Feasibility of Embedding a Scalable, Virtually Enabled Biorepository in the Electronic Health Record for Precision Medicine.

Importance: A cornerstone of precision medicine is the identification and use of biomarkers that help subtype patients for targeted treatment. Such an approach requires the development and subsequent interrogation of large-scale biobanks linked to well-annotated clinical data. Traditional means of creating these data-linked biobanks are costly and lengthy, especially in acute conditions that require time-sensitive clinical data and biospecimens. Objectives: To develop a virtually enabled biorepository and electronic health record (EHR)-embedded, scalable cohort for precision medicine (VESPRE) and compare the feasibility, enrollment, and costs of VESPRE with those of a traditional study design in acute care. Design, Setting, and Participants: In a prospective cohort study, the EHR-embedded screening alert was generated for 3428 patients, and 2199 patients (64%) were eligible and screened. Of these, 1027 patients (30%) were enrolled. VESPRE was developed for regulatory compliance, feasibility, internal validity, and cost in a prospective cohort of 1027 patients (aged ≥18 years) with sepsis-3 within 6 hours of presentation to the emergency department. The VESPRE infrastructure included (1) automated EHR screening, (2) remnant blood collection for creation of a virtually enabled biorepository, and (3) automated clinical data abstraction. The study was conducted at an academic institution in southwestern Pennsylvania from October 17, 2017, to June 6, 2019. Main Outcomes and Measures: Regulatory compliance, enrollment, internal validity of automated screening, biorepository acquisition, and costs. Results: Of the 1027 patients enrolled in the study, 549 were included in the proof-of-concept analysis (305 [56%] men); median (SD) age was 59 (17) years. VESPRE collected 12 963 remnant blood and urine samples and demonstrated adequate feasibility for clinical, biomarker, and microbiome analyses. Over the 20-month test, the total cost beyond the existing operations infrastructure was $39 417.50 ($14 880.00 project management, $22 717.50 laboratory supplies/staff, and $1820.00 data management)-approximately $39 per enrolled patient vs $239 per patient for a traditional cohort study. Conclusions and Relevance: Results of this study suggest that, in a large US health system that collects data using a common EHR platform and centralized laboratory system, VESPRE, a large-scale, inexpensive EHR-embedded infrastructure for precision medicine can be used. Tested in the sepsis setting, VESPRE appeared to capture a high proportion of eligible patients at low incremental cost.

Independent Registries Are Cost-Effective Tools to Provide Mandatory Postauthorization Surveillance for Orphan Medicinal Products.

OBJECTIVES: Orphan medicinal products (OMPs) often receive market authorization under conditions imposed by regulators for ongoing postauthorization surveillance (PAS) to answer questions that remain at the time of market entry. This surveillance may be provided through industry-funded registries (IFRs). Nevertheless, data in these registries may not be of sufficient quality to answer these questions and may not always be accessible for regulatory review. We propose that a mandatory independent registry is an efficient and cost-effective tool for PAS for OMPs. METHODS: Using data from the Canadian Fabry Disease Initiative, we reviewed costs per unique patient from sites participating in both the independent national registry and IFRs for Fabry disease and compared data completeness from the Canadian Fabry Disease Initiative to that in published documents from IFRs. RESULTS: The costs of data collection through the independent registry were 17% to 36% (depending on site) lower than costs to collect data in the IFRs, and completeness of data collected through the independent registry was higher than that through the IFRs. Data from the independent registry were reviewed annually to guide indications for publicly funded Fabry disease therapy. Even when enrollment ceased to be a requirement to receive therapy, 77% of patients continued to enroll in the registry, suggesting the structure was acceptable to patients. CONCLUSIONS: Independent registries are cost-effective and efficient tools and should be mandated by regulatory agencies as the preferred tool for PAS for OMPs. Countries with publicly funded health systems should consider investment in registry infrastructure for OMPs.

Completeness of open access FluNet influenza surveillance data for Pan-America in 2005-2019.

