Proposal for the Creation of New ICD-10 Codes for Environmental and Climate Change-Related Health Conditions

Executive Summary

This proposal calls for the establishment of specific ICD-10 codes to categorize health conditions directly related to environmental factors and climate change. The introduction of these codes is imperative for accurately identifying, monitoring, and managing the health impacts of environmental changes, facilitating targeted research, and informing effective public health interventions.

Background

The global impact of climate change and environmental degradation on human health is increasingly recognized. Health conditions arising from air pollution, extreme weather events, temperature extremes, and increased prevalence of vector-borne diseases are of growing concern. However, the current ICD-10 coding system lacks the granularity to specifically identify health conditions related to environmental and climate change factors, which hampers efforts to systematically address these issues.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes within a distinct category for environmental and climate change-related health conditions. These codes would enable the classification of conditions by their environmental determinants. Proposed codes could include:

· EC01: Respiratory Conditions Exacerbated by Air Pollution

· EC02: Heat-related Illnesses and Heatstroke

· EC03: Health Conditions Resulting from Extreme Weather Events

· EC04: Vector-borne Diseases Exacerbated by Climate Change

1. Clinical Guidelines for Diagnosis and Management: Develop comprehensive clinical guidelines that utilize the new codes, offering healthcare providers clear criteria for diagnosing, reporting, and managing health conditions related to environmental and climate factors. These guidelines should include preventive measures and adaptation strategies for at-risk populations.

2. Educational Initiatives: Implement education and awareness programs targeting healthcare professionals, patients, and the broader community to increase understanding of the health risks posed by environmental and climate change. Education should promote preventive health behaviors and environmental stewardship.

3. Research and Surveillance: Encourage research into the health impacts of environmental and climate change, leveraging the new ICD-10 codes for consistent data collection and analysis. Establish surveillance systems to monitor trends and outcomes related to these conditions, informing public health strategies and policy-making.

Benefits

- Improved Patient Care: Specific ICD-10 codes for environmental and climate change-related health conditions will enable more accurate diagnosis and targeted management, improving patient outcomes and health resilience.

- Enhanced Research and Data Collection: The introduction of these codes will facilitate standardized data collection, supporting epidemiological research, and enabling the evaluation of public health interventions.

- Informed Public Health Strategies: Better data and understanding of the health impacts of environmental and climate change will inform public health strategies, guiding interventions to mitigate these impacts and adapt healthcare systems to emerging challenges.

Conclusion

The creation of ICD-10 codes for environmental and climate change-related health conditions is a critical step toward addressing the complex health challenges posed by global environmental changes. By providing a framework for accurate diagnosis, reporting, and management, these codes will enhance healthcare delivery, support research, and inform public health policies designed to protect and promote human health in the face of environmental and climate threats. We strongly advocate for the adoption of these proposed codes to facilitate a proactive and informed response to one of the most pressing health issues of our time.

References

Ebi, K. L., & Semenza, J. C. (2008). Community-based adaptation to the health impacts of climate change. American Journal of Preventive Medicine 35(5), 501-507.

Lake, I. R., Hooper, L., Abdelhamid, A., Bentham, G., Boxall, A. B. A., Draper, A., Fairweather-Tait, S., Hulme, M., Hunter, P. R., Nichols, G., & Waldron, K. W. (2012). Climate change and food security: health impacts in developed countries. Environmental Health Perspectives 120(11), 1520-1526.

McIver, L., Kim, R., Woodward, A., Hales, S., Spickett, J., Katscherian, D., Hashizume, M., Honda, Y., Kim, H., Iddings, S., Naicker, J., Bambrick, H., McMichael, A. J., & Ebi, K. L. (2016). Health impacts of climate change in Pacific Island countries: a regional assessment of vulnerabilities and adaptation priorities. Environmental Health Perspectives, 124(11), 1707-1714.

McMichael, A. J., Woodruff, R. E., & Hales, S. (2006). Climate change and human health: impacts, vulnerability, and mitigation. The Lancet 367(9528), 859-869.

Patz, J. A., McGeehin, M. A., Bernard, S. M., Ebi, K. L., Epstein, P. R., Grambsch, A., Gubler, D. J., Reiter, P., Romieu, I., Rose, J. B., Samet, J. M., & Trtanj, J. (1998). Health impacts of climate change and ozone depletion: an ecoepidemiologic modeling approach. Environmental Health Perspectives, 106(Suppl 1), 241-251.

Proposal for the Introduction of New ICD-10 Codes: Drug-Induced Cognitive Impairment

Executive Summary

This proposal aims to introduce specific ICD-10 codes for cognitive impairments attributed to the use of certain medications. The recognition of drug-induced cognitive impairment in the ICD-10 coding system would facilitate improved diagnosis, treatment, and prevention strategies, enhancing patient care and safety. Given the aging population and the prevalence of polypharmacy, addressing this issue is of paramount importance for healthcare providers, patients, and caregivers alike.

Background

Cognitive impairment can significantly affect an individual's quality of life, encompassing a range of symptoms from mild cognitive deficits to severe dementia. While various factors contribute to cognitive impairment, evidence suggests that certain medications can induce or exacerbate cognitive dysfunction. These include, but are not limited to, benzodiazepines, anticholinergics, opioids, and some antipsychotics. Despite this knowledge, the link between specific medications and cognitive impairment often goes unrecognized in clinical settings, leading to underdiagnosis and inadequate management.

Proposal Details

1. Creation of ICD-10 Codes: We propose the establishment of new ICD-10 codes under the category of "Drug-Induced Cognitive Impairment." These codes would allow for the classification of cognitive impairment based on the class of medication implicated. Examples might include:

· DCI01: Cognitive Impairment Induced by Benzodiazepines

· DCI02: Cognitive Impairment Induced by Anticholinergics

· DCI03: Cognitive Impairment Induced by Opioids

· DCI04: Cognitive Impairment Induced by Antipsychotics

2. Clinical Guidelines and Management Strategies: Develop and disseminate clinical guidelines to assist healthcare providers in identifying, diagnosing, and managing drug-induced cognitive impairment. These guidelines should include recommendations on assessing cognitive function before and during treatment with high-risk medications, strategies for minimizing exposure to these drugs, and alternatives with a lower risk of cognitive side effects.

3. Educational Initiatives: Implement education and awareness programs targeting healthcare professionals, patients, and the general public. The aim would be to increase awareness of the potential cognitive side effects of certain medications, promote careful medication management, and encourage regular cognitive assessments for individuals at risk.

4. Research and Surveillance: Encourage research into the prevalence, mechanisms, and long-term effects of drug-induced cognitive impairment. Additionally, support the development of surveillance systems to monitor trends and outcomes associated with this condition, which could inform future healthcare policies and guidelines.

Benefits

· Improved Patient Care: With specific ICD-10 codes, healthcare providers can more accurately diagnose and manage drug-induced cognitive impairment, potentially reversing or mitigating its effects.

· Enhanced Awareness and Education: Increased awareness among healthcare providers and patients could lead to more cautious use of medications known to impair cognitive function, reducing the incidence of drug-induced cognitive deficits.

· Better Research and Data Collection: Specific codes would facilitate research and data collection on drug-induced cognitive impairment, leading to a better understanding of its prevalence, risk factors, and effective management strategies.

Conclusion

Introducing ICD-10 codes for drug-induced cognitive impairment is a crucial step toward improving patient outcomes and healthcare practices. By enabling precise diagnosis and management, and by fostering greater awareness and research, these codes will address an important gap in patient care related to medication use. We advocate for the adoption of these proposed codes by healthcare coding authorities to enhance the safety and well-being of patients receiving medication with potential cognitive side effects.

References

Abdul-Monim, Z., Reynolds, G. P., & Neill, J. C. (2003). The effect of repeated administration of phencyclidine, amphetamine and MK-801 selectively impairs spatial learning in mice: A possible model of psychotomimetic drug-induced cognitive deficits. Behavioural Pharmacology 14(7), 533-544.

