Systematic review of performance-enhancing health worker supervision approaches in low- and middle-income countries

Background The strength of a health system—and ultimately the health of a population—depends to a large degree on health worker performance. However, insufficient support to build, manage and optimize human resources for health (HRH) in low- and middle-income countries (LMICs) results in inadequate health workforce performance, perpetuating health inequities and low-quality health services. Methods The USAID-funded Human Resources for Health in 2030 Program (HRH2030) conducted a systematic review of studies documenting supervision enhancements and approaches that improved health worker performance to highlight components associated with these interventions’ effectiveness. Structured by a conceptual framework to classify the inputs, processes, and results, the review assessed 57 supervision studies since 2010 in approximately 29 LMICs. Results Of the successful supervision approaches described in the 57 studies reviewed, 44 were externally funded pilots, which is a limitation. Thirty focused on community health worker (CHW) programs. Health worker supervision was informed by health system data for 38 approaches (67%) and 22 approaches used continuous quality improvement (QI) (39%). Many successful approaches integrated digital supervision technologies (e.g., SmartPhones, mHealth applications) to support existing data systems and complement other health system activities. Few studies were adapted, scaled, or sustained, limiting reports of cost-effectiveness or impact. Conclusion Building on results from the review, to increase health worker supervision effectiveness we recommend to: integrate evidence-based, QI tools and processes; integrate digital supervision data into supervision processes; increase use of health system information and performance data when planning supervision visits to prioritize lowest-performing areas; scale and replicate successful models across service delivery areas and geographies; expand and institutionalize supervision to reach, prepare, protect, and support frontline health workers, especially during health emergencies; transition and sustain supervision efforts with domestic human and financial resources, including communities, for holistic workforce support. In conclusion, effective health worker supervision is informed by health system data, uses continuous quality improvement (QI), and employs digital technologies integrated into other health system activities and existing data systems to enable a whole system approach. Effective supervision enhancements and innovations should be better integrated, scaled, and sustained within existing systems to improve access to quality health care.

Evaluation of the management of PARP inhibitor toxicities in ovarian and endometrial cancer within a multi-institution health-system

Introduction Poly-adenosine diphosphate ribose polymerase inhibitors (PARPi) have become a cornerstone of therapy in the management ovarian cancer and other cancers. PARPi are associated with significant toxicities and management strategies are primarily founded on clinical trial experience. This study aimed to provide an evaluation of patients receiving PARPi therapy within an academic health-system. Methods A retrospective, observational study of adult patients with gynecologic malignancy was conducted at the University of Pennsylvania Health System. Data was collected on patients prescribed a PARPi between December 2014 and October 2019. The primary endpoint was the status of PARPi therapy at the end of the study period. Key secondary endpoints included toxicity management strategies, time to discontinuation due to toxicity, progression free survival (PFS), and overall survival (OS). Results Of the 85 patients included, 45 (53%) received olaparib, 24 (28%) niraparib, and 16 (19%) rucaparib. Twenty-nine patients (34%) continued on therapy, 15 (18%) discontinued due to toxicity, and 41 (48%) discontinued due to progression. Fifty-one percent of patients required a dose reduction due to toxicities. The median time to discontinuation due to toxicity was 69 days (9-353). Median PFS was 181 days (9-365) and median OS was 338 days (9-365). Conclusion PARPi therapy is associated with numerous toxicities that are best managed through a multi-modal approach. Importantly, about half the patients in the current study required a dose reduction. Overall, this observational study outlines the incidence of PARPi toxicities and reviews potential management strategies, further guiding practitioners in an area with limited real-world experience.

Evaluation of multiple myeloma clinical decision support tool value for assessing treatment selection variation when populated with community health system data.

e18781 Background: Clinical decision support (CDS) technology has the potential to improve health outcomes by offering physicians an informational resource to support review and application of best practices. The Multiple Myeloma Research Foundation (MMRF) and Intermountain Healthcare (IMH) conducted a study to assess the suitability of a single health system’s data for a myeloma-specific CDS tool that visualizes treatment pathways, and to assess the effort needed to support a CDS program. This research is part of a longer-term effort to explore how CDS technology can help: Increase awareness of and apply treatment guidelines by visualizing pathways for specific MM patient cohorts, Improve understanding of treatment variation for quality improvement within healthcare systems, Improve outcomes research by visualizing relationships between treatments and outcomes. This abstract focuses on the second use case, showing suitability of community health system data to assess treatment variability within the health system. Methods: IA12 data from the CoMMpass study was used to create a CDS tool prototype. These data were aggregated into state and transition maps to identify nodes and pathways with corresponding outcomes, including response, progression-free survival (PFS), and overall survival (OS). We also tested if EMR data from a community health system (i.e., IMH) could support such visualization. Inclusion criteria included patients with active MM between January 2016–June 2018; adult aged 18 years to 89 years at diagnosis of active or smoldering MM. An IMH-specific data dictionary was assessed for variable importance, quantity, and ease of acquisition. Results: Ninety-six of an initial 146 patients meeting eligibility criteria had sufficient data usable for the study, reflecting 44 unique drug combinations across 9 lines of therapy. The tool was able to associate and visualize all patients and their clinical states and transitions to their outcomes. Clinical data was typically complete (99% of the time), including key clinician-derived data, such as ECOG scores (78%) and treatment response (99%). Conclusions: The IMH portion of the study supports the hypothesis that a community health system can provide sufficiently high-quality information to power a CDS tool with priority features including display of treatment selection variability. Only 65% (96/146) of the initial study group had usable data because some patients had received partial care outside of the IMH integrated delivery network (IDN) leaving associated data inaccessible. Initial biostatistical analysis suggests that roughly 750-1000 complete patient records would be required for statistically significant outcomes research with granularly stratified cohorts. The MMRF plans to recruit additional large IDNs to obtain the patients to power more generalizable functionality.

