Graeme Miller

Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice

Objectives Prevalence 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. Design National prospective cross-sectional study. Setting Australian general practice. Participants 8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners. Main outcome measures Prevalence estimates of multimorbidity using different definitions. Results Data 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. Conclusions Multimorbidity 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.

A computational linguistics motivated mapping of ICPC-2 PLUS to SNOMED CT.

BackgroundA great challenge in sharing data across information systems in general practice is the lack of interoperability between different terminologies or coding schema used in the information systems. Mapping of medical vocabularies to a standardised terminology is needed to solve data interoperability problems.MethodsWe present a system to automatically map an interface terminology ICPC-2 PLUS to SNOMED CT. Three steps of mapping are proposed in this system. The UMLS metathesaurus mapping utilises explicit relationships between ICPC-2 PLUS and SNOMED CT terms in the UMLS library to perform the first stage of the mapping. Computational linguistic mapping uses natural language processing techniques and lexical similarities for the second stage of mapping between terminologies. Finally, the post-coordination mapping allows one ICPC-2 PLUS term to be mapped into an aggregation of two or more SNOMED CT terms.ResultsA total 5,971 of all 7,410 ICPC-2 terms (80.58%) were mapped to SNOMED CT using the three stages but with different levels of accuracy. UMLS mapping achieved the mapping of 53.0% ICPC2 PLUS terms to SNOMED CT with the precision rate of 96.46% and overall recall rate of 44.89%. Lexical mapping increased the result to 60.31% and post-coordination mapping gave an increase of 20.27% in mapped terms. A manual review of a part of the mapping shows that the precision of lexical mappings is around 90%. The accuracy of post-coordination has not been evaluated yet. Unmapped terms and mismatched terms are due to the differences in the structures between ICPC-2 PLUS and SNOMED CT. Terms contained in ICPC-2 PLUS but not in SNOMED CT caused a large proportion of the failures in the mappings.ConclusionMapping terminologies to a standard vocabulary is a way to facilitate consistent medical data exchange and achieve system interoperability and data standardisation. Broad scale mapping cannot be achieved by any single method and methods based on computational linguistics can be very useful for the task. Automating as much as is possible of this process turns the searching and mapping task into a validation task, which can effectively reduce the cost and increase the efficiency and accuracy of this task over manual methods.

A new drug classification for computer systems: the ATC extension code

During the testing of the Read Clinical Codes in general practice medical records in Australia, it became apparent that the pharmaceutical section of the codes was not applicable in a country with different brand names, pack sizes and forms. For pharmacoepidemiological studies, structured classification of both morbidity and pharmaceuticals is required for meaningful analysis. The search for a suitable pharmaceutical classification proved fruitless. While the Australian Government has recently adopted the Anatomical Therapeutic Chemical (ATC) Classification as the national standard, this only classifies drugs to the generic level. None of the extended coding systems used in hospital pharmacies, by community pharmacists, or by Government are hierarchically structured. The extension code we have developed, is an analytical algorithm comprising independent fields for: dosage; strength; manufacturer and brand; and pack size. The codes within each field are also structured in a hierarchical manner. The result is an extension code of 21 digits, each digit or group of digits having a meaning. The structure of this classification will allow analysis of any aspect of the drug prescribed. This system is designed for computerised entry of text and transparent coding of the data--not for manual coding on paper nor manual code entry to the computer.

Prevalence of chronic conditions in Australia.

