In 2021, we are stepping into a new decade with a pandemic on board; there is a widespread agreement on the importance of focusing on healthier individuals and communities with better and more affordable hospital management systems.
Population health analytics is defined as the first step toward developing a system that successfully manages a population's health.
Further, let's explore Population health and population health management as a methodological approach that any hospital management system uses to move towards population health management solutions.
The data illustrated for the global market regarding population health management solutions in 2016 gives an estimated number for 2025. In 2016, the global market was estimated to be worth roughly $8.9 billion. By 2025, the market is expected to increase by more than $50 billion.
In this paradigm, population health is one of the cost containment solutions that focuses on a group of people inside a given geopolitical area. It highlights population health analytics that incorporates social, economic, environmental, and individual behaviors and genetic factors in addition to clinical components of healthcare management software.
On the other side, population health management is the management of health and outcomes for sub-populations such as the patients treated by a health facility
Importance of Population Health Management:
The pandemic of coronavirus disease 2019 (COVID-19) has drastically transformed how population health management strategies deliver services, exposing the vulnerability of care delivery based on face-to-face routine care and fee-for-service reimbursement structures.
Value-based contract participation fosters robust population health management, which blends analytics and agile clinical programs and is adaptable to optimize results and reduce risk during community-level crises.
Researchers have revealed how established population health analytics-based programs in a learning health system quickly leverage to address the pandemic's concerns.
Identifying age group inequalities and community outreach has been made easier thanks to population-level data and careful monitoring. Telemedicine and integrated healthcare solutions behavioral health have ensured crucial primary care and specialized access. In contrast, mobile health(mHealth) and post-acute therapies have changed care sites and reduced in-patient hospital utilization.
From a value-based perspective, population health can dominate as a foundation of a robust health system, adequately equipped to enhance public health and manage risk.
Before the coronavirus pandemic of 2019 (COVID-19), the US healthcare system underwent tremendous changes, turning away from inefficiencies and towards patient-centeredness.
In the short term, health care systems may reasonably focus on intensity to compensate for lost revenue. They may be concerned that joining a care management organization may put them at more economic burden due to the unclear influence of COVID-19 on contract performance.
However, after COVID-19, population health management will play a critical role in assisting financial recovery and leading the change of health care delivery.
Population health programs can help build a robust health system after the pandemic. Providing personalized services, the analytics, strategic engagement, and program innovation that enabled success during the initial COVID-19 boom can help prevent a resurgence.
Cases at the immense risk of poor consequences can be identified using clinical registries and risk prediction algorithms. High-risk care management needs to be adapted more flexibly to medical and social demands. Telemedicine should be viewed as a critical tool for reducing low-value care while increasing efficiency and improving the patient experience.
The Main Purpose of Population Health Management:
Suppose organizations do not have the strategy and information technology capabilities to make outreach more targeted, accurate, and efficient. In that case, comprehensive data analysis is done through EHR solutions, and patient engagement activities can soon manage significant cost containment in healthcare.
The purpose of Population Health Management is as follows:
Chronic disease management:
Healthcare institutions use population healthcare management solutions to manage chronic disease treatment methods, such as diabetes and chronic obstructive pulmonary disease (COPD).
Wellness and preventive health:
Population health management companies offer campaigns to encourage adolescents and adults to adopt healthy lifestyle choices. This category includes healthcare interoperability solutions that encourage youngsters to indulge in weight loss and smoking suspension programs.
Clinically integrated networks:
Primary care physicians, specialists, and hospitals collaborate to improve patient care by forming networks. Delivery of high-quality treatment and decreased costs, these networks integrate health record systems and track data.
At-risk payment structures:
These organizations are dedicated to enhancing the quality of care provided to their members and providing financial incentives.
At-risk cost structures:
This initiative encompasses Medicaid-managed care and self-insured employment plans, among other things. Medicare scores are determined by the multiple diagnostic codes that physicians report. In theory, the concept encourages clinicians to keep patients healthy through population health management tools such as clinical decision support systems, EHR solutions, and integrated healthcare solutions.
Functions of Population Health Management :
Certain Core functions will be necessary for the journey toward population health management as health centers build new care delivery structures, broader collaborations, new payment arrangements, and enhanced IT and data capabilities.
Patient-Centered healthcare:
The ability to build healthcare management software embedded with HIPAA compliant software development strategies around which the population's health and results are successfully managed, and patients can be more actively involved.
Patient Registry:
Health centers must have EHR systems or EMR systems that include all patients associated with a practice, not just those currently enrolled.
Clinical and administrative data, such as lab, pharmacy, treatment codes, and diagnostic and screening results, should be included at a minimum in these healthcare interoperability solutions.
