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Background Diabetes is a medical and economic burden in the United States. In this study, a machine learning predictive model was developed to predict unplanned medical visits among patients with diabetes, and findings were used to design a clinical intervention in the sponsoring healthcare organization. This study presents a case study of how predictive analytics can inform clinical actions, and describes practical factors that must be incorporated in order to translate research into clinical practice. Methods Data were drawn from electronic medical records (EMRs) from a large healthcare organization in the Northern Plains region of the US, from adult (≥ 18 years old) patients with type 1 or type 2 diabetes who received care at least once during the 3-year period. A variety of machine-learning classification models were run using standard EMR variables as predictors (age, body mass index (BMI), systolic blood pressure (BP), diastolic BP, low-density lipoprotein, high-density lipoprotein (HDL), glycohemoglobin (A1C), smoking status, number of diagnoses and number of prescriptions). The best-performing model after cross-validation testing was analyzed to identify strongest predictors. Results The best-performing model was a linear-basis support vector machine, which achieved a balanced accuracy (average of sensitivity and specificity) of 65.7%. This model outperformed a conventional logistic regression by 0.4 percentage points. A sensitivity analysis identified BP and HDL as the strongest predictors, such that disrupting these variables with random noise decreased the model’s overall balanced accuracy by 1.3 and 1.4 percentage points, respectively. These recommendations, along with stakeholder engagement, behavioral economics strategies, and implementation science principles helped to inform the design of a clinical intervention targeting behavioral changes. Conclusion Our machine-learning predictive model more accurately predicted unplanned medical visits among patients with diabetes, relative to conventional models. Post-hoc analysis of the model was used for hypothesis generation, namely that HDL and BP are the strongest contributors to unplanned medical visits among patients with diabetes. These findings were translated into a clinical intervention now being piloted at the sponsoring healthcare organization. In this way, this predictive model can be used in moving from prediction to implementation and improved diabetes care management in clinical settings.

Background Smoking exacerbates the complications of diabetes, but little is known about whether patients with diabetes who smoke have more unplanned medical visits than those who do not smoke. This study examines the association between smoking status and unplanned medical visits among patients with diabetes. Methods Data were drawn from electronic medical records (EMR’s) from a large healthcare provider in the Northern Plains region of the US, from adult (≥18 years old) patients with type 1 or type 2 diabetes who received care at least once during 2014–16 ( N  = 62,149). The association between smoking status (current, former, or never smoker) and having ≥1 unplanned visit (comprised of emergency department visits, hospitalizations, hospital observations, and urgent care) was examined after adjusting for age, race/ethnicity, and body mass index (BMI). The top ten most common diagnoses for unplanned visits were examined by smoking status. Results Both current and former smoking were associated with an approximately 1.2-fold increase in the odds of having at least one unplanned medical visit in the 3-year period (OR = 1.22, 95% CI = 1.16–129; OR = 1.23, 95% CI = 1.19–1.28, respectively), relative to never-smokers. Most common diagnoses for all patients were pain-related. However, diagnoses related to musculoskeletal system and connective tissue disorders were more common among smokers. Smoking is associated with a higher rate of unplanned medical visits among patients with diabetes in this regional healthcare system. Conclusions Results from this study reveal higher rates of unplanned visits among smokers and former smokers, as well as increased frequencies of unplanned medical visits among current smokers.

Background Children who leave the emergency department (ED) without complete evaluation or care (LWCET) have poorer outcomes in general. Previous studies have found that American Indian (AI) children have higher rates of LWCET than other racial or ethnic groups. Therefore, this study aims to examine LWCET in AI children by exploring differences by ED location and utilization patterns. Methods This is a retrospective cohort study of five EDs in the upper Midwest between June 2011 and May 2012. We included all visits by children aged 0–17 who identified as African American (AA), AI or White. Logistic regression was used to determine differences in LWCET by race and ED location controlling for other possible confounding factors including sex, age, insurance type, triage level, distance from ED, timing of visit, and ED activity level. Results LWCET occurred in 1.73% of 68,461 visits made by 47,228 children. The multivariate model revealed that AIs were more likely to LWCET compared to White children (Odds Ratio (OR) = 1.62, 95% Confidence Interval (CI) = 1.30–2.03). There was no significant difference in LWCET between AA and White children. Other factors significantly associated with LWCET included triage level, distance from the ED, timing of visit, and ED activity level. Conclusion Our results show that AI children have higher rates of LWCET compared to White children; this association is different from other racial minority groups. There are likely complex factors affecting LWCET in AI children throughout the upper Midwest, which necessitates further exploration.

