Tag Archives: care coordination

Two proposed rules open up opportunities for care coordination through telehealth

Over the summer, the Centers for Medicare and Medicaid Services (CMS) issued two proposed rules that will create mechanisms for some providers to receive payment for telehealth as well as other non-face-to-face and care coordination services using telecommunications technologies. Together, the changes proposed in the calendar year 2019 Medicare Physician Fee Schedule (PFS) and the Medicare Shared Savings Program (MSSP) proposed rules have the potential to enable new interactions that strengthen care access and coordination for a much broader set of patients.

The term “telehealth” is often used to broadly refer to the use of telecommunication technologies to furnish healthcare services. However, Medicare telehealth services specifically refer to a set of Part B-covered services specified under section 1834(m) of the Social Security Act. By law, Medicare fee-for-service (FFS) telehealth services under the PFS are currently subject to the following conditions:

• Provided using real-time, interactive audio and video
• Geographic restrictions on originating site (beneficiary location)
• Setting restrictions on distant site (provider location)
• Provider restrictions (and possibly further limitations due to state licensure laws)
• Limitations on type of visits

Waivers of Medicare telehealth rules are currently available under specific CMS Center for Medicare and Medicaid Innovation models. For example, under the existing Next Generation ACO Model, CMS has waived the geographic and originating site requirements for Medicare telehealth services. In addition, beginning in 2018, the Next Generation ACO Telehealth Waiver was expanded to include asynchronous telehealth services for teledermatology and teleophthalmology, which provides physician payment for the receipt and analysis of remote, asynchronous images for dermatologic and/or ophthalmologic evaluation.

MSSP accountable care organizations (ACOs) do not currently have such flexibility because no telehealth waivers are available to them. However, under the MSSP proposed rule, for 2020, CMS has proposed changes for telehealth services provided by ACOs that take on two-sided risk. Specifically, CMS proposes to expand the use of telehealth by ACOs by removing the geographic and originating site restrictions on these services. This means that ACOs will be able to provide telehealth services to beneficiaries in their homes as well as for beneficiaries obtaining care in metropolitan statistical areas (MSAs).

In addition, under the PFS proposed rule, CMS proposes to provide separate payment for new non-face-to-face services, virtual check-in visits, chronic care remote physiologic monitoring, interprofessional consultation, and remote professional evaluation of patient-transmitted information.

In this paper, Milliman’s Susan Philip, Carol Bazell, and Laurie Lingefelt describe these changes in greater detail and also discuss the possible implications for providers and MSSP ACOs in particular.

ACO: Care coordination measurement

Ward-BarbaraAccountable care organizations (ACOs) are evolving in their ability to measure the effectiveness of their efforts. This blog focuses on ACO analytics. It also reviews some insights from Modern Healthcare’s 3rd Annual ACO Survey and MedInsight analytic support of ACO effectiveness in care coordination.

Discussing results from Modern Healthcare’s ACO survey, the article titled “Still seeking best practices: Annual ACO survey shows care coordination remains a work in progress for many providers,” (subscription required) highlights both the progress and challenges facing ACOs at all levels of the ACO payment model, from providers to patients. The survey captured responses from over 35 ACOs across a variety of organizations including ACOs with and without hospitals, ranging in size from those that manage care for 553,000 covered lives to those with 5,600 covered lives. As noted in the article, as accountable care continues to expand and evolve, organizations seeking to embrace the payment model are experimenting with how best to measure the impact of critical strategies to improve patient care, including better care coordination.

To gain a better understanding of the care coordination measurements currently in place, Modern Healthcare added two new care coordination questions to this survey for the first time this year. They were: 1) Is care coordination measured? and 2) If so, name the ACO’s top five measures. The responses varied but it is clear that effective care coordination measures are still evolving.

While there are limited consistent measures across the spectrum of care coordination, there was consistent feedback from the respondents about what is currently used. Measures mentioned in the article and available in Milliman tools include:

• Readmission rates
• High-cost members
• Emergency department (ED) frequent visits
• Medication management
• Where patients received care, such as the emergency room, including the level of care
• Health promotion and education to monitor care coordination
• In-network coordination of care
• Patient engagement in care management

The patient engagement capabilities are available through the use of Milliman’s Enrollment Assessment and Survey tool. This is a web-based tool that includes three online survey tools that measure the level of engagement patients have in their own care, as well as the ability to track individuals and the related outreach made to members on a periodic basis, including action plans.

Below is an example of population level reporting for “in-network vs. out-of-network” emergency department (ED) visits. MedInsight uses the claim detail and the Milliman Heath Cost Guidelines analytic engine to efficiently bucket and identify the ED visits. Using this same engine and the MedInsight Analytic Cube, Figure 1 below delivers a report that provides a wealth of information about ED visits for a given population. In this example, the utilization of ED visits are split between in- and out-of-network visits, including the distribution of visits across each day of the week. Additionally, MedInsight provides additional metrics that provide further insight into the relationship between ED visits and inpatient admissions. Subsequent analysis may include:

• The review of admit hour to evaluate whether these visits were after hours or during normal office hours, highlighting education opportunities and access issues.
• Facility location of these ED visits.
• Evaluate the distribution of visits across the primary care physicians (PCPs) as well as members, to identify frequent visitors to the ED or specific patterns.
• Compare ED utilization to benchmarks: The percentage of admits from ED visits nationally is approximately 13%, according to CDC Fast Stats. More specific benchmarks, integrated into MedInsight reporting and analytics, are the Milliman Benchmarks, as shown in Figure 2 below.

