Health Care Decisions Research Articles

Ethical dilemmas concerning orthodontic treatment among orthodontists in a sample from Saudi Arabia: a pilot study

BackgroundEthics is based on moral principles that should be the foundation for every healthcare decision, however, ethical concepts can often be challenging to define in specific clinical scenarios. There are several instances where a practising clinician often finds it difficult to make a proper decision despite maintaining integrity and professionalism. The objective of the present study was to explore the ethical dilemma faced by orthodontists practicing in Saudi Arabia concerning orthodontic treatment.MethodThis was a questionnaire-based cross-sectional study that was adapted from the scenarios of ethical dilemmas presented by Jerrold in 1998. Ten orthodontists from each province of Saudi Arabia were requested to participate in this study and the questionnaire were sent through email and their responses were analysed.ResultsA total of 37 responses were obtained (out of 130) with a response rate of 28.46%. Among them 23 were female and 14 were male. Most participants belonged to the age group 30–39 years and most of them have clinical experience of more than 5 years. There was a wide variation in the responses among the participants in all the scenarios presented. The median likelihood of getting similar scenarios in their clinical practice in Saudi Arabia ranged from 3 to 3.5.ConclusionThere was a wide variation in the opinion among the practising orthodontists in Saudi Arabia in the scenarios presented. The presented scenarios are less likely to be perceived in the local context and some new situations of ethical dilemmas are identified.

Advancing Principled Pharmacoepidemiologic Research to Support Regulatory and Healthcare Decision Making: The Era of Real-World Evidence.

A compilation of factors over the past decade-including the availability of increasingly large and rich healthcare datasets, advanced technologies to extract unstructured information from health records and digital sources, advancement of principled study design and analytic methods to emulate clinical trials, and frameworks to support transparent study conduct-has ushered in a new era of real-world evidence (RWE). This review article describes the evolution of the RWE era, including pharmacoepidemiologic methods designed to support causal inferences regarding treatment effects, the role of regulators and other health authorities in establishing distributed real-world data networks enabling analytics at scale, and the many global guidance documents on principled methods of producing RWE. This article also highlights the growing opportunity for RWE to support decision making by regulators, health technology assessment groups, clinicians, patients, and other stakeholders and provides examples of influential RWE studies. RWE holds promise to address important questions that clinical trials typically do not answer about treatment benefits and risks, and to ultimately impact public health by helping to guide decision making across the healthcare ecosystem.

Decision-making capacity in rehabilitation psychology practice: Historical, contemporary, and future perspectives.

This article will review the historical underpinnings of informed consent and decisional capacity, current practices, and potential evolving future modifications or elaborations of decision-making practices in clinical settings. Ethical and legal foundations for informed consent for health care are reviewed. Contemporary issues with decision making, clinical capacity, and proxy decision making in rehabilitation psychology practice are discussed with a specific focus on health care decision making. As a subspecialist in psychology, a rehabilitation psychologist necessarily seeks to incorporate a working knowledge of its historical anchors while simultaneously seeking changes sensitive to honoring and advocating for the rights of the individuals whom they serve. The contributions of the disability rights movement have been immeasurable in ensuring that those most impacted with potential challenges to their right to self-determine their choices across a wide range of psycholegal issues are safeguarded. As rehabilitation psychologists, we must remain steadfast stewards and constructive supporters of those under our care through protecting and advocating for their rights. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Decomposition and comparative analysis of urban-rural disparity in attitude towards advance care planning among Chinese adults: A nationwide study

BackgroundExamining urban-rural disparity in Chinese adults’ advance care planning (ACP) attitudes is crucial for healthcare decision-making. A comprehensive understanding of contributing factors, especially through decomposition and comparative analysis, remains limited.MethodsData were derived from Psychology and Behavior Investigation of Chinese Residents (PBICR) including 19,738 participants, representative of Chinese adults. We constructed multivariate linear regression models to investigate the primary factors influencing the attitudes toward ACP among Chinese adults. Additionally, we employed Blinder-Oaxaca decomposition to analyze the factors contributing to the urban-rural disparities in ACP attitudes among Chinese adults and their respective contributions. The STROBE checklist was used in reporting this study.ResultsThe mean acceptance scores for ACP were 64.83 (standard deviation (SD) 25.83) among urban Chinese adults, significantly surpassing the scores observed in rural areas, which were 61.71 (SD 25.57) (p < 0.001). Blinder-Oaxaca decomposition analysis indicates that 98% of the urban-rural disparity in ACP attitudes among adults can be explained. This disparity is primarily associated with differences in household per capita monthly income (31.55%), health literacy (31.25%), education level (18.71%), age (-15.12%), family health (13.95%), perceived social support (10.48%), and self-efficacy (7.46%).ConclusionsThe findings suggest policymakers should enhance ACP education in rural areas to reduce disparities. Clinically, tailored ACP discussions and integration into routine care can improve acceptance, particularly in underserved regions.

