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Randomized controlled comparison of cross-sectional survey approaches to optimize follow-up completeness in clinical studies.

ABSTRACT: INTRODUCTION:In outcome research, incomplete follow-up is a major, yet potentially correctable source of bias. Cross-sectional surveys may theoretically increase completeness of follow-up, but low response rates are reported typically. We investigated whether a pre-notification letter improved patient availability for follow-up phone interviews and thereby improved cross-sectional survey yield. METHODS:A consecutive series of vascular patients was randomly divided into a trial and a validation population. The trial population was then randomized 1:1 to one of two cross-sectional contact strategies: Strategy 1 consisted of direct contact attempts by up to 12 systematically timed phone calls, whereas Strategy 2 used a personalized pre-notification letter to arrange for scheduled phone call interviews. Response rates, average time and efforts needed per patient and overall survey duration were compared. Subsequently, trial findings were externally validated in the validation population. RESULTS:Of 728 consecutive patients, 370 were allocated to the trial population. Trial patients contacted by strategy 1 (n = 183) had a similar profile when compared to trial patients contacted by strategy 2 (n = 187). Follow-up periods following surgery (54.3 versus 53.6 months) and all-cause mortality rates (21.3% versus 18.7%) were comparable between the trial groups. Cross-sectional information on survival outcomes was almost complete after both contact strategies (99.5% versus 98.9%, P = 1.0). In 144/187 strategy 2 patients (77%) interviews were scheduled successfully necessitating significantly less contact attempts (median of 1.3 versus 2.3 per patient, P<0.0001). However, invested time per patient was similar between the groups (median of 10.1 versus 9.6 minutes), and survey strategy 1 completed earlier (median time to contact 4 versus 11 days, P<0.0001). Therefore, strategy 1 was validated in the validation population (n = 358): a low lost to follow-up rate below 1% (P = 1.0) was reconfirmed necessitating an average of 2.3 contact attempts per patient. CONCLUSIONS:Both contact strategies were equally successful in contacting almost all patients cross-sectionally. If systematically timed, direct phone calls were less complicated to organize and faster completed. Given the low time and effort per patient, outcome studies should invest in systematic follow-up surveys to minimize attrition bias.

SUBMITTER: von Allmen RS

PROVIDER: S-EPMC6422260 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Randomized controlled comparison of cross-sectional survey approaches to optimize follow-up completeness in clinical studies.

von Allmen Regula S RS Tinner Christian C Schmidli Jürg J Tevaearai Hendrik T HT Dick Florian F

PloS one 20190318 3

<h4>Introduction</h4>In outcome research, incomplete follow-up is a major, yet potentially correctable source of bias. Cross-sectional surveys may theoretically increase completeness of follow-up, but low response rates are reported typically. We investigated whether a pre-notification letter improved patient availability for follow-up phone interviews and thereby improved cross-sectional survey yield.<h4>Methods</h4>A consecutive series of vascular patients was randomly divided into a trial and ...[more]

PMID: 30883589

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Project description:ObjectiveTo comprehensively update and survey the current provision of recovery, rehabilitation and follow-up services for adult critical care patients across the UK.DesignCross-sectional, self-administered, predominantly closed-question, electronic, online survey.SettingInstitutions providing adult critical care services identified from national databases.ParticipantsMultiprofessional critical care clinicians delivering services at each site.ResultsResponses from 176 UK hospital sites were included (176/242, 72.7%). Inpatient recovery and follow-up services were present at 127/176 (72.2%) sites, adopting multiple formats of delivery and primarily delivered by nurses (n=115/127, 90.6%). Outpatient services ran at 130 sites (73.9%), predominantly as outpatient clinics. Most services (n=108/130, 83.1%) were co-delivered by two or more healthcare professionals, typically nurse/intensive care unit (ICU) physician (n=29/130, 22.3%) or nurse/ICU physician/physiotherapist (n=19/130, 14.6%) teams. Clinical psychology was most frequently lacking from inpatient or outpatient services. Lack of funding was consistently the primary barrier to service provision, with other barriers including logistical and service prioritisation factors indicating that infrastructure and profile for services remain inadequate. Posthospital discharge physical rehabilitation programmes were relatively few (n=31/176, 17.6%), but peer support services were available in nearly half of responding institutions (n=85/176, 48.3%). The effects of the COVID-19 pandemic resulted in either increasing, decreasing or reformatting service provision. Future plans for long-term service transformation focus on expansion of current, and establishment of new, outpatient services.ConclusionOverall, these data demonstrate a proliferation of recovery, follow-up and rehabilitation services for critically ill adults in the past decade across the UK, although service gaps remain suggesting further work is required for guideline implementation. Findings can be used to enhance survivorship for critically ill adults, inform policymakers and commissioners, and provide comparative data and experiential insights for clinicians designing models of care in international healthcare jurisdictions.

