This document discusses population health management and outlines four key aspects: data control and governance, population management and risk stratification, care management, and patient engagement. It summarizes the challenges of collecting and analyzing large amounts of patient data from electronic health records, developing risk profiles of patient subgroups, implementing targeted care models, and encouraging patient accountability through new technologies. The overall goal is for healthcare organizations to successfully address these areas and achieve true population health management.
Enhance Healthcare Analytics with Consumer DataRay Pun
To succeed in the new value-based care landscape, healthcare providers must expand beyond traditional data sources for healthcare analytics. Leading providers are using consumer data, available at the individual and household level, to supplement clinical and claims data. By integrating consumer insights into models for understanding and predicting patient health, providers can improve the health of Americans and achieve these outcomes:
• Improve community health needs assessments
• Drive patient retention and engagement with personalized
wellness programs
• Reduce patient readmission rates
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Providers need to move towards real-time analytics that have become critical to demonstrate their quality of care, as reimbursement by government programs can be contingent upon how providers are measured in “Quality of Care”. For example, the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015, also called the Permanent Doc Fix, changes the way Medicare doctors are reimbursed with the implementation of a merit based incentive. The performance-based pressure is huge, which makes it imperative that every provider consider technology solutions. Read more at https://www.solix.com/solutions/data-driven-solutions/healthcare/
The Population Health Management Market 2015Lifelog Health
Population health management is a problem term because it can mean something different to each person who hears it. However, I believe that the words capture the overall spirit and energy of healthcare reform in a unique way. Providers are thinking big when it comes to a patient’s engagement, responsibility, and preventative care, and they’re leveraging technology to do it. I discuss an overall picture of PHM, present some useful technology, and tell a few PHM stories herein.
Big data is more than just a buzzword in healthcare. It's the promise of being able to extract, cull, and interpret medical data to directly benefit population and individual health. learn more about the benefits of big data, roadblocks to leveraging it's potential, how Meaningful Use enablesbig data, what types of cross-country collaboration projects are advancing the use of big data on an international scale, big data's impact on patient privacy and much more! Special thanks to Mandi Bishop for her time on the podcast.
Enhance Healthcare Analytics with Consumer DataRay Pun
To succeed in the new value-based care landscape, healthcare providers must expand beyond traditional data sources for healthcare analytics. Leading providers are using consumer data, available at the individual and household level, to supplement clinical and claims data. By integrating consumer insights into models for understanding and predicting patient health, providers can improve the health of Americans and achieve these outcomes:
• Improve community health needs assessments
• Drive patient retention and engagement with personalized
wellness programs
• Reduce patient readmission rates
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Providers need to move towards real-time analytics that have become critical to demonstrate their quality of care, as reimbursement by government programs can be contingent upon how providers are measured in “Quality of Care”. For example, the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015, also called the Permanent Doc Fix, changes the way Medicare doctors are reimbursed with the implementation of a merit based incentive. The performance-based pressure is huge, which makes it imperative that every provider consider technology solutions. Read more at https://www.solix.com/solutions/data-driven-solutions/healthcare/
The Population Health Management Market 2015Lifelog Health
Population health management is a problem term because it can mean something different to each person who hears it. However, I believe that the words capture the overall spirit and energy of healthcare reform in a unique way. Providers are thinking big when it comes to a patient’s engagement, responsibility, and preventative care, and they’re leveraging technology to do it. I discuss an overall picture of PHM, present some useful technology, and tell a few PHM stories herein.
Big data is more than just a buzzword in healthcare. It's the promise of being able to extract, cull, and interpret medical data to directly benefit population and individual health. learn more about the benefits of big data, roadblocks to leveraging it's potential, how Meaningful Use enablesbig data, what types of cross-country collaboration projects are advancing the use of big data on an international scale, big data's impact on patient privacy and much more! Special thanks to Mandi Bishop for her time on the podcast.
