Care Management Program Research Articles

Hubungan Perilaku Self Management Dengan Kadar Gula Darah Pada Pasien Diabetes Melitus Tipe II Di Puskesmas Sekupang Kota Batam

Diabetes mellitus is a chronic disease but can be controlled or prevented with self-management. Self-management of diabetes aims to control blood glucose levels optimally and prevent complications that arise. Activities that can be done include diet, physical activity/exercise, blood glucose control, taking medication regularly and foot care. This research aims to determine the relationship between self-management behavior and blood sugar levels in type 2 diabetes mellitus patients. This type of research is a quantitative research method with a correlative descriptive design with a cross sectional approach. Data collection used a non-probability sampling technique in the form of accidental sampling with a sample size of 36 respondents, using the chi square test. Most respondents have sufficient self-management (69.4%). Apart from that, the majority of respondents had normal blood sugar levels (97.2%). The results of the analysis test were obtained with a P value = 0.004 (<0.05). It is hoped that the UPTD BLUD Sekupang Community Health Center will create a diabetes self care management program with efforts to improve blood sugar control.

A - 29 Understanding the Role of Caregiver Self-Efficacy in Dementia Healthcare: Findings from the Care Ecosystem Program.

Identify changes in healthcare utilization (HCU) and admission risk scores (ARS) by caregiver self-efficacy levels (CGSE) in persons with dementia (PWD). 179 community-dwelling dyads (PWD-CG) with at least 1 emergency or hospital admission 12-months prior to enrollment in the Care Ecosystem (dementia care-management program), provided data at baseline, 6, and 12-months. Analyzed data included caregiver self-reported HCU, dementia ratings (QDRS, NPI), wellbeing (ZBI-12, NPI-Distress, PHQ9), and CGSE scales. HCU confirmation and ARS were extracted from electronic medical records. Repeated measures ANOVA and paired sample t-tests compared ARS and HCU across time points by baseline CGSE. On average, PWD and caregivers were 80 (SD:8) and 64years-old (SD:11); predominantly female (PWD:63%, CG: 77%) and white (62%), with 12+ years of education (PWD: 84%, CG: 98%). Self-efficacy improved over time [F(1.92, 281.74 = 11.56, p < 0.001, ηp2 = 0.13]; post-hoc Bonferroni indicated increases from 19.37 to 20.62 at 6-months (95% CI, 0.59-1.92) and 20.56 at 12-months (95% CI, 0.41-1.98). Reductions in ARS [t(178) = 2.63, p = 0.009, MD = 3.34, d = 0.2] and HCU [t(177) = 5.37, p < 0.001, MD = 0.85, d = 0.4] were observed at program completion. The high-CGSE group demonstrated significant ARS [t(98) = 3.43, p = 0.001, d = 0.4] and HCU reductions [t(98) = 3.65, p < 0.001, d = 0.4]. HCU also decreased for the moderate-CGSE cohort [t(43) = 4.17, p < 0.001, d = 0.6]. Groups with higher CGSE experienced greater reductions in ARS and HCU compared to lower CGSE. Self-reported measures and CGSE-group sample sizes may limit our findings.

Impact of Self Care Management Program on Improving Self Efficacy of Multiple Sclerosis Patients

Impact of Self Care Management Program on Improving Self Efficacy of Multiple Sclerosis Patients

Hospital Readmissions by Variation in Engagement in the Health Care Hotspotting Trial

