Assessing ICD-9-CM and ICPC-2 Use in Primary Care. An Italian Case Study

Controlled vocabularies and standardized coding systems play a fundamental role in the healthcare domain. The International Classification of Diseases (ICD) is one of the most widely used classification systems for clinical problems and procedures. In Italy the 9th revision of the standard is used and recommended in primary care for encoding prescription documents. This paper describes a statistical and terminological study to assess ICD-9-CM use in primary care and its comparison to the International Classification of Primary Care (ICPC), specifically designed for primary care. The study has been conducted by analyzing the clinical records of about 199,000 patients provided by a set of 166 General Practitioners (GPs) in different Italian areas. The analysis has been based on several techniques for detecting coding practice and errors, like natural language processing and text-similarity comparison. Results showed that the selected GPs do not fully exploit the diseases and procedures descriptive capabilities of ICD-9-CM due to its complexity. Furthermore, compared to ICPC-2, it resulted less feasible in the primary care setting, particularly for the high granularity of the structure and for the lack of reasons for encounters

Fitness for purpose of routinely recorded health data to identify patients with complex diseases: The case of Sjögren's syndrome

Background: This study is part of the EU-funded project HarmonicSS, aimed at improving the treatment and diagnosis of primary Sjögren's syndrome (pSS). pSS is an underdiagnosed, long-term autoimmune disease that affects particularly salivary and lachrymal glands. Objectives: We assessed the usability of routinely recorded primary care and hospital claims data for the identification and validation of patients with complex diseases such as pSS. Methods: pSS patients were identified in primary care by translating the formal inclusion and exclusion criteria for pSS into a patient selection algorithm using data from Nivel Primary Care Database (PCD), covering 10% of the Dutch population between 2006 and 2017. As part of a validation exercise, the pSS patients found by the algorithm were compared to Diagnosis Related Groups (DRG) recorded in the national hospital insurance claims database (DIS) between 2013 and 2017. Results: International Classification of Primary Care (ICPC) coded general practitioner (GP) contacts combined with the mention of “Sjögren” in the disease episode titles, were found to best translate the formal classification criteria to a selection algorithm for pSS. A total of 1462 possible pSS patients were identified in primary care (mean prevalence 0.7‰, against 0.61‰ reported globally). The DIS contained 208 545 patients with a Sjögren related DRG or ICD10 code (prevalence 2017: 2.73‰). A total of 2 577 577 patients from Nivel PCD were linked to the DIS database. A total of 716 of the linked pSS patients (55.3%) were confirmed based on the DIS. Conclusion: Our study finds that GP electronic health records (EHRs) lack the granular information needed to apply the formal diagnostic criteria for pSS. The developed algorithm resulted in a patient selection that approximates the expected prevalence and characteristics, although only slightly over half of the patients were confirmed using the DIS. Without more detailed diagnostic information, the fitness for purpose of routine EHR data for patient identification and validation could not be determined

