Population Health Management, Emerging Technologies, and the Science of the Individual

Population Health Management, Emerging Technologies, and the Science of the Individual

Anastasius S. Moumtzoglou, Abraham Pouliakis
Copyright: © 2020 |Pages: 42
DOI: 10.4018/978-1-7998-2390-2.ch002
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Abstract

Population health management (PHM) has been a discipline that studies and facilitates care delivery across a group of individuals or the general population. In the context of PHM, the life science industry has had no motivation to design drugs or devices and even offer treatment of patient management that is only effective for a distinct population segment. The primary outgrowth of the science of individuality, as well as the rising ‘wiki medicine', fully recognizes the uniqueness of the individual. Cloud computing, big data, m-health, and recently, internet of things can offer the resources to deal with numerous shortcomings such as data collection and processing, of the PHM approach, as they facilitate the propagation of the science of individuality.
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Introduction

Public health connotes a relatively narrow field with activities carried out by agencies granted with official functions. ‘Population health’ a term with broader content, is related to a field relevant to the study of several important factors for health. As a result, it involves many terms, such as outcomes, disparities, determinants, and risk factors (Kindig, 2007).

Notwithstanding the term ‘population health’ combines the concepts of both health and population, every term has an essential meaning of its own. The population is related to a group of persons being organized into numerous different units of analysis. Similarly, the term health was defined negatively, i.e., the absence of disease. Nowadays, modern understanding stresses the positive aspects as well, and health is considered to be related to all life issues. Summarizing, today it is debated whether population health and public health are different or identical. Nevertheless, population health is defined as health outcomes and their distribution in a population (Kindig, 2007).

Population health management (PHM) has been defined as ‘the technical field of endeavor which utilizes a variety of individual, organizational and cultural interventions to help improve the morbidity patterns (i.e., the illness and injury burden) and the health care use behavior of defined populations (Hillman, 2002). It is differentiated from disease management because it includes (Howe & Spence, 2004):

  • More chronic conditions and diseases.

  • Uses a single point of contact and coordination and predictive modeling across multiple clinical conditions.

Moreover, PHM is considered a broader term than disease management, as it includes (Coughlin, Pope, & Leedle(Jr), 2006):

  • Intensive care management for individuals at the highest level of risk.

  • Personal health management for those at lower levels of predicted health risk.

At the provider level, there are three highlighted components (Care Continuum Alliance, 2012):

  • The leadership and the central care delivery role of the primary care physician.

  • The importance of patient activation.

  • The expansion of care coordination.

In this context, to successfully achieve all of these requirements, an organization should provide proactive, preventive and chronic care services to all managed patients. Furthermore, this should take place both during encounters of patients with the healthcare system and in between. Therefore, providers should maintain regular contact with their patients and support them in the management of their health. Additionally, providers must manage patients at high risk, to prevent the deterioration of their health and avoid the development of complications. Finally, evidence-based protocols for the diagnosis and treatment of patients, consistently and cost-effectively, are also required if a provider-based PHM approach is followed.

The Federal Agency for Healthcare Research and Quality (AHRQ) developed the concept of 'practice-based population health' (PBPH) and defined it as “an approach to care that uses information on a group of patients within a primary care practice or group of practices to improve the care and clinical outcomes of patients within that practice.’ (Cusack, Knudson, Kronstadt, Singer, & Brown, 2010).

The implementation of health IT is among the essential components and requirements for planning and implementing PHM. The adoption of Electronic Health Records is just the first step toward the creation of the requisite infrastructure. However, a wide range of other IT applications to automate PHM, track results and engage the patients in their health care is required. Additionally, IT systems should repeatedly be evaluated because of rapid technological changes, new government regulations and new approaches to patient management (Moumtzoglou & Pouliakis, 2015).

AHRQ recommends health IT tools for the stratification and monitoring of populations, as follows:

Key Terms in this Chapter

Public Health: A term which connotes a relatively narrow field with activities carried out by agencies granted with official functions.

Population Health Management: The aggregation of patient information (data) across multiple resources related to health information, the analysis of the data into a single patient record, and the outcome of the actions of health care providers which can improve clinical and economic outcomes.

Cloud Computing: A large number of computers connected through a network, capable of running an application on many computers and of configuring virtual servers which do not have physical presence and can be moved around and scaled up or down without being noticed by end-users.

Population Health: A term with broader content, which is related to a field relevant to the study of several important factors for health. As a result, it involves many terms, such as outcomes, disparities, determinants, and risk factors

Mobile Health (mHealth): The practice of medicine and public health supported by mobile devices.

Big Data: The term used for the collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

Internet of Things (IoT): The interconnection and the created network via the Internet of devices embedded in everyday objects. This interconnection adds bidirectional communication capability to these devices enabling them to send and receive data.

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