Effects on alcohol consumption of announcing and implementing revised UK low-risk drinking guidelines: findings from an interrupted time series analysis

Background: In January 2016, the UK announced and began implementing revised guidelines for low-risk drinking of 14 units (112 g) per week for men and women. This was a reduction from the previous guidelines for men of 3–4 units (24–32 g) per day. There was no large-scale promotion of the revised guidelines beyond the initial media announcement. This paper evaluates the effect of announcing the revised guidelines on alcohol consumption among adults in England. / Methods: Data come from a monthly repeat cross-sectional survey of approximately 1700 adults living in private households in England collected between March 2014 and October 2017. The primary outcomes are change in level and time trend of participants’ Alcohol Use Disorders Identification Test—Consumption (AUDIT-C) scores. / Results: In December 2015, the modelled average AUDIT-C score was 2.719 out of 12 and was decreasing by 0.003 each month. After January 2016, AUDIT-C scores increased immediately but non-significantly to 2.720 (β=0.001, CI −0.079 to 0.099) and the trend changed significantly such that scores subsequently increased by 0.005 each month (β=0.008, CI 0.001 to 0.015), equivalent to 0.5% of the population increasing their AUDIT-C score by 1 point each month. Secondary analyses indicated the change in trend began 7 months before the guideline announcement and that AUDIT-C scores reduced significantly but temporarily for 4 months after the announcement (β=−0.087, CI −0.167 to 0.007). / Conclusions: Announcing new UK drinking guidelines did not lead to a substantial or sustained reduction in drinking or a downturn in the long-term trend in alcohol consumption, but there was evidence of a temporary reduction in consumption

Mapping oral health related quality of life to generic health state values

BACKGROUND: A summary utility index is useful for deriving quality-adjusted life years (QALY) for cost analyses or disability weights for burden of disease studies. However, many quality of life instruments provide descriptive profiles rather than a single utility index. Transforming quality of life instruments to a utility index could extend the use of quality of life instruments to costs analyses and burden of disease studies. The aims of the study were to map a specific oral health measure, the Oral Health Impact Profile to a generic health state measure, the EuroQol, in order to enable the estimation of health state values based on OHIP data. METHODS: Data were collected from patients treated by a random sample of South Australian dentists in 2001–02 using mailed self-complete questionnaires. Dentists recorded the diagnosis of dental conditions and provided patients with self-complete questionnaires to record the nature, severity and duration of symptoms using the EuroQol (EQ-5D) and 14-item version of the Oral Health Impact Profile (OHIP-14) instruments. Data were available from 375 patients (response rate = 72%). A random two-thirds sample of patients was used in tobit regressions of EQ-5D health state values estimated using OHIP-14 in a model with categories of OHIP responses as indicator variables and in a model with OHIP responses as continuous variables. Age and sex were included as covariates in both models. The remaining one-third sample of patients was used to test the models. RESULTS: The OHIP item 'painful aching in mouth' was significantly related to health state values in both models while 'life less satisfying' was also significant in the continuous model. Mean forecast errors relative to the mean observed health state value were higher when fitted to the categorical model (17.4%) compared to the continuous model (15.2%) (P < 0.05). CONCLUSION: The findings enable health state values to be derived from OHIP-14 scores for populations where utility has not or cannot be measured directly

Is the Internet a useful and relevant source for health and health care information retrieval for German cardiothoracic patients? First results from a prospective survey among 255 Patients at a German cardiothoracic surgical clinic

BACKGROUND: It is not clear how prevalent Internet use among cardiopathic patients in Germany is and what impact it has on the health care utilisation. We measured the extent of Internet use among cardiopathic patients and examined the effects that Internet use has on users' knowledge about their cardiac disease, health care matters and their use of the health care system. METHODS: We conducted a prospective survey among 255 cardiopathic patients at a German university hospital. RESULTS: Forty seven respondents (18 %) used the internet and 8,8 % (n = 23) went online more than 20 hours per month. The most frequent reason for not using the internet was disinterest (52,3 %). Fourteen patients (5,4 %) searched for specific disease-related information and valued the retrieved information on an analogous scale (1 = not relevant, 5 = very relevant) on median with 4,0. Internet use is age and education dependent. Only 36 (14,1 %) respondents found the internet useful, whereas the vast majority would not use it. Electronic scheduling for ambulatory visits or postoperative telemedical monitoring were rather disapproved. CONCLUSION: We conclude that Internet use is infrequent among our study population and the search for relevant health and disease related information is not well established

