Recorded quality of care for depression in general practice: an observational study

Practice list size, workforce composition and performance in English general practice: a latent profile analysis

BACKGROUND

Following government calls for General Practices in England to work at scale, some practices have grown in size from traditionally small, General Practitioner (GP)-led organisations to large multidisciplinary enterprises. We assessed the effect of practice list size and workforce composition on practice performance in clinical outcomes and patient experience.

METHODS

We linked five practice-level datasets in England to obtain a single dataset of practice workforce, list size, proportion of registered patients ≥ 65 years of age, female-male sex ratio, deprivation, rurality, GP contract type, patient experience of care, and Quality and Outcomes Framework (QOF) and non-QOF clinical processes and outcomes. Latent Profile Analysis (LPA) was used to cluster general practices into groups based on practice list size and workforce composition. Bayesian Information Criterion, Akaike Information Criterion and deliberation within the research team were used to determine the most informative number of groups. One-way ANOVA was used to assess how groups differed on indicator variables and other variables of interest. Linear regression was used to assess the association between practice group and practice performance.

RESULTS

A total of 6024 practices were available for class assignment. We determined that a 3-class grouping provided the most meaningful interpretation; 4494 (74.6%) were classified as 'Small GP-reliant practices', 1400 (23.2%) were labelled 'Medium-size GP-led practices with a multidisciplinary team (MDT) input' and 131 (2.2%) practices were named 'Large multidisciplinary practices'. Small GP-reliant practices outperformed larger multidisciplinary practices on all patient-reported indicators except on confidence and trust where medium-size GP-led practices with MDT input appeared to do better. There was no difference in performance between small GP-reliant practices and larger multidisciplinary practices on QOF incentivised indicators except on asthma reviews where medium-size GP-led practices with MDT input performed worse than smaller GP-reliant practices and immunisation coverage where the same group performed better than smaller GP-reliant practices. For non-incentivised indicators, larger multidisciplinary practices had higher cancer detection rates than small GP-reliant practices.

CONCLUSION

Small GP-reliant practices were found to provide better patient reported access, continuity of care, experience and satisfaction with care. Larger multidisciplinary practices appeared to have better cancer detection rates but had no effect on other clinical processes and outcomes. As England moves towards larger multidisciplinary practices efforts should be made to preserve good patient experience.

Care pathways for people with major depressive disorder: a European Brain Council Value of Treatment study

Background

Despite well-established guidelines for managing major depressive disorder, its extensive disability burden persists. This Value of Treatment mission from the European Brain Council aimed to elucidate the nature and extent of “gaps” between best-practice and current-practice care, specifically to:Identify current treatment gaps along the care pathway and determine the extent of these gaps in comparison with the stepped-care model and Recommend policies intending to better meet patient needs (i.e., minimize treatment gaps).

Methods

After agreement upon a set of relevant treatment gaps, data pertaining to each gap were gathered and synthesized from several sources across six European countries. Subsequently, a modified Delphi approach was undertaken to attain consensus among an expert panel on proposed recommendations for minimizing treatment gaps.

Results

Four recommendations were made to increase the depression diagnosis rate (from ~50% episodes), aiming to both increase the number of patients seeking help, and the likelihood of a practitioner to correctly detect depression. These should reduce time to treatment (from ~1 to ~8 years after illness onset) and increase rates of treatment; nine further recommendations aimed to increase rates of treatment (from ~25 to ~50% of patients currently treated), mainly focused on targeting the best treatment to each patient. To improve follow-up after treatment initiation (from ~30 to ~65% followed up within 3 months), seven recommendations focused on increasing continuity of care. For those not responding, 10 recommendations focused on ensuring access to more specialist care (currently at rates of ~5–25% of patients).

Conclusions

The treatment gaps in depression care are substantial and concerning, from the proportion of people not entering care pathways to those stagnating in primary care with impairing and persistent illness. A wide range of recommendations can be made to enhance care throughout the pathway.

How to early recognize mood disorders in primary care: A nationwide, population-based, cohort study

Background

Mood disorders are managed predominantly in primary care. However, general practitioners’ (GPs) ability to detect and diagnose patients with mood disorders is still considered unsatisfactory. The aim of the present study was to identify predictors for the early recognition of depressive disorder (DD) and bipolar disorder (BD) in general practice.