Health Care Data Sets and their purpose
UHDDS, UACDS, MDS, OASIS, DEEDS and EMDS.
Explain the standardization data collection efforts.
Explain the five type of standards that need to be in place to implement the Nationwide Health Information Network (NHIN).
Standard Development Organizations
Evolving and Emerging Health Information Standards
FTC Spring Privacy Series: Consumer Generated and Controlled Health DataBrian Ahier
Increasingly, consumers are taking a more active role in managing and generating their own health data. For example, consumers are researching their health conditions and diagnosing themselves online. Consumers are also uploading their information into personal health records and apps that allow them to manage and analyze their data, and utilizing connected health and fitness devices that regularly collect information about them and transmit this information to other entities.
The movement of health data outside the traditional medical provider context has many potential benefits; however, it also raises potential privacy concerns. The seminar will address questions such as:
What types of websites, products, and services are consumers using to generate and control their health data, and how are consumers using them?
Who are the companies behind these websites, products, and services, what are their business models, and what does the current marketplace look like?
How can consumers benefit from these companies’ websites, products, and services?
What actions are these companies taking to protect consumers’ privacy and security?
What do consumers expect from these companies regarding privacy and security protections?
Do consumers differentiate between these companies and those that offer traditional medical products and services that are covered by HIPAA?
What restrictions, if any, do advertising networks and others impose on tracking of health data?
www.panorama.com
Panorama Necto uncovers the hidden insights in your data and presents them in beautiful dashboards powered with KPI Alerts, which is managed by a the most secure, centralized & state of the art BI solution.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Data-Driven Precision Medicine: A Must-Have for the Next-Generation of Person...Health Catalyst
Under a precision medicine approach, clinicians, academics, and pharma and biotech researchers and regulators aim to deliver the right drug for the right patient at the right time. Data, however, can present a challenge to precision medicine goals due to gaps in clinical care, research, and drug development when organizations don’t have the ability to capture and report on relevant real-world data. With the right systems to collect and share clinical and molecular data, the healthcare industry can realize the full benefits of precision medicine.
Continuity of Care Documents: Today’s Top Solution for Healthcare Interoperab...Health Catalyst
While healthcare waits for the expanded data interoperability that FHIR promises, the industry needs an immediate solution for accessing and using disparate data from across the continuum of care. With FHIR potentially several years away, continuity of care documents (CCDs) are the best option for acquiring the ambulatory clinical care data health systems need to close quality gaps today. Because organizations that rely only on claims data to drive quality improvement risk missing out on more that 80 percent of patient information, CCDs are the current must-have answer to interoperability for successful quality improvement.
Examination of the value of data analytics and integration to support new care models such as ACOs and Patient-Centered Medical Homes. The EHR is necessary but not sufficient!
Building Clinical Integration as a Foundation to Become a Successful ACOPhytel
More and more healthcare organizations are recognizing that clinical integration of providers is a prerequisite to care coordination, population health management, and accountable care organizations. They also know that patient centered medical homes—the building blocks of ACOs—can thrive only in patient-centered medical neighborhoods where specialists collaborate with primary care physicians. For this cooperation to be truly effective, all of these providers must be clinically integrated. This paper explains the components of clinical integration and summarizes the kinds of information technology required for its implementation. Case studies of organizations that are building the necessary infrastructure are also included.
Improving Clinical and Operational Outcomes by Leveraging Healthcare Data Ana...NUS-ISS
Presented by Mr. Sandeep Makhijani, Regional Director for Asia Pacific (APAC), Truven Health Analytics at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
Hospital Capacity Management: How to Prepare for COVID-19 Patient SurgesHealth Catalyst
Health system resource strain became an urgent concern early in the COVID-19 pandemic. Hard-hit areas exhausted their hospital beds, ventilators, personal protective equipment, staffing, and other life-saving essentials, while other regions scrambled to prepare for inevitable surges. These resource concerns heightened the need for accurate, localized hospital capacity planning. With additional waves of infection in the summer months following the initial spring 2020 crisis, health systems must continue to forecast resource demands for the foreseeable future. An accurate capacity planning tool uses population demographics, governmental policies, local culture, and the physical environment to predict healthcare resource needs and help health systems prepare for surges in patient demand.
