Identification Of Medical Conditions Research Articles

Broadening risk factor or disease definition as a driver for overdiagnosis: A narrative review

Medical overuse—defined as the provision of health services for which potential harms exceed potential benefits—constitutes a paradigm of low‐value care and is seen as a threat to the quality of care. Value in healthcare implies a precise definition of disease. However, defining a disease may not be straightforward since clinical data do not show discrete boundaries, calling for some clinical judgment. And, if in time a redefinition of disease is needed, it is important to recognize that it can induce overdiagnosis, the identification of medical conditions that would, otherwise, never cause any significant symptoms or lead to clinical harm. A classic example is the impact of recommendations from professional societies in the late 1990s, lowering the threshold for abnormal total cholesterol from 240 mg/dl to 200 mg/dl. Due to these changes in risk factor definition, literally overnight there were 42 million new cases eligible for treatment in the United States. The same happened with hypertension—using either the 2019 NICE guidelines or the 2018 ESC/ECC guidelines criteria for arterial hypertension, the proportion of people overdiagnosed with hypertension was calculated to be between 14% and 33%. In this review, we will start by discussing resource overuse. We then present the basis for disease definition and its conceptual problems. Finally, we will discuss the impact of changing risk factor/disease definitions in the prevalence of disease and its consequences in overdiagnosis and overtreatment (a problem particularly relevant when definitions are widened to include earlier or milder disease).

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims-based algorithms (CBAs) are highly dependent on the knowledge level and not necessarily optimized for target conditions. We investigated whether machine learning methods can supplement researchers’ knowledge of target conditions in building CBAs. Retrospective cohort study using a claims database combined with annual health check-up results of employees’ health insurance programs for fiscal year 2016–17 in Japan (study population for hypertension, N = 631,289; diabetes, N = 152,368; dyslipidemia, N = 614,434). We constructed CBAs with logistic regression, k-nearest neighbor, support vector machine, penalized logistic regression, tree-based model, and neural network for identifying patients with three common chronic conditions: hypertension, diabetes, and dyslipidemia. We then compared their association measures using a completely hold-out test set (25% of the study population). Among the test cohorts of 157,822, 38,092, and 153,608 enrollees for hypertension, diabetes, and dyslipidemia, 25.4%, 8.4%, and 38.7% of them had a diagnosis of the corresponding condition. The areas under the receiver operating characteristic curve (AUCs) of the logistic regression with/without subject-matter knowledge about the target condition were .923/.921 for hypertension, .957/.938 for diabetes, and .739/.747 for dyslipidemia. The logistic lasso, logistic elastic-net, and tree-based methods yielded AUCs comparable to those of the logistic regression with subject-matter knowledge: .923-.931 for hypertension; .958-.966 for diabetes; .747-.773 for dyslipidemia. We found that machine learning methods can attain AUCs comparable to the conventional knowledge-based method in building CBAs.

Healthcare resource utilization and expenditures among newly-diagnosed elderly non-valvular atrial fibrillation patients initiating oral anticoagulants

Aims: Non-valvular atrial fibrillation (NVAF) prevalence increases with age. Hence, evaluating the economic burden among older-aged patients is vital. This study aimed to compare healthcare resource utilization (HRU) and costs among newly-diagnosed older-aged NVAF patients treated with warfarin, rivaroxaban, or apixaban vs. dabigatran.Materials and Methods: Newly-diagnosed older-aged (aged ≥65 years) NVAF patients initiating dabigatran, warfarin, rivaroxaban, or apixaban (first prescription date = index date) from 01JAN2010-31DEC2015 and with continuous enrollment for ≥12 months pre-index date were included from 100% Medicare database. Patient data were assessed until drug discontinuation/switch/dose change/death/disenrollment/study end (up to 12 months). Dabigatran initiators were 1:1 propensity score-matched (PSM) with warfarin, rivaroxaban, or apixaban initiators. Generalized linear models were used to compare all-cause HRU and costs per-patient-per-month (PPPM) between the matched cohorts.Results: After PSM with dabigatran, 70,531 warfarin, 51,673 rivaroxaban, and 25,209 apixaban patients were identified. Dabigatran patients had significantly fewer generalized-linear-model-adjusted PPPM hospitalizations (0.114 vs. 0.123; 0.111 vs. 0.121), and outpatient visits (2.864 vs. 4.201; 2.839 vs. 2.949) than warfarin and rivaroxaban patients, respectively, but had significantly more PPPM hospitalizations (0.103 vs. 0.090) and outpatient visits (2.780 vs. 2.673) than apixaban patients (all p < .0001). Dabigatran patients incurred significantly lower adjusted total PPPM costs ($3,309 vs. $3,362; $3,285 vs. $3,474) than warfarin and rivaroxaban patients, respectively (all p < .01) but higher total PPPM costs ($3,192 vs. $2,986) than apixaban patients (all p < .0001).Limitations: This study is subject to the inherent limitations of any claims dataset, including potential bias from coding errors and identification of medical conditions using diagnosis codes as opposed to clinical evidence. Medications filled over-the-counter or provided as samples by the physician are never captured in claims data.Conclusions: Newly-diagnosed older-aged NVAF patients initiating dabigatran incurred significantly lower adjusted all-cause HRU and costs than warfarin and rivaroxaban patients but higher adjusted HRU and costs than apixaban patients.

