WHITE PAPER
Maximize the Impact and Efficiency of
Care Management Teams Through
Whole-Patient Insight
Augment Clinical and Utilization Data with Whole Patient
Insight to Drive Healthcare Quality Up and Costs Down
Alicia Gomez, MSW, MBA
Randy K. Hawkins, MD
The transition of volume-based healthcare to a value-based model of payment and delivery has
brought care management and care coordination to the forefront of healthcare operations. With
the assumption of financial risk has come the need for hospitals and health systems to optimize
care across the continuum in a cost-effective manner. Data aggregation and information sharing
within care management systems and population health platforms are important elements of the
overall plan, but targeted resource allocation and program matching will drive hospitals and
health systems to their bundled payment initiative and accountable care goals by delivering
higher quality care at a much lower cost. Care management teams and processes are central to
managing length of stay, achieving full and fair reimbursement, and facilitating patient transition
from the controlled environment of the hospital to home, or other post-acute care setting. In our
last white paper, we described the role of predictive analytics and workflow optimization in
readmission reduction programs of hospitals and health systems. Here, we focus on the role of
predictive analytics and whole-patient insight in resource allocation, cost-containment, and
patient relationship management strategies of the provider.
Delivering Quality in the Face of Rising Uncertainty
A systematic approach to managing and optimizing care delivery across multiple settings is a key
component of any value-based healthcare strategy. At issue is the increased uncertainty and risk
that are introduced as a patient transitions from one level of care to the next, and especially as it
occurs upon discharge from the hospital. In fact, the hospital admission represents the most
controlled and predictable point along the care continuum. Patients are monitored, examined,
and treated by professional medical staff, around the clock in accordance with a detailed
inpatient treatment plan. Negative changes in the patient’s medical condition can, and do occur,
but physicians, nurses, and ancillary providers are in attendance to quickly diagnose and treat the
problem. Upon discharge from the hospital, a patient’s clinical condition has stabilized to the
point where it is safe for them to be transferred to a post-acute care setting of lower acuity and
reduced cost, but what about the uncertainty and risk patients face in the context of their daily
lives? How much is known about a patient’s home stability or financial resources? Are there
transportation issues? Do they have a car? Are healthy food options located near their home? Can
they adhere to a medication regimen and comply with the discharge plan? Do they have the
resources and support to follow up with their provider, as needed, and participate in their own
well-being? There is little information in the electronic health record (EHR) to answer these
questions, and care management teams need this insight in order to effectively allocate resources
and coordinate care. As unrecognized risk rises, so do failed discharges, unplanned readmissions,
and associated healthcare costs. Predictive analytics can provide key socio-demographic insight
into the lives of patients to help providers develop targeted intervention strategies for the diverse
populations they treat.
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
Delivering Quality at a Reduced Cost
In addition to promoting high quality care, a targeted approach to care delivery can reduce the
overall cost to the hospital, health system, or network. Care management costs rise from the
human resource requirements to deliver the care, and from the cost of programs and program
delivery. Allocating these resources in a patient-specific manner improves the quality of the
intervention strategy and drive efficiencies into team performance. As the insured patient
population rises, and the complexity of post-acute care they receive increases, care
coordination resources are becoming increasingly strained. It is critical that we drive
efficiencies into the care management system, to enable these resources to do their jobs
effectively and to maximize the return on the investment already made in this area. It is
unlikely that technology-enabled solutions will result in a reduction of case managers and care
coordinators, but rather predictive analytics and workflow solutions will enable teams to
operate with greater capacity and throughput to meet the rising number of patients under
management. As an example, caseload complexity is highly variable and can adversely affect
the productivity, throughput and overall success of a care management team. The Case
Management Association of America along with the National Association of Social Workers has
indicated that caseload volume must be adjusted to account for individual case complexity.
The clinical, psychosocial and environmental needs of patients all contribute to case
complexity, and they each influence the total time required to assess patient risk. A care
management team armed with patient-specific insight can assign patients based upon
complexity instead of number of cases per day. Senior case managers may be more valuable
handling fewer, more complex cases, while less experienced care team members may
efficiently handle a greater number of routine cases. Allocating resources by skill and
experience will deliver a higher quality of care at a lower cost to the provider.
