Evidence-based rules from family practice to inform family practice; the learning healthcare system case study on urinary tract infections.

BACKGROUND: Analysis of encounter data relevant to the diagnostic process sourced from routine electronic medical record (EMR) databases represents a classic example of the concept of a learning healthcare system (LHS). By collecting International Classification of Primary Care (ICPC) coded EMR data as part of the Transition Project from Dutch and Maltese databases (using the EMR TransHIS), data mining algorithms can empirically quantify the relationships of all presenting reasons for encounter (RfEs) and recorded diagnostic outcomes. We have specifically looked at new episodes of care (EoC) for two urinary system infections: simple urinary tract infection (UTI, ICPC code: U71) and pyelonephritis (ICPC code: U70). METHODS: Participating family doctors (FDs) recorded details of all their patient contacts in an EoC structure using the ICPC, including RfEs presented by the patient, and the FDs' diagnostic labels. The relationships between RfEs and episode titles were studied using probabilistic and data mining methods as part of the TRANSFoRm project. RESULTS: The Dutch data indicated that the presence of RfE's "Cystitis/Urinary Tract Infection", "Dysuria", "Fear of UTI", "Urinary frequency/urgency", "Haematuria", "Urine symptom/complaint, other" are all strong, reliable, predictors for the diagnosis "Cystitis/Urinary Tract Infection" . The Maltese data indicated that the presence of RfE's "Dysuria", "Urinary frequency/urgency", "Haematuria" are all strong, reliable, predictors for the diagnosis "Cystitis/Urinary Tract Infection". The Dutch data indicated that the presence of RfE's "Flank/axilla symptom/complaint", "Dysuria", "Fever", "Cystitis/Urinary Tract Infection", "Abdominal pain/cramps general" are all strong, reliable, predictors for the diagnosis "Pyelonephritis" . The Maltese data set did not present any clinically and statistically significant predictors for pyelonephritis. CONCLUSIONS: We describe clinically and statistically significant diagnostic associations observed between UTIs and pyelonephritis presenting as a new problem in family practice, and all associated RfEs, and demonstrate that the significant diagnostic cues obtained are consistent with the literature. We conclude that it is possible to generate clinically meaningful diagnostic evidence from electronic sources of patient data.

Quality of care for hypertensive patients with type 2 diabetes in a rural area of Southern Italy: is the recording of patient data and the achievement of quality indicators targets satisfactory?

INTRODUCTION: Type 2 diabetes mellitus and hypertension are commonly associated chronic conditions which require regular structured treatment. In the UK many quality markers have been improved through an incentivisation scheme. The aim of this study was to discover if there is potential for improving the quality of care for patients with type 2 diabetes and hypertension in rural Italy, through a quality and outcome incentivisation scheme. METHODS: The study was conducted in a rural practice context in Southern Italy and seven family doctors were involved. The main outcome measures were glycated haemoglobin A1c (HbA1c), LDL cholesterol, and systolic and diastolic blood pressure. The patient characteristics examined were age, sex, educational level, behaviour-related factors such as smoking and BMI, and the presence of comorbidities. RESULTS: A poor level of registration was found for important variables such as HBA1c (61.4% compared with the UK Quality Indicator of 90%). An adequate level of registration and control was found only for blood pressure (95.7% and 82.1%, respectively), while an acceptable but not optimal level of control for HBA1c was also achieved (88.4% ≤10%). In comparison with levels in UK practices, the Italian district studied performed much less favorably, especially regarding process indicators. Intermediate outcome and treatment indicators were slightly better for blood pressure control but slightly worse for HBA1c and cholesterol control. CONCLUSION: The data confirm a poor registration level for important healthcare indicators in the study area, and that optimal levels are rarely reached for many quality indicators. A quality and outcome incentivisation scheme similar to the UK Quality and Outcomes Framework may offer a tool for achieving improvements.