Identification of people with autosomal dominant polycystic kidney disease using routine data: a cross sectional study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) causes progressive renal damage and is a leading cause of end-stage renal failure. With emerging therapies it is important to devise a method for early detection. We aimed to identify factors from routine clinical data which can be used to distinguish people with a high likelihood of having ADPKD in a primary health care setting. METHOD: A cross-sectional study was undertaken using data from the Quality Intervention in Chronic Kidney Disease trial extracted from 127 primary care practices in England. The health records of 255 people with ADPKD were compared to the general population. Logistic regression was used to identify clinical features which distinguish ADPKD. These clinical features were used to stratify individual risk using a risk score tool. RESULTS: Renal impairment, proteinuria, haematuria, a diastolic blood pressure over 90 mmHg and multiple antihypertensive medications were more common in ADPKD than the general population and were used to build a regression model (area under the receiver operating characteristic curve; 0.79). Age, gender, haemoglobin and urinary tract infections were not associated with ADPKD. A risk score (range -3 to +10) of ≥0 gave a sensitivity of 70.2% and specificity 74.9% of for detection. CONCLUSIONS: Stratification of ADPKD likelihood from routine data may be possible. This approach could be a valuable component of future screening programs although further longitudinal analyses are needed

Confidence and quality in managing CKD compared with other cardiovascular diseases and diabetes mellitus: a linked study of questionnaire and routine primary care data

Background: Much of chronic disease is managed in primary care and chronic kidney disease (CKD) is a recent addition. We are conducting a cluster randomised study of quality improvement interventions in CKD (QICKD) - Clinical Trials Registration: ISRCTN56023731. CKD registers have a lower than expected prevalence and an initial focus group study suggested variable levels of confidence in managing CKD. Our objective is to compare practitioner confidence and achievement of quality indicators for CKD with hypertension and diabetes. Method: We validated a new questionnaire to test confidence. We compared confidence with achievement of pay-for-performance indicators (P4P) and implementation of evidence-based guidance. We achieved a 74% (148/ 201) response rate. Results: 87% (n = 128) of respondents are confident in managing hypertension (HT) compared with 59% (n = 87) in managing HT in CKD (HT+CKD); and with 61% (n = 90) in HT, CKD and diabetes (CKD+HT+DM). 85.2% (P4P) and 62.5% (National targets) of patients with hypertension are at target; in patients with HT and CKD 65.1% and 53.3%; in patients with HT, CKD and DM 67.8% and 29.6%. Confidence in managing proteinuria in CKD is low (42%, n = 62). 87% of respondents knew BP treatment thresholds in CKD, but only 53% when proteinuria is factored in. Male GPs, younger ( 54 yrs) clinicians are more confident than females and 35 to 54 year olds in managing CKD. 84% of patients with hypertension treated with angiotensin modulating drugs achieve achieved P4P targets compared to 67% of patients with CKD. Conclusions: Practitioners are less likely to achieve management targets where their confidence is low

Ethnicity Recording in Primary Care Computerised Medical Record Systems: An Ontological Approach

Background Ethnicity recording within primary care computerised medical record (CMR) systems is suboptimal, exacerbated by tangled taxonomies within current coding systems.Objective To develop a method for extending ethnicity identification using routinely collected data.Methods We used an ontological method to maximise the reliability and prevalence of ethnicity information in the Royal College of General Practitioner’s Research and Surveillance database. Clinical codes were either directly mapped to ethnicity group or utilised as proxy markers (such as language spoken) from which ethnicity could be inferred. We compared the performance of our method with the recording rates that would be identified by code lists utilised by the UK pay for the performance system, with the help of the Quality and Outcomes Framework (QOF).Results Data from 2,059,453 patients across 110 practices were included. The overall categorisable ethnicity using QOF codes was 36.26% (95% confidence interval (CI): 36.20%–36.33%). This rose to 48.57% (CI:48.50%–48.64%) using the described ethnicity mapping process. Mapping increased across all ethnic groups. The largest increase was seen in the white ethnicity category (30.61%; CI: 30.55%–30.67% to 40.24%; CI: 40.17%–40.30%). The highest relative increase was in the ethnic group categorised as the other (0.04%; CI: 0.03%–0.04% to 0.92%; CI: 0.91%–0.93%).Conclusions This mapping method substantially increases the prevalence of known ethnicity in CMR data and may aid future epidemiological research based on routine data

A simple clinical coding strategy to improve recording of child maltreatment concerns: an audit study

Background Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE) but there is evidence of substantial under-recording.Aim To determine whether a simple coding strategy improved recording of maltreatment-related concerns in electronic primary care records.Design and Setting Clinical audit of rates of maltreatment-related coding before January 2010–December 2011 and after January–December 2012 implementation of a simple coding strategy in 11 English family practices. The strategy included encouraging general practitioners to use, always and as a minimum, the Read code ‘Child is cause for concern’. A total of 25,106 children aged 0–18 years were registered with these practices. We also undertook a qualitative service evaluation to investigate barriers to recording.Method Outcomes were recording of 1) any maltreatment-related codes, 2) child protection proceedings and 3) child was a cause for concern.Results We found increased recording of any maltreatment-related code (rate ratio 1.4; 95% CI 1.1–1.6), child protection procedures (RR 1.4; 95% CI 1.1–1.6) and cause for concern (RR 2.5; 95% CI 1.8–3.4) after implementation of the coding strategy. Clinicians cited the simplicity of the coding strategy as the most important factor assisting implementation.Conclusion This simple coding strategy improved clinician’s recording of maltreatment-related concerns in a small sample of practices with some ‘buy-in’. Further research should investigate how recording can best support the doctor–patient relationshipHow this fits in Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE), but there is evidence of substantial underrecording. We describe a simple clinical coding strategy that helped general practitioners to improve recording of maltreatment-related concerns. These improvements could improve case finding of children at risk and information sharing