A very comprehensive and detailed introduction to Portugal and its real estate market.
Find information and descriptions of the main regions of Portugal and a vast property listing.
Health Care Data Sets and their purpose
UHDDS, UACDS, MDS, OASIS, DEEDS and EMDS.
Explain the standardization data collection efforts.
Explain the five type of standards that need to be in place to implement the Nationwide Health Information Network (NHIN).
Standard Development Organizations
Evolving and Emerging Health Information Standards
FTC Spring Privacy Series: Consumer Generated and Controlled Health DataBrian Ahier
Increasingly, consumers are taking a more active role in managing and generating their own health data. For example, consumers are researching their health conditions and diagnosing themselves online. Consumers are also uploading their information into personal health records and apps that allow them to manage and analyze their data, and utilizing connected health and fitness devices that regularly collect information about them and transmit this information to other entities.
The movement of health data outside the traditional medical provider context has many potential benefits; however, it also raises potential privacy concerns. The seminar will address questions such as:
What types of websites, products, and services are consumers using to generate and control their health data, and how are consumers using them?
Who are the companies behind these websites, products, and services, what are their business models, and what does the current marketplace look like?
How can consumers benefit from these companies’ websites, products, and services?
What actions are these companies taking to protect consumers’ privacy and security?
What do consumers expect from these companies regarding privacy and security protections?
Do consumers differentiate between these companies and those that offer traditional medical products and services that are covered by HIPAA?
What restrictions, if any, do advertising networks and others impose on tracking of health data?
www.panorama.com
Panorama Necto uncovers the hidden insights in your data and presents them in beautiful dashboards powered with KPI Alerts, which is managed by a the most secure, centralized & state of the art BI solution.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Data-Driven Precision Medicine: A Must-Have for the Next-Generation of Person...Health Catalyst
Under a precision medicine approach, clinicians, academics, and pharma and biotech researchers and regulators aim to deliver the right drug for the right patient at the right time. Data, however, can present a challenge to precision medicine goals due to gaps in clinical care, research, and drug development when organizations don’t have the ability to capture and report on relevant real-world data. With the right systems to collect and share clinical and molecular data, the healthcare industry can realize the full benefits of precision medicine.
Continuity of Care Documents: Today’s Top Solution for Healthcare Interoperab...Health Catalyst
While healthcare waits for the expanded data interoperability that FHIR promises, the industry needs an immediate solution for accessing and using disparate data from across the continuum of care. With FHIR potentially several years away, continuity of care documents (CCDs) are the best option for acquiring the ambulatory clinical care data health systems need to close quality gaps today. Because organizations that rely only on claims data to drive quality improvement risk missing out on more that 80 percent of patient information, CCDs are the current must-have answer to interoperability for successful quality improvement.
Examination of the value of data analytics and integration to support new care models such as ACOs and Patient-Centered Medical Homes. The EHR is necessary but not sufficient!
Building Clinical Integration as a Foundation to Become a Successful ACOPhytel
More and more healthcare organizations are recognizing that clinical integration of providers is a prerequisite to care coordination, population health management, and accountable care organizations. They also know that patient centered medical homes—the building blocks of ACOs—can thrive only in patient-centered medical neighborhoods where specialists collaborate with primary care physicians. For this cooperation to be truly effective, all of these providers must be clinically integrated. This paper explains the components of clinical integration and summarizes the kinds of information technology required for its implementation. Case studies of organizations that are building the necessary infrastructure are also included.
