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We lead multidisciplinary applied research and training to rethink the way health care is delivered in general practice and across the community.
Cardiovascular Disorders and Falls Among Older Adults: A Systematic Review and Meta-Analysis.
BACKGROUND: Falls are a common cause of injury, hospitalisation, functional decline, and residential care admission among older adults. Cardiovascular disorders are recognised risk factors for falls. This systematic review assesses the association between cardiovascular disorders and falls in older adults. METHODS: Systematic searches were conducted on MEDLINE and EMBASE, encompassing all literature published prior to 31/12/2022. Included studies addressed persons aged 50 years and older, and assessed the association between cardiovascular disorders and falls or the efficacy of cardiovascular based interventions to reduce falls. Two reviewers independently extracted data and assessed study quality utilising a modified Newcastle-Ottawa scale for observational studies, and the Cochrane Risk of Bias 2 tool for interventional studies. A systematic narrative analysis of all cardiovascular outcomes, and meta-analyses of unadjusted odds ratios were performed. RESULTS: 184 studies were included: 181 observational, three interventional. Several cardiovascular disorders, including stroke, coronary artery disease, valvular heart disease, arterial stiffness, arrhythmia, orthostatic hypotension, and carotid sinus hypersensitivity were consistently associated with falls. In meta-analysis of unadjusted odds ratios (ORs) the largest positive pooled associations with falls during a 12-month reporting interval were for stroke (OR: 1.90, 95% CI 1.70-2.11), peripheral arterial disease (OR: 1.82, 95% CI: 1.12-2.95), atrial fibrillation (OR: 1.52 , 95% CI: 1.27-1.82), and orthostatic hypotension (OR: 1.39, 95% CI: 1.18-1.64). CONCLUSIONS: Several cardiovascular disorders are associated with falls. These results suggest the need to incorporate cardiovascular assessments for patients with falls. This review informed the cardiovascular recommendations in the new World Guidelines for falls in older adults.
Automated virtual reality cognitive therapy versus virtual reality mental relaxation therapy for the treatment of persistent persecutory delusions in patients with psychosis (THRIVE): a parallel-group, single-blind, randomised controlled trial in England with mediation analyses
Background: Persecutory delusions are a major psychiatric problem that often do not respond sufficiently to standard pharmacological or psychological treatments. We developed a new brief automated virtual reality (VR) cognitive treatment that has the potential to be used easily in clinical services. We aimed to compare VR cognitive therapy with an alternative VR therapy (mental relaxation), with an emphasis on understanding potential mechanisms of action. Methods: THRIVE was a parallel-group, single-blind, randomised controlled trial across four UK National Health Service trusts in England. Participants were included if they were aged 16 years or older, had a persistent (at least 3 months) persecutory delusion held with at least 50% conviction, reported feeling threatened when outside with other people, and had a primary diagnosis from the referring clinical team of a non-affective psychotic disorder. We randomly assigned (1:1) patients to either THRIVE VR cognitive therapy or VR mental relaxation, using a permuted blocks algorithm with randomly varying block size, stratified by severity of delusion. Usual care continued for all participants. Each VR therapy was provided in four sessions over approximately 4 weeks, supported by an assistant psychologist or clinical psychologist. Trial assessors were masked to group allocation. Outcomes were assessed at 0, 2 (therapy mid-point), 4 (primary endpoint, end of treatment), 8, 16, and 24 weeks. The primary outcome was persecutory delusion conviction, assessed by the Psychotic Symptoms Rating Scale (PSYRATS; rated 0–100%). Outcome analyses were done in the intention-to-treat population. We assessed the treatment credibility and expectancy of the interventions and the two mechanisms (defence behaviours and safety beliefs) that the cognitive intervention was designed to target. This trial is prospectively registered with the ISRCTN registry, ISRCTN12497310. Findings: From Sept 21, 2018, to May 13, 2021 (with a pause due to COVID-19 pandemic restrictions from March 16, 2020, to Sept 14, 2020), we recruited 80 participants with persistent persecutory delusions (49 [61%] men, 31 [39%] women, with a mean age of 40 years [SD 13, range 18–73], 64 [80%] White, six [8%] Black, one [1%] Indian, three [4%] Pakistani, and six [8%] other race or ethnicity). We randomly assigned 39 (49%) participants assigned to VR cognitive therapy and 41 (51%) participants to VR mental relaxation. 