Early identification of persistent somatic symptoms in primary care: data-driven and theory-driven predictive modelling based on electronic medical records of Dutch general practices

OBJECTIVE

The present study aimed to early identify patients with persistent somatic symptoms (PSS) in primary care by exploring routine care data-based approaches.

DESIGN/SETTING

A cohort study based on routine primary care data from 76 general practices in the Netherlands was executed for predictive modelling.

PARTICIPANTS

Inclusion of 94 440 adult patients was based on: at least 7-year general practice enrolment, having more than one symptom/disease registration and >10 consultations.

METHODS

Cases were selected based on the first PSS registration in 2017-2018. Candidate predictors were selected 2-5 years prior to PSS and categorised into data-driven approaches: symptoms/diseases, medications, referrals, sequential patterns and changing lab results; and theory-driven approaches: constructed factors based on literature and terminology in free text. Of these, 12 candidate predictor categories were formed and used to develop prediction models by cross-validated least absolute shrinkage and selection operator regression on 80% of the dataset. Derived models were internally validated on the remaining 20% of the dataset.

RESULTS

All models had comparable predictive values (area under the receiver operating characteristic curves=0.70 to 0.72). Predictors are related to genital complaints, specific symptoms (eg, digestive, fatigue and mood), healthcare utilisation, and number of complaints. Most fruitful predictor categories are literature-based and medications. Predictors often had overlapping constructs, such as digestive symptoms (symptom/disease codes) and drugs for anti-constipation (medication codes), indicating that registration is inconsistent between general practitioners (GPs).

CONCLUSIONS

The findings indicate low to moderate diagnostic accuracy for early identification of PSS based on routine primary care data. Nonetheless, simple clinical decision rules based on structured symptom/disease or medication codes could possibly be an efficient way to support GPs in identifying patients at risk of PSS. A full data-based prediction currently appears to be hampered by inconsistent and missing registrations. Future research on predictive modelling of PSS using routine care data should focus on data enrichment or free-text mining to overcome inconsistent registrations and improve predictive accuracy.

Fatigue after neurosurgery in patients with a brain tumor: The role of autonomic dysregulation and disturbed sleep

Background Fatigue is prevalent in patients with a brain tumor and high levels of fatigue persist after neurosurgical tumor resection. The underlying mechanisms are insufficiently understood and this study examines the role of autonomic nervous system dysregulation and objective sleep characteristics in fatigue among post-surgical patients. Methods Patients undergoing craniotomy (N = 52; age 52.1 ± 15.0 years; 44% women) were evaluated at 3 months after surgery (median = 86 days). Fatigue was measured using the Multidimensional Fatigue Inventory. Autonomic nervous system indices were based on 24-h heart rate variability (HRV) analysis. Sleep parameters were measured using actigraphy: total sleep duration, efficiency, onset latency and wake after sleep onset (WASO). Data analyses of this cross-sectional study included correlation and multiple regression analysis. Results Fatigue scores were significantly elevated in tumor resection patients compared to healthy reference norms (p's < 0.05) with no differences between patients with glioma (N = 32) versus meningioma (N = 20). Associations between HRV indices and fatigue were non-significant (r values <0.16, p values > 0.25). Sleep duration was associated with physical fatigue (r = 0.35, p = 0.02), whereas WASO was associated with mental fatigue levels (r = 0.40, p = 0.006). Disturbed sleep measures were associated with HRV indices of reduced parasympathetic nervous system activity in glioma patients but not in meningioma patients. Conclusions Multiple nocturnal awakenings may result in mental fatigue and longer sleep time was associated with physical fatigue, which may reflect compensatory sleep patterns. Future intervention studies addressing sleep quality may be beneficial in treating fatigue in patients following neurosurgery for tumor resection.

Identifying persistent somatic symptoms in electronic health records: exploring multiple theory-driven methods of identification

OBJECTIVE

Persistent somatic symptoms (PSSs) are defined as symptoms not fully explained by well-established pathophysiological mechanisms and are prevalent in up to 10% of patients in primary care. The present study aimed to explore methods to identify patients with a recognisable risk of having PSS in routine primary care data.

DESIGN

A cross-sectional study to explore four identification methods that each cover part of the broad spectrum of PSS was performed. Cases were selected based on (1) PSS-related syndrome codes, (2) PSS-related symptom codes, (3) PSS-related terminology and (4) Four-Dimensional Symptom Questionnaire scores and all methods combined.

SETTING

Coded electronic health record data were extracted from 76 general practices in the Netherlands.

PARTICIPANTS

Patients who were registered for at least 1 year during 2014-2018, were included (n=169 138).

OUTCOME MEASURES

Identification methods were explored based on (1) PSS sample sizes and demographics, (2) presence of chronic conditions and (3) healthcare utilisation (HCU) variables. Overlap between methods and practice specific differences were examined.

RESULTS

The percentage of cases identified varied between 0.3% and 7.0% across the methods. Over 58.1% of cases had chronic physical condition(s) and over 33.8% had chronic mental condition(s). HCU was generally higher for cases selected by any method compared with the total cohort. HCU was higher for method B compared with the other methods. In 26.7% of cases, cases were selected by multiple methods. Overlap between methods was low.

CONCLUSIONS

Different methods yielded different patient samples which were general practice specific. Therefore, for the most comprehensive data-based selection of PSS cases, a combination of methods A, C and D would be recommended. Advanced (data-driven) methods are needed to create a more sensitive algorithm for identifying the full spectrum of PSS. For clinical purposes, method B could possibly support screening of patients who are currently missed in daily practice.

The general practitioners perspective regarding registration of persistent somatic symptoms in primary care: a survey

Background

Persistent somatic symptoms (PSS) are common in primary care and often accompanied by an increasing disease burden for both the patient and healthcare. In medical practice, PSS is historically considered a diagnosis by exclusion or primarily seen as psychological. Besides, registration of PSS in electronic health records (EHR) is unambiguous and possibly does not reflect classification adequately. The present study explores how general practitioners (GPs) currently register PSS, and their view regarding the need for improvements in classification, registration, and consultations.

Method

Dutch GPs were invited by email to participate in a national cross-sectional online survey. The survey addressed ICPC-codes used by GPs to register PSS, PSS-related terminology added to free text areas, usage of PSS-related syndrome codes, and GPs’ need for improvement of PSS classification, registration and care.

Results

GPs (n = 259) were most likely to use codes specific to the symptom presented (89.3%). PSS-related terminology in free-text areas was used sparsely. PSS-related syndrome codes were reportedly used by 91.5% of GPs, but this was primarily the case for the code for irritable bowel syndrome. The ambiguous registration of PSS is reported as problematic by 47.9% of GPs. Over 56.7% of GPs reported needing additional training, tools or other support for PSS classification and consultation. GPs also reported needing other referral options and better guidelines.

Conclusions

Registration of PSS in primary care is currently ambiguous. Approximately half of GPs felt a need for more options for registration of PSS and reported a need for further support. In order to improve classification, registration and care for patients with PSS, there is a need for a more appropriate coding scheme and additional training.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01525-6.