A.A. Uijen

Multimorbidity in primary care: Prevalence and trend over the last 20 years

Objective: To determine the prevalence of multimorbidity in primary care, by age, sex, and socio-economic class, and to analyse the trend in multimorbidity over the last 20 years. Methods: We performed an observational study using data from the Continuous Morbidity Registration (CMR) Nijmegen. This registration includes approximately 13 500 enlisted patients. To study the distribution of multimorbidity by age, sex, and socio-economic class, we analysed all patients enlisted in the CMR in 2005. To analyse the trend of multimorbidity over time, we studied the prevalence of multimorbidity from 1985 to 2005. Results: We found that increasing age, female sex, and low socio-economic class are associated with an increasing number of patients with multimorbidity. The prevalence of chronic diseases doubled between 1985 and 2005. The proportion of patients with four or more chronic diseases increased in this period by approximately 300%. Conclusion: The increasing amount of multimorbidity in primary care as well as the increasing number of chronic diseases per patient leads to more complex medical care. The general practitioner needs guidelines focusing on multimorbidity to support this care. The registration of chronic diseases by the general practitioner will become more complex and time-consuming.

Measurement properties of questionnaires measuring continuity of care: a systematic review.

Background Continuity of care is widely acknowledged as a core value in family medicine. In this systematic review, we aimed to identify the instruments measuring continuity of care and to assess the quality of their measurement properties. Methods We did a systematic review using the PubMed, Embase and PsycINFO databases, with an extensive search strategy including ‘continuity of care’, ‘coordination of care’, ‘integration of care’, ‘patient centered care’, ‘case management’ and its linguistic variations. We searched from 1995 to October 2011 and included articles describing the development and/or evaluation of the measurement properties of instruments measuring one or more dimensions of continuity of care (1) care from the same provider who knows and follows the patient (personal continuity), (2) communication and cooperation between care providers in one care setting (team continuity), and (3) communication and cooperation between care providers in different care settings (cross-boundary continuity). We assessed the methodological quality of the measurement properties of each instrument using the COSMIN checklist. Results We included 24 articles describing the development and/or evaluation of 21 instruments. Ten instruments measured all three dimensions of continuity of care. Instruments were developed for different groups of patients or providers. For most instruments, three or four of the six measurement properties were assessed (mostly internal consistency, content validity, structural validity and construct validity). Six instruments scored positive on the quality of at least three of six measurement properties. Conclusions Most included instruments have problems with either the number or quality of its assessed measurement properties or the ability to measure all three dimensions of continuity of care. Based on the results of this review, we recommend the use of one of the four most promising instruments, depending on the target population Diabetes Continuity of Care Questionnaire, Alberta Continuity of Services Scale-Mental Health, Heart Continuity of Care Questionnaire, and Nijmegen Continuity Questionnaire.

Heart failure patients’ experiences with continuity of care and its relation to medication adherence: a cross-sectional study

BackgroundA growing number of health care providers are nowadays involved in heart failure care. This could lead to discontinuity and fragmentation of care, thus reducing trust and hence poorer medication adherence. This study aims to explore heart failure patients’ experiences with continuity of care, and its relation to medication adherence.MethodsWe collected data from 327 primary care patients with chronic heart failure. Experienced continuity of care was measured using a patient questionnaire and by reviewing patients’ medical records. Continuity of care was defined as a multidimensional concept including personal continuity (seeing the same doctor every time), team continuity (collaboration between care providers in general practice) and cross-boundary continuity (collaboration between general practice and hospital). Medication adherence was measured using a validated patient questionnaire. The relation between continuity of care and medication adherence was analysed by using chi-square tests.ResultsIn total, 53% of patients stated not seeing any care provider in general practice in the last year concerning their heart failure. Of the patients who did contact a care provider in general practice, 46% contacted two or more care providers. Respectively 38% and 51% of patients experienced the highest levels of team and cross-boundary continuity. In total, 14% experienced low levels of team continuity and 11% experienced low levels of cross-boundary continuity. Higher scores on personal continuity were significantly related to better medication adherence (p < 0.01). No clear relation was found between team- or cross-boundary continuity and medication adherence.ConclusionsA small majority of patients that contacted a care provider in general practice for their heart failure, contacted only one care provider. Most heart failure patients experienced high levels of collaboration between care providers in general practice and between GP and cardiologist. However, in a considerable number of patients, continuity of care could still be improved. Efforts to improve personal continuity may lead to better medication adherence.

Measuring continuity of care: psychometric properties of the Nijmegen Continuity Questionnaire.

