A practical model for research with learning health systems: Building and implementing effective complex case management

Transforming Health Care from Volume to Value: Moving the Needle Through Population Health

United States health systems face unique challenges in transitioning from volume-based to value-based care, particularly for academic institutions. Providing complex specialty and tertiary care dependent on servicing large geographic areas, and concomitantly meeting education and research academic missions may limit the time and resources available for focusing on the care coordination needs of complex local populations. Despite these challenges, academic medicine is well situated to capitalize on the promise of value-based care and to lead broad improvements in both teaching and nonteaching hospitals. If properly executed, value-based care and complex specialty care can be complementary and synergistic. We postulate that the transition from volume to value in population health requires all health care organizations to advance and formalize infrastructure in 3 core areas: organizational capabilities; provider engagement; and engagement of the patient, family, and community. Although these apply to all organizations, for academic health systems, this transition must also be interwoven with the other domains of the tripartite mission.

Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study

Background

Impactability modeling promises to help solve the nationwide crisis in caring for high-need high-cost patients by matching specific case management programs with patients using a “benefit” or “impactability” score, but there are limitations in tailoring each model to a specific program and population.

Objective

We evaluated the impact on Medicare accountable care organization savings from developing a benefit score for patients enrolled in a historic case management program, prospectively implementing the score, and evaluating the results in a new case management program.

Methods

We conducted a longitudinal cohort study of 76,140 patients in a Medicare accountable care organization with multiple before-and-after measures of the outcome, using linked electronic health records and Medicare claims data from 2012 to 2019. There were 489 patients in the historic case management program, with 1550 matched comparison patients, and 830 patients in the new program, with 2368 matched comparison patients. The historic program targeted high-risk patients and assigned a centrally located registered nurse and social worker to each patient. The new program targeted high- and moderate-risk patients and assigned a nurse physically located in a primary care clinic. Our primary outcomes were any unplanned hospital events (admissions, observation stays, and emergency department visits), count of event-days, and Medicare payments.

Results

In the historic program, as expected, high-benefit patients enrolled in case management had fewer events, fewer event-days, and an average US $1.15 million reduction in Medicare payments per 100 patients over the subsequent year when compared with the findings in matched comparison patients. For the new program, high-benefit high-risk patients enrolled in case management had fewer events, while high-benefit moderate-risk patients enrolled in case management did not differ from matched comparison patients.

Conclusions

Although there was evidence that a benefit score could be extended to a new case management program for similar (ie, high-risk) patients, there was no evidence that it could be extended to a moderate-risk population. Extending a score to a new program and population should include evaluation of program outcomes within key subgroups. With increased attention on value-based care, policy makers and measure developers should consider ways to incorporate impactability modeling into program design and evaluation.

Risk from delayed or missed care and non-COVID-19 outcomes for older patients with chronic conditions during the pandemic

Background

During the COVID‐19 pandemic, patients with chronic illnesses avoided regular medical care, raising concerns about long‐term complications. Our objective was to identify a population of older patients with chronic conditions who may be at risk from delayed or missed care (DMC) and follow their non‐COVID outcomes during the pandemic.

Methods

We used a retrospective matched cohort design using Medicare claims and electronic health records at a large health system with community and academic clinics. Participants included 14,406 patients over 65 years old with two or more chronic conditions who had 1 year of baseline data and up to 9 months of postpandemic follow‐up from March 1, 2019 to December 31, 2020; and 14,406 matched comparison patients from 1 year prior. Risk from DMC was defined by 13 indicators, including chronic conditions, frailty, disability affecting the use of telehealth, recent unplanned acute care, prior missed outpatient care, and social determinants of health. Outcomes included mortality, inpatient events, Medicare payments, and primary care and specialty care visits (in‐person and telehealth).

