Case Management Society of America


Optimizing Electronic Health Record Technology to Maximize the Value and Efficiency of Care Coordination


Care coordination has been identified by the National Institute of Medicine as a critical strategy that has the utmost potential to create pathways for effectiveness, safety and efficiency of the U.S. healthcare system (Agency for Health Care Research and Quality [AHRQ], 2016). However, the current healthcare landscape faces barriers in care coordination and transitions resulting in medical errors, waste of resources and, ultimately, harm to patients (Yeaman, Ko & del Castillo, 2015). The Joint Commission posits that 80 percent of errors are due to miscommunication, fragmentation of care and the need for standardized tools and processes for seamless communication (The Joint Commission, 2012). In addition, there are existing pressures from government and private payors, such as reducing 30-day readmissions and improving health outcomes while sustaining revenues. Today, most healthcare providers will agree that health information technology could have a significantly positive impact in the coordination of care that can avoid waste, improve health outcomes and lessen healthcare expenditures for the U.S. healthcare system (Lallemand, 2012).

Barriers in Care Coordination During Transitions of Care

Care coordination is defined as the organization of patient care activities between two or more participants in the patient’s care to facilitate appropriate delivery of healthcare services (AHRQ, 2016). However, the lack of clarity around what “care coordination” means is the challenge for information systems designers in their efforts to come up with ways to overcome the barriers through healthcare information technology (Schneider, Yudin & Gidengil, 2016). While the electronic health record (EHR) plays a crucial role in care coordination, Cedars-Sinai Health System recognized gaps in care documentation, information transmission, and care transitions. Therefore, these identified gaps collectively served as the impetus for stakeholders in the Cedars-Sinai Health System (CSHS) to design viable solutions to address this dilemma.

Cedars-Sinai Health System is a large quaternary healthcare system located in Los Angeles, California, with a population health strategy that includes a comprehensive care management program. Our care management model is based on the Case Management Society of America’s (CMSA) framework, which is a collaborative process of assessment, planning, facilitation, care coordination, evaluation and advocacy options and services with the individual and support system at the center (CMSA, 2017). This is accomplished through efficient communication and bridging the individual to appropriate resources to ensure quality of care and cost-effective outcomes. The population health program consists of patients for whom CSHS has some degree of financial accountability through healthcare contracts with payors. The aim for population health is to reduce cost by delivering quality care and achieving positive health outcomes.

The care management program is composed of the inpatient specialty practice care management (ISP-CM) and the ambulatory care management (ACM), which is outpatient-based. The program aims to become an industry leader in patient-centered care management. However, effective clinical information management system was a barrier to achieving this goal. Care gaps were inevitable due to challenges in accessing real-time data and visibility of clinical documentation among care team members. There was also heavy reliance on manual data collection and lack of standardization in care transitions documentation and handoffs that were not readily available for viewing or discovery by other healthcare providers. Finally, the multiple systems for inpatient clinical review documentation that is sent to the payors for certification of continued hospital stays resulted in workflow overload. These issues led to a strategic goal of optimizing Cedars-Sinai’s (EHR) system to develop patient-centered care coordination tools to be made available to team members across the pathways of care.

Gaps in Communication and Data Availability

Through the years, Cedars-Sinai’s ISP-CM and ACM processes were designed to focus on filling the gaps in communication handoffs during transitions of care. But it was impossible to accomplish this without the availability of a seamless technology-driven communication tool between providers, patients, caregivers and community support systems (NTOCC, 2010). Other than manual checks and utilizing internal audit tools, there were no other ways to validate the efficiency of care management goal-setting, interventions, prioritization, patient engagement, timeliness of telephonic outreach to patients, follow-up and substance of care management documentation.

The system needed to ensure that there was a tight chain with “checks and balances” from the point care management assessment, goal-setting and interventions are completed up to the daily prioritization of patient care using real-time information from the EHR. Our team identified a need to routinely validate adherence to these processes at any time and to produce a monthly program evaluation report to track our progress and measure our staff capacity. Furthermore, there was a need to have a reliable method of identifying potentially high-risk patients in real time. This was critical for timely outreach by the ACM to facilitate patient engagement, and this is accomplished by utilizing criteria that are embedded in the EHR, rather than depending on a monthly list that has information from 45 days ago. Patient engagement is a combination of patient activation using best-practice interventions by the healthcare provider to increase patient participation, such as complying with treatment or medication regimen or exercising (James, 2013). To build a high-risk registry, we needed to utilize evidence-based criteria that are embedded in the EHR rather than depending on a monthly list that has information from 45 days ago based on claims and other clinical data.