Methods

A cohort of 1,144,622 patients (605,285 women, 539,337 men) was investigated, using the Health Search IMS Health Longitudinal Patient Database. Predictors of DD or BD were identified at baseline encompassing somatization-related features, lifestyle variables, medical and psychiatric comorbidities. Patients were followed up as long as the following events occurred: diagnoses of DD or BD, death, end of the registration with the GP, end of the study period.

Results

We found an incidence rate of DD or BD of 53.61 and 1.5 per 10,000 person-years, respectively. For both the conditions, the incidence rate grew with age. Most of the lifestyle variables and medical comorbidities increased the risk of mood disorders. The strongest effect was found for migraine/headache (HR [95% CI] = 1.32 [1.26–1.38]), fatigue (1.32 [1.25–1.39]) irritable bowel syndrome (1.15 [1.08-1.23]), and pelvic inflammation disease (1.28 [1.18–1.38]).

Conclusions

Several predictors, in particular somatic symptoms, could be interpreted as an early sign of a mood disorder, and represent a valid indication for the GPs diagnostic process of mental disorders.

Equity of utilisation of cardiovascular care and mental health services in England: a cohort-based cross-sectional study using small-area estimation

Background

A strong policy emphasis on the need to reduce both health inequalities and unmet need in deprived areas has resulted in the substantial redistribution of English NHS funding towards deprived areas. This raises the question of whether or not socioeconomically disadvantaged people continue to be disadvantaged in their access to and utilisation of health care.

Objectives

To generate estimates of the prevalence of cardiovascular disease (CVD) and common mental health disorders (CMHDs) at a variety of scales, and to make these available for public use via Public Health England (PHE). To compare these estimates with utilisation of NHS services in England to establish whether inequalities of use relative to need at various stages on the health-care pathway are associated with particular sociodemographic or other factors.

Design

Cross-sectional analysis of practice-, primary care trust- and Clinical Commissioning Group-level variations in diagnosis, prescribing and specialist management of CVD and CMHDs relative to the estimated prevalence of those conditions (calculated using small-area estimation).

Results

The utilisation of CVD care appears more equitable than the utilisation of care for CMHDs. In contrast to the reviewed literature, we found little evidence of underutilisation of services by older populations. Indeed, younger populations appear to be less likely to access care for some CVD conditions. Nor did deprivation emerge as a consistent predictor of lower use relative to need for either CVD or CMHDs. Ethnicity is a consistent predictor of variations in use relative to need. Rates of primary management are lower than expected in areas with higher percentages of black populations for diabetes, stroke and CMHDs. Areas with higher Asian populations have higher-than-expected rates of diabetes presentation and prescribing and lower-than-expected rates of secondary care for diabetes. For both sets of conditions, there are pronounced geographical variations in use relative to need. For instance, the North East has relatively high levels of use of cardiac care services and rural (shire) areas have low levels of use relative to need. For CMHDs, there appears to be a pronounced ‘London effect’, with the number of people registered by general practitioners as having depression, or being prescribed antidepressants, being much lower in London than expected. A total of 24 CVD and 41 CMHD prevalence estimates have been provided to PHE and will be publicly available at a range of scales, from lower- and middle-layer super output areas through to Clinical Commissioning Groups and local authorities.

Conclusions

We found little evidence of socioeconomic inequality in use for CVD and CMHDs relative to underlying need, which suggests that the strong targeting of NHS resources to deprived areas may well have addressed longstanding concerns about unmet need. However, ethnicity has emerged as a significant predictor of inequality, and there are large and unexplained geographical variations in use relative to need for both conditions which undermine the principle of equal access to health care for equal needs. The persistence of ethnic variations and the role of systematic factors (such as rurality) in shaping patterns of utilisation deserve further investigation, as does the fact that the models were far better at explaining variation in use of CVD than mental health services.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Does practice size matter? Review of effects on quality of care in primary care

BACKGROUND

There is a trend towards consolidating smaller primary care practices into larger practices worldwide. However, the effects of practice size on quality of care remain unclear.