For several decades, the World Health Organization has collected, maintained, and distributed invaluable country-specific disease surveillance data that allow experts to develop new analytical tools for disease tracking and forecasting. To capture the extent of available data within these sources, we proposed a completeness metric based on the effective time series length. Using FluNet records for 29 Pan-American countries from 2005 to 2019, we explored whether completeness was associated with health expenditure indicators adjusting for surveillance system heterogeneity. We observed steady improvements in completeness by 4.2-6.3% annually, especially after the A(H1N1)-2009 pandemic, when 24 countries reached > 95% completeness. Doubling in decadal health expenditure per capita was associated with ~ 7% increase in overall completeness. The proposed metric could navigate experts in assessing open access data quality and quantity for conducting credible statistical analyses, estimating disease trends, and developing outbreak forecasting systems.

Prioritizing Additional Data Collection to Reduce Decision Uncertainty in the HIV/AIDS Response in 6 US Cities: A Value of Information Analysis.

OBJECTIVES: The ambitious goals of the US Ending the HIV Epidemic initiative will require a targeted, context-specific public health response. Model-based economic evaluation provides useful guidance for decision making while characterizing decision uncertainty. We aim to quantify the value of eliminating uncertainty about different parameters in selecting combination implementation strategies to reduce the public health burden of HIV/AIDS in 6 US cities and identify future data collection priorities. METHODS: We used a dynamic compartmental HIV transmission model developed for 6 US cities to evaluate the cost-effectiveness of a range of combination implementation strategies. Using a metamodeling approach with nonparametric and deep learning methods, we calculated the expected value of perfect information, representing the maximum value of further research to eliminate decision uncertainty, and the expected value of partial perfect information for key groups of parameters that would be collected together in practice. RESULTS: The population expected value of perfect information ranged from $59 683 (Miami) to $54 108 679 (Los Angeles). The rank ordering of expected value of partial perfect information on key groups of parameters were largely consistent across cities and highest for parameters pertaining to HIV risk behaviors, probability of HIV transmission, health service engagement, HIV-related mortality, health utility weights, and healthcare costs. Los Angeles was an exception, where parameters on retention in pre-exposure prophylaxis ranked highest in contributing to decision uncertainty. CONCLUSIONS: Funding additional data collection on HIV/AIDS may be warranted in Baltimore, Los Angeles, and New York City. Value of information analysis should be embedded into decision-making processes on funding future research and public health intervention.

Health promotion with physiolytics: What is driving people to subscribe in a data-driven health plan.

Data-driven health promotion programs and health plans try to harness the new possibilities of ubiquitous and pervasive physiolytics devices. In this paper we seek to explore what drives people to subscribe to such a data-driven health plan. Our study reveals that the decision to subscribe to a data-driven health plan is strongly influenced by the beliefs of seeing physiolytics as enabler for positive health behavior change and of perceiving health insurances as trustworthy organizations that are capable of securely and righteously manage the data collected by physiolytics.

Cost Analysis of Health Facility Electronic Integrated Disease Surveillance and Response in One District in Sierra Leone.

Global health security depends on effective surveillance systems to prevent, detect, and respond to disease threats. Real-time surveillance initiatives aim to develop electronic systems to improve reporting and analysis of disease data. Sierra Leone, with the support of Global Health Security Agenda partners, developed an electronic Integrated Disease Surveillance and Response (eIDSR) system capable of mobile reporting from health facilities. We estimated the economic costs associated with rollout of health facility eIDSR in the Western Area Rural district in Sierra Leone and projected annual direct operational costs. Cost scenarios with increased transport costs, decreased use of partner personnel, and altered cellular data costs were modeled. Cost data associated with activities were retrospectively collected and were assessed across rollout phases. Costs were organized into cost categories: personnel, office operating, transport, and capital. We estimated costs by category and phase and calculated per health facility and per capita costs. The total economic cost to roll out eIDSR to the Western Area Rural district over the 14-week period was US$64,342, a per health facility cost of $1,021. Equipment for eIDSR was the primary cost driver (45.5%), followed by personnel (35.2%). Direct rollout costs were $38,059, or 59.2% of total economic costs. The projected annual direct operational costs were $14,091, or $224 per health facility. Although eIDSR equipment costs are a large portion of total costs, annual direct operational costs are projected to be minimal once the system is implemented. Our findings can be used to make decisions about establishing and maintaining electronic, real-time surveillance in Sierra Leone and other low-resource settings.