Mula, M., & Sander, J. W. (2009). Antiepileptic drug-induced cognitive adverse effects: Potential mechanisms and contributing factors. CNS Drugs 23(2), 121-137.

O'Keeffe, S. T., & Lavan, J. N. (1999). Drug-induced cognitive impairment in the elderly. Drugs & Aging 15(1), 15-28.

Tune, L. E. (1999). Drug-induced cognition disorders in the elderly: Incidence, prevention and management. Drug Safety 21(2), 101-115.

Vonmoos, M., Hulka, L. M., Preller, K. H., Minder, F., Baumgartner, M. R., & Quednow, B. B. (2014). Cognitive impairment in cocaine users is drug-induced but partially reversible: Evidence from a longitudinal study. Neuropsychopharmacology 39(9), 2200-2210.

Proposal for the Introduction of a Separate ICD-10 Code for Rhinitis - Geriatric Non-Allergic Type

Executive Summary

This proposal seeks the creation of a distinct ICD-10 code for Geriatric Non-Allergic Rhinitis, a prevalent condition in the elderly, characterized by chronic nasal symptoms not attributed to allergic reactions. The introduction of a specific code for this condition will enhance diagnostic accuracy, streamline treatment approaches, and improve patient outcomes by distinguishing it from other forms of rhinitis that require more invasive and complex interventions.

Background

Geriatric Non-Allergic Rhinitis affects approximately 40% of the elderly population, presenting with symptoms such as chronic nasal drippiness, sneezing, coughing, post-nasal dripping, bronchitis, rib cage exhaustion, and even cough syncope. This condition typically arises from the thinning or atrophy of nasal tissue, leading to a heightened sensitivity to irritants like dust particles. Unlike other forms of rhinitis, which necessitate comprehensive workups including CT scans and nasal endoscopy, Geriatric Non-Allergic Rhinitis can often be effectively managed with simpler remedies, such as the use of a humidifier.

Current Classification Challenges

The current ICD-10 classification under J31.0 encompasses various chronic forms of rhinitis without providing a specific code for Geriatric Non-Allergic Rhinitis. This lack of specificity complicates the treatment protocol, which is already perceived as complex, and does not cater to the simpler management needs of Geriatric Non-Allergic Rhinitis.

Proposal for New ICD-10 Code

· Proposed Code: Introduce a new ICD-10 code specifically for Rhinitis - Geriatric Non-Allergic Type.

· Rationale: A dedicated code will facilitate a more accurate diagnosis, allowing healthcare providers to adopt the most appropriate and less invasive treatment strategies, significantly improving the quality of life for affected elderly patients.

Benefits of the Proposed Code

· Enhanced Diagnostic Precision: Clinicians will be able to more accurately identify and diagnose Geriatric Non-Allergic Rhinitis, distinguishing it from allergic rhinitis and other chronic forms that may require different treatment approaches.

· Simplified Treatment Protocols: With a specific code, healthcare providers can streamline treatment protocols, emphasizing simpler, cost-effective remedies like humidifiers, which are particularly suited to managing this condition.

· Improved Patient Outcomes: By recognizing Geriatric Non-Allergic Rhinitis as a distinct condition, the proposed ICD-10 code will enable targeted management strategies, reducing the burden of unnecessary investigations and interventions for elderly patients.

· Facilitated Research and Surveillance: A specific ICD-10 code will aid in epidemiological studies, helping to track prevalence, treatment outcomes, and the effectiveness of various management strategies for this condition.

Conclusion

The introduction of a distinct ICD-10 code for Rhinitis - Geriatric Non-Allergic Type is imperative to address the unique challenges and treatment needs of the elderly population afflicted by this condition. By providing a dedicated code, healthcare systems can offer more precise, effective, and simplified care protocols, significantly enhancing patient care and outcomes for this vulnerable demographic. We strongly advocate for the adoption of this proposed code to improve clinical practice and patient well-being.

References

American Academy of Allergy, Asthma & Immunology. "Rhinitis 2020: A Practice Parameter Update." https://www.aaaai.org/Aaaai/media/MediaLibrary/PDF%20Documents/Practice%20and%20Parameters/Rhinitis-2020-A-practice-parameter-update.pdf

Eliyan, Y., Varga-Huettner, V.E., Pinto, J.M. (2023). Physiology of the Aging Nose and Geriatric Rhinitis. In: Celebi, Ö.Ö., Önerci, T.M. (eds) Nasal Physiology and Pathophysiology of Nasal Disorders. Springer, Cham. https://doi.org/10.1007/978-3-031-12386-3_14

Healthline Media. (2021, September 24). Humidifier for Sinus Problems: What works best? Healthline. https://www.healthline.com/health/humidifier-for-sinus#humidifier-tips 

National Center for Biotechnology Information. "Management of Rhinitis: Allergic and Non-Allergic." https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2794852/

Nkosi, V., Rathogwa-Takalani, F., & Voyi, K. (2020). Non-allergic rhinitis and associated risk factors among the elderly in communities close to Gold Mine dumps in Gauteng and North West Provinces in South Africa: A cross-sectional study. International Archives of Occupational and Environmental Health, 93(6), 715–721. https://doi.org/10.1007/s00420-020-01526-5 

Pinto, J. M., & Jeswani, S. (2010). Rhinitis in the geriatric population. Allergy, Asthma & Clinical Immunology, 6(1). https://doi.org/10.1186/1710-1492-6-10 

Bernstein, J. A. (2018). Rhinitis and related upper respiratory conditions: A clinical guide. Springer. 

Proposal for the Introduction of New ICD-10 Codes: Medication-Related Osteoporosis

Executive Summary

This proposal seeks to advocate for the establishment of specific ICD-10 codes for osteoporosis induced by the use of certain medications. Recognizing medication-related osteoporosis in the ICD-10 coding system would significantly enhance the ability of healthcare providers to diagnose, manage, and prevent this condition. It would also facilitate better patient education, research, and policy-making regarding bone health and the side effects of long-term medication use.

Background

Osteoporosis is a condition characterized by weakened bones, increasing the risk of fractures. While several factors contribute to osteoporosis, certain medications have been identified as potential risks for diminishing bone density. Notably, glucocorticoids, proton pump inhibitors (PPIs), anticonvulsants, and some treatments for breast cancer and prostate cancer are linked to an increased risk of osteoporosis. Despite this knowledge, medication-related osteoporosis is often underdiagnosed until a fracture occurs, suggesting a gap in proactive management and prevention.

Proposal Details

1. Creation of ICD-10 Codes: We propose introducing new ICD-10 codes within the existing osteoporosis section, specifically dedicated to medication-related osteoporosis. These codes would differentiate osteoporosis by the class of medication causing it, for example:

· MO01: Osteoporosis Due to Glucocorticoids

· MO02: Osteoporosis Due to Proton Pump Inhibitors

· MO03: Osteoporosis Due to Anticonvulsants

· MO04: Osteoporosis Due to Endocrine Therapy (Breast/Prostate Cancer)

1. Clinical Guidelines and Recommendations: Accompanying the new codes, we recommend the development and dissemination of clinical guidelines for the prevention, screening, and management of medication-related osteoporosis. These guidelines should include recommendations on baseline and periodic bone density testing, calcium and vitamin D supplementation, lifestyle modifications, and alternative medication considerations where feasible.

2. Educational Initiatives: Implement educational programs targeting healthcare providers, patients, and caregivers to increase awareness about the risk of medication-related osteoporosis and strategies for prevention and management. This could include informational brochures, online resources, and continuing medical education courses.

3. Research and Surveillance: Encourage and support research focused on understanding the epidemiology of medication-related osteoporosis, evaluating the effectiveness of various management strategies, and developing new treatments to mitigate bone loss associated with medication use.

Benefits

· Enhanced Patient Management: Specific ICD-10 codes would enable healthcare providers to more accurately diagnose and manage osteoporosis related to medication use, potentially preventing fractures and other complications.