Improving Clinical and Operational Outcomes by Leveraging Healthcare Data Ana...NUS-ISS
Presented by Mr. Sandeep Makhijani, Regional Director for Asia Pacific (APAC), Truven Health Analytics at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
Hospital Capacity Management: How to Prepare for COVID-19 Patient SurgesHealth Catalyst
Health system resource strain became an urgent concern early in the COVID-19 pandemic. Hard-hit areas exhausted their hospital beds, ventilators, personal protective equipment, staffing, and other life-saving essentials, while other regions scrambled to prepare for inevitable surges. These resource concerns heightened the need for accurate, localized hospital capacity planning. With additional waves of infection in the summer months following the initial spring 2020 crisis, health systems must continue to forecast resource demands for the foreseeable future. An accurate capacity planning tool uses population demographics, governmental policies, local culture, and the physical environment to predict healthcare resource needs and help health systems prepare for surges in patient demand.
A very comprehensive and detailed introduction to Portugal and its real estate market.
Find information and descriptions of the main regions of Portugal and a vast property listing.
Suggested ResourcesThe resources provided here are optional. You.docxdeanmtaylor1545
Suggested Resources
The resources provided here are optional. You may use other resources of your choice to prepare for this assessment; however, you will need to ensure that they are appropriate, credible, and valid. The MHA-FP5064 Health Care Information Systems Analysis and Design for Administrators Library Guide can help direct your research, and the Supplemental Resources and Research Resources, both linked from the left navigation menu in your courseroom, provide additional resources to help support you.
The Role of Informatics in Health Care
The following articles address the increasingly important role of informatics, which may provide useful insight when examining the data needs of an organization.
· Centers for Medicare & Medicaid Services. (2017). Data and program reports. Retrieved from https://www.cms.gov/regulations-and-guidance/legislation/ehrincentiveprograms/dataandreports.html
. The Web page provides access to Medicare and Medicaid Electronic Health Records Incentive Program payment and registration data contained in various reports.
· Chen, M., Lukyanenko, R., & Tremblay, M. C. (2017). Information quality challenges in shared healthcare decision making. Journal of Data and Information Quality (JDIQ), 9(1), 1–3.
. Discusses the challenges for patients in making sense of the enormous volume of health information made available through current information and communications technologies and how the quality of that information affects shared decision-making between patients and providers.
· Crawford, M. (2014). Making data smart. Journal of AHIMA, 85(2), 24–27, 28.
. Discusses applied informatics and how it can be used to derive useful information from big data, as health care becomes a data-driven industry.
· Dinov, I. D. (2016). Methodological challenges and analytic opportunities for modeling and interpreting big healthcare data. GigaScience, 5(1), 1–15.
. Discusses the challenges of big data analysis and addresses the need for technology and education in creating valuable knowledge assets from big data.
· Hegwer, L. R. (2014). Digging deeper into data. Healthcare Financial Management, 68(2), 80–84.
. Discusses the role of data analysts in improving the financial and clinical performance of health care organizations.
2
Running Head: Organizational Data needs
2
Organizational Data needs
Organization Data Needs Capella UniversityAssignment 2
Internal data sources can include data systems, for example, a radiology data system, medical library data, or the patient finance and billing system. Internal data sources also include EHR data systems such as the demographics, medical history of patients and disease records, medication and allergies records, laboratory test results, personal patient statistics such as gender age, weight and billing information (Porter et al, 2018).
External data sources include data from Centres for Medicare and Medicaid Services (CMS), benchmarking data from other hospitals are ex.
Ensuring Data IntegrityIn Health Information ExchangeTanaMaeskm
Ensuring Data Integrity
In Health Information Exchange
Inaccurate health information may adversely affect the quality of an individual’s
healthcare, insurance, and employability. As computerization of health information
continues and the scope of organizational exchange of health information widens into
health information exchanges (HIEs), maintaining the integrity and completeness of
health data is paramount.
The overarching goal of HIEs is to allow authorized users to quickly and accurately
exchange health information to enhance patient safety and improve efficiency.
Achieving this goal is dependent on the ability to link (match) multiple, disparate
records relating to a single individual.
