Deliverable 6 - Chronic Diseases and Population Health Management

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Running Head: Population Health Management Patterns

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Population Health Management Patterns

Population Health Management Patterns

Kimberly Huff

Rasmussen College

Deliverable 5 Submitted February 22nd, 2021.

Population Health Management Patterns

Population health management is an essential part of the health care sector, and every health system needs to effectively create it in different forms due to the presence of diverse populations. It is the sum of patient data in several health information technology resources, and it involves the analysis of information into one, actionable record for patients, and the regular actions that are taken by health care providers to improve the clinical results of patients and the financial outcomes of health care professionals (Devereaux, & Zilz, 2018). Our health system is creating several patterns of population health management that will serve the diverse population effectively. These patterns include expanding chronic disease management, investing in in-home intervention, managing care transitions, and optimizing network management. These patterns will heavily rely on data that is comprehensive, timely, and relevant in order to enable our organization to make better decisions.

In optimizing the management of the network, the first thing we will do is to determine the network we will use to refer patients to specialists because a higher percentage of our health care spending is used to pay the cost of services that are offered by physicians. The rate of physician referrals is increasing each day, and the management of the network has the likelihood of yielding greater savings into our health care organization. In contracts that will be based on value, the physicians will refer patients to specialists who provide cost-effective and high-quality care in their best interests. They will be able to analyze the claims and clinical data of their patients, which will help them to determine specialists who provide the best care at the best value (May, Byonanebye, & Meurer, 2017). Sharing of data on the performance of physicians will be made part of the organization's culture by showing them what they do instead of telling them what to do. We will set up a physician culture that will allow us to share analytics transparently. Optimization of network management through data transparency will have a positive effect on the individual patients and the entire population.

Another strategy will be paying much attention to the health providers' efforts in managing care transitions. Health professionals will be incentivized to make sure that those patients who go home or shift to another skilled nursing amenity acquire the support that they require both outside and inside the facility. Proactive and post discharge outreach will assist to make the transition of patients from one health care to another more easy which will prevent readmissions in our organization (Quinn, et al., 2018). We will introduce programs with complex care management consisting of various workers such as behavioral health specialists, pharmacists, social workers and care managers. The addition of a community based model to supplement our workers' telephonic care management programs will help to utilize the costs that are driven by some subsets of our population (Puro, & Falca-Dodson, 2016). Launching an integrated transitions care management program will increase our health system’s telephonic engagement with patients discharged from our health facility. Analytics will provide more strength in care management programs by aiding to forecast which patients need additional support.

Investing in the in-home intervention will consist of various models and targets of different populations, which is very critical from a population, cost, and quality perspective. In order to find the right patients to target with our in-home interventions, we will start by applying analytics to data. Other methods of intervention that we will use apart from an acute care environment comprise in-home monitoring, wellness education, and telephonic case management (Moraros, Lemstra, & Nwankwo, 2016). These interventions will assist the health care providers to improve post-acute care by allowing them to recommend and ensure proper follow up appointments, identifying critical topics for patients to discuss with primary care physicians, triggering alerts for possible urgent issues, sharing outcomes with treating physicians, and carrying out thorough in-home assessments.

References

Devereaux, D. S., & Zilz, D. A. (2018). Population health management: A community imperative. American Journal Of Health-System Pharmacy, 75(2), 46-48.

May, T., Byonanebye, J., & Meurer, J. (2017). The Ethics of Population Health Management: Collapsing the Traditional Boundary Between Patient Care and Public Health. Population Health Management, 20(3), 167-169.

Moraros, J., Lemstra, M., & Nwankwo, C. (2016). Lean interventions in healthcare: do they actually work? A systematic literature review. International Journal for Quality in Health Care, 28(2), 150-165.

Puro, J., & Falca-Dodson, M. (2016). Population Health: How Two Community-Based Collaborations Are Changing the Face of Healthcare in New Jersey and Beyond. MD Advisor: A Journal For New Jersey Medical Community, 9(1), 4-7.

Quinn Ahonen, E., Kaori, F., Cunningham, T., & Flynn, M. (2018). Work as an Inclusive Part of Population Health Inequities Research and Prevention. American Journal Of Public Health, 108(3), 306.