scholarly journals Assessing and predicting adolescent and early adulthood common mental disorders in the ALSPAC cohort using electronic primary care data

2021 ◽  
Author(s):  
Daniel Smith ◽  
Kathryn Willan ◽  
Stephanie L Prady ◽  
Josie Dickerson ◽  
Gillian Santorelli ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Outcome Measures ◽  
Predictive Accuracy ◽  
Common Mental Disorders ◽  
Early Adulthood ◽  
Predictive Modelling ◽  
Free Text ◽  
Reference Standard ◽  
Primary Care Data

Objectives: This paper has three objectives: 1) examine agreement between common mental disorders (CMDs) derived from primary health care records and repeated CMD questionnaire data from ALSPAC (the Avon Longitudinal Study of Parents and Children); 2) explore the factors affecting CMD identification in primary care records; and 3) taking ALSPAC as the reference standard, to construct models predicting ALSPAC-derived CMDs using primary care data. Design and Setting: Prospective cohort study (ALSPAC) with linkage to electronic primary care data. Participants: Primary care records were extracted for 11,807 ALSPAC participants (80% of the 14,731 eligible participants). The number of participants with both linked primary care and ALSPAC CMD data varied between 3,633 (age 15/16) to 1,298 (age 21/22). Outcome measures: Outcome measures from ALSPAC data were diagnoses of suspected depression and/or CMDs. For the primary care data, Read codes for diagnosis, symptoms and treatment were used to indicate the presence of depression and CMDs. For each time point, sensitivities and specificities (using ALSPAC-derived CMDs as the reference standard) were calculated and the factors associated with identification of primary care-based CMDs in those with suspected ALSPAC-derived CMDs explored. Lasso models were then performed to predict ALSPAC CMDs from primary care data. Results: Sensitivities were low for CMDs (range: 3.5 to 19.1%) and depression (range: 1.6 to 34.0%), while specificities were high (nearly all >95%). The strongest predictor of identification in the primary care data was symptom severity. The lasso models had relatively low prediction rates, especially for out-of-sample prediction (deviance ratio range: -1.3 to 12.6%), but improved with age. Conclusions: Even with predictive modelling using all available information, primary care data underestimate CMD rates compared to estimates from population-based studies. Research into the use of free-text data or secondary care information is needed to improve the predictive accuracy of models using clinical data.

scholarly journals Assessing and predicting adolescent and early adulthood common mental disorders using electronic primary care data: analysis of a prospective cohort study (ALSPAC) in Southwest England

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e053624
Author(s):  
Daniel Smith ◽  
Kathryn Willan ◽  
Stephanie L Prady ◽  
Josie Dickerson ◽  
Gillian Santorelli ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Mental Disorders ◽  
Outcome Measures ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Common Mental Disorders ◽  
Free Text ◽  
Primary Care Data ◽  
Time Point

ObjectivesWe aimed to examine agreement between common mental disorders (CMDs) from primary care records and repeated CMD questionnaire data from ALSPAC (the Avon Longitudinal Study of Parents and Children) over adolescence and young adulthood, explore factors affecting CMD identification in primary care records, and construct models predicting ALSPAC-derived CMDs using only primary care data.Design and settingProspective cohort study (ALSPAC) in Southwest England with linkage to electronic primary care records.ParticipantsPrimary care records were extracted for 11 807 participants (80% of 14 731 eligible). Between 31% (3633; age 15/16) and 11% (1298; age 21/22) of participants had both primary care and ALSPAC CMD data.Outcome measuresALSPAC outcome measures were diagnoses of suspected depression and/or CMDs. Primary care outcome measure were Read codes for diagnosis, symptoms and treatment of depression/CMDs. For each time point, sensitivities and specificities for primary care CMD diagnoses were calculated for predicting ALSPAC-derived measures of CMDs, and the factors associated with identification of primary care-based CMDs in those with suspected ALSPAC-derived CMDs explored. Lasso (least absolute selection and shrinkage operator) models were used at each time point to predict ALSPAC-derived CMDs using only primary care data, with internal validation by randomly splitting data into 60% training and 40% validation samples.ResultsSensitivities for primary care diagnoses were low for CMDs (range: 3.5%–19.1%) and depression (range: 1.6%–34.0%), while specificities were high (nearly all >95%). The strongest predictors of identification in the primary care data for those with ALSPAC-derived CMDs were symptom severity indices. The lasso models had relatively low prediction rates, especially in the validation sample (deviance ratio range: −1.3 to 12.6%), but improved with age.ConclusionsPrimary care data underestimate CMDs compared to population-based studies. Improving general practitioner identification, and using free-text or secondary care data, is needed to improve the accuracy of models using clinical data.