Lack of an Integrated System for Inpatient Clinical Reviews

Previously, Cedars-Sinai Health System’s EHR was not programmed to integrate critical features with workflows that integrated daily inpatient clinical reviews to justify continued stay in the hospital as required by payors. It consisted of two disparate systems for these required inpatients stay clinical reviews. The inpatient and outpatient assessments were also separate, and there was no ability to make the information visible to both ISP-CM and ACM staff. This resulted in duplicate efforts to procure patient information.

Evidence-Based Tools

The risk for readmission was not validated using an evidence-based tool that is embedded in the EHR. Therefore, it was left to the care manager to manually review a set criteria for identification of readmission risk. Additionally, referrals from the care managers to other disease-management programs such as diabetes, congestive heart failure, and hypertension were done manually instead of electronically. The care managers also had to fax clinical information to vendors for lower level of care referrals, such as skilled nursing facilities, and this function was not optimized using prompts in the EHR. Finally, patient instructions by the care managers were documented in the EHR progress notes with no ability to transfer to the patient’s discharge paperwork.

Electronic Referrals

The ACMs received referrals from multiple sources, e.g., phone, email, in-basket messaging, etc., without a centralized system. Primary care physicians (PCP) and other providers required an easy button within the EHR that will prompt a reminder and will generate an electronic referral with choices for the specific reasons for referral. Additionally, high-risk patients were identified monthly outside of the EHR and reported using spreadsheets. The care managers also utilized multiple lists such as ED list and daily inpatient discharge list, among others. Finally, care management workflows were not standardized, and adherence to processes could not be electronically tracked, thus requiring manual audits.

Other Areas for Optimization

The team, composed of our care management representatives and our information technology department, conducted an extensive review of other areas within the EHR that might benefit from technological enhancements. These areas for optimization included automating manual capture of interventions, tracking of the timing of follow-up outreach calls and automatic reminders to update care plans. It was also found that care management activation should be done without the manual searching for any patient activity in the electronic chart that may require intervention and prioritization, e.g., recent hospitalization, emergency room visit, abnormal blood glucose, and instead making these activities appear as alerts.

Care managers were also required to meet specific timelines in their documentation with required elements to ensure quality and substance, but these were extracted and assessed through manual chart audits. In addition, care management assessments were completed using preformed templates and free texts without the ability to extract discreet fields for future data analysis. There was also no availability for other healthcare providers to utilize existing care management documentation as a basis when conducting a subsequent clinical assessment to avoid repeating questions that were already answered by the patient.

In summary, the challenges to effective and efficient care coordination and transition of care management at Cedars-Sinai Health System stemmed from the lack of available real-time information among care teams, which resulted in significant gaps in care. The heavy reliance on manual data capture, manual hand-off communication during care transitions, and fragmented systems used for clinical documentation resulted in duplicative, time-consuming work.

Improvements Post Optimization

Between the period of March 2015 to August 2015, a team of information technology (IT) specialists and representatives from the care management team collaborated intensively to identify the vision for the project as well as the existing needs, challenges, and viable solutions. The steps included discovery and the identification of requirements, scope definition, workflow design and build, testing, training and the go live. These steps were all illustrated in a timeline that all team members and project leaders adhered to. The scope of the project was divided into three categories.

Reporting Goals

The first category was reporting goals. This task included creating patient triggers for activation in care management. It also tackled the development of patient registries, such as high risk and falls. The team also worked on the creation of staff and management dashboards that provide real-time patient information for prioritizing care and to track productivity or adherence to established processes.

Outpatient Outreach Management Enhancement Goals

The second category was outpatient outreach management enhancement goals. This included creating easy electronic referrals, longitudinal plan of care that is shown through a patient snapshot. This allows specific care activities to be displayed, such as the ACM care plan status toward achieving goals, recent ED and hospitalizations, risk tier or level, fall risk score, depression screening and others. In addition, patient care plans were embedded with best practices through branching logic that illustrates the appropriate interventions and desired outcomes based on the identified problem.

Inpatient Care Management Enhancement Goals

The third category was inpatient care management enhancement goals. This included dashboards that show ISP-CM patient lists and allowed for online real-time management to monitor staff workload and process adherence. Additionally, patients needing initial CM assessment are identified in real time as well as those needing daily clinical reviews for submission to payors to certify the hospital day.