Variability in intervention participation within care management programs can complicate standard analysis strategies. To evaluate whether care management was associated with reduced hospital readmissions among individuals with higher participation probabilities. A total of 800 hospitalized patients aged 18 years and older were randomized as part of the Health Care Hotspotting randomized clinical trial, which was conducted in Camden, New Jersey, from June 2014 to September 2017. Data were collected through October 2018. In this new analysis performed between April 6, 2022, and April 23, 2023, the distillation method was applied to account for variable intervention participation. A gradient-boosting machine learning model produced predicted probabilities of engaged participation using baseline covariates only. Predicted probabilities were used to trim both intervention and control populations in an equivalent manner, and intervention effects were reevaluated within study population subsets that were increasingly concentrated with patients having higher participation probabilities. Patients had 2 or more hospitalizations in the 6-month preenrollment period and documented evidence of chronic illness and social complexity. Multidisciplinary teams provided services to patients in the intervention arm for a mean 120 days after hospital discharge. Patients in the control group received usual postdischarge care. Hospital readmission rates and counts 30, 90, and 180 days postdischarge. Of 800 eligible patients, 782 had complete discharge information and were included in this analysis (mean [SD] age, 56.6 [12.7] years; 395 [50.5%] female). In the intent-to-treat analysis, the unadjusted 180-day readmission rate for treatment and control groups was 60.1% vs 61.7% (adjusted odds ratio, 0.95; 95% CI, 0.71-1.28; P = .73) and the mean (SD) number of 180-day readmissions was 1.45 (1.89) vs 1.48 (1.94) (adjusted incidence rate ratio, 0.99, 95% CI, 0.88-1.12; P = .86). Among the population with the highest participation probabilities, the mean (SD) 180-day readmission count was 1.22 (1.74) vs 1.57 (1.74) and the incidence rate ratio attained statistical significance (adjusted incidence rate ratio, 0.74; 95% CI, 0.56-0.99; P = .045). Adjusted odds ratios and adjusted incidence rate ratios for 30- and 90-day outcomes reached statistical significance after population distillation. This secondary analysis of a randomized clinical trial found that care management was associated with reduced readmissions among patients with higher participation probabilities, suggesting that program operation could be improved by addressing barriers to participation and refining inclusion criteria to identify patients most likely to benefit. ClinicalTrials.gov Identifier: NCT02090426.

Does Interdisciplinary Care Team Care Management Improve Health Quality and Demonstrate Cost-Effectiveness?

This study evaluated the impact of an interdisciplinary care teams (IDCT) care management program on cost and quality outcomes using a novel algorithm to identify 400 high-risk patients out of 48,235 Medicare Advantage (MA) beneficiaries. Of the 400, 252 were enrolled in the IDCT care management intervention program, while the remaining 148 were not enrolled. A second comparison group consisted of 660 who were referred to the IDCT program but not selected by the algorithm. The program's effectiveness was evaluated 1-year postintervention. Analyses found that health care costs for members enrolled in the IDCT program were reduced by US$1,121.76 and US$1,625.61 per member per month, respectively, relative to those not enrolled and those enrolled by referral. The cost reduction from the program generated a net savings of US$1.9MM, covering the program's cost. Findings suggest IDCTs can cost-effectively manage populations of high-risk patients with better selection and fostering greater interdependence.

Association of body indices and risk of mortality in patients with type 2 diabetes

IntroductionA body shape index (ABSI) is independently associated with mortality in general population, but studies on the predictability of ABSI in the risk of mortality in patients with type 2...

Evaluation of a Telehealth-Based Pharmacist Led Chronic Care Management Program

Background: Clinical pharmacy services improve several patient chronic disease outcomes. This review evaluates a pharmacist-led chronic care management (CCM) program partnered with a health system for patient outcomes and sustainability. Methods: A mixed methods evaluation based on the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework was completed. Patient A1c and blood pressure readings were retrospectively collected from the electronic health record from August 2018-April 2022. Patients that completed >4 CCM visits with a diagnosis of diabetes and/or hypertension were included. Results: 557 patients enrolled, 53 had uncontrolled systolic blood pressure (SBP), SBP >130 mmHg. Average SBP at baseline was 141.0 mmHg and average SBP at 6 months was 130.2 mmHg, (P < .001). 76 patients had uncontrolled diabetes, A1c > 7%. Average A1c at baseline = 9.1% and average A1c at 6 months = 8.3%, (P < .001). 4464 CCM visits with 247 disease-state targeted patients were completed over 44-month with a 100% adoption rate across clinic locations. Implementation facilitators included patient medication cost concerns, disease burden, provider revenue generation, CCM dedicated software, streamlined call process, and remote EMR access. Implementation barriers included provider discomfort “selling the program,” potential patient costs, unclear need from patient, pharmacists not considered providers, pharmacist cost, multi-platform software, reprioritized stakeholder support, and lack of partner site diversification. Program maintenance showed revenue generation was $5925.31-$8879.89 from August 2021-May 2022 and profitability was $3385.61-$1614.23. Conclusion: This study provides lessons learned, strategies for implementation, and ideas for process efficiencies leading to maintenance of a telehealth pharmacist-led CCM service.

Social Determinants of Health Documentation Among Individuals With Rheumatic and Musculoskeletal Conditions in an Integrated Care Management Program.