· Improved Monitoring and Reporting: The introduction of these codes would facilitate better tracking of the prevalence and outcomes associated with medication-related osteoporosis, informing public health strategies and research.

· Increased Awareness: Focused educational efforts would raise awareness among both healthcare professionals and patients about the risks of certain medications to bone health, leading to more proactive management strategies.

Conclusion:

Introducing ICD-10 codes for medication-related osteoporosis is a necessary step towards improving patient outcomes, enhancing clinical practices, and expanding our understanding of the relationship between medications and bone health. By recognizing the impact of certain drugs on osteoporosis risk, healthcare providers can take steps to mitigate this risk, ultimately reducing the incidence of fractures and improving the quality of life for patients on long-term medication therapies. We strongly advocate for the adoption of these proposed codes by the relevant healthcare coding authorities.

References

Aljohani, S., Fliefel, R., Ihbe, J., Kühnisch, J., Ehrenfeld, M., & Otto, S. (2017). What is the effect of anti-resorptive drugs (ARDS) on the development of medication-related osteonecrosis of the jaw (MRONJ) in osteoporosis patients: A systematic review. Journal of Cranio-Maxillofacial Surgery, 45(9), 1493–1502. https://doi.org/10.1016/j.jcms.2017.05.028 

Guan, H. (2023). Medication-related osteonecrosis of the jaw. Radiopaedia.Org. https://doi.org/10.53347/rid-164428 

Nicolatou-Galitis, O., Schiødt, M., Mendes, R. A., Ripamonti, C., Hope, S., Drudge-Coates, L., Niepel, D., & Van den Wyngaert, T. (2019). Medication-related osteonecrosis of the jaw: Definition and best practice for prevention, diagnosis, and treatment. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, 127(2), 117–135. https://doi.org/10.1016/j.oooo.2018.09.008 

Supanumpar, N., Pisarnturakit, P. P., Charatcharoenwitthaya, N., & Subbalekha, K. (2024). Physicians’ awareness of medication-related osteonecrosis of the jaw in patients with osteoporosis. PLOS ONE, 19(1). https://doi.org/10.1371/journal.pone.0297500 

Yeam, C. T., Chia, S., Tan, H. C., Kwan, Y. H., Fong, W., & Seng, J. J. (2018). A systematic review of factors affecting medication adherence among patients with osteoporosis. Osteoporosis International, 29(12), 2623–2637. https://doi.org/10.1007/s00198-018-4759-3 

Proposal for the Introduction of New ICD-10 Codes: Night Bliss Disorder

Executive Summary

This proposal advocates for the establishment of specific ICD-10 codes for Night Bliss Disorder, a condition characterized by the occurrence of exceptionally positive, blissful dreams. While the ICD-10 currently includes a code for nightmare disorder (F51.5), there is a notable absence of codes for categorizing dreams that have a profoundly positive impact on an individual’s mental health. Recognizing these blissful dream experiences with distinct ICD-10 codes would enhance understanding, facilitate research, and underscore the importance of positive psychological experiences in overall mental health.

Background

Blissful dreams can significantly contribute to an individual's emotional well-being, offering therapeutic benefits and insights. Examples of such dreams include, but are not limited to, sexual dreams, dreams of regained lost function, dreams of deceased loved ones, flying dreams, adventure dreams, reunions, love and romance, success and achievement, peaceful and serene settings, magical or fantasy elements, childhood memories, celebrations, creative endeavors, and problem-solving (Eureka) dreams. The recognition and systematic documentation of these experiences are crucial for advancing our understanding of their impact on mental health and well-being.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes under a category dedicated to Night Bliss Disorder. These codes would classify various types of blissful dreams, acknowledging their positive effects. Proposed codes might include:

· NBD01: Night Bliss Disorder with Sexual Content

· NBD02: Night Bliss Disorder with Regained Function

· NBD03: Night Bliss Disorder with Deceased Loved Ones

· NBD04: Night Bliss Disorder with Flying Sensation

· NBD05: Night Bliss Disorder with Adventure

· Additional codes for other specific types of blissful dreams as outlined in the background.

1. Clinical Guidelines for Documentation and Research: Develop guidelines for healthcare providers on documenting occurrences of Night Bliss Disorder using the new codes. This includes identifying the types of blissful dreams and their potential implications for mental health and therapeutic applications.

2. Educational Initiatives: Implement education and awareness programs for healthcare professionals to increase understanding of the significance of blissful dreams and their potential positive impact on mental health. 

3. Research and Surveillance: Encourage research into Night Bliss Disorder, utilizing the new ICD-10 codes to facilitate the collection of data on prevalence, patterns, and psychological effects. This research could inform therapeutic practices and deepen understanding of positive psychological experiences.

Benefits

· Enhanced Understanding of Positive Dream Experiences: The introduction of specific ICD-10 codes for Night Bliss Disorder will enable a more nuanced understanding of the role of positive dreams in mental health.

· Improved Patient Care: Recognizing and documenting blissful dreams can contribute to a more comprehensive approach to mental health care, considering positive psychological experiences alongside disorders.

· Support for Research: Specific codes will facilitate research into the therapeutic benefits of blissful dreams, potentially leading to innovative approaches to mental health treatment and well-being.

Conclusion

The creation of ICD-10 codes for Night Bliss Disorder represents an important step in recognizing the full spectrum of dream experiences and their impact on mental health. By providing a structured way to document and study these positive experiences, healthcare professionals can gain insights into their therapeutic potential, contributing to a more holistic approach to mental health and well-being. We strongly advocate for the adoption of these proposed codes to enhance the understanding and appreciation of blissful dreams in psychological health.

References

Donderi, D. C. (1986). Dream content and self-reported well-being among recurrent dreamers, past-recurrent dreamers, and nonrecurrent dreamers. Psychological Reports 59(2), 467-482.

Zadra, A., & Stickgold, R. (2007). Absorption, psychological boundaries and attitude towards dreams as correlates of dream recall: two decades of research seen through a meta analysis. Journal of Sleep Research 16(1), 51-59.

Hill, C. E., Diemer, R., & Heaton, K. J. (1994). Are the effects of dream interpretation on session quality, insight, and emotions due to the dream itself, to projection, or to the interpretation process? Dreaming 4(2), 99-134.

Zadra, A. L. (1996). 17 recurrent dreams: Their relation to life events. Trauma and Dreams, 231–248. https://doi.org/10.4159/9780674270534-019 

Proposal for the Introduction of a New ICD-10 Code: Hypodipsia - Drug Induced

Background and Rationale

Hypodipsia, or decreased thirst sensation, can significantly impact patient health, particularly when it leads to dehydration. This condition can exacerbate the risk of kidney malfunction, a notable concern with the use of certain medications, including GLP-1 agonists. GLP-1 agonists, known for their appetite-suppressing effects, may inadvertently suppress thirst due to their interaction with the dopamine system, which plays a crucial role in the rewarding properties of eating and drinking.

The mechanism of thirst regulation involves the lamina terminalis located beneath the third ventricle of the brain, where specific cells lie outside the blood-brain barrier. The act of drinking water is perceived as rewarding well before any detectable change in blood osmolarity occurs, suggesting that the gratification from drinking does not solely depend on physiological needs for water balance but also involves the brain's reward systems, particularly those governed by dopamine. Given that GLP-1 agonists and certain dopaminergic drugs, such as stimulants, can modulate this system, there is a plausible link between these medications and the suppression of thirst.

Proposal

It is proposed to introduce a new ICD-10 code specifically for Drug-Induced Hypodipsia, with subdivisions to account for the different classes of drugs implicated, namely:

1. Hypodipsia - Drug Induced from GLP-1 Agonists: This category would address the specific risk associated with GLP-1 agonist therapy, highlighting the need for healthcare providers to advise patients on the importance of regular fluid intake, regardless of their perceived need to drink.

