Analysis of the impact of COVID-19 on Scotland's care-homes from March 2020 to October 2021: national linked data cohort analysis.

BACKGROUND: The impact of the COVID-19 pandemic on long-term care residents remains of wide interest, but most analyses focus on the initial wave of infections. OBJECTIVE: To examine change over time in: (i) The size, duration, classification and pattern of care-home outbreaks of COVID-19 and associated mortality and (ii) characteristics associated with an outbreak. DESIGN: Retrospective observational cohort study using routinely-collected data. SETTING: All adult care-homes in Scotland (1,092 homes, 41,299 places). METHODS: Analysis was undertaken at care-home level, over three periods. Period (P)1 01/03/2020-31/08/2020; P2 01/09/2020-31/05/2021 and P3 01/06/2021-31/10/2021. Outcomes were the presence and characteristics of outbreaks and mortality within the care-home. Cluster analysis was used to compare the pattern of outbreaks. Logistic regression examined care-home characteristics associated with outbreaks. RESULTS: In total 296 (27.1%) care-homes had one outbreak, 220 (20.1%) had two, 91 (8.3%) had three, and 68 (6.2%) had four or more. There were 1,313 outbreaks involving residents: 431 outbreaks in P1, 559 in P2 and 323 in P3. The COVID-19 mortality rate per 1,000 beds fell from 45.8 in P1, to 29.3 in P2, and 3.5 in P3. Larger care-homes were much more likely to have an outbreak, but associations between size and outbreaks were weaker in later periods. CONCLUSIONS: COVID-19 mitigation measures appear to have been beneficial, although the impact on residents remained severe until early 2021. Care-home residents, staff, relatives and providers are critical groups for consideration and involvement in future pandemic planning.

The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: A cross-sectional study using a large, primary care population dataset.

BACKGROUND: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. METHODS AND FINDINGS: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of "comorbidity." Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. CONCLUSIONS: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence.

Optimizing communication strategies and designing a comprehensive program to facilitate cascade testing for familial hypercholesterolemia.

BACKGROUND: This project aimed to optimize communication strategies to support family communication about familial hypercholesterolemia (FH) and improve cascade testing uptake among at-risk relatives. Individuals and families with FH provided feedback on multiple strategies including: a family letter, digital tools, and direct contact. METHODS: Feedback from participants was collected via dyadic interviews (n = 11) and surveys (n = 98) on communication strategies and their proposed implementation to improve cascade testing uptake. We conducted a thematic analysis to identify how to optimize each strategy. We categorized optimizations and their implementation within the project's healthcare system using a Traffic Light approach. RESULTS: Thematic analysis resulted in four distinct suggested optimizations for each communication strategy and seven suggested optimizations that were suitable across all strategies. Four suggestions for developing a comprehensive cascade testing program, which would offer all optimized communication strategies also emerged. All optimized suggestions coded green (n = 21) were incorporated. Suggestions coded yellow (n = 12) were partially incorporated. Only two suggestions were coded red and could not be incorporated. CONCLUSIONS: This project demonstrates how to collect and analyze stakeholder feedback for program design. We identified feasible suggested optimizations, resulting in communication strategies that are patient-informed and patient-centered. Optimized strategies were implemented in a comprehensive cascade testing program.

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis.

BACKGROUND: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised. AIM: To examine variation in prevalence using different definitions of multimorbidity. DESIGN AND SETTING: Cross-sectional study of 1 168 620 people in England. METHOD: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions. RESULTS: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM. CONCLUSION: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

Derivation and validation of the CFracture competing risk fracture prediction tool compared with QFracture in older people and people with comorbidity: a population cohort study.