This system should eventually incorporate or link to claims data.
Accountable Care:
Each patient in the health center register must be assigned to a primary care practitioner or care team responsible for planning and delivering the appropriate care at the appropriate time, minimizing wasteful duplication of services and medical errors.
Risk-stratification :
Due to the distinct community serviced by health facilities, stratification of patients is required, not only for complex medical disorders but also for health determinants that influence results.
A health center can start with a simple stratification algorithm and work its way up to a risk stratification procedure that considers social determinants of health.
Health Screenings:
Improving clinical measurements and preventative screenings necessitates a system of treatment that is tailored to these goals. Patients should be scheduled for an annual medical checkup that includes all recommended preventative screenings as well as a social vulnerability assessment in health centers.
This procedure can be implemented gradually, depending on the size of the treatment regimen, and should commence with high-risk individuals.
Personnel to Assist with Population Health Management:
Innovate appropriate care teams that integrate care, connect to social services, and effectively monitor and communicate with high-risk individuals at least once every 90 days for whole-person care.
Use Data to Manage Patient Populations:
Monitor the health of each provider's panel and the population as a whole using dashboards and other tools.
Health/Community System Partnerships and Communication:
Establish relationships and effective communication connections with healthcare agencies and social-service groups that provide meals and transportation and exchange recommendations and outcomes.
Furthermore, including alternatives for patients to participate in communication and care.
Advantages of Population Health Management:
Population Health Management can help you be more proactive in your healthcare treatment and prevention. This approach could help individuals feel more empowered to manage their health. PHM may also provide the following advantages:
Financial improvement: Evaluating the utilization of necessary services to assist in cost avoidance may result in financial improvement for the company.
Better health outcomes: Better health outcomes by focusing on chronic illness prevention and treatment and identifying care gaps by analyzing the patient population's health. This benefit can help the practitioner determine the patient population's most pressing healthcare needs, allowing for better disease management and better resource allocation.
Patient Engagement:
Patients may benefit from enhanced patient engagement and commitment to maintaining wellness through preventative care before shifting into high-risk categories.
Reduction of Care Gaps:
Physicians and organizations can use Population Health Management to access patients' needs in real-time and deliver assistance as quickly as possible. Hospital expenses, laboratory data, health records, and medications are all taken into account to address and service patients' unmet requirements. As a result, service delivery gaps can be eliminated positively.
Disease Prevention:
Population Health Management provides excellent care to people suffering from chronic diseases with substantial treatment expenditures. PHM employs effective methods to manage the treatment that these patients receive from healthcare providers.
Disadvantages of Population Health Management:
It's not a mystery that healthcare in the United States is costly and doesn't always produce the best results. A modern paradigm that focuses on population health analytics and wellbeing may be able to assist solve this challenge.
It is preferable for patients, providers, and health systems when the subscription model focuses on and promotes positive results. The dynamics are finally aligning, yet such a paradigm shift is not without its difficulties.
One size doesn't fit all:
For the most part, the population health model works effectively, but for the elderly and weak and individuals with chronic illnesses, a more tailored approach is required. There's much work going on right now in this arena as we try to figure out how traditional players can address the requirements of 100% of people in a population health paradigm.
Engaging communities:
Another problem is determining how to interpret and quantify data about social determinants of health for our patients. A yearly patient survey is one way of accomplishing this. The survey allows people to share their experiences with us in a new way. It facilitates communication and allows us to offer assistance and resources.
High-cost utilization:
Despite efforts to cut wasteful healthcare costs, high-cost utilization that is avoidable continues to be a problem. Patients who visit the emergency room for non-emergent issues and hospital admissions could have been avoided if healthcare had been more structured and systematic upstream. These patterns are beginning to shift in the right direction, but they remain elevated. As a result, most of the effort in population health is focused on defragmenting the operation and assuring that the patients understand how to get the best care possible.
Conclusion:
The correct population health management solutions may help you better understand patients, automate work that people shouldn't do so they can focus on patients, physicians, and caregivers, and even forecast or recommend the optimal next step. It should pull together data from a growing number of sources, assist you in categorizing your patient base, and, honestly, go beyond sending automatic appointment reminders.
Automation and artificial intelligence (AI) are two technologies that are becoming increasingly important. For example, in care, automation allows physicians and caregivers to spend more time on patients' care plans because digital assistants handle appointment scheduling, reminders, and notifications.
The purpose of balancing quality and affordability in the delivery of patient care remains the same, regardless of how population health management is defined. The use of appropriate technology that can collect and analyze the required complete patient data can be beneficial. This patient data analysis can help pave the way for better population health management, resulting in beneficial outcomes for both the patient and the practitioner.