Impact of quality circles for improvement of asthma care: results of a randomized controlled trial

Contains fulltext : 69846.pdf (publisher's version ) (Closed access)RATIONALE AND AIMS: Quality circles (QCs) are well established as a means of aiding doctors. New quality improvement strategies include benchmarking activities. The aim of this paper was to evaluate the efficacy of QCs for asthma care working either with general feedback or with an open benchmark. METHODS: Twelve QCs, involving 96 general practitioners, were organized in a randomized controlled trial. Six worked with traditional anonymous feedback and six with an open benchmark; both had guided discussion from a trained moderator. Forty-three primary care practices agreed to give out questionnaires to patients to evaluate the efficacy of QCs. RESULTS: A total of 256 patients participated in the survey, of whom 185 (72.3%) responded to the follow-up 1 year later. Use of inhaled steroids at baseline was high (69%) and self-management low (asthma education 27%, individual emergency plan 8%, and peak flow meter at home 21%). Guideline adherence in drug treatment increased (P = 0.19), and asthma steps improved (P = 0.02). Delivery of individual emergency plans increased (P = 0.008), and unscheduled emergency visits decreased (P = 0.064). There was no change in asthma education and peak flow meter usage. High medication guideline adherence was associated with reduced emergency visits (OR 0.24; 95% CI 0.07-0.89). Use of theophylline was associated with hospitalization (OR 7.1; 95% CI 1.5-34.3) and emergency visits (OR 4.9; 95% CI 1.6-14.7). There was no difference between traditional and benchmarking QCs. CONCLUSIONS: Quality circles working with individualized feedback are effective at improving asthma care. The trial may have been underpowered to detect specific benchmarking effects. Further research is necessary to evaluate strategies for improving the self-management of asthma patients

Associations of frailty with health care costs – results of the ESTHER cohort study

Background: The concept of frailty is rapidly gaining attention as an independent syndrome with high prevalence in older adults. Thereby, frailty is often related to certain adverse outcomes like mortality or disability. Another adverse outcome discussed is increased health care utilization. However, only few studies examined the impact of frailty on health care utilization and corresponding costs. The aim of this study was therefore to investigate comprehensively the relationship between frailty, health care utilization and costs. Methods: Cross sectional data from 2598 older participants (57–84 years) recruited in the Saarland, Germany, between 2008 and 2010 was used. Participants passed geriatric assessments that included Fried’s five frailty criteria: weakness, slowness, exhaustion, unintentional weight loss, and physical inactivity. Health care utilization was recorded in the sectors of inpatient treatment, outpatient treatment, pharmaceuticals, and nursing care. Results: Prevalence of frailty (≥3 symptoms) was 8.0 %. Mean total 3-month costs of frail participants were €3659 (4 or 5 symptoms) and €1616 (3 symptoms) as compared to €642 of nonfrail participants (no symptom). Controlling for comorbidity and general socio-demographic characteristics in multiple regression models, the difference in total costs between frail and non-frail participants still amounted to €1917; p < .05 (4 or 5 symptoms) and €680; p < .05 (3 symptoms). Among the 5 symptoms of frailty, weight loss and exhaustion were significantly associated with total costs after controlling for comorbidity. Conclusions: The study provides evidence that frailty is associated with increased health care costs. The analyses furthermore indicate that frailty is an important factor for health care costs independent from pure age and comorbidity. Costs were rather attributable to frailty (and comorbidity) than to age. This stresses that the overlapping concepts of multimorbidity and frailty are both necessary to explain health care use and corresponding costs among older adults

Substantial reduction of inappropriate tablet splitting with computerised decision support: a prospective intervention study assessing potential benefit and harm

Abstract Background Currently ambulatory patients break one in four tablets before ingestion. Roughly 10% of them are not suitable for splitting because they lack score lines or because enteric or modified release coating is destroyed impairing safety and effectiveness of the medication. We assessed impact and safety of computerised decision support on the inappropriate prescription of split tablets. Methods We performed a prospective intervention study in a 1680-bed university hospital. Over a 15-week period we evaluated all electronically composed medication regimens and determined the fraction of tablets and capsules that demanded inappropriate splitting. In a subsequent intervention phase of 15 weeks duration for 10553 oral drugs divisibility characteristics were indicated in the system. In addition, an alert was generated and displayed during the prescription process whenever the entered dosage regimen demanded inappropriate splitting (splitting of capsules, unscored tablets, or scored tablets unsuitable for the intended fragmentation). Results During the baseline period 12.5% of all drugs required splitting and 2.7% of all drugs (257/9545) required inappropriate splitting. During the intervention period the frequency of inappropriate splitting was significantly reduced (1.4% of all drugs (146/10486); p = 0.0008). In response to half of the alerts (69/136) physicians adjusted the medication regimen. In the other half (67/136) no corrections were made although a switch to more suitable drugs (scored tablets, tablets with lower strength, liquid formulation) was possible in 82% (55/67). Conclusion This study revealed that computerised decision support can immediately reduce the frequency of inappropriate splitting without introducing new safety hazards.</p

The impact of potentially inappropriate medication on the development of health care costs and its moderation by the number of prescribed substances. Results of a retrospective matched cohort study.