This study examines the extent to which data linkages between Indian Health Service, tribal data, and cancer registries affect cancer incidence rates among American Indians/Alaska Natives (AI/ANs) in Michigan. The incidence of tobacco- and alcohol-associated cancers for 1995-2012 was analyzed to compare rates of the Upper Peninsula (UP) and Lower Peninsula (LP) in Michigan and among AI/ANs and non-Hispanic Whites (NHWs). Complete linkage resulted in 1,352 additional AI/AN cases; 141 cases were linked via IHS records alone, while 373 were linked via tribal records alone; 838 were linked through both IHS and tribal records. Age-adjusted incidence rates for AI/ANs increased from 214.39 per 100,000 to 405.41 per 100,000, similar to that of NHWs after complete linkage (421.46 per 100,000). In the UP, AI/ANs had age-adjusted incidence rates 1.67 times higher than NHWs (596.69 per 100,000 vs. 356.32 per 100,000 respectively). This study indicates a substantial number of AI/AN cancer cases remain misclassified in Michigan.

Emergency department (ED) utilization by American Indian (AI) children is among the highest in the nation. Numerous health disparities have been well documented in AI children, but limited information is available on parental experiences of care for AI children in the ED. Our objective was to understand parental attitudes towards ED careforAIchildren. FocusgroupswereheldwithAI parents/caregivers at five sites in the Upper Midwest. Traditional content analysis was used to identify themes. A total of 70 parents participated in ten focus groups. Three main themes were identified: healthcare environment, access to care, and interaction with providers. Healthcare environment issues included availability of specialists, wait times, and child-friendly areas. Transportation and financial considerations were major topics in access to care. Issues in interaction with providers included discrimination, stereotyping, and trust. This is one of the first studies to assess parent perspectives on ED use for AI children. Obtaining parental perspectives on ED experiences is critical to improve patient care and provide important information for ED providers.

A community needs assessment during a tribally-led Changing High-Risk Alcohol Use and Increasing Contraception Effectiveness Study (CHOICES) intervention highlighted the need to reduce the risk for alcohol exposed pregnancy (AEP) among American Indian and Alaska Native (AIAN) adolescent girls. The CHOICES for American Indian Teens (CHAT) Program aims to reduce the risk of AEP among AIAN teens in one Northern Plains tribal community. The CHAT team adopted an iterative process to modify the tribally-led CHOICES curriculum for AIAN teens. This paper describes the iterative process as well as the community perception towards AEP prevention among AIAN teens. The CHAT team conducted several levels of formative and qualitative research, including one-on-one interviews (n = 15) with community members, AIAN elders and school counsellors; and three focus groups with AIAN adolescent girls (n = 15). A qualitative data analysis identified several recommendations that centered on making the information regarding alcohol and birth control appealing to teens; ensuring the confidentiality of the participants; making the program culturally relevant; and including boys in the program. This study outlines various components prioritized by community members in creating a culturally-relevant and age-appropriate AEP prevention program and provides community perceptions of AEP prevention for the teens in this community

Brant Mayor Ron Eddy gesticulated wildly and demanded that his constituents not ask for \"too much\" because this is a \"crunch year.\" Don't ask Eddy to explain economics or the county's financial plans, all you'll get is wild gesticulating and a violent condemnation for something or other. All designed to cleverly divert your attention away from his shortcomings and focus on yours or somebody else's.

These recommendations were systematically developed on behalf of the Network for Early Onset Cystic Kidney Disease (NEOCYST) by an international group of experts in autosomal dominant polycystic kidney disease (ADPKD) from paediatric and adult nephrology, human genetics, paediatric radiology and ethics specialties together with patient representatives. They have been endorsed by the International Pediatric Nephrology Association (IPNA) and the European Society of Paediatric Nephrology (ESPN). For asymptomatic minors at risk of ADPKD, ongoing surveillance (repeated screening for treatable disease manifestations without diagnostic testing) or immediate diagnostic screening are equally valid clinical approaches. Ultrasonography is the current radiological method of choice for screening. Sonographic detection of one or more cysts in an at-risk child is highly suggestive of ADPKD, but a negative scan cannot rule out ADPKD in childhood. Genetic testing is recommended for infants with very-early-onset symptomatic disease and for children with a negative family history and progressive disease. Children with a positive family history and either confirmed or unknown disease status should be monitored for hypertension (preferably by ambulatory blood pressure monitoring) and albuminuria. Currently, vasopressin antagonists should not be offered routinely but off-label use can be considered in selected children. No consensus was reached on the use of statins, but mTOR inhibitors and somatostatin analogues are not recommended. Children with ADPKD should be strongly encouraged to achieve the low dietary salt intake that is recommended for all children.This Consensus Statement developed on behalf of the Network for Early Onset Cystic Kidney Disease provides guidance on counselling, diagnosing and monitoring children with autosomal dominant polycystic kidney disease based on current evidence and a multi-stakeholder discussion of ethical issues.