Asymptotic convergence in distribution of the area bounded by prevalence-weighted Kaplan-Meier curves using empirical process modelling.

The Kaplan–Meier product-limit estimator is a simple and powerful tool in time to event analysis. An extension exists for populations stratified into cohorts where a population survival curve is generated by weighted averaging of cohort-level survival curves. For making population-level comparisons using this statistic, we analyse the statistics of the area between two such weighted survival curves. We derive the large sample behaviour of this statistic based on an empirical process of product-limit estimators. This estimator was used by an interdisciplinary National Institutes of Health–Social Security Administration team in the identification of medical conditions to prioritize for adjudication in disability benefits processing.

Pediatric Comorbidities and Medical Complications Identified in Children with Down Syndrome

Objective: Children with Down syndrome (DS) have an increased risk of neonatal complications and comorbidities compared to the general population; however, the incidence, optimal screening intervals and outcomes in this population are uncertain. The purpose of this study is to phenotypically define this population of children with DS using a large multi-age and ethnic sample and current American Academy of Pediatrics (AAP) Guidelines testing practices. Method: This is a retrospective review of a large cohort of 1,108 children with DS (male=602; mean age at initial contact: 5.72 years, SD ± 5.51) who received care at the Sie Center for Down Syndrome (SCDS) at The Children’s Hospital Colorado from 2011 and 2016. Clinical data were collected from a prospective patient clinic database. Clinical details were collected, which included demographics, prenatal and birth history and complications, comorbidities, procedures, treatment plans and outcomes. Results: Medical complications requiring admission to the neonatal intensive care unit were identified in 70.6% of children with DS. Frequent causes for these neonatal admissions included: Required oxygen (60.7%), feeding problem (48.2%), Respiratory Distress Syndrome (21.4%) and pulmonary hypertension (14.7%). Incidence of medical comorbidities in our population with DS included cardiac defects (64.3%), abnormal sleep study (71.1%), abnormal thyroid study (29.1%), pulmonary aspiration (12.2%), celiac disease (5.0%) and pulmonary arterial hypertension (28.3%). Conclusion: Clinical data provides results from one of the largest investigations at a single pediatric hospital for children and young adults with DS in the US. This study describes the comorbidities affecting individuals with DS more accurately by applying AAP guidelines in studying a larger population than previously defined. This result improves our understanding of the incidence and identification of medical conditions in children with DS and reinforces recommendations on medical care screening for individuals with DS.

New conditions identified through a comprehensive geriatric assessment in cancer patients.

133 Background: Chronologic age cannot be used to predict the degree of comorbidity and of functional deterioration of older adults. Assessment of older adults includes health, functional status, nutrition, cognition, socio-economic and mood disorders evaluations. This multidisciplinary assessment is referred to as comprehensive geriatric assessment (CGA). The risk of comorbid conditions increases with age and may result in under diagnosis: in older patients, new symptoms may not be clearly recognized by the patient and may be dismissed by practitioners as manifestations of preexisting conditions. Methods: We conducted a retrospective cohort analysis, of older adult patients (aged 70 years of age and older) evaluated at the Program for Healthy Aging at MD Anderson from January 1, 2013 through December 31, 2014. Assessment was conducted using Katz’ ADLs, Lawton’s IADLs, PHQ-9, the short physical performance battery, the Montreal cognitive assessment, mini nutritional assessment and Charlson co-morbidity index. Medication review and social assessment were also included. Analysis: cross tabulations were performed in SAS 9.4 (SAS Institute INC, Cary, NC) Results: We evaluated 198 patients, (n = 99, 51.6% females). Most common malignancies evaluated included hematologic malignancies (n = 62, 33%), breast cancer (n = 32, 13.2 %), prostate cancer (n = 19, 10 %) and other solid malignancies (n = 85, 43%). The comprehensive geriatric assessment identified a mean of 3 new conditions (range 1-10). The most commonly identified conditions included cognitive impairment and dementia (n = 148, 77%), low bone mass and osteoporosis (n = 67, 34%), malnutrition (n = 65, 34%), frailty (n = 58, 30.2%), and polypharmacy (n = 64, 33%). These conditions are relevant in the management of such patients and could lead to recurring admissions if left unaddressed. Conclusions: A CGA program in a cancer center allows for the identification of medical conditions that directly contribute to clinical outcomes. A CGA allows for the development of a comprehensive plan of care that addresses such issues preventing adverse consequences.