Social determinants of health (SDoH), such as poverty, are associated with increased burden and severity of rheumatic and musculoskeletal diseases. This study was undertaken to study the prevalence and documentation of SDoH-related needs in electronic health records (EHRs) of individuals with these conditions. We randomly selected individuals with ≥1 International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) code for a rheumatic/musculoskeletal condition enrolled in a multihospital integrated care management program that coordinates care for medically and/or psychosocially complex individuals. We assessed SDoH documentation using terms for financial needs, food insecurity, housing instability, transportation, and medication access according to EHR note review and ICD-10 SDoH billing codes (Z codes). We used multivariable logistic regression to examine associations between demographic factors (age, gender, race, ethnicity, insurance) and ≥1 (versus 0) SDoH need as the odds ratio (OR) with 95% confidence interval (95% CI). Among 558 individuals with rheumatic/musculoskeletal conditions, 249 (45%) had ≥1 SDoH need documented in EHR notes by social workers, care coordinators, nurses, and physicians. A total of 171 individuals (31%) had financial insecurity, 105 (19%) had transportation needs, 94 (17%) had food insecurity; 5% had ≥1 related Z code. In the multivariable model, the odds of having ≥1 SDoH need was 2.45 times higher (95% CI 1.17-5.11) for Black versus White individuals and significantly higher for Medicaid or Medicare beneficiaries versus commercially insured individuals. Nearly half of this sample of complex care management patients with rheumatic/musculoskeletal conditions had SDoH documented within EHR notes; financial insecurity was the most prevalent. Only 5% of patients had representative billing codes suggesting that systematic strategies to extract SDoH from notes are needed.

Care manager, older adult, and caregiver perspectives on co-occurring care management among high-need older adults.

Care management programs are widely used to improve care coordination and management of chronic conditions for high-need older adults. With many care management programs targeting a small number of people, high-need older adults may receive services from more than one care management program (co-occurring care management), the implications of which are unknown. We conducted semi-structured interviews with 37 care managers, 15 older adults, and 13 caregivers, who were recruited through an urban academic medical center and a large rural health system in Maryland. We analyzed interview transcripts using qualitative content analysis with the aim of understanding contributors to, implications of, and strategies to manage co-occurring care management among high-need older adults. Contributors to co-occurring care management included siloed programs due to program-specific financial incentives and inability to easily identify other involved care managers, and the complex needs of the enrolled older adult population, which motivated involvement of more than one program. Implications of co-occurring care management included older adults and caregivers feeling cared for and safe when they had multiple care management programs involved and reporting value in their relationships with care managers. Older adults were identified as having greater access to resources and improved care when care manager roles were aligned in a complementary way; however, misaligned roles posed the potential for confusion about care manager accountability for tasks and resulted in frustration and lack of follow-through. Strategies for managing co-occurring care management included alignment of care manager roles through communication and negotiation and older adults and caregivers identifying and relying on a single care manager with whom they had the strongest relationship. Initiatives that clarify strengthen the relationship between care managers and older adults, increase care manager visibility, and facilitate communication across care managers may help foster collaboration.

Development and feasibility study of the heart failure management program 'SupportHeart'

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Disease management programs for HF are characterized by heterogeneity and different levels of complexity, thus the results regarding of their effectiveness are controversial. The trajectory of HF makes supportive care controversial. Supportive care consists the following four aspects: Communication, education, psychological and spiritual issues and symptom management. Purpose To evaluate the effectiveness of an individualized supportive care management program in terms of the four different components that comprise supportive care in patients with HF. Methods This was a multi-method, randomized control trial (RCT) study [control group (CG)and intervention group (IG)] to assess a new developed supportive care management program for patients with HF. Patients allocated in the IG received written material for HF self-management and an educational session was conducted by a nurse in the bedside of the patient. The intervention was consisted by monthly educational sessions including information about the HF syndrome, pharmacological and non- pharmacological treatment and self-management. The evaluation of the intervention included health-related quality of life (HR-QoL), self-care management, exercise, anxiety and depression and perceived support. Furthermore, acute events (readmissions and deaths) and deterioration of symptoms were measured. Statistical comparisons were performed using the "Kruskal Wallis Test", Chi-Square and the Fisher’s test. Kaplan Meir curves and the log-rank test were utilised to explore the time until the first acute event. Statistical analysis was conducted in the statistical software R v.3.6.1. Results Thirty-five patients with HF participated in the study and the intervention lasted for six months. A better HR-QoL was found for both groups in the sixth time period, but with a difference in the social dimension of the HR-QoL favoring the IG [IG baseline= 4.8 (4.9) / 1st month=3.3 (3.5) / 6th month =2.8 (3.1)] [ CG baseline= 2.3 (1,1) / 1st month=3.4 (2,7) / 6th month =2.7 (2.8) ]. Also, a difference in the sub-scale of family/significant others in the IG was indicated, with an increased trend [IG baseline=50.9 (5.4) / 6th month= 52.7 (3.4)] [CG baseline =50.3 (8.9) / 6th month = 49.9 (4.2)]. No difference between the two groups was found for self-care management. The survival of the CG was lower than that of the IG in all three time points; 30 days: (log-rank test, X2(1) = 5.7, p = 0.02), 90 days: (log-rank test, X2(1) = 12.3, p&amp;lt;0.001) and 180 days: (log-rank test, X2(1) = 6.8, p = 0.009). Discussion/Conclusion: This is the first RCT assessing the effectiveness of supportive care in patients with HF. Supportive care seems to be a promising concept for HF management programs. There was a great effect in acute events as it was found a reduced risk by 87% for a patient receiving supportive care. Also, the study illustrated the effectiveness regarding multiple outcomes, such as HR-QoL and perceived support.Survival AnalysisHealth Related Quality of Life