AIM

This review aims to systematically appraise the effects of practice size on the quality of care in primary care.

DESIGN AND SETTING

A systematic review and narrative synthesis of studies examining the relationship between practice size and quality of care in primary care.

METHOD

Quantitative studies that focused on primary care practices or practitioners were identified through PubMed, CINAHL, Embase, Cochrane Library, CRD databases, ProQuest dissertations and theses, conference proceedings, and MedNar databases, as well as the reference lists of included studies. Independent variables were team or list size; outcome variables were measures of clinical processes, clinical outcomes, or patient-reported outcomes. A narrative synthesis of the results was conducted.

RESULTS

The database search yielded 371 articles, of which 34 underwent quality assessment, and 17 articles (13 cross-sectional studies) were included. Ten studies examined the association of practice size and clinical processes, but only five found associations of larger practices with selected process measures such as higher specialist referral rates, better adherence to guidelines, higher mammography rates, and better monitoring of haemoglobin A1c. There were mixed results for cytology and pneumococcal coverage. Only one of two studies on clinical outcomes found an effect of larger practices on lower random haemoglobin A1 value. Of the three studies on patient-reported outcomes, smaller practices were consistently found to be associated with satisfaction with access, but evidence was inconsistent for other patient-reported outcomes evaluated.

CONCLUSION

There is limited evidence to support an association between practice size and quality of care in primary care.

Depression in primary care: current and future challenges

OBJECTIVES

To describe the current state of knowledge about detection and treatment of major depressive disorder (MDD) by family physicians (FPs), and to identify gaps in practice and current and future challenges.

METHODS

We reviewed the recent literature on MDD (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, or International Classification of Diseases, Revision 10) in primary care, with an emphasis on systematic reviews and meta-analyses addressing prevalence, the impact of an aging population and of chronic disease on MDD rates in primary care, detection and treatment rates by FPs, adequacy of treatment, and interventions that could improve recognition and treatment.

RESULTS

About 10% of primary care patients are likely to meet criteria for MDD. The number of cases will increase as the baby boomer cohort ages and as the prevalence of chronic disease increases. The bidirectional relation between MDD and chronic disease is now firmly established. Detection and treatment rates in primary care remain low. Treatment quality is frequently inadequate in terms of follow-up and monitoring. Formal case management and collaborative care interventions are likely to provide some benefits.

CONCLUSIONS

Low detection rates and low treatment rates need to be addressed. Planned reassessment may improve detection rates when the FP is uncertain whether MDD is present, but further research is needed to determine why FPs frequently do not initiate treatment, even when MDD is detected. A caring, attentive FP who monitors depressed patients is likely to have considerable placebo effect. Greater focus on integrated, concurrent treatment for MDD and chronic physical diseases in the middle-aged and elderly is also required.

Health care costs before and after diagnosis of depression in patients with unexplained pain: a retrospective cohort study using the United Kingdom General Practice Research Database

Purpose

To assess the impact of pain severity and time to diagnosis of depression on health care costs for primary care patients with pre-existing unexplained pain symptoms who subsequently received a diagnosis of depression.

Patients and methods

This retrospective cohort study analyzed 4000 adults with unexplained pain (defined as painful physical symptoms [PPS] without any probable organic cause) and a subsequent diagnosis of depression, identified from the UK General Practice Research Database using diagnostic codes. Patients were categorized into four groups based on pain severity (milder or more severe; based on number of pain-relief medications and use of opioids) and time to diagnosis of depression (≤1 year or>1 year from PPS index date). Annual health care costs were calculated (2009 values) and included general practitioner (GP) consultations, secondary care referrals, and prescriptions for pain-relief medications for the 12 months before depression diagnosis and in the subsequent 2 years. Multivariate models of cost included time period as a main independent variable, and adjusted for age, gender, and comorbidities.

