence, is shown in Table 2.

Most Common Medications

With similar methodology applied to assess the prevalence of pharmacologic drugs, morphine was the most commonly mentioned with 303 occurrences, followed by atropine (188 occurrences) and lidocaine (165). Notably, these three represented over 49% of all mentions of the top 40 pharmacologic agents across both shows. Figure 3 displays the complete list and relative prevalence of the most frequently mentioned drugs.
After sorting all drugs into their respective classes, analgesics (morphine, ibuprofen, etc.) were the most prevalent, accounting for 34% of all medication mentions. This was followed by medications for cardiac issues such as atropine and adenosine (21%) and anesthetics like lidocaine (19%). The miscellaneous category consisted of drugs that did not clearly fit into any other categories, which were albuterol, acetaminophen, betadine, octreotide, lactulose, antacids, phenytoin, and theophylline. A summary of the pharmacologic classes represented by the top 40 most commonly mentioned drugs is shown in Table 3.

Discussion

The relationship between media exposure and patient knowledge has been explored in various contexts. For example, Hoffman et al. posited that viewers of medical dramas may have higher expectations for medical care due to unrealistic expectations put forth by medical television (Hoffman et al., 2017; Primack et al., 2012). Similarly, Quick demonstrated that heavy viewers of Grey’s Anatomy firstly had increased credibility for the show but also correlated ideas such as courage with competence in physicians (Quick, 2009). Ye & Ward examined both ER and Grey’s Anatomy through a content analysis of 127 episodes, similarly finding that cardiovascular diseases such as hypertension and myocardial infarction were represented along with different cancers (Ye & Ward, 2010). These findings underscore the importance of understanding the content of medical dramas and their potential impact on patient-provider communication.
The novelty of the present study is that it is reliant upon lexical frequency as opposed to semantics, allowing for larger-scale queries and pattern analysis. Staying agnostic to the semantics of the medical condition and/or drug mention has unique benefits; for example, past studies have surveyed diagnoses in shows like Grey’s Anatomy and concluded that rarer ones are overrepresented (Ismail & Salama, 2023). However, even if a diagnosis is given at the end of an episode, it was likely not the only one mentioned throughout the episode - oftentimes, other medical symptoms and conditions have been discussed and thus the audience is made aware of far more than just the ultimate underlying diagnosis. This study aimed to analyze the corpus of dialogue in Grey’s Anatomy and ER, two heavily popular, genre-defining medical TV shows, highlighting what medical conditions and medications are most popular in the shows’ scripts and thus could develop a connotation in an audience member’s mind. It was found that some of the most commonly referenced diseases such as stroke, heart attack, and pneumonia are also, in reality, common diagnoses. On the other hand, several rare diseases were also disproportionately mentioned when compared to real life. Overall, there was also an observed reduction in mentions of the most common diseases over time in both shows. Additionally, the cardiovascular, nervous, and respiratory organ systems were shown to be most frequently mentioned when discussing diseases. Finally, the analysis of drug names revealed that morphine, lidocaine, and atropine encompassed about half of all total mentions, and analgesics were the most commonly referenced drug class. These findings can help mindful healthcare providers to anticipate conversations and improve education surrounding patients’ condition and treatment regimen. If certain terms are overrepresented in the media and thus more familiar to audiences, discussions can be constructed around such vocabulary to ensure greater patient comprehension.
The identification of the most frequently mentioned diseases and medications in these shows offers clinicians a unique perspective on the medical knowledge to which their patients may have been exposed. While common diseases and conditions such as pneumonia, hernias, and diabetes are, in fact, among the most commonly cited in medical dramas, rarer conditions like compartment syndrome and teratomas, with which the majority of the public may be unfamiliar, are also relatively frequently mentioned - a theme that has been present in prior studies (Lemal et al., 2013). Awareness on both ends of the spectrum can guide healthcare providers in their communication strategies, allowing them to anticipate and address preconceived notions that patients might have developed through media exposure. For instance, when discussing a condition or medication that frequently appears in medical dramas with which patients may have a baseline familiarity, clinicians can proactively elaborate on its real-world application, prognosis, or side effects. On the other hand, rarer conditions that appear on TV more commonly may need to be explained more thoroughly to ensure no misconceptions arise down the line. For instance, compartment syndrome, a rare surgical complication, was the 33rd most mentioned condition with 24 mentions, accounting for about 0.59% of all mentioned conditions (about 1 in 170), yet only occurs in 7.3 males and 0.7 females per 100,000 (Torlincasi et al., 2024). Conversely, anemia, which affects about 5.6% of the US population (Le, 2016), only accounted for 1.3% of disease mentions in the shows. This disproportionate representation can lead to skewed expectations among patients about a disease’s prevalence, etiology, and severity. Healthcare providers should be mindful of this media-induced bias and be prepared to appropriately contextualize these conditions, first anticipating what underlying misconceptions may exist to subsequently eradicate them.