A 2008 RAND report, “Identity Crisis: An Examination of the Costs and Benefits of a
Unique Patient Identifier for the US Health Care System,” noted that avoiding adverse
drug events, which are often the result of incomplete linking information about a
patient’s medications or allergies, could save the healthcare system in the US about
$4.5 billion per year.1 This report also points out that on average an 8 percent duplicate
record rate existed in the master patient index (MPI) databases studied. The average
duplicate record rate increased to 9.4 percent in MPI databases with more than 1 million
records. Additionally, the report identified that the duplicate record rates of the enterprise
master patient/person index (EMPI) databases studied were as high as 39.1 percent.
High duplicate record rates within EMPI databases are commonly the result of loading
unresolved duplicate records from contributing MPI files. EMPI systems that leverage
advanced matching algorithms are designed to automatically link records from multiple
systems if there is only one existing viable matching record. If the EMPI system identifies
two or more viable matching records when loading a patient record, as is the case when
the EMPI contains unresolved duplicate record sets, it must create a new patient record
and flag it as an unresolved duplicate record set to be manually reviewed and resolved.
Therefore, if care is not taken to resolve the existing EMPI duplicate records, the duplicate
rate in an EMPI can significantly grow as additional MPI files are added.
Patient identity integrity is the accuracy, quality, and completeness of demographic data
attached to or associated with an individual patient. This includes the accuracy and
quality of the data as it relates to the individual, as well as the correctness of the linking
or matching of all existing records for that individual within and across information
AHIMA HIE Practice Council Contributors:
Linda Bailey-Woods, RHIA, CPHIMS; Teresa
M. Hall, MHA, RHIT, CPC; Aviva M. Halpert,
RHIA, MA, CHPS; Steven Kotyk ; Shirley Neal,
RHIT; Letha Stewart, MA, RHIA; and Susan O.
Torzewski, RHIA
Editor: Anne Zender, MA
Design: Candy Ramos
Representing more than 64,000 specially
educated health information management
professi ...
The care business traditionally has generated massive amounts of inf.pdfanudamobileshopee
The care business traditionally has generated massive amounts of information, driven by record
keeping, compliance & regulative needs, and patient care [1]. whereas most knowledge is hold
on in text type, the present trend is toward fast conversion of those massive amounts of
information. Driven by obligatory needs and also the potential to enhance the standard of health
care delivery in the meantime reducing the prices, these huge quantities of information (known
as ‘big data’) hold the promise of supporting a good vary of medical and care functions, as well
as among others clinical call support, illness police work, and population health management [2,
3, 4, 5]. Reports say knowledge from the U.S. care system alone reached, in 2011, one hundred
fifty exabytes. At this rate of growth, huge knowledge for U.S. care can before long reach the
zettabyte (1021 gigabytes) scale and, shortly when, the yottabyte (1024 gigabytes) [6]. Kaiser
Permanente, the California-based health network, that has over nine million members, is
believed to possess between twenty six.5 and forty four petabytes of doubtless made knowledge
from EHRs, as well as pictures and annotations [6].
By definition, huge knowledge in care refers to electronic health knowledge sets therefore
massive and complicated that they\'re tough (or impossible) to manage with ancient computer
code and/or hardware; nor will they be simply managed with ancient or common knowledge
management tools and strategies [7]. huge knowledge in care is overwhelming not solely due to
its volume however additionally due to the range of information varieties and also the speed at
that it should be managed [7]. The totality of information associated with patient care and well-
being compose “big data” within the care business. It includes clinical knowledge from CPOE
and clinical call support systems (physician’s written notes and prescriptions, medical imaging,
laboratory, pharmacy, insurance, and alternative body knowledge); patient knowledge in
electronic patient records (EPRs); machine generated/sensor data, like from observance
important signs; social media posts, as well as Twitter feeds (so-called tweets) [8], blogs [9],
standing updates on Facebook and alternative platforms, and net pages; and fewer patient-
specific data, as well as emergency care knowledge, news feeds, and articles in medical journals.