A Study of Managed Care Health System During Pandemic

The present study reports the comprehensive study on managed care during the pandemic, regarding to the cases of the covid-19 outbreak increased every day, even reaching 2,000 cases per day in Indonesia. The surge in the cost of handling covid-19 patients and delays in payment of covid-19 claims by the Indonesian Ministry of Health have worsened the situation and the handling of the quality of services by health service providers. For this reason, the role of managed care is needed in these conditions. The purpose of this study is to analyze and find out the pattern and course of managed care in Indonesia by comparing it with several countries that have also been infected with covid-19. This research method is a literature review study with an online database search strategy or search engine in the form of related research journals from the year 2020-2023. The results obtained by researchers are the lack of health human resources, medical devices and "pandemic fatigue" which are problems that contribute to the course of managed care in almost every region in Indonesia. The role of society and government policies affect the overall implementation of managed care programs. When the community complies with the policies that apply in the pandemic era and the government provides policies in collaboration with health experts. Managed care program one of prospective plan for Indonesia healthcare industry development in the future.

Understanding what really helps to ensure access to diagnostic services in the Indian Public Health System: a realist synthesis of the Common Review Mission reports (2007-2021)

Background In India, the National Health Mission (NHM) has been supporting the states in building an integrated public healthcare network across the levels of care. This effort has improved access to, and utilization of, diagnostic services at public healthcare facilities. To continually enhance citizens’ ability to seek and avail quality and affordable services, it is imperative to take stock of various components of the diagnostic ecosystem that may be common or unique to states and understand their influence on equipping the health system. The objective of the study was to understand key health system factors augmenting or limiting access to diagnostic services and outcomes. Methods Common Review Mission (CRM) reports between 2007 and 2021 were selected for the study. Data relevant to diagnostic services were retrieved using defined search terms. The data were segregated for each Indian state and categorized under the pre-determined themes: state-specific practices, key findings, and challenges. Analysis of the data was done iteratively to identify the themes emerging from the reports over the years. Each theme was analysed further to deduce context-specific enablers and barriers influencing access to diagnostic service delivery. Results The major themes that emerged include (i) the approach to health systems strengthening, (ii) efficiency of procurement and distribution systems, (iii) infrastructure, (iv) modes of service delivery, (v) implementation of Free Diagnostic Service Initiative, Comprehensive Primary Health Care and Biomedical Equipment Management and Maintenance Program, and (vi) quality of care , and (vii) diagnostic service outcomes. Conclusions In a complex adaptive system, access to diagnostic services depends on the concurrent strengthening of various health system components across the levels of care. The nation has strategized accessible, affordable and acceptable diagnostic services to achieve universal health coverage and care-continuum pathways. States need to leverage the existing mechanisms, assess their implementation, and arrive at feasible and sustainable solutions to strengthen access to diagnostic services.

Organizational Health Literacy and Health Among New York State Medicaid Members.