33 (85%) participants who were assigned to VR cognitive therapy attended all four sessions, and 35 (85%) participants assigned to VR mental relaxation attended all four sessions. We found no significant differences between the two VR interventions in participant ratings of treatment credibility (adjusted mean difference –1·55 [95% CI –3·68 to 0·58]; p=0·15) and outcome expectancy (–0·91 [–3·42 to 1·61]; p=0·47). 77 (96%) participants provided follow-up data at the primary timepoint. Compared with VR mental relaxation, VR cognitive therapy did not lead to a greater improvement in persecutory delusions (adjusted mean difference –2·16 [–12·77 to 8·44]; p=0·69). Compared with VR mental relaxation, VR cognitive therapy did not lead to a greater reduction in use of defence behaviours (adjusted mean difference –0·71 [–4·21 to 2·79]; p=0·69) or a greater increase in belief in safety (–5·89 [–16·83 to 5·05]; p=0·29). There were 17 serious adverse events unrelated to the trial (ten events in seven participants in the VR cognitive therapy group and seven events in five participants in the VR mental relaxation group). Interpretation: The two VR interventions performed similarly, despite the fact that they had been designed to affect different mechanisms. Both interventions had high uptake rates and were associated with large improvements in persecutory delusions but it cannot be determined that the treatments accounted for the change. Immersive technologies hold promise for the treatment of severe mental health problems. However, their use will likely benefit from experimental research on the application of different therapeutic techniques and the effects on a range of potential mechanisms of action. Funding: Medical Research Council Developmental Pathway Funding Scheme and National Institute for Health and Care Research Oxford Health Biomedical Research Centre.
Plasminogen activator inhibitor-1 gene polymorphism 4G/4G genotype and lupus nephritis in Chinese patients
Background. Abnormal regulation in the coagulation and fibrinolytic system may play an important role in mediating glomerular damage in lupus nephritis. Indeed, glomerular thrombosis occurs frequently in lupus nephritis and predicts the future development of glomerular sclerosis. In the murine model of active lupus nephritis, plasminogen activator inhibitor-1 (PAI-1) gene was overexpressed throughout the kidney, both within the glomeruli and also in tubules and vessels. The level of PAI-1 expression in the tissues appeared to correlate with the progression of lupus nephritis. Recently, a single base pair insertion/deletion 4G/5G polymorphism of the PAI-1 gene has been identified and shown to alter plasma PAI-1 activity. This study was therefore conducted to determine the association of the 4G/5G polymorphism of the PAI-1 gene with the development and severity of lupus nephritis. Methods. The PAI-1 gene polymorphism of 118 systemic lupus erythematosus (SLE) patients and 103 healthy controls who were gender and age matched was determined using standard polymerase chain reaction. PAI-1 genotype results were studied in relationship to the development and severity of lupus nephritis. Results. Allele frequencies of 4G/5G allele were 0.59/0.41 in lupus patients and 0.59/0.41 in controls (P = 1.000). No significant difference was noted in the genotype distribution between SLE patients with and without nephritis. However, lupus nephritis patients with the 4G4G genotype showed significantly heavier proteinuria (5.0 vs. 3.7 g/day; P = 0.023) when compared with patients with 4G5G and 5G5G genotypes. Also, 73.3% patients with 4G4G had an activity index ≥8 versus 37.3% patients with 4G5G and 5G5G (P = 0.003). Extensive necrotizing lesions were seen in 51.7% patients with 4G4G as compared with 23.5% patients with 4G5G and 5G5G (P = 0.014). The association of the 4G4G gene polymorphism with a higher nephritis activity and more severe necrotizing lesions persisted when only class III and class IV nephritis patients were studied. On the other hand, no significant association was noted between the PAI-1 gene polymorphism and the chronicity of the nephritis. Conclusion. These findings suggest that the 4G/5G polymorphism of the PAI-1 gene is associated with the activity but not the chronicity of lupus nephritis. The presence of the 4G4G genotype does not increase the risk of developing SLE or lupus nephritis, but predicts the development of higher nephritis activity and more extensive necrotizing lesions.