For the massive knowledge person, there is, amongst this large quantity and array of information,
chance. By discovering associations and understanding patterns and trends inside the
information, huge knowledge analytics has the potential to enhance care, save lives and lower
prices. Thus, huge knowledge analytics applications in care cash in of the explosion in
knowledge to extract insights for creating higher enlightened selections [10, 11, 12], and as a
groundwork class square measure noted as, no surprise here, huge knowledge analytics in care
[13, 14, 15]. once huge knowledge is synthesized and an.
In search of a digital health compass: My data, my decision, our powerchronaki
Knowledge is power. Despite extensive investments in digital health technology, navigating the health system online is challenging for most citizens. Also for eHealth, the “Inverse Care Law” proposed by Hart in 1971, seems to apply. Availability of good medical or social care services and tools online, varies inversely with the need of the population. The low adoption of eHealth services, and persistent disparities in health triggers a call for multidisciplinary action.
Barriers and challenges are not to be underestimated. Culture, education, skills, costs, perceptions of power and role, are essential for multidisciplinary action. This comes together in digital health literacy, which ought to become an integral part to navigate any health system. Patients living with an implanted device or coping with persistent, chronic disease such as diabetes, as well as citizens engaged in self-care, caring for an elderly relative, a neighbor, or their child with illness or deteriorating health, need a digital health compass.
The panel will engage the audience to elaborate on a vision for this personal, digital health compass and drive advancement in health informatics and digital health standards. The transformative power of health data fueled by targeted digital health literacy interventions can be leveraged by open, massive, and individualized delivery. This way, digital health literate, confident patients and citizens join health professionals, researchers and policy makers to address age-related health and wellness changes to shape the emerging precision medicine and population health initiatives.
From a panel in the eHealthweek 2016. http://www.ehealthweek.org/ehome/128630/hl7-efmi-sessions/
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Healthcare data and its impact upon the patient care decision process via accurate, real-time, reliable data from disparate sources is creating a digital health revolution. Data-driven healthcare is beginning to have a huge impact addressing the challenges of every provider, through efficient handling of huge volumes of patient care data.
76 CHAPTER 4 Assessing Health and Health Behaviors Objecti.docxpriestmanmable
76
CHAPTER 4
Assessing Health and Health Behaviors
Objectives
this chapter will enable the reader to:
1. Describe the expected outcomes of a nursing health assessment.
2. Identify the components of a nursing health assessment conducted for an individual client.
3. Examine life span, language, and culturally appropriate nursing health assessment tools for children, adults, and older adults.
4. Compare the similarities and differences among the various approaches to assessing the family, mindful of cultural influences.
5. Evaluate the criteria for conducting a screening in the community.
6. Compare the similarities and differences among the various approaches to assessing
the community.
Athorough assessment of health and health behaviors is the foundation for tailoring a health promotion-prevention plan. Assessment provides the database for making clinical judgments about the client’s health strengths, health problems, nursing diagnoses, desired health or behavioral outcomes, as well as the interventions likely to be effective. This information also forms the nature of the client–nurse partnership such as the frequency of con- tact and the need for coordination with other health professionals. The portfolio of assessment measures depends on the characteristics of the client, including developmental stage and cul- tural orientation. The nurse assesses age, language, and cultural appropriateness of the various measures selected.
Cultural competence is the ability to communicate effectively with people of different cultures. Providing culturally competent care is the cornerstone of the nursing assessment. The nurse’s aware- ness of her own attitude toward cultural differences and her cultural worldview and characteristics
Chapter4 • AssessingHealthandHealthBehaviors 77
are critical to her understanding and knowledge of various cultures. Recognizing that diversity exists in all cultures based on educational level, socioeconomic status, religion, rural/urban residence, and individual and family characteristics will ensure a more successful encounter (The Office of Minority Health, 2013). An online cultural educational program, designed specifically for nurses and featur- ing videotaped case studies and interactive tools, is available.