Measuring multimorbidity in Australia

The ageing of the population is expected to lead to increases in the prevalence of chronic conditions, multimorbidity, and raised demand for primary care services. To enable health systems to respond to these increases, the prevalence of chronic conditions and multimorbidity need to be measured in an accurate and timely manner. However, prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods used in research. The aim of this thesis is to develop a reliable and practical method of measuring multimorbidity in Australia. The research reported in this thesis is based on two sets of sub-studies of the Bettering the Evaluation and Care of Health (BEACH) program, a continuous national survey of Australian general practice activity. The first survey was conducted between August 2008 and May 2009, and involved 290 randomly selected general practitioners (GPs) who recorded all diagnosed chronic conditions in 8,707 patients at their encounters. Having GPs record patients’ diagnosed chronic conditions avoids the limitations of self-reported data used in most large population prevalence studies. However, patients sampled at GP encounters are not representative of the population as only about 87% of people visit a GP in any year and because older people are more likely to attend and to attend more often. To estimate population prevalence, I weighted each age-sex group to match the distribution of the population. I then weighted the outcome by the proportion in each age-sex group who visited a GP at least once in the survey year, assuming those who did not see a GP did not have a diagnosed chronic condition. I estimated that two-thirds (66.3%) of patients at GP encounters had at least one diagnosed chronic condition as did half (50.8%) of the Australian population. Hypertension was the most prevalent condition, 26.6% of patients at GP encounters and 17.4% of the population having this diagnosed condition. While multimorbidity has been most often defined as 2+ chronic conditions, there have been recent moves towards using 3+. There have been calls for standardisation of multimorbidity research, inconsistent definitions and methods having led to large variance in estimated prevalence between studies. I examined the independent effects on prevalence estimates of: iii 1. how ‘morbidity’ is defined either as a single chronic condition or a ‘group’ of conditions using the chapter/domain structure of the International Classification of Primary Care (Version 2) (ICPC-2), the International Classification of Disease (10th revision)(ICD-10), or the Cumulative Illness Rating Scale (CIRS); 2. the number of ‘morbidities’ required in the definition of multimorbidity; 3. the number of diagnosed chronic conditions included in the study. I found that data grouped by ICPC-2 chapters, ICD-10 chapters or CIRS domains produced similar multimorbidity prevalence estimates. Multimorbidity defined as 2+ morbidities provided similar estimates whether individual conditions or groups of conditions were counted and whether as few as 12 prevalent chronic conditions were studied or all chronic conditions, but it lacked the specificity to be useful, especially among older people. Multimorbidity, defined as 3+ morbidities, required more measurement conformity and inclusion of all chronic conditions, but provided greater specificity than the 2+ definition. These results led to a set of guidelines for multimorbidity researchers, which if followed, will produce results that can be compared with results from other studies adhering to the same guidelines. I also proposed the concept of ‘complex multimorbidity’, the co-occurrence of three or more chronic conditions classified in three or more different body systems within one person, without defining an index chronic condition. Using ‘complex multimorbidity’ may identify high-need individuals. I estimated that: 47.4% of patients at GP encounters and one-third (32.6%) of the population had multimorbidity (2+); further, that 27.4% of patients at GP encounters and 17.0% of the Australian population had complex multimorbidity. The most prevalent pattern of three conditions was hypertension + hyperlipidaemia + osteoarthritis (5.5% of patient at encounters and 3.3% of the population). In my second, larger, survey, conducted between November 2012 and March 2016, 1,449 randomly selected GPs recorded all diagnosed chronic conditions for 43,501 patients. They also recorded the number of times each patient had seen a GP in the previous 12 months. Data collected in Survey 1 had not allowed adjustment for high and low attenders within each age-sex group. The individual attendance data in survey 2 allowed me to adjust for each patient’s chance of being in the survey sample. iv My prevalence estimates for patients at encounters were similar to those from Survey 1, with 26.5% of patients at encounters having diagnosed hypertension, 51.6% multimorbidity and 30.4% having complex multimorbidity. However, the population prevalence estimates produced with the new method were significantly lower than those from the previous method, an estimated 12.4% of the population having diagnosed hypertension, 25.7% multimorbidity and 12.1% complex multimorbidity. This suggests that patients with more chronic conditions attend more often than others in their age-sex group. Adjusting for individual patient attendance is therefore required to produce reliable population estimates from data collected from patients sampled at GP encounters. My final task was to develop a parsimonious model to predict patient GP-visit rate, testing the assumption that the number of chronic conditions is driving GP service use. In Survey 2, the number of diagnosed chronic conditions alone accounted for a significant proportion of the variance (25.5%) in patient GP-visit rate. The number of body systems involved also explained a significant proportion of variance (23.9%). Including patient age, sex and Commonwealth concession health care card status only marginally increased the predictive value of the model to 27.9%. In summary, this thesis demonstrates a practical method of measuring multimorbidity in Australia, using GPs as expert interviewers and adjusting for each patient’s individual attendance. I have shown that to produce robust results that can be compared with other studies, multimorbidity researchers should ideally define multimorbidity as 3+ conditions and include as many chronic conditions as possible in their study. Finally the measure has practical application as the number of diagnosed chronic conditions in an individual is the most significant driver of general practice service use. The results of this research will help inform health policy makers in their response to the challenges posed by continued growth in the prevalence of multimorbidity

An inventory of European data sources to support pharmacoepidemiologic research on neurodevelopmental outcomes in children following medication exposure in pregnancy: A contribution from the ConcePTION project

BACKGROUND: Studies on medication safety in pregnancy are increasingly focusing on child neurodevelopmental outcomes. Establishing neurodevelopmental safety is complex due to the range of neurodevelopmental outcomes and the length of follow-up needed for accurate assessment. The aim of this study was to provide an inventory of European data sources for use in pharmacoepidemiologic studies investigating neurodevelopment following maternal medication exposure. METHOD: The EUROmediSAFE inventory of data sources in Europe for evaluating perinatal and long-term childhood risks associated with in-utero exposure to medication was updated by contacting colleagues across 31 European countries, literature review and internet searches. Included data sources must record at least one neurodevelopmental outcome and maternal medication use in pregnancy must be available, either in the data source itself or through linkage with another data source. Information on the domain of neurodevelopment, measure/scale used and the approach to measurement were recorded for each data source. RESULTS: Ninety data sources were identified across 14 countries. The majority (63.3%) were created for health surveillance and research with the remaining serving administrative purposes (21.1% healthcare databases,15.6% other administrative databases). Five domains of neurodevelopment were identified—infant development (36 data sources,13 countries), child behaviour (27 data sources, 10 countries), cognition (29 data sources, 12 countries), educational achievement (20 data sources, 7 countries), and diagnostic codes for neurodevelopmental disorders (42 data sources, 11 countries). Thirty-nine data sources, in 12 countries, had information on more than one domain of neurodevelopment. CONCLUSION: This inventory is invaluable to future studies planning to investigate the neurodevelopmental impact of medication exposures during pregnancy. Caution must be used when combining varied approaches to neurodevelopment outcome measurement, the age of children in the data source, and the sensitivity and specificity of the outcome measure selected should be borne in mind

