ObjectivesPrevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how ‘disease entity’ is defined—as a single chronic condition or chapters/domains in the International Classification of Primary Care (V.2; ICPC-2), International Classification of Disease (10th revision; ICD-10) or the Cumulative Illness Rating Scale (CIRS), the number of disease entities required for multimorbidity, and the number of chronic conditions studied.DesignNational prospective cross-sectional study.SettingAustralian general practice.Participants8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners.Main outcome measuresPrevalence estimates of multimorbidity using different definitions.ResultsData classified to ICPC-2 chapters, ICD-10 chapters or CIRS domains produce similar multimorbidity prevalence estimates. When multimorbidity was defined as two or more (2+) disease entities: counting individual chronic conditions and groups of chronic conditions produced similar estimates; the 12 most prevalent chronic conditions identified about 80% of those identified using all chronic conditions. When multimorbidity was defined as 3+ disease entities: counting individual chronic conditions produced significantly higher estimates than counting groups of chronic conditions; the 12 most prevalent chronic conditions identified only two-thirds of patients identified using all chronic conditions.ConclusionsMultimorbidity defined as 2+ disease entities can be measured using different definitions of disease entity with as few as 12 prevalent chronic conditions, but lacks specificity to be useful, especially in older people. Multimorbidity, defined as 3+, requires more measurement conformity and inclusion of all chronic conditions, but provides greater specificity than the 2+ definition. The proposed concept of “complex multimorbidity”, the co-occurrence of three or more chronic conditions affecting three or more different body systems within one person without defining an index chronic condition, may be useful in identifying high-need individuals.

Chronic pain impairs patient quality of life, and is a public health burden. This study provides a national overview of the prevalence, causes, severity, management and impact of chronic pain in Australian general practice patients, and the parity between GP and patient satisfaction with pain management.

Objective: To measure prevalence of multimorbidity and complex multimorbidity in the Australian population from a nationally representative prospective study and to identify the most prevalent patterns of chronic conditions and body systems affected. Methods:A sub-study of the nationally representative BEACH program, using a random sample of 8,707 patients at encounters with 290 general practitioners. All diagnosed chronic conditions were recorded for each patient. Multimorbidity was defined as co-occurrence of 2+ chronic conditions, while complex multimorbidity was defined as 3+ body systems each affected by at least one chronic condition. Results:We estimated: 47.4% of patients at GP encounters and one-third (32.6%) of the population had multimorbidity; and 27.4% of patients at GP encounters and 17.0% of the Australian population had complex multimorbidity. The most prevalent combination pattern of three conditions was hypertension+hyperlipidaemia+ osteoarthritis (5.5% of patient at encounters and 3.3% of the population). Most prevalent combination of three body systems affected was circulatory+musculoskeletal+endocrine / nutritional/metabolic systems (11.1% of patients at encounters and 7.0% of the population). Conclusions and implications:A significant proportion of Australians have not only multimorbidity, but complex multimorbidity. To meet the challenge posed by complex multimorbidity, the single disease focus of our healthcare system needs to be re-evaluated.

ObjectivesTo estimate the prevalence of common chronic conditions and multimorbidity among patients at GP encounters and among people in the Australian population. To assess the extent to which use of each individual patient’s GP attendance over the previous year, instead of the average for their age-sex group, affects the precision of national population prevalence estimates of diagnosed chronic conditions.Design, setting and participantsA sub-study (between November 2012 and March 2016) of the Bettering the Evaluation and Care of Health program, a continuous national study of GP activity. Each of 1,449 GPs provided data for about 30 consecutive patients (total 43,501) indicating for each, number of GP attendances in previous year and all diagnosed chronic conditions, using their knowledge of the patient, patient self-report, and patient's health record.ResultsHypertension (26.5%) was the most prevalent diagnosed chronic condition among patients surveyed, followed by osteoarthritis (22.7%), hyperlipidaemia (16.6%), depression (16.3%), anxiety (11.9%), gastroesophageal reflux disease (GORD) (11.3%), chronic back pain (9.7%) and Type 2 diabetes (9.6%).After adjustment, we estimated population prevalence of hypertension as 12.4%, 9.5% osteoarthritis, 8.2% hyperlipidaemia, 8.0% depression, 5.8% anxiety and 5.2% asthma. Estimates were significantly lower than those derived using the previous method.About half (51.6%) the patients at GP encounters had two or more diagnosed chronic conditions and over one third (37.4%) had three or more. Population estimates were: 25.7% had two or more diagnosed chronic conditions and 15.8% had three or more.ConclusionsOf the three approaches we have tested to date, this study provides the most accurate method for estimation of population prevalence of chronic conditions using the GP as an expert interviewer, by adjusting for each patient’s reported attendance.

Objectives: To estimate prevalence of selected diagnosed chronic diseases among patients attending general practice, in the general practice patient population, and in the Australian population, and to compare population estimates with those of the National Health Survey (NHS). Design, setting and participants: In late 2005, 305 general practitioners each provided data for about 30 consecutive patients (total, 9156) as part of the BEACH (Bettering the Evaluation And Care of Health) program, a continuous national study of general practice activity. GPs used their knowledge of the patient, patient self‐report, and medical records as sources. Main outcome measures: Crude prevalence of each listed condition currently under management among surveyed patients, and adjusted prevalence for the general practice patient population, and the national population. Results: 39.6% of respondents had none of the listed conditions diagnosed; 30.0% had a cardiovascular problem (uncomplicated hypertension, 17.6%; ischaemic heart disease, 9.5%); 24.8% had a psychological problem (depression, 14.2%; anxiety, 10.7%); 22.8% had arthritis, mostly osteoarthritis (20.0%); 10.7% had asthma; and 8.3% had diabetes, mostly type 2 (7.2%). Adjustment to the population attending general practice resulted in lower estimates for cardiovascular disease, arthritis and diabetes but had little effect on prevalence of asthma and psychological problems. After adjusting for non‐attenders, about one in five people in the population had a cardiovascular problem, a similar proportion had a psychological problem, 14.8% had arthritis, and about 10% had asthma, hyperlipidaemia and gastro‐oesophageal reflux disease. Estimates were similar to NHS results for any arthritis, asthma, and malignant neoplasms; higher for any cardiovascular problem; far higher for specific cardiovascular diseases, cerebrovascular disease and hyperlipidaemia; and almost twice the NHS estimate for psychological problems (particularly depression and anxiety). Estimates for type 1 diabetes aligned with NHS results, but were far higher for “all diabetes” and type 2 diabetes. Conclusions: This study offers an alternative, perhaps more accurate, approach to measurement of disease prevalence than the NHS approach, which relies on respondent self‐report alone. It provides valid prevalence estimates with the help of GPs at a fraction of the cost of the NHS. This study could be repeated annually to augment other data sources and better define existing health needs in the population.