Innovative Research on Physical Data Management of Football Players Under the Background of Smart Medical Treatment

With the intensification of the competition for public medical resources and the rapid development of smart medical technology, the demand for in-depth analysis of athletes’ basic information and decision support is growing day by day. However, the practice of applying smart medicine to athletes’ physical information management is still relatively limited. This paper aims to explore how to use smart medical decision technology to build an integrated athlete physical information management and decision support platform. Taking football players as the research object, this paper integrates data mining technology into a smart medical decision-making model, to achieve accurate analysis and effective management of athletes’ physical fitness information. The core of the research is to develop a smart healthcare decision model that can identify key information and patterns on the platform through data mining technology. In the selection of the decision algorithm, this paper adopts cluster analysis and association rule mining algorithms, which can deeply dig into the potential rules and correlations in the data. Through the application of an algorithm, we can accurately evaluate the physical condition of football players, and provide scientific guidance and suggestions for their subsequent physical training. The algorithm in this study is not only innovative in theory, but also shows good adaptability and effectiveness in practical application.

Guidance for an Effective Approach to Integrated Evidence Planning in a Dynamic World.

The value of a medicine is defined by its impact on patients, caregivers, health system, and society. A pharmaceutical company will generate evidence to demonstrate this value in various studies, including randomized clinical trials, non-interventional and observational studies, real-world data analyses, modeling, and simulation. The quality and strength of the evidence supporting a medicine's effectiveness, safety and product quality will drive decisions by healthcare system stakeholders for marketing authorization (regulatory authorities). Additional evidence of comparative clinical, humanistic, economic, and societal value of the medicine will be critical for reimbursement coverage by HTA (health technology assessment) bodies and payers, guideline inclusion by clinical societies, and ultimately the treatment decision between a patient and their healthcare provider (HCP). The purpose of this article is to provide practical guidance for an effective approach to evidence planning for pharmaceutical companies. In the first section, we give a brief overview of the requirements for evidence generation from the perspectives of healthcare system decision makers, key functions involved in evidence generation within a pharmaceutical company, and different archetypes of products. We then discuss how a company can implement effective integrated evidence planning across the lifecycle of a product. We also review how requirements are likely to evolve given recent changes in major healthcare system regulations, such as Centers for Medicare & Medicaid Services (CMS) drug price negotiations in the US and EU HTA Regulation (HTAR) in Europe, and finally provide some practical recommendations of how to start implementing a new integrated evidence approach.

Redefining intelligence: collaborative tinkering of healthcare professionals and algorithms as hybrid entity in public healthcare decision-making

Redefining intelligence: collaborative tinkering of healthcare professionals and algorithms as hybrid entity in public healthcare decision-making

Parental and Medical Classification of Neurodevelopment in Children Born Preterm.

The likelihood and severity of neurodevelopmental impairment (NDI) affects critical health care decisions. NDI definitions were developed without parental perspectives. We investigated the agreement between parental vs medical classification of NDI among children born preterm. In this multicenter study, parents of children born preterm (<29weeks) evaluated at 18 to 21months corrected age (CA) were asked whether they considered their child as developing normally, having mild/moderate impairment, or having severe impairment. Medical categorization was based on hearing, vision, cerebral palsy status, and Bayley Scales of Infant and Toddler Development Third Edition (Bayley-III) scores. Agreement was analyzed using Cohen's weighted κ. Discrepancies in categorization by NDI components and parental demographics were examined using the Pearson χ2 test, Fisher exact test, or Wilcoxon signed-rank test. Children (n = 1098, gestational age 26.1 ± 1.5weeks, birthweight 919 ± 247g) were evaluated at 19.6 ± 2.6months CA at 13 clinics. Agreement between parental and medical NDI classification was poor (κ = 0.30; 95% CI: 0.26-0.35). Parents described their child's development as normal or less impaired. Only 12% of parents of children classified as having a severe NDI according to the medical definition agreed. There were significant disagreements between classification for children based on Bayley-III cognitive, language, and motor scores but not for cerebral palsy. Discrepancies varied by parental education and ethnicity but not by single caregiver status. Parent perception of NDI differs from medical categorization, creating a risk of miscommunication. This indicates an overestimation of the impact of disability by clinicians, which may affect life-and-death decisions. Parental perspectives should be considered when reporting and discussing neurodevelopmental outcomes.