Lumos: a statewide linkage programme in Australia integrating general practice data to guide system redesign

ObjectiveWith ageing of the Australian population, more people are living longer and experiencing chronic or complex health conditions. The challenge is to have information that supports the integration of services across the continuum of settings and providers, to deliver person-centred, seamless, efficient and effective healthcare. However, in Australia, data are typically siloed within health settings, precluding a comprehensive view of patient journeys. Here, we describe the establishment of the Lumos programme—the first statewide linked data asset across primary care and other settings in Australia and evaluate its representativeness to the census population.Methods and analysisRecords extracted from general practices throughout New South Wales (NSW), Australia’s most populous state, were linked to patient records from acute and other settings. Innovative privacy and security technologies were employed to facilitate ongoing and regular updates. The marginal demographic distributions of the Lumos cohort were compared with the NSW census population by calculating multiple measures of representation to evaluate its generalisability.ResultsThe first Lumos programme data extraction linked 1.3 million patients’ general practice records to other NSW health system data. This represented 16% of the NSW population. The demographic distribution of patients in Lumos was >95% aligned to that of the NSW population in the calculated measures of representativeness.ConclusionThe Lumos programme delivers an enduring, regularly updated data resource, providing unique insights about statewide, cross-setting healthcare utilisation. General practice patients represented in the Lumos data asset are representative of the NSW population overall. Lumos data can reliably be used to identify at-risk regions and groups, to guide the planning and design of health services and to monitor their impact throughout NSW.

Collaboration with First Nations Communities to Produce Tailored Community-Driven Results

IntroductionWhile First Nations communities are well aware of the unique health challenges and requirements of their populations, research evidence is often needed to support this knowledge. First Nations communities face continual challenges accessing data pertaining to the health of their people that is held by the government or other organizations. Objectives and ApproachThrough the Applied Health Research Question (AHRQ) program at ICES, First Nations communities in Ontario, Canada, have an avenue to access vital population health information about their people. While keeping questions of privacy, data sovereignty, data governance, and the OCAP® principles at the forefront, First Nations partners are active members and collaborators on community driven projects that are of importance to their communities. An Indigenous health data training program has also been developed to run concurrently with these projects, to enhance research knowledge and capacity within partner First Nations communities. ResultsFirst Nations community partners are the main drivers in deciding and refining the research questions for their projects. They are engaged throughout the project process to ensure the production of results that suit the specific needs of the partners. Project results are only shared with the partners, who utilize and disseminate them as appropriate within their communities. Conclusion / ImplicationsWith access to previously difficult to access population health data sources, First Nations communities are able to use health system data as an additional tool to better plan and implement community health programs, to lobby for additional funding, and ultimately to contribute to positive policy change.

Super-Utilization of the Emergency Department in a Universally Insured Population

ABSTRACT Introduction Super-utilizers (patients with 4 or more emergency department [ED] visits a year) account for 10% to 26% of all ED visits and are responsible for a growing proportion of healthcare expenditures. Patients recognize the ED as a reliable provider of acute care, as well as a timely resource for diagnosis and treatment. The value of ED care is indisputable in critical and emergent conditions, but in the case of non-urgent conditions, ED utilization may represent an inefficiency in the healthcare system. We sought to identify patient and clinical characteristics associated with ED super-utilization in a universally insured population. Material and Methods We performed a retrospective cohort study using TRICARE claims data from the Military Health System Data Repository (2011-2015). We reviewed the claims data of all adult patients (aged 18-64 years) who had at least one encounter at the ED for any cause. Multivariable logistic regression was used to determine independent factors associated with ED super-utilization. Results Factors associated with increased odds of ED super-utilization included Charlson Score ≥2 (adjusted odds ratio [aOR] 1.98, 95% confidence interval [CI]: 1.90-2.06), being eligible for Medicare (aOR 1.95, 95% CI: 1.90-2.01), and female sex (aOR 1.35, 95% CI: 1.33-1.37). Active duty service members (aOR 0.69, 95% CI 0.68-0.72) and beneficiaries with higher sponsor-rank (Officers: aOR 0.50, 95% CI: 0.55-0.57; Senior enlisted: aOR 0.82, 95% CI: 0.81-0.83) had lower odds of ED super-utilization. The most common primary diagnoses for ED visits among super-utilizers were abdominal pain, headache and migraine, chest pain, urinary tract infection, nausea and vomiting, and low back pain. Conclusions Risk of ED super-utilization appears to increase with age and diminished health status. Patient demographic and clinical characteristics of ED super-utilization identified in this study can be used to formulate healthcare policies addressing gaps in primary care in diagnoses associated with ED super-utilization and develop interventions to address modifiable risk factors of ED utilization.