Best practices in the real-world data life cycle.

With increasing digitization of healthcare, real-world data (RWD) are available in greater quantity and scope than ever before. Since the 2016 United States 21st Century Cures Act, innovations in the RWD life cycle have taken tremendous strides forward, largely driven by demand for regulatory-grade real-world evidence from the biopharmaceutical sector. However, use cases for RWD continue to grow in number, moving beyond drug development, to population health and direct clinical applications pertinent to payors, providers, and health systems. Effective RWD utilization requires disparate data sources to be turned into high-quality datasets. To harness the potential of RWD for emerging use cases, providers and organizations must accelerate life cycle improvements that support this process. We build on examples obtained from the academic literature and author experience of data curation practices across a diverse range of sectors to describe a standardized RWD life cycle containing key steps in production of useful data for analysis and insights. We delineate best practices that will add value to current data pipelines. Seven themes are highlighted that ensure sustainability and scalability for RWD life cycles: data standards adherence, tailored quality assurance, data entry incentivization, deploying natural language processing, data platform solutions, RWD governance, and ensuring equity and representation in data.

Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study.

OBJECTIVES: To estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer. METHODS: We employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England. RESULTS: Declines in urgent referrals (median=-70.4%) and chemotherapy attendances (median=-41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=-44.5%) and chemotherapy attendances (median=-31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity. CONCLUSIONS: Dramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks.

An International Standard Set of Patient-Centered Outcome Measures After Stroke.

BACKGROUND AND PURPOSE: Value-based health care aims to bring together patients and health systems to maximize the ratio of quality over cost. To enable assessment of healthcare value in stroke management, an international standard set of patient-centered stroke outcome measures was defined for use in a variety of healthcare settings. METHODS: A modified Delphi process was implemented with an international expert panel representing patients, advocates, and clinical specialists in stroke outcomes, stroke registers, global health, epidemiology, and rehabilitation to reach consensus on the preferred outcome measures, included populations, and baseline risk adjustment variables. RESULTS: Patients presenting to a hospital with ischemic stroke or intracerebral hemorrhage were selected as the target population for these recommendations, with the inclusion of transient ischemic attacks optional. Outcome categories recommended for assessment were survival and disease control, acute complications, and patient-reported outcomes. Patient-reported outcomes proposed for assessment at 90 days were pain, mood, feeding, selfcare, mobility, communication, cognitive functioning, social participation, ability to return to usual activities, and health-related quality of life, with mobility, feeding, selfcare, and communication also collected at discharge. One instrument was able to collect most patient-reported subdomains (9/16, 56%). Minimum data collection for risk adjustment included patient demographics, premorbid functioning, stroke type and severity, vascular and systemic risk factors, and specific treatment/care-related factors. CONCLUSIONS: A consensus stroke measure Standard Set was developed as a simple, pragmatic method to increase the value of stroke care. The set should be validated in practice when used for monitoring and comparisons across different care settings.

Meeting the ambition of measuring the quality of hospitals' stroke care using routinely collected administrative data: a feasibility study.

OBJECTIVE: To examine the potential for using routinely collected administrative data to compare the quality and safety of stroke care at a hospital level, including evaluating any bias due to variations in coding practice. DESIGN: A retrospective cohort study of English hospitals' performance against six process and outcome indicators covering the acute care pathway. We used logistic regression to adjust the outcome measures for case mix. SETTING: Hospitals in England. PARTICIPANTS: Stroke patients (ICD-10 I60-I64) admitted to English National Health Service public acute hospitals between April 2009 and March 2010, accounting for 91 936 admissions. MAIN OUTCOME MEASURE: The quality and safety were measured using six indicators spanning the hospital care pathway, from timely access to brain scans to emergency readmissions following discharge after stroke. RESULTS: There were 182 occurrences of hospitals performing statistically differently from the national average at the 99.8% significance level across the six indicators. Differences in coding practice appeared to only partially explain the variation. CONCLUSIONS: Hospital administrative data provide a practical and achievable method for evaluating aspects of stroke care across the acute pathway. However, without improvements in coding and further validation, it is unclear whether the cause of the variation is the quality of care or the result of different local care pathways and data coding accuracy.

Dying for the weekend: a retrospective cohort study on the association between day of hospital presentation and the quality and safety of stroke care.

OBJECTIVE: To examine the association between day of admission and measures of the quality and safety of the care received by patients with stroke. DESIGN: Retrospective cohort study of patients admitted to hospitals with stroke (codes I60-I64 from the International Statistical Classification of Diseases and Related Health Problems, Tenth Version) from April 1, 2009, through March 31, 2010. SETTING: English National Health Service public hospitals. PATIENTS: PATIENTS during the study period accounted for 93 621 admissions. We used logistic regression to adjust the outcome measures for case mix. MAIN OUTCOME MEASURES: Quality and safety measurements using 6 indicators spanning the hospital care pathway, from timely brain scans to emergency readmissions after discharge. RESULTS: Performance across 5 of the 6 measures was significantly lower on weekends (confidence level, 99%). One of the largest disparities was seen in rates of same-day brain scans, which were 43.1% on weekends compared with 47.6% on weekdays (unadjusted odds ratio, 0.83 [95% CI, 0.81-0.86]). In particular, the rate of 7-day in-hospital mortality for Sunday admissions was 11.0% (adjusted odds ratio, 1.26 [95% CI, 1.16-1.37], with Monday used as a reference) compared with a mean of 8.9% for weekday admissions. CONCLUSIONS: Strong evidence suggests that, nationally, stroke patients admitted on weekends are less likely to receive urgent treatments and have worse outcomes across a range of indicators. Although we adjusted the results for case mix, we cannot rule out some of the effect being due to unmeasured differences in patients admitted on weekends compared with weekdays. The findings suggest that approximately 350 in-hospital deaths each year within 7 days are potentially avoidable, and an additional 650 people could be discharged to their usual place of residence within 56 days if the performance seen on weekdays was replicated on weekends.