Writing through Mess
This chapter includes a published version of a blog piece from the Disrupting Inequalities series, 'At the edge-lands of mental healthcare, whose vulnerability counts?' with and author’s commentary on ‘Writing Through Mess’. It argues that ‘placing’ problems and writing through their sociomaterial mess is a productive means to materialise banal inequalities. This kind of writing can arrange stories in space and time so that ethical and moral tensions within them are not resolved or tidied up, but rather held ‘in place’.
Psychometric Evaluation of the PedsQL GCS and CHU9D in Australian Children and Adolescents with Common Chronic Health Conditions.
BACKGROUND: Generic instruments such as the Pediatric Quality of Life Inventory™ v4.0 Generic Core Scales (PedsQL GCS) and Child Health Utility 9D (CHU9D) are widely used to assess health-related quality of life (HRQOL) of the general childhood population, but there is a paucity of information about their psychometric properties in children with specific health conditions. This study assessed psychometric properties, including acceptability, reliability, validity, and responsiveness, of the PedsQL GCS and the CHU9D in children and adolescents with a range of common chronic health problems. METHODS: We used data from the Longitudinal Study of Australian Children (LSAC), for children aged 10-17 years with at least one of the following six parent-reported health conditions: asthma, anxiety/depression, attention deficit hyperactivity disorder (ADHD), autism/Asperger's, epilepsy, and type 1 diabetes mellitus. The LSAC used parent proxy-reported PedsQL GCS and child self-reported CHU9D assessments. The performance of each instrument (PedsQL GCS and CHU9D) for each psychometric property (acceptability, reliability, validity, and responsiveness) was assessed against established criteria. RESULTS: The study sample included 7201 children and adolescents (mean age = 14 years; range 10.1-17.9 years; 49% female) with 15,568 longitudinal observations available for analyses. Across the six health conditions, acceptability of the PedsQL GCS was high, while acceptability for the CHU9D was mixed. Both the PedsQL GCS and CHU9D showed strong internal consistency (Cronbach's alpha range: PedsQL GCS = 0.70-0.95, CHU9D = 0.76-0.84; item-total correlations range: PedsQL GCS = 0.35-0.84, CHU9D = 0.32-0.70). However, convergent validity for both the PedsQL GCS and CHU9D was generally weak (Spearman's correlations ≤ 0.3). Known group validity was strong for the PedsQL GCS (HRQOL differences were detected for children with and without asthma, anxiety/depression, ADHD, autism/Asperger's, and epilepsy). CHU9D was only able to discriminate between children with and without anxiety/depression, ADHD, and autism/Asperger's. The responsiveness of both the PedsQL GCS and CHU9D was variable across the six conditions, and most of the estimated effect sizes were relatively small (
Uptake and adoption of the NHS App in England: an observational study.
BACKGROUND: Technological advances have led to the use of patient portals that give people digital access to their personal health information. The NHS App was launched in January 2019 as a 'front door' to digitally enabled health services. AIM: To evaluate patterns of uptake of the NHS App, subgroup differences in registration, and the impact of COVID-19. DESIGN AND SETTING: An observational study using monthly NHS App user data at general-practice level in England was conducted. METHOD: Descriptive statistics and time-series analysis explored monthly NHS App use from January 2019-May 2021. Interrupted time-series models were used to identify changes in the level and trend of use of different functionalities, before and after the first COVID-19 lockdown. Negative binomial regression assessed differences in app registration by markers of general-practice level sociodemographic variables. RESULT: Between January 2019 and May 2021, there were 8 524 882 NHS App downloads and 4 449 869 registrations, with a 4-fold increase in App downloads when the COVID Pass feature was introduced. Analyses by sociodemographic data found 25% lower registrations in the most deprived practices (P<0.001), and 44% more registrations in the largest sized practices (P<0.001). Registration rates were 36% higher in practices with the highest proportion of registered White patients (P<0.001), 23% higher in practices with the largest proportion of 15-34-year-olds (P<0.001) and 2% lower in practices with highest proportion of people with long-term care needs (P<0.001). CONCLUSION: The uptake of the NHS App substantially increased post-lockdown, most significantly after the NHS COVID Pass feature was introduced. An unequal pattern of app registration was identified, and the use of different functions varied. Further research is needed to understand these patterns of inequalities and their impact on patient experience.
Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study
Background: Analysis of circulating tumour DNA could stratify cancer risk in symptomatic patients. We aimed to evaluate the performance of a methylation-based multicancer early detection (MCED) diagnostic test in symptomatic patients referred from primary care. Methods: We did a multicentre, prospective, observational study at National Health Service (NHS) hospital sites in England and Wales. Participants aged 18 or older referred with non-specific symptoms or symptoms potentially due to gynaecological, lung, or upper or lower gastrointestinal cancers were included and gave a blood sample when they attended for urgent investigation. Participants were excluded if they had a history of or had received treatment for an invasive or haematological malignancy diagnosed within the preceding 3 years, were taking cytotoxic or demethylating agents that might interfere with the test, or had participated in another study of a GRAIL MCED test. Patients were followed until diagnostic resolution or up to 9 months. Cell-free DNA was isolated and the MCED test performed blinded to the clinical outcome. MCED predictions were compared with the diagnosis obtained by standard care to establish the primary outcomes of overall positive and negative predictive value, sensitivity, and specificity. Outcomes were assessed in participants with a valid MCED test result and diagnostic resolution. SYMPLIFY is registered with ISRCTN (ISRCTN10226380) and has completed follow-up at all sites. Findings: 6238 participants were recruited between July 7 and Nov 30, 2021, across 44 hospital sites. 387 were excluded due to staff being unable to draw blood, sample errors, participant withdrawal, or identification of ineligibility after enrolment. Of 5851 clinically evaluable participants, 376 had no MCED test result and 14 had no information as to final diagnosis, resulting in 5461 included in the final cohort for analysis with an evaluable MCED test result and diagnostic outcome (368 [6·7%] with a cancer diagnosis and 5093 [93·3%] without a cancer diagnosis). The median age of participants was 61·9 years (IQR 53·4–73·0), 3609 (66·1%) were female and 1852 (33·9%) were male. The MCED test detected a cancer signal in 323 cases, in whom 244 cancer was diagnosed, yielding a positive predictive value of 75·5% (95% CI 70·5–80·1), negative predictive value of 97·6% (97·1–98·0), sensitivity of 66·3% (61·2–71·1), and specificity of 98·4% (98·1–98·8). Sensitivity increased with increasing age and cancer stage, from 24·2% (95% CI 16·0–34·1) in stage I to 95·3% (88·5–98·7) in stage IV. For cases in which a cancer signal was detected among patients with cancer, the MCED test's prediction of the site of origin was accurate in 85·2% (95% CI 79·8–89·3) of cases. Sensitivity 80·4% (95% CI 66·1–90·6) and negative predictive value 99·1% (98·2–99·6) were highest for patients with symptoms mandating investigation for upper gastrointestinal cancer. Interpretation: This first large-scale prospective evaluation of an MCED diagnostic test in a symptomatic population demonstrates the feasibility of using an MCED test to assist clinicians with decisions regarding urgency and route of referral from primary care. Our data provide the basis for a prospective, interventional study in patients presenting to primary care with non-specific signs and symptoms. Funding: GRAIL Bio UK.
Exploring the value of in-practice point-of-care testing (POCT) for high-risk groups
BACKGROUND: Mounting evidence for poorer seroconversion and accelerating vaccine waning in clinical risk groups (CRGs) suggests that, even if vaccinated, monoclonals and antivirals may still be required. However, the efficacy of said alternatives are highly time sensitive. As such, a clinical workflow that unlocks access to these treatments in both a timely and antimicrobially-responsible manner is essential. In-practice point-of-care testing (POCT) may offer a solution to this dual challenge. AIM: The present study investigated the uptake and prescription outcomes of POCT in a past patient cohort that attended primary care with symptoms of influenza-like illness (ILI). This work extracted CRG patient data from the overall cohort with a special emphasis on the immunosuppressed. METHOD: Researchers utilised data gathered between October 2019 and March 2020 where POCT was instituted in 12 practices within the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network. Researchers subdivided full cohort data (n = 648) by CRG and, specifically, immunosuppressed status. RESULTS: Patients in CRGs constituted 24.8% of swabbed patients; the immunosuppressed constituted 1.9%. Key predictors for POCT positivity in CRG patients were similar to those of the underlying cohort. Evidence was found for increased - and sometimes inappropriate - antibiotic prescription in CRGs via inflated odds ratios (ORs) between POCT positivity and antibiotic prescribing in these patients versus the full cohort (OR 0.75, 95% confidence interval [CI] = 0.31 to 1.80, P = 0.52 versus OR 0.61, 95% CI = 0.38 to 0.99, P = 0.03). Antivirals were consistently underutilised. CONCLUSION: This work highlights the value of POCT for vulnerable patients.