The Enhanced National Standards for Culturally and Linguistically Appropriate Services, based on a definition of culture expanded to include geography, spirituality, language, race and ethnicity, and biology, provides a practical guide to culturally and linguistically sensitive care (The Office of Minority Health, 2013).
Technology is having a significant impact on health care. The Electronic Health Record (EHR) promotes involvement of the client in developing a dynamic, tailored database. The EHR offers great promise to improve health and increase the client’s satisfaction with his care. Data aggregation, cross-continuum coordination, and clinical care plan management are critical com- ponents of the.
IDC White Paper - Integrated Patient Record - Empowering Patient Centric Care...buntib
Despite the growing use of electronic health records (EHRs) and health information exchange (HIE) technologies, providers and payers still face challenges with regard to accessing all the information known about a given patient or member. Patient health information can be trapped in siloed healthcare information systems, paper-based documents and processes, or non-machine-readable documents. An integrated view of patient information improves the experience of clinicians by enabling them to better serve their patients, which in turn leads to better outcomes. The ability to create comprehensive patient-centric records is crucial for improving not only quality of care but also patient safety.
Chapter 4 Information Systems to Support Population Health Managem.docxketurahhazelhurst
Chapter 4 Information Systems to Support Population Health Management Learning Objectives To be able to understand the data and information needs of health systems in managing population health effectively under value-based payment models. To be able to discuss key health IT tools and strategies for population health management including EHRs, registries, risk stratification, patient engagement, and outreach, care coordination and management, analytics, health information exchange, and telemedicine and telehealth. To be able to discuss the application and use of data analytics to monitor, predict, and improve performance. The enactment of the Affordable Care Act (ACA) brought about sweeping legislation intended to reduce the numbers of uninsured and make health care accessible to all Americans. It also ushered in an era in which changing reimbursement and care delivery models are driving providers from the current fragmented system focused on volume-based services to an outcomes orientation. As a result, the health care system now taking shape is one in which value-based payment models financially reward patient-centered, coordinated, accountable care. Against this backdrop, providers' increasing use of evidence-based medicine and growing capabilities in managing volumes of clinical evidence through sophisticated health IT systems will mean that treatments can be tailored for the individual and interventions can be made earlier to keep patients well. Furthermore, patient engagement is fast becoming a critical component in the care process, particularly in the area of population health management (PHM). Health care providers' interest in improving population health appears to be increasing because of the sudden ubiquity of the phrase, because many are participating in accountable care organizations (ACOs), and because even hospitals not participating in an ACO increasingly have incentives to reduce their number of potentially unavoidable admissions, readmissions, and emergency department visits (Casalino, Erb, Joshi, & Shortell, 2015). In this chapter we'll not only seek a common understanding of PHM but also explore how the advent of shared accountability financial arrangements between providers and purchasers of care has created significant focus on PHM. We'll also review the core processes associated with accountable care and examine the strategic IT investments and data management capabilities required to support population health management and enable a successful transition from volume-based to value-based care. PHM: Key to Success Although the ACO model is still new and evolving, approximately 750 ACOs are in operation today, covering some 23.5 million lives under Medicare, Medicaid, and private insurers. Although not all ACOs have demonstrated success in delivering better health outcomes at a lower cost, many have achieved promising results (Houston & McGinnis, 2016). As such, significant ACO growth is expected. In fact, it is predicte ...
Electronic Health Records: purpose of electronic health records, popular electronic health record system, advantages of electronic records, challenges of electronic health records, the key players involved.
2015 05 01 Pop Health - Laying the Foundation (00000002)
1. Redefining ConsulƟng. Transforming Healthcare.
POPULATION HEALTH
Laying the Foundation of Healthcare’s
Next Generation of Care
white paper
written by
Dana Alexander, Divurgent Vice President, Clinical Transformation
Colin Konschak, Divurgent CEO & Managing Partner