Delivering Insight Seamlessly for Providers
Predictive analytics can augment the clinical information in an EHR if they provide sociodemographic, economic, and behavioral insight into a patient’s life. As much as 70% of
consumer health is driven by these factors [see below], yet this information is not routinely
available in the EHR. If available, it would provide much needed context and help guide the
best treatment plan across care settings. Clinical results and utilization data are easily found in
the EHR, and are certainly important factors when assessing risk, but socio-demographic data
elements complete the picture for providers, and in order to optimize care team efficiency, this
level of whole-patient insight is required.
What is Whole-Patient Insight?
According to the CDC, social and economic factors drive
upwards of 40% of consumer health, and behavioral
elements account for another 30%. NCQA as part of
their Patient Centered Medical Home certification
criteria identified patient context as a critical input to
physician accreditation as a medical home.
Much of this important socio-demographic data is not
present in the electronic medical record or easily
accessible to clinicians. Technology, today, can gather
whole-patient insight in a proactive manner.
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
In order for this approach to be successful, predictive analytics must be integrated in a manner
that supports provider workflow, as well as the targeted intervention strategies that follow.
Both raw data and detailed analyses must remain in the background, so as not to further
inundate providers who already suffer from data fatigue. If done well, however, an integrated,
technology-enabled solution can help improve both the capacity and performance of the care
management team. Imagine logging into the case management system and each case manager
has an assigned list of patients including patient-specific socio-demographic risk factors – red,
yellow, green – and for those in the highest risk segments, the underlying stressors – nutrition,
housing, finances, transportation etc. are flagged. Interventions can then be mapped to
patient-specific need instead of broad-based program being offered to every patient. By
employing this approach of program matching, wasted effort and costs could be dramatically
reduced.
Delivering High Quality Care with a Personal Touch
In addition to the quality, efficiency, and cost benefits, excellence in care transition
management also represents an important point of differentiation for providers looking to
stand out to the healthcare consumer, as well as for those looking to build upon existing
consumer loyalty initiatives.
Source: IHI Innovation Series white paper. Cambridge, Massachusetts: Institute for Healthcare Improvement; 2012.
Patient perception of the care they receive is a key component of the Institute for Healthcare
Improvement’s Triple Aim Initiative. Providers must appreciate this patient perspective, not
only as it pertains to quality, but also as it relates to patient relationship management and
loyalty programs. Competition in the healthcare market is at an all time high. Patients have
become active healthcare consumers, and they shop for high quality, low cost healthcare
options in their communities. High-deductible plans and increased co-pays drive patients to
engage in their own health, and align with providers who help them succeed in these efforts.
As with consumers in other service industries, patients value service quality, in addition to
overall cost. They form lasting opinions and assign loyalty to the best service providers in an
industry. Healthcare is no exception. Personalized service and individual attention are
attractive components of healthcare, and patients perceive providers as more engaged when
they act in this manner. When providers demonstrate deeper insight into their customers it
helps establish a differentiated level of engagement and care. Predictive analytics which focus
upon these socio-demographic insights help shape patient perception, and further promote
patient loyalty to an individual clinician or a provider network.
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
With whole patient insight embedded into case management systems and workflow, valuable
and often constrained provider resources are better positioned for success. To understand the
context within which patients live is to better understand the programs and services that will
deliver the highest quality care in a patient-specific manner. In addition, the re-imagined
process delivers an enhanced patient experience by delivering a higher level of engagement to
healthcare consumers. While the power of whole patient insight is far-reaching, the
opportunity for provider organizations is to augment clinical and utilization data with sociodemographic, economic, and behavior elements to drive healthcare quality up, and total
healthcare costs down.
About Connance: Connance is the industry’s premier source of predictive analytic technology
solutions that enable healthcare providers to optimize financial and clinical workflows for
sustained performance improvement.
About The Authors: Randy K. Hawkins, MD is Chief Medical Officer at Connance.
Alicia Gomez, MSW, MBA, is Director, Population Health Management at Connance.
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com
200 West Street, Third Floor I Waltham, MA 02451 I www.connance.com