The two disparate inpatient and clinical review documentation systems, namely CareWebQI® and InterQual®, that payors require are now embedded in the EHR. Further, patients with discharge orders are now identified in real time, and they appear on a list in the dashboard so that prioritization can be made by the ISP-CM to avoid delays in discharge. Also, referrals to other facilities are faxed automatically via communication management in EHR rather than manually. Finally, instructions and patient discharge goals now appear in a form called After Visit Summary, which is part of the patient’s discharge paperwork as well as in the patient personal EHR record (MyCSLink®), which can be accessed remotely. Comparisons of the pre-optimization and post-optimization environments illustrate a significant improvement in time and effort to effectively coordinate care across the continuum.

Case Example: Fall Risk Patient

One of the positive outcomes from the new checks and balances provided by the improved EHR system and processes is our Fall Risk Assessment and Intervention Workflow. It depicts the proactive process of managing patients at risk for falls from identification to the interventions using predefined criteria. The process begins when a patient has been identified as fall risk by the primary care physician (PCP) using a tool in the EHR but the result is not readily identifiable or collectible for the ACM. This information may sit in the EHR until later discovered incidentally by the ACM while doing additional chart review when a patient is referred or unless there was a referral from the PCP to ACM to specifically address the fall risk issue.

Timely initiation of the fall risk protocol using specified interventions is critical to avoid foreseeable injuries to the patient. This gap in care transition may be avoided using automatic alerts and an accessible patient registry in the EHR with real-time information. The fall risk assessment and intervention workflow illustrates the process from patient identification to the subsequent process for interventions utilizing predefined criteria.

After the optimization, predefined criteria were selected and embedded in the EHR to accurately identify a fall risk patient. These criteria included any patient with a positive fall risk score that was documented either in the inpatient setting or outpatient setting, patients with documented medications that may predispose someone to falls, those who have fall-risk related diagnoses, and patients who are over 85 years old. Their names are automatically entered in the fall risk registry. An alert appears in the ACM daily dashboard located in the EHR, and the patients are referred to the ACM for care management outreach. The EHR optimization also allowed the ACM to benefit from electronic best practice alerts, branching logic for specific interventions, such as referral to home health, automatic reminder prompts to ensure ACM adherence to specified workflows and best practices and timely telephonic follow-up.

Utilizing Reports for Performance Improvement and to Validate Adherence to Process

One of the biggest challenges in providing care management services is to be able to show value by delivering health benefits to those with many needs while improving patient experience of the care system and driving overall healthcare costs (Craig, Eby & Whittington, 2011). Our challenge was to better evaluate and capture value of care management work through key metrics and indicators. We needed reports that are connected to our organizational priorities and reflective of our adherence to established workflows. These organizational priorities include increasing quality of care and reduction in hospital readmissions, unnecessary hospitalizations and emergency room visits, and patient compliance with treatment regimen, to name a few. We also needed to have daily reports that are reflective of staff performance in real time when it comes to care manager productivity or caseloads, timeliness in conducting initial assessments and clinical reviews, and list of patients with 30-day readmissions, among others as illustrated below.

Inpatient Care Management

As a result of this optimization, reports will be generated on a weekly and monthly basis to show key inpatient admission information to validate the efficiency of our inpatient care management processes. This includes the following:

  • Number of patients with 30-day readmissions by care manager, primary care physician, diagnosis, date of discharge, discharging hospitalist, and payor.
  • Average patient length of stay categorized by care manager and program total based on the number of patients in Cedars-Sinai population health attributed patients in its registry compared to previous year’s performance.
  • Percentage of referrals by each ISP-CM to population health programs, such as disease management, ambulatory care management and supportive care medicine, among others.
  • ISP-CM’s individual performance dashboards to validate compliance with departmental, regulatory and accrediting standards. This includes timeliness of initial assessments within 24 hours of admission, daily utilization reviews, progress notes, documenting the estimated day of discharge, and others.

Ambulatory Care Management

Similarly, our ambulatory care management reports depict elements to validate efficiency of processes, workflows, adjustment of patient assignments as needed and the adherence to process of following up with outreach calls to patients. These daily reports, which are now visible and readily accessible in the daily dashboards appearing in the EHR, include:

  • Enrollment information containing concurrent disease management programs a patient is not enrolled in, percentage of patients with advance directives or Physicians Orders for Life Sustaining Treatment (POLST)
  • Patients enrolled and outreached telephonically within 72 hours of referral per established workflows
  • Panel size by month and number of open and closed cases per ACM per month
  • Case mix of enrolled patients by type of payor
  • Complex cases opened for more than 90 days
  • Patient goals information that shows patients with unmet or overdue goals and exceeding 90 days of enrollment
  • Non-capture that shows reasons for non-enrollment


The results of this initiative reinforced the need for healthcare organizations that are involved in population health management care coordination to leverage technology to bridge the gap in care transitions. Organizations can no longer sustain meeting changes in healthcare delivery demands using a one-size-fits-all approach to achieve affordable, high-quality population health outcomes (Craig, Eby & Whittington, 2011). In the advent of value-based purchasing models, patient satisfaction, and accountable care organizations, population health management becomes even more important to provide stronger technological infrastructure to care management services (AHC Media, 2015).