Disability weights for the burden of oral disease in South Australia

BACKGROUND: Australian burden of disease estimates appeared inconsistent with the reported repetitive and ubiquitous nature of dental problems. The aims of the study were to measure the nature, severity and duration of symptoms for specific oral conditions, and calculate disability weights from these measures. METHODS: Data were collected in 2001–02 from a random sample of South Australian dentists using mailed self-complete questionnaires. Dentists recorded the diagnosis of dental problems and provided patients with self-complete questionnaires to record the nature, severity and duration of symptoms using the EuroQol instrument. Data were available from 378 dentists (response rate = 60%). RESULTS: Disability weights were highest for pulpal infection (0.069), caries (0.044) and dentinal sensitivity (0.040), followed by denture problems (0.026), periodontal disease (0.023), failed restorations (0.019), tooth fractures (0.014) and tooth wear (0.011). Aesthetic problems had a low disability weight (0.002), and both recall/maintenance care and oral hygiene had adjusted weights of zero. CONCLUSIONS: Disability weights for caries (0.044), periodontal disease (0.023) and denture problems (0.026) in this study were higher than comparable oral health conditions in the Australian Burden of Disease and Injury Study (0.005 for caries involving a filling and 0.014 for caries involving an extraction, 0.007 for periodontal disease, and 0.004 for edentulism). A range of common problems such as pulpal infection, failed restorations and tooth fracture that were not included in the Australian Burden of Disease and Injury Study had relatively high disability weights. The inclusion of a fuller range of oral health problems along with revised disability weights would result in oral health accounting for a larger amount of disability than originally estimated

Demographic and indication-specific characteristics have limited association with social network engagement: evidence from 24,954 members of four health care support groups

Background: Digital health social networks (DHSNs) are widespread, and the consensus is that they contribute to wellness by offering social support and knowledge sharing. The success of a DHSN is based on the number of participants and their consistent creation of externalities through the generation of new content. To promote network growth, it would be helpful to identify characteristics of superusers or actors who create value by generating positive network externalities. Objective: The aim of the study was to investigate the feasibility of developing predictive models that identify potential superusers in real time. This study examined associations between posting behavior, 4 demographic variables, and 20 indication-specific variables. Methods: Data were extracted from the custom structured query language (SQL) databases of 4 digital health behavior change interventions with DHSNs. Of these, 2 were designed to assist in the treatment of addictions (problem drinking and smoking cessation), and 2 for mental health (depressive disorder, panic disorder). To analyze posting behavior, 10 models were developed, and negative binomial regressions were conducted to examine associations between number of posts, and demographic and indication-specific variables. Results: The DHSNs varied in number of days active (3658-5210), number of registrants (5049-52,396), number of actors (1085-8452), and number of posts (16,231-521,997). In the sample, all 10 models had low R2 values (.013-.086) with limited statistically significant demographic and indication-specific variables. Conclusions: Very few variables were associated with social network engagement. Although some variables were statistically significant, they did not appear to be practically significant. Based on the large number of study participants, variation in DHSN theme, and extensive time-period, we did not find strong evidence that demographic characteristics or indication severity sufficiently explain the variability in number of posts per actor. Researchers should investigate alternative models that identify superusers or other individuals who create social network externalities