2. Hypodipsia - Drug Induced from Dopaminergic Drugs (e.g., Stimulants): Given the broader impact of dopaminergic drugs on the reward system and their potential to suppress thirst, this category would encompass a wider range of medications that could lead to hypodipsia, thereby alerting clinicians to monitor hydration status in patients prescribed these drugs.

Clinical Implications and Recommendations

The introduction of these specific ICD-10 codes would facilitate better patient monitoring, targeted interventions, and research into the prevalence and outcomes of drug-induced hypodipsia. It would also serve as a critical reminder for healthcare providers to educate patients about the importance of maintaining adequate hydration, especially those on GLP-1 agonists or dopaminergic medications, who might not experience normal thirst cues. Such proactive measures could significantly mitigate the risk of dehydration and its associated complications, improving patient safety and outcomes in populations vulnerable to drug-induced hypodipsia.

References

Giustina, A., Allora, A., Frara, S., Spina, A., & Mortini, P. (2022). The Hypothalamus. The Pituitary, 301–340. https://doi.org/10.1016/b978-0-323-99899-4.00002-0 

Lee, M. D., & Clifton, P. G. (2010). Role of the serotonergic system in appetite and ingestion control. Handbook of Behavioral Neuroscience, 331–345. https://doi.org/10.1016/s1569-7339(10)70088-6

McKay, N. J., Kanoski, S. E., Hayes, M. R., & Daniels, D. (2011). Glucagon-like peptide-1 receptor agonists suppress water intake independent of effects on Food Intake. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 301(6). https://doi.org/10.1152/ajpregu.00472.2011 

Wysokiński, A., Sobów, T., Kłoszewska, I. et al. Mechanisms of the anorexia of aging—a review. AGE 37, 81 (2015). https://doi.org/10.1007/s11357-015-9821-x

Proposal for the Introduction of New ICD-10 Codes for Caffeine Addiction

Introduction and Rationale

Caffeine addiction, often referred to as caffeine dependence, manifests as a compelling urge to consume caffeine despite potential adverse health effects or disruption to daily functioning. Characterized by symptoms of tolerance, withdrawal, and an inability to control use, caffeine addiction significantly impacts individuals' physical and psychological well-being. While the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) recognizes caffeine withdrawal, it does not formally acknowledge caffeine addiction as a disorder. Given the widespread consumption of caffeine and evidence suggesting a subset of individuals experience problematic use, there is a critical need for the ICD-10 to include specific codes for caffeine addiction. This inclusion would aid in diagnosis, treatment, and research, fostering a deeper understanding of its prevalence and impact.

Proposal for New ICD-10 Codes

We propose the introduction of specific ICD-10 codes under the category of “Mental and Behavioral Disorders Due to Psychoactive Substance Use,” (specifically, under code F15.929 for caffeine intoxication and code F15.93 for caffeine withdrawal), focusing on caffeine addiction. These codes would enhance the ability of healthcare providers to identify and treat individuals suffering from this condition, promoting more targeted and effective interventions.

Criteria for Caffeine Addiction

The proposed diagnostic criteria for caffeine addiction include experiencing at least three of the following over a 12-month period:

· Increased tolerance to caffeine.

· Withdrawal symptoms upon cessation.

· Consumption of larger amounts or over a longer period than intended.

· Persistent desire or unsuccessful efforts to cut down use.

· Significant time spent in activities necessary to obtain, use, or recover from caffeine's effects.

· Continued use despite knowledge of adverse physical or psychological problems.

· Sacrifice of social, occupational, or recreational activities.

Prevalence and Need for Recognition

Studies indicate that a significant percentage of caffeine users exhibit dependence criteria, with estimates suggesting up to 30% of users demonstrating problematic use. The varied prevalence rates underscore the necessity for formal recognition and coding within the ICD-10 to accurately reflect the disorder's impact and guide healthcare strategies.

Current ICD-10 Coding Limitations

Although the ICD-10 includes codes for caffeine intoxication and withdrawal, the absence of codes for caffeine addiction limits comprehensive care and research. By introducing specific codes for caffeine addiction, healthcare professionals can better document, study, and address this condition.

Proposed Benefits

· Enhanced Clinical Recognition and Treatment: Specific ICD-10 codes will enable healthcare providers to accurately diagnose and treat caffeine addiction, leading to improved patient outcomes.

· Facilitated Research: Standardized diagnostic criteria will promote research into caffeine addiction, advancing understanding of its epidemiology, etiology, and treatment.

· Informed Public Health Strategies: Better data on caffeine addiction will inform public health initiatives aimed at reducing the prevalence and impact of this condition.

Conclusion

The introduction of ICD-10 codes for caffeine addiction is a necessary step toward recognizing the significant health implications of problematic caffeine use. By formalizing these diagnostic criteria, we can improve patient care, enhance research capabilities, and inform more effective public health strategies. We urge the adoption of these proposed codes to address the growing concern over caffeine addiction and its consequences on individual and public health.

References

Addicott, M. A. Caffeine Use Disorder: A Review of the Evidence and Future Implications. Current Addiction Reports 1(3), 186-192.

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Juliano, L. M., & Griffiths, R. R. A critical review of caffeine withdrawal: empirical validation of symptoms and signs, incidence, severity, and associated features. Psychopharmacology 176(1), 1-29.

Meredith, S. E., Juliano, L. M., Hughes, J. R., & Griffiths, R. R. (2013). Caffeine use disorder: a comprehensive review and research agenda. Journal of Caffeine Research 3(3), 114–130.

Striley, C. W., Griffiths, R. R., & Cottler, L. B. Caffeine Use Disorder: An Item Response Theory Analysis of DSM-IV/ICD-10 Criteria. American Journal of Addiction 20(1), 72–81.

Sweeney, M.M., Griffiths, R.R. (2023). Disorders Due to Substance Use: Caffeine. In: Tasman, A., et al. Tasman’s Psychiatry. Springer, Cham. https://doi.org/10.1007/978-3-030-42825-9_49-1

World Health Organization. (1993). The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization

Proposal: Improving the User Friendliness of ICD Coding

Executive Summary

This proposal focuses on making the International Classification of Diseases, Tenth Revision (ICD-10) more user-friendly and accessible by addressing numerous components of its overall structure including search capabilities, its accessibility features, and compliance with the Americans with Disabilities Act Amendments Act (ADAAA) requirements. Adopting the proposed changes and enhancements to the ICD-10 will result in dramatic improvements to this de facto standard used globally in healthcare systems.

1. Reconsider the Nomenclature: Prioritizing Nouns over Adjectives

· Rationale: Currently, some of the classification names are challenging to understand, particularly for those outside medical professionals or those starting their professional training. A simple change such as placing Nouns before Adjectives would align with the natural language processing patterns, making it easier and quicker for users to understand and locate conditions. For instance, "Diabetes Mellitus, Type 2" is mirrored better to our mental processing than "Type 2 Diabetes Mellitus." Ideally, both would be present.

· Implementation: A comprehensive review and revision/enhancement of the coding guidelines to prioritize the essential subject of the disorder in the nomenclature would be required. This requires a systematic review and modification of current codes and descriptions.

· Benefits: This simple modification will noticeably enhance the intuitiveness of the classification system thereby increasing user-friendliness, especially for non-specialists or those in training.

1. Streamline Search Capabilities

· Incorporate Mechanism for Misspelled Entries: Incorporating a robust search function that can handle misspellings and typographical errors can be a substantial time saver. Implementing algorithms that suggest corrections or provide the most relevant results despite inaccuracies in the query can be game-changing.

· Leverage Natural Language Processing (NLP): NLP can be utilized to handle conversational or varied input styles, accommodating for different terminologies or phrasings used by diverse healthcare professionals.

· Refine Semantic Search: Enhance the search engine to interpret and comprehend context and semantics, rather than just seeking an exact match. This allows users to trace codes based on associated terms, presenting symptoms, or medical conditions.

1. Develop a Standardized XML Schema for Nosology

· Rationale: Currently there is no standardized XML schema specifically for nosology, although health-related data can be structured to some extent using HL7 standards, in particular the Clinical Document Architecture (CDA) standard. 