BACKGROUND: UK guidelines recommend the QFracture tool to predict the risk of major osteoporotic fracture and hip fracture, but QFracture calibration is poor, partly because it does not account for competing mortality risk. The aim of this study was to derive and validate a competing risk model to predict major osteoporotic fracture and hip fracture (CFracture) and compare its performance with that of QFracture in UK primary care. METHODS: We used UK linked primary care data from the Clinical Practice Research Datalink GOLD database to identify people aged 30-99 years, split into derivation and validation cohorts. In the derivation cohort, we derived models (CFracture) using the same covariates as QFracture with Fine-Gray competing risk modelling, and included the Charlson Comorbidity Index score as an additional predictor of non-fracture death. In a separate validation cohort, we examined discrimination (using Harrell's C-statistic) and calibration of CFracture compared with QFracture. Reclassification analysis examined differences in the characteristics of patients reclassified as higher risk by CFracture but not by QFracture. FINDINGS: The derivation cohort included 1 831 606 women and 1 789 820 men, and the validation cohort included 915 803 women and 894 910 men. Overall discrimination of CFracture was excellent (C-statistic=0·813 [95% CI 0·810-0·816] for major osteoporotic fracture and 0·914 [0·908-0·919] for hip fracture in women; 0·734 [0·729-0·740] for major osteoporotic fracture and 0·886 [0·877-0·895] for hip fracture in men) and was similar to QFracture. CFracture calibration overall and in people younger than 75 years was generally excellent. CFracture overpredicted major osteoporotic fracture and hip fracture in older people and people with comorbidity, but was better calibrated than QFracture. Patients classified as high-risk by CFracture but not by QFracture had a higher prevalence of current smoking and previous fracture, but lower prevalence of dementia, cancer, cardiovascular disease, renal disease, and diabetes. INTERPRETATION: CFracture has similar discrimination to QFracture but is better calibrated overall and in younger people. Both models performed poorly in adults aged 85 years and older. Competing risk models should be recommended for fracture risk prediction to guide treatment recommendations. FUNDING: National Institute for Health and Care Research, Wellcome Trust, Health Data Research UK.

Adjustment for survey non-participation using record linkage and multiple imputation: A validity assessment exercise using the Health 2000 survey.

AIMS: It is becoming increasingly possible to obtain additional information about health survey participants, though not usually non-participants, via record linkage. We aimed to assess the validity of an assumption underpinning a method developed to mitigate non-participation bias. We use a survey in Finland where it is possible to link both participants and non-participants to administrative registers. Survey-derived alcohol consumption is used as the exemplar outcome. METHODS: Data on participants (85.5%) and true non-participants of the Finnish Health 2000 survey (invited survey sample N=7167 aged 30-79 years) and a contemporaneous register-based population sample (N=496,079) were individually linked to alcohol-related hospitalisation and death records. Applying the methodology to create synthetic observations on non-participants, we created 'inferred samples' (participants and inferred non-participants). Relative differences (RDs) between the inferred sample and the invited survey sample were estimated overall and by education. Five per cent limits were used to define acceptable RDs. RESULTS: Average weekly consumption estimates for men were 129 g and 131 g of alcohol in inferred and invited survey samples, respectively (RD -1.6%; 95% confidence interval (CI) -2.2 to -0.04%) and 35 g for women in both samples (RD -1.1%; 95% CI -2.4 to -0.8%). Estimates for men with secondary levels of education had the greatest RD (-2.4%; 95% CI -3.7 to -1.1%). CONCLUSIONS: The sufficiently small RDs between inferred and invited survey samples support the assumption validity and use of our methodology for adjusting for non-participation. However, the presence of some significant differences means caution is required.

Unscheduled care pathways in patients with myocardial infarction in Scotland.

