Tag Archives: population health management

Chronic disease management considerations

Disease management strategies can include a range of activities with varying approaches and levels of intensity. These strategies are also often mixed with other care management approaches.

Differentiating the disease management programme components, targets and interventions is important before evaluating return on investment or cost and quality impact. There are three broad programme designs to consider:

• Transitional care models
• Telephone-based disease management
• Utilisation and case-based disease management programmes

Although demonstrating savings in disease management programmes has proven difficult, it is not impossible. In this paper, Milliman’s Lalit Baveja and Mason Roberts explain the reasons why and also explain why it’s important to thoughtfully manage and continually review performance.

Population health and value-based care collaboration: Primary care case study

Many health systems around the world are introducing new care models which claim to replace expensive acute inpatient care with more primary and community-based services. This paper by Milliman consultants examines the primary care redesign of seven US practices over the course of three years, including their reported utilisation and savings achievements.

Population health analytics for India’s health insurance industry

In India, recent regulatory changes mandating guaranteed renewability, lifetime coverage and restricted premium revision opportunities imply that any substandard risk in the current portfolio could potentially be retained for life. This necessitates a different approach to managing insurers’ growing portfolios.

This article by Milliman’s Lalit Baveja explains how insurers can benefit from treating their covered members using analytics based on population health principles. Such an approach requires a better clinical understanding of member populations to identify the most effective and cost-efficient strategies for managing members’ health and preventing hospitalizations and claims in the long run.

Cascade Health Alliance chooses Milliman PRM Analytics for population risk management

Milliman PRM Analytics™ (PRM), a leader in data-driven value-based healthcare support systems, today announced that Cascade Health Alliance (CHA), a coordinated care organization (CCO) serving Klamath County, Oregon, has selected the PRM Platform and its suite of cloud-based analytic and population risk management solutions to support their growing clinical integration initiatives.

“By giving us greater ability to better manage our population health, the PRM tool allows for more efficient risk stratification and management,” said Peter Waziri, CHA’s Chief Financial Officer. “Working with Milliman and PRM Analytics will help CHA to better serve our members by allowing staff deeper insights to those members’ health information.”

“We are pleased to be selected by Cascade to help them manage their risk-based populations. Milliman continues to be the industry leader in helping providers manage population risk. PRM™ represents a disruptive approach to population stratification and management. The analysis focuses on the prospective opportunity for potentially avoidable costs so the patient care team can focus on them in advance. Care management can then be focused on the patients with the greatest potential to ‘bend the cost curve’ resulting in the optimal deployment of limited care management team resources,” said Art Wilmes, FSA, MAAA, a Principal and Consulting Actuary in Milliman’s Indianapolis office.

“I have access to new ways of seeing cross-sectional data and how it all works together,” said Angela Leach, CHA’s medical informatics analyst. “Case managers will use it to get at-a-glance profiles of patients they are caring for, and the quality management department can use it to find ‘hot spots’ that may benefit from additional programs.”

The case management team at CHA can use PRM Analytics in a variety of ways, according to Diane Barr, Director of Case Management. “We can identify high-cost members, plus we can filter for diagnosis and identify members for disease management,” Barr said. “We can also look at an individual member to determine their utilization, chronic conditions and other details. The best part is we can do risk stratification and identify members that are at the highest risk for re-hospitalization or emergency department utilization. The program is easy to use and provides us with volumes of useful information.”

Developing population health management programs under risk-based contracts

Risk-based contracts are driving the development of population health management programs (PHMPs) that are designed to achieve the Institute for Healthcare Improvement’s Triple Aim goals. Health systems may need to redesign how they deliver healthcare to meet these goals. Risk-based contracts often give providers both the financial flexibility and incentive to redesign care.

In the article “Population health management program development: The path to the Triple Aim,” Milliman’s Nick Creten and Blaine Miller discuss the following five steps healthcare organizations must address when developing a PHMP in a risk-based contracting environment.

Step 1: Assess population costs, utilization, and risk
Step 2: Identify opportunities
Step 3: Segmentation
Step 4: Intervention development
Step 5: Monitor, assess, and improve

Developing a population health management program: Considerations for population segmentation

Predictive analytics can improve medical outcomes by identifying patients needing medical interventions. Population segmentation is a common method used to identify such patients. Individuals are grouped into cohorts to help improve the quality of their care. In this paper, Milliman’s Jordan Paulus and Nick Creten explore four common methods for population segmentation: cost cohort segmentation, condition cohort segmentation, utilization cohort segmentation, and social cohort segmentation.