Extracting primary care records for prostate cancer patients in the CHHiP multicentre randomised control trial: A healthcare data linkage study

Introduction The aim is to investigate the effect of cardiovascular and diabetes comorbidities on radiotherapy-related side-effects in prostate cancer. Previous research suggests that comorbidities increase the risk of side-effects, but some cardiovascular medications may reduce symptoms by protecting against radiation damage. The evidence is inconclusive and mechanisms are not fully understood. Objective To explore whether routine primary care data can supplement clinical trial data in evaluating the impact of comorbidities and prescription medications on patient outcomes. Approach The CHHiP radiotherapy trial (CRUK/06/16) recruited 3,216 prostate cancer patients from 71 centres in UK, Ireland, Switzerland, and New Zealand between 2002 and 2011. Baseline comorbidity and radiotherapy-related side-effects over time were recorded. This was linked to computerised medical records (CMRs) from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. RCGP RSC is a network of 192 English general practices with over 2 million patients (2.8% of the population). Results The English population of CHHiP patients (N=2811) was used. 120 CMRs were linked, which exceeded the estimation of 79 linked records. However, six CMRs showed no evidence of regular GP care and a further eight patients were not recruited into the CHHiP trial until after they had de-registered from an RCGP RSC practice. Information on cardiovascular and diabetes comorbidities was extracted for 106 patients. The mean age was 69±7 years, representative of the CHHiP population. From the CMRs, 23 (22%) patients had diabetes and 47 (44%) had hypertension including 37 (35%) who took angiotensin converting enzyme (ACE) inhibitors (medications lowering blood pressure). In addition, 44 (41%) patients took aspirin, 65 (61%) statins (lowering blood lipids) and 14 (13%) took metformin (lowering blood sugar levels).  Conclusion/Implications The small sample limits statistical analysis. However, a clinical trial was successfully linked to GP data to determine comorbidities and medications of patients. This will serve as a pilot for further research. The advantage of data linkage is that it may provide a mechanism for long-term follow-up of radiotherapy-related side-effects

The QICKD study protocol: a cluster randomised trial to compare quality improvement interventions to lower systolic BP in chronic kidney disease (CKD) in primary care

BACKGROUND: Chronic kidney disease (CKD) is a relatively newly recognised but common long-term condition affecting 5 to 10% of the population. Effective management of CKD, with emphasis on strict blood pressure (BP) control, reduces cardiovascular risk and slows the progression of CKD. There is currently an unprecedented rise in referral to specialist renal services, which are often located in tertiary centres, inconvenient for patients, and wasteful of resources. National and international CKD guidelines include quality targets for primary care. However, there have been no rigorous evaluations of strategies to implement these guidelines. This study aims to test whether quality improvement interventions improve primary care management of elevated BP in CKD, reduce cardiovascular risk, and slow renal disease progression DESIGN: Cluster randomised controlled trial (CRT) METHODS: This three-armed CRT compares two well-established quality improvement interventions with usual practice. The two interventions comprise: provision of clinical practice guidelines with prompts and audit-based education. The study population will be all individuals with CKD from general practices in eight localities across England. Randomisation will take place at the level of the general practices. The intended sample (three arms of 25 practices) powers the study to detect a 3 mmHg difference in systolic BP between the different quality improvement interventions. An additional 10 practices per arm will receive a questionnaire to measure any change in confidence in managing CKD. Follow up will take place over two years. Outcomes will be measured using anonymised routinely collected data extracted from practice computer systems. Our primary outcome measure will be reduction of systolic BP in people with CKD and hypertension at two years. Secondary outcomes will include biomedical outcomes and markers of quality, including practitioner confidence in managing CKD. A small group of practices (n = 4) will take part in an in-depth process evaluation. We will use time series data to examine the natural history of CKD in the community. Finally, we will conduct an economic evaluation based on a comparison of the cost effectiveness of each intervention. CLINICAL TRIALS REGISTRATION: ISRCTN56023731. ClinicalTrials.gov identifier

Measuring the impact of the computer on the consultation: an open source application to combine multiple observational outputs

A diverse range of tools and techniques can be used to observe the clinical consultation and the use of information technology. These technologies range from transcripts; to video observation with one or more cameras; to voice and pattern recognition applications. Currently, these have to be observed separately and there is limited capacity to combine them. Consequently, when multiple methods are used to analyse the consultation a significant proportion of time is spent linking events in one log file (e.g. mouse movements and keyboard use when prescribing alerts appear) with what was happening in the consultation at that time. The objective of this study was to develop an application capable of combining and comparing activity log-files and with facilities to view simultaneously all data relating to any time point or activity. Interviews, observations and design prototypes were used to develop a specification. Class diagram of the application design was used to make further development decisions. The application development used object-orientated design principles. We used open source tools; Java as the programming language and JDeveloper as the development environment. The final output is log file aggregation (LFA) tool which forms part of the wider aggregation of log files for analysis (ALFA) open source toolkit ( www.biomedicalinformatics.info/alfa/ ). Testing was done using sample log files and reviewed the application's utility for analysis of the consultation activities. Separation of the presentation and functionality in the design stage enabled us to develop a modular and extensible application. The application is capable of converting and aggregating several log files of different formats and displays them in different presentation layouts. We used the Java Media Framework to aggregate video channels. Java extensible mark-up language (XML) package facilitated the conversion of aggregated output into XML format. Analysts can now move easily between observation tools and find all the data related to an activity. The LFA application makes new analysis tasks feasible and established tasks much more efficient. Researchers can now store multiple log file data as a single file isolate and investigate different doctor-computer-patient interaction