Project description:BackgroundThe continued increase in hospital admissions is a significant and complex issue facing health services. There is little research exploring patient perspectives or examining individual admissions among patients with frequent admissions for chronic ambulatory care sensitive (ACS) conditions. This paper aims to describe characteristics of older, rural patients frequently admitted with ACS conditions and identify factors associated with their admissions from the patient perspective.MethodsPatients aged 65+ resident in North Coast NSW with three or more admissions for selected ACS chronic conditions within a 12 month period, were invited to participate in a postal survey and follow up telephone call. Survey and telephone data were linked to admission and health service program data. Descriptive statistics were generated for survey respondents; logistic regression models developed to compare characteristics of patients with 3 or with 4+ admissions; and comparisons made between survey respondents and non-respondents.ResultsSurvey respondents (n=102) had a mean age of 77.1 years (range 66-95 years), and a mean of 4.1 admissions within 12 months; 49% had at least three chronic conditions; the majority had low socioeconomic status; one in five (22%) reported some difficulty affording their medication; and 35% lived alone. The majority reported psychological distress with 31% having moderate or severe psychological distress. While all had a GP, only 38% reported having a written GP care plan. 22% of those who needed regular help with daily tasks did not have a close friend or relative who regularly cared for them. Factors independently associated with more frequent (n=4+) relative to less frequent (n=3) admissions included having congestive heart failure (p=0.003), higher social isolation scores (p=0.040) and higher Charlson Comorbidity Index scores (p=0.049). Most respondents (61%) felt there was nothing that could have avoided their most recent admission, although some potential avoidability of admission was described around medication and health behaviours. Respondents were younger and less sick than non-respondents.ConclusionsThis study provides a detailed description of older patients with multiple chronic conditions and a history of frequent admission in rural Australia. Our results suggest that programs targeting medication use, health behaviours and social isolation may help reduce multiple hospital admissions for chronic disease.

Project description:ObjectivesMethods for pharmacoepidemiologic studies of large-scale data repositories are established. Although clinical cohorts of older adults often contain critical information to advance our understanding of medication risk and benefit, the methods best suited to manage medication data in these samples are sometimes unclear and their degree of validation unknown. We sought to provide researchers, in the context of a clinical cohort study of delirium in older adults, with guidance on the methodological tools to use data from clinical cohorts to better understand medication risk factors and outcomes.DesignProspective cohort study.SettingThe Successful Aging After Elective Surgery (SAGES) prospective cohort.ParticipantsA total of 560 older adults (aged ≥70 years) without dementia undergoing elective major surgery.MeasurementsUsing the SAGES clinical cohort, methods used to characterize medications were identified, reviewed, analyzed, and distinguished by appropriateness and degree of validation for characterizing pharmacoepidemiologic data in smaller clinical data sets.ResultsMedication coding is essential; the American Hospital Formulary System, most often used in the United States, is not preferred over others. Use of equivalent dosing scales (e.g., morphine equivalents) for a single medication class (e.g., opioids) is preferred over multiclass analgesic equivalency scales. Medication aggregation from the same class (e.g., benzodiazepines) is well established; the optimal prevalence breakout for aggregation remains unclear. Validated scale(s) to combine structurally dissimilar medications (e.g., anticholinergics) should be used with caution; a lack of consensus exists regarding the optimal scale. Directed acyclic graph(s) are an accepted method to conceptualize causative frameworks when identifying potential confounders. Modeling-based strategies should be used with evidence-based, a priori variable-selection strategies.ConclusionAs highlighted in the SAGES cohort, the methods used to classify and analyze medication data in clinically rich cohort studies vary in the rigor by which they have been developed and validated.

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Randomized controlled comparison of cross-sectional survey approaches to optimize follow-up completeness in clinical studies.

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Randomized controlled comparison of cross-sectional survey approaches to optimize follow-up completeness in clinical studies.

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