Multimorbidity Among Adult Primary Health Care Patients In Canada: Examining Multiple Chronic Diseases Using An Electronic Medical Record Database

Introduction: The coexistence of multiple chronic diseases within an individual, also known as multimorbidity, is an ongoing challenge for patients, caregivers and primary health care (PHC) providers. An enhanced understanding of the burden of multimorbidity in Canada is needed. Objectives: This research had two main objectives. Objective One aimed to understand the prevalence of multimorbidity among adult PHC patients, as well as the patterns of unordered and ordered clusters of multiple chronic diseases. Objective Two aimed to determine the natural progression of multimorbidity over time, as well as the patient-, provider- and practice-level predictors of progressing into more complex clinical profiles. Methods: Data were derived from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical record (EMR) database. For Objective One, descriptive and computational analyses were conducted and for Objective Two, multilevel survival analyses were conducted to account for clustering. Patients with at least one encounter recorded in their EMR and who were at least 18 years of age at their first encounter were included in the analyses. Chronic disease diagnoses were identified using the International Classification of Diseases, 9th Revision (ICD-9) and a list of 20 chronic disease categories identified patients with multimorbidity. Results: Overall, 53.3% and 33.1% of adult PHC patients were living with at least two and at least three chronic diseases, respectively. Patients with at least two chronic diseases had a mean age of 59.0 years (SD: 17.0), while the majority were female (57.8%) and living in an urban setting (52.2%). Among female patients with multimorbidity, 6,095 unique combinations and 14,911 unique permutations were found. Among male patients with multimorbidity, 4,316 unique combinations and 9,736 unique permutations were detected. The multilevel survival analysis indicated that several patient-level (patient age, patient sex and total number of chronic diseases), provider-level (provider age) and practice-level (EMR type and practice location) variables predicted time until subsequent chronic disease diagnoses. Conclusion: This research explored the prevalence, patterns and natural progression of multimorbidity over time among a large cohort of adult PHC patients. When carefully assessed, these findings will help to create a more nuanced understanding of the burden of multimorbidity

Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review

PurposeTo identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. MethodsSystematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study. ResultsWe found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median=4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). ConclusionsPharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing. (c) 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.Peer reviewe

Mortality, substance use disorder and cardiovascular health care in persons with severe mental illness

Background and aims - In the Nordic countries, people with severe mental illness die 15-20 years younger than others. Substance use and higher level of undiagnosed/untreated somatic diseases contribute to this disparity. We aimed to investigate; (i) mortality among people with schizophrenia and/or substance use disorder, with emphasis on the impact of a dual diagnosis; (ii) whether people with schizophrenia or bipolar disorder had higher odds of not being diagnosed with cardiovascular disease prior to cardiovascular death, and; (iii) whether people with schizophrenia or bipolar disorder had equal prevalence of diagnostic testing and treatment of cardiovascular disease prior to cardiovascular death as people without such disorders. Methods - We calculated standardized mortality ratios in a 7-year open cohort study including all residents of Norway aged 20-79 with schizophrenia and/or substance use disorders diagnosed in specialized care (i). We used multivariate logistic (ii) and log-binomial regression (iii) to study uptake of CVD-related health care services in residents aged 18 and above. Results - We found a four-fold (schizophrenia only) to seven-fold (substance use disorder with or without schizophrenia) increased mortality compared to the general population, implicating that five out of six persons with schizophrenia and/or substance use disorder died prematurely. We also found that people with schizophrenia and women with bipolar disorder were more likely to die from undiagnosed cardiovascular disease. They also had lower prevalence of specialized cardiovascular examinations and invasive cardiovascular treatment prior to cardiovascular death, compared to individuals without schizophrenia or bipolar disorder. We found no difference in uptake of invasive cardiovascular treatment in those diagnosed with cardiovascular disease prior to death. Conclusion - The large mortality gap between persons with severe mental illness and the general population highlights the need of securing proper access to specialized somatic care, and a more effective prevention of deaths from unnatural causes in this group