· Benefits: Developing a standardized XML schema specifically for nosology can offer multiple benefits:

o Improved Interoperability: A standardized XML schema facilitates better communication and data exchange between different healthcare systems. This can increase interoperability and seamless sharing of disease-related information across various platforms.

o Consistency and Accuracy: Having a standardized format ensures that all data are recorded and classified uniformly, reducing discrepancies and increasing the accuracy of information.

o Enhanced Analysis: Standardization allows for easier aggregation of disease data, which can facilitate advanced analysis, like tracking disease patterns and conducting epidemiological studies.

o Facilitates Automation: A standardized XML schema can handle automated systems better. For instance, computer-based patient record systems can easily decipher and use the data, which will enhance automated decision support in healthcare.

o Faster Transactions: Standardized data may be validated and processed quicker, leading to faster transactions, a critical feature in scenarios like clinical trials and other time-sensitive situations.

o Reusability: A standard XML schema can be reusable across different systems and applications dealing with nosology, reducing the effort and cost of developing new schemas for each system.

o Enhanced Accessibility: This schema can be configured to be easily understandable and accessible for various stakeholders in healthcare, including researchers, doctors, data analysts, and public health officials.

o Regulatory Compliance: A standardized schema may be more likely in sync with specified data structure requirements set by healthcare regulatory bodies, which will facilitate compliance reporting. 

o Efficient Training: Training healthcare personnel and researchers on using one standardized format for recording and retrieving data may be more efficient than multiple different systems.

o Promotion of Research: A standardized XML schema for nosology can promote research by making disease-related data more accessible to researchers globally. It encourages collaboration and comparison of data between different studies.

1. Incorporate Accessibility Features for Differently-abled

· For Visually Impaired Users:

o Seamless Compatibility with Screen Readers: Ensure that the digital variant of the ICD-10 is fully compatible with screen readers. This includes proper tagging of elements, alt text for images, ensuring intuitive guidance for navigation.

o Text-to-Speech (TTS) Integration: Adopt TTS technology to read out the codes and associated descriptions clearly, providing hassle-free access for individuals who heavily rely on auditory senses.

o High-Contrast and Large-Text Options: Cater to users with restricted vision by offering user interfaces that support high-contrast modes and adaptable text sizes.

· For Users with Auditory Impairments:

o Ensure Visual Alerts and Instructions: A well-designed visual guide, cues, and text instructions ought to replace or supplement audio alerts, ensuring all notifications and directions are universally accessible.

o Closed Captioning and Sign Language Interpretation: Every multimedia content and instructional video must support closed captioning and sign language interpretation options.

1. Assure Compliance with ADAAA

· Perform Comprehensive Accessibility Testing: Conduct rigorous testing with individuals who represent a range of disabilities to identify and promptly address any potential user accessibility hurdles.

· User-Centered Design Approach: Champion a user-oriented design philosophy involving professional and personal feedback from distinctive users with disabilities, fostering a system that caters to each user's needs efficaciously.

· Ongoing Updates and Support: Chart out a protocol for regular updates encompassing technological advancements and user feedback to consistently meet accessibility prerequisites.

1. Build a Supportive Ecosystem

· Accessible Training Materials: Develop training programs and materials that are universally accessible. This should include creating multimedia content with interpretations in braille, audio guides, and videos with sign language interpretation, amongst others.

· Exemplary Support Services: Users with disabilities should have access to dedicated and impeccable support services, aiding them to use the ICD-10 system effectively and effortlessly.

1. User-Friendly Interface Design 

· Simplified Navigation: Design the interface of the ICD-10 system with navigation features that are intuitive and easy to understand. This includes clear labeling, easy-to-understand icons, and consistent placement of important features on the pages. 

· Optimized Layout: Optimally arrange the information on the screen to help users find what they are looking for more quickly. Important information or frequently used features should be prominently displayed and easily accessible. 

· Mobile Compatibility: Ensure that the design is compatible with various devices, including smartphones and tablets, which are increasingly being used by healthcare professionals. 

· Bi-directional Dictionary: Integrate a dictionary that can work in both directions i.e., code to condition and condition to code. This can prove especially helpful for users who, for instance, only know the code but not the condition it represents, or vice versa. 

1. Multilingual Support

· Language Options: Add support for multiple languages to accommodate a diverse user base. This will make the ICD-10 system more user-friendly for healthcare professionals around the world. 

· Language-Specific Search: Include a language-specific search option to allow users to search for codes and other information in their preferred language. 

1. Personalized User Experience 

· User Profiles: Implement user profiles that save individual preferences, such as commonly used codes or favorite features, making the tool more efficient for repeated use. 

· Customizable Display: Allow users to customize the way the information is displayed according to their preference, such as changing the font size, color themes, or layout. 

1. Enhanced Data Management 

· Bulk Import/Export: Add the ability to import or export data in bulk to allow healthcare organizations to effectively manage their coding data. This functionality can save a lot of time when dealing with large datasets. 

· Data Security: Ensure that all user data is securely stored and transmitted, conforming to requirements of Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR).

· REST API Development: The ICD-10 website should provide an API through which queries to the database can be made. This will greatly simplify the development of automation systems that rely upon ICD-10 coding.

1. Feedback Mechanism

· User Feedback: Implement a user feedback system where users can report bugs, propose new features, or provide other feedback about their experience with the ICD-10 system. 

· Regular System Updates: Use the feedback to regularly update the system, ensuring it continues to meet the evolving needs of its users and keeps up with changes in the healthcare industry. 

Conclusion

Implementing these recommendations will significantly improve the user-friendliness, accessibility, and practicality of the ICD-10 coding system, leading to more accurate, effective, and efficient healthcare practices.

Proposal for the Creation of New ICD-10 Codes for Technology-Related Health Conditions

Executive Summary

This proposal advocates for the establishment of specific ICD-10 codes to categorize health conditions directly related to the use of technology. The introduction of these codes is crucial for recognizing and addressing the growing impact of technology on health, improving diagnosis, treatment, and prevention of technology-related conditions.

Background

The pervasive use of digital devices and technology has led to the emergence of new health conditions and the exacerbation of existing ones. Conditions such as digital eye strain, tech neck, and repetitive strain injuries from device use are becoming increasingly common, reflecting the significant role that technology plays in modern life. Despite their prevalence, there is currently a lack of specific ICD-10 codes to report and manage these conditions systematically.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes within a distinct category for technology-related health conditions. These codes would allow for the classification of conditions based on the type of technology use and the specific health issue. Proposed codes could include:

· TR01: Digital Eye Strain from Screen Use

· TR02: Tech Neck from Prolonged Device Use

· TR03: Repetitive Strain Injury from Computer Use

· TR04: Sleep Disorders Related to Blue Light Exposure

1. Clinical Guidelines for Diagnosis and Management: Develop and disseminate clinical guidelines that utilize the new codes, providing healthcare providers with clear criteria for diagnosing, reporting, and managing technology-related health conditions. These guidelines should emphasize ergonomic practices, breaks during technology use, and other preventive measures.

2. Educational Initiatives: Implement education and awareness programs targeting healthcare professionals, patients, and the public to increase awareness about the health risks associated with technology use and strategies for prevention. Education should also focus on promoting a healthy balance between technology use and physical activity.

3. Research and Surveillance: Encourage research into the prevalence, mechanisms, and effective treatment of technology-related health conditions. Use the new ICD-10 codes to facilitate consistent data collection and analysis, supporting epidemiological studies and the development of targeted interventions.

Benefits

· Improved Patient Care: The introduction of specific ICD-10 codes for technology-related health conditions will enable more accurate diagnosis and tailored management, potentially reducing the incidence and severity of these conditions.

· Enhanced Data Collection and Research: Specific codes will facilitate the collection of standardized data, supporting research into the impact of technology on health and informing the development of effective prevention and treatment strategies.