A stronger technological infrastructure simply means a higher ability for care managers to efficiently coordinate care that is timely, appropriate and contributes to patient satisfaction. Our organization’s commitment to adequately position itself in this changing healthcare landscape became more evident through investments in healthcare information technology. Tailoring this healthcare technology to meet the specific needs of our population health patients helped in creating care management workflows and electronic safeguards to ensure adherence to these workflows as well as providing measurable standards to validate efficiency in care coordination. Finally, it offered an ability to ensure that care management resources are utilized for the appropriate patients based on risk stratification and an efficient electronic referral process.

Future Implications

The completion of this initiative prompted further discussions among Cedars-Sinai Health System’s leaders to continue leveraging technology to connect its many operations. Although there was no formal survey conducted among members of the care management team, many staff members have expressed relief to be able to document in one system and to see what other members of the team have done to facilitate continuity of care. Additionally, avoiding the duplication of work that is made possible through the portability of clinical information across the continuum is a welcome relief, especially in care transitions. Currently, planning and execution of enhancements are underway to include additional patient engagement tools, such as the Patient Activation Measure (PAM®), interoperability functionality to share information with select post-acute discharge facilities, and doing the same optimization for clinical social work.

Further, the timeliness of complying with health plan requirements for inpatient clinical reviews has been achieved by centralizing two disparate systems into one platform. Equally important are the productivity dashboards that provide real-time information to managers to ensure that existing and potential gaps in care coordination are identified and addressed timely. The work of the care management team members has dramatically improved across the board.

This program showed that technology that can cater to the specific needs of the organization is currently available. However, organizations must continue to ask about its commitment to support these population health initiatives with the available health information technology (Vincent, 2014). In our case, Cedars-Sinai Health System responded to the need. Its efforts to increase its technological efficiencies to support the care management programs are a testament to this readiness.  ■

Carlo Carado, JD, MSN, RN, CCM, CCCTM, is the Director of Care Management and Social Work at Cedars-Sinai Medical Network, the physician network of Cedars-Sinai Health System in Los Angeles, California. He has been involved in population health, care management, care coordination and education for over twenty years combined. He is also a certified case manager (CCM), board certified in care coordination and transition management (CCCTM) and holds a Master of Science in Nursing and Juris Doctorate degrees. Currently, he is a doctoral candidate in education with specialization in transformational leadership.


Agency for Healthcare Research and Quality. (2016). Care Coordination. Retrieved on Feb. 8, 2017 from

AHC Media (2015). Is your staffing ratio right for your case management model? Retrieved on Feb. 8, 2017 from

Case Management Society of America (CMSA), 2017. What is a case manager? Retrieved on Feb. 23, 2017 from

Craig, C., Eby, D., Whittington, J. (2011). Care Coordination Model: Better Care at Lower Cost for People with Multiple Health and Social Needs. IHI Innovation Series white paper. Retrieved on Feb. 21, 2017 from

James, J. (2013). Patient engagement. Health Policy Briefs. Retrieved on Feb. 12, 2017 from

Lallemand, N. (2012). Reducing waste in health care. Health Policy Briefs, December 12, 2012. Retrieved on Feb. 22, 2017 from

Schneider, E., Rudin, S., Predmore, Z., Gidengil, C. (2016). Knowledge gaps inhibit health IT development for coordinating complex patients’ care. American Journal of Managed Care, 22(9), 317-322. Retrieved on Nov. 2, 2016 from

The Joint Commission (2012). Joint commission center for transforming healthcare releases targeted solutions tool for hand-off communications. Retrieved on Feb. 22, 2017 from

Vincent, W. (2014). Using technology to optimize population health care coordination outcomes. Healthcare Informatics. Retrieved February 2017 from

Yeaman, B., Ko, K., del Castillo, R. (2015). Care transitions in long-term care and acute care: Health information exchange and readmission rates. The Online Journal of Issues in Nursing, 20 (3). DOI: 10.3912/OJIN.Vol20No03Man05.

Recent Tweets

Connect with CMSA