Clinical outcomes resulting from telemedicine interventions: a systematic review

BACKGROUND: The use of telemedicine is growing, but its efficacy for achieving comparable or improved clinical outcomes has not been established in many medical specialties. The objective of this systematic review was to evaluate the efficacy of telemedicine interventions for health outcomes in two classes of application: home-based and office/hospital-based. METHODS: Data sources for the study included deports of studies from the MEDLINE, EMBASE, CINAHL, and HealthSTAR databases; searching of bibliographies of review and other articles; and consultation of printed resources as well as investigators in the field. We included studies that were relevant to at least one of the two classes of telemedicine and addressed the assessment of efficacy for clinical outcomes with data of reported results. We excluded studies where the service did not historically require face-to-face encounters (e.g., radiology or pathology diagnosis). All included articles were abstracted and graded for quality and direction of the evidence. RESULTS: A total of 25 articles met inclusion criteria and were assessed. The strongest evidence for the efficacy of telemedicine in clinical outcomes comes from home-based telemedicine in the areas of chronic disease management, hypertension, and AIDS. The value of home glucose monitoring in diabetes mellitus is conflicting. There is also reasonable evidence that telemedicine is comparable to face-to-face care in emergency medicine and is beneficial in surgical and neonatal intensive care units as well as patient transfer in neurosurgery. CONCLUSIONS: Despite the widespread use of telemedicine in virtually all major areas of health care, evidence concerning the benefits of its use exists in only a small number of them. Further randomized controlled trials must be done to determine where its use is most effective

Loss of lag-response curvilinearity of indices of heart rate variability in congestive heart failure

BACKGROUND: Heart rate variability (HRV) is known to be impaired in patients with congestive heart failure (CHF). Time-domain analysis of ECG signals traditionally relies heavily on linear indices of an essentially non-linear phenomenon. Poincaré plots are commonly used to study non-linear behavior of physiologic signals. Lagged Poincaré plots incorporate autocovariance information and analysis of Poincaré plots for various lags can provide interesting insights into the autonomic control of the heart. METHODS: Using Poincaré plot analysis, we assessed whether the relation of the lag between heart beats and HRV is altered in CHF. We studied the influence of lag on estimates of Poincaré plot indices for various lengths of beat sequence in a public domain data set (PhysioNet) of 29 subjects with CHF and 54 subjects with normal sinus rhythm. RESULTS: A curvilinear association was observed between lag and Poincaré plot indices (SD1, SD2, SDLD and SD1/SD2 ratio) in normal subjects even for a small sequence of 50 beats (p value for quadratic term 3 × 10(-5), 0.002, 3.5 × 10(-5 )and 0.0003, respectively). This curvilinearity was lost in patients with CHF even after exploring sequences up to 50,000 beats (p values for quadratic term > 0.5). CONCLUSION: Since lagged Poincaré plots incorporate autocovariance information, these analyses provide insights into the autonomic control of heart rate that is influenced by the non-linearity of the signal. The differences in lag-response in CHF patients and normal subjects exist even in the face of the treatment received by the CHF patients

A UMLS-based spell checker for natural language processing in vaccine safety

BACKGROUND: The Institute of Medicine has identified patient safety as a key goal for health care in the United States. Detecting vaccine adverse events is an important public health activity that contributes to patient safety. Reports about adverse events following immunization (AEFI) from surveillance systems contain free-text components that can be analyzed using natural language processing. To extract Unified Medical Language System (UMLS) concepts from free text and classify AEFI reports based on concepts they contain, we first needed to clean the text by expanding abbreviations and shortcuts and correcting spelling errors. Our objective in this paper was to create a UMLS-based spelling error correction tool as a first step in the natural language processing (NLP) pipeline for AEFI reports. METHODS: We developed spell checking algorithms using open source tools. We used de-identified AEFI surveillance reports to create free-text data sets for analysis. After expansion of abbreviated clinical terms and shortcuts, we performed spelling correction in four steps: (1) error detection, (2) word list generation, (3) word list disambiguation and (4) error correction. We then measured the performance of the resulting spell checker by comparing it to manual correction. RESULTS: We used 12,056 words to train the spell checker and tested its performance on 8,131 words. During testing, sensitivity, specificity, and positive predictive value (PPV) for the spell checker were 74% (95% CI: 74–75), 100% (95% CI: 100–100), and 47% (95% CI: 46%–48%), respectively. CONCLUSION: We created a prototype spell checker that can be used to process AEFI reports. We used the UMLS Specialist Lexicon as the primary source of dictionary terms and the WordNet lexicon as a secondary source. We used the UMLS as a domain-specific source of dictionary terms to compare potentially misspelled words in the corpus. The prototype sensitivity was comparable to currently available tools, but the specificity was much superior. The slow processing speed may be improved by trimming it down to the most useful component algorithms. Other investigators may find the methods we developed useful for cleaning text using lexicons specific to their area of interest