The definition of health literacy has recently expanded beyond the idea of individual skills to include the system and environment the individual interacts with to receive care, known as organizational health literacy (OHL). However, neither the prevalence of OHL nor the impact of OHL on individuals' perceptions of their health and healthcare have been examined in New York's Medicaid managed care population. This study aimed to estimate the prevalence of organizational health literacy in the New York State (NYS) Medicaid Managed Care (MMC) program. A brief measure to assess organizational health literacy was developed from responses to two questions in the 2018 NYS Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. Generalized Estimating Equation models were developed to analyze the association between organizational health literacy and three aspects of perceptions of health and health care, controlling for demographic differences and clustering effects from health insurance plans. Missing data were handled using multiple imputation. Among 3,598 members included in the study, 20% of the MMC members reported inadequate organizational health literacy. These members were more likely to be older, less educated, from racial and ethnic minority groups, and less fluent with English. They are more likely to have poorer self-reported health (odds ratio [OR] 1.49), lower perceived access to health care (OR 6.97), and lower satisfaction with their health care (OR 6.49) than members who did not report inadequate organizational health literacy. Our results suggest that a proportion of the NYS MMC population faces inadequate organizational health literacy, which can present a barrier to health care access and result in patients having a significantly poorer health care experience. Using an existing data source that is part of existing data collection allows for routine assessment of organizational health literacy, which can help inform health plans about areas for potential improvement. [HLRP: Health Literacy Research and Practice. 2023;7(3):e154-e164.].

Augmenting a Transitional Care Model With Artificial Intelligence Decreased Readmissions.

Evaluate if augmenting a transitions of care delivery model with insights from artificial intelligence (AI) that applied clinical and exogenous social determinants of health data would reduce rehospitalization in older adults. Retrospective case-control study. Adult patients discharged from integrated health system between November 1, 2019, and February 31, 2020, and enrolled in a rehospitalization reduction transitional care management program. An AI algorithm utilizing multiple data sources including clinical, socioeconomic, and behavioral data was developed to predict patients at highest risk for readmitting within 30days and provide care navigators five care recommendations to prevent rehospitalization. Adjusted incidence of rehospitalization was estimated with Poisson regression and compared between transitional care management enrollees that used AI insights and matched enrollees for whom AI insights were not used. Analyses included 6371 hospital encounters between November 2019 and February 2020 across 12 hospitals. Of the encounters 29.3% were identified by AI as being medium-high risk for re-hospitalizing within 30days, for which AI provided transitional care recommendations to the transitional care management team. The navigation team completed 40.2% of AI recommendations for these high-risk older adults. These patients had overall 21.0% less adjusted incidence of 30-day rehospitalization compared with matched control encounters, or 69 fewer rehospitalizations per 1000 encounters (95% CI 0.65‒0.95). Coordinating a patient's care continuum is critical for safe and effective transition of care. This study found that augmenting an existing transition of care navigation program with patient insights from AI reduced rehospitalization more than without AI insights. Augmenting transitional care with insights from AI could be a cost-effective intervention to improve transitional care outcomes and reduce unnecessary rehospitalization. Future studies should examine cost-effectiveness of augmenting transitional care models of care with AI when hospitals and post-acute providers partner with AI companies.

1826-PUB: Efficacy of Digital Diabetes Care Program in India—Retrospective Analysis

Background: Lack of knowledge in self-management and limited access to specialized healthcare services leads to uncontrolled diabetes. Continuous digital care delivered through a mobile healthcare app aid in metabolic control. Aims: To analyze the efficacy of BeatO’s digital diabetes care management program among people with diabetes Methods: A retrospective analysis of 721 participants enrolled in BeatO’s mobile app-based diabetes care program for 3 months, the period of enrollment was between 28th February to 31st August 2022. Participants received remote access to health professionals for diabetes education, nutritional guidance and doctor consultation through the BeatO app. Throughout the care program, they were connected with a dedicated health coach. The medication prescribed by the doctor was delivered to the participant’s home. Regular blood glucose monitoring was done using BeatO’s smartphone-connected glucometer that works in accordance with the BeatO app. The parameters like FBG, PPBG, HbA1c, lipid profile and weight was recorded at baseline and after 3 months. Results: Of the 721 participants, 96.5 % had Type 2 diabetes. The mean age of the participants was 47.5 years, and the majority (80.8%) were males. T2DM was present in 696, T1DM (11), LADA (9), Prediabetes (3) and GDM (2). Out of these, 704 participants completed the program. A significant improvement in blood glucose control was observed, as reflected by a mean decrease in FBG by 38 mg/dL (p &amp;lt;0.0001), PPBG by 37 mg/dL (p &amp;lt;0.0001) and HbA1c reduced by 2.16% (p &amp;lt; 0.0001) at the end of 3 months. There was a significant weight loss of about 1.8 kg (p = 0.01) and a reduction in total cholesterol by 15 mg/dl through this remote personalized care. Conclusions: BeatO's digital diabetes care management program among people with diabetes showed good efficacy in terms of glycemic control and weight loss. Hence, the implementation of digital technology in diabetes care can help in increasing access and awareness of diabetes care and achieving glycemic targets. Disclosure N.Agrawal: Advisory Panel; Biocon, Eris Lifesciences Ltd., Lupin Pharmaceuticals, Inc., Sanofi, USV Private Limited, Other Relationship; BeatO, Health Arx Technologies Pvt LTD. A.Panjabi: Advisory Panel; Torrent Pharmaceuticals Ltd, USV Private Limited, Consultant; BeatO, Health Arx Technologies. P.K.Dixit: Advisory Panel; USV Private Limited, Intas Pharmaceuticals Ltd., Consultant; Beato, Health Arx Technologies. B.D: Consultant; BEAT-O, HEALTH ARX TECHNOLOGIES.