Prevalence and determinants of full vaccination coverage according to the national schedule among children aged 12–35 months in Ghana

Universal immunization of children against common vaccine-preventable diseases is crucial in reducing infant and child morbidity and mortality. Assessing the vaccination coverage is a key step to improve utilization and coverage of vaccines for under-five children. Accordingly, vaccination coverage according to the national schedule assesses the vaccination coverage of children aged 12–35 months. However, there is a scarcity of information on the full vaccination coverage according to the national schedule and its determinants in Ghana. Therefore, this study aimed to assess the prevalence and predictors of vaccination coverage according to the national schedule among children aged 12–35 months in Ghana. A cross-sectional study design using the most recent demographic and health survey data from the Ghana Demographic and Health Survey was used. We included a total weighted sample of 1,823 children aged 12–35 months in the five years preceding the survey. We used a multilevel logistic regression model to identify associated factors for vaccination coverage according to the national schedule in Ghana. The adjusted odds ratio at 95% Cl was computed to assess the strength and significance of the association between explanatory and outcome variables. Factors with a p-value of < 0.05 are declared statistically significant. In this study, the full coverage of vaccination according to the national schedule among children aged 12–35 months in Ghana was 56.45% (95% CI 51.77–56.17). Women having an ANC visit were 40% more likely (AOR = 1.40, 95% CI 1.07–1.83), women involved in healthcare decision-making were 35% more likely (AOR = 1.35, 95% CI 1.05–1.75), Women who deliver in a health facility were 1.91 times more likely (AOR = 1.91, 95% CI 1.36–2.66), and communities with high media exposure were 47% more likely (AOR = 1.47, 95% CI 1.06–2.05) to achieve full vaccination coverage as compared to their counterparts. On the other hand, being in the Western (AOR = 0.4, 95% CI 0.18–0.88) and Northern (AOR = 0.33, 95% CI 0.15–0.74) regions decreased the odds of attaining full vaccination coverage according to the national schedule in Ghana. The full vaccination coverage according to the national schedule in Ghana was lower as compared to 90% coverage recommendation by World Health organization, and there is also in-equality among regions. Maternal optimal ANC contact, health facility delivery, women involved in health care decision-making, community media exposure, and region were significantly associated with full vaccination coverage according to the national schedule in Ghana. To improve child immunization coverage, relevant authorities and stakeholders should work together to improve ANC visits, media exposure, facility delivery, and women’s empowerment, and attention should be given to deviant regions.

Predicting Heart Attack Risk Using Machine Learning: A Review

Abstract: Machine learning in the healthcare field involves developing predictive models for early disease detection, such as analyzing patient data and identify individuals at high risk of conditions like heart attacks, diabetes, or cancer. This paper explores the use of machine learning to predict the risk of heart attacks, helping to assess and classify the likelihood of occurrence. The study highlights its potential to improve early detection and support better healthcare decisions

The Impact of Obesity in the UAE: Real-world Physician and Patient Perspectives

Background: Limited evidence exists on the impacts of obesity in the United Arab Emirates (UAE). Real-world evidence is required to support obesity-related healthcare decision-making in the UAE. Materials and Methods: The Adelphi Real World Obesity Disease Specific ProgrammeTM is a multicountry , cross-sectional survey with retrospective data capture including physicians directly involved in chronic weight management and people living with obesity (PwO) presenting to them in a real-world clinical setting. UAE data were collected between April and August 2022. Physicians completed online questionnaires reporting demographics and clinical characteristics for eligible PwO (aged ≥18 years participating in a weight management plan and/or presenting with a body mass index [BMI] ≥30 kg/m2). PwO voluntarily completed questionnaires reporting out-of-pocket costs and patient-reported outcomes: Work Productivity and Activity Impairment Questionnaire (WPAI), Short Form 36 v2 Health Survey (SF-36v2), Jenkins Sleep Evaluation Questionnaire ( JSEQ). Analyses were descriptive. Results: 41 physicians identified 201 PwO; 49% were male and 65% were of Middle Eastern origin. Mean age, BMI, and median time since obesity diagnosis were 39.1 years, 33.7 kg/m2, and 11.5 months, respectively. PwO (n = 84) reported a mean of 7.4% monthly household income spent on medicine for weight and weight-related health conditions. Mean WPAI was 35.3% activity impairment and 37.5% overall work impairment due to obesity. Generally, SF-36v2 scores were &lt;47, indicating impairment, and mean JSEQ score was 3.6. Conclusion: PwO in the UAE had a high level of complications and measurable negative obesity-related impacts. These data may contribute to improving obesity awareness and management in the UAE.

