GP and patient predictions of sick-listing duration: how well do they correspond? A prospective observational study

A prognostic model for predicting the duration of 20,049 sickness absence spells due to shoulder lesions in a population-based cohort in Sweden

MAIN OBJECTIVE

Sickness absence duration for shoulder lesion patients is difficult to prognosticate, and scientific evidence for the sick-listing practice is lacking. Our objective was to develop a clinically implementable prediction model for the duration of a sickness absence spell due to shoulder lesions.

METHODS

All new sickness absence spells due to shoulder lesions (ICD-10-code: M75) issued in the period January 2010-June 2012 that were longer than 14 days were identified through the nationwide sickness absence insurance register. Information on predictors was linked from four other nationwide registers. Piecewise-constant hazards regression models were fitted to predict duration of sickness absence. The model was developed and validated using split sample validation. Variable selection was based on log-likelihood loss ranking when excluding a variable from the model. The model was evaluated using calibration plots and the c-statistic.

RESULTS

20 049 sickness absence spells were identified, of which 34% lasted >90 days. Predictors included in the model were age, sex, geographical region, occupational status, educational level, birth country, specialized healthcare at start of the spell, number of sickness absence days in the last 12 months, and specialized healthcare the last 12 months, before start date of the index sickness absence spell. The model was satisfactorily specified and calibrated. Overall c-statistic was 0.54 (95% CI 0.53-0.55). C-statistic for predicting durations >90, >180, and >365 days was 0.61, 0.66, and 0.74, respectively.

SIGNIFICANCE

The model can be used to predict the duration of sickness absence due to shoulder lesions. Covariates had limited predictive power but could discriminate the very long sickness absence spells from the rest.

Factors Influencing Physician Prognosis: A Scoping Review

Introduction. Prognosis is an essential component of informed consent for medical decision making. Research shows that physicians display discrepancies in their prognostication, leading to variable, inaccurate, optimistic, or pessimistic prognosis. Factors driving these discrepancies and the supporting evidence have not been reviewed systematically. Methods. We undertook a scoping review to explore the literature on the factors leading to discrepancies in medical prognosis. We searched Medline (Ovid) and Embase (Ovid) databases for peer-reviewed articles from 1970 to 2017. We included articles that discussed prognosis variation or discrepancy and where factors influencing prognosis were evaluated. We extracted data outlining the participants, methodology, and prognosis discrepancy information and measured factors influencing prognosis. Results. Of 4,723 articles, 73 were included in the final analysis. There was significant variability in research methodologies. Most articles showed that physicians were pessimistic regarding patient outcomes, particularly in early trainees and acute care specialties. Accuracy rates were similar across all time periods. Factors influencing prognosis were clustered in 4 categories: patient-related factors (such as age, gender, race, diagnosis), physician-related factors (such as age, race, gender, specialty, training and experience, attitudes and values), clinical situation-related factors (such as physician-patient relationship, patient location, and clinical context), and environmental-related factors (such as country or hospital size). Discussion. Obtaining accurate prognostic information is one of the highest priorities for seriously ill patients. The literature shows trends toward pessimism, especially in early trainees and acute care specialties. While some factors may prove difficult to change, the physician's personality and psychology influence prognosis accuracy and could be tackled using debiasing strategies. Exposure to long-term patient outcomes and a multidisciplinary practice setting are environmental debiasing strategies that may warrant further research.

Highlights

Literature on discrepancies in physician's prognostication is heterogeneous and sparse.Literature shows that physicians are mostly pessimistic regarding patient outcomes.Literature shows that a physician's personality and psychology influence prognostic accuracy and could be improved with evidence-based debiasing strategies.Medical specialty strongly influences prognosis, with specialties exposed to acutely ill patients being more pessimistic, whereas specialties following patients longitudinally being more optimistic.Physicians early in their training were more pessimist than more experienced physicians.

Predicting the duration of sickness absence due to knee osteoarthritis: a prognostic model developed in a population-based cohort in Sweden

Background

Predicting the duration of sickness absence (SA) among sickness absent patients is a task many sickness certifying physicians as well as social insurance officers struggle with. Our aim was to develop a prediction model for prognosticating the duration of SA due to knee osteoarthritis.

