PubMed Health⌕ Search

Biomedical subjects

Simon de Lusignan

Publications and source records attributed to Simon de Lusignan.

At least 19 recordsLinked to original sources
PubMed2006

e-Prescribing, efficiency, quality: lessons from the computerization of UK family practice.

Nearly all general practice physicians (GPs) in the United Kingdom (UK) have electronic health record (EHR) systems in their practices compared with perhaps 15% of primary care physicians in the United States (U.S.). Based on interviews of 13 general GPs and review of current literature, the authors argue that the historical experience of widespread electronic health record uptake in the UK provides insight into features that might motivate broad adoption in the United States. These features include electronic prescribing, improved quality and consistency of care, practice efficiencies that have both timesaving and revenue generating effects, and potential shielding from malpractice claims.

Diffusion of Innovation↗
PubMed2006

Management of cardiovascular risk factors in people with diabetes in primary care: cross-sectional study.

OBJECTIVES: Cardiovascular disease is the major cause of morbidity and mortality in people with diabetes. The management of cardiovascular risk factors in people with diabetes in primary care was compared with National Institute of Clinical Excellence guidelines. DESIGN: A cross-sectional study in 26 general practices, with a combined list size of 256,188 patients, participating in the Kent, Surrey and Sussex Primary Care Research Network. Primary outcomes were process of care measures. METHODS: Analysis of general practice computer data on the management of 5980 patients with diabetes, of whom 86% were aged 45 years and over. RESULTS: The prevalence of diabetes was 2.0% in women and 2.6% in men, much lower than the estimated expected prevalence of 4.8% for women and 3.3% in men. Blood pressure was well recorded (96% in both sexes), cholesterol levels less well (79% of women, 84% of men). Hypertension (78% of women, 72% of men) was common. Twenty-one percent of women and 16% of men had a blood pressure above 160/100 mmHg, suggesting under use of antihypertensive therapy. Cholesterol levels were >or=5 mmol/l in 46% of women and 38% of men. Lipid-lowering drugs were prescribed in 38% of women and men. Aspirin was prescribed in 38% of women and 40% of men. CONCLUSIONS: There is an under-diagnosis of diabetes and an under-treatment of blood pressure and blood cholesterol, more marked in women than in men. There is scope for improved management within general practice, including addressing sex inequalities.

Adolescent↗
PubMed2006

The roles of policy and professionalism in the protection of processed clinical data: a literature review.

BACKGROUND: Routinely collected clinical data is increasingly used for health service management, audit, and research. Even apparently anonymised data are subject to data protection. The relevant principles were set out in a treaty of the Council of Europe and subsequent policy has been based on these. However, little has been written about implementing policy and the role of health informaticians in this process. OBJECTIVE: To define the elements of an effective implementation policy; the role of the health informatician in protecting processed clinical data. METHODS: We performed a literature review of bibliographic databases, a manual search of the major medical informatics associations' websites, relevant working groups and an affiliated journal. Fifty-four papers relevant to implementation were identified. RESULTS: The effective implementation of policy requires consideration of technical, organisational, personnel and professional issues. However, there is no clearly defined formula for successful implementation of data protection policy. CONCLUSIONS: Patients and professionals need a system they can trust, and processes that can be easily incorporated into everyday practice. The lack of a core generalisable theory or strong professional code in health informatics limits the ability of the health informaticians to implement policy.

Confidentiality↗
PubMed2006

A study of cardiovascular risk in overweight and obese people in England.

OBJECTIVES: To report current levels of obesity and associated cardiac risk using routinely collected primary care computer data. METHODS: 67 practices took part in an educational intervention to improve computer data quality and care in cardiovascular disease. Data were extracted from 435,102 general practice computer records. 64.3% (229,108/362,861) of people age 15 y and older had a body mass index (BMI) recording or a valid height and weight record that enabled BMI to be derived. Data about cardiovascular disease and risk factors were also extracted. The prevalence of disease and the control of risk factors in the overweight and obese population were compared with those of normal body weight. RESULTS: 56.8% of men and 69.3% of women aged over 15 y had a BMI record. 22% of men and 32.3% of women aged 15 to 24 y were overweight or obese; rising each decade to a peak of 65.6% of men and 57.5% of women aged 55 to 64 y. Thereafter, the proportion who were overweight or obese declined. The prevalence of ischaemic heart disease, diabetes mellitus and hypertension rose with increasing levels of obesity; their prevalence in those who are moderately obese was between two and three times that of the general population. Systolic and diastolic blood pressure, blood glucose even in non-diabetics, cholesterol and triglycerides were all elevated in the overweight and obese population. CONCLUSION: Based on the recorded data over half of men and nearly half of women are overweight or obese. They have increased cardiovascular risk, which is not adequately controlled by current practice.