Objectives To estimate prevalence of chronic conditions among patients seeing a general practitioner (GP), patients attending general practice at least once in a year, and the Australian population. Design, setting and participants A sub-study of the BEACH (Bettering the Evaluation and Care of Health) program, a continuous national study of general practice activity conducted between July 2008 and May 2009. Each of 290 GPs provided data for about 30 consecutive patients (total 8,707) indicating diagnosed chronic conditions, using their knowledge of the patient, patient self-report, and patients health record. Main outcome measures Estimates of prevalence of chronic conditions among patients surveyed, adjusted prevalence in patients who attended general practice at least once that year, and national population prevalence. Results Two-thirds (66.3%) of patients surveyed had at least one chronic condition: most prevalent being hypertension (26.6%), hyperlipidaemia (18.5%), osteoarthritis (17.8%), depression (13.7%), gastro-oesophageal reflux disease (11.6%), asthma (9.5%) and Type 2 diabetes (8.3%). For patients who attended general practice at least once, we estimated 58.8% had at least one chronic condition. After further adjustment we estimated 50.8% of the Australian population had at least one chronic condition: hypertension (17.4%), hyperlipidaemia (12.7%), osteoarthritis (11.1%), depression (10.5%) and asthma (8.0%) being most prevalent. Conclusions This study used GPs to gather information from their knowledge, the patient, and health records, to provide prevalence estimates that overcome weaknesses of studies using patient self-report or health record audit alone. Our results facilitate examination of primary care resource use in management of chronic conditions and measurement of prevalence of multimorbidity in Australia.

Relationship between general practitioner certification and characteristics of care.

Background:The introduction of mandatory or quasimandatory certification processes for general/family doctors has become common in many countries, including Australia. Whether certification effects the care provided is rarely investigated. Objectives:The objective of this study was to determine whether certification of general/family physicians is associated with clinical performance. Research Design:We conducted a secondary comparative analysis of data from an Australian national cross-sectional survey (April 2000–March 2002). Subjects:Subjects consisted of a random sample of 1982 general practitioners (GPs) Methods:Each participant provided demographic details and information about 100 consecutive patient encounters (total 197,500). We compared characteristics of certified and uncertified general practitioners (GPs), their patients, encounters, problems, management actions, and tested 34 performance indicators. We investigated whether differences identified in descriptive analyses were explained by other factors. Results:Of 1975 GPs who indicated certification status, 659 (33.4%) were vocationally certified. Certificants were more likely to be female, younger, Australian graduates, working fewer sessions, in larger practices, in accredited practices, and using computers for clinical purposes. Their patients were younger, more often female, and less likely to hold a healthcare concession card. Their consultations were longer; they prescribed fewer medications and more clinical treatments and procedures, ordered more pathology tests, and referred more to other health professionals. After adjustment for GP/practice, patient and morbidity differences, certificants had longer consultations, did more therapeutic procedures, prescribed less overall, prescribed fewer nonsteroidal antiinflammatory drugs in the elderly, and fewer antibiotics for upper respiratory infections. Conclusion:Certification of general practitioners has a significant association with consultation behavior and patient management.

ICPC PLUS for community health? A feasibility study.

Background: The development of information systems in community health is being led by the Community Health Information Management Enterprise, a multi state consortium of State Health Departments. To ensure reliable and valid data collection, client problems (issues) presented to community health providers and the activities they undertook will require coding and classification. The suitability of existing classification systems for issues and activities in the community health setting therefore warranted investigation. Aims: To assess the extent to which the extended version of the International Classification of Primary Care (ICPC PLUS©) is a feasible tool with which to code issues and activities in community health settings. Method: 62 providers representing 22 service groups recorded, in their own words, details about issues and activities at all client contacts for a period of two weeks. These were secondarily coded with ICPC PLUS© and subjective judgment made about the “goodness” of fit between the recorded term and the term available in ICPC PLUS©. Results: Of the 2146 issues recorded, 90.5% could be coded with ICPC PLUS©. Codes with a “good fit” were available for 71.2%. ICPC PLUS© had suitable codes for 67.5% of the 2470 recorded activities, but only half of these were a “good fit”. Some ICPC PLUS© terms required greater specificity and some of the terms recorded needed to be further defined before a code could be allocated. Conclusion: It is feasible to use ICPC PLUS© to classify issues with only minor additions and alterations. Activities could also be classified with ICPC PLUS© but far more development would be required.

The prevalence of complex multimorbidity in Australia

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.

