Impact of stratification on the effectiveness of a comprehensive patient‐centered strategy for multimorbid patients

Abstract

Objective The objective of this work was to assess the effectiveness of a population‐level patient‐centered intervention for multimorbid patients based on risk stratification for case finding in 2014 compared with the baseline scenario in 2012. Data Source Clinical and administrative databases. Study Design This was an observational cohort study with an intervention group and a historical control group. A propensity score by a genetic matching approach was used to minimize bias. Generalized linear models were used to analyze relationships among variables. Data Collection We included all eligible patients at the beginning of the year and followed them until death or until the follow‐up period concluded (end of the year). The control group (2012) totaled 3558 patients, and 4225 patients were in the intervention group (2014). Principal Finding A patient‐centered strategy based on risk stratification for case finding and the implementation of an integrated program based on new professional roles and an extensive infrastructure of information and communication technologies avoided 9 percent (OR: 0.91, CI: 0.86‐0.96) of hospitalizations. However, this effect was not found in nonprioritized groups whose probability of hospitalization increased (OR: 1.19, CI = 1.09‐1.30). Conclusions In a before‐and‐after analysis using propensity score matching, a comprehensive, patient‐centered, integrated care intervention was associated with a lower risk of hospital admission among prioritized patients, but not among patients who were not prioritized to receive the intervention.

Assessment of the Adjusted Clinical Groups system in Dutch primary care using electronic health records: a retrospective cross-sectional study

“…A study by Soto-Gordoa used risk stratification to select cases for a patient-centered intervention for multimorbid patients with the goal to lower hospitalization. The approach avoided 9 % of hospitalization when cases were selected with the ACG tool [ 4 ].…”

“…With risk stratification, differences in individual health risks can be screened for, and used to assign interventions to the population and individuals that will benefit the most. With rising pressure on medical services provided by general practitioners (GPs) in most European countries [ 1 ], primary care can benefit from proven advantages of risk stratification approaches, such as improved care management [ 2 ], resource allocation [ 3 ] and identification of sub-populations for tailored care interventions [ 4 ].…”

Identifying subgroups of high-need, high-cost, chronically ill patients in primary care: A latent class analysis

“…With the growing recognition of the effectiveness of segmentation for patient-centered interventions, [54] the segmentation conducted in the present study can guide clinical practice toward more integrated and person-centered care. By gathering insight into demographic characteristics other than age and gender (e.g., household position) as well as the socioeconomic context of patients (e.g., main source of income), clinical practice in primary care can be attuned to a more holistic view of patients.…”

Assessment of The ACG System in Dutch Primary Care Using GP’s Electronic Health Records: A Retrospective Cross-Sectional Study

“…With risk strati cation, differences in individual health risks can be screened for, and used to assign interventions to the population and individuals that will bene t the most. With rising pressure on medical services provided by general practitioners (GPs) in most European countries (1), primary care can bene t from proven advantages of risk strati cation approaches, such as improved care management (2), resource allocation (3) and identi cation of subpopulations for tailored care interventions (4).…”