BACKGROUND:In the growing population of the elderly, drug-related problems are considered an important health care safety issue. One aspect of this is the prescription of potentially inappropriate medication (PIM) which is considered to increase health care costs. OBJECTIVE:Using data from the Health Economics of Potentially Inappropriate Medication (HEPIME) study, we aimed to analyze how the number of prescribed substances moderates the association of PIM use as defined by the German PRISCUS list and health care costs applying a longitudinal perspective. METHODS:An initial number of 6,849,622 insurants aged 65+ of a large German health insurance company were included in a retrospective matched cohort study. Based on longitudinal claims data from the four separate quarters of a 12-month pre-period, 3,860,842 individuals with no exposure to PIM in 2011 were matched to 508,212 exposed individuals. Exposure effects of PIM use on health care costs and the number of prescribed substances were measured based on longitudinal claims data from the four separate quarters of the 12-month post-period. RESULTS:After successful balancing for the development of numerous matching variables during the four quarters of the pre-period, exposed individuals consumed 2.1 additional prescribed substances and had higher total health care costs of 1,237 € when compared to non-exposed individuals in the 1st quarter of the post-period. Controlling for the number of prescribed substances, the difference in total health care costs between both study groups was 401 €. The average effect of one additionally prescribed substance (other than PIM) on total health care costs was increased by an amount of 137 € for those being exposed to a PIM. In quarters 2-4 of the post-period, the differences between both study groups tended to decrease sequentially. CONCLUSIONS:PIM use has an increasing effect on the development of health care costs. This cost-increasing effect of PIM use is moderated by the number of prescribed substances

Health care costs in the elderly in Germany: an analysis applying Andersen’s behavioral model of health care utilization

BACKGROUND: To analyze the association of health care costs with predisposing, enabling, and need factors, as defined by Andersen’s behavioral model of health care utilization, in the German elderly population. METHODS: Using a cross-sectional design, cost data of 3,124 participants aged 57–84 years in the 8-year-follow-up of the ESTHER cohort study were analyzed. Health care utilization in a 3-month period was assessed retrospectively through an interview conducted by trained study physicians at respondents’ homes. Unit costs were applied to calculate health care costs from the societal perspective. Socio-demographic and health-related variables were categorized as predisposing, enabling, or need factors as defined by the Andersen model. Multimorbidity was measured by the Cumulative Illness Rating Scale for Geriatrics (CIRS-G). Mental health status was measured by the SF-12 mental component summary (MCS) score. Sector-specific costs were analyzed by means of multiple Tobit regression models. RESULTS: Mean total costs per respondent were 889 € for the 3-month period. The CIRS-G score and the SF-12 MCS score representing the need factor in the Andersen model were consistently associated with total, inpatient, outpatient and nursing costs. Among the predisposing factors, age was positively associated with outpatient costs, nursing costs, and total costs, and the BMI was associated with outpatient costs. CONCLUSIONS: Multimorbidity and mental health status, both reflecting the need factor in the Andersen model, were the dominant predictors of health care costs. Predisposing and enabling factors had comparatively little impact on health care costs, possibly due to the characteristics of the German social health insurance system. Overall, the variables used in the Andersen model explained only little of the total variance in health care costs

Medication Underuse in Aging Outpatients with Cardiovascular Disease: Prevalence, Determinants, and Outcomes in a Prospective Cohort Study.

Cardiovascular disease is a leading cause of death in older people, and the impact of being exposed or not exposed to preventive cardiovascular medicines is accordingly high. Underutilization of beneficial drugs is common, but prevalence estimates differ across settings, knowledge on predictors is limited, and clinical consequences are rarely investigated.Using data from a prospective population-based cohort study, we assessed the prevalence, determinants, and outcomes of medication underuse based on cardiovascular criteria from Screening Tool To Alert to Right Treatment (START).Medication underuse was present in 69.1% of 1454 included participants (mean age 71.1 ± 6.1 years) and was significantly associated with frailty (odds ratio: 2.11 [95% confidence interval: 1.24-3.63]), body mass index (1.03 [1.01-1.07] per kg/m2), and inversely with the number of prescribed drugs (0.84 [0.79-0.88] per drug). Using this information for adjustment in a follow-up evaluation (mean follow-up time 2.24 years) on cardiovascular and competing outcomes, we found no association of medication underuse with cardiovascular events (fatal and non-fatal) (hazard ratio: 1.00 [0.65-1.56]), but observed a significant association of medication underuse with competing deaths from non-cardiovascular causes (2.52 [1.01-6.30]).Medication underuse was associated with frailty and adverse non-cardiovascular clinical outcomes. This may suggest that cardiovascular drugs were withheld because of serious co-morbidity or that concurrent illness can preclude benefit from cardiovascular prevention. In the latter case, adapted prescribing criteria should be developed and evaluated in those patients

Predictive margins of growth curves for total health care costs in balanced EG and NEG, at mean of the number of prescribed ATC codes (mean 4.8), balanced by weights based on entropy balancing.

<p>Fig is based on fully saturated linear mixture regression model with maximum likelihood estimators with a quadratic term for the number of prescribed ATC codes.</p