OBJECTIVE: Treatment of acute myocardial infarction (MI) requires rapid transfer of people with chest pain to hospital, however, unscheduled care pathways vary in their directness (the minimal number of contacts to hospital admission). The aim was to examine unscheduled care pathways and the associations with mortality in people admitted with MI. METHODS: Retrospective population study of all people admitted to Scottish hospitals with a diagnosis of MI between 1 January 2015 and 31 December 2017. Linked data for all National Health Service Scotland unscheduled care services (NHS24 telephone triage service, primary care out of hours, ambulance, emergency department (ED)) was used to define continuous unscheduled care pathways (pathways), which were categorised by initial contact, and whether they were 'direct' (had minimum number of contacts between first contact and admission). Analysis estimated ORs and 95% CIs in adjusted models in which all covariates were included. RESULTS: 26 325 people admitted with MI (63.1% men, 61.6% aged 65+ years), of whom 5.6% died from coronary heart disease within 28 days. For 47.0%, the first unscheduled care contact was ambulance, 23.3% attended ED directly and 18.7% called telephone triage. 92.1% of pathways were direct. Pathways starting with telephone triage were more likely to be indirect compared with other initial contacts (adjusted OR (aOR) 1.97, 95% CI 1.61 to 2.40). Compared to direct pathways, indirect pathways starting with telephone triage were associated with higher mortality (aOR 1.97, 95% CI 1.61 to 2.40) as were indirect pathways starting with another service (aOR 1.55, 95% CI 1.19 to 2.01), but not direct pathways starting with telephone triage (aOR 0.87, 95% CI 0.74 to 1.02). CONCLUSION: Unscheduled care pathways leading to admission with MI in Scotland are usually direct, but those starting with telephone triage were more commonly indirect. Those indirect pathways were associated with higher mortality.

Motivating cascade testing for familial hypercholesterolemia: applying the extended parallel process model for clinician communication.

Motivating at-risk relatives to undergo cascade testing for familial hypercholesterolemia (FH) is critical for diagnosis and lifesaving treatment. As credible sources of information, clinicians can assist in family communication about FH and motivate cascade testing uptake. However, there are no guidelines regarding how clinicians should effectively communicate with probands (the first person diagnosed in the family) and at-risk relatives. Individuals and families with FH can inform our understanding of the most effective communications to promote cascade testing. Guided by the extended parallel process model (EPPM), we analyzed the perspectives of individuals and families with FH for effective messaging clinicians can use to promote cascade testing uptake. We analyzed narrative data from interviews and surveys collected as part of a larger mixed-methods study. The EPPM was used to identify message features recommended by individuals and families with FH that focus on four key constructs (severity, susceptibility, response efficacy, self-efficacy) to promote cascade testing. Participants included 22 individuals from 11 dyadic interviews and 98 survey respondents. Participants described prioritizing multiple messages that address each EPPM construct to alert relatives about their risk. They illustrated strategies clinicians could use within each EPPM construct to communicate to at-risk relatives about the importance of pursuing diagnosis via cascade testing and subsequent treatment for high cholesterol due to FH. Findings provide guidance on effective messaging to motivate cascade testing uptake for FH and demonstrates how the EPPM may guide communication with at-risk relatives about genetic risk and motivate cascade testing broadly.

Socio-economic inequalities in rates of amenable mortality in Scotland: Analyses of the fundamental causes using the Scottish Longitudinal Study, 1991-2010.

Socio-economic inequalities in amenable mortality rates are increasing across Europe, which is an affront to universal healthcare systems where the numbers of, and inequalities in, amenable deaths should be minimal and declining over time. However, the fundamental causes theory proposes that inequalities in health will be largest across preventable causes, where unequally distributed resources can be used to gain an advantage. Information on individual-level inequalities that may better reflect the fundamental causes remains limited. We used the Scottish Longitudinal Study, with follow-up to 2010 to examine trends in amenable mortality by a range of socioeconomic position measures. Large inequalities were found for all measures of socioeconomic position and were lowest for educational attainment, higher for social class and highest for social connection. To reduce inequalities, amenable mortality needs to be interpreted both as an indicator of healthcare quality and as a reflection of the unequal distribution of socio-economic resources.

Effect of competing mortality risks on predictive performance of the QFracture risk prediction tool for major osteoporotic fracture and hip fracture: external validation cohort study in a UK primary care population.