scholarly journals Defining adolescent common mental disorders using electronic primary care data: a comparison with outcomes measured using the CIS-R

BMJ Open ◽  
2016 ◽  
Vol 6 (12) ◽  
pp. e013167 ◽  
Author(s):  
Rosie P Cornish ◽  
Ann John ◽  
Andy Boyd ◽  
Kate Tilling ◽  
John Macleod
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Primary Care Data

scholarly journals Case definitions for common mental health disorders among adolescents using electronic primary care data: a comparison with self-reported data from ALSPAC

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Rosie Cornish ◽  
Ann John ◽  
Andy Boyd ◽  
Kate Tilling ◽  
John Macleod
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Help Seeking ◽  
Common Mental Disorders ◽  
Case Definitions ◽  
Clinical Databases ◽  
Primary Care Data ◽  
Parents And Children ◽  
Reported Data ◽  
Clinical Records

ABSTRACT ObjectivesRates of common mental disorders may be increasing among children and adolescents, though evidence of this is mixed. Symptom questionnaires in population surveys may overestimate clinical disease. Conversely, lower participation of individuals with mental disorders may lead to underestimates in surveys. Clinical databases may have greater population coverage and contain information of more obvious clinical validity; however, several factors, including the help-seeking behaviour of individuals and the recording practices of clinicians, may influence burden-of-disease estimates based on these databases. The aim of the current investigation was to compare case definitions of common mental disorders (CMD) using linked electronic primary care data to definitions derived from self-reported data obtained in an observational study. ApproachWe studied 1,562 adolescents who had completed the Revised Clinical Interview Schedule (CIS-R) in the Avon Longitudinal Study of Parents and Children (ALSPAC) at age 17-18 years and had linkage established to their electronic primary care records for at least 6 months after the time they completed the CIS-R. We used lists of Read codes corresponding to diagnoses, symptoms and treatment to create twelve definitions of CMD and also of depression alone. We calculated sensitivities and specificities of these, using CIS-R case definitions as the reference standard. All analyses were carried in Stata 13.0. ResultsSensitivities ranged from 5.2% to 24.3% for depression and from 3.8% to 19.2% for CMD. The specificities of all definitions were above 98% for depression and above 96% for CMD. For both depression and CMD, the definition that included current diagnosis, treatment or symptoms identified the highest proportion of cases. ConclusionsMost individuals meeting case definitions for CMD based on information in clinical records also met CMD case definitions based on symptoms reported in a contemporaneous survey. Conversely, many individuals identified as CMD cases based on reported symptoms had no evidence of CMD in their clinical records. A small number of individuals with CMD recorded in their clinical records had not reported symptoms of this in the survey. Overall, these data suggest that clinical databases are likely to yield underestimates of the burden of CMD in the population. Clinical records appear to yield highly valid diagnoses of common mental disorders which may be useful for studying risk factors and outcomes of these conditions. The greatest epidemiological value is likely to be obtained when the combination of information from both survey and clinical records is possible.

scholarly journals Detecting common mental disorders in primary care in India: a comparison of five screening questionnaires

2007 ◽  
Vol 38 (2) ◽  
pp. 221-228 ◽  
Author(s):  
V. Patel ◽  
R. Araya ◽  
N. Chowdhary ◽  
M. King ◽  
B. Kirkwood ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
General Health Questionnaire ◽  
Diagnostic Interview ◽  
Systematic Sampling ◽  
Health Questionnaire ◽  
Primary Care Settings ◽  
Self Reporting Questionnaire ◽  
Distress Scale

BackgroundScreening of patients for common mental disorders (CMDs) is needed in primary-care management programmes. This study aimed to compare the screening properties of five widely used questionnaires.MethodAdult attenders in five primary-care settings in India were recruited through systematic sampling. Four questionnaires were administered, in pairs, in random order to participants: the General Health Questionnaire (GHQ, 12 items); the Primary Health Questionnaire (PHQ, nine items); the Kessler Psychological Distress Scale (K10, 10 items), and from which we could extract the score of the shorter 6-item K6; and the Self-Reporting Questionnaire (SRQ, 20 items). All participants were interviewed with a structured lay diagnostic interview, the Revised Clinical Interview Schedule (CIS-R).ResultsComplete data were available for 598 participants (participation rate 99.3%). All five questionnaires showed moderate to high discriminating ability; the GHQ and SRQ showed the best results. All five showed moderate to high degrees of correlation with one another, the poorest being between the two shortest questionnaires, K6 and PHQ. All five had relatively good internal consistency. However, the positive predictive value (PPV) of the questionnaires compared with the diagnostic interview ranged from 51% to 77% at the optimal cut-off scores.ConclusionsThere is little difference in the ability of these questionnaires to identify cases accurately, but none showed high PPVs without a considerable compromise on sensitivity. Hence, the choice of an optimum cut-off score that yields the best balance between sensitivity and PPV may need to be tailored to individual settings, with a higher cut-off being recommended in resource-limited primary-care settings.