Adolescent↗
PubMed2006

Does a higher 'quality points' score mean better care in stroke? An audit of general practice medical records.

BACKGROUND: The Royal College of Physicians (RCP) have produced guidelines for stroke management in primary care; this guidance is taken to be the gold standard for the care of people with stroke. UK general practitioners now have a quality-based contract which includes a Quality and Outcomes Framework (QOF). This consists of financially remunerated 'quality points' for specific disease areas, including stroke. Achievement of these quality points is measured by extracting a limited list of computer codes from practice computer systems. OBJECTIVES: To investigate whether a high stroke quality score is associated with adherence to RCP guidelines. DESIGN: Examination of computer and written medical records of all patients with a diagnosis of stroke. SETTING: Two general practices, one in southwest London, one in Surrey, with a combined practice population of over 20 000. Both practices had a similar age-sex profile and prevalence of stroke. RESULTS: One practice scored 93.5% (29/31) of the available stroke quality points. The other practice achieved 73.4% (22.75/31), and only did better in one stroke quality target. However, the practice scoring fewer quality points had much better adherence to RCP guidance: 96% of patients were assessed in secondary care compared with 79% (P=0.001); 64% of stroke patients were seen the same day, compared with 44%; 56% received rehabilitation compared with 37%. CONCLUSIONS: Higher quality points did not reflect better adherence to RCP guidance. This audit highlights a gap between relatively simplistic measures of quality in the QOF, dependent on the recording of a narrow range of computer codes, and the actual standard of care being delivered. Research is needed to see whether this finding is generalisable and how the Quality and Outcomes Framework might be better aligned with delivering best practice.

Adolescent↗
PubMed2006

Routinely-collected general practice data are complex, but with systematic processing can be used for quality improvement and research.

BACKGROUND: UK general practice is computerised, and quality targets based on computer data provide a further incentive to improve data quality. A National Programme for Information Technology is standardising the technical infrastructure and removing some of the barriers to data aggregation. Routinely collected data is an underused resource, yet little has been written about the wide range of factors that need to be taken into account if we are to infer meaning from general practice data. OBJECTIVE: To report the complexity of general practice computer data and factors that need to be taken into account in its processing and interpretation. METHOD: We run clinically focused programmes that provide clinically relevant feedback to clinicians, and overview statistics to localities and researchers. However, to take account of the complexity of these data we have carefully devised a system of process stages and process controls to maintain referential integrity, and improve data quality and error reduction. These are integrated into our design and processing stages. Our systems document the query, reference code set and create unique patient ID. The design stage is followed by appraisal of: data entry issues, how concepts might be represented in clinical systems, coding ambiguities, using surrogates where needed, validation and pilot-ing. The subsequent processing of data includes extraction, migration and integration of data from different sources, cleaning, processing and analysis. RESULTS: Results are presented to illustrate issues with the population denominator, data entry problems, identification of people with unmet needs, and how routine data can be used for real-world testing of pharmaceuticals. CONCLUSIONS: Routinely collected primary care data could contribute more to the process of health improvement; however, those working with these data need to understand fully the complexity of the context within which data entry takes place.

Ambulatory Care Information Systems↗
PubMed2006

The optimum granularity for coding diagnostic data in primary care: report of a workshop of the EFMI Primary Care Informatics Working Group at MIE 2005.

