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Comparing measures of multimorbidity to predict outcomes in primary care: a cross sectional study.

ABSTRACT: BACKGROUND: An increasing proportion of people are living with multiple health conditions, or 'multimorbidity'. Measures of multimorbidity are useful in studies of interventions in primary care to take account of confounding due to differences in case-mix. OBJECTIVES: Assess the predictive validity of commonly used measures of multimorbidity in relation to a health outcome (mortality) and a measure of health service utilization (consultation rate). METHODS: We included 95372 patients registered on 1 April 2005 at 174 English general practices included in the General Practice Research Database. Using regression models we compared the explanatory power of six measures of multimorbidity: count of chronic diseases from the Quality and Outcomes Framework (QOF); Charlson index; count of prescribed drugs; three measures from the John Hopkins ACG software [Expanded Diagnosis Clusters count (EDCs), Adjusted Clinical Groups (ACGs), Resource Utilisation Bands (RUBs)]. RESULTS: A model containing demographics and GP practice alone explained 22% of the uncertainty in consultation rates. The number of prescribed drugs, ACG category, EDC count, RUB category, QOF disease count, or Charlson index increased this to 42%, 37%, 36%, 35%, 30%, and 26%, respectively. Measures of multimorbidity made little difference to the fit of a model predicting 3-year mortality. Nonetheless, Charlson index score was the best performing measure, followed by the number of prescribed drugs. CONCLUSION: The number of prescribed drugs is the most powerful measure for predicting future consultations and the second most powerful measure for predicting mortality. It may have potential as a simple proxy measure of multimorbidity in primary care.

SUBMITTER: Brilleman SL

PROVIDER: S-EPMC3604888 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Comparing measures of multimorbidity to predict outcomes in primary care: a cross sectional study.

Brilleman Samuel L SL Salisbury Chris C

Family practice 20121008 2

<h4>Background</h4>An increasing proportion of people are living with multiple health conditions, or 'multimorbidity'. Measures of multimorbidity are useful in studies of interventions in primary care to take account of confounding due to differences in case-mix.<h4>Objectives</h4>Assess the predictive validity of commonly used measures of multimorbidity in relation to a health outcome (mortality) and a measure of health service utilization (consultation rate).<h4>Methods</h4>We included 95372 p ...[more]

PMID: 23045354

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Project description:BackgroundTo understand how to improve care for patients with chronic diseases and multimorbidity we wanted to describe the prevalence of different chronic diseases and the pattern of multimorbidity and to analyse the associations between occurrence of diseases and primary care utilization, adherence to guideline-based pharmacotherapy, and continuity of care.MethodsRetrospective cross-sectional study of routine care data of the general population in region Jönköping in Sweden (345 916 inhabitants using primary care services) covering 4.3 years.ParticipantsPatients fulfilling the inclusion criteria of having ≥ 1 of 10 common chronic diseases and ≥ 3 visits to primary care between 2011 and 2015.Primary outcome measuresIn order to determine diseases and multimorbidity, primary care utilisation, adherence to guideline-based pharmacotherapy, frequencies and percentages, interval and ratio scaled variables were described using means, standard deviations, and various percentiles in the population. Two continuity indices were used (MMCI, COC) to describe continuity.ResultsOf the general population, 25 829 patients fulfilled the inclusion criteria (7.5% of the population). Number of diseases increased with increasing age, and multimorbidity was much more common than single diseases (mean 2.0 per patient). There was a slight positive correlation (0.29) between number of diseases and visits, but visits did not increase proportionally to the number of diseases. Patients with physical diseases combined with anxiety and/or depression made more visits than others. The number of diseases per patient was negatively associated with the adherence to pharmacotherapy guidelines. There was no association between continuity and healthcare utilisation or adherence to pharmacotherapy guidelines.ConclusionsMultimorbid patients are common in primary care and for many chronic diseases it is more common to have other simultaneous diseases than having only one disease. This can make adherence to pharmacotherapy guidelines a questionable measure for aged multimorbid patients. Existing continuity indices also revealed limitations. Holistic and patient-centred measures should be used for quality assessment of care for multimorbid patients in primary care.

Dataset Information

Comparing measures of multimorbidity to predict outcomes in primary care: a cross sectional study.

Publications

Comparing measures of multimorbidity to predict outcomes in primary care: a cross sectional study.

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