Multisociety sedation curriculum for gastrointestinal endoscopy

Multisociety sedation curriculum for gastrointestinal endoscopy

The “Toe Walking Tool”: a novel method of assessing toe walking children

Background Idiopathic toe walking (ITW) can present in children above the age of three, and occurs in the absence of any medically diagnosed conditions. Identification of medical conditions that are associated with toe walking can be complex and a potentially daunting task for those that infrequently assess children. In order to facilitate entry for appropriate toe walking children into an ITW study, a tool was developed and validated. Methods A review of literature established key indicators that may be found within the medical history and clinical presentation that identify an underlying condition potentially being responsible for the toe-walking gait. These key indicators were translated into a simple web based program or a paper version of 21 questions. The tool content was validated via a Delphi panel with medical and allied health professionals. It was then tested for reliability with twelve children and 10 allied health professionals. Results The content of this tool and its design was determined valid by a Delphi panel process. Minor changes to order and wording were applied. Th er esults of the reliability testing determine the tool to be reliable with a Fleiss Kappa=0.9028; z=29.6091; p<0.0001. This was calculated from 120 individual uses of the tool. Conclusions There is a need for appropriate assessment tools for both training new clinicians working with the paediatric population, and for clinicians that infrequently assess children. The Toe Walking Tool is a valid and comprehensive way to assess children who toe walk. This tool will assist in the appropriate referral of children who may have a medical reason for their gait pattern and the identification of children with an ITW gait.

Relations among chronic medical conditions, medications, and automobile crashes in the elderly: a population-based case-control study.

Older drivers have elevated crash rates and are more likely to be injured or die if they have a crash. Medical conditions and medications have been hypothesized as determinants of crash involvement. This population-based case-control study sought to identify medical conditions and medications associated with risk of at-fault crashes among older drivers. A total of 901 drivers aged 65 years and older were selected in 1996 from Alabama Department of Public Safety driving records: 244 at-fault drivers involved in crashes; 182 not at-fault drivers involved in crashes; and 475 drivers not involved in crashes were enrolled. Information on demographic factors, chronic medical conditions, medications, driving habits, visual function, and cognitive status was collected. Older drivers with heart disease (odds ratio (OR) = 1.5, 95% confidence interval (CI): 1.0, 2.2) or stroke (OR = 1.9, 95% CI: 0.9, 3.9) were more likely to be involved in at-fault automobile crashes. Arthritis was also associated with an increased risk among females (OR =1.8, 95% CI: 1.1, 2.9). Use of nonsteroidal antiinflammatory drugs (OR = 1.7, 95% CI 1.0, 2.6), angiotensin converting enzyme inhibitors (OR = 1.6, 95 CI: 1.0, 2.7), and anticoagulants (OR = 2.6, 95% CI: 1.0, 73) was associated with an increased risk of at-fault involvement in crashes. Benzodiazepine use (OR = 5.2, 95% CI: 0.9, 30.0) was also associated with an increased risk. Calcium channel blockers (OR = 0.5, 95% CI: 0.2, 0.9) and vasodilators (OR = 0.3, 95% CI: 0.1, 1.0) were associated with a reduced risk of crash involvement. The identification of medical conditions and medications associated with risk of crashes is important for enhancing the safety and mobility of older drivers.

Morbidity, comorbidity, and their association with disability among community-dwelling oldest-old in Israel.

The impact of chronic conditions on the development of disability has not yet been comprehensively studied among the elderly population living in Israel. This study evaluates the prevalence of disability and morbidity among the community-dwelling oldest-old population and examines the association between medical conditions, comorbidity, and disability in basic and instrumental activities of daily living (ADLs, IADLs). The data are based on a national random stratified sample of 1,820 Israeli Jewish individuals 75-94 years old, of whom 1,487 lived in the community. Nineteen percent of the population was disabled in ADLs and 36% in IADLs. Disability rose with age and was higher for women and among individuals of Middle Eastern and North African origin. Stepwise logistic regression indicates that the variables associated with disability in ADLs and IADLs were older age, Middle Eastern or North African origin, living with others, and the following conditions: stroke, hip fracture, diabetes, osteoporosis, anemia, and heart attack. In addition, lower education and suffering from urinary or kidney diseases, respiratory disease, and/or Parkinson's disease were related to disability in ADLs; being a woman and suffering from heart diseases other than heart attack were related to disability in IADLs. Comorbidity was related to increased disability only for individuals with three or more conditions. The identification of medical conditions and sociodemographic variables related to limitations in functioning may serve as a basis for health promotion and disease prevention in elders by attempting to reduce the incidence and disabling consequences of known disabling conditions.