Continuity of care and mortality in patients with type 2 diabetes.

BACKGROUND: How continuity of general practitioner care (GP-CoC) affects mortality in patients with type 2 diabetes (T2D) is unclear. AIM: The aim of this study was 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: Cohort study in patients aged 60 years or older with T2D within the public PHC of the city of Vantaa, Finland. METHOD: Inclusion period was between 2002-2011 and follow-up period between 2011-2018. Six groups were formed (no appointments, one appointment and Modified, Modified Continuity Index [MMCI] quartiles). Mortality was measured with standardized 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%CI: 2.24-2.71), 3.55 (3.05-4.14), 1.15 (1.06-1.25), 0.97 (0.89-1.06), 0.92 (0.84-1.01) and 1.21 (1.11-1.31), 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 adjusted HR for death between men and women was 1.45 (1.35-1.58). CONCLUSIONS: 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 turned to rise with high GP-CoC.

Symptomatic diagnoses in primary care: an observational cohort study.

BACKGROUND: Among primary health care patients, it is sometimes impossible to assign a definitive diagnosis for the patient's reported or observed symptoms. Therefore, symptomatic diagnoses are often used. AIM: The aim of the present study was to examine the proportion of symptomatic diagnoses among primary health care patients. We also explored which symptomatic diagnoses were most frequently recorded as well as their age and gender distribution. DESIGN & SETTING: This is a register-based study in the public primary health care of the city of Vantaa, Finland. METHOD: Diagnoses were entered according to the 10th revision of the International Classification of Diseases (ICD-10). The data consisted of every diagnosis entered into the electronic health record between January first 2016 and December 31st 2018. Both absolute numbers and relative proportions of various symptomatic diagnosis recordings (chapter 'R') were reported. RESULTS: Of all the recorded diagnoses (N=503,001), the proportion of R-diagnoses was 13.5% (N=67,905). Diagnoses of symptoms and signs involving the digestive system and abdomen (R10-19) (4.1% of all; n=18,550), the circulatory and respiratory systems (R00-09) (3.9%; n=17,426), general symptoms and signs (R50-69) (3.4%; n=15,165), and the skin and subcutaneous tissue (R20-23) (2.2%; n=9,812) were the most prevalent. Age was also a major factor determining how the symptomatic diagnoses were distributed between women and men. Overall, the symptomatic diagnoses were more common among women than men (14.1% and 12.4%, respectively). The major symptomatic diagnosis categories, including symptoms and signs involving the digestive system and abdomen, the skin and the subcutaneous tissue, and general symptoms and signs, were more predominant among women, while symptoms and signs involving the circulatory and respiratory systems were more common among men. CONCLUSION: A symptomatic diagnosis code was recorded in about one eighth of the GP appointments, although there were significant sex differences in the prevalence within and between diagnosis groups.

Who visits primary health care general practitioners and why? A register-based study in a Finnish city.

This is a register-based study that examines the distribution of diagnoses made by general practitioners (GPs) in the public primary health care of the city of Vantaa, Finland. Data were gathered from the electronic health record (EHR) system and consisted of every record entered into the EHR system between 1 January 2016 and 31 December 2018. Both absolute numbers and relative proportions of the 10th edition of International Classification of Diseases (ICD-10) diagnosis recordings were reported and calculated. Among GP visits, the 88 most common diagnoses covered 75% of all diagnoses. The most common diagnoses were related to the musculoskeletal (3.8%, ICD code M54) and respiratory systems (6.0%, ICD-10 code J06). Primary health care GP services were mostly used by children (age <5 years) and older adults (>65 years). Health examinations - mostly children's and maternity clinics appointments/visits - covered 20% of the GP office visits. Women between the ages 15-79 years had relatively more GP visits compared to men. The 88 most commonly recorded diagnoses covered the majority of the GP visits. Health examinations for the healthy were an important part of GPs' work. In an urban Finnish city, GP services were predominantly used by children and older adults.

Comparison of two GP service provider models in older adults: a register-based follow-up study.

BACKGROUND: In Finland, there have been various strategies attempting to provide access to GPs. The 'restricted-List General Practitioner model' (rLGP) was launched in primary health care (PHC) in the city of Vantaa after the 'named General Practitioner model' (nGP) failed to provide sufficient access to GPs. This was done to improve access to GP appointments for those most needing care. AIM: To evaluate the impact of the transition from nGP to rLGP on access to non-urgent scheduled appointments among patients aged ≥75 years. DESIGN & SETTING: A register-based follow-up study in public PHC in Vantaa, Finland. METHOD: The study focused on patients aged ≥75 years who used PHC from 2004-2008. It looked at the number of non-urgent and urgent scheduled appointments, patient contacts, home visits, PHC emergency department appointments, and cancelled appointments, which were recorded 7 years before and after the transition from nGP to rLGP in 2011 and adjusted to patient-years. Non-urgent appointments were booked to the patient's own nGP or rLGP in public PHC, whereas urgent appointments could be to any GP. RESULTS: The number of non-urgent scheduled appointments to GPs was halved during the time of nGP, before launching the rLGP. Simultaneously, the number of urgent scheduled appointments more than tripled. The number of both started to plateau a year before the rLGP was launched. The number of both non-urgent and urgent scheduled appointments remained mainly at that level after rLGP was implemented. CONCLUSION: The rLGP model was unsuccessful in improving access to non-urgent scheduled appointments to GPs.