· Informed Public Health Strategies: Better understanding and tracking of technology-related health conditions will inform public health strategies aimed at mitigating these issues, including recommendations for technology use, ergonomics, and digital wellness programs.

Conclusion

The creation of ICD-10 codes for technology-related health conditions is an essential step in recognizing and addressing the health impacts of our increasingly digital world. By providing a framework for accurate diagnosis, reporting, and management, these codes will enhance patient care, support research, and inform public health initiatives designed to promote healthier interactions with technology. We strongly advocate for the adoption of these proposed codes to improve healthcare outcomes and address the challenges posed by the digital age.

References

Agbo, C., Mahmoud, Q., & Eklund, J. (2019). Blockchain technology in Healthcare: A systematic review. Healthcare, 7(2), 56. https://doi.org/10.3390/healthcare7020056 

Gell, N. M., Rosenberg, D. E., Demiris, G., LaCroix, A. Z., & Patel, K. V. (2013). Patterns of technology use among older adults with and without disabilities. The Gerontologist, 55(3), 412–421. https://doi.org/10.1093/geront/gnt166 

Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., Dijkstra, K., Fisk, A. D., Rogers, W. A., & Sharit, J. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710–1721. https://doi.org/10.1016/j.chb.2010.06.020 

Skinner, H., Biscope, S., Poland, B., & Goldberg, E. (2003). How adolescents use technology for health information: Implications for health professionals from Focus Group Studies. Journal of Medical Internet Research 5(4). https://doi.org/10.2196/jmir.5.4.e32 

Vargo, D., Zhu, L., Benwell, B., & Yan, Z. (2020). Digital technology use during covid 19 pandemic: A rapid review. Human Behavior and Emerging Technologies, 3(1), 13–24. https://doi.org/10.1002/hbe2.242 

Proposal for the Creation of ICD-10 Codes for E-Cigarette or Vaping Product Use-Associated Lung Injury (EVALI)

 Executive Summary

This proposal seeks the establishment of specific ICD-10 codes for E-Cigarette or Vaping Product Use-Associated Lung Injury (EVALI). The recognition of EVALI with dedicated codes within the ICD-10 classification system is critical for accurate diagnosis, epidemiological tracking, and the development of effective treatment protocols. These codes would also facilitate research into the condition and inform public health strategies aimed at reducing the incidence of EVALI.

Background

EVALI is a recently identified health condition associated with the use of e-cigarette or vaping products. It presents with a variety of pulmonary symptoms ranging from mild to severe, including cough, shortness of breath, and chest pain, often accompanied by gastrointestinal symptoms and fever. The identification and classification of EVALI have been challenging due to the lack of specific diagnostic codes, leading to potential underreporting and variability in treatment approaches.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes under a distinct category for EVALI. This category would include codes that specify the severity, symptoms, and outcomes of the condition. Proposed codes could include:

· EV01: EVALI with predominantly respiratory symptoms

· EV02: EVALI with mixed respiratory and gastrointestinal symptoms

· EV03: EVALI with acute respiratory distress syndrome (ARDS)

· EV04: EVALI with complications requiring mechanical ventilation

1. Clinical Guidelines for Diagnosis and Management: Develop comprehensive clinical guidelines that utilize the new EVALI codes, providing healthcare providers with clear criteria for diagnosis, reporting, and management. These guidelines should emphasize the importance of patient history regarding e-cigarette or vaping product use.

Educational Initiatives: Launch education and awareness programs targeting healthcare providers, patients, and the public about the risks associated with e-cigarette or vaping product use and the potential for EVALI. These programs should include information on recognizing early symptoms and seeking timely medical care.

Research and Surveillance: Encourage research into the causes, mechanisms, and treatments of EVALI, leveraging the new ICD-10 codes for consistent data collection and analysis. Establish surveillance systems to monitor the incidence, prevalence, and outcomes of EVALI, contributing to ongoing public health efforts to mitigate the impact of vaping products.

Benefits

Improved Patient Care: The introduction of specific ICD-10 codes for EVALI will enable healthcare providers to accurately diagnose and manage the condition, potentially improving patient outcomes.

Enhanced Data Collection and Research: Specific codes will facilitate the collection of standardized data on EVALI, supporting research and enabling public health authorities to track trends and identify risk factors associated with vaping product use.

Informed Public Health Strategies: Better data and understanding of EVALI will inform public health strategies and interventions aimed at reducing the use of e-cigarettes and vaping products, particularly among vulnerable populations.

Conclusion

The creation of ICD-10 codes for E-Cigarette or Vaping Product Use-Associated Lung Injury (EVALI) represents an essential step in addressing this emerging public health issue. By providing a mechanism for accurate diagnosis and reporting, these codes will enhance patient care, support research, and inform effective public health strategies to combat the harmful effects of vaping. We strongly advocate for the prompt adoption of these proposed codes to improve health outcomes and safeguard public health.

References

Blount, B. C., Karwowski, M. P., Shields, P. G., Morel-Espinosa, M., Valentin-Blasini, L., Gardner, M., Braselton, M., Brosius, C. R., Caron, K. T., Chambers, D., Corstvet, J., Cowan, E., De Jesus, V. R., Espinosa, P., Fernandez, C., Holder, C., Kuklenyik, Z., Kusovschi, J. D., Newman, C., Reis, G. B., Rees, J., Reese, C., Silva, L., Seyler, T., Song, M. A., Sosnoff, C., Spitzer, C. R., Tevis, D., Wang, L., Watson, C., Wewers, M. D., Xia, B., Tremeau-Bravard, A., Wang, G., & Lung Injury Response Laboratory Working Group. (2019). Evaluation of bronchoalveolar lavage fluid from patients in an outbreak of e-cigarette, or vaping, product use–associated lung injury—10 states, August–October 2019. MMWR. Morbidity and Mortality Weekly Report, 68, 1040-1041.

Ghinai, I., Pray, I. W., Navon, L., O’Laughlin, K., Saathoff-Huber, L., Hoots, B., Kimball, A., Tenforde, M. W., Chevinsky, J. R., Layer, M., Ezike, N. O., Meiman, J., Layden, J. E., & Mikosz, C. A. (2020). Risk factors for e-cigarette, or vaping, product use–associated lung injury (EVALI) among adults who use e-cigarette, or vaping, products—Illinois, July–October 2019. MMWR. Morbidity and Mortality Weekly Report, 68, 1034-1039.

Madison, M. C., Landers, C. T., Gu, B. H., Chang, C. Y., Tung, H. Y., You, R., Hong, M. J., Baghaei, N., Song, L. Z., Porter, P., Putluri, N., Salas, R., Gilbert, B. E., Levental, I., Campen, M. J., Corry, D. B., & Kheradmand, F. (2019). Pulmonary toxicity and the pathophysiology of electronic cigarette, or vaping product, use associated lung injury. Frontiers in Pharmacology, 10, 1619.

Kalininskiy, A., Bach, C. T., Nacca, N. E., Ginsberg, G., Marraffa, J., Navarette, K. A., McGraw, M. D., & Croft, D. P. (2019). E-cigarette, or vaping, product use associated lung injury (EVALI): case series and diagnostic approach. The Lancet Respiratory Medicine, 7(12), 1017-1026.

Krishnasamy, V. P., Hallowell, B. D., Ko, J. Y., Board, A., Hartnett, K. P., Salvatore, P. P., Danielson, M., Kite-Powell, A., Twentyman, E., Kim, L., Cyrus, A., Wallace, M., Melstrom, P., Haag, B. L., King, B. A., Briss, P. A., Mikosz, C. A., & Rose, D. A. (2020). Update: characteristics of a nationwide outbreak of e-cigarette, or vaping, product use–associated lung injury—United States, August 2019–January 2020. MMWR. Morbidity and Mortality Weekly Report, 69, 90-94.

