Systematizing Heart Failure Population Health

Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system

BACKGROUND

Mental health (MH) care often exhibits uneven quality and poor coordination of physical and MH needs, especially for patients with severe mental disorders. This study tests a Population Health Management (PHM) approach to identify patients with severe mental disorders using administrative health databases in Italy and evaluate, manage and monitor care pathways and costs. A second objective explores the feasibility of changing the payment system from fee-for-service to a value-based system (e.g., increased care integration, bundled payments) to introduce performance measures and guide improvement in outcomes.

METHODS

Since diagnosis alone may poorly predict condition severity and needs, we conducted a retrospective observational study on a 9,019-patient cohort assessed in 2018 (30.5% of 29,570 patients with SMDs from three Italian regions) using the Mental Health Clustering Tool (MHCT), developed in the United Kingdom, to stratify patients according to severity and needs, providing a basis for payment for episode of care. Patients were linked (blinded) with retrospective (2014-2017) physical and MH databases to map resource use, care pathways, and assess costs globally and by cluster. Two regions (3,525 patients) provided data for generalized linear model regression to explore determinants of cost variation among clusters and regions.

RESULTS

Substantial heterogeneity was observed in care organization, resource use and costs across and within 3 Italian regions and 20 clusters. Annual mean costs per patient across regions was €3,925, ranging from €3,101 to €6,501 in the three regions. Some 70% of total costs were for MH services and medications, 37% incurred in dedicated mental health facilities, 33% for MH services and medications noted in physical healthcare databases, and 30% for other conditions. Regression analysis showed comorbidities, resident psychiatric services, and consumption noted in physical health databases have considerable impact on total costs.

CONCLUSIONS

The current MH care system in Italy lacks evidence of coordination of physical and mental health and matching services to patient needs, with high variation between regions. Using available assessment tools and administrative data, implementation of an episodic approach to funding MH could account for differences in disease phase and physical health for patients with SMDs and introduce performance measurement to improve outcomes and provide oversight.

Factors Associated With Receipt of Diabetes Self-Management Education and Support for Type 2 Diabetes: Potential for a Population Health Management Approach

BACKGROUND

Population health management approaches can help target diabetes resources like Diabetes Self-Management Education and Support (DSMES) to individuals at the highest risk of complications and poor outcomes. Little is known about patient characteristics associated with DSMES receipt since widespread uptake of telemedicine for diabetes care in 2020.

METHODS

In this retrospective cohort study, we used electronic medical record (EMR) data to assess patterns of DSMES delivery from May 2020 to May 2022 among adults who used telemedicine for type 2 diabetes (T2D) endocrinology care in a large integrated health system. Multilevel regression models were used to evaluate the association of key patient characteristics with DSMES receipt.

RESULTS

Of 3530 patients in the overall cohort, 401 patients (11%) received DSMES. In adjusted multivariable logistic regression, higher baseline HbA1c (odds ratios [OR] 3.10 [95% confidence interval 2.22-4.33] for HbA1c ≥9% vs <7%), insulin regimen complexity (OR 3.53 [2.59-4.80] for multiple daily injections vs no insulin), and number of noninsulin medications (OR 1.17 [1.05-1.30] per 1 additional medication) were significantly associated with receipt of DSMES, whereas rurality and area-level deprivation of patient residence were not.

CONCLUSIONS

Diabetes Self-Management Education and Support remains underutilized in this cohort of adults using telemedicine to access endocrinology care for T2D. Factors contributing to clinical complexity increased the odds of receiving DSMES. These results support a potential population health management approach using EMR data, which could target DSMES resources to those at higher risk of poor outcomes. This risk-stratified approach may be even more effective now that more people can access DSMES via telemedicine in addition to in-person care.

Using Sacubitril/Valsartan to Decrease Health care Costs in Population Health Patients

Value-based care is the foundation of population health. The Health care Economic Efficiency Ratio (HEERO) scoring system is a promising new tool to measure the cost benefits of care in our Accountable Care Organization. HEERO score compares actual costs spent (utilizing insurance claims) and expected costs spent (estimated using the Centers for Medicare/Medicaid Services Risk score). Scores <1 suggest economic benefit. Sacubitril/valsartan has been shown to decrease readmissions for patients with heart failure (HF) and decrease health care costs. We explored the utility of sacubitril/valsartan in reducing HEERO scores and decreasing overall health care expenditure in patients with HF. Patients with HF in the population health cohort were enrolled. HEERO score was calculated for patients taking sacubitril/valsartan and other HF medications at 3-month intervals up to a year. We compared the average and total health care expenditure and inpatient days for patients on sacubitril/valsartan, spironolactone, β blocker (BB) along with spironolactone, BB and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker. For patients on sacubitril/valsartan, HEERO scores and inpatient days decreased (decreased health care expenditure) as the number of days of utilization increased (p <0.0001). In total, 270+ days of sacubitril/valsartan decreased health care costs by 22%. This cost reduction was mainly attributed to decreased inpatient days. Additionally, the combination of sacubitril/valsartan, spironolactone, and BB showed decreased HEERO score and inpatient days compared with spironolactone, BB and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker in male patients. Sacubitril/valsartan use beyond 270 days resulted in decreased health care expenditure in a population health cohort compared with other HF medications. This economic benefit is achieved through the reduction in hospitalizations. Sacubitril/valsartan is an integral part of value-based care providing high-value, cost-effective care, and bolstering the economic wellbeing of patient care. Payor sources should consider this in subsidizing the cost of the medicine.

Guidance for Timely and Appropriate Referral of Patients With Advanced Heart Failure: A Scientific Statement From the American Heart Association

Among the estimated 6.2 million Americans living with heart failure (HF), ≈5%/y may progress to advanced, or stage D, disease. Advanced HF has a high morbidity and mortality, such that early recognition of this condition is important to optimize care. Delayed referral or lack of referral in patients who are likely to derive benefit from an advanced HF evaluation can have important adverse consequences for patients and their families. A 2-step process can be used by practitioners when considering referral of a patient with advanced HF for consideration of advanced therapies, focused on recognizing the clinical clues associated with stage D HF and assessing potential benefits of referral to an advanced HF center. Although patients are often referred to an advanced HF center to undergo evaluation for advanced therapies such as heart transplantation or implantation of a left ventricular assist device, there are other reasons to refer, including access to the infrastructure and multidisciplinary team of the advanced HF center that offers a broad range of expertise. The intent of this statement is to provide a framework for practitioners and health systems to help identify and refer patients with HF who are most likely to derive benefit from referral to an advanced HF center.