Comprehensive Analysis of Factors Influencing Patients' Preferences and Attitudes toward Dental Treatment Choices.

In recent years, patient preferences and attitudes have become crucial in shaping dental treatment choices and service utilization. Understanding these preferences is crucial for improving service delivery and patient satisfaction. This study aims to comprehensively analyze the factors influencing these preferences, focusing on demographic, socio-economic, and behavioral variables, and the growing role of social media in healthcare decisions. A cross-sectional survey using an online questionnaire was conducted among Indian individuals aged 18 years and above, yielding 231 responses. The data were analyzed using descriptive statistics, Chi-square tests, and ANOVA to assess associations and significant differences among variables. Factor analysis was used to determine factors influencing the selection of dental care services. The findings suggest that younger adults (76.6% aged 18-43 years) and females (65.8%) are more engaged in digital consultations and dental care decisions. Key factors influencing dental care choices include previous experience, painless treatment, and availability. Trust in social media for dental information is low, with 72.7% expressing doubts about its accuracy. Factor analysis identified four key dimensions affecting dental care choices which were grouped as patient-centric dental service quality, external validation and assurance, experience and cost-driven decisions, and professional competence. The study underscores the importance of maintaining high-quality service, effective communication, and leveraging professional referrals and online reviews to enhance patient trust and satisfaction. Despite social media's rising role, direct professional advice remains the preferred source for dental care decisions.

A Socioecological Approach to Support the Transition to Adult Care for Youth With Medical Complexity: Family Perspectives and Recommendations

ABSTRACTIntroductionThe transition from paediatric to adult health care (i.e., ‘health care transition’) poses many challenges for youth with medical complexity (YMC) and their families. YMC need specific approaches to supporting transition, tailored to individual youth and family contexts. In this study, we examine the contextual factors influencing families' transition experiences and describe their recommendations for improving the experience.MethodsWe conducted a qualitative explanatory case study in Ontario, Canada. We completed 21 interviews with 17 participants (11 mothers, 2 fathers, 2 YMC, 2 siblings) from 11 families of YMC. Six YMC (55%) were under 18 years of age (pre‐transfer) and five (45%) were aged 18 years and older (post‐transfer). Analytic approaches included reflexive thematic analysis and directed content analysis.FindingsParticipants described how the interplay of personal and environmental factors impacted their transition experiences. Recommendations for health care providers focused on providing instrumental and psychological support, advocacy and care continuity. Families expressed a need for better access to information and support from primary care providers. System‐level recommendations included streamlining transition processes, improving adult health care services and expanding community supports. A socioecological model is presented to guide health care providers and decision makers in assessing and tackling the challenges faced by YMC and their families during transition.ConclusionFindings highlight the complexity and scope of issues surrounding the transition to adult care for YMC in Ontario, with evidence of major gaps in services across multiple sectors and settings. Ongoing efforts are needed to move evidence into practice and advocate for more equitable and responsive care for YMC during the transition and beyond.Patient or Public ContributionThe research team included two parent co‐researchers with lived experience, who contributed to protocol refinement, funding acquisition, recruitment, findings interpretation and ongoing knowledge translation efforts.

Breast Implant Surgery: The Importance of Informed Health Care Decisions and Outcome Monitoring.

Breast implant surgery is a popular, globally performed, and frequently requested cosmetic and reconstructive surgical procedure. Breast implant surgery can cause implant-associated systemic symptoms and types of implant-associated cancers, so it is vital to monitor patient outcomes. Most patients who undergo breast implant surgery do not experience health problems. However, patients who do experience health problems as a result of breast implant surgery form a unique patient population. When plastic and aesthetic surgeons, nurses, and other healthcare providers are knowledgeable and experienced in recognizing and treating patients with health problems related to breast implant surgery, the health outcomes of this patient population improve. This article aims to promote informed decision-making and increase patient safety by providing information about the health problems associated with breast implant surgery. This article also highlights recent safety announcements and updates from the United States Food and Drug Administration (FDA). Ensuring the safety of patients undergoing breast implant surgery is a responsibility shared by plastic and aesthetic surgeons, nurses, and other healthcare providers; the general medical community; breast implant manufacturers; and the FDA. These entities must collaborate and coordinate as a united group to accomplish this important goal. The nursing profession can contribute to these collaborative efforts by serving as professional liaisons to these entities and advocating for continued collaborative efforts to increase the safety of patients who have undergone breast implant surgery.