BACKGROUND Recently, the Nijmegen Continuity Questionnaire (NCQ) was developed. It aims to measure continuity of care from the patient perspective across primary and secondary care settings. Initial pilot testing proved promising. AIM To further examine the validity, discriminative ability, and reliability of the NCQ. DESIGN A prospective psychometric instrument validation study in primary and secondary care in the Netherlands. METHOD The NCQ was administered to patients with a chronic disease recruited from general practice (n = 145) and hospital outpatient departments (n = 123) (response rate 76%). A principal component analysis was performed to confirm three subscales that had been found previously. Construct validity was tested by correlating the NCQ score to scores of other scales measuring quality of care, continuity, trust, and satisfaction. Discriminative ability was tested by investigating differences in continuity subscores of different subgroups. Test-retest reliability was analysed in 172 patients. RESULTS Principal factor analysis confirmed the previously found three continuity subscales - personal continuity, care provider knows me; personal continuity, care provider shows commitment; and team/cross-boundary continuity. Construct validity was demonstrated through expected correlations with other variables and discriminative ability through expected differences in continuity subscores of different subgroups. Test-retest reliability was high (the intraclass correlation coefficient varied between 0.71 and 0.82). CONCLUSION This study provides evidence for the validity, discriminative ability, and reliability of the NCQ. The NCQ can be of value to identify problems in continuity of care.

Experienced continuity of care in patients at risk for depression in primary care

Abstract Background: Existing studies about continuity of care focus on patients with a severe mental illness. Objectives: Explore the level of experienced continuity of care of patients at risk for depression in primary care, and compare these to those of patients with heart failure. Methods: Explorative study comparing patients at risk for depression with chronic heart failure patients. Continuity of care was measured using a patient questionnaire and defined as (1) number of care providers contacted (personal continuity); (2) collaboration between care providers in general practice (team continuity) (six items, score 1–5); and (3) collaboration between GPs and care providers outside general practice (cross-boundary continuity) (four items, score 1–5). Results: Most patients at risk for depression contacted several care providers throughout the care spectrum in the past year. They experienced high team continuity and low cross-boundary continuity. In their general practice, they contacted more different care providers for their illness than heart failure patients did (P < 0.01). Patients at risk for depression experienced a slightly better collaboration between these care providers in their practice: a mean score of 4.3 per item compared to 4.0 for heart failure patients (P = 0.03). The perceived cross-boundary continuity, however, was reversed: a mean score of 3.5 per item for patients at risk for depression, compared to 4.0 for heart failure patients (P = 0.01). Conclusion: The explorative comparison between patients at risk for depression and heart failure patients shows small differences in experienced continuity of care. This should be analysed further in a more robust study.

Which questionnaire to use when measuring continuity of care

TheNijmegenContinuityQuestionnaire (NCQ)measures patients’ experienced personal, team, and cross-boundary continuity of care regardless of morbidity and across multiple care settings [1]. We agree with Aller et al. [2] that existing measurement instruments should be taken into account when developing a new instrument. That is why we performed a systematic literature review to assess all existing instrumentsmeasuring continuity of care or related concepts, such as coordination or integration of care. This resulted in 82 identified instruments measuring items about continuity of care. We used these items to develop the NCQ [1]. We regret that we did not identify the Continuity of Care Across Care Levels Questionnaire (CCAENA) [3]. This questionnaire was published after we performed our literature review, and we probably did not notice this questionnaire afterward because it is published in Spanish. The CCAENA, similar to the NCQ, also measures patients’ experienced continuity of care as a multidimensional concept, regardless of morbidity and across multiple care settings. The CCAENA seems to be a useful instrument. As Aller et al. [2] also describe, there are several differences between the two instruments, of which we would like to add the following comments:

Patient perspectives on continuity of care: adaption and preliminary psychometric assessment of a Norwegian version of the Nijmegen Continuity Questionnaire (NCQ-N)

BackgroundContinuity of care is regarded as a core quality element in healthcare. Continuity can be related to one or more specific caregivers but also applies to collaboration within a team or across boundaries of healthcare. Measuring continuity is important to identify problems and evaluate quality improvement of interventions.This study aimed to assess the feasibility and psychometric properties of a Norwegian version of the Nijmegen Continuity Questionnaire (NCQ).MethodsThe NCQ was developed in The Netherlands. It measures patients’ experienced continuity of care across multiple care settings and as a multidimensional concept regardless of morbidity. The NCQ comprises 28 items categorised into three subscales; two personal continuity scales, “care giver knows me” and “shows commitment”, asked regarding the patient’s general practitioner (GP) and the most important specialist; and one “team/cross boundary continuity” scale, asked regarding primary care, specialised care and cooperation between GP and specialist, with a total of seven factors. The NCQ was translated and adapted to Norwegian (NCQ-N) and distributed among patients referred to somatic rehabilitation (N = 984, response rate 34.5%). Confirmatory factor analyses (CFA), Cronbach’s alpha, intra-class correlation (ICC) and Bland–Altman plots were used to assess psychometric properties.ResultsAll patients (N = 375) who had responded to all parts of the NCQ-N were included in CFA. The CFA fit indices (CFI 0.941, RMSEA 0.064 (95% CI 0.059–0.070), SRMR 0.041) support a seven-factor structure in the NCQ-N based on the three subscales of the original NCQ. Cronbach’s alpha showed internal consistency (0.84–0.97), and was highest for the team/cross-boundary subscales. The NCQ-N showed overall high reliability with ICC 0.84–91 for personal continuity factors and 0.67–0.91 for team factors, with the lowest score for team continuity within primary care.ConclusionsPsychometric assessment of the NCQ-N supports that this instrument, based on the three subscales of the original Dutch NCQ, captures the concept of “continuity of care” among adult patients with a variety of longstanding medical conditions who use healthcare on a regular basis. However, its usefulness among varied patient groups, including younger people, patients with acute disorders and individuals with mental health problems, should be further evaluated.