Objective: To externally evaluate the QFracture risk prediction tool for predicting the risk of major osteoporotic fracture and hip fracture. Design: External validation cohort study. Setting: UK primary care population. Linked general practice (Clinical Practice Research Datalink (CPRD) Gold), mortality registration (Office of National Statistics), and hospital inpatient (Hospital Episode Statistics) data, from 1 January 2004 to 31 March 2016. Participants: 2 747 409 women and 2 684 730 men, aged 30-99 years, with up-to-standard linked data that had passed CPRD checks for at least one year. Main outcome measures: Two outcomes were modelled based on the QFracture: major osteoporotic fracture and hip fracture. Major osteoporotic fracture was defined as any hip, distal forearm, proximal humerus, or vertebral crush fracture, from general practice, hospital discharge, and mortality data. The QFracture 10 year predicted risk of major osteoporotic fracture and hip fracture was calculated, and performance evaluated versus observed 10 year risk of fracture in the whole population, and in subgroups based on age and comorbidity. QFracture calibration was examined accounting for, and not accounting for, competing risk of mortality from causes other than the major osteoporotic fracture. Results: 2 747 409 women with 95 598 major osteoporotic fractures and 36 400 hip fractures, and 2 684 730 men with 34 321 major osteoporotic fractures and 13 379 hip fractures were included in the analysis. The incidence of all fractures was higher than in the QFracture internal derivation. Competing risk of mortality was more common than fracture from middle age onwards. QFracture discrimination in the whole population was excellent or good for major osteoporotic fracture and hip fracture (Harrell's C statistic in women 0.813 and 0.918, and 0.738 and 0.888 in men, respectively), but was poor to moderate in age subgroups (eg, Harrell's C statistic in women and men aged 85-99 years was 0.576 and 0.624 for major osteoporotic fractures, and 0.601 and 0.637 for hip fractures, respectively). Without accounting for competing risks, QFracture systematically under-predicted the risk of fracture in all models, and more so for major osteoporotic fracture than for hip fracture, and more so in older people. Accounting for competing risks, QFracture still under-predicted the risk of fracture in the whole population, but over-prediction was considerable in older age groups and in people with high comorbidities at high risk of fracture. Conclusions: The QFracture risk prediction tool systematically under-predicted the risk of fracture (because of incomplete determination of fracture rates) and over-predicted the risk in older people and in those with more comorbidities (because of competing mortality). The use of QFracture in its current form needs to be reviewed, particularly in people at high risk of death from other causes.

Telephone triage of young adults with chest pain: population analysis of NHS24 calls in Scottish unscheduled care.

BACKGROUND: Telephone triage is increasingly used to manage unscheduled care demand. Younger adults are frequent users, and commonly call with chest pain. We compared pathways of care in younger adults calling with chest pain, and associations of patient characteristics and telephone triage recommendation with hospital admission. METHODS: A retrospective study of all triage calls with chest pain to NHS24 advice line by people aged 15-34 years between 1 January 2015 and 31 December 2017 where chest pain was recorded as the call reason. Recommended outcome and subsequent use of services were determined using the continuous urgent care pathways (CUPs) database which records single episodes of care spanning multiple services. We determined the number of services involved, the proportion of patients with inpatient admission, those with an admission for an 'acute-and-serious' diagnosis, and the association between the triage call recommendation and these outcomes. RESULTS: There were 102 822 CUPs identified, with 1251 different combinations of services. The most common pathway was an NHS24 call then attendance at a primary care out-of-hours (PCOOH) centre, accounting for 38 643 (37.6%) CUPs. 9060 (8.8%) CUPs ended with hospital admission, 3030 (3.0%) the result of an 'acute-and-serious' diagnosis. 8453 (8.2%) were given 'self-care' advice and not referred further, while 46.9% ended at PCOOH and 15.2% at ED. 'Asthma, unspecified' was the most frequent 'acute-and-serious' diagnosis. Compared with people given self-care advice, referral to other services had increased odds of inpatient admission (adjusted OR (aOR) for ambulance called 28.7, 95% CI 22.6 to 36.3; for 1-hour in-home general practitioner (GP) visit arranged aOR 36.8, 95% CI 23.2 to 58.5) and for admission with an 'acute-and-serious' diagnosis (aOR ambulance called 23.9, 95% CI 16.2 to 35.4; aOR 1-hour GP visit 48.3, 95% CI 25.5 to 91.6). CONCLUSION: Chest pain triage by NHS24 appears safe, but care pathways can involve multiple service contacts. While acuity assigned to the call is strongly related to the odds of hospital admission and odds of an 'acute-and-serious' diagnosis, 'overtriage' means few patients are directed to self-care advice.