One observation was the prominence of HIV and Alzheimer’s disease across the two shows. Upon examination, it was found that these diseases likely topped the list due to their role in the shows’ plots. The titular character in Grey’s Anatomy, Meredith Grey, tests positive for genetic markers for Alzheimer’s in the show’s ninth season, turning into the impetus for many conversations in the show. Similarly, Dr. Jeanie Boulet of ER was diagnosed with HIV during the show’s third season - a plot point that has been mentioned several times since. Appropriately, the term “HIV” appeared 183 times in ER, as opposed to just 33 times in Grey’s Anatomy. It is undoubtedly important to recognize that these terms’ high frequency is partly due to a recurring plot point as opposed to frequent exposure to the disease condition. However, this does not necessarily diminish the predictive value of the tallies to suggest that audience members may be more familiar with these diseases, perhaps learning plot-adjacent topics like the communicable nature of HIV (Bekker et al., 2023) or the hereditary aspects of Alzheimer’s (Levy et al., 1990; Murrell et al., 1991).
The study also demonstrated that certain organ systems are more commonly represented than others, namely the cardiovascular and nervous systems which accounted for almost 43% of all mentions of the top 40 conditions. The cardiovascular system had the highest variety of conditions mentioned, including cardiac arrest, cardiomyopathy, and congestive heart failure. This disparity may be due to the perceived acuity or dramatic potential of conditions affecting these systems. For example, cardiovascular conditions, which are often critical and dramatic and can be appealing content for medical dramas (Diem et al., 1996), frequently appear in these shows and can lead to potential confusion among viewers regarding closely related terms such as cardiomyopathy, cardiac arrest, heart disease, and congestive heart failure. It is imperative that healthcare providers offer a clear delineation of terms to their patients who may be afflicted by one, but not all, of these conditions, making sure to emphasize their unique characteristics, causes, and treatment approaches. Moreover, the overrepresentation of certain organ systems beyond their real-world prevalence may inadvertently downplay the importance and prevalence of less dramatically portrayed yet more common systems and conditions, predisposing patients to consider “zebras rather than horses” (Ismail & Salama, 2023). For example, while cellulitis is a condition affecting over 14 million Americans yearly (Brown & Hood Watson, 2024), it was the only integumentary disease mentioned in the top 40 and comprises only about 1% of mentions. Conversations with patients should work to emphasize by firstly emphasizing the significance of all organ systems in maintaining overall health and secondly take extra care in clarifying potential misconceptions amongst interrelated conditions within the more frequently discussed organ systems.
The observed decrease in medical terminology usage over the course of both shows could reflect several underlying factors of interest to healthcare providers. One likely explanation is that once the initial novelty of these dramas, often centered around compelling medical storylines, is worn off, character development and interpersonal relationships often take center stage. Another explanation could be simply the effort to appeal to newer viewers, using less specialized terminology to avoid alienating a broader audience. This finding could have mixed implications, either indicating a lower overall educational value of this type of television in more recent years or perhaps suggesting a lower chance for misconceptions arising from incorrect interpretation of excessive medical jargon. Either way, awareness of this trend helps highlight that familiarity with a show may not be sufficient to gauge medical knowledge, so asking driver questions to prompt patients to share what they may remember from such sources should be considered to more accurately gauge a knowledge base.