scholarly journals Latvian Family Physicians’ Experience and Attitude in Diagnosing and Managing Depression

2019 ◽  
Vol 73 (2) ◽  
pp. 164-170
Author(s):  
Vineta Viktorija Vinogradova ◽  
Jeļena Vrubļevska ◽  
Elmārs Rancāns
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Current Knowledge ◽  
Family Physicians ◽  
Research Programme ◽  
Primary Care Settings ◽  
National Research Programme ◽  
Management Approaches ◽  
Training Programmes

Abstract Depression is among the most common mental disorders in primary care. Despite high prevalence rates it remains to be under-diagnosed in primary care settings over the world. This study was aimed to identify Latvian family physicians’ (FPs) experience and attitude in diagnosing and managing depression. It was carried out within the framework of the National Research Programme BIOMEDICINE 2014–2017. After educational seminars on diagnosing and managing depression, FPs were asked to complete a structured questionnaire. In total 216 respondents were recruited. Most of the doctors, or 72.2% (n = 156), agreed with the statement that patients with depression use primary care facilities more often than other patients. More than a half of physicians, or 66.3% (n = 143) quite often asked their patients about their psycho-emotional status and 65.7% (n = 142) of clinicians thought that they can successfully assess a patient’s psychoemotional status and possible mental disorders. The majority, or 91.6 % (n = 198), supposed that routine screening for depression is necessary in Latvia. Despite the fact that a significant number, or 62.6% (n = 135) of FPs thought that their practice was well suitable for the treatment of depressive patients, half of the respondents, or 50.9% (n = 110), assessed their ability to build a trustful contact and to motivate patients for treatment as moderate. Although FPs acknowledged the importance and necessity to treat depression, current knowledge and management approaches were far from optimal. This justifies the need to provide specific training programmes for FPs.

scholarly journals O3.6. PREVALENCE OF AND RECOVERY FROM COMMON MENTAL DISORDERS INCLUDING PSYCHOTIC EXPERIENCES

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S8-S8
Author(s):  
Jesus Perez ◽  
Clare Knight ◽  
Debra A Russo ◽  
Jan Stochl ◽  
Peter B Jones
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Health Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Psychotic Experiences ◽  
Recovery Rates ◽  
Psychological Therapies ◽  
Primary Mental Health Care ◽  
Threshold Score

Abstract Background Systematic reviews indicate that approximately one third of people with at-risk mental states for psychosis (ARMS) will transition to a psychotic disorder. Research in non-specialised services, such as primary care settings, has shown that far fewer make such a conversion. Nonetheless, psychotic experiences (PE) may also be linked to common mental disorders (CMD), particularly depression and anxiety, and still predict poor outcomes. Population studies modelling the co-occurrence of CMD and PE have found an underlying unitary psychopathological factor, with PE emerging towards its more severe end. We know little about the prevalence of and recovery from PE in primary mental health care, where most CMD are treated. One example of primary mental health care setting in England is the Improving Access to Psychological Therapies (IAPT) programme (https://www.england.nhs.uk/mental-health/adults/iapt/). The IAPT programme provides evidence-based psychological therapies for mild to moderate CMD across the UK National Health Service (NHS). IAPT services adhere to current diagnostic paradigms and, therefore, do not either measure or treat PE. We aimed to establish the prevalence of PE in a large sample of patients with CMD from the IAPT programme and compare recovery rates between patients with CMD and PE (CMD-P) and those without PE. Methods We used the Community Assessment of Psychic Experiences - Positive 15-item Scale (CAPE-P15) to determine the prevalence of PE in patients with CMD receiving treatment from IAPT services across England. We employed the CAPE-P15 threshold score of 1.47, which identifies individuals with ARMS, and also a lower threshold of 1.30, chosen as within one standard error of measurement, in order to explore threshold effects in the association between PE and recovery. Patient-reported measures of depression (PHQ-9) and anxiety (GAD-7) are routinely collected in IAPT services and determine ‘caseness’ before, during and after therapy. Using recovery rates (moving from ‘caseness’ to recovery) monitored nationally in the IAPT programme, we stratified patients according to the absence and presence of PE. Multi-group growth models estimated improvement trajectories for each group. Results 2,042 patients with CMD completed the CAPE-P15. The mean age was 39.8. The overall prevalence of CMD-P was 29.68% at CAPE-P15 threshold score for ARMS, i.e. 1.47, and 48.09% at threshold score 1.30. The overall recovery rate at threshold of 1.47 was 27.87% and 36.3% at 1.30. Recovery rates for those without PE were 58.92% and 62.43% for thresholds 1.47 and 1.30, respectively. Although patients with or without PE shared similar improvement trajectories, the initial severity of patients with CMD-P impeded their likelihood of recovery during treatment. Discussion At least one in four patients receiving treatment from IAPT services in primary care experience CMD-P. This significant group of people experience a lower recovery rate, with adverse implications not only for them but also for efficiency of services. Although recovery trajectories for this group showed improvement over therapy sessions, remittance of symptoms was insufficient to meet national IAPT standards of recovery. This patient group is not well-served by current interventions in primary care. This work forms part of a nation-wide NIHR research programme (TYPPEX; https://www.nihr.ac.uk/news/innovative-mental-health-study-launchesin-eastern-region) aiming to develop innovative therapies for people with CMD-P in primary care. Preliminary results related to feasibility and effectiveness of new therapeutic approaches will also be presented.