Proposal for the Introduction of a Separate ICD-10 Category for Interactive Video Addiction Disorders

Executive Summary

This proposal advocates for the creation of a dedicated ICD-10 category for Interactive Video Addiction Disorders, encompassing a spectrum of disorders arising from the compulsive use of various digital media forms. Despite the increasing prevalence and significant impact on mental and physical health, these disorders are not adequately categorized within the current ICD-10 framework. A separate category would facilitate precise diagnosis, inform treatment strategies, and spur further research into these emerging disorders.

Background and Rationale

Interactive Video Addiction Disorders, including gaming, pornography, social media, and other digital media addictions, have emerged as significant behavioral health concerns. These disorders share common mechanisms such as reward pathways activation, escapism, and the compulsion loop, contributing to their addictive potential. The prevalence of these disorders varies globally, with estimates suggesting a significant impact across different populations and age groups, including children and adolescents. The current ICD-10 classification lacks specific codes to adequately represent these disorders, hindering effective clinical management and research efforts.

Proposal for New ICD-10 Category and Sub-Categories

· New ICD-10 Category: “Addiction to Interactive Video and Digital Media” (AIVDM)

· Sub-Categories:

o AIVDM1: Interactive Video Gaming Disorder

o AIVDM2: Interactive Pornography Addiction

o AIVDM3: Interactive Social Media Disorder

o AIVDM4: Online Dating Addiction

o AIVDM5: Smartphone Addiction

o AIVDM6: Internet Addiction

o AIVDM7: Streaming and Video Content Addiction

o AIVDM8: Online Shopping Addiction

Justification and Benefits

1. Enhanced Clinical Recognition: Specific codes will enable healthcare providers to accurately diagnose and differentiate between various forms of digital media addictions, leading to more tailored and effective treatment plans.

2. Facilitated Research: Dedicated ICD-10 codes will promote research into the prevalence, risk factors, and treatment outcomes of these disorders, contributing to the development of evidence-based interventions.

3. Public Health Strategy: Standardized classification will inform public health initiatives aimed at addressing and mitigating the impact of digital media addiction on society, particularly among vulnerable populations such as youth.

4. Global Consistency: Aligning with the proposed ICD-11 classification for Interactive Digital Media Use Disorder, these codes would ensure consistency in diagnostic criteria and reporting standards worldwide.

Conclusion

The introduction of a separate ICD-10 category for Interactive Video Addiction Disorders is imperative to address the growing challenge posed by the addictive use of digital media. By recognizing these disorders with specific codes, the medical community can better understand, treat, and prevent the adverse effects associated with digital media addiction. We urge the adoption of this proposal to enhance patient care, support research, and guide public health strategies in the digital age.

References

Koepp, M. J., Gunn, R. N., Lawrence, A. D., Cunningham, V. J., Dagher, A., Jones, T., Brooks, D. J., Bench, C. J., & Grasby, P. M. (1998). Evidence for striatal dopamine release during a video game. Nature 393(6682), 266–268. https://doi.org/10.1038/30498 

Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and Emotion 30(4), 344–360. https://doi.org/10.1007/s11031-006-9051-8 

Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., & Khoo, A. (2011). Pathological video game use among youths: A two-year longitudinal study. Pediatrics 127(2). https://doi.org/10.1542/peds.2010-1353 

Griffiths, M. (2000). Excessive internet use: Implications for sexual behavior. CyberPsychology & Behavior 3(4), 537–552. https://doi.org/10.1089/109493100420151 

Kuss, D., & Griffiths, M. (2017). Social Networking sites and addiction: Ten lessons learned. International Journal of Environmental Research and Public Health 14(3), 311. https://doi.org/10.3390/ijerph14030311 

Lin, Y.-H., Chang, L.-R., Lee, Y.-H., Tseng, H.-W., Kuo, T. B., & Chen, S.-H. (2014). Development and validation of the Smartphone Addiction Inventory (SPAI). PLoS ONE, 9(6). https://doi.org/10.1371/journal.pone.0098312 

Proposal for the Creation of New ICD-10 Codes for Disorders Caused by Virtual Reality (VR)

Executive Summary

This proposal calls for the establishment of specific ICD-10 codes to categorize health disorders directly related to the use of Virtual Reality (VR) technology. As VR becomes increasingly prevalent in entertainment, education, and therapeutic settings, recognizing and coding VR-related disorders is critical for effective diagnosis, treatment, and prevention. These new codes would enable healthcare providers to accurately document and treat conditions arising from VR use, facilitating research and informing safer VR practices.

Background

Virtual Reality technology immerses users in digital environments, offering novel experiences and interactions. However, prolonged or improper VR use can lead to a range of physical and psychological health issues, including but not limited to motion sickness (VR-induced nausea), eye strain, headaches, and disorientation, as well as potential long-term effects on mental health and spatial awareness. Despite growing awareness of these issues, the current ICD-10 lacks specific codes to report health conditions associated with VR, hindering systematic healthcare responses.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes under a category specifically designated for disorders caused by virtual reality. These codes would classify health issues based on their nature and severity. Proposed codes might include:

· VR01: Virtual Reality-Induced Motion Sickness

· VR02: Virtual Reality-Induced Visual Fatigue

· VR03: Virtual Reality-Induced Postural Instability

· VR04: Psychological Effects Induced by Virtual Reality

1. Clinical Guidelines for Diagnosis and Management: Develop comprehensive guidelines that utilize the new codes, providing healthcare providers with criteria for diagnosing and managing VR-related health issues. These guidelines should emphasize early detection, appropriate therapeutic interventions, and guidelines for safer VR use.

2. Educational Initiatives: Implement education and awareness programs for healthcare professionals, patients, and the general public to increase understanding of the potential health impacts of VR. Highlight preventive measures and best practices for minimizing adverse effects.

3. Research and Surveillance: Encourage research into the prevalence, mechanisms, and long-term effects of disorders caused by VR. Use the new ICD-10 codes to standardize data collection, supporting epidemiological studies and the development of evidence-based guidelines for VR use.

Benefits

· Enhanced Healthcare Delivery: Specific ICD-10 codes for VR-related disorders will enable more accurate diagnosis and effective management, improving patient outcomes.

· Informed VR Usage: Increased awareness and understanding of the health risks associated with VR can lead to safer usage practices among the public and professionals, reducing the incidence of VR-related health issues.

· Advancement in VR Research: Standardized codes will facilitate research into VR's health impacts, guiding the development of safer technologies and therapeutic applications.

Conclusion

The creation of ICD-10 codes for disorders caused by virtual reality is an essential step toward addressing the health challenges posed by emerging technologies. By providing a structured approach to documenting and managing VR-related health issues, these codes will enhance patient care, support research, and promote the development of safer VR practices. We strongly advocate for the adoption of these proposed codes to better understand and mitigate the health risks associated with virtual reality technology.

References

Felnhofer, A., Kothgassner, O. D., Schmidt, M., Heinzle, A. K., Beutl, L., Hlavacs, H., & Kryspin-Exner, I. (2016). Transforming experience: The potential of augmented reality and virtual reality for enhancing personal and clinical change. Frontiers in Psychiatry 7, 164.

Freeman, D., Reeve, S., Robinson, A., Ehlers, A., Clark, D., Spanlang, B., & Slater, M. (2007). Virtual reality in the assessment, understanding, and treatment of mental health disorders. Psychological Medicine 37(10), 1427-1438.

Gorini, A., Gaggioli, A., Vigna, C., & Riva, G. (2008). Virtual reality in the treatment of generalized anxiety disorders. Studies in Health Technology and Informatics 142, 253-258.

Maples-Keller, J. L., Bunnell, B. E., Kim, S. J., & Rothbaum, B. O. (2017). The use of virtual reality technology in the treatment of anxiety and other psychiatric disorders. Harvard Review of Psychiatry 25(3), 103-113.

Valmaggia, L. R., Latif, L., Kempton, M. J., & Rus-Calafell, M. (2016). Virtual reality in the psychological treatment for mental health problems: A systematic review of recent evidence. Psychiatry Research 236, 189-195.