Methods

A population-based prospective study of SA spells was conducted using comprehensive microdata linked from five Swedish nationwide registers. All 12,098 new SA spells > 14 days due to knee osteoarthritis in 1/1 2010 through 30/6 2012 were included for individuals 18–64 years. The data was split into a development dataset (70 %, n_spells =8468) and a validation data set (n_spells =3690) for internal validation. Piecewise-constant hazards regression was performed to prognosticate the duration of SA (overall duration and duration > 90, >180, or > 365 days). Possible predictors were selected based on the log-likelihood loss when excluding them from the model.

Results

Of all SA spells, 53 % were > 90 days and 3 % >365 days. Factors included in the final model were age, sex, geographical region, extent of sickness absence, previous sickness absence, history of specialized outpatient healthcare and/or inpatient healthcare, employment status, and educational level. The model was well calibrated. Overall, discrimination was poor (c = 0.53, 95 % confidence interval (CI) 0.52–0.54). For predicting SA > 90 days, discrimination as measured by AUC was 0.63 (95 % CI 0.61–0.65), for > 180 days, 0.69 (95 % CI 0.65–0.71), and for SA > 365 days, AUC was 0.75 (95 % CI 0.72–0.78).

Conclusion

It was possible to predict patients at risk of long-term SA (> 180 days) with acceptable precision. However, the prediction of duration of SA spells due to knee osteoarthritis has room for improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04400-8.

The experiences of care managers and rehabilitation coordinators of a primary care intervention to promote return to work for patients with common mental disorders: a qualitative study

BACKGROUND

In an earlier study, PRIM-CARE RCT, a care manager implementation at the primary care centre showed improved return to work and reduced sick leave for patients with CMD. To further improve return to work, the project Co-Work-Care added a person-centered dialogue meeting between the patient, the employer and the rehabilitation coordinator, preceded by an increased collaboration between care manager, rehabilitation coordinator and GP. In this first qualitative study of the Co-Work-Care project, we explored how care managers and rehabilitation coordinators experienced the Co-Work-Care model. The purpose of this study was to explore care managers' and rehabilitation coordinators' perceptions and experiences of a close collaboration and the use of the person-centred dialogue meeting.

METHODS

From an ongoing RCT with 20 primary care centres, care managers (CMs) (n = 13) and rehabilitation coordinators (RCs) (n = 12) participated in a qualitative study with focus groups. The study was conducted in the primary health care in a Swedish region. The data was analysed with Systematic Text Condensation by Malterud.

RESULTS

Seven codes describing the participants' experiences of the Co-Work-Care model were identified: 1) The importance of collaboration at the primary care centre, 2) Collaboration and division of roles between the RC and the CM, 3) Collaboration with the General practitioner (GP), 4) The person-centred dialogue meeting, 5) Initiating the person-centred dialogue meeting, 6) The person-centred dialogue meeting to improve collaboration with the employer, and 7) The person-centred dialogue meeting to teach about the return to work process.

CONCLUSION

The increased collaboration within the Co-Work-Care model created a common picture and understanding of the patient's situation. The person-centred dialogue meeting in the rehabilitation process became a bridge between the employer and the patient.

TRIAL REGISTRATION

NCT03250026 (registered August 15, 2017).

Influence of antidepressant therapy on sick leave in primary care: ADAS, a comparative observational study

BACKGROUND

Compared to other European countries, Sweden's yearly sick leave expenditures are moderate. Common mental disorders (CMD) are important causes of sick leave, affecting 10-15% of the adult population. A Swedish register based study indicates that antidepressant therapy for patients on long-term sick leave for CMD leads to longer sick leave and higher frequency of non-time-limited sickness compensation as compared to psychotherapy, work oriented rehabilitation, and other therapies.

AIM

To verify if patients on antidepressant therapy and on long-term sick leave for depression, anxiety and stress-related mental disorders have a longer sick leave than patients treated with other therapies.

METHOD

Prospective, observational study at 28 primary health care centers in the Region Västra Götaland, Sweden, including 192 patients on sick leave for CMD. Outcome measures were gross and net sick leave days.

INTERPRETATION

There were no significant differences in sick leave days (gross or net) due to CMD when comparing the patients treated and not treated with antidepressants during the 12 month observation period. The groups differed at baseline only concerning frequency of exhaustion disorder, with a higher frequency of exhaustion disorder in the group without antidepressants. Analysis of other possible factors associated with shorter or longer sick leave only showed associations with the patient's own perception of possibility of returning to work in near and distant future. An important factor associated with longer sick leave was the patient's own perception of possibility of return to present workplace. As CMD are important causes of sick leave and sick leave costs, this factor should be highlighted in future research on the rehabilitation process.

Reporting and prediction of work-related sickness absence by general practitioners

BACKGROUND

Information on sickness absence (SA) duration in general practice is difficult to record. The duration of absence certified by general practitioners (GPs) can be viewed as a prognosis for return to work. The Health and Occupation Research network in General Practice (THOR-GP) collects SA information from GPs associated with cases of work-related ill-health. A sample of these cases is followed up 1 year retrospectively to gather information on the duration of absence.

AIMS

To examine the extent of the underestimation of SA in routinely reported data and to investigate how well GPs predict patients' return to work.

METHODS

THOR-GPs submit case and SA information using a web-based form. GPs who submitted selected cases were asked about the total number of days of SA and whether the patient had returned to work.

RESULTS

THOR-GPs' routine SA data collection underestimated absence duration by 61%. According to the retrospective data, a much larger proportion of periods of absence due to work-related mental ill-health developed into long-term SA (60%) than episodes attributed to musculoskeletal disorders (32%). In over half the reported cases, the return to work was longer than the GP initially predicted.

CONCLUSIONS

THOR-GP prospectively reported SA data underestimated the total length of absence; however, these data can examine the episodic rates of absence within different groups. More accurate longitudinal data can be collected retrospectively. GPs' ability to predict the length of time a patient will be away from work is important to enable treatment and rehabilitation planning in order to decrease the likelihood of a patient falling into long-term SA.

Sick-listing adherence: a register study of 1.4 million episodes of sickness benefit 2010-2013 in Sweden

Background

This register study aims to increase the knowledge on how common it is that sickness benefit recipients are sick-listed for as long as their physician prescribes in their medical sickness certificate, i.e. sick-listing adherence, or wholly/partly bring return-to-work (RTW) forward, i.e. early RTW.

Methods

The unit for analysis was an episode of 100% sickness benefit, commenced between 1 January 2010 and 31 December 2013. Completed episodes of sickness benefit and full or partial early RTW was analysed by comparing the prescribed length of sick leave in medical sickness certificates and benefit days disbursed by the sickness insurance system. Probability for a full and partial early RTW was estimated with hazard ratio (HR) using the Cox proportional hazard model.

Results

In total, about 1.4 million episodes of sickness benefit (60% women) were included in the study. The overall sick-listing adherence was 84% for women and 82% for men during the first year of sick leave. Adherence varied between 82 and 87% among women and between 79 and 86% among men with regard to ICD-10 diagnosis chapter. The probability of an early RTW varied between diagnosis chapters, where mental disorders was associated with a lower probability of a full early RTW among women and men (HR 0.52 and HR 0.47) as well as a partial early RTW (HR 0.51 and HR 0.46). Younger age (16–29 years), high educational level and high income was associated with a higher probability of an early RTW, while older age (≥50 years), not native-born, low educational level, unemployment and parental leave were associated with a lower probability.

Conclusion

The study demonstrates that sick-listing adherence is relatively high. Probability of an early RTW differs with regard to diagnosis chapter, demographic, socioeconomic and labour market characteristics of the sickness benefit recipients. Interventions intended to improve the sick-listing process, and to affect the length and degree of sick leave in certain target groups, should include measures targeted at physicians’ sick-listing practices. Policies and economic incentives aimed at promoting RTW need to focus on individuals’ residual capacity for work.