Feasibility and Preliminary Behavioral and Clinical Efficacy of a Diabetes Education Chatbot Pilot Among Adults With Type 2 Diabetes.

Diabetes self-management education and support (DSMES) improves diabetes outcomes yet remains consistently underutilized. Chatbot technology offers the potential to increase access to and engagement in DSMES. Evidence supporting the case for chatbot uptake and efficacy in people with diabetes (PWD) is needed. A diabetes education and support chatbot was deployed in a regional health care system. Adults with type 2 diabetes with an A1C of 8.0% to 8.9% and/or having recently completed a 12-week diabetes care management program were enrolled in a pilot program. Weekly chats included three elements: knowledge assessment, limited self-reporting of blood glucose data and medication taking behaviors, and education content (short videos and printable materials). A clinician facing dashboard identified need for escalation via flags based on participant responses. Data were collected to assess satisfaction, engagement, and preliminary glycemic outcomes. Over 16 months, 150 PWD (majority above 50 years of age, female, and African American) were enrolled. The unenrollment rate was 5%. Most escalation flags (N = 128) were for hypoglycemia (41%), hyperglycemia (32%), and medication issues (11%). Overall satisfaction was high for chat content, length, and frequency, and 87% reported increased self-care confidence. Enrollees completing more than one chat had a mean drop in A1C of -1.04%, whereas those completing one chat or less had a mean increase in A1C of +0.09% (P = .008). This diabetes education chatbot pilot demonstrated PWD acceptability, satisfaction, and engagement plus preliminary evidence of self-care confidence and A1C improvement. Further efforts are needed to validate these promising early findings.

Effect of an oncology care management program on unplanned hospital admissions in a commercially insured population.

1547 Background: Despite advances in cancer outcomes, costs of cancer care continue to rise. Acute care utilization contributes significantly to these costs. The Cancer Support Program’s (CSP) care management services focus on providing education on symptom management, palliative care and advance care planning, addressing psychosocial needs and closing gaps in care in members with cancer who are at high risk for unplanned hospital admissions (UHA). Methods: Beginning 1/1/22, commercially insured members with an active cancer diagnosis were clinically stratified as high or low risk for UHA. All high-risk members were invited to participate in the CSP program. Individuals who agreed to participate received individualized telephonic care management support. Medical claims from 1/1/22 through 9/30/22 were evaluated, and rates of UHA were compared between participants and non-participants within the identified high-risk population for an average period of 4 months after identification (the period equivalent to the average enrollment period of participants). Results: The study population included 3,113 members who stratified as high risk. Of those, 36% were enrolled in the program. Reasons for non-enrollment include inability to reach (72%), member refused (27%) and bad contact information (1%). There were no statistically significant differences between the two groups’ demographic composition except for age (the enrolled group had slightly more in the 51-64 age group [63% vs. 59%; p &lt; 0.001] and slightly fewer in the &gt; 65 age group (9% vs. 15%; p &lt; 0.001]). There were 358 UHA in the participating group and 737 UHA in the non-participating group. When normalized, there were 1,179 UHA per thousand members per year (PTMPY), 99% CI [1,171 UHA, 1,184 UHA] (bootstrap) in the participating group and 1,526 UHA PTMPY, 99% CI [1,523 UHA, 1,535 UHA] (bootstrap) in the non-participating group. Conclusions: Early results show lower UHA rates for members who participated in the care management program, suggesting the program is effective in reducing acute care utilization within the high-risk population. Limitations of this study include potential enrollment bias, changes in risk status from clinical or social factors, and the potential for human error or inconsistency in the risk stratification process. Further study is underway to validate these results.