The Diagnostic Value of the Patient’s Reason for Encounter for Diagnosing Cancer in Primary Care

Purpose: Family physicians (FPs) have to recognize alarm symptoms and estimate the probability of cancer to manage these symptoms correctly. Mostly, patients start the consultation with a spontaneous statement on why they visit the doctor. This is also called the reason for encounter (RFE). It precedes the interaction and interpretation by FPs and patients. The aim of this study is to investigate the predictive value of alarm symptoms as the RFE for diagnosing cancer in primary care. Design and setting: Retrospective cohort study in a Dutch practice-based research network (Family Medicine Network). Method: We analyzed all patients >45 years of age listed in the practice-based research network, FaMe-net, in the period 1995 to 2014 (118.219 patient years). We focused on a selection of alarm symptoms as defined by the Dutch Cancer Society and Cancer Research UK. We calculated the positive predictive value (PPV) of alarm symptoms, spontaneously mentioned in the beginning of the consultation by the patient (RFE), for diagnosing cancer. Results: The highest PPVs were found for patients spontaneously mentioning a breast lump (PPV 14.8%), postmenopausal bleeding (PPV 3.9%), hemoptysis (PPV 2.7%), rectal bleeding (PPV 2.6%), hematuria (PPV 2.2%) and change in bowel movements (PPV 1.8%). Conclusion: Patients think about going to their physician and think about their first uttered statements during the consultation. In the case of cancer, the diagnostic workup during the consultation on alarm symptoms will add to the predictive value of these reasons for encounter. However, it is important to realize that the statement made by the patient entering the consultation room has a significant predictive value in itself.

FaMe-Net: twee oude registratienetwerken in een nieuw jasje

SamenvattingHet belangrijke historische eerstelijns registratienetwerk CMR (Continue Morbiditeits Registratie) heeft een aantal ingrijpende veranderingen doorgemaakt waarbij na het samengaan met het Transitieproject onder andere de naam is veranderd naar FaMe-Net (Family Medicine Network).

Alarmsymptomen voor kanker als reden van komst

SamenvattingInleiding Huisartsen moeten alarmsymptomen voor kanker niet alleen kunnen herkennen, maar ook kunnen inschatten hoe groot de kans is dat het echt om kanker gaat. De spontaan genoemde klacht of wens van een patiënt bij de huisarts noemt men de ‘reden van komst’ oftewel de reason for encounter (RFE). Sommige RFE’s zijn een alarmsymptoom voor kanker. Wij onderzochten de voorspellende waarde van deze RFE’s.Methode Wij voerden een retrospectief cohortonderzoek uit in het eerstelijns registratienetwerk Family Medicine Network. We selecteerden patiënten ouder dan 45 jaar die tussen 1995 en 2014 (118.219 patiëntjaren) bij de huisarts kwamen met als RFE een van de alarmsymptomen die gedefinieerd zijn door KWF Kankerbestrijding en UK Cancer Research. We berekenden de positief voorspellende waarde (PVW) van deze RFE’s voor de diagnose ‘kanker’.Resultaten Een knobbel in de borst had de hoogste PVW (14,8%), gevolgd door postmenopauzale bloeding (3,9%), hemoptoë (2,7%), rectaal bloedverlies (2,6%), hematurie (2,2%) en verandering in de stoelgang (1,8%).Conclusie Alarmsymptomen voor kanker die de patiënt bij binnenkomst spontaan noemt, hebben op zichzelf een voorspellende waarde, al wordt het beleid natuurlijk vooral bepaald door anamnese en lichamelijk onderzoek. De positief voorspellende waarde van zulke alarmsymptomen, die ook gecommuniceerd worden in publiekscampagnes, is een factor om rekening mee te houden.