The Wittmann-Price Theory of Emancipated Decision-Making in Women's Health Care: An Analysis Based on McEwen.

The use of theories in nursing reflects the discipline's progression toward autonomy and delineates its scope, directly guiding practice, research, education, and administration. This paper analyzes and evaluates the theoretical model for nursing care of women involved in health care decisions-The Wittmann-Price Theory of Emancipated Decision-Making in Women's Health Care-based on McEwen's systematic theory 3-phase evaluation method. Developed through a rigorous process, this theory centers on the concept of emancipation and its associated subconcepts crucial to decision-making in women's health. This included crafting explanatory propositions and incorporating them into a structured theoretical framework. Having been applied and refined in various clinical settings, the theory has improved in applicability and proven effective for guiding nursing care across diverse environments. Furthermore, fostering a flexible environment that enhances personal knowledge significantly contributes to emancipated decision-making, which is closely linked to decision satisfaction.

Surrogate Wars: The "Best Interest Values" Hierarchy & End-of-Life Conflicts with Surrogate Decision-Makers.

Conflicts involving end-of-life care between healthcare providers (HCPs) and surrogate decision-makers (SDMs) have received sustained attention for more than a quarter of a century, with early studies demonstrating a frequency of HCP-SDM conflict in ICUs ranging from 32-78% of all admissions (Abbott et al. 2001; Breen et al. 2001; Studdert et al. 2003; Azoulay et al. 2009). More recent studies not only acknowledge the persistence of clinical conflict in end-of-life care (Leland et al. 2017), but they have begun to focus on the ways in which these conflicts escalate to verbal or physical violence in the ICU (Slack et al. 2023; Bass et al. 2024; Berger et al. 2024; Sjöberg et al. 2024). I will argue that part of the explanation for the persistence-and even escalation-of ICU disputes is the incommensurable value systems held by many conflicting HCPs and SDMs. I will argue that a common value system among HCPs can be understood as a "Best Interest Values" (BIV) hierarchy, which I will argue is irreconcilable with the set of "Life-Continuation Values" (LCV) held by a sizable minority of families in the United States. I argue this values-conflict undergirds many ICU disputes. If I am correct that an incommensurable value system underlies many ICU conflicts, then it is not just ineffectual for HCPs to impose their BIV system on LCV families, but also wrong given the American commitment to values pluralism. I conclude that the way to navigate continuous ICU surrogate wars is for BIV-focused healthcare institutions to engage more constructively with LCV stakeholders.

ChatGPT's Performance in Spinal Metastasis Cases-Can We Discuss Our Complex Cases with ChatGPT?

Background: The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT-4, is transforming healthcare. ChatGPT's potential to assist in decision-making for complex cases, such as spinal metastasis treatment, is promising but widely untested. Especially in cancer patients who develop spinal metastases, precise and personalized treatment is essential. This study examines ChatGPT-4's performance in treatment planning for spinal metastasis cases compared to experienced spine surgeons. Materials and Methods: Five spine metastasis cases were randomly selected from recent literature. Consequently, five spine surgeons and ChatGPT-4 were tasked with providing treatment recommendations for each case in a standardized manner. Responses were analyzed for frequency distribution, agreement, and subjective rater opinions. Results: ChatGPT's treatment recommendations aligned with the majority of human raters in 73% of treatment choices, with moderate to substantial agreement on systemic therapy, pain management, and supportive care. However, ChatGPT's recommendations tended towards generalized statements, with raters noting its generalized answers. Agreement among raters improved in sensitivity analyses excluding ChatGPT, particularly for controversial areas like surgical intervention and palliative care. Conclusions: ChatGPT shows potential in aligning with experienced surgeons on certain treatment aspects of spinal metastasis. However, its generalized approach highlights limitations, suggesting that training with specific clinical guidelines could potentially enhance its utility in complex case management. Further studies are necessary to refine AI applications in personalized healthcare decision-making.