Care-home outbreaks of COVID-19 in Scotland March to May 2020: National linked data cohort analysis.

BACKGROUND: understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents. OBJECTIVE: to describe all outbreaks of COVID-19 infection in Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up to 30/06/2020. DESIGN AND SETTING: National linked data cohort analysis of Scottish care-homes for older people. METHODS: data linkage was used to identify outbreaks of COVID-19 in care-homes. Care-home characteristics associated with the presence of an outbreak were examined using logistic regression. Size of outbreaks was modelled using negative binomial regression. RESULTS: 334 (41%) Scottish care-homes for older people experienced an outbreak, with heterogeneity in outbreak size (1-63 cases; median = 6) and duration (1-94 days, median = 31.5 days). Four distinct patterns of outbreak were identified: 'typical' (38% of outbreaks, mean 11.2 cases and 48 days duration), severe (11%, mean 29.7 cases and 60 days), contained (37%, mean 3.5 cases and 13 days) and late-onset (14%, mean 5.4 cases and 17 days). Risk of a COVID-19 outbreak increased with increasing care-home size (for ≥90 beds vs <20, adjusted OR = 55.4, 95% CI 15.0-251.7) and rising community prevalence (OR = 1.2 [1.0-1.4] per 100 cases/100,000 population increase). No routinely available care-home characteristic was associated with outbreak size. CONCLUSIONS: reducing community prevalence of COVID-19 infection is essential to protect those living in care-homes. More systematic national data collection to understand care-home residents and the homes in which they live is a priority in ensuring we can respond more effectively in future.

Clinical Findings and Diagnostic Yield of Arrhythmogenic Cardiomyopathy Through Genomic Screening of Pathogenic or Likely Pathogenic Desmosome Gene Variants.

BACKGROUND: Genomic screening holds great promise for presymptomatic identification of hidden disease, and prevention of dramatic events, including sudden cardiac death associated with arrhythmogenic cardiomyopathy (ACM). Herein, we present findings from clinical follow-up of carriers of ACM-associated pathogenic/likely pathogenic desmosome variants ascertained through genomic screening. METHODS: Of 64 548 eligible participants in Geisinger MyCode Genomic Screening and Counseling program (2015-present), 92 individuals (0.14%) identified with pathogenic/likely pathogenic desmosome variants by clinical laboratory testing were referred for evaluation. We reviewed preresult medical history, patient-reported family history, and diagnostic testing results to assess both arrhythmogenic right ventricular cardiomyopathy and left-dominant ACM. RESULTS: One carrier had a prior diagnosis of dilated cardiomyopathy with arrhythmia; no other related diagnoses or diagnostic family history criteria were reported. Fifty-nine carriers (64%) had diagnostic testing in follow-up. Excluding the variant, 21/59 carriers satisfied at least one arrhythmogenic right ventricular cardiomyopathy task force criterion, 11 (52%) of whom harbored DSP variants, but only 5 exhibited multiple criteria. Six (10%) carriers demonstrated evidence of left-dominant ACM, including high rates of atypical late gadolinium enhancement by magnetic resonance imaging and nonsustained ventricular tachycardia. Two individuals received new cardiomyopathy diagnoses and received defibrillators for primary prevention. CONCLUSIONS: Genomic screening for pathogenic/likely pathogenic variants in desmosome genes can uncover both left- and right-dominant ACM. Findings of overt cardiomyopathy were limited but were most common in DSP-variant carriers and notably absent in PKP2-variant carriers. Consideration of the pathogenic/likely pathogenic variant as a major criterion for diagnosis is inappropriate in the setting of genomic screening.

Evaluation of a multidisciplinary lipid clinic to improve the care of individuals with severe lipid conditions: a RE-AIM framework analysis.

