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Adoption and learning across hospitals: The case of a revenue-generating practice.

ABSTRACT: Performance-raising practices tend to diffuse slowly in the health care sector. To understand how incentives drive adoption, I study a practice that generates revenue for hospitals: submitting detailed documentation about patients. After a 2008 reform, hospitals could raise their Medicare revenue over 2% by always specifying a patient's type of heart failure. Hospitals only captured around half of this revenue, indicating that large frictions impeded takeup. Exploiting the fact that many doctors practice at multiple hospitals, I find that four-fifths of the dispersion in adoption reflects differences in the ability of hospitals to extract documentation from physicians. A hospital's adoption of coding is robustly correlated with its heart attack survival rate and its use of inexpensive survival-raising care. Hospital-physician integration and electronic medical records are also associated with adoption. These findings highlight the potential for institution-level frictions, including agency conflicts, to explain variations in health care performance across providers.

SUBMITTER: Sacarny A

PROVIDER: S-EPMC9175183 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Adoption and learning across hospitals: The case of a revenue-generating practice.

Sacarny Adam A

Journal of health economics 20180619

Performance-raising practices tend to diffuse slowly in the health care sector. To understand how incentives drive adoption, I study a practice that generates revenue for hospitals: submitting detailed documentation about patients. After a 2008 reform, hospitals could raise their Medicare revenue over 2% by always specifying a patient's type of heart failure. Hospitals only captured around half of this revenue, indicating that large frictions impeded takeup. Exploiting the fact that many doctors ...[more]

PMID: 30007212

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Project description:BackgroundDietetics mobile health apps provide lifestyle tracking and support on demand. Mobile health has become a new trend for health service providers through which they have been shifting their services from clinical consultations to online apps. These apps usually offer basic features at no cost and charge a premium for advanced features. Although diet apps are now more common and have a larger user base, in general, there is a gap in literature addressing why users intend to use diet apps. We used Diyetkolik, Turkey's most widely used online dietetics platform for 7 years, as a case study to understand the behavioral intentions of users.ObjectiveThe aim of this study was to investigate the factors that influence the behavioral intentions of users to adopt and use mobile health apps. We used the Technology Acceptance Model and extended it by exploring other factors such as price-value, perceived risk, and trust factors in order to assess the technology acceptance of users.MethodsWe conducted quantitative research on the Diyetkolik app users by using random sampling. Valid data samples gathered from 658 app users were analyzed statistically by applying structural equation modeling.ResultsStatistical findings suggested that perceived usefulness (P<.001), perceived ease of use (P<.001), trust (P<.001), and price-value (P<.001) had significant relationships with behavioral intention to use. However, no relationship between perceived risk and behavioral intention was found (P=.99). Additionally, there was no statistical significance for age (P=.09), gender (P=.98), or previous app use experience (P=.14) on the intention to use the app.ConclusionsThis research is an invaluable addition to Technology Acceptance Model literature. The results indicated that 2 external factors (trust and price-value) in addition to Technology Acceptance Model factors showed statistical relevance with behavioral intention to use and improved our understanding of user acceptance of a mobile health app. The third external factor (perceived risk) did not show any statistical relevance regarding behavioral intention to use. Most users of the Diyetkolik dietetics app were hesitant in purchasing dietitian services online. Users should be frequently reassured about the security of the platform and the authenticity of the platform's dietitians to ensure that users' interactions with the dietitians are based on trust for the platform and the brand.

Project description:BackgroundDespite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce.ObjectiveWe performed an experimental vignette study to investigate how four factors related to the business model of an mHealth app affect its adoption and users' willingness to pay: (1) the revenue model (ie, sharing data with third parties vs accepting advertisements); (2) the data protection model (General Data Protection Regulation [GDPR]-compliant data handling vs nonGDPR-compliant data handling); (3) the recommendation model (ie, doctor vs patient recommendation); and (4) the provider model (ie, pharmaceutical vs medical association provider). In addition, health consciousness, health information orientation, and electronic health literacy were explored as intrapersonal predictors of adoption.MethodsWe conducted an experimental study in three countries, Spain (N=800), Germany (N=800), and the Netherlands (N=416), to assess the influence of multiple business models and intrapersonal characteristics on the willingness to pay and intention to download a health app.ResultsThe revenue model did not affect willingness to pay or intentions to download the app in all three countries. In the Netherlands, data protection increased willingness to pay for the health app (P<.001). Moreover, in all three countries, data protection increased the likelihood of downloading the app (P<.001). In Germany (P=.04) and the Netherlands (P=.007), a doctor recommendation increased both willingness to pay and intention to download the health app. For all three countries, apps manufactured in association with a medical organization were more likely to be downloaded (P<.001). Finally, in all three countries, men, younger individuals, those with higher levels of education, and people with a health information orientation were willing to pay more for adoption of the health app and had a higher intention to download the app.ConclusionsThe finding that people want their data protected by legislation but are not willing to pay more for data protection suggests that in the context of mHealth, app privacy protection cannot be leveraged as a selling point. However, people do value a doctor recommendation and apps manufactured by a medical association, which particularly influence their intention to download an mHealth app.

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Project description:ObjectiveThe goal of this scoping review was to summarize the literature on facilitators and barriers to surgical practice change. This information can inform research to implement best practices and evaluate new surgical innovations.BackgroundIn an era of accelerated innovations, surgeons face the difficult decision to either acknowledge and implement or forgo new advances. Although changing surgical practice to align with evidence is an imperative of health systems, evidence-based guidelines have not translated into consistent change. The literature on practice change is limited and has largely focused on synthesizing information on methods and trials to evaluate innovative surgical interventions. No reviews to date have grounded their analysis within an implementation science framework.MethodsA systematic review of the literature on surgical practice change was performed. Abstracts and full-text articles were reviewed for relevance using inclusion and exclusion criteria and data were extracted from each article. Cited facilitators and barriers were then mapped across domains within the implementation science Theoretical Domains Framework and expanded to the Capability, Opportunity, Motivation, and Behavior model.ResultsComponents of the Capability, Opportunity, Motivation, and Behavior model were represented across the Theoretical Domains Framework domains and acted as both facilitators and barriers to practice change depending on the circumstances. Domains that most affected surgical practice change, in order, were: opportunity (environmental context and resources and social influences), capability (knowledge and skills), and motivation (beliefs about consequences and reinforcement).ConclusionsPractice change is predicated on a conducive environment with adequate resources, but once that is established, the surgeon's individual characteristics, including skills, motivation, and reinforcement determine the likelihood of successful change. Deficiencies in the literature underscore the need for further study of resource interventions and the role of surgical team dynamics in the adoption of innovation. A better understanding of these areas is needed to optimize our ability to disseminate and implement best practices in surgery.

Dataset Information

Adoption and learning across hospitals: The case of a revenue-generating practice.

Publications

Adoption and learning across hospitals: The case of a revenue-generating practice.

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