The subtitle corpus also revealed a prominence of several medical drugs, especially morphine, lidocaine, and atropine. These three drugs comprised almost half of the mentions of the top 40 drugs, and are noteworthy due to their clinical importance, versatility, and dramatic potential. Potent opioid analgesics like morphine have been a cornerstone of pain management in hospital settings for decades (Hyland et al., 2021), and their ubiquity in medical dramas is likely a function of its use in acute care scenarios. The dramatic potential of morphine is also multifold, representing both life-saving pain relief and the risk of addiction. This is corroborated by the fact that analgesics were the most common drug class in the analysis, largely due to morphine and other newer opioids such as fentanyl which boast enormous potential for abuse (Comer & Cahill, 2019). Lidocaine is a local anesthetic and antiarrhythmic, with utility anywhere from minor surgeries to cardiac emergencies (Torp et al., 2024). Its versatility in both topical and injectable forms makes it a go-to medication in many clinical scenarios, easily lending itself to diverse plot points. Atropine, an anticholinergic drug, plays a crucial role in emergency medicine, particularly in the treatment of bradycardia and as an antidote for certain poisonings (Brady et al., 1999; McDonough & Shih, 2007). Its use in high-stakes, life-or-death situations aligns well with the intense narratives often portrayed in medical television. It is worth noting that while these medications are indeed common and important in real-life medical practice, their overrepresentation in television may inadvertently skew public perception of their appropriate use cases. This underscores the need for healthcare providers to be prepared to explicitly contextualize the appropriate use of certain medications, analgesics in particular, to set expectations for patients whose expectations may be influenced by these portrayals.
In examining lexical frequencies, it is vital to understand the fundamental obstacle of semantics and how this should be navigated in a healthcare setting. While these results demonstrate that terms such as hernia, asthma, and anemia are among the most common conditions represented in the two surveyed medical dramas, the manifestation and treatment of these conditions is variable. A common inguinal hernia versus a traumatic hernia, for example, would differ in epidemiology, pathogenesis, and treatment (Holzheimer, 2005). In keeping with the theme of exciting television, chronic conditions affecting millions of Americans like asthma and anemia are likely shown in an extreme, dramatized isotype when referenced in television or with an exaggerated mortality rate (Hetsroni, 2014), thus potentially distorting viewers’ expectations when encountering these conditions in real life. Just as it is helpful to know when viewers may be familiar with certain terms and conditions, it is possibly even more vital to dispel any myths about the management of certain conditions with varied manifestations. Further studies may explore this in-depth, perhaps building off this study’s findings to identify myths and misconceptions about certain commonly represented conditions as a preventive measure for healthcare providers to avoid miscommunications down the line.
While these insights can improve medical providers’ mindfulness, it is important to acknowledge the study’s limitations. Firstly, this analysis is based on subtitle text, which may not capture all nuances and semantics of the spoken dialogue or visual medical references in the shows. The size and scope of this study have thus limited its analysis from a semantic standpoint, which has already been explored in previous studies (Ye & Ward, 2010), and instead urge a lexical, quantitative approach. Also, the methodology could not assess informal terms that may connote to diseases (e.g., “depression” for major depressive disorder) as the tally would be skewed by other encapsulating terms (e.g. respiratory depression). The study is also limited to two specific medical dramas and, while these are highly popular and influential, may not be fully representative of all medical television content. Lastly, while potential impacts on viewer perceptions based on content analysis can be inferred, this study does not directly measure changes in audience understanding resulting from exposure to these shows.
This corpus analysis of Grey’s Anatomy and ER provides implementable lessons from examining the medical landscape presented to millions of viewers over nearly three decades. It was found that while some common conditions often seen in US healthcare such as stroke, pneumonia, hernias, and diabetes are often mentioned, so too are rarer diseases, like tetanus and the plague, to a significantly higher-than-expected extent. The lower usage of such medical terms over time emphasizes a potential variance in knowledge even amongst those familiar with these shows. Additionally, the dominance of certain organ systems including cardiovascular and nervous, and analgesic drugs like morphine, gives medical providers direction on where to direct efforts to clarify and clear possible misconceptions, as well as potentially build off an existing knowledge base. From the perspective of the media, these findings can aid in understanding the reality of dramatic portrayals of medicine and taking steps necessary to either augment, complement, or overcome these in hopes of providing a more accurate depiction. Future academic research may, in turn, choose to incorporate a level of semantic analysis, such as analyzing the scenes in which top diagnoses are mentioned, to provide another angle into understanding how media representations of disease may shape public perception. As such studies progress, clinicians can be better prepared to incorporate media-influenced exposure into patient communication, effectively bridging the gap between dramatized portrayals and clinical reality.

