Gls Models In India
Sanna Pospicil
The site is secure.
The ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.
Importance: Hypertension contributes to more than 1.6 million deaths annually in India, with many individuals being unaware they have the condition or receiving inadequate treatment. Policy initiatives to strengthen disease detection and management through primary care services in India are not currently informed by population preferences.
Design, setting, and participants: This cross-sectional study involved administration of a household survey to a population-based sample of adults with hypertension in the Bengaluru Nagara district (Bengaluru City; urban setting) and the Kolar district (rural setting) in the state of Karnataka, India, from June 22 to July 27, 2021. A discrete choice experiment was designed in which participants selected preferred primary care clinic attributes from hypothetical alternatives. Eligible participants were 30 years or older with a previous diagnosis of hypertension or with measured diastolic blood pressure of 90 mm Hg or higher or systolic blood pressure of 140 mm Hg or higher. A total of 1422 of 1927 individuals (73.8%) consented to receive initial screening, and 1150 (80.9%) were eligible for participation, with 1085 (94.3%) of those eligible completing the survey.
Main outcomes and measures: Relative preference for health care service attributes and preference class derived from respondents selecting a preferred clinic scenario from 8 sets of hypothetical comparisons based on wait time, staff courtesy, clinician type, carefulness of clinical assessment, and availability of free medication.
Conclusions and relevance: In this study, stated population preferences suggested that consistent medication availability and quality of clinical assessment should be prioritized in primary care services in Karnataka, India. The heterogeneity observed in population preferences supports considering additional models of care, such as fast-track medication dispensing to reduce wait times in urban settings and physician-led services in rural areas.
I just bought one of the products and it was very well packaged and in a mint condition and shipping time given at the time of purchase and delivery was made very fast the car was packed very well and I would like to suggest that they should also take in the the requests for specific models or inform the customer when the required model is available through email
We wanted to show our appreciation to you with our exclusive rewards program. By creating an account, you'll earn points for activities on our site, like referrals and purchases. You can use them to earn discounts off purchases, so the more you collect the more you save.
Bavarian Motor Works (Bayerische Motoren Worke in German) or BMW is a German luxury automobile manufacturer that was founded back in 1916. Headquartered in Munich, the brand made its debut in India in 2006. The Indian arm of the company has its headquarters in Gurugram while their factory is located in Chennai.
Premium small car brand Mini also works under the BMW India division, similar to the Motorrad division. In the near future, BMW plans to launch models including the all-new X6, BMW i8 Roadster and the 8 Series. These models could also be displayed at the 2020 Auto Expo ahead of their launch.
Many observers posit that a stark contest between democracy and autocracy will shape the governance of technology and data. But two Asian democracies, India and Korea, are carving out distinctive paths on data policy, not just following Western or Chinese models.
The Asia Program in Washington studies disruptive security, governance, and technological risks that threaten peace, growth, and opportunity in the Asia-Pacific region, including a focus on China, Japan, and the Korean peninsula.
But this binary framing elides the extent to which democracies have developed diverse approaches. Some democracies, especially in Asia, have adapted policy and regulatory features that deepen and extend the reach of the state. Some democracies, again especially in Asia, have developed data governance regimes that reflect the unique features of their institutions and political cultures. It is important to dig into this diversity, especially at a moment when there is a growing focus on data policy at both the international and national levels.
Bluntly put, to those who believe that the world faces a stark or binary choice between transatlantic-centered democratic models or China-centric authoritarian ones, this volume should be an eye-opener. Like the 2021 volume on Korea, this study demonstrates that additional players are leading the way in several key respects. Both India and Korea are consolidated democracies, and neither of them is simply emulating U.S. or European experiences. Instead, they are pioneering their own approaches, mixing and matching elements of their unique democratic institutional frameworks with national requirements and policies derived from distinctive political cultures.
But this binary framing elides the extent to which democracies have developed diverse approaches. Some democracies, especially in Asia, have adapted policy and regulatory features that deepen and extend the reach of the state. Some democracies, again especially in Asia, have developed data governance regimes that reflect the unique features of their institutions and political cultures.
It is important, therefore, to dig into this diversity, especially at a moment when there is a growing focus on data policy at both the international and national levels. This intensifying focus on data is being driven by several factors, including
To be sure, progress on data governance in both India and Korea has been uneven. Their stories are by no means simple ones. For example, this volume shows that different agencies in the governments of each of these countries have conflicting policy goals and, when their preferred policies have collided, it has proved almost impossible to develop a clear, consistent vision and strategy. The result has been inadequate investment; stalled-out projects; and missed opportunities to share, combine, and use data to solve problems in the Indian and Korean public and private sectors.
An important theme that links both the 2021 and 2022 volumes is that disparate agencies in a fragmented bureaucracy can lead to disparate policy goals. The two chapters in this volume by Korean authors (along with a chapter in The Korean Way With Data, by Nohyoung Park) highlight inconsistencies and points of conflict and competition across the Korean bureaucracy in Seoul.2
But India and Korea do diverge in one respect: in India, these arguments from law enforcement often seem to win the day. In Korea, by contrast, national security concerns have had a much greater impact on outcomes and policies than the concerns of law enforcement have.
Countries whose presidents and prime ministers take the lead on policy decisions related to the digital economy often force competing ministries to forge a consensus. These countries end up with a huge advantage in helping data-intensive industries compete. Ultimately, these countries tend to fashion new e-government solutions, foster machine learning, and enable new, data-driven business models.
Today, in most countries, there is even more potential for digital innovation but less digital leadership. The result has been conflicting policies promulgated by different agencies that can discourage innovators and risk-takers in both the private sector and the government bureaucracies. These players want to offer new tools and online services but fear running afoul of government regulations regarding data protection, export controls, surveillance requirements, cybersecurity, and more. From a global perspective, the Indian and Korean experiences highlighted in the four chapters that follow are standouts.
But, of course, leadership does not mean that presidents and prime ministers must delve deeply into the arcana of data management and technical standards for them to shape digital policy. In many cases, their most important contribution can simply be to share a vision for how information technology and the data it generates, collects, combines, and analyzes can benefit the citizens they govern and the countries they lead. Simply put, savvy national leaders can explain how to think about the digital future.
The critical top-level issue for policymakers wrestling with data policy is whether to try to create a single overarching approach to data management or instead to take a more federated approach.16 To extend the water metaphor a bit further, the choice policymakers face is whether to have a single unified national water utility that serves every home, or instead to encourage the formation of multiple local water companies and home-based wells that operate within a broad regulatory framework.
In their chapter in this volume, Indian authors Rahul Matthan and Shreya Ramann explain how the Indian government is promoting a Data Empowerment Protection Architecture (DEPA) to consolidate data sets throughout the Indian government and beyond. But in Korea, as Taewoo Nam shows in his chapter, the government has encouraged hundreds of companies to work with different ministries to find new, useful ways to apply the data they collect. These two Asian democracies have thus arrived at two very different approaches.
c80f0f1006