Dosage and outcomes in a complex care intervention.

The purpose of our study was to assess the relationship between intervention dosage and hospital utilization outcomes among patients with complex health and social needs enrolled in a care management program. We highlight the importance of measuring patient engagement and intervention dosage in program evaluation. We performed a secondary analysis of data collected between 2014 and 2018 as part of a randomized controlled trial of the Camden Coalition's signature care management intervention. Our analytical sample consisted of 393 patients. We calculated a time-invariant cumulative dosage rank based on the number of hours spent by care teams working with or on behalf of patients and then divided patients into low- and high-dosage groups. We applied propensity score reweighting to compare hospital utilization outcomes between patients in these 2 groups. Compared with patients in the low-dosage group, those in the high-dosage group had a lower readmission rate at 30 (21.6% vs 36.6%; P < .001) and 90 (41.7% vs 55.2%; P = .003) days post enrollment. The difference between the 2 groups at 180 days post enrollment was not statistically significant (57.5% vs 64.9%; P = .150). Our study elucidates a gap in how care management programs for patients with complex health and social needs are evaluated. Although the study shows an association between intervention dosage and care management outcomes, patients' medical complexity and social circumstances are among the factors that can attenuate the dose-response relationship over time.

Employment and leave while parenting children with medical complexity.

Children with medical complexity (CMC) require frequent medical care and are at risk of recurrent hospitalizations. The Family Medical Leave Act (FMLA) allows some workers to take unpaid leave from work to care for family members. This study examines caregiving obligations of parents of CMC, the availability and appropriateness of FMLA in facilitating their roles as caregivers and employees, and how these challenges affect employment and financial security. Parents of CMC were recruited from a primary care pediatric care management program for semistructured interviews. An integrated approach, using both deductive and inductive codes, was used to conduct a thematic analysis. All 16 respondents were female, with half working full-time, five working part-time, and three not employed at the time of participation. On average, their CMC experienced 1.8 hospitalizations in the prior 12 months. Parents described that caring for CMC required ongoing and unpredictable time commitments that conflicted with job duties and schedules. This conflict led to frequent employment changes that negatively impacted parents' eligibility for FMLA, their financial health, and their own well-being. Parents often described not having access to FMLA due to exhausting the allotted time, part-time status, insufficient tenure at their job, or the inability to take unpaid leave. Parents depended on informal workplace policies and relationships with supervisors to maintain employment, as well as personal and formal supports to care for CMC and their families' financial stability. Parents want and need to work in order to support their families and pay for the added expenses related to care for their CMC. Remaining active in the workforce requires that they have flexible schedules that accommodate their unpredictable and ongoing caregiving responsibilities. The eligibility criteria and unpaid nature of FMLA, however, make employment and financial stability elusive for caregivers of CMC. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Tacking upwind: reducing spending among high-risk commercially insured patients.

The study examined a commercial accountable care organization (ACO) population and then assessed the impact of an integrated care management program on medical spending and clinical event rates. Retrospective cohort study of high-risk individuals (n = 487) in a population of 365,413 individuals aged 18 to 64 years within the Mass General Brigham health system who were part of commercial ACO contracts with 3 large insurers between 2015 and 2019. Using medical spending claims and other enrollment data, the study assessed the demographic and clinical characteristics, medical spending, and clinical event rates of patients in the ACO and its high-risk care management program. The study then examined the impact of the program using a staggered difference-in-difference design with individual-level fixed effects and compared outcomes of those who had entered the program with those of similar patients who had not entered. The commercially insured ACO population was healthy on average but included several hundred high-risk patients (n = 487). After adjustment, patients within the ACO's integrated care management program for high-risk patients had lower monthly medical spending (by $1361 per person per month) as well as lower emergency department visit and hospitalization rates compared with similar patients who had yet to start the program. Accounting for early ACO departure decreased the magnitude of the program effects as expected. Commercial ACO populations may be healthy on average but still include some high-risk patients. Identifying which patients might benefit from more intensive care management could be critical for reaping the potential savings.