Optimising medication data collection in a large-scale clinical trial.

OBJECTIVE: Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework. METHODS: The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding. RESULTS: Overall, 122,910 participant structured medication reports were entered using the type-to-search box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as free-text. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD $0.20 per medication for the traditional method. CONCLUSION: Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data.

The Dutch Parelsnoer Institute Cerebrovascular Disease Initiative: a retrospective study of the effects of integrating clinical care and research on costs and quality of care in patients with ischaemic stroke.

INTRODUCTION: The Dutch Parelsnoer Institute (PSI) is a collaboration between all university medical centres in which clinical data, imaging and biomaterials are prospectively and uniformly collected for research purposes. The PSI has the ambition to integrate data collected in the context of clinical care with data collected primarily for research purposes. We aimed to evaluate the effects of such integrated registration on costs, efficiency and quality of care. METHODS: We retrospectively included patients with cerebral ischaemia of the PSI Cerebrovascular Disease Consortium at two participating centres, one applying an integrated approach on registration of clinical and research data and another with a separate method of registration. We determined the effect of integrated registration on (1) costs and time efficiency using a comparative matched cohort study in 40 patients and (2) quality of the discharge letter in a retrospective cohort study of 400 patients. RESULTS: A shorter registration time (mean difference of -4.6 min, SD 4.7, p=0.001) and a higher quality score of discharge letters (mean difference of 856 points, SD 40.8, p<0.001) was shown for integrated registration compared with separate registration. Integrated registration of data of 300 patients per year would save around €700 salary costs per year. CONCLUSION: Integrated registration of clinical and research data in patients with cerebral ischaemia is associated with some decrease in salary costs, while at the same time, increased time efficiency and quality of the discharge letter are accomplished. Thus, we recommend integrated registration of clinical and research data in centres with high-volume registration only, due to the initial investments needed to adopt the registration software.

ZOO: an automatic data-collection system for high-throughput structure analysis in protein microcrystallography.

Owing to the development of brilliant microfocus beamlines, rapid-readout detectors and sample changers, protein microcrystallography is rapidly becoming a popular technique for accessing structural information from complex biological samples. However, the method is time-consuming and labor-intensive and requires technical expertise to obtain high-resolution protein crystal structures. At SPring-8, an automated data-collection system named ZOO has been developed. This system enables faster data collection, facilitates advanced data-collection and data-processing techniques, and permits the collection of higher quality data. In this paper, the key features of the functionality put in place on the SPring-8 microbeam beamline BL32XU are described and the major advantages of this system are outlined. The ZOO system will be a major driving force in the evolution of the macromolecular crystallography beamlines at SPring-8.

Implementing a Scientifically Valid, Cost-Effective, and Scalable Data Collection System at Point of Care: The Cleveland Clinic OME Cohort.

BACKGROUND: Improving outcomes after surgical procedures and determining the value of health care can be facilitated by a scientifically valid, cost-effective, and scalable data outcome collection system. We hypothesized that such a system could be constructed in orthopaedic surgery to (1) capture >95% of baseline validated patient-reported outcome measures (PROMs) for patients undergoing elective surgery, (2) capture >95% of surgeon-entered data on disease severity and treatment, and (3) be implemented as standard clinical care in daily practice. METHODS: A modified Research Electronic Data Capture (REDCap) system was developed and was implemented at the time of surgery in a prospective cohort to collect demographic data, general health PROMs, joint-specific PROMs, and disease severity and treatments from patients and surgeons. All elective knee, hip, and shoulder orthopaedic surgical procedures performed in the Cleveland Clinic system at 7 hospitals were included. RESULTS: Of 16,021 consecutive eligible patients (February 18, 2015, to July 31, 2017), 2% (320) were excluded because of language or physical barriers, and 0.6% (91) of the remaining 15,701 patients refused to participate. Of the remaining 15,610 patients, 97.4% (15,202) completed PROMs, and surgeons provided details on the disease severity and treatment for 99.9% (15,592) of the 15,610 patients. Overall, 97.3% (15,185) of the 15,610 patients had complete patient-reported and surgeon-reported baseline enrollment. The median completion time was 11.5 minutes for the patients and 1.6 minutes for the surgeons. The overall complete 1-year follow-up rate was 72.5% (9,354 of 12,896). CONCLUSIONS: A data collection system with validated measures with >97% baseline completion of PROMs and surgeon forms regarding disease severity and treatments, across elective knee, hip, and shoulder orthopaedic surgical procedures, was successfully implemented at 7 hospitals. The system is potentially scalable to the entire orthopaedic community and could serve as a template for all procedural-based specialties during routine patient care.

