Subject(s)
Alcohol Drinking , COVID-19 , Pandemics , Humans , Alcohol Drinking/epidemiology , Alcohol Drinking/mortality , Alcohol Drinking/psychology , Alcohol Drinking/trends , Alcoholism/complications , Alcoholism/epidemiology , Alcoholism/mortality , Alcoholism/psychology , COVID-19/epidemiology , COVID-19/mortality , Pandemics/statistics & numerical data , United States/epidemiology , Binge Drinking/epidemiology , Binge Drinking/mortality , Binge Drinking/psychology , Binge Drinking/trends , Comorbidity/trends , Accidents, Traffic/mortality , Accidents, Traffic/statistics & numerical data , Suicide/psychology , Suicide/statistics & numerical data , Suicide/trends , Chronic Disease/epidemiology , Chronic Disease/mortality , Chronic Disease/psychology , Chronic Disease/trends , Male , Female , Health Services Accessibility/statistics & numerical dataABSTRACT
Introducción y objetivos: La condición crónica compleja (CCC) es una realidad cada vez más prevalente en pediatría. Sin embargo, padecer una CCC no supone necesariamente ser un paciente crónico complejo (PCC). Desde esta perspectiva, nos propusimos el desarrollo de un instrumento (Escala PedCom) que facilitase la identificación del PCC. Material y métodos: Inicialmente se definieron aspectos generales para la clasificación de un paciente como PCC. Posteriormente se desarrollaron los ítems de la escala puntuándolos de 0,5 a 4 puntos. Se realizó análisis factorial confirmatorio (AFC) y se estudió la consistencia interna mediante alfa de Cronbach. La concordancia se evaluó mediante estudio intra- e interobservador. El gold standard fue la clasificación realizada por 2 evaluadores tras valoración de la historia clínica del paciente. El punto de corte para considerar al paciente como PCC se estableció mediante curva ROC. Resultados: La versión inicial incluyó 43 ítems con índice de validez de contenido global (IVC) de 0,94. Para el estudio se incluyeron 180 pacientes. Tras el AFC se eliminó un ítem, por lo que la versión final consta de 42 ítems con IVC de 0,95. El valor alfa de Cronbach fue 0,723. El índice de correlación intraclase del análisis test-retest fue de 0,998 y 0,996 para el estudio interobservador. El punto de corte para considerar a un paciente como PCC se estableció en 6,5 puntos, con el que se obtuvo una sensibilidad del 98% y especificidad del 94%. Conclusiones: La Escala PedCom es una herramienta de fácil uso enfocada a la identificación del PCC. En nuestra muestra, presentó adecuada consistencia interna y niveles adecuados de concordancia intra- e interobservador; con buenos resultados de sensibilidad y especificidad para la identificación del PCC. (AU)
Introduction and objectives: The complex chronic condition (CCC) is an increasingly prevalent reality in pediatrics. However, having a CCC does not necessarily mean being a complex chronic patient (CCP). From this perspective, we developed an instrument (PedCom Scale) that would facilitate the identification of the PCC. Material and methods: Initially, general aspects for the classification of patients as CCP were defined. Subsequently, the items of the scale were developed, scoring them from 0.5 to 4 points. We performed a confirmatory factor analysis (CFA) and the internal consistency was studied using alpha-Cronbach. Concordance was evaluated by intra- and inter-observer study. The gold standard was the classification performed by two evaluators after assessing the patient's medical history. The cut-off point for considering the patient as a CCP was established using the ROC curve. Results: The initial version included 43 items with a global content validity index (CVI) of 0.94. A total of 180 patients were included. After the CFA, one item was eliminated, so the final version consists of 42 items with an CVI of 0.95. The alpha-Cronbach value was 0.723. The intraclass correlation coefficient of the testretest analysis was 0.998 and 0.996 for the inter-observer study. The cut-off point for considering a patient as a CCP was established at 6.5 points, with these results we obtained a sensitivity of 98% and specificity of 94%. Conclusions: The PedCom Scale is an easy-to-use tool focused on the identification of the CCP. In our sample, it presented satisfactory levels of internal consistency and adequate levels of intra- and inter-observer agreement, with good sensitivity and specificity for the identification of the PCC. (AU)
Subject(s)
Humans , Infant, Newborn , Infant , Child, Preschool , Child , Adolescent , Chronic Disease/classification , Chronic Disease/trends , Surveys and Questionnaires , Factor Analysis, StatisticalABSTRACT
BACKGROUND: Although many children with medical complexity (CMC) use home health care (HHC), little is known about all pediatric HHC utilizers. Our objective was to assess characteristics of pediatric HHC recipients, providers, and payments. METHODS: We conducted a retrospective analysis of 5 209 525 children age 0-to-17 years enrolled Medicaid in the 2016 IBM Watson MarketScan Medicaid Database. HHC utilizers had ≥ 1 HHC claim. Healthcare Common Procedure Coding System (HCPCS) and Current Procedural Terminology (CPT) codes were reviewed to codify provider types when possible: registered nurse (RN), licensed practical nurse (LPN), home health aide (HHA), certified nursing assistant (CNA), or companion/personal attendant. Enrollee clinical characteristics, HHC provider type, and payments were assessed. Chronic conditions were evaluated with Agency for Healthcare Research and Quality's Chronic Condition Indicators and Feudtner's Complex Chronic Conditions. RESULTS: Of the 0.8% of children who used HHC, 43.8% were age <1 year, 25% had no chronic condition, 38.6% had a noncomplex chronic condition, 21.5% had a complex chronic condition without technology assistance, and 15.5% had technology assistance (eg, tracheostomy). HHC for children with technology assistance accounted for 72.6% of all HHC spending. Forty-five percent of HHC utilizers received RN/LPN-level care, 7.9% companion/personal attendant care, 5.9% HHA/CNA-level care, and 36% received care from an unspecified provider. For children with technology assistance, the majority (77.2%) received RN/LPN care, 17.5% companion/personal assistant care, and 13.8% HHA/CNA care. CONCLUSIONS: Children using HHC are a heterogeneous population who receive it from a variety of providers. Future investigations should explore the role of nonnurse caregivers, particularly with CMC.
Subject(s)
Delivery of Health Care/trends , Home Care Services/trends , Medicaid/trends , Patient Acceptance of Health Care , Adolescent , Child , Child, Preschool , Chronic Disease/epidemiology , Chronic Disease/trends , Delivery of Health Care/methods , Female , Humans , Infant , Infant, Newborn , Male , Retrospective Studies , United States/epidemiologyABSTRACT
No disponible
Subject(s)
Humans , Child , Chronic Disease/trends , Disabled Persons , Periodicals as TopicABSTRACT
Multimorbidity, frequently associated with aging, can be operationally defined as the presence of two or more chronic conditions. Predicting the likelihood of a patient with multimorbidity to develop a further particular disease in the future is one of the key challenges in multimorbidity research. In this paper we are using a network-based approach to analyze multimorbidity data and develop methods for predicting diseases that a patient is likely to develop. The multimorbidity data is represented using a temporal bipartite network whose nodes represent patients and diseases and a link between these nodes indicates that the patient has been diagnosed with the disease. Disease prediction then is reduced to a problem of predicting those missing links in the network that are likely to appear in the future. We develop a novel link prediction method for static bipartite network and validate the performance of the method on benchmark datasets. By using a probabilistic framework, we then report on the development of a method for predicting future links in the network, where links are labelled with a time-stamp. We apply the proposed method to three different multimorbidity datasets and report its performance measured by different performance metrics including AUC, Precision, Recall, and F-Score.
Subject(s)
Chronic Disease/trends , Multimorbidity/trends , Forecasting/methods , Humans , ProbabilityABSTRACT
Adolescence can be a particularly challenging period for individuals with a chronic illness. To help the specialized healthcare teams, an expert panel drafted a checklist of topics to be addressed throughout adolescence that are often not covered in subspecialty clinic visits such as peers, coping, adherence, understanding of illness, sexuality, etc., since these topics apply to youth with special healthcare needs. Each member of the specialized team can discuss one of the themes according to their role with the adolescent as a doctor, educator, nurse, dietician, etc. The coherence of the team enables a comprehensive approach and will facilitate the transition to adult medical care.
Subject(s)
Aftercare/methods , Checklist/standards , Transitional Care/standards , Adaptation, Psychological , Adolescent , Adult , Aftercare/trends , Checklist/methods , Checklist/trends , Chronic Disease/epidemiology , Chronic Disease/psychology , Chronic Disease/trends , Female , Follow-Up Studies , Humans , Male , Transitional Care/statistics & numerical dataABSTRACT
BACKGROUND: Children with neurologic impairment (NI) are at risk for developing co-occurring chronic conditions, increasing their medical complexity and morbidity. We assessed the prevalence and timing of onset for those conditions in children with NI. METHODS: This longitudinal analysis included 6229 children born in 2009 and continuously enrolled in Medicaid through 2015 with a diagnosis of NI by age 3 in the IBM Watson Medicaid MarketScan Database. NI was defined with an existing diagnostic code set encompassing neurologic, genetic, and metabolic conditions that result in substantial functional impairments requiring subspecialty medical care. The prevalence and timing of co-occurring chronic conditions was assessed with the Agency for Healthcare Research and Quality Chronic Condition Indicator system. Mean cumulative function was used to measure age trends in multimorbidity. RESULTS: The most common type of NI was static (56.3%), with cerebral palsy (10.0%) being the most common NI diagnosis. Respiratory (86.5%) and digestive (49.4%) organ systems were most frequently affected by co-occurring chronic conditions. By ages 2, 4, and 6 years, the mean (95% confidence interval [CI]) numbers of co-occurring chronic conditions were 3.7 (95% CI 3.7-3.8), 4.6 (95% CI 4.5-4.7), and 5.1 (95% CI 5.1-5.2). An increasing percentage of children had ≥9 co-occurring chronic conditions as they aged: 5.3% by 2 years, 10.0% by 4 years, and 12.8% by 6 years. CONCLUSIONS: Children with NI enrolled in Medicaid have substantial multimorbidity that develops early in life. Increased attention to the timing and types of multimorbidity in children with NI may help optimize their preventive care and case management health services.
Subject(s)
Chronic Disease/epidemiology , Chronic Disease/trends , Medicaid/trends , Multimorbidity/trends , Nervous System Diseases/diagnosis , Nervous System Diseases/epidemiology , Age Factors , Child , Child, Preschool , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Longitudinal Studies , Male , Retrospective Studies , United States/epidemiologySubject(s)
Adverse Childhood Experiences/trends , COVID-19/complications , Chronic Disease/trends , Environmental Exposure/adverse effects , Adult , Adverse Childhood Experiences/history , Child , Environmental Exposure/history , Famine/history , Female , Forecasting , History, 20th Century , History, 21st Century , Humans , Male , SARS-CoV-2ABSTRACT
ABSTRACT Objective: To assess the factors associated with the de-hospitalization of children and adolescents with complex chronic condition. Methods: This cross-sectional and retrospective study investigated a sample of children and adolescents admitted to the Dehospitalization Training Unit, from January 2012 to December 2017. Data were collected by consulting medical records and patient record books, from November 2018 to June 2019. The length of stay in the unit, de-hospitalization, readmissions, frequency and cause of death, age, sex, diagnosis, place of residence, number of caregivers and kinship, and use of devices were studied. The chi-square test was used to verify the association between the dependent variable (de-hospitalization) and the independent variables (age, sex, place of residence, use of devices, and clinical diagnosis). Results: A total of 93 patient records were analyzed, 37.6% aged between 7 months and 2 years old, 58.1% boys, 95.7% used tracheostomy, 92.5% gastrostomy, and 71% invasive mechanical ventilation. Hypoxic-ischemic encephalopathy was the diagnosis of 40.3% of the sample. Average hospitalization time was 288 ± 265 days; 60.2% were hospitalized between 31 days and one year, representing 50% of deaths. Of those de-hospitalized, 76.3% were discharged to the Ventilatory Assistance Homecare Program. De-hospitalization was associated with the child or adolescent's place of residence (p=0.027) and use of ventriculoperitoneal shunt (p=0.021). Conclusions: This study identified that de-hospitalization may be associated with the place of residence of the child or adolescent, with the highest number of discharges to the state capital, and non-dehospitalization when using ventricular-peritoneal shunt.
RESUMO Objetivo: Avaliar os fatores associados à desospitalização de crianças e adolescentes com condição crônica complexa. Métodos: Estudo transversal e retrospectivo, que investigou a população de crianças e adolescentes internados na Unidade de Treinamento para Desospitalização (UTD), de janeiro de 2012 a dezembro de 2017. Os dados foram coletados por meio da consulta aos prontuários e livros de registros, de novembro de 2018 a junho de 2019. Foram estudados o período de internamento na UTD, a desospitalização, as reinternações, a frequência e causa dos óbitos, a idade, o sexo, o diagnóstico, o local de residência, o número de cuidadores e parentesco e o uso de dispositivos. Utilizou-se o teste do qui-quadrado para verificar a associação entre a variável dependente (desospitalização) e as variáveis independentes (idade, sexo, local de residência, uso de dispositivos e diagnóstico clínico). Resultados: O total de 93 prontuários de pacientes foi analisado, 37,6% tinham idade entre sete meses e dois anos, 58,1% eram meninos, 95,7% usavam traqueostomia, 92,5% gastrostomia e 71% ventilação mecânica invasiva. Encefalopatia hipóxico-isquêmica foi o diagnóstico de 40,3% da população. O tempo médio de hospitalização foi 288±265 dias; 60,2% ficaram internados entre 31 dias e um ano, representando 50% dos óbitos. Dos desospitalizados, 76,3% receberam alta para o Programa de Assistência Ventilatória Domiciliar (PAVD). A desospitalização foi associada ao local de procedência (p=0,027) e ao uso de derivação ventriculoperitoneal (DVP) (p=0,021). Conclusões: Identificou-se que a desospitalização esteve associada ao local de residência da criança ou adolescente e ao uso de DVP, sendo o maior número de altas para a capital do estado.
Subject(s)
Humans , Male , Female , Infant , Child, Preschool , Child , Adolescent , Hospital Mortality , Hospitalization/statistics & numerical data , Chronic Disease/mortality , Chronic Disease/trends , Cross-Sectional Studies , Retrospective StudiesABSTRACT
INTRODUCTION: Policies to adequately respond to the rise in multimorbidity have top-priority. To understand the actual burden of multimorbidity, this study aimed to: 1) estimate the trend in prevalence of multimorbidity in the Netherlands, 2) study the association between multimorbidity and physical and mental health outcomes and healthcare cost, and 3) investigate how the association between multimorbidity and health outcomes interacts with socio-economic status (SES). METHODS: Prevalence estimates were obtained from a nationally representative pharmacy database over 2007-2016. Impact on costs was estimated in a fixed effect regression model on claims data over 2009-2015. Data on physical and mental health and SES were obtained from the National Health Survey in 2017, in which the Katz-10 was used to measure limitations in activities of daily living (ADL) and the Mental Health Inventory (MHI) to measure mental health. SES was approximated by the level of education. Generalized linear models (2-part models for ADL) were used to analyze the health data. In all models an indicator variable for the presence or absence of multimorbidity was included or a categorical variable for the number of chronic conditions. Interactions terms of multimorbidity and educational level were added into the previously mentioned models. RESULTS: Over the past ten years, there was an increase of 1.6%-point in the percentage of people with multimorbidity. The percentage of people with three or more conditions increased with +2.1%-point. People with multimorbidity had considerably worse physical and mental health outcomes than people without multimorbidity. For the ADL, the impact of multimorbidity was three times greater in the lowest educational level than in the highest educational level. For the MHI, the impact of multimorbidity was two times greater in the lowest than in the highest educational level. Each additional chronic condition was associated with a greater worsening in health outcomes. Similarly, for costs, where there was no evidence of a diminishing impact of additional conditions either. In patients with multimorbidity total healthcare costs were on average 874 higher than in patients with a single morbidity. CONCLUSION: The impact of multimorbidity on health and costs seems to be greater in the sicker and lower educated population.
Subject(s)
Chronic Disease/economics , Health Care Costs/statistics & numerical data , Multimorbidity/trends , Activities of Daily Living , Adult , Aged , Aged, 80 and over , Chronic Disease/trends , Comorbidity , Cost of Illness , Cross-Sectional Studies , Databases, Factual , Educational Status , Female , Health Surveys , Humans , Male , Middle Aged , Morbidity , Netherlands/epidemiology , Prevalence , Social ClassABSTRACT
BACKGROUND: In Japan, a high-sodium diet is the most important dietary risk factor and is known to cause a range of health problems. This study aimed to forecast Japan's disability-adjusted life year (DALYs) for chronic diseases that would be associated with high-sodium diet in different future scenarios of salt intake. We modelled DALY forecast and alternative future scenarios of salt intake for cardiovascular diseases (CVDs), chronic kidney diseases (CKDs), and stomach cancer (SC) from 2017 to 2040. METHODS: We developed a three-component model of disease-specific DALYs: a component on the changes in major behavioural and metabolic risk predictors including salt intake; a component on the income per person, educational attainment, and total fertility rate under 25 years; and an autoregressive integrated moving average model to capture the unexplained component correlated over time. Data on risk predictors were obtained from Japan's National Health and Nutrition Surveys and from the Global Burden of Disease Study 2017. To generate a reference forecast of disease-specific DALY rates for 2017-2040, we modelled the three diseases using the data for 1990-2016. Additionally, we generated better, moderate, and worse scenarios to evaluate the impact of change in salt intake on the DALY rate for the diseases. RESULTS: In our reference forecast, the DALY rates across all ages were predicted to be stable for CVDs, continuously increasing for CKDs, and continuously decreasing for SC. Meanwhile, the age group-specific DALY rates for these three diseases were forecasted to decrease, with some exceptions. Except for the ≥70 age group, there were remarkable differences in DALY rates between scenarios, with the best scenario having the lowest DALY rates in 2040 for SC. This represents a wide scope of future trajectories by 2040 with a potential for tremendous decrease in SC burden. CONCLUSIONS: The gap between scenarios provides some quantification of the range of policy impacts on future trajectories of salt intake. Even though we do not yet know the policy mix used to achieve these scenarios, the result that there can be differences between scenarios means that policies today can have a significant impact on the future DALYs.
Subject(s)
Chronic Disease/trends , Disabled Persons/statistics & numerical data , Health Promotion/organization & administration , Quality-Adjusted Life Years , Sodium Chloride, Dietary/adverse effects , Adult , Cardiovascular Diseases/epidemiology , Diet/statistics & numerical data , Forecasting , Humans , Japan , Male , Middle Aged , Nutrition Surveys , Renal Insufficiency, Chronic/epidemiology , Risk Factors , Sodium Chloride, Dietary/administration & dosageABSTRACT
Hospital admissions in the US fell dramatically with the onset of the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about differences in admissions patterns among patient groups or the extent of the rebound. In this study of approximately one million medical admissions from a large, nationally representative hospitalist group, we found that declines in non-COVID-19 admissions from February to April 2020 were generally similar across patient demographic subgroups and exceeded 20 percent for all primary admission diagnoses. By late June/early July 2020, overall non-COVID-19 admissions had rebounded to 16 percent below prepandemic baseline volume (8 percent including COVID-19 admissions). Non-COVID-19 admissions were substantially lower for patients residing in majority-Hispanic neighborhoods (32 percent below baseline) and remained well below baseline for patients with pneumonia (-44 percent), chronic obstructive pulmonary disease/asthma (-40 percent), sepsis (-25 percent), urinary tract infection (-24 percent), and acute ST-elevation myocardial infarction (-22 percent). Health system leaders and public health authorities should focus on efforts to ensure that patients with acute medical illnesses can obtain hospital care as needed during the pandemic to avoid adverse outcomes.
Subject(s)
Chronic Disease/trends , Hospitalization , Pandemics/statistics & numerical data , Patient Admission , Aged , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections , Female , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Male , Middle Aged , Patient Admission/statistics & numerical data , Patient Admission/trends , Pneumonia , Pneumonia, Viral , Pulmonary Disease, Chronic Obstructive , SARS-CoV-2 , ST Elevation Myocardial Infarction , United StatesABSTRACT
BACKGROUND AND AIMS: We sought to measure the effect of lockdown, implemented to contain COVID-19 infection, on routine living and health of patients with chronic diseases and challenges faced by them. METHODS: A semi-structured online questionnaire was generated using "Google forms" and sent to the patients with chronic diseases using WhatsApp. Data were retrieved and analyzed using SPSS. RESULTS: Out of 181 participants, 98% reported effect of lockdown on their routine living while 45% reported an effect on their health. The key challenges due to lockdown were to do daily exercise, missed routine checkup/lab testing and daily health care. CONCLUSION: It is important to strategize the plan for patients with chronic diseases during pandemic or lockdown.
Subject(s)
COVID-19/psychology , Chronic Disease/psychology , Chronic Disease/trends , Quarantine/psychology , Quarantine/trends , Surveys and Questionnaires , Adolescent , Adult , COVID-19/epidemiology , Chronic Disease/epidemiology , Female , Humans , Male , Middle Aged , Young AdultABSTRACT
BACKGROUND: Strategies to improve medication adherence are widespread in the literature; however, their impact is limited in real practice. Few patients persistently engage long-term to improve health outcomes, even when they are aware of the consequences of poor adherence. Despite the potential of mobile phone apps as a tool to manage medication adherence, there is still limited evidence of the impact of these innovative interventions. Real-world evidence can assist in minimizing this evidence gap. OBJECTIVE: The objective of this study was to analyze the impact over time of a previously implemented digital therapeutic mobile app on medication adherence rates in adults with any chronic condition. METHODS: A retrospective observational study was performed to assess the adherence rates of patients with any chronic condition using Perx Health, a digital therapeutic that uses multiple components within a mobile health app to improve medication adherence. These components include gamification, dosage reminders, incentives, educational components, and social community components. Adherence was measured through mobile direct observation of therapy (MDOT) over 3-month and 6-month time periods. Implementation adherence, defined as the percentage of doses in which the correct dose of a medication was taken, was assessed across the study periods, in addition to timing adherence or percentage of doses taken at the appropriate time (±1 hour). The Friedman test was used to compare differences in adherence rates over time. RESULTS: We analyzed 243 and 130 patients who used the app for 3 months and 6 months, respectively. The average age of the 243 patients was 43.8 years (SD 15.5), and 156 (64.2%) were female. The most common medications prescribed were varenicline, rosuvastatin, and cholecalciferol. The median implementation adherence was 96.6% (IQR 82.1%-100%) over 3 months and 96.8% (IQR 87.1%-100%) over 6 months. Nonsignificant differences in adherence rates over time were observed in the 6-month analysis (Fr(2)=4.314, P=.505) and 3-month analysis (Fr(2)=0.635, P=.728). Similarly, the timing adherence analysis revealed stable trends with no significant changes over time. CONCLUSIONS: Retrospective analysis of users of a medication adherence management mobile app revealed a positive trend in maintaining optimal medication adherence over time. Mobile technology utilizing gamification, dosage reminders, incentives, education, and social community interventions appears to be a promising strategy to manage medication adherence in real practice.
Subject(s)
Chronic Disease/trends , Medication Adherence/statistics & numerical data , Mobile Applications/trends , Telemedicine/methods , Adult , Female , Humans , Male , Retrospective StudiesABSTRACT
No disponible
Subject(s)
Humans , Telecardiology , Coronavirus Infections/epidemiology , Ambulatory Care/methods , Cardiovascular Diseases/therapy , Pandemics , Chronic Disease/trends , Coronavirus Infections/prevention & control , Telemedicine Emergency CareABSTRACT
BACKGROUND/OBJECTIVES: Dementia is associated with higher healthcare expenditures, in large part due to increased hospitalization rates relative to patients without dementia. Data on contemporary trends in the incidence and outcomes of potentially preventable hospitalizations of patients with dementia are lacking. DESIGN: Retrospective cohort study using the National Inpatient Sample from 2012 to 2016. SETTING: U.S. acute care hospitals. PARTICIPANTS: A total of 1,843,632 unique hospitalizations of older adults (aged ≥65 years) with diagnosed dementia. MEASUREMENTS: Annual trends in the incidence of hospitalizations for all causes and for potentially preventable conditions including acute ambulatory care sensitive conditions (ACSCs), chronic ACSCs, and injuries. In-hospital outcomes including mortality, discharge disposition, and hospital costs. RESULTS: The survey weighted sample represented an estimated 9.27 million hospitalizations for patients with diagnosed dementia (mean [standard deviation] age = 82.6 [6.7] years; 61.4% female). In total, 3.72 million hospitalizations were for potentially preventable conditions (40.1%), 2.07 million for acute ACSCs, .76 million for chronic ACSCs, and .89 million for injuries. Between 2012 and 2016, the incidence of all-cause hospitalizations declined from 1.87 million to 1.85 million per year (P = .04) while the incidence of potentially preventable hospitalizations increased from .75 million to .87 million per year (P < .001), driven by an increased number of hospitalizations of community-dwelling older adults. Among patients with dementia hospitalized for potentially preventable conditions, inpatient mortality declined from 6.4% to 6.1% (P < .001), inflation-adjusted median costs increased from $7,319 to $7,543 (P < .001), and total annual costs increased from $7.4 to $9.3 billion. Although 86.0% of hospitalized patients were admitted from the community, only 32.7% were discharged to the community. CONCLUSION: The number of potentially preventable hospitalizations of older adults with dementia is increasing, driven by hospitalizations of community-dwelling older adults. Improved strategies for early detection and goal-directed treatment of potentially preventable conditions in patients with dementia are urgently needed. J Am Geriatr Soc 68:2240-2248, 2020.