INTRODUCTION: The EFMI Primary Care Informatics Working Group held a workshop to explore interventions used across Europe to improve the data quality in primary care computerised medical records. METHOD: A plenary session reviewed the UK literature about improving data quality and then the session split into three small groups. Fifteen delegates from nine countries contributed to the workshop. These groups reported back at the end of the session. RESULTS: The groups defined what they meant by data quality. The principal requirement was that data must be 'fit for purpose'. The participants felt this was particularly important for diagnostic data, while recognising that the purpose might not be known at the point of data recording. They also described the barriers to recording structured and coded data. The most important were an inappropriate interface with the coding system and inappropriate granularity of codes. There was a wide range of suggestions as to how to overcome these barriers, including providing feedback, links to expert systems, education and training, use of the data for care elsewhere in the health system and mandation of electronic data recording. CONCLUSIONS: The workshop developed a new characteristic of data quality: 'fit for purpose'. This is different from definitions that focus on completeness, accuracy, currency, or its positive predictive value and sensitivity. The group also highlighted the importance of data quality of diagnoses, as these data are important throughout the health system as well as acting as a prompt for other interventions within the individual consultation. More research is needed into appropriate levels of granularity for diagnostic recording in primary care.

Diagnostic Tests, Routine↗
PubMed2006

Using UMLS to map from a library to a clinical classification: Improving the functionality of a digital library.

The Metathesaurus of the Unified Medical Language System (UMLS) offers the possibility of mapping between various medical vocabularies. The Primary Care Electronic Library (PCEL) contains a database of over six thousand Medical Subject Headings (MeSH terms) describing the resources of the electronic library. We were interested to know if it was possible to map from MeSH to the Systemized Nomenclature of Medicine Clinical Terms (SNOMED CT). Such a mapping would aid healthcare professionals to retrieve relevant data from our digital library as it would enable links between clinical systems and indexed material.

Databases, Bibliographic↗
PubMed2006

Specific classification of elibrary resources says more about users' preferences.

BACKGROUND: Medical Subject Headings (MeSH) are a hierarchical taxonomy of over 42,000 descriptors designed to classify scientific literature; it is hierarchical with generic high order headings and specific low order headings. Over 1,000 resources in the Primary Care Electronic Library (PCEL - www.pcel.info) were classified with MeSH. METHODS: Each of the entries or resources in the primary care digital library was assigned up to five MeSH terms. We compared whether the most generic or specific MeSH term ascribed to each resource best predicted user preferences. RESULTS: over the four month period analysed statistically significant differences were found for resources according to specific key MeSH terms they were classified by. This result was not repeated for generic key MeSH terms. CONCLUSIONS: Analysis of the use of specific MeSH terms reveals user preferences that would have otherwise remained obscured. These preferences are not found if more generic MeSH terms are analysed.

Consumer Behavior↗
PubMed2005

The use of routinely collected computer data for research in primary care: opportunities and challenges.

INTRODUCTION: Routinely collected primary care data has underpinned research that has helped define primary care as a specialty. In the early years of the discipline, data were collected manually, but digital data collection now makes large volumes of data readily available. Primary care informatics is emerging as an academic discipline for the scientific study of how to harness these data. This paper reviews how data are stored in primary care computer systems; current use of large primary care research databases; and, the opportunities and challenges for using routinely collected primary care data in research. OPPORTUNITIES: (1) Growing volumes of routinely recorded data. (2) Improving data quality. (3) Technological progress enabling large datasets to be processed. (4) The potential to link clinical data in family practice with other data including genetic databases. (5) An established body of know-how within the international health informatics community. CHALLENGES: (1) Research methods for working with large primary care datasets are limited. (2) How to infer meaning from data. (3) Pace of change in medicine and technology. (4) Integrating systems where there is often no reliable unique identifier and between health (person-based records) and social care (care-based records-e.g. child protection). (5) Achieving appropriate levels of information security, confidentiality, and privacy. CONCLUSION: Routinely collected primary care computer data, aggregated into large databases, is used for audit, quality improvement, health service planning, epidemiological study and research. However, gaps exist in the literature about how to find relevant data, select appropriate research methods and ensure that the correct inferences are drawn.

Biomedical Research↗
PubMed2005

The validity of searching routinely collected general practice computer data to identify patients with chronic kidney disease (CKD): a manual review of 500 medical records.