Evaluating the effectiveness, efficiency, cost and value of contacting study authors in a systematic review: a case study and worked example.

BACKGROUND: Studies find that identifying additional study data is possible by contacting study authors or experts. What is less certain is the time taken, costs involved and value found by using this supplementary search method. The purpose of this study is to determine the effectiveness, efficiency, cost and value of contacting study authors by e-mail, updating the evidence available for this search method. METHODS: Eighty-eight study authors, whose studies met title/abstract inclusion in a. systematic review, were contacted by e-mail. * effectiveness was assessed by comparing the number of study authors contacted. compared to the number of replies received; * efficiency was assessed by recording the time taken to contact study authors; * cost was assessed by comparing the efficiency of contacting authors with the. effectiveness; and * value was assessed by reading and comparing the published studies with the replies received to see if any unique data was identified. RESULTS: Contacting study authors took 6 h, 54 min and 25 s across 7 weeks. 38 answers (46%) were received from 83 possible contacts. Contacting study authors cost £80.33 or £2.11 per reply. We identified unique data from author replies when compared with data reported in published studies, determining this method as 'valuable'. CONCLUSIONS: Whilst our effectiveness findings differ from other studies, we believe that this study demonstrates the effectiveness of contacting study authors. By linking effectiveness to value and cost, we offer a new way to interpret the 'effectiveness' of this supplementary search method.

The Value of Further Research: The Added Value of Individual-Participant Level Data.

Judgements based on average cost-effectiveness estimates may disguise significant heterogeneity in net health outcomes. Decisions about coverage of new interventions are often more efficient when they consider between-patient heterogeneity, which is usually operationalized as different selections for different subgroups. While most model-based cost-effectiveness studies are populated with aggregated-level sub-group estimates, individual-level data are recognized as the best source of evidence to produce unbiased and efficient estimates to explore this heterogeneity. This paper extends a previously published framework to assesses the added value of having access to individual-level data, compared to using aggregate-level data only, in the absence/presence of mutually exclusive population subgroups. Supported by a case study on the cost-effectiveness of interventions to increase uptake of smoke-alarms, the extended framework provided a quantification of the benefits foregone of not using individual-level data, pointed to the optimal number of subgroups and where further research should be undertaken. Although not indicating changes in reimbursement decisions, results showed that irrespective of using aggregate or individual-level data, no substantial additional gains are obtained if more than two subgroups are taken into account. However, depending on the evidence type used, different subgroups are revealed as warranting larger research funds. The use of individual-level data, rather than aggregate, may however influence not only the extent to which an appropriate understanding of existing heterogeneity is attained, but, more importantly, it may shape approval decisions for particular population subgroups and judgements of future research.

Challenges in Collecting Big Data in A Clinical Environment with Vulnerable Population: Lessons Learned from A Study Using A Multi-modal Sensors Platform.

Agitation is one of the most common behavioural and psychological symptoms in people living with dementia (PLwD). This behaviour can cause tremendous stress and anxiety on family caregivers and healthcare providers. Direct observation of PLwD is the traditional way to measure episodes of agitation. However, this method is subjective, bias-prone and timeconsuming. Importantly, it does not predict the onset of the agitation. Therefore, there is a need to develop a continuous monitoring system that can detect and/or predict the onset of agitation. In this study, a multi-modal sensor platform with video cameras, motion and door sensors, wristbands and pressure mats were set up in a hospital-based dementia behavioural care unit to develop a predictive system to identify the onset of agitation. The research team faced several barriers in the development and initiation of the study, namely addressing concerns about the study ethics, logistics and costs of study activities, device design for PLwD and limitations of its use in the hospital. In this paper, the strategies and methodologies that were implemented to address these challenges are discussed for consideration by future researchers who will conduct similar studies in a hospital setting.

