High variation between healthcare professionals in nutrition therapy plans of patients with feeding tubes admitted to a long-term rehabilitation center from an acute-care hospital.

BACKGROUND: Nutrition therapy plans (NTPs) in discharge summaries of tube-fed patients transferred from acute-care hospitals to rehabilitation centers are fundamental for continuity of care. This study examined the presence and quality of NTPs in discharge summaries of tube-fed patients. METHODS: This cross-sectional study was based on data retrieved from electronic medical records. The outcome measures were the presence of NTPs in discharge summaries, the presence of key elements of the NTPs, and the level of compatibility between multiple NTPs per discharge summary prepared by different health professionals. Descriptive statistics were used to assess the number of NTPs, the presence of key elements, and the degree of compatibility between NTPs for the same patient. RESULTS: A total of 100 discharge summaries of tube-fed patients admitted to a rehabilitation hospital during 2015-2017 were identified. The majority (91%) of discharge summaries included at least one NTP; 57 included more than one. Variance in the presence of key elements was observed in 165 NTPs prepared by physicians, nurses, and dietitians. Water amount and nutrition route were least reported by dietitians (6.3% and 9.4%, respectively), compared with physicians (77.6% and 81%) and nurses (77.3% and 62.7%). However, nutrition details were reported more frequently by dietitians (65.6%) than physicians (20.7%) and nurses (32%). Low compatibility was observed between dietitians and both nurses and physicians, in the range of 0%-26%. CONCLUSION: Large discrepancies were found between NTPs for the same patient prepared by dietitians, physicians, and/or nurses, and a portion of patients arrived without any NTP.

The relationship between inpatient hyperglycaemia and mortality is modified by baseline glycaemic status.

AIMS: There is a well-established association between inpatient hyperglycaemia and mortality. However, evidence is inconsistent regarding whether this association is differential among those with and without type 2 diabetes mellitus (T2DM). Most studies are based on convenience samples or are unable to adjust for comorbidities. We examined whether the association between hyperglycaemia and 30-day mortality was modified by baseline glycaemic status. MATERIALS AND METHODS: This was a retrospective cohort study of 174,671 eligible hospitalized individuals between 2012 and 2015. Thirty-day mortality was assessed during the first inpatient stay up to 30 days post discharge. The adjusted association between hyperglycaemia and mortality was assessed with logistic regression models. Then, four interaction terms were entered into the model to assess if the association between hyperglycaemia and mortality differed by baseline glycaemic status. RESULTS: The multivariate model demonstrated a 2.18-fold risk of mortality associated with hyperglycaemia (odds ratio [OR] [95%CI]: 2.19 [2.08-2.31]). Adding the interaction terms between hyperglycaemia and baseline glycaemic status the ORs of 30-day mortality were 1.41 (1.25-1.60) in non-T2DM status, 1.32 (1.16-1.51) in pre-diabetes status and 1.30 (1.04-1.62) in unscreened status, as compared to T2DM status with hyperglycaemia. CONCLUSIONS: Hyperglycaemia is positively associated with mortality and both those without and with controlled T2DM are at highest risk. These findings may help medical staff identify potential increased risk of mortality upon hospital entry and discharge, and direct further research to assess how hyperglycaemia control and proactive deterioration prevention throughout the entire inpatient stay may prevent adverse outcomes.

Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study.

PURPOSE: Previous studies have demonstrated differences in atrial fibrillation (AF) detection based on data from hospital sources without data from outpatient sources. We investigated the detection of documented diagnoses of non-valvular AF in a large Israeli health-care organization using electronic health record data from multiple sources. PATIENTS AND METHODS: This was an open-chart validation study. Three distinct algorithms for identifying AF in electronic health records, differing in the source of their International Classification of Diseases, Ninth Revision code and use of the associated free text, were defined. Algorithm 1 incorporated inpatient data with outpatient data and the associated free text. Algorithm 2 incorporated inpatient and outpatient data regardless of the free text associated with AF diagnosis. Algorithm 3 used only inpatient data source. These algorithms were compared to a gold standard and their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. To establish the gold standard (documentation of arrhythmia based on electrocardiography interpretation or a cardiologist's written diagnosis), 200 patients at highest risk for having non-valvular AF were randomly selected for open-chart validation by two physicians. RESULTS: The algorithm that included hospital settings, outpatient settings, and incorporated associated free text in the outpatient records had the optimal balance between all validation measures, with a high level of sensitivity (85.4%), specificity (95.0%), PPV (81.4%), and NPV (96.2%). The alternative algorithm that combined inpatient and outpatient data without free text also performed better than the algorithm that included only hospital data (82.9%, 95.0%, 81.0%, and 95.6%, compared to 70.7%, 96.9%, 85.3%, and 92.8%, sensitivity, specificity, PPV, and NPV, respectively). CONCLUSION: In this study, involving a comprehensive data collection from inpatient and outpatient sources, incorporating outpatient data with inpatient data improved the diagnosis of non-valvular AF compared to inpatient data alone.

The metabolic syndrome and its components are differentially associated with chronic diseases in a high-risk population of 350 000 adults: A cross-sectional study.

AIMS: We compared strengths of associations conferred by the metabolic syndrome (MetS) and its components across four chronic disease categories (cancer, cardiovascular diseases [CVDs], chronic kidney disease [CKD], and chronic obstructive pulmonary disease [COPD]) in a community-dwelling high-risk population. METHODS: This is a cross-sectional analysis of Israeli adults insured in a single health maintenance organization during 2010 to 2013 and having greater than or equal to two MetS components (hypertension, dysglycemia, low high-density lipoprotein level, high plasma triglyceride level, and obesity). Data regarding MetS components, chronic disease prevalence, and sociodemographic variables were retrieved from electronic health records and disease registries. RESULTS: Among 347 244 eligible members, 54.2% had MetS. MetS was negatively associated with cancer, (prevalence ratio [PR] = 0.86; 95% confidence interval, 0.79-0.93) and positively associated with CKD (PR = 1.07, [1.01-1.13]). Some MetS components conferred different associations across the chronic diseases: a high triglyceride level was positively associated with cancer (PR = 1.15, 1.12-1.18) and CKD (PR = 1.37, 1.32-1.41) but negatively associated with CVD (PR = 0.88, 0.86-0.90) and COPD (PR = 0.93, 0.88-0.98). In the presence of MetS, those with dysglycemia had higher cancer prevalence than those with normoglycemia (PR-interaction MetS*dysglycemia on cancer = 1.14, 1.06-1.22). Likewise, in the presence of MetS, men were more likely than women to present with CVD (PR-interaction MetS*sex on CVD = 1.12, [1.05-1.20]). CONCLUSIONS: Prevalences of the MetS and MetS components distribute unequally across four chronic diseases. MetS including dysglycemia may warrant screening for cancer, and MetS in males may indicate the presence of CVD. Longitudinal studies may reveal if MetS is associated with different risks or merely indicates better prognosis once having a chronic illness.