BACKGROUND: Individuals with complex dyslipidemia, or those with medication intolerance, are often difficult to manage in primary care. They require the additional attention, expertise, and adherence counseling that occurs in multidisciplinary lipid clinics (MDLCs). We conducted a program evaluation of the first year of a newly implemented MDLC utilizing the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework to provide empirical data not only on program effectiveness, but also on components important to local sustainability and future generalizability. METHODS: The purpose of the MDLC is to increase the uptake of guideline-based care for lipid conditions. Established in 2019, the MDLC provides care via a centralized clinic location within the healthcare system. Primary care providers and cardiologists were invited to refer individuals with lipid conditions. Using a pre/post-study design, we evaluated the implementation outcomes from the MDLC using the RE-AIM framework. RESULTS: In 2019, 420 referrals were made to the MDLC (reach). Referrals were made by 19% (148) of the 796 active cardiology and primary care providers, with an average of 35 patient referrals per month in 2019 (SD 12) (adoption). The MDLC saw 83 patients in 2019 (reach). Additionally, 50% (41/82) had at least one follow-up MDLC visit, and 12% (10/82) had two or more follow-up visits in 2019 (implementation). In patients seen by the MDLC, we found an improved diagnosis of specific lipid conditions (FH (familial hypercholesterolemia), hypertriglyceridemia, and dyslipidemia), increased prescribing of evidence-based therapies, high rates of medication prior authorization approvals, and significant reductions in lipid levels by lipid condition subgroup (effectiveness). Over time, the operations team decided to transition from in-person follow-up to telehealth appointments to increase capacity and sustain the clinic (maintenance). CONCLUSIONS: Despite limited reach and adoption of the MDLC, we found a large intervention effect that included improved diagnosis, increased prescribing of guideline-recommended treatments, and clinically significant reduction of lipid levels. Attention to factors including solutions to decrease the large burden of unseen referrals, discussion of the appropriate number and duration of visits, and sustainability of the clinic model could aid in enhancing the success of the MDLC and improving outcomes for more patients throughout the system.

Developing and Optimizing Innovative Tools to Address Familial Hypercholesterolemia Underdiagnosis: Identification Methods, Patient Activation, and Cascade Testing for Familial Hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. METHODS AND RESULTS: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. CONCLUSIONS: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.

Alcohol-related Outcomes and All-cause Mortality in the Health 2000 Survey by Participation Status and Compared with the Finnish Population.

BACKGROUND: In the context of declining levels of participation, understanding differences between participants and non-participants in health surveys is increasingly important for reliable measurement of health-related behaviors and their social differentials. This study compared participants and non-participants of the Finnish Health 2000 survey, and participants and a representative sample of the target population, in terms of alcohol-related harms (hospitalizations and deaths) and all-cause mortality. METHODS: We individually linked 6,127 survey participants and 1,040 non-participants, aged 30-79, and a register-based population sample (n = 496,079) to 12 years of subsequent administrative hospital discharge and mortality data. We estimated age-standardized rates and rate ratios for each outcome for non-participants and the population sample relative to participants with and without sampling weights by sex and educational attainment. RESULTS: Harms and mortality were higher in non-participants, relative to participants for both men (rate ratios = 1.5 [95% confidence interval = 1.2, 1.9] for harms; 1.6 [1.3, 2.0] for mortality) and women (2.7 [1.6, 4.4] harms; 1.7 [1.4, 2.0] mortality). Non-participation bias in harms estimates in women increased with education and in all-cause mortality overall. Age-adjusted comparisons between the population sample and sampling weighted participants were inconclusive for differences by sex; however, there were some large differences by educational attainment level. CONCLUSIONS: Rates of harms and mortality in non-participants exceed those in participants. Weighted participants' rates reflected those in the population well by age and sex, but insufficiently by educational attainment. Despite relatively high participation levels (85%), social differentiating factors and levels of harm and mortality were underestimated in the participants.

Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper.

INTRODUCTION: Decreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus. METHODS AND ANALYSIS: We made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology's performance. ETHICS AND DISSEMINATION: Ethical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations.