Removing Dust From the German Health Care System by Introducing Health Apps Into Standard Care: Semistructured Interview Study.

BACKGROUND: In 2019, Germany launched the Digital Healthcare Act. The reform enables physicians to prescribe health apps as treatments to their statutory-insured patients. OBJECTIVE: We aimed to determine the extent to which the integration of health apps into standard care could be considered beneficial and which aspects of the regulation could still be improved. METHODS: We conducted a semistructured interview study with 23 stakeholders in Germany and analyzed them thematically. We used descriptive coding for the first-order codes and pattern coding for the second-order codes. RESULTS: We created 79 first-order codes and 9 second-order codes following the interview study. Most stakeholders argued that the option of prescribing health apps could improve treatment quality. CONCLUSIONS: The inclusion of health apps into German standard care could improve the quality of treatment by expanding treatment portfolios. The educational elements of the apps might additionally lead to more patient emancipation through a better understanding of personal conditions. Location and time flexibility are the biggest advantages of the new technologies, but they also raise the most significant concerns for stakeholders because app use requires personal initiative and self-motivation. Overall, stakeholders agree that the Digital Healthcare Act has the potential to remove dust from the German health care system.

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.

Effects of Hospital Digitization on Clinical Outcomes and Patient Satisfaction: Nationwide Multiple Regression Analysis Across German Hospitals.

BACKGROUND: The adoption of health information technology (HIT) by health care providers is commonly believed to improve the quality of care. Policy makers in the United States and Germany follow this logic and deploy nationwide HIT adoption programs to fund hospital investments in digital technologies. However, scientific evidence for the beneficial effects of HIT on care quality at a national level remains mostly US based, is focused on electronic health records (EHRs), and rarely accounts for the quality of digitization from a hospital user perspective. OBJECTIVE: This study aimed to examine the effects of digitization on clinical outcomes and patient experience in German hospitals. Hence, this study adds to the small stream of literature in this field outside the United States. It goes beyond assessing the effects of mere HIT adoption and also considers user-perceived HIT value. In addition, the impact of a variety of technologies beyond EHRs was examined. METHODS: Multiple linear regression models were estimated using emergency care outcomes, elective care outcomes, and patient satisfaction as dependent variables. The adoption and user-perceived value of HIT represented key independent variables, and case volume, hospital size, ownership status, and teaching status were included as controls. Care outcomes were captured via risk-adjusted, observed-to-expected outcome ratios for patients who had stroke, myocardial infarction, or hip replacement. The German Patient Experience Questionnaire of Weisse Liste provided information on patient satisfaction. Information on the adoption and user-perceived value of 10 subdomains of HIT and EHRs was derived from the German 2020 Healthcare IT Report. RESULTS: Statistical analysis was based on an overall sample of 383 German hospitals. The analyzed data set suggested no significant effect of HIT or EHR adoption on clinical outcomes or patient satisfaction. However, a higher user-perceived value or quality of the installed tools did improve outcomes. Emergency care outcomes benefited from user-friendly overall digitization (ß=-.032; P=.04), which was especially driven by the user-friendliness of admission HIT (ß=-.023; P=.07). Elective care outcomes were positively impacted by user-friendly EHR installations (ß=-.138; P=.008). Similarly, the results suggested user-friendly, overall digitization to have a moderate positive effect on patient satisfaction (ß=-.009; P=.01). CONCLUSIONS: The results of this study suggest that hospital digitization is not an end in itself. Policy makers and hospitals are well advised to not only focus on the mere adoption of digital technologies but also continuously work toward digitization that is perceived as valuable by physicians and nurses who rely on it every day. Furthermore, hospital digitization strategies should consider that the assumed benefits of single technologies are not realized across all care domains.

Physicians' preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists.

BACKGROUND: Artificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologists. The goal was to generate insights for tool providers and policymakers regarding the development and funding of ideally designed and priced tools. Ultimately, healthcare systems can only benefit from quality enhancing AI when provider adoption is considered. METHODS: Since there is no established market for AI-based assistance tools in radiology yet, a discrete choice experiment was conducted. Respondents from the two major German professional radiology associations chose between hypothetical tools composed of five attributes and a no-choice option. The attributes included: provider, application, quality impact, time savings and price. A conditional logit model was estimated identifying preferences for attribute levels, the no-choice option, and significant subject-related interaction effects. RESULTS: 114 respondents were included for analysis of which 46% were already using an AI-based assistance tool. Average adoption probability for an AI-based tool was 81% (95% CI 77.1% - 84.4%). Radiologists preferred a tool that assists in routine diagnostics performing at above-radiologist-level quality and saves 50% in diagnostics time at a price-point of €3 per study. The provider is not a significant factor in the decisions. Time savings were considered more important than quality improvements (i.e., detecting more anomalies). CONCLUSIONS: Radiologists are overall willing to invest in AI-based assistance tools. Development, funding, and research regarding these tools should, however, consider providers' preferences for features of immediate everyday and economic relevance like time savings to optimize adoption.

Call (and pay) the midwife: A discrete choice experiment on mothers' preferences and their willingness to pay for midwifery care.

BACKGROUND: Mothers in Germany are entitled to midwifery care; however, they face a lack of skilled professionals. While the reliability of the access to midwifery is of great public interest, we know little about clients' preferences. OBJECTIVES: We conduct a discrete choice experiment to study preferences and willingness to accept copayment for the entire scope of midwifery care (pregnancy, delivery, and postnatal). Thereby, we aim to provide policy recommendations for priority settings in times of scarcity. Furthermore, we evaluate to what extent midwives' education matters to parents and assess the degree of support for the latest Midwifery Reform Act that transfers education from vocational schools to universities. DESIGN: Discrete choice experiment with separated adaptive dual response. SETTINGS: Online Survey promoted through Facebook to parents in Germany. RESPONDENTS: 2080 respondents completed the experiment. They all have or are expecting at least one natural child, mainly born between 2018 and 2020 (87%). The average respondent is female (99%), 33 years old, with a university degree (50%). METHODS: We use a d-optimal fractional factorial design and obtain individual parameter estimates through a Multinomial Logit analysis with Hierarchical Bayes estimation techniques. We calculate willingness to pay and importance weights and simulate uptake probabilities for different packages of care. To avoid extreme choice behavior, we apply separated adaptive dual response. RESULTS: Home visits during the postnatal phase are most important (importance weight 50%); online support is demanded when no personal support is available. We find that 1:1 care during delivery is highly preferred, but one midwife supporting two women intrapartum is still acceptable. The midwife´s education plays a minor role with an importance weight of 3%; however, we find a preference for midwives trained at vocational schools rather than at universities. CONCLUSIONS: In times of scarcity, postnatal care in the form of home visits should be prioritized over pregnancy counseling, and online services should be promoted as an add-on but not as a substitute for personal support. There is a high level of willingness to accept co-financing to ensure the availability of services usually covered by health insurance.

Pricing through health apps generated data-Digital dividend as a game changer: Discrete choice experiment.

OBJECTIVES: The objective of this paper is to study under which circumstances wearable and health app users would accept a compensation payment, namely a digital dividend, to share their self-tracked health data. METHODS: We conducted a discrete choice experiment alternative, a separated adaptive dual response. We chose this approach to reduce extreme response behavior, considering the emotionally-charged topic of health data sales, and to measure willingness to accept. Previous experiments in lab settings led to demands for high monetary compensation. After a first online survey and two pre-studies, we validated four attributes for the final online study: monthly bonus payment, stakeholder handling the data (e.g., health insurer, pharmaceutical or medical device companies, universities), type of data, and data sales to third parties. We used a random utility framework to evaluate individual choice preferences. To test the expected prices of the main study for robustness, we assigned respondents randomly to one of two identical questionnaires with varying price ranges. RESULTS: Over a period of three weeks, 842 respondents participated in the main survey, and 272 respondents participated in the second survey. The participants considered transparency about data processing and no further data sales to third parties as very important to the decision to share data with different stakeholders, as well as adequate monetary compensation. Price expectations resulting from the experiment were high; pharmaceutical and medical device companies would have to pay an average digital dividend of 237.30€/month for patient generated health data of all types. We also observed an anchor effect, which means that people formed price expectations during the process and not ex ante. We found a bimodal distribution between relatively low price expectations and relatively high price expectations, which shows that personal data selling is a divisive societal issue. However, the results indicate that a digital dividend could be an accepted economic incentive system to gather large-scale, self-tracked data for research and development purposes. After the COVID-19 crisis, price expectations might change due to public sensitization to the need for big data research on patient generated health data. CONCLUSION: A continuing success of existing data donation models is highly unlikely. The health care sector needs to develop transparency and trust in data processing. An adequate digital dividend could be an effective long-term measure to convince a diverse and large group of people to share high-quality, continuous data for research purposes.

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.

Economic Value of Data and Analytics for Health Care Providers: Hermeneutic Systematic Literature Review.

BACKGROUND: The benefits of data and analytics for health care systems and single providers is an increasingly investigated field in digital health literature. Electronic health records (EHR), for example, can improve quality of care. Emerging analytics tools based on artificial intelligence show the potential to assist physicians in day-to-day workflows. Yet, single health care providers also need information regarding the economic impact when deciding on potential adoption of these tools. OBJECTIVE: This paper examines the question of whether data and analytics provide economic advantages or disadvantages for health care providers. The goal is to provide a comprehensive overview including a variety of technologies beyond computer-based patient records. Ultimately, findings are also intended to determine whether economic barriers for adoption by providers could exist. METHODS: A systematic literature search of the PubMed and Google Scholar online databases was conducted, following the hermeneutic methodology that encourages iterative search and interpretation cycles. After applying inclusion and exclusion criteria to 165 initially identified studies, 50 were included for qualitative synthesis and topic-based clustering. RESULTS: The review identified 5 major technology categories, namely EHRs (n=30), computerized clinical decision support (n=8), advanced analytics (n=5), business analytics (n=5), and telemedicine (n=2). Overall, 62% (31/50) of the reviewed studies indicated a positive economic impact for providers either via direct cost or revenue effects or via indirect efficiency or productivity improvements. When differentiating between categories, however, an ambiguous picture emerged for EHR, whereas analytics technologies like computerized clinical decision support and advanced analytics predominantly showed economic benefits. CONCLUSIONS: The research question of whether data and analytics create economic benefits for health care providers cannot be answered uniformly. The results indicate ambiguous effects for EHRs, here representing data, and mainly positive effects for the significantly less studied analytics field. The mixed results regarding EHRs can create an economic barrier for adoption by providers. This barrier can translate into a bottleneck to positive economic effects of analytics technologies relying on EHR data. Ultimately, more research on economic effects of technologies other than EHRs is needed to generate a more reliable evidence base.

Potential Benefits and Risks Resulting From the Introduction of Health Apps and Wearables Into the German Statutory Health Care System: Scoping Review.

BACKGROUND: Germany is the first country worldwide that has introduced a digital care act as an incentive system to enhance the use of digital health devices, namely health apps and wearables, among its population. The act allows physicians to prescribe statutory financed and previously certified health apps and wearables to patients. This initiative has the potential to improve treatment quality through better disease management and monitoring. OBJECTIVE: The aim of this paper was to outline the key concepts related to the potential risks and benefits discussed in the current literature about health apps and wearables. Furthermore, this study aimed to answer the research question: Which risks and benefits may result from the implementation of the digital care act in Germany? METHODS: We conducted the scoping study by searching the databases PubMed, Google Scholar, and JMIR using the keywords health apps and wearables. We discussed 55 of 136 identified articles published in the English language from 2015 to March 2019 in this paper using a qualitative thematic analysis approach. RESULTS: We identified four key themes within the articles: Effectivity of health apps and wearables to improve health; users of health apps and wearables; the potential of bring-your-own, self-tracked data; and concerns and data privacy risks. Within these themes, we identified three main stages of benefits for the German health care system: Usage of health apps and wearables; continuing to use health apps and wearables; and sharing bring-your-own; self-tracked data with different agents in the health care sector. CONCLUSIONS: The digital care act could lead to an improvement in treatment quality through better patient monitoring, disease management, personalized therapy, and better health education. However, physicians should play an active role in recommending and supervising health app use to reach digital-illiterate or health-illiterate people. Age must not be an exclusion criterion. Yet, concerns about data privacy and security are very strong in Germany. Transparency about data processing should be provided at all times for continuing success of the digital care act in Germany.

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.

Resistance Elasticity of Antibiotic Demand in Intensive Care.

The emergence and spread of antimicrobial resistance (AMR) is still an unresolved problem worldwide. In intensive care units (ICUs), first-line antibiotic therapy is highly standardized and widely empiric while treatment failure because of AMR often has severe consequences. Simultaneously, there is a limited number of reserve antibiotics, whose prices and/or side effects are substantially higher than first-line therapy. This paper explores the implications of resistance-induced substitution effects in ICUs. The extent of such substitution effects is shown in a dynamic fixed effect regression analysis using a panel of 66 German ICUs with monthly antibiotic use and resistance data between 2001 and 2012. Our findings support the hypothesis that demand for reserve antibiotics substantially increases when resistance towards first-line agents rises. For some analyses the lagged effect of resistance is also significant, supporting the conjecture that part of the substitution effect is caused by physicians changing antibiotic choices in empiric treatment by adapting their resistance expectation to new information on resistance prevalence. The available information about resistance rates allows physicians to efficiently balance the trade-off between exacerbating resistance and ensuring treatment success. However, resistance-induced substitution effects are not free of charge. These effects should be considered an indirect burden of AMR. Copyright © 2016 John Wiley & Sons, Ltd.

Societal savings in patients with advanced non-squamous non-small-cell lung cancer receiving bevacizumab-based versus non-bevacizumab-based treatments in France, Germany, Italy, and Spain.

BACKGROUND: The purpose of this study was to investigate the savings accrued using bevacizumab-based treatment for non-small-cell lung cancer from the societal perspective, taking only public costs into account, in France, Germany, Italy, and Spain. METHODS: Societal costs were estimated by collecting and analyzing labor costs, carer costs, sickness benefits, disability benefits, and home care benefits. Cost inputs were derived from publicly available databases or from the published literature. Expert opinion was only used if no other source was available. Efficacy data from two randomized clinical trials were used. The time horizon in the health economic model was lifetime. Efficacy and costs were discounted by 3.5%. All main model parameters were tested in deterministic and probabilistic sensitivity analyses. RESULTS: Mean incremental savings to society per patient ranged from €2277 in Italy to €4461 in Germany. The results were most sensitive to the change in proportion of patients working fulltime and the proportion of patients who were able to return to work. CONCLUSION: This analysis shows that bevacizumab-based treatment in non-small-cell lung cancer is associated with more savings to society compared to standard chemotherapy in terms of increased productivity and decreased social benefits paid to patients who are able to work in France, Germany, Italy, and Spain.

Two time-series analyses of the impact of antibiotic consumption and alcohol-based hand disinfection on the incidences of nosocomial methicillin-resistant Staphylococcus aureus infection and Clostridium difficile infection.

OBJECTIVE: To determine the impact of antibiotic consumption and alcohol-based hand disinfection on the incidences of nosocomial methicillin-resistant Staphylococcus aureus (MRSA) infection and Clostridium difficile infection (CDI). METHODS: Two multivariate time-series analyses were performed that used as dependent variables the monthly incidences of nosocomial MRSA infection and CDI at the Freiburg University Medical Center during the period January 2003 through October 2007. The volume of alcohol-based hand rub solution used per month was quantified in liters per 1,000 patient-days. Antibiotic consumption was calculated in terms of the number of defined daily doses per 1,000 patient-days per month. RESULTS: The use of alcohol-based hand rub was found to have a significant impact on the incidence of nosocomial MRSA infection (P< .001). The multivariate analysis (R2=0.66) showed that a higher volume of use of alcohol-based hand rub was associated with a lower incidence of nosocomial MRSA infection. Conversely, a higher level of consumption of selected antimicrobial agents was associated with a higher incidence of nosocomial MRSA infection. This analysis showed this relationship was the same for the use of second-generation cephalosporins (P= .023), third-generation cephalosporins (P= .05), fluoroquinolones (P= .01), and lincosamides (P= .05). The multivariate analysis (R2=0.55) showed that a higher level of consumption of third-generation cephalosporins (P= .008), fluoroquinolones (P= .084), and/or macrolides (P= .007) was associated with a higher incidence of CDI. A correlation with use of alcohol-based hand rub was not detected. CONCLUSION: In 2 multivariate time-series analyses, we were able to show the impact of hand hygiene and antibiotic use on the incidence of nosocomial MRSA infection, but we found no association between hand hygiene and incidence of CDI.

The impact of antimicrobial drug consumption and alcohol-based hand rub use on the emergence and spread of extended-spectrum beta-lactamase-producing strains: a time-series analysis.

BACKGROUND: The aim of this study was to explore the temporal relationship between the consumption of different antibiotics, alcohol-based hand disinfection and the incidence of nosocomial bacterial strains producing extended-spectrum beta-lactamases (ESBLs). METHODS: Time-series analysis was performed based on monthly data available from January 2005 to October 2007. The incidence of nosocomial ESBL (cases/1000 patient-days) was regressed on the different antibiotic agents and the volume of alcohol-based hand rub orders. Antibiotic consumption was defined as monthly defined daily doses (DDD)/1000 patient-days, while alcohol-based hand rub was quantified in litres/1000 patient-days. RESULTS: The multivariate analysis showed that using alcohol-based hand rub for hand disinfection had a significant influence on the ESBL incidence (P = 0.002). A higher volume of alcohol-based hand rub use was subsequently associated with a lower incidence of ESBL-producing strains. Additionally, the model showed that temporal increase in the use of third-generation cephalosporins (P = 0.022) and fluoroquinolones (P = 0.001) is, after a time lag of up to 3 months, followed by temporal variations in the incidence of nosocomial ESBLs. Furthermore, the incidence of patients admitted with ESBL was also shown to have an influence on the incidence of nosocomial ESBLs (P < 0.001). The final model explained 75% of the monthly variations in the incidence of nosocomial ESBLs. CONCLUSIONS: The analysis identifies selective pressure caused by the use of different antimicrobial agents as a driving factor in the emergence and spread of ESBLs. Furthermore, the study confirms that hand disinfection is key to the prevention of nosocomial ESBLs.

Optional deductibles in social health insurance systems: findings from Germany.

A fundamental aspect of the German health insurance system is the principle of solidarity. At the same time, it is possible for certain socio-economic groups to opt out of the otherwise compulsory system. To determine whether rates incorporating deductibles are compatible with the principles of solidarity and have the ability to heighten the appeal of statutory health insurance (SHI) funds compared with private health insurance companies, Germany's third largest SHI fund, Techniker Krankenkasse, implemented a pilot scheme involving the use of deductibles. Preliminary scientific evaluations of the pilot scheme indicate three main results for these deductibles: Firstly, they are compatible with the principles of solidarity in the statutory health insurance system; secondly, they provide an effective means of preventing defection to private health insurance companies and thirdly, they reduced the volume of insurance claims (moral hazard).