Representativeness, Vaccination Uptake, and COVID-19 Clinical Outcomes 2020-2021 in the UK Oxford-Royal College of General Practitioners Research and Surveillance Network: Cohort Profile Summary
Background: The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe’s oldest sentinel systems, working with the UK Health Security Agency (UKHSA) and its predecessor bodies for 55 years. Its surveillance report now runs twice weekly, supplemented by online observatories. In addition to conducting sentinel surveillance from a nationally representative group of practices, the RSC is now also providing data for syndromic surveillance. Objective: The aim of this study was to describe the cohort profile at the start of the 2021-2022 surveillance season and recent changes to our surveillance practice. Methods: The RSC’s pseudonymized primary care data, linked to hospital and other data, are held in the Oxford-RCGP Clinical Informatics Digital Hub, a Trusted Research Environment. We describe the RSC’s cohort profile as of September 2021, divided into a Primary Care Sentinel Cohort (PCSC)—collecting virological and serological specimens—and a larger group of syndromic surveillance general practices (SSGPs). We report changes to our sampling strategy that brings the RSC into alignment with European Centre for Disease Control guidance and then compare our cohort’s sociodemographic characteristics with Office for National Statistics data. We further describe influenza and COVID-19 vaccine coverage for the 2020-2021 season (week 40 of 2020 to week 39 of 2021), with the latter differentiated by vaccine brand. Finally, we report COVID-19–related outcomes in terms of hospitalization, intensive care unit (ICU) admission, and death. Results: As a response to COVID-19, the RSC grew from just over 500 PCSC practices in 2019 to 1879 practices in 2021 (PCSC, n=938; SSGP, n=1203). This represents 28.6% of English general practices and 30.59% (17,299,780/56,550,136) of the population. In the reporting period, the PCSC collected >8000 virology and >23,000 serology samples. The RSC population was broadly representative of the national population in terms of age, gender, ethnicity, National Health Service Region, socioeconomic status, obesity, and smoking habit. The RSC captured vaccine coverage data for influenza (n=5.4 million) and COVID-19, reporting dose one (n=11.9 million), two (n=11 million), and three (n=0.4 million) for the latter as well as brand-specific uptake data (AstraZeneca vaccine, n=11.6 million; Pfizer, n=10.8 million; and Moderna, n=0.7 million). The median (IQR) number of COVID-19 hospitalizations and ICU admissions was 1181 (559-1559) and 115 (50-174) per week, respectively. Conclusions: The RSC is broadly representative of the national population; its PCSC is geographically representative and its SSGPs are newly supporting UKHSA syndromic surveillance efforts. The network captures vaccine coverage and has expanded from reporting primary care attendances to providing data on onward hospital outcomes and deaths. The challenge remains to increase virological and serological sampling to monitor the effectiveness and waning of all vaccines available in a timely manner.
Towards Equitable and Resilient Digital Primary Care Systems: An International Comparison and Insight for Moving Forward
Objective: While the COVID-19 pandemic provided a global stimulus for digital health capacity, its development has often been inequitable, short-term in planning, and lacking in health system coherence. Inclusive digital health and the development of resilient health systems are broad outcomes that require a systematic approach to achieving them. This paper from the IMIA Primary Care Informatics Working Group (WG) provides necessary first steps for the design of a digital primary care system that can support system equity and resilience. Methods: We report on digital capability and growth in maturity in four key areas: (1) Vaccination/Prevention, (2) Disease management, (3) Surveillance, and (4) Pandemic preparedness for Australia, Canada, and the United Kingdom (data from England). Our comparison looks at seasonal influenza management prior to COVID-19 (2019-20) compared to COVID-19 (winter 2020 onwards). Results: All three countries showed growth in digital maturity from the 2019-20 management of influenza to the 2020-21 year and the management of the COVID-19 pandemic. However, the degree of progress was sporadic and uneven and has led to issues of system inequity across populations. Conclusion: The opportunity to use the lessons learned from COVID-19 should not be wasted. A digital health infrastructure is not enough on its own to drive health system transformation and to achieve desired outcomes such as system equity and resilience. We must define specific measures to track the growth of digital maturity, including standardized and fit-for-context data that is shared accurately across the health and socioeconomic sectors.
Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis
Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model’s AUC was augmented from 67.26% (CI 67.25–67.28%) to 67.67% (CI 67.66–67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes.
The drivers of non-adherence to albuminuria testing guidelines and the clinical and economic impact of not identifying chronic kidney disease.
BACKGROUND: Regular monitoring is required to ensure that patients who have, or are at risk of, chronic kidney disease (CKD) receive appropriate management. Guidelines recommend regular testing of estimated glomerular filtration rate (GFR) and albuminuria. However, evidence suggests that albuminuria testing rates, specifically urine albumin-to-creatinine ratio (UACR), are suboptimal. AIM: To assess published evidence relating to the drivers of non-adherence to albuminuria testing guidelines and the impact of not identifying CKD across the course of progression. MATERIALS AND METHODS: A systematic review of five bibliographic databases was conducted, supplemented by hand searches of relevant conference abstracts. RESULTS: One study was identified that reported drivers of non-adherence to albuminuria testing guidelines. The largest barrier was the perception that testing does not impact patient management. Thirteen studies were identified that evaluated the impact of not identifying CKD patients. All included studies analyzed the effect of not identifying worsening CKD severity leading to late referral (LR). 12/13 studies reported only on clinical impact, and 1/13 reported on clinical and economic impact. LR led to higher costs and worse outcomes than early referral, including higher rates of mortality and worsened kidney replacement therapy preparation. CONCLUSION: This systematic review demonstrates a gap in evidence exploring the drivers of non-adherence to albuminuria testing guidelines and the impact of not identifying patients in the early stages of CKD. Guideline-recommended testing allows timely identification, referral, and treatment for patients with, or at risk of, CKD, providing the best chance of avoiding the worsened outcomes identified in this review.
Influence of research evidence on the use of cardiovascular clinical prediction rules in primary care: an exploratory qualitative interview study
Background: Cardiovascular clinical prediction rules (CPRs) are widely used in primary care. They accumulate research evidence through derivation, external validation, and impact studies. However, existing knowledge about the influence of research evidence on the use of CPRs is limited. Therefore, we explored how primary care clinicians’ perceptions of and experiences with research influence their use of cardiovascular CPRs. Methods: We conducted an exploratory qualitative interview study with thematic analysis. Primary care clinicians were recruited from the WWAMI (Washington, Wyoming, Alaska, Montana and Idaho) region Practice and Research Network (WPRN). We used purposeful sampling to ensure maximum variation within the participant group. Data were collected by conducting semi-structured online interviews. We analyzed data using inductive thematic analysis to identify commonalities and differences within themes. Results: Of 29 primary care clinicians who completed the questionnaire, 15 participated in the interview. We identified two main themes relating to the influence of clinicians’ perceptions of and experiences with cardiovascular CPR research on their decisions about using cardiovascular CPRs: “Seek and judge” and “be acquainted and assume.” When clinicians are familiar with, trust, and feel confident in using research evidence, they might actively search and assess the evidence, which may then influence their decisions about using cardiovascular CPRs. However, clinicians, who are unfamiliar with, distrust, or find it challenging to use research evidence, might be passively acquainted with evidence but do not make their own judgment on the trustworthiness of such evidence. Therefore, these clinicians might not rely on research evidence when making decisions about using cardiovascular CPRs. Conclusions: Clinicians’ perceptions and experiences could influence how they use research evidence in decisions about using cardiovascular CPRs. This implies, when promoting evidence-based decisions, it might be useful to target clinicians’ unfamiliarity, distrust, and challenges regarding the use of research evidence rather than focusing only on their knowledge and skills. Further, because clinicians often rely on evidence-unrelated factors, guideline developers and policymakers should recommend cardiovascular CPRs supported by high-quality evidence.