Notes

Data Availability Statement

The data used in this analysis is publicly available, while the code used to compile and analyze the data is available from the corresponding author upon reasonable request. This code is not publicly available due to its ongoing development and potential reuse in related studies.

Ethics and Disclosures

This study evaluated publicly available content and did not involve human or animal subjects. Thus, ethical approval was not required. The author discloses no potential conflict of interest.

Funding

This research did not receive a grant from any funding agency in the public, commercial, or non-profit sectors.

Figure 1
Top 40 most common medical conditions mentioned across Grey’s Anatomy and ER.
hnmr-2025-00038f1.jpg
Figure 2
Temporal patterns in representation of top 40 medical conditions in (a) ER and (b) Grey’s Anatomy (GA). Note: regression lines have been vertically translated for viewing clarity.
hnmr-2025-00038f2.jpg
Figure 3
Top 40 most common pharmacologic drugs mentioned across Grey’s Anatomy and ER.
hnmr-2025-00038f3.jpg
Table 1
Most common medical conditions.
Organ System Entries (n=40) Entries (%) Mentions (n=2415) Mentions (%)
Cardiovascular 8 20% 615 25%
Nervous 7 18% 417 17%
Respiratory 5 13% 363 15%
Digestive 7 18% 334 14%
Hematologic 2 5% 93 4%
Endocrine 1 3% 79 3%
Reproductive 2 5% 72 3%
Musculoskeletal 2 5% 54 2%
Lymphatic 1 3% 30 1%
Integumentary 1 3% 24 1%
Multiple 4 10% 334 14%
Table 2
Comparison with Real-World Incidence.
Incidence Percent (Fraction) of Top 40 Diseases Representative Diseases Percent (Fraction) of Top 20 Inpatient Admissions (2018) Representative Principal Diagnoses p-value
Common (>1 million yearly US cases) 40% (16/40) anemia, arthritis, asthma, cellulitis, dementia, diabetes, diarrhea, heart attack, heart disease, hernia, hypertension, migraine, pneumonia, pulmonary edema, sepsis, tremor 79% (15/19) acute MI, acute renal failure, cardiac dysrhythmias, COPD, depressive disorders, diabetes, fluid/electrolyte disorders, heart disease, heart failure, osteoarthritis, pneumonia, respiratory failure, septicemia, skin/subcutaneous infections, UTIs 0.033
Uncommon (200,000 - 1 million yearly US cases) 30% (12/40) Alzheimer’s disease, appendicitis, bowel obstruction, cardiac arrest, cardiomyopathy, congestive heart failure, diverticulitis, ischemia, lung cancer, pancreatitis, stroke aortic aneurysm, compartment syndrome, epilepsy, hepatitis, 5% (1/19) cerebral infarction
Rare (<200,000 yearly US cases) 25% (10/40) leukemia, biliary tract disease, psychotic disorders, spondylopathy, meningitis, pneumothorax, syphilis, teratoma 16% (3/19)
Extremely Rare (<50 yearly US cases) 5% (2/40) plague, tetanus 0% (0/19)
Indeterminate N/A - (1) complications of previous care
Table 3
Summary of the pharmacologic classes.
Pharmacologic Class Entries (n=40) Entries (%) Mentions (n=1333) Mentions (%)
Analgesic 4 10% 454 34%
Hypertensive/Cardiac 8 20% 275 21%
Anesthetic 3 8% 248 19%
Antibiotic 9 22% 120 9%
Diuretic 2 5% 57 4.30%
Sedative/Anxiolytic 4 10% 57 4.30%
Steroid 2 5% 25 1.90%
Miscellaneous 8 20% 112 8.40%

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