Results

A total of 25% of patients had four or more indicators for risk from DMC. Per 1000 patients annually, those with four or more indicators had increased mortality of 19 patients (95% confidence interval, 4 to 32) and decreased utilization, including unplanned events (−496 events, −611 to −381) and primary care visits (−1578 visits, −1793 to −1401).

Conclusions

Older patients who had four or more indicators for risk from DMC had higher mortality and steep declines in inpatient and outpatient utilization during the pandemic.

Self-Assessment of Biomedical Activity Related to Medical Devices Embedded in EMS Ambulances: Towards a Roadmap for an Efficient Improvement

Objective:

The present investigation is focused on a self-assessment of the biomedical activity related to embedded Medical Devices on board a fleet of 46 EMS medicalized ambulances, according to the High Authority of Health standard (criterion 8K) and the Guide of the Good Practices of Biomedical Engineering.

Materials and Methods:

The methodology adopted for this purpose is based on an analysis allowing the evaluation and observation of practices related to biomedical activity in these ambulances. An initial assessment, carried out in March 2021, made it possible to measure the gaps between the actual situation and the recommendations of the two self-diagnosis tools (High Authority of Health and Guide of the Good Practices of Biomedical Engineering standards). A series of corrective actions were proposed and then implemented. A second self-assessment took place after 6 months, in October 2021.

Results:

Between March and October 2021, an improvement in the scores for almost all the axes of the two self-assessment tools was noted. Indeed, the score of the self-assessment for the High Authority of Health reference system rose from 44% in March 2021 to 63% in October 2021, i.e. an increase of 19%, and that of the Guide of the Good Practices of Biomedical Engineering increased from 67.54% in March 2021 to 80.96% in October 2021, i.e. an increase of 13.42%.

Conclusion:

The implementation of a maintenance strategy integrating the notion of quality, relevant procedures and pertinent work tools has made it possible to significantly improve the biomedical activity within the medical ambulances and to optimise the embedded medical devices.

Learning health systems in primary care: a systematic scoping review

BACKGROUND

Learning health systems have been gaining traction over the past decade. The purpose of this study was to understand the spread of learning health systems in primary care, including where they have been implemented, how they are operating, and potential challenges and solutions.

METHODS

We completed a scoping review by systematically searching OVID Medline®, Embase®, IEEE Xplore®, and reviewing specific journals from 2007 to 2020. We also completed a Google search to identify gray literature.

RESULTS

We reviewed 1924 articles through our database search and 51 articles from other sources, from which we identified 21 unique learning health systems based on 62 data sources. Only one of these learning health systems was implemented exclusively in a primary care setting, where all others were integrated health systems or networks that also included other care settings. Eighteen of the 21 were in the United States. Examples of how these learning health systems were being used included real-time clinical surveillance, quality improvement initiatives, pragmatic trials at the point of care, and decision support. Many challenges and potential solutions were identified regarding data, sustainability, promoting a learning culture, prioritization processes, involvement of community, and balancing quality improvement versus research.

CONCLUSIONS

We identified 21 learning health systems, which all appear at an early stage of development, and only one was primary care only. We summarized and provided examples of integrated health systems and data networks that can be considered early models in the growing global movement to advance learning health systems in primary care.

Remembering Ben-Tzion Karsh's scholarship, impact, and legacy

Dr. Ben-Tzion (Bentzi) Karsh was a mentor, collaborator, colleague, and friend who profoundly impacted the fields of human factors and ergonomics (HFE), medical informatics, patient safety, and primary care, among others. In this paper we honor his contributions by reflecting on his scholarship, impact, and legacy in three ways: first, through an updated simplified bibliometric analysis in 2020, highlighting the breadth of his scholarly impact from the perspective of the number and types of communities and collaborators with which and whom he engaged; second, through targeted reflections on the history and impact of Dr. Karsh's most cited works, commenting on the particular ways they impacted our academic community; and lastly, through quotes from collaborators and mentees, illustrating Dr. Karsh's long-lasting impact on his contemporaries and students.