Natural Language Processing (NLP) in Analyzing Electronic Health Records for Better Decision Making

Natural Language Processing (NLP) is transforming healthcare decision-making by extracting valuable insights from Electronic Health Records (EHR). This paper explores the integration of NLP with EHR systems, focusing on its potential to enhance clinical workflows, patient outcomes, and the accuracy of healthcare decision-making. Using advanced NLP techniques, such as BERT and spaCy, the study analyzes both structured and unstructured EHR data to uncover patterns in diagnosis, treatment recommendations, and patient outcomes. The study compares NLP-based analysis with traditional data analysis methods, demonstrating its effectiveness in improving clinical decision support systems. Despite the promising potential, challenges such as data quality, model interpretability, and seamless integration with existing healthcare systems are highlighted. The paper concludes by emphasizing the need for continued advancements in NLP models and real-time data processing, suggesting future research directions to optimize the implementation of NLP in healthcare settings.

Registry as a tool for assessing economic costs of managing pediatric patients with hypertrophic cardiomyopathy

Background. Hypertrophic cardiomyopathy (HCM) is one of the most common form of cardiomyopathy in children, with an estimated annual incidence of 2.9 per 100,000 children. The management of patients with HCM requires high healthcare costs. Registry-based medical research is an important tool in assessing health care decision making. Objective. To analyze the costs of the state for the management of pediatric HCM based on the data of the pediatric patient registry. Materials and methods. The study was performed on the basis of the Department of Pediatric Cardiology and Medical Rehabilitation of the Almazov National Medical Research Centre. Currently, the electronic database includes information on 159 children with HCM, including 52 (34 %) girls. The mean age of onset of HCM was 5 years [0; 11], and 68 (44.4 %) children had the onset of myocardial hypertrophy before the age of 1 year. Medical costs included direct medical costs of drug therapy, surgical treatments (implantation of a cardioverter-defibrillator and myectomy) and hospitalization, and indirect costs which included the costs of family caregiving; social benefits due to disability, and death impact on the gross domestic product. Results. The total economic impact of HCM in the context of government spending, is RUB 107.8 million, including medical costs of RUB 27.96 million, direct nonmedical costs of RUB 13.17 million, and indirect costs of RUB 66.7 million. Indirect costs accounted for the lion’s share (61.8 %) of economic impact. Direct medical costs were 26 % of economic impact. The average impact of family caregiving accounted to RUB 11,263.89, and total value were RUB 1.04 million. Conclusion. The intermediate results of our study allow to estimate the economic impact of pediatric HCM to the state. Optimization of financial resource use will help reduce the economic impact on the state to the healthcare sector in the future.

Incidence and Prevalence of Alzheimer's Disease in Medicare Beneficiaries.

The availability of anti-amyloid therapy for mild cognitive impairment (MCI) due to Alzheimer's disease and mild Alzheimer's dementia (AD) has underscored the need for realistic estimates of the population with AD/MCI within the healthcare system to assure adequate preparedness. We hypothesize that administrative databases can provide real-world epidemiologic estimates reflecting the population with diagnosed (known) MCI and AD. This study was conducted to estimate diagnostic incidence and prevalence of AD and all-cause MCI among the Medicare fee-for-service (FFS) and Medicare Advantage (MA) beneficiaries in the United States. This was a retrospective analysis of Medicare beneficiaries (aged 65 and older) with identified diagnoses of AD/MCI based on ≥2 diagnostic codes ≥30 days apart. Incidence/prevalence estimates were reported per 10,000 person-years. In FFS, AD incidence (2008-2018) decreased (138 to 104); MCI incidence increased (8 to 47), but the sum (MCI+AD) was relatively stable (146 to 151). Prevalence (2008-2017) increased for AD (318 to 354), and MCI (13 to 99). In MA (2016) epidemiological estimates were consistent with FFS. In 2017, older age, female sex and the Northeastern region were consistently associated with higher AD/MCI prevalence among FFS beneficiaries. In FFS, AD/MCI diagnostic prevalence increased over 10 years, especially for MCI; prevalence estimates in MA (2016) were comparable. Diagnostic prevalence in 2016 (FFS+MA) was 3.4% for AD and 0.85% for MCI. Our findings address the reality of Alzheimer's disease in clinical practice in the United States that is confronted by healthcare professionals, payors, healthcare decision-makers, patients, and caregivers, and may offer a realistic gauge for patient triage for treatment, healthcare resource allocation, and health-systems' operational prioritization. With the availability of anti-amyloid treatments, we anticipate that the population with diagnosed MCI/AD within the Medicare database may rise over time; therefore, periodic updates of incidence/prevalence estimates may provide support for timely healthcare decision-making.