The potential savings of using thiazides as the first choice antihypertensive drug: cost-minimisation analysis

BACKGROUND: All clinical practice guidelines recommend thiazides as a first-choice drug for the management of uncomplicated hypertension. Thiazides are also the lowest priced antihypertensive drugs. Despite this, the use of thiazides is much lower than that of other drug-classes. We wanted to estimate the potential for savings if thiazides were used as the first choice drug for the management of uncomplicated hypertension. METHODS: For six countries (Canada, France, Germany, Norway, the UK and the US) we estimated the number of people that are being treated for hypertension, and the proportion of them that are suitable candidates for thiazide-therapy. By comparing this estimate with thiazide prescribing, we calculated the number of people that could switch from more expensive medication to thiazides. This enabled us to estimate the potential drug-cost savings. The analysis was based on findings from epidemiological studies and drug trials, and data on sales and prescribing provided by IMS for the year 2000. RESULTS: For Canada, France, Germany, Norway, the UK and the US the estimated potential annual savings were US$13.8 million, US$37.4 million, US$72.2 million, US$10.7 million, US$119.7 million and US$433.6 million, respectively. CONCLUSIONS: Millions of dollars could be saved each year if thiazides were prescribed for hypertension in place of more expensive drugs. Our calculations are based on conservative assumptions. The potential for savings is likely considerably higher and may be more than US$1 billion per year in the US

A new approach of nonparametric estimation of incidence and lifetime risk based on birth rates and incident events

<p>Abstract</p> <p>Background</p> <p>Incidence and lifetime risk of diabetes are important public health measures. Traditionally, nonparametric estimates are obtained from survey data by means of a Nelson-Aalen estimator which requires data information on both incident events and risk sets from the entire cohort. Such data information is rarely available in real studies.</p> <p>Methods</p> <p>We compare two different approaches for obtaining nonparametric estimates of age-specific incidence and lifetime risk with emphasis on required assumptions. The first and novel approach only considers incident cases occurring within a fixed time window–we have termed this <it>cohort-of-cases </it>data–which is linked explicitly to the birth process in the past. The second approach is the usual Nelson-Aalen estimate which requires knowledge on observed time at risk for the entire cohort and their incident events. Both approaches are used on data on anti-diabetic medications obtained from Odense Pharmacoepidemiological Database, which covers a population of approximately 470,000 over the period 1993–2003. For both methods we investigate if and how incidence rates can be projected.</p> <p>Results</p> <p>Both the new and standard method yield similar sigmoidal shaped estimates of the cumulative distribution function of age-specific incidence. The Nelson-Aalen estimator gives somewhat higher estimates of lifetime risk (15.65% (15.14%; 16.16%) for females, and 17.91% (17.38%; 18.44%) for males) than the estimate based on cohort-of-cases data (13.77% (13.74%; 13.81%) for females, 15.61% (15.58%; 15.65%) for males). Accordingly the projected incidence rates are higher based on the Nelson-Aalen estimate–also too high when compared to observed rates. In contrast, the cohort-of-cases approach gives projections that fit observed rates better.</p> <p>Conclusion</p> <p>The developed methodology for analysis of cohort-of-cases data has potential to become a cost-effective alternative to a traditional survey based study of incidence. To allow more general use of the methodology, more research is needed on how to relax stationarity assumptions.</p

Validating the Johns Hopkins ACG Case-Mix System of the elderly in Swedish primary health care

