Impact of a complex health services intervention in long-term care nursing homes on 3-year overall survival: results from the CoCare study.

BACKGROUND: The Coordinated medical Care (CoCare) project aimed to improve the quality of medical care in nursing homes by optimizing collaboration between nurses and physicians. We analyze the impact of the CoCare intervention on overall survival. METHODS: The effect of time-varying treatment on 3-year overall survival was analyzed with treatment as time-varying covariate within the entire cohort. To reduce bias due to non-random assignment to treatment groups, regression adjustment was applied. Therefore, age, sex, and level of care were used as potential confounders. RESULTS: The study population consisted of 8,893 nursing home residents (NHRs), of which 1,330 participated in the CoCare intervention. The three-year overall survival was 49.8% in the entire cohort. NHRs receiving the intervention were associated with a higher survival probability compared to NHRs of the control group. In a univariable cox model with time-dependent treatment, the intervention was associated with a hazard ratio of 0.70 [95%CI 0.56-0.87, p = 0.002]. After adjustment for age, sex and level of care, the hazard ratio increased to 0.82 but was still significant [95%CI 0.71-0.96, p = 0.011]. CONCLUSION: The analysis shows that optimizing collaboration between nurses and physicians leads to better survival of NHRs in Germany. This adds to the already published favorable cost-benefit ratio of the CoCare intervention and shows that a routine implementation of optimized collaboration between nurses and physicians is highly recommended.

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes.

BACKGROUND: Although pharmaceutical expenditures have been rising for decades, the question of their drivers remains unclear, and long-term projections of pharmaceutical spending are still scarce. We use a Markov approach considering different cost-risk groups to show the possible range of future drug spending in Germany and illustrate the influence of various determinants on pharmaceutical expenditure. METHODS: We compute different medium and long-term projections of pharmaceutical expenditure in Germany up to 2060 and compare extrapolations with constant shares, time-to-death scenarios, and Markov modeling based on transition probabilities. Our modeling is based on data from a large statutory sickness fund covering around four million insureds. We divide the population into six risk groups according to their share of total pharmaceutical expenditures, determine their cost growth rates, survival and transition probabilities, and compute different scenarios related to changes in life expectancy or spending trends in different cost-risk groups. RESULTS: If the spending trends in the high-cost groups continue, per-capita expenditure will increase by over 40% until 2040. By 2060, pharmaceutical expenditures could more than double, even if these groups would not benefit from rising life expectancy. By contrast, the isolated effect of demographic change would "only" lead to a long-term increase of around 15%. CONCLUSION: The long-term development of pharmaceutical spending in Germany will depend mainly on future expenditure and life expectancy trends of particularly high-cost patients. Thus, appropriate pricing of new expensive pharmaceuticals is essential for the sustainability of the German healthcare system.

Healing, surviving, or dying? - projecting the German future disease burden using a Markov illness-death model.

BACKGROUND: In view of the upcoming demographic transition, there is still no clear evidence on how increasing life expectancy will affect future disease burden, especially regarding specific diseases. In our study, we project the future development of Germany's ten most common non-infectious diseases (arthrosis, coronary heart disease, pulmonary, bronchial and tracheal cancer, chronic obstructive pulmonary disease, cerebrovascular diseases, dementia, depression, diabetes, dorsal pain and heart failure) in a Markov illness-death model with recovery until 2060. METHODS: The disease-specific input data stem from a consistent data set of a major sickness fund covering about four million people, the demographic components from official population statistics. Using six different scenarios concerning an expansion and a compression of morbidity as well as increasing recovery and effective prevention, we can show the possible future range of disease burden and, by disentangling the effects, reveal the significant differences between the various diseases in interaction with the demographic components. RESULTS: Our results indicate that, although strongly age-related diseases like dementia or heart failure show the highest relative increase rates, diseases of the musculoskeletal system, such as dorsal pain and arthrosis, still will be responsible for the majority of the German population's future disease burden in 2060, with about 25-27 and 13-15 million patients, respectively. Most importantly, for almost all considered diseases a significant increase in burden of disease can be expected even in case of a compression of morbidity. CONCLUSION: A massive case-load is emerging on the German health care system, which can only be alleviated by more effective prevention. Immediate action by policy makers and health care managers is needed, as otherwise the prevalence of widespread diseases will become unsustainable from a capacity point-of-view.

Adverse selection in the German Health Insurance System - the case of civil servants.

At the beginning of their career, civil servants in Germany can choose between the social health insurance (SHI) system and a private plan combined with a direct reimbursement of the government of up to 70 percent. Most civil servants chose the latter, not only but also because they have to cover all contributions in the social system themselves, while regular employees get nearly 50 percent from their employers. The city state of Hamburg decided to change the system by paying half of the contributions if civil servants choose the social plan. We use a stochastic microsimulation model to analyse which socio-economic types of civil servants could benefit from the Hamburg plan and if this changes the mix of insured persons in the SHI system. Our results show that low income and high morbidity types as well as families have a substantially higher incentive to choose SHI. This reform might thereby increase the adverse selection of high risk cases towards SHI.

[The future development of dementia diseases in Germany-a comparison of different forecast models]. / Die zukünftige Entwicklung von Demenzerkrankungen in Deutschland ­ ein Vergleich unterschiedlicher Prognosemodelle.

Dementia is one of the most frequent diseases of people aged 65 and older. As a result of the upcoming demographic transition, a significant increase is expected to the current number of around 1.7 million dementia patients. A precise estimate of this increase is especially important for decision-makers and payers to the health-care system. This study examined the effects of different assumptions on the future frequency of disease using a time-discrete Markov model with population-related and disease-specific components. Based on health insurers' administrative data from AOK Baden-Württemberg, we determined age- and gender-specific prevalence rates, incidence rates, and mortality differences of dementia patients and combined them with demographic components from German population statistics. As a result, our Markov model showed a 20 to 25% higher number of dementia patients in 2030, compared to the results of the status quo projection applied in most previous studies, with the assumption of constant prevalence rates over time. Hence, our results indicate that even in the medium term payers will have to face significant increases in dementia-related health expenditures. By 2060, the number of dementia patients in Germany would rise to 3.3 million assuming a further increase to life expectancy and constant incidence rates over time. The assumption of a compression of the morbidity would reduce this number to 2.6 million.

Results of a randomized controlled trial analyzing telemedically supported case management in the first year after living donor kidney transplantation - a budget impact analysis from the healthcare perspective.

ᅟ: We analyze one-year costs and savings of a telemedically supported case management program after kidney transplantation from the perspective of the German Healthcare System. Recipients of living donor kidney transplantation (N = 46) were randomly allocated to either (1) standard aftercare or (2) standard aftercare plus additional telemedically supported case management. A range of cost figures of each patient's medical service utilization were calculated at month 3, 6 and 12 and analyzed using two-part regression models. In comparison to standard aftercare, patients receiving telemedically supported case management are associated with substantial lower costs related to unscheduled hospitalizations (mean difference: €3,417.46 per patient for the entire one-year period, p = 0.003). Taking all cost figures into account, patients receiving standard aftercare are associated, on average, with one-year medical service utilization costs of €10,449.28, while patients receiving telemedically supported case management are associated with €5,504.21 of costs (mean difference: € 4,945.07 per patient, p < 0.001). With estimated expenditures of €3,001.5 for telemedically supported case management of a single patient, we determined a mean difference of €1,943.57, but this result is not statistically significant (p = 0.128). Sensitivity analyses show that the program becomes cost-neutral at around ten participating patients, and was beneficial starting at 15 patients. Routine implementation of telemedically supported case management in German medium and high-volume transplant centers would result in annual cost savings of €791,033 for the German healthcare system. Patients with telemedically supported case management showed a lower utilization of medical services as well as better medical outcomes. Therefore, such programs should be implemented in medium and high-volume transplant centers. TRIAL REGISTRATION: DRKS00007634 ( http://www.drks.de/DRKS00007634 ).

[The German Pharmaceutical Market Reorganization Act (AMNOG) from an economic point of view]. / Das Arzneimittelmarktneuordnungsgesetz (AMNOG) aus ökonomischer Sicht.

Since the introduction of early benefit assessments in Germany, prices for new medicinal products are set in accordance with the "degree of additional benefit." The major aim of the present work is to point out the economic rationale for the definition of a regulatory price for patent-protected drugs. With regard to the economic objectives of efficient allocation of resources, reducing information asymmetries, and promoting high-value innovation, the applied benefit assessments represent major progress in the German health care sector. In addition to the multifaceted criticism of procedural details, there is a general risk that the institutions involved are lagging behind societal preferences. In this case, early benefit assessments may lead to suboptimal results. The pharmaceutical industry's ability to innovate, on the other hand, may be seen to be a result of the interaction between national benefit assessments and the research activities of internationally oriented drug manufacturers. Accordingly, recent trends toward the implementation of national early benefit assessments in combination with international reference pricing may be seen to be critical; however, Germany is merely following the trend of other countries.