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. 2025 Apr 24;9(1):BJGPO.2024.0144.
doi: 10.3399/BJGPO.2024.0144. Print 2025 Apr.

Continuity of care and mortality in patients with type 2 diabetes: a cohort study

Affiliations

Continuity of care and mortality in patients with type 2 diabetes: a cohort study

Eero H Mellanen et al. BJGP Open. .

Abstract

Background: How GP continuity of care (GP-CoC) affects mortality in patients with type 2 diabetes (T2D) is unclear.

Aim: To examine the effect of having no continuity of care (CoC) and GP-CoC on mortality in primary health care (PHC) patients with T2D.

Design & setting: A cohort study in patients aged ≥60 years with T2D, which was conducted within the public PHC of the city of Vantaa, Finland.

Method: The inclusion period was between 2002 and 2011 and follow-up period between 2011 and 2018. Six groups were formed (no appointments, one appointment and Modified, Modified Continuity Index [MMCI] quartiles). Mortality was measured with standardised mortality ratio (SMR) and adjusted hazard ratio (aHR). GP-CoC was measured with MMCI. Comorbidity status was determined with Charlson Comorbidity Index (CCI).

Results: In total, 11 020 patients were included. Mean follow-up time was 7.3 years. SMRs for the six groups (no appointments, one appointment, MMCI quartiles) were 2.46 (95% confidence interval [CI] = 2.24 to 2.71), 3.55 (95% CI = 3.05 to 4.14), 1.15 (95% CI = 1.06 to 1.25), 0.97 (95% CI = 0.89 to 1.06), 0.92 (95% CI = 0.84 to 1.01) and 1.21 (95% CI = 1.11 to 1.31), respectively. With continuous MMCI, mortality formed a U-curve. The inflection point was at a MMCI value of 0.65 with corresponding SMR of 0.86. Age and CCI aHR for death between men and women was 1.45 (95% CI = 1.35 to 1.58).

Conclusion: Patients with no CoC had the highest mortality. In patients having care over time, the effect of GP-CoC on mortality was minor and mortality increased with high GP-CoC.

Keywords: continuity of patient care; diabetes mellitus; family medicine; primary healthcare.

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Conflict of interest statement

The authors declare that no competing interests exist.

Figures

Figure 1.
Figure 1.. Age, sex, and Charlson Comorbidity Index adjusted cumulative mortality in the study patients aged ≥60 years who were diagnosed with type 2 diabetes within the primary health care of the city of Vantaa, Finland, divided into six groups, according to either the number of appointments (no appointments or one appointment during the follow-up period) or the quarters of the Modified, Modified Continuity Index. Grey area represents 95% confidence intervals
Figure 2.
Figure 2.. Standardised mortality ratio in the study patients aged ≥60 years who were diagnosed with type 2 diabetes within the primary health care of the city of Vantaa, Finland. Divided into no appointments or one appointment during the follow-up period or the continuous of the Modified, Modified Continuity Index (MMCI). Non-linear trends of SMR were displayed using restricted cubic spline curves estimated by a multivariable-adjusted Poisson regression model. We used 4-knots of continuous MMCI placed at the 5th, 35th, 65th, and 95th percentiles of the cumulative MMCI distribution. The restricted cubic spline models were adjusted for age, sex, and Charlson Comorbidity Index. Whiskers and grey area represent 95% confidence intervals

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