The Bettering the Evaluation and Care of Health (BEACH) program: where to from here?

he Bettering the Evaluation and Care of Health (BEACH) program, which began in 1998, is a continuous, national, cross-sectional survey of the clinical activity of general practitioners.1 The survey collects information from rolling random samples of GPs with the aim of gaining an understanding of the characteristics of the GPs themselves, the content of GP–patient encounters, and the services and treatments provided. General practice has changed dramatically since BEACH began. In 2012 the profession was older (41% of GPs aged 55 years and over, versus 25% in 1998), more feminised (41% women, versus 30% in 1998), with fewer Australian graduates (66%, versus 77% in 1998) and more Fellows of the Royal Australian College of General Practitioners (57%, versus 27% in 1998).2 Only 12% of GPs now practise solo (compared with 18% in 1998), with the movement to larger practices encouraged by government financial incentives, shared infrastructure costs and increased flexibility of working hours — on average, GPs now work 3 fewer face-to-face clinical hours per week than they did in 2001–2002. However, government-claimable consultations have consistently averaged 15 minutes,2 perhaps reflecting reliance on a fee-for-service system that pays more to the GP per minute for multiple shorter consultations than for longer consultations. Yet consultations have become more complex. Middleaged and older people are making up an increasing proportion of patient encounters (from 47% in 1998 to 57% in 2012), resulting in the management of more (particularly chronic) problems, more clinical treatments, procedures, tests and investigations, and referrals to specialists and allied health professionals. GPs face more demands on their time with an ageing population, improved primary prevention, early diagnosis of chronic disease and therefore more need for longer-term management. BEACH also measures changes in the management of specific conditions in response to new evidence, pharmacological and other products, screening and diagnostic tests, and government policies and incentives. This relies on the GPs’ direct linkage of management to the patient Helena C Britt BA, PhD, Associate Professor and Director

The prevalence of diagnosed chronic conditions and multimorbidity in Australia: A method for estimating population prevalence from general practice patient encounter data

Objectives To 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 participants A 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 patients health record. Results Hypertension (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. Conclusions Of 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.

Drugs causing adverse events in patients aged 45 or older: a randomised survey of Australian general practice patients

Objective To determine prevalence of adverse drug events (ADEs) in patients aged 45 years or older presenting to Australian general practitioners (GPs) and identify drug groups related to ADEs, their severity and manifestation. Design Substudy of the Bettering the Evaluation and Care of Health continuous survey of Australian GP clinical activity in which randomly selected GPs collected survey data from patients. Data are reported with 95% CIs. Setting General practice in Australia. Main outcome measures Prevalence in the preceding 6 months, type, implicated drugs, severity (including hospitalisation) and manifestation of ADEs. Participants From three survey samples, January–October 2007, and two samples, January–March 2010, responses were received from 482 GPs about 7561 patients aged 45 years or older. Results Of a final sample of 7518 patients (after duplicate patients removed), 871 (11.6%) reported ADEs in the previous 6 months. The type of ADE was recognised side effect (75.8%, 95% CI 72.0 to 79.7), drug sensitivity (9.9%, 95% CI 7.2 to 12.7) and drug allergy (7.4%, 95% CI 4.7 to 10.1). Drug interaction (1.0%, 95% CI 0.1 to 1.8), overdose (0.8%, 95% CI 0.0 to 1.5) and contraindications (0.2%, 95% CI 0.0 to 0.6) were very infrequent. A severity rating was provided for 846 patients. Almost half (45.9%, 95% CI 42.0 to 49.7) were rated as ‘mild’ events, 42.2% (95% CI 38.8 to 45.6) ‘moderate’, 11.8% (95% CI 9.5 to 14.1) severe and 5.4% (95% CI 3.8 to 7.0) had been hospitalised as a result of the most recent ADE. Thirteen commonly prescribed drug groups accounted for 58% of all ADEs, opioids being the group most often implicated. Conclusion ADEs in patients aged 45 or older are frequent and are associated with significant morbidity. Most of ADEs result from commonly prescribed drugs at therapeutic dosage. The list of causative agents bears little relationship to published lists of ‘inappropriate medications’.