Sobolik, Gerald J.

Introduction The Centers for Medicare & Medicaid skilled nursing facility (SNF) 3-day waiver permits patients attributed to an Accountable Care Organization (ACO) to be admitted to an SNF or transitional care unit from an emergency department, outpatient setting, inpatient stay (<3 days), or observational status without Medicare’s requisite 3-day inpatient stay. Methods Our institution’s ACO implemented the waiver program in 2023. We report our experience with implementing the waiver and describe benefits and barriers, as well as interventions developed, outcomes achieved, and opportunities presented for patients and health care facilities. Results Through a streamlined process, patients can more readily access essential care, and health care facilities benefit from enhanced efficiency. Furthermore, the ACO can more effectively manage health care utilization and cost. Although the program offers benefits to patients, their families, and health care facilities, implementing and maintaining the program has challenges, with barriers including underdeveloped workflows, gaps in staff education and communication, difficulties in patient identification, and challenges with specific facility requirements. Conclusions The SNF 3-day rule waiver has been valuable in enhancing patient care and optimizing health care delivery within our ACO. Ongoing efforts to refine processes and address challenges will further improve the program’s effectiveness and sustainability.

Objectives: To assess how social risk factors and socioeconomic status (SES) affect health care costs at a large, integrated health system of 45 clinics in Iowa, Minnesota, and Wisconsin. Methods: We retrospectively reviewed administrative patient cost data from January 1 through December 31, 2022. Social risk factors (lack of financial resources, food insecurity, intimate partner violence, unmet transportation needs, and housing instability) were determined with patient questionnaires. Cost z -scores were compared across all risk-factor quartiles. We used a housing-based measure to objectively determine SES. Results: We analyzed data from 410 624 patients empaneled with 689 family medicine clinicians. Self-reported risk factor data were incomplete for 219 321 patients. Costs were higher for those with higher social risk (mean cost z -score: high risk = 0.38, low risk = 0.11; P < .001). In addition, higher costs were associated with increasing age, greater medical complexity (higher Adjusted Clinical Group scores), White race, and lack of financial resources. Although we observed geographic variations in cost, urban and rural locations did not have significant cost differences. Costs were similar across all quartiles of SES, and the absolute difference in cost z -scores between the highest and lowest SES quartiles was only 0.04. The multivariate analysis, which adjusted for age, medical complexity, race, sex, and objective SES, showed that these specific associations were substantially decreased and no longer significantly associated with mean cost z -scores. Conclusions: Patient-reported social risk factors were significantly associated with increased cost of care in a large, multispecialty health system in the midwestern US. These associations were decreased in the multivariate analysis. Results should be interpreted cautiously for readers outside the midwestern US, given potential responder bias and the racial homogeneity (92% White) of the study cohort.

AbstractObjectiveTo evaluate health care costs as a function of assigned primary care clinician type and care team characteristics.MethodsAdministrative data were collected for 68 family medicine clinicians (40 physicians and 28 nurse practitioners [NPs]/physician assistant [PAs]), on 11 care teams (variable MD, NP and PA on teams), caring for 77,141 patients. We performed a generalized linear mixed multivariable regression model of standardized per member per month (PMPM) median cost as the outcome, with four practice sites included as random effects.ResultsIn bivariate analysis, cost was higher in physicians than NP/PAs, in more complex patients, and associated with emergency department (ED) visit rate. On multivariate analysis, patient complexity, ED visit rate and higher patient experience ratings were independently associated with greater PMPM cost. More time in practice was associated with lower PMPM cost. In the adjusted multivariate model, physicians had 8.3% lower median PMPM costs than NP/PAs (p = 0.046).ConclusionsThe primary drivers of greater PMPM cost were patient complexity, ED visits and patient satisfaction.

The objective was to determine if a greater proportion of physician full-time equivalent (FTE%) relative to nurse practitioners/physician assistants (NPs/PAs) on care teams was associated with improved individual clinician diabetes quality outcomes. The authors conducted a retrospective cross-sectional study of 420 family medicine clinicians in 110 care teams in a Midwest health system, using administrative data from January 1, 2017 to December 31, 2017. Poisson regression was used to examine the relationship between physician FTE% and the number of patients meeting 5 criteria included in a composite metric for diabetes management (D5). Covariates included panel size, clinician type, sex, years in practice, region, patient satisfaction, care team size, rural location, and panel complexity. Of the 420 clinicians, 167 (40%) were NP/PA staff and 253 (60%) were physicians. D5 criteria were achieved in 37.9% of NP/PA panels compared with 44.5% of physician panels ( P < .001). In adjusted analysis, rate of patients achieving D5 was unrelated to physician FTE% on the care team ( P = .78). Physicians had a 1.082 (95% confidence interval 1.007–1.164) times greater rate of patients with diabetes achieving D5 than NPs/PAs. Clinicians at rural locations had a .904 (.852-.959) times lower rate of achieving D5 than those at urban locations. Physicians had a greater rate of patients achieving D5 compared with NPs/PAs, but physician FTE% on the care team was unrelated to D5 outcomes. This suggests that clinician team composition matters less than team roles and the dynamics of collaborative care between members.