Relationship between continuity of care and clinical outcomes in patients with dyslipidemia in Korea: a real world claims database study

Continuity of primary care and avoidable hospitalization in a young population with asthma: a population-based cohort study

Existing evidence regarding the impact of continuity of care (COC) in asthma patients is limited, and its quality is low to moderate. This study aimed to investigate associations between relational COC within primary care and asthma-related hospitalizations in children using a robust methodology. This study is a population-based cohort study that utilized a national claims database in South Korea. The study comprised 136,296 individuals under 20 years old who were newly diagnosed with asthma between 2015 and 2016. These were classified into high, medium, and low continuity groups based on the continuity of care index (COCI). The primary outcome measure was the incidence of asthma-related hospitalizations. During a two-year follow-up period, 10,922 patients (8.01%) were hospitalized: 2520 (5.59%) in the high-continuity group, 3188 (6.98%) in the medium-continuity group, and 3867 (8.48%) in the low-continuity group. After adjusting for confounding covariates, patients in the low- and medium-continuity groups exhibited significantly higher risks of hospital admission (adjusted hazard ratio (aHR) = 1.30 [95% confidence interval = 1.24-1.37] and aHR = 1.14 [1.08-1.20], than those in the high-continuity group. Sensitivity and subgroup analyses findings were consistent. In a young population with asthma increased continuity of primary care was associated with less hospitalization.

Relationship between continuity of primary care and hospitalisation for patients with COPD: population-based cohort study from South Korea

OBJECTIVES

The existing evidence for the impacts of continuity of care (COC) in patients with chronic obstructive pulmonary disease (COPD) is low to moderate. This study aimed to investigate the associations between relational COC within primary care and COPD-related hospitalisations using a robust methodology.

DESIGN

Population-based cohort study.

SETTING

National Health Insurance Service database, South Korea.

PARTICIPANTS

92 977 adults (≥40 years) with COPD newly diagnosed between 2015 and 2016 were included. The propensity score (PS) matching approach was used. PSs were calculated from a multivariable logistic regression that included eight baseline characteristics.

EXPOSURE

COC within primary care.

MAIN OUTCOME MEASURES

The primary outcome was the incidence of COPD-related hospitalisations. Cox proportional hazard models were used to estimate HRs and 95% CIs.

RESULTS

Out of 92 977 patients, 66 677 of whom were cared for continuously by primary doctors (the continuity group), while 26 300 were not (the non-continuity group). During a 4-year follow-up period, 2094 patients (2.25%) were hospitalised; 874 (1.31%) from the continuity group and 1220 (4.64%) from the non-continuity group. After adjusting for confounding covariates, patients in the non-continuity group exhibited a significantly higher risk of hospital admission (adjusted HR (aHR) 2.43 (95% CI 2.22 to 2.66)). This risk was marginally reduced to 2.21 (95% CI 1.99 to 2.46) after PS matching. The risk of emergency department (ED) visits, systemic corticosteroid use and costs were higher for patients in the non-continuity group (aHR 2.32 (95% CI 2.04 to 2.63), adjusted OR 1.25 (95% CI 1.19 to 1.31) and expβ=1.89 (95% CI 1.82 to 1.97), respectively). These findings remained consistent across the PS-matched cohort, as well as in the sensitivity and subgroup analyses.

CONCLUSIONS

In patients with COPD aged over 40, increased continuity of primary care was found to be associated with less hospitalisation, fewer ED visits and lower healthcare expenditure.

Continuity of care between dyslipidemia patients and multiple providers: A cohort study

OBJECTIVE

This study aimed to investigate the impacts of continuity of care (COC) between patients and multiple providers, i.e., doctors and community pharmacists, on clinical and economic outcomes.

METHODS

This is a retrospective cohort study and analyzed Korean national claims data for ambulatory care setting between 2007 and 2018. Patients with dyslipidemia newly diagnosed in 2008 were identified. COC between providers and patients was computed using the continuity of care index (COCI). Based on COCIs, the study patients were allocated to four groups: HM/HP, HM/LP, LM/HP, and LM/LP. Each symbol represents H for high, L for low, M for doctor, and P for pharmacist. The primary study outcome was the incidence of atherosclerotic cardiovascular disease (ASCVD).

RESULTS

126,710 patients were included. Percentages of patients in the four study groups were as follows: HM/HP 35%, HM/LP 19%, LM/HP 12%, and LM/LP 34%. During the seven-year outcome period, 8,337 patients (6.6%) developed an ASCVD, and percentages in the study groups were as follows; HM/HP 6.2%, HM/LP 6.3%, LM/HP 6.8%, and LM/LP 7.1%. After adjusting for confounding covariates, only the LM/LP group had a significantly higher risk of ASCVD than the reference group, HM/HP (aHR = 1.16 [95% confidence interval = 1.10~1.22]). The risk of inappropriate medication adherence gradually increased 1.03-fold in the HM/LP group, 1.67-fold in the LM/HP, and 2.26-fold in the LM/LP group versus the HM/HP group after adjusting for covariates. Disease-related costs were lower in the HM/HP and LM/HP groups.

CONCLUSIONS

The study shows that patients with high relational care continuity with doctors and pharmacists achieved better clinical results and utilized health care less, resulting in reduced expenses. Further exploration for the group that exhibits an ongoing relationship solely with pharmacists is warranted.

Lowering Barriers to Health Risk Assessments in Promoting Personalized Health Management

This study investigates the feasibility of accurately predicting adverse health events without relying on costly data acquisition methods, such as laboratory tests, in the era of shifting healthcare paradigms towards community-based health promotion and personalized preventive healthcare through individual health risk assessments (HRAs). We assessed the incremental predictive value of four categories of predictor variables-demographic, lifestyle and family history, personal health device, and laboratory data-organized by data acquisition costs in the prediction of the risks of mortality and five chronic diseases. Machine learning methodologies were employed to develop risk prediction models, assess their predictive performance, and determine feature importance. Using data from the National Sample Cohort of the Korean National Health Insurance Service (NHIS), which includes eligibility, medical check-up, healthcare utilization, and mortality data from 2002 to 2019, our study involved 425,148 NHIS members who underwent medical check-ups between 2009 and 2012. Models using demographic, lifestyle, family history, and personal health device data, with or without laboratory data, showed comparable performance. A feature importance analysis in models excluding laboratory data highlighted modifiable lifestyle factors, which are a superior set of variables for developing health guidelines. Our findings support the practicality of precise HRAs using demographic, lifestyle, family history, and personal health device data. This approach addresses HRA barriers, particularly for healthy individuals, by eliminating the need for costly and inconvenient laboratory data collection, advancing accessible preventive health management strategies.