How does the cellular phone help in epidemiological surveillance? A review of the scientific literature.

BACKGROUND: In the field of epidemiological surveillance, no systematic literature review appears to exist of implemented projects using cellular phone technology. METHOD: We performed a systematic literature review using the Pubmed and Scopus databases to retrieve articles published up to December 2015. We analyzed information reported in these publications according to the mobile health (mHealth) evidence reporting and assessment (mERA) checklist, and complemented this work with specific items related to epidemiology, in order to clarify the types of results reported and summarized in this context. RESULTS: Thirty-three articles were selected and reviewed. Each article was related to a different project. Two mERA items were systematically and fully reported, while two others were never reported. Three projects were deployed in very specific zones. Most of the projects were implemented in Africa. Infectious diseases were the elements most monitored. Most projects were based on daily data collection and SMS transmission. Economic assessment was limited to SMS, mobile phone, and implementation costs. DISCUSSION-CONCLUSION: Although suitable for epidemiologic surveillance, the mERA checklist needs further interpretation. The technical and transmission modes of cellular phone use varied greatly from one study to another. No evaluation of the interoperability capabilities of cellular phones with other applications or sub-systems was possible.

Comparing time and motion methods to study personnel time in the context of a family planning supply chain intervention in Senegal.

BACKGROUND: A family planning (FP) supply chain intervention was introduced in Senegal in 2012 to reduce contraceptive stock-outs. Labour is the highest cost in low- and middle-income country supply chains. In this paper, we (1) understand time use of personnel working in the FP supply chain at health facilities in Senegal, (2) estimate the validity of self-administered timesheets (STs) relative to continuous observations (COs), and (3) describe the cost of data collection for each method. METHODS: We collected time use data for seven stockroom managers in six facilities using both ST and CO. Activities were categorized as follows: stock management associated with FP, non-FP stock management, other productive activities, non-productive activities, and waiting time. Paired t tests were used to compare the mean differences between the two methods in all categories and in productive time alone. RESULTS: Among all activities, the absolute and relative time spent on productive activities was higher when estimated by ST compared to CO. Conversely, waiting time was underestimated by STs. There was no difference in the relative time spent on non-productive activities. When comparing the distribution of the three productive activity categories, we found no evidence of a difference in relative time percentage estimates between CO and ST (FP stockroom management - 3.0%, 95% CI - 7.4 to 1.4%; non-FP stockroom management 3.4%, 95% CI - 2.8 to 9.6%; and other productive activities - 0.1%, 95% CI - 6.3 to 6.0%). Data collection costs for CO are 140% more than ST. CONCLUSION: STs were not a reliable method for measuring absolute labour time at health facilities in Senegal due to considerable underestimates of time waiting for clients. However, ST had acceptable reliability when examining distribution of productive time. Although CO provides more accurate absolute time estimates, the unit costs for data collection using this method are more than triple those for STs in Senegal.

Uncertainty in monetary cost estimates for assessing working postures using inclinometry, observation or self-report.

OBJECTIVE: To assess uncertainty in cost estimates for collecting posture data by inclinometry, observations and self-report. METHOD: In a study addressing physical workloads at a paper mill, costs were calculated for measuring postures of twenty-eight workers during three shifts. Uncertainty in costs was assessed for all three methods as the range between an assumed best case (lowest cost) and worst case (highest cost) using scenario analysis. RESULTS: The cost for observation was larger, but also more uncertain (€16506 and €89552 in the best and worst case, respectively) than that of inclinometry (€7613 - €45896). Self-report costs were both lower and less uncertain (€3743 - €23368). CONCLUSIONS: The extent of uncertainty in cost estimates implies that observation could be less expensive than inclinometry, e.g., in a scenario where experienced observers could use existing software, while inclinometers would have to be purchased. We propose adding uncertainty assessments to cost estimates when selecting a method for measuring working postures, and offer guidance in how to proceed in a specific setting.

Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets.

BACKGROUND: There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. METHODS: We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. RESULTS: We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. CONCLUSIONS: As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.