How are reasons for encounter associated with influenza-like illness and acute respiratory infection diagnoses and interventions? A cohort study in eight Italian general practice populations.

BACKGROUND: Influenza-like illness (ILI) and Acute Respiratory Infections (ARI) are a considerable health problem in Europe. Most diagnoses are made by family physicians (FPs) and based on symptoms and clinical signs rather than on diagnostic testing. The International Classification of Primary Care (ICPC) advocates that FPs record patients' 'Reasons for Encounters' (RfEs) as they are presented to them. This study analyses the association of patients' RfEs with FPs' diagnoses of ILI and ARI diagnoses and FPs' management of those patients. METHODS: Cohort study of practice populations. Over a 4-month period during the winter season 2013-14, eight FPs recorded ILI and ARI patients' RfEs and how they were managed. FPs recorded details of their patients using the ICPC format, collecting data in an Episode of Care (EoC) structure. RESULTS: There were 688 patients diagnosed as having ILI; between them they presented with a total of 2,153 RfEs, most commonly fever (79.7%), cough (59.7%) and pain (33.0%). The 848 patients with ARI presented with a total of 1,647 RfEs, most commonly cough (50.4%), throat symptoms (25.9%) and fever (19.9%). For patients with ILI, 37.0% of actions were related to medication for respiratory symptoms; this figure was 38.4% for patients with ARI. FPs referred six patients to specialists or hospitals (0.39% of all patients diagnosed with ILI and ARI). CONCLUSIONS: In this study of patients with ILI and ARI, less than half received a prescription from their FPs, and the illnesses were mainly managed in primary care, with few patients' needing referral. The ICPC classification allowed a standardised data collection system, providing documentary evidence of the management of those diseases.

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.

The fractured lens: a controversial revision of the International Classification of Primary Care.

Background: The International Classification of Primary Care (ICPC) has represented the international standard reduction for measuring the content of primary care for over 30 years. In the process of its third revision, its authors, the Wonca International Classification Committee (WICC), delegated a major part of the technical work to a purposely formed Consortium. However, in the process of such revision, standard classification principles and rules have been inconsistently applied with the result that ICPC-3 has been published with major errors and an inconsistent structure. Objectives: To formally describe and critically appraise the revision process of ICPC-3. Methods: The formal review of ICPC-3 performed by an expert group within WICC and commissioned by the Executive Council of Wonca Europe is presented in abridged form. Results: ICPC-3 as currently presented introduces major departures from formal classification principles and rules, besides other major errors and inconsistencies, all of which are listed and described. Conclusion: Major changes in ICPC-3 defy categorisation and conceptualisation standards. ICPC-3 now represents an untested departure from international standard presentations, without a formal academic base. The direct inclusion of measures of functioning in a classification of reasons for encounter and health problems fails to address the dichotomy of these domains, the boundaries of and relationships between which are not satisfactorily resolved by the system. Analysis of ICPC-3 data will require the development and implementation of alternative, as yet undefined, models of the relationships between disease and health. By including different domains without resolving ambiguity, and by splitting function from other body systems, ICPC-3 becomes an internally fractured instrument.

An international comparative family medicine study of the Transition Project data from the Netherlands, Malta and Serbia. Is family medicine an international discipline? Comparing diagnostic odds ratios across populations.