Proposal for the Creation of New ICD-10 Codes for Medication-Induced Weight Gain or Metabolic Disorders

Executive Summary

This proposal advocates for the establishment of specific ICD-10 codes to categorize medication-induced weight gain and metabolic disorders. Recognizing these conditions with dedicated codes is crucial for accurate diagnosis, monitoring, and management, enhancing patient care, and facilitating research into the prevention and treatment of these adverse effects.

Background

Medication-induced weight gain and metabolic disorders are significant concerns, affecting patients' long-term health and quality of life. These conditions are associated with a wide range of medications, including antipsychotics, antidepressants, antiepileptics, and corticosteroids. Current ICD-10 codes do not adequately capture the nuance of weight gain and metabolic changes directly attributed to medication use, complicating clinical management and epidemiological tracking of these conditions.

Proposal Details

1. Creation of ICD-10 Codes: We propose the introduction of new ICD-10 codes within a distinct category for medication-induced weight gain and metabolic disorders. These codes would allow for the differentiation of conditions based on the type of medication and the specific metabolic disorder induced. Proposed codes could include:

· MW01: Weight Gain Induced by Antipsychotics

· MW02: Metabolic Syndrome Induced by Corticosteroids

· MW03: Hyperglycemia Induced by Antipsychotics

· MW04: Dyslipidemia Induced by Antiretroviral Medications

1. Clinical Guidelines for Diagnosis and Management: Develop and disseminate clinical guidelines that utilize the new codes, providing healthcare providers with clear criteria for diagnosis, reporting, and management strategies. These guidelines should include recommendations for monitoring metabolic parameters and managing weight gain in patients on long-term medication therapy.

2. Educational Initiatives: Implement education and awareness programs targeting healthcare professionals and patients to increase awareness about the risks of medication-induced weight gain and metabolic disorders. Education should focus on preventive strategies, early detection, and management options.

3. Research and Surveillance: Encourage research into the mechanisms, prevalence, and treatment of medication-induced weight gain and metabolic disorders. Use the new ICD-10 codes to facilitate consistent data collection and analysis, supporting epidemiological studies and clinical trials aimed at finding effective interventions.

Benefits

· Improved Patient Care: The introduction of specific ICD-10 codes will enable more accurate diagnosis and tailored management of medication-induced weight gain and metabolic disorders, potentially reducing the risk of long-term health complications.

· Enhanced Data Collection and Research: Specific codes will facilitate the collection of standardized data, supporting research into the causes and treatment of these conditions and enabling healthcare providers to make informed prescribing decisions.

· Informed Public Health Strategies: Better understanding and tracking of medication-induced metabolic disorders will inform public health strategies aimed at mitigating these adverse effects, improving patient education, and guiding policy on medication use.

Conclusion

The creation of ICD-10 codes for medication-induced weight gain and metabolic disorders is an essential step in recognizing and addressing these significant side effects of medication therapy. By providing a framework for accurate diagnosis and reporting, these codes will enhance patient management, support research, and inform public health interventions. We strongly advocate for the adoption of these proposed codes to improve healthcare outcomes for patients experiencing these medication-induced conditions.

References

Barenbaum, S. R., Kumar, R. B., & Aronne, L. J. (2023). Management of medication-induced weight gain. Gastroenterology Clinics of North America 52(4), 751–760. https://doi.org/10.1016/j.gtc.2023.08.006 

Casey, D. E., Haupt, D. W., Newcomer, J. W., Henderson, D. C., Sernyak, M. J., Davidson, M., Lindenmayer, J. P., Manoukian, S. V., Banerji, M. A., Lebovitz, H. E., & Hennekens, C. H. (2004). Antipsychotic-induced weight gain and metabolic abnormalities: implications for increased mortality in patients with schizophrenia. The Journal of clinical psychiatry 65 Suppl 7, 4–20.

Maayan, L., & Correll, C. U. (2011). Weight gain and metabolic risks associated with antipsychotic medications in children and adolescents. Journal of Child and Adolescent Psychopharmacology 21(6), 517–535. https://doi.org/10.1089/cap.2011.0015 

Menon, V., & Praharaj, S. K. (2021). Management of drug-induced weight gain in persons receiving psychotropic drugs. Indian Journal of Private Psychiatry 15(1), 10–16. https://doi.org/10.5005/jp-journals-10067-0071 

Tschoner, A., Engl, J., Laimer, M., Kaser, S., Rettenbacher, M., Fleischhacker, W. W., Patsch, J. R., & Ebenbichler, C. F. (2007). Metabolic side effects of antipsychotic medication. International Journal of Clinical Practice 61(8), 1356–1370. https://doi.org/10.1111/j.1742-1241.2007.01416.x 

Changes in ICD 10 or 11 Should be Submitted to the CDC Before March , 2024

 This link describes the process:

Process for Requesting New/Revised ICD-10-PCS Procedure Codes | CMS

A coordinator will help to put the proposal into the proper format. A meeting to review the proposal will be scheduled. The author may speak to present the proposal, or may choose to just answer questions. In the absense of strong, evidence based objections, the proposal is likely to be adopted. Your proposal cannot be any more edgy than these. 

https://www.healthcaredive.com/news/the-16-most-absurd-icd-10-codes/285737/

 Foot Surgery Shopping List

An assistant and caregiver for several weeks

Living space with all rooms on one floor, bedroom, bathroom, workspace

Garbage bags to cover foot dripping blood and serum the first few days

Knee Scooter for single floor living plus clip on cup holder

4 X 4 dressing silicone pad for the knee to address pressure sores from the scooter

Cane with a single prong, not 4 prongs for stairs

Walker for a single step

Grabber Reacher, second one to pick up the first from the floor

Ace bandages for when visiting nurses have none

Thermometer to catch a fever from a wound infection

Bathtub transfer chair if have a big bathroom. Alternative: Bidet feature on toilet and sponge baths. 

Aspirin 81 mg likely, twice a day to lessen  clotting and a pulmonary embolus 

Hard boiled Eggs are nutritious but have zero bulk to avoid a bowel movement Day 1 or 2 post-op. 

Imodium to avoid a bowel movement and its cleanup day one or two post op

Tylenol 500 mg, likely 2 twice or three times a day, do not forget to count the Tylenol in the pain med toward the 3000 mg daily limit for most people.

Alternate with Naprosyn 220 mg 2 tablets twice a day

Urinal to save trips to the toilet all day, to save water, to prevent falls 

Pulse Oximeter in case of a pulmonary embolism

Leg cast sock cover for your toes sticking out 

The Puritanical Jihad or Crusade Against Benzodiazepines

 https://www.doximity.com/articles/74e47da9-aed2-4b57-a731-a69e6e6a8181

Both jihadists and crusaders were just just organized crime gangs with bogus religious masking ideologies. 

My Comment: This article is fact free series of ipse dixits by wokes. I doubt any of these geniuses suffers from anxiety. The article is part of the puritinical jihad against benzos. Benzos are the safest psychiatric drugs of all, including buspirone and anti-depressnats. This jihad is driven by rent seeking people who want to enrich themselves from endless but ineffective talk therapy, versus an effective pill for 25 cents. The article disrespects the experience based judgment of the doctors who prescribe them to tens of millions of people. Where would these people go for treatment when off benzos? What are the risks of anti-histamines, of clonidine, of sedating anti-depressants, of neuroleptic tranquilizers? What is the wait for 92 million people to see cognitive behavior therapists?

When WSJ publishes woke, it should present a counterpoint article for clinicians to make an informed judgement about the matter.

Oh, Heck, To the No. Euthanasia for Fatigue

 28-year-old Lauren Hoeve died by euthanasia – to a degree, I understand her pain (msn.com)

There is no list of remedies for treatment resistant depression, for the differential diagnosis of fatigue (500 conditions long, divided by organ systems), for infectious diseases. Say, all that was negative. There is no treatment for treatment resistant depression, including a dose of ketamine to end this in 45 minutes. Failing all that, send to the Mayo Clinic for their work up Special of the 500 causes of fatigue.