BACKGROUND: We conducted a search of 12 practices' routinely collected computer data in three localities across the UK and found that 4.9% of the registered population had an estimated glomerular filtration rate (GFR) of <60 ml/min/1.73 m(2) (equivalent to stages 3-5 CKD). Only 3.6% of these were known to have renal disease. Although UK general practice is computerized, important clinical data might be recorded in letters or free-text computer entries and might therefore be invisible to the standard computer search tools. We therefore manually searched through all the records of patients with stages 3-5 CKD in one practice, to test the validity of the computer generated diagnosis and to see if other relevant information was missed by the computer search. METHODS: We identified 492 people with stages 3-5 CKD using computer searching and then manually searched their computer records and written notes for any missed data. The dataset included cardiovascular morbidities and risk factors including diabetes; drugs which may impair renal function; known renal disease; and terminal diagnoses and dementia. RESULTS: The manual searches only added four renal diagnoses to the 36 already identified. Although heart failure and stroke appear to be over-estimated by computer searches, other cardiovascular diagnoses were reliably recorded. Cardiovascular risk factors and drug recording is a strength of general practice computer data. It is complete and contemporary, though most patients had scope to have their cardiovascular risk reduced further. Eighty-four percent had a haemoglobin estimation, and a higher proportion with reduced renal function were anaemic (P<0.001). Testing for proteinuria was less well recorded; negative stick tests were not recorded. Clinical diagnoses of prostatism and bladder outflow problems made these data hard to interpret. CONCLUSIONS: Automated searching of general practice computer records could provide a reliable and valid way of identifying people with stages 3-5 CKD who could benefit from interventions readily available in primary care.

Adult↗
PubMed2005

Identifying patients with chronic kidney disease from general practice computer records.

BACKGROUND: Chronic kidney disease (CKD) is an important predictor of end-stage renal disease, as well as a marker of increased mortality. The New Opportunities for Early Renal Intervention by Computerised Assessment (NEOERICA) project aimed to assess whether people with undiagnosed CKD who might benefit from early intervention could be identified from GP computer records. METHODS: The simplified Modification of Diet in Renal Disease (MDRD) equation was used to estimate glomerular filtration rate (GFR) and determine stage of CKD in patients from 12 practices in Surrey, Kent and Greater Manchester with SCr recorded in their notes. Further data were extracted on associated co-morbidities and potentially modifiable risk factors. RESULTS: One quarter (25.7%; 28,862/112,215) had an SCr recorded and one in five (18.9%) of them had a GFR <60 ml/min/1.73 m2 (equivalent to Stage 3-5 CKD), representing 4.9% of the population. Only 3.6% of these were recorded as having renal disease. Three-quarters (74.6%; 4075/5449) of those with Stage 3-5 CKD had one or more circulatory diseases; 346 were prescribed potentially nephrotoxic drugs and over 4000 prescriptions were issued for drugs recommended to be used with caution in renal impairment. CONCLUSIONS: Patients with CKD can be identified by searching GP computer databases; along with associated co-morbidities and treatment. Results revealed a similar rate of Stage 3-5 CKD to that found previously in the USA. The very low rate of recording of renal disease in patients found to have CKD indicates scope for improving detection and early intervention.

Adult↗
PubMed2005

Do primary care professionals work as a team: a qualitative study.

Teamworking is a vital element in the delivery of primary healthcare. There is evidence that well organised multidisciplinary teams are more effective in developing quality of care. Personal Medical Services (PMS) is a health reform that allows general practices more autonomy and flexibility in delivering quality based primary care. Practices in the locality where this study was conducted were offered resources to employ additional staff. Such arrangements provided the opportunity to expand and develop Primary Care Teams. In this qualitative study, semi-structured interviews were conducted with primary care professionals in 21 second wave PMS practices. Some participants felt they had used PMS to build their teams and develop quality based patient care. For other practices teamworking was limited by the absence of a common goal, recruitment difficulties, inadequate communication and hierarchical structures, and prevented practices from moving forward with clear direction. The study indicates that changing the contractual arrangements does not necessarily improve teamworking. It highlights the need for more sustained educational and quality improvement initiatives to encourage greater collaboration and understanding between healthcare professionals.

Humans↗
PubMed2005

Codes, classifications, terminologies and nomenclatures: definition, development and application in practice.

The Primary Care Informatics Working Group of EFMI is working to help develop the core theory of primary care informatics (PCI). Codes, classifications, terminologies and nomenclatures form an important part of the science of PCI, as they allow clinical information to be readily stored and processed in information systems. This article provides definitions and a history of the International Classification for Primary Care (ICPC), and of the Read code and the Systematized Nomenclature for Medicine (SNOMED). The Working Group wishes to encourage shared definitions and an understanding of the practical application of structured data to improve quality in clinical practice.

Ambulatory Care Information Systems↗