INTRODUCTION: This is an international study of the epidemiology of family medicine (FM) in three practice populations from the Netherlands, Malta and Serbia. Diagnostic associations between common reasons for encounter (RfEs) and episodes titles are compared and similarities and differences are described and analysed. METHODOLOGY: Participating family doctors (FDs) recorded details of all their patient contacts in an 'episode of care (EoC)' structure using the International Classification of Primary Care (ICPC). RfEs presented by the patient and episode titles (diagnostic labels of EoCs) were classified with ICPC. The relationships between RfEs and episode titles were studied with Bayesian methods. RESULTS: Distributions of diagnostic odds ratios (ORs) from the three population databases are presented and compared. CONCLUSIONS: ICPC, the RfE and the EoC data model are appropriate tools to study the process of diagnosis in FM. Distributions of diagnostic associations between RfEs and episode titles in the Transition Project international populations show remarkable similarities and congruencies in the process of diagnosis from both the RfE and the episode title perspectives. The congruence of diagnostic associations between populations supports the use of such data from one population to inform diagnostic decisions in another. Differences in the magnitude of such diagnostic associations are significant, and population-specific data are therefore desirable. We propose that both an international (common) and a local (health care system specific) content of FM exist and that the empirical distributions of diagnostic associations presented in this paper are a reflection of both these effects. We also observed that the frequency of exposure to such diagnostic challenges had a strong effect on the confidence intervals of diagnostic ORs reflecting these diagnostic associations. We propose that this constitutes evidence that expertise in FM is associated with frequency of exposure to diagnostic challenges.

An international comparative family medicine study of the Transition Project data from the Netherlands, Malta, Japan and Serbia. An analysis of diagnostic odds ratios aggregated across age bands, years of observation and individual practices.

INTRODUCTION: This is a study of the process of diagnosis in family medicine (FM) in four practice populations from the Netherlands, Malta, Serbia and Japan. Diagnostic odds ratios (ORs) for common reasons for encounter (RfEs) and episode titles are used to study the process of diagnosis in international FM and to test the assumption that data can be aggregated across different age bands, practices and years of observation. METHODOLOGY: Participating family doctors (FDs) recorded details of all their patient contacts in an episode of care (EoC) structure using the International Classification of Primary Care (ICPC). RfEs presented by the patient and the diagnostic labels (EoC titles) recorded for each encounter were classified with ICPC. The relationships between RfEs and episode titles were expressed as ORs using Bayesian probability analysis to calculate the posterior (post-test) odds of an episode title given an RfE, at the start of a new EoC. RESULTS: The distributions of diagnostic ORs from the four population databases are tabled across age groups, years of observation and practices. CONCLUSIONS: There is a lot of congruence in diagnostic process and concepts between populations, across age groups, years of observation and FD practices, despite differences in the strength of such diagnostic associations. There is particularly little variability of diagnostic ORs across years of observation and between individual FD practices. Given our findings, it makes sense to aggregate diagnostic data from different FD practices and years of observation. Our findings support the existence of common core diagnostic concepts in international FM.

An international comparative family medicine study of the Transition Project data from the Netherlands, Malta and Serbia. Is family medicine an international discipline? Comparing incidence and prevalence rates of reasons for encounter and diagnostic titles of episodes of care across populations.

INTRODUCTION: This is a study of the epidemiology of family medicine (FM) in three practice populations from the Netherlands, Malta and Serbia. Incidence and prevalence rates, especially of reasons for encounter (RfEs) and episode labels, are compared. METHODOLOGY: Participating family doctors (FDs) recorded details of all their patient contacts in an episode of care (EoC) structure using electronic patient records based on the International Classification of Primary Care (ICPC), collecting data on all elements of the doctor-patient encounter. RfEs presented by the patient, all FD interventions and the diagnostic labels (EoCs labels) recorded for each encounter were classified with ICPC (ICPC-2-E in Malta and Serbia and ICPC-1 in the Netherlands). RESULTS: The content of family practice in the three population databases, incidence and prevalence rates of the common top 20 RfEs and EoCs in the three databases are given. CONCLUSIONS: Data that are collected with an episode-based model define incidence and prevalence rates much more precisely. Incidence and prevalence rates reflect the content of the doctor-patient encounter in FM but only from a superficial perspective. However, we found evidence of an international FM core content and a local FM content reflected by important similarities in such distributions. FM is a complex discipline, and the reduction of the content of a consultation into one or more medical diagnoses, ignoring the patient's RfE, is a coarse reduction, which lacks power to fully characterize a population's health care needs. In fact, RfE distributions seem to be more consistent between populations than distributions of EoCs are, in many respects.