Results

Total annual health care costs before and after depression diagnosis for the four patient groups were higher for the groups with more severe pain (£819–£988 versus £565–£628; P < 0.001 for all pairwise comparisons) and highest for the group with more severe pain and longer time to depression diagnosis in the subsequent 2 years (P < 0.05). Total GP costs were highest in the group with more severe pain and longer time to depression diagnosis both before and after depression diagnosis (P < 0.05). In the second year following depression diagnosis, this group also had the highest secondary care referral costs (P < 0.01). The highest drug costs were in the groups with more severe pain (P < 0.001), although costs within each group were similar before and after depression diagnosis.

Conclusion

Among patients with unexplained pain symptoms, significant pain in combination with longer time from pain symptoms to depression diagnosis contribute to higher costs for the UK health care system.

The Effects Of Practice Size On Quality Of Care In Primary Care Settings: A Systematic Review

BACKGROUND

There is a trend towards the consolidation of small primary care practices into larger practices, which potentially have economies of scales for employment of staff and use of information technologies. However, the effects of practice size on quality of care remain unclear.

OBJECTIVE

The objective of this review was to systematically appraise the effects of practice size on the quality of care in primary care.

INCLUSION CRITERIA

All quantitative studies that focused on primary care practices or primary care practitioners were considered. Independent variables were team size or list size; outcome variables were measures of clinical processes, clinical outcomes, or patient reported outcomes.

SEARCH STRATEGY

We searched the following databases: PubMed, CINAHL, EMBASE, Cochrane Library, CRD databases, Proquest Dissertations and Theses, Conference proceedings and Mednar from 1990 to 2010. Searches were restricted to English language. We also searched the reference lists of included studies.

METHODOLOGICAL QUALITY

Methodological quality of the studies was assessed using a modified critical appraisal checklist from the Joanna Briggs Institute. Studies that did not fulfill or were unclear in any of the following criteria were excluded: 1) independent variable measured in a reliable way; 2) outcome variables measured in a reliable way; 3) use of appropriate statistical analysis; or 4) confounding factors adjusted for in analysis.

DATA COLLECTION

Data was extracted using standardised data extraction forms from the Joanna Briggs Institute.

DATA SYNTHESIS

A narrative synthesis of the results was conducted.

RESULTS

The search yielded 371 articles. Of these, 34 articles were considered relevant and underwent quality assessment. This resulted in 17 articles (13 studies) being included in the review. All studies reviewed were cross-sectional in design. Eight examined the effects of practice size on clinical processes, one on clinical outcomes, two on patient reported outcomes, one on both clinical processes and outcomes, and one on both clinical processes and patient reported outcomes.Of the ten studies on the association between practice size and clinical processes, three found larger practices to have statistically significantly higher specialist referral rates for eating disorder (Rate ratio=1.11, 95% CI: 1.07-1.16, p<0.001), better adherence to American Academy of Pediatrics (AAP) guidelines (OR=2, 95% CI: 1.11-3.33), and better pneumococcal vaccination coverage (OR=1.45, p<0.0001). Three found statistically significant associations in only selected process measures, while four did not find any association between practice size and clinical processes. Of the latter seven studies, four may be underpowered.The two studies on clinical outcomes did not find any statistically significant association with practice size, although both studies may be underpowered. Of the three studies on patient reported outcomes, one reported statistically significant association between smaller practices and satisfaction with access, two found statistically significant associations in about half of the patient reported outcomes evaluated. However, one of the latter two studies may be underpowered.

CONCLUSIONS

There is limited evidence available to support an association between practice size and quality of care in primary care. Although some studies showed that larger practices adhered to or implemented clinical processes better than smaller practices, other studies did not find any statistical significance between practice size and other process measures. None of the studies that examined clinical outcomes found statistically significant associations with practice size. For patient reported outcomes, there was some evidence that smaller practice size was associated with better patient reported access, however the evidence for other patient reported outcomes was inconsistent.

IMPLICATIONS FOR PRACTICE

The findings of this review support the current evidence that smaller practices are comparable to larger practices in clinical performance. However, some evidence suggests that larger practices may perform better in certain process measures, while smaller practices may have better satisfaction in certain patient reported outcomes. With the trend towards larger primary care practices, there may be a trade-off between high quality clinical care and interpersonal care.

