Deliverable 6 - Chronic Diseases and Population Health Management

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Running head: POPULATION HEALTH MANAGEMENT DASHBOARD

POPULATION HEALTH MANAGEMENT DASHBOARD 2

Population Health Management Dashboard

Kimberly Huff

Rasmussen College

Deliverable 4 Submitted January 24th, 2021

Population Health Management Dashboard

Health Needs of the Population

Approaches to Care for Patients with Diabetes	Explanation
Individual patient care	The goals and needs of diabetes patients regardless of their age or gender are unique. Therefore, treatment plans are devised based on a comprehensive understanding of the patients’ medical needs. Additionally, a wide range of factors that impact on the treatment plan such as the barrier to care, education needs, cultural issues, race and social history should be considered. The treatment plan to be employed should include a wide range of factors including ongoing support, follow-up interventions as well as medical treatment.
The patient-centered treatment plan	Diabetes is a chronic condition that calls for a high level of self-awareness and involvement in the treatment. As such, a collaborative model that entails goal setting and patient involvement paves the way for behavioral change.
Teamwork	The best approach that can be used to manage diabetes is using a team that could be composed of health specialists, exercise physiologists, diabetes educators and clinicians,

Diabetes patients should receive an accurate diagnosis to determine the type of disease that they could be ailing from. It follows that the diagnosis will be made based on the fasting plasma glucose, random plasma glucose as well as the oral glucose tolerance tests. These tests should be repeated to ensure that the patient gets an accurate diagnosis. Following an accurate diagnosis, a management plan is established for patients to address various areas including physical activity, meal planning and nutrition, SMBG (self-monitoring blood glucose), the treatment of hyperglycemia and hypoglycemia and revaluation of the treatment goals after which medications are adjusted accordingly.

Data sources

Clinical Data

Survey Data

DARTNet

This is an institute that works in collaboration with institutions to establish a wide range of data from patient-reported outcomes, claims, and electronic health records.

NAMCS (National Ambulatory Medical Care Survey)

This is a survey that represents the national population based on the patients’ patient to physician’s office.

This contains objective information on chosen risk factors including ethnicity, race, sex and age, laboratory results and diagnosis.

ACS (American Community Survey)

This is a national survey that offers information on demographic variables such as income, education, sex, age and ethnicity.

BRFSS (Behavioral Risk Factor Surveillance System)

This is a telephone survey that aims at collecting information on chronic heath conditions and associated health risk behaviors.

CHIS (California Health Information Survey)

This survey concentrates on the state of California and it covers information on demographics, and risk factors.

Data Sets

It has been found that administrative data that is used for health insurance claims, survey data, laboratory reporting systems, clinical data from EHR (electronic health records). The various data types have their pros and cons. These data sets are important in the evaluation of the condition, its impacts on the population and the role of the health care system in managing the condition.

Pros

Cons

Clinical and administrative data

Large sample size

Clinical data collects comprehensive information in laboratory tests, vital signs, medications, procedures and diagnoses.

Administrative data entails information on procedure codes, diagnosis, prescriptions and insurance enrollment.

Individuals that have not been served by the health system are left out

Geographical clustering

Does not have critical information on income and race

Gaps exist when the test have not been ordered

Non-random samples exist

Survey data

Entails important information such as income and race

Represent specific populations.

Some of the data that is used can represent the state level

Some of the tests that are conducted can cover undiagnosed diabetes

Possibility of bias

It does not entail the tests for undiagnosed cases of diabetes

The data is not adequate to be applied at the national and state levels