Revisiting the concept of 'chronic disease' from the perspective of the episode of care model. Does the ratio of incidence to prevalence rate help us to define a problem as chronic?

BACKGROUND: This is a study of the epidemiology of acute and chronic episodes of care (EoCs) in the Transition Project in three countries. We studied the duration of EoCs for acute and chronic health problems and the relationship of incidence to prevalence rates for these EoCs. METHOD: The Transition Project databases collect data on all elements of the doctor-patient encounter in family medicine. Family doctors code these elements using the International Classification of Primary Care. We used the data from three practice populations to study the duration of EoCs and the ratio of incidence to prevalence for common health problems. RESULTS: We found that chronic health problems tended to have proportionately longer duration EoCs, as expected, but also a lower incidence to prevalence rate ratio than acute health problems. Thus, the incidence to prevalence index could be used to define a chronic condition as one with a low ratio, below a defined threshold. CONCLUSIONS: Chronic health problems tend to have longer duration EoCs, proportionately, across populations. This result is expected, but we found important similarities and differences which make defining a problem as chronic on the basis of time rather difficult. The ratio of incidence to prevalence rates has potential to categorise health problems into acute or chronic categories, at different ratio thresholds (such as 20, 30 or 50%). It seems to perform well in this study of three family practice populations, and is proposed to the scientific community for further evaluation.

The interpretation of the reasons for encounter 'cough' and 'sadness' in four international family medicine populations.

BACKGROUND: This is a study of the relationships between common reasons for encounter (RfEs) and common diagnoses (episode titles) within episodes of care (EoCs) in family practice populations in four countries. METHOD: Participating family doctors (FDs) recorded details of all their patient contacts in an EoC structure using the International Classification of Primary Care (ICPC), including RfEs presented by the patient, and the FDs' diagnostic labels. The relationships between RfEs and episode titles were studied using Bayesian methods. RESULTS: The RfE 'cough' is a strong, reliable predictor for the diagnoses 'cough' (a symptom diagnosis), 'acute bronchitis', 'URTI' and 'acute laryngitis/tracheitis' and a less strong, but reliable predictor for 'sinusitis', 'pneumonia', 'influenza', 'asthma', 'other viral diseases (NOS)', 'whooping cough', 'chronic bronchitis', 'wheezing' and 'phlegm'. The absence of cough is a weak but reliable predictor to exclude a diagnosis of 'cough', 'acute bronchitis' and 'tracheitis'. Its presence allows strong and reliable exclusion of the diagnoses 'gastroenteritis', 'no disease' and 'health promotion/prevention', and less strong exclusion of 'adverse effects of medication'. The RfE 'sadness' is a strong, reliable predictor for the diagnoses 'feeling sad/depressed' and 'depressive disorder'. It is a less strong, but reliable predictor of a diagnosis of 'acute stress reaction'. The absence of sadness (as a symptom) is a weak but reliable predictor to exclude the symptom diagnosis 'feeling sad/depressed'. Its presence does not support the exclusion of any diagnosis. CONCLUSIONS: We describe clinically and statistically significant diagnostic associations observed between the RfEs 'cough' and 'sadness', presenting as a new problem in family practice, and all the episode titles in ICPC.

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.

A methodology for mining clinical data: experiences from TRANSFoRm project.

Data mining of electronic health records (eHRs) allows us to identify patterns of patient data that characterize diseases and their progress and learn best practices for treatment and diagnosis. Clinical Prediction Rules (CPRs) are a form of clinical evidence that quantifies the contribution of different clinical data to a particular clinical outcome and help clinicians to decide the diagnosis, prognosis or therapeutic conduct for any given patient. The TRANSFoRm diagnostic support system (DSS) is based on the construction of an ontological repository of CPRs for diagnosis prediction in which clinical evidence is expressed using a unified vocabulary. This paper explains the proposed methodology for constructing this CPR repository, addressing algorithms and quality measures for filtering relevant rules. Some preliminary application results are also presented.