BACKGROUND: Individualbased measures for comorbidity are of increasing importance for planning and funding health care services. No measurement for individualbased healthcare costs exist in Sweden. The aim of this study was to validate the Johns Hopkins ACG Case-Mix System's predictive value of polypharmacy (regular use of 4 or more prescription medicines) used as a proxy for health care costs in an elderly population and to study if the prediction could be improved by adding variables from a population based study i.e. level of education, functional status indicators and health perception. METHODS: The Johns Hopkins ACG Case-Mix System was applied to primary health care diagnoses of 1402 participants (60–96 years) in a cross-sectional community based study in Karlskrona, Sweden (the Swedish National study on Ageing and Care) during a period of two years before they took part in the study. The predictive value of the Johns Hopkins ACG Case-Mix System was modeled against the regular use of 4 or more prescription medicines, also using age, sex, level of education, instrumental activity of daily living- and measures of health perception as covariates. RESULTS: In an exploratory biplot analysis the Johns Hopkins ACG Case-Mix System, was shown to explain a large part of the variance for regular use of 4 or more prescription medicines. The sensitivity of the prediction was 31.9%, whereas the specificity was 88.5%, when the Johns Hopkins ACG Case-Mix System was adjusted for age. By adding covariates to the model the sensitivity was increased to 46.3%, with a specificity of 90.1%. This increased the number of correctly classified by 5.6% and the area under the curve by 11.1%. CONCLUSION: The Johns Hopkins ACG Case-Mix System is an important factor in measuring comorbidity, however it does not reflect an individual's capability to function despite a disease burden, which has importance for prediction of comorbidity. In this study we have shown that information on such factors, which can be obtained from short questionnaires increases the probability to correctly predict an individual's use of resources, such as medications

Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

<p>Abstract</p> <p>Background</p> <p>In the financing of a national health system, where pharmaceutical spending is one of the main cost containment targets, predicting pharmacy costs for individuals and populations is essential for budget planning and care management. Although most efforts have focused on risk adjustment applying diagnostic data, the reliability of this information source has been questioned in the primary care setting. We sought to assess the usefulness of incorporating pharmacy data into claims-based predictive models (PMs). Developed primarily for the U.S. health care setting, a secondary objective was to evaluate the benefit of a local calibration in order to adapt the PMs to the Spanish health care system.</p> <p>Methods</p> <p>The population was drawn from patients within the primary care setting of Aragon, Spain (n = 84,152). Diagnostic, medication and prior cost data were used to develop PMs based on the Johns Hopkins ACG methodology. Model performance was assessed through r-squared statistics and predictive ratios. The capacity to identify future high-cost patients was examined through c-statistic, sensitivity and specificity parameters.</p> <p>Results</p> <p>The PMs based on pharmacy data had a higher capacity to predict future pharmacy expenses and to identify potential high-cost patients than the models based on diagnostic data alone and a capacity almost as high as that of the combined diagnosis-pharmacy-based PM. PMs provided considerably better predictions when calibrated to Spanish data.</p> <p>Conclusion</p> <p>Understandably, pharmacy spending is more predictable using pharmacy-based risk markers compared with diagnosis-based risk markers. Pharmacy-based PMs can assist plan administrators and medical directors in planning the health budget and identifying high-cost-risk patients amenable to care management programs.</p

Sense of coherence and diabetes: A prospective occupational cohort study

<p>Abstract</p> <p>Background</p> <p>Sense of coherence (SOC) is an individual characteristic related to a positive life orientation leading to effective coping. A weak SOC has been associated with indicators of general morbidity and mortality. However, the relationship between SOC and diabetes has not been studied in prospective design. The present study prospectively examined the relationship between a weak SOC and the incidence of diabetes.</p> <p>Methods</p> <p>The relationship between a weak SOC and the incidence of diabetes was investigated among 5827 Finnish male employees aged 18–65 at baseline (1986). SOC was measured by questionnaire survey at baseline. Data on prescription diabetes drugs from 1987 to 2004 were obtained from the Drug Imbursement Register held by the Social Insurance Institution.</p> <p>Results</p> <p>During the follow-up, 313 cases of diabetes were recorded. A weak SOC was associated with a 46% higher risk of diabetes in participants who had been =<50 years of age on entry into the study. This association was independent of age, education, marital status, psychological distress, self-rated health, smoking status, binge drinking and physical activity. No similar association was observed in older employees.</p> <p>Conclusion</p> <p>The results suggest that besides focusing on well-known risk factors for diabetes, strengthening SOC in employees of =<50 years of age can also play a role in attempts to tackle increasing rates of diabetes.</p

Clinical effectiveness and cost-effectiveness of issuing longer versus shorter duration (3-month vs. 28-day) prescriptions in patients with chronic conditions: systematic review and economic modelling.

BACKGROUND: To reduce expenditure on, and wastage of, drugs, some commissioners have encouraged general practitioners to issue shorter prescriptions, typically 28 days in length; however, the evidence base for this recommendation is uncertain. OBJECTIVE: To evaluate the evidence of the clinical effectiveness and cost-effectiveness of shorter versus longer prescriptions for people with stable chronic conditions treated in primary care. DESIGN/DATA SOURCES: The design of the study comprised three elements. First, a systematic review comparing 28-day prescriptions with longer prescriptions in patients with chronic conditions treated in primary care, evaluating any relevant clinical outcomes, adherence to treatment, costs and cost-effectiveness. Databases searched included MEDLINE (PubMed), EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science and Cochrane Central Register of Controlled Trials. Searches were from database inception to October 2015 (updated search to June 2016 in PubMed). Second, a cost analysis of medication wastage associated with < 60-day and ≥ 60-day prescriptions for five patient cohorts over an 11-year period from the Clinical Practice Research Datalink. Third, a decision model adapting three existing models to predict costs and effects of differing adherence levels associated with 28-day versus 3-month prescriptions in three clinical scenarios. REVIEW METHODS: In the systematic review, from 15,257 unique citations, 54 full-text papers were reviewed and 16 studies were included, five of which were abstracts and one of which was an extended conference abstract. None was a randomised controlled trial: 11 were retrospective cohort studies, three were cross-sectional surveys and two were cost studies. No information on health outcomes was available. RESULTS: An exploratory meta-analysis based on six retrospective cohort studies suggested that lower adherence was associated with 28-day prescriptions (standardised mean difference -0.45, 95% confidence interval -0.65 to -0.26). The cost analysis showed that a statistically significant increase in medication waste was associated with longer prescription lengths. However, when accounting for dispensing fees and prescriber time, longer prescriptions were found to be cost saving compared with shorter prescriptions. Prescriber time was the largest component of the calculated cost savings to the NHS. The decision modelling suggested that, in all three clinical scenarios, longer prescription lengths were associated with lower costs and higher quality-adjusted life-years. LIMITATIONS: The available evidence was found to be at a moderate to serious risk of bias. All of the studies were conducted in the USA, which was a cause for concern in terms of generalisability to the UK. No evidence of the direct impact of prescription length on health outcomes was found. The cost study could investigate prescriptions issued only; it could not assess patient adherence to those prescriptions. Additionally, the cost study was based on products issued only and did not account for underlying patient diagnoses. A lack of good-quality evidence affected our decision modelling strategy. CONCLUSIONS: Although the quality of the evidence was poor, this study found that longer prescriptions may be less costly overall, and may be associated with better adherence than 28-day prescriptions in patients with chronic conditions being treated in primary care. FUTURE WORK: There is a need to more reliably evaluate the impact of differing prescription lengths on adherence, on patient health outcomes and on total costs to the NHS. The priority should be to identify patients with particular conditions or characteristics who should receive shorter or longer prescriptions. To determine the need for any further research, an expected value of perfect information analysis should be performed. STUDY REGISTRATION: This study is registered as PROSPERO CRD42015027042. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Discrepancies between prescribed daily doses and WHO defined daily doses of antibacterials at a university hospital

International audienceAIMS: The defined daily doses (DDD) defined by the WHO are widely used as an indicator to measure antibiotic use in the hospital setting. However, discrepancies exist between countries in terms of antibiotic dosage. The aim of the present study was to compare, for each antibacterial agent available at our university hospital, the prescribed daily doses (PDD) with the DDD. METHODS: Data were extracted from the pharmacy computer system. Antibiotic use was expressed in DDD per 1000 patient days. We also calculated the ratio of number of DDD:number of treatment-days and estimated the average PDD for each antibiotic and route of administration. RESULTS: The average PDD did not correspond to the DDD for many classes of antibiotics. If fluoroquinolones and cephalosporins were prescribed at a dosage close to the DDD, other antimicrobial classes such as penicillins, aminoglycosides or macrolides were not. Overall, the number of DDD overestimated the number of treatment days by 40%. For the most consumed antibiotic at our hospital, i.e. oral amoxicillin-clavulanic acid, the PDD was three times the DDD. CONCLUSIONS: Our study shows that, except for the fluoroquinolones and the cephalosporins, the number of DDD did not correctly reflect the number of antibiotic treatment days at our hospital. This does not invalidate the systematic approach of the WHO and hospitals should use the DDDs to make national and international comparisons of their antibiotic use. However, each hospital should define and validate its own indicators to describe the local exposures to antibiotics and to study the relationship with resistance