Figure 1: ED Cases = In and out of ED, ED Visits Admitted = ED visit turned into IP Admit, ED Patient Visits = Total of ED Cases and ED Visits Admitted

Care Coordination

Figure 2: Compares the ED Visits to 50% Degree of Health Care Management and Well Managed degree of health care management (degree of health care management is a measure of the level of management processes in place, e.g., case management, UM, disease management)

Care Coordination 2

While real-time data is important for immediate care transition management, retrospective measures are also critical to evaluating success. MedInsight’s strength is to efficiently report cost and utilization detail at a population level as well as the ability to report on detailed member data. This provides access to several levels of analysis to more effectively manage and measure care coordination trends and analytics.

This article first appeared at Milliman MedInsight.

Help me, help you: Patient engagement and care coordination

As Jerry Maguire famously said, “Help me, help you!”

That sentiment has made its way in to our healthcare system. Accountable care organizations (ACOs) and patient-centered medical homes (PCMHs) have begun to demonstrate early successes of tangible savings with an emphasis on care coordination and higher involvement of patients to improve outcomes. While there are several variables that contribute to ACOs’ successes, the focus on more patient-centered care is critical. To address the challenge of involving patients more effectively, whether within an ACO or not, there is an interesting concept of identifying and managing patient engagement. The thought is that the more engaged patients are in their health decisions and their own behavior choices, the more effectively their health can be managed. This results in better patient outcomes and lower costs.

There have been a few studies recently that are beginning to show this trend.

Patient engagement can be defined using a general definition of the interventions designed to increase patient involvement, and the patient behavior that results from it. While there are multiple tools to evaluate and manage patient engagement, one particular tool known as patient activation measure is emerging as an up and coming tool to help to better understanding a person’s willingness and skills to engage in their care.

Patient activation is a term that describes the skills and confidence that patients possess to become actively engaged in their healthcare. The Patient Activation Measure (PAM) is an assessment consisting of 13 items. The assessment produces a score of zero to 100 based on how patients answer questions about their beliefs, knowledge, and confidence in managing health-related tasks. The score can be used to assign people to one of four levels, ranging from least activated (level 1) to most activated (level 4).

A study at the University of Oregon, reported in the February issue of Health Affairs, highlights the role that patients play in determining health-related outcomes. Patients who were more knowledgeable, skilled, and confident about managing their day-to-day health and healthcare (also known as “patient activation,” measured by the Patient Activation Measure) had healthcare costs that were 8% lower in the base year and 21% lower in the next year compared to patients who lacked this type of confidence and skill. As noted below, the level 1 or lowest level of patient activation, had a predicted per capita cost of $966 while the highest level of patient activation, or level 4, had a predicted per capita cost of $766. It is noteworthy that the inpatient and prescription drug costs were not included in the 2011 data because of system changes.

Below is an example of a PAM report for a member.

When combined with updated cost and utilization information, as well as the predictive capabilities within Milliman’s MedInsight decision warehouse, the addition of a patient engagement tool can be powerful. With this more comprehensive data set, it can help in effectively targeting outreach efforts as well as monitor the impact of patient engagement for improved patient outcomes and managing to lower costs.

Watch the blog for more details on how to approach these analytics.

This article first appeared at Milliman MedInsight.

Potentially avoidable events: The link to care coordination

Care coordination is a critical success factor in the broader spectrum of improved outcomes and effective cost management. There are many considerations when evaluating care coordination successes and opportunities.

Potentially avoidable events have been identified as a means of opportunity savings and improved access to care, including, but not limited to:

• Preventable hospitalizations
• Avoidable emergency department (ED) visits

These are critical components to analyze because:

• They may be an indication of access difficulties to the appropriate primary care
• When evaluating these events, it is also important to understand the geographic and socioeconomic factors to help identify opportunities for improved care coordination within a given population
• From a financial perspective, these events can also contribute to higher costs, presenting an opportunity for savings if better care coordination is in place
• The ability to identify and monitor occurrences of these types of events depends on the ability to identify events that are potentially preventable and events that are not preventable

Preventable hospitalization: Prevention quality indicators (PQI) of the Agency for Healthcare Research and Quality (AHRQ) provide a consistent and industry-accepted basis for objective measurement and analysis. Based on the AHRQ literature, hospitalization for an ambulatory care sensitive condition (ACSC) is considered to be a measure of access to appropriate primary healthcare. As a reminder, ACSCs are medical problems that are potentially preventable. While not all admissions for ACSCs are avoidable, it is assumed that appropriate ambulatory care could prevent the onset of this type of illness or condition, control an acute episodic illness or condition, or manage a chronic disease or condition. For example, hypertension (high blood pressure) is a condition that can be treated outside of a hospital. With proper medication and management of care, most people should not need to be hospitalized for hypertension. When interpreting the data, a disproportionately high rate is presumed to reflect problems in obtaining access to appropriate primary care.

The identified conditions include angina, asthma, chronic obstructive pulmonary disease (COPD), diabetes, grand mal status and other epileptic convulsions, heart failure and pulmonary edema, and hypertension.

Avoidable ED visits: The use of algorithms that provide bucketing of ED visits based on diagnosis codes supports the analysis of preventable ED visits. Some examples include the New York University algorithm and the Medi-Cal algorithm. Below is a sample from a large data set for a one-year period showing the percent of visits identified as preventable/avoidable and primary care treatable at a high-level rollup by line of business. Further analysis would include population-specific information to identify factors contributing to these types of visits. Risk adjusting these populations and evaluating by more specific demographics such as age and gender will provide further detail to drive an action plan to reduce these types of visits.

In closing, a better understanding of costs and benefits—how and to whom to target incentives, at which levels of risk—is essential for care coordination and other improvement initiatives to be economically viable and sustainable.

An interesting strategy to address readmissions: Nurse Led Clinics Battle Readmissions.

This article first appeared at Milliman MedInsight.