A Proof of Concept for Assessing Emergency Room Use with Primary Care Data and Natural Language Processing

2013 ◽  
Vol 52 (01) ◽  
pp. 33-42 ◽  
Author(s):  
M.-H. Kuo ◽  
P. Gooch ◽  
J. St-Maurice
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Natural Language Processing ◽  
Natural Language ◽  
Emergency Room ◽  
Language Processing ◽  
Free Text ◽  
Proof Of Concept ◽  
Term Extraction ◽  
Primary Care Data

SummaryObjective: The objective of this study was to undertake a proof of concept that demonstrated the use of primary care data and natural language processing and term extraction to assess emergency room use. The study extracted biopsychosocial concepts from primary care free text and related them to inappropriate emergency room use through the use of odds ratios.Methods: De-identified free text notes were extracted from a primary care clinic in Guelph, Ontario and analyzed with a software toolkit that incorporated General Architecture for Text Engineering (GATE) and MetaMap components for natural language processing and term extraction.Results: Over 10 million concepts were extracted from 13,836 patient records. Codes found in at least 1% percent of the sample were regressed against inappropriate emergency room use. 77 codes fell within the realm of biopsychosocial, were very statistically significant (p < 0.001) and had an OR > 2.0. Thematically, these codes involved mental health and pain related concepts.Conclusions: Analyzed thematically, mental health issues and pain are important themes; we have concluded that pain and mental health problems are primary drivers for inappropriate emergency room use. Age and sex were not significant. This proof of concept demonstrates the feasibly of combining natural language processing and primary care data to analyze a system use question. As a first work it supports further research and could be applied to investigate other, more complex problems.

scholarly journals Who Should Play a Key Role in Preventing Common Mental Disorders that Affect Employees in the Workplace? Results of a Survey with Occupational Health Physicians, Primary Care Physicians, Psychotherapists, and Human Resource Managers

2019 ◽  
Vol 16 (8) ◽  
pp. 1383 ◽  
Author(s):  
Martina Michaelis ◽  
Elisabeth Maria Balint ◽  
Florian Junne ◽  
Stephan Zipfel ◽  
Harald Gündel ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Occupational Health ◽  
Health Professionals ◽  
Primary Care Physicians ◽  
Common Mental Disorders ◽  
Human Resource Managers ◽  
Insurance Agents ◽  
Professional Groups ◽  
Resource Managers

The rising burden of common mental disorders (CMDs) in employees requires strategies for prevention. No systematic data exist about how those involved perceive their roles, responsibilities, and interactions with other professional groups. Therefore, we performed a multi-professional standardized survey with health professionals in Germany. A self-administered questionnaire was completed by 133 occupational health physicians (OHPs), 136 primary care physicians (PCPs), 186 psychotherapists (PTs), and 172 human resource managers (HRMs). Inter alia, they were asked which health professionals working in the company health service and in the outpatient care or in the sector of statutory insurance agents should play a key role in the primary, secondary, and tertiary prevention of CMDs in employees. The McNemar test was used in order to compare the attributed roles among the professionals involved. With regard to CMDs, all the professional groups involved in this study declared OHPs as the most relevant pillar in the field of prevention. In primary prevention, HRMs regarded themselves, OHPs, and health insurance agents as equally relevant in terms of prevention. PTs indicated an important role for employee representatives in this field. In secondary prevention, PCPs were regarded as important as OHPs. HRMs indicated themselves as equally important as OHPs and PCPs. In tertiary prevention, only OHPs identified themselves as main protagonists. The other groups marked a variety of several professions. There is a common acceptance from the parties involved that might help the first steps be taken toward overcoming barriers, e.g., by developing a common framework for quality-assured intersectional cooperation in the field of CMD prevention in employees.

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