IMPLICATIONS FOR RESEARCH

Further research needs to be done to ascertain an optimal practice size for primary care to retain the benefits that small and large practices can offer. Future studies should address common methodological limitations such as the lack of power due to small sample sizes, and to account for the effects of clustering and collinearity in statistical analyses.

Primary care experience of people with long-standing psychological problems: evidence from a national survey in England

People with psychological problems face important challenges in obtaining high quality healthcare. We review evidence on the experience of primary care by people with mental health problems, including reasons why their care may be reported as worse than other groups. In the 2009 English GP Patient Survey, 5.7% of 2,163,456 respondents reported that they had a long-standing psychological or emotional condition. In an unadjusted regression model, respondents with long-standing emotional or psychological conditions rated their experiences worse than people without such problems, with scores which were up to 3 percentage points lower on individual survey items. However, after controlling for age, gender, ethnicity, deprivation and self-reported general health, people with long-standing psychological or emotional problems had slightly higher scores on 16 out of the 18 survey items, though with the equivalent of less than 2 percentage points difference for most items. Part of the reason for the difference between the adjusted and unadjusted models was the high prevalence of self-reported 'fair' or 'poor' general health among people who reported psychological problems. Overall, the results suggest that people with long-standing psychological and emotional conditions have similar experiences of English primary care compared to the rest of the population.

Screening for distress and depression in cancer settings: 10 lessons from 40 years of primary-care research

OBJECTIVE

There has been at least 40 years of active research on screening for depression and distress in primary care. Both successes and failures have been documented. The purpose of this focussed narrative review was to summarise this research and present the key lessons for clinicians and researchers working in psychosocial oncology.

METHODS

We searched for studies assessing the utility of screening in primary care in seven electronic bibliographic databases (CENTRAL, CINAHL, Embase, HMIC, Medline, PsycINFO, Web of Knowledge) from inception to December 2010. Results were reviewed and summarised into key areas.

RESULTS

We found that research could be distilled into the following key learning points. (1) Primary care is an important partner in psychosocial care. (2) Both over and under detection are problematic. (3) Barriers to identification involve patient and clinician factors. (4) Acceptability of screening is critical to implementation. (5) Underserved groups need special attention in screening. (6) Patient-clinician trust is an important modifiable variable. (7) Greater contact influences detection. (8) Clinician confidence/skills influence screening success and subsequent action. (9) Training may improve confidence but effects upon long-term outcomes are modest. (10) Screening is generally ineffective without aftercare.

CONCLUSIONS

Primary care has shown largely what does not work in relation to screening. Namely relying on clinicians' unassisted judgement without infrastructural support, using over-complex scales with low acceptability, looking for depression alone, using screening without linked treatment, treating in the absence of follow-up and failing to engage patients in their own care. These pitfalls can and should be avoided in psychosocial oncology.

Predictors of the quality of care for asthma in general practice: an observational study

BACKGROUND

Asthma is a common and important health condition in the UK, predominantly managed in primary care. Little is known about how characteristics of practices and patients are associated with achievement of quality indicators (QIs) for asthma.

OBJECTIVE

To measure the recorded quality of primary care for asthma and to assess whether quality of care differed by patient and practice characteristics.

METHODS

Medical records were examined for 253 randomly selected asthma patients from 18 general practices in England. Quality of care was assessed against seven predetermined QIs. Logistic regression models were used to test variations in quality of care by age, gender, patient postcode deprivation rank, practice size and time point.

RESULTS

There was substantial variation in achievement of individual QIs (range 39-97%). Participants whose postcodes were in the most deprived areas were more likely to be asked about difficulties sleeping [odds ratios (ORs) 1.7, 95% confidence interval (CI) 1.2-2.5] or whether asthma interfered with daily activities (OR 1.8, CI 1.2-2.7) than those from middle or least deprived postcode areas. QIs were more likely to be achieved in 2005 than 2003 (ORs 4.4, 2.4, 3.0). There were no significant differences by other characteristics.

CONCLUSIONS

Great variations exist in the quality of primary care for asthma and considerable scope for improvement. Asthma care improved over time. The preliminary findings that quality of asthma care varied with deprivation support the idea that primary care may be targeting care to those in most need. However, variations were small and only significant for two QIs.