Health Care Delivery Network Research Articles

Measuring the Maturity of Integrated Care in Singapore with the SCIROCCO Exchange Tool.

How have we progressed and where are the gaps of integrated care in Singapore? Social-health care provision in the context of an ageing population is critical in the city-state's management of the unprecedented demand as the proportion of seniors with multiple complex medical needs have almost doubled in the past decade. This study measures the maturity level of Singapore's integrated care, identifies key gaps and discusses their implications using the SCIROCCO Exchange tool, an online self-assessment tool consisting of the 12 dimensions necessary for the provision of integrated care. A three-step mixed method Delphi study was used to derive expert consensus. Participants across the social-healthcare sector as well as representatives from all three public healthcare delivery networks with at least five years of experience were included. Participants rated each of the twelve dimensions of the SCIROCCO Exchange tool on a six-point ordinal scale and provided justifications for each rating. Criteria from the RAND UCLA appropriateness method and thematic analysis were adopted for the analysis. All participants completed the study. The study found five dimensions in the "Initial" maturity level and five dimensions in the "Progressing" maturity level. There were two dimensions which were "Uncertain" because of split responses, possibly due to their differing vantage points and conceptualisations of integrated care. The overall medians were plotted on a spider diagram. The absence of a systematic approach for integrated care was the most common subtheme across all dimensions. This is foundational for integrated care as this would enable stakeholders across health and social care to identify with a common goal. The findings emphasise the imperative to reshape social-health care delivery by focusing on foundational dimensions (such as structure, governance and citizen empowerment) to enable progress in other dimensions. Following the conclusion of this study, Singapore initiated a primary care reform with the launch of Healthier SG in July 2023. Future research may wish to explore the impact of Healthier SG on maturity of integrated care in Singapore.

A-207 Enhancing Healthcare Delivery Network Laboratories: The Role of Third-Party Consultants in Benchmarking and Reviewing RFP Results

Abstract Background Healthcare delivery networks, particularly laboratory services, play a critical role in patient care and diagnosis. However, ensuring the quality and efficiency of these services can be challenging due to the complex and dynamic nature of healthcare systems. Third-party consultants offer valuable expertise in benchmarking and reviewing Request for Proposal (RFP) results, which can improve the quality and cost-effectiveness of laboratory services within healthcare networks. Methods To evaluate the role of third-party consultants in enhancing healthcare delivery network laboratories, the author conducted surveys to 50 laboratory leaders with a 50% response rate and analyzed the following aspects: Benchmarking: Comparing laboratory performance metrics with industry best practices and peer institutions to identify areas for improvement. RFP Review: Utilizing subject matter experts to assess the technical and financial proposals submitted by vendors to ensure compliance with RFP requirements and to identify the most suitable vendor for the network. Emotional Procurement: Minimizing the influence of emotional factors, such as personal relationships or brand loyalty, during the RFP process. Results Improved Quality: 65% said they can save >50 hours of labor utilizing a 3rd party for RFP, thus able to focus on patient results and quality. Cost Savings: 76% of respondents said consultants can help networks reduce expenses and improve their financial performance by 10-20% above and beyond incumbent negotiations. Emotional Procurement Mitigation: While the specific statistics supporting the influence of consultants on mitigating emotional factors in procurement decisions are not readily available, the broader impact of emotions on decision-making is well-documented. Therefore, while direct statistics may be limited, the influence of emotions on procurement decisions is a recognized factor in the field of decision science and consumer behavior. Turn around time: 70% of respondents said utilizing a 3rd party can reduce the turnaround time of a sourcing event from >3 months to < 1months. Conclusions Third-party consultants can provide valuable insights and expertise in benchmarking and reviewing RFP results, leading to several benefits. They can play a crucial role in enhancing healthcare delivery network laboratories by providing valuable expertise in benchmarking, reviewing RFP results, communication and reducing turnaround time. By improving quality, reducing costs, mitigating emotional procurement based on brand loyalty, and enhancing collaboration, consultants can help networks deliver high-quality services to patients and improve their overall performance. Consultants can facilitate more focused communication and partnership development between laboratories, vendors, and other stakeholders, ensuring a seamless transition and optimal performance without scope creep. As healthcare networks continue to evolve and face new challenges, the role of third-party consultants will become increasingly important in ensuring the quality and efficiency of laboratory services, potentially resulting in $100’s of millions in cost takeout across the country.

Learning healthcare delivery network with longitudinal electronic health records data

Learning healthcare delivery network with longitudinal electronic health records data

Comparing first-line (1L) atezolizumab plus bevacizumab (A+B) to lenvatinib (L) or sorafenib (S) in patients with unresectable hepatocellular carcinoma (uHCC): Findings from the National Veteran Health Administration (VHA) database.

446 Background: The approval of A+B has reshaped the treatment paradigm for patients with uHCC, establishing a new standard of care for 1L uHCC treatment. The VHA is the largest independent healthcare delivery network and the largest provider of liver-related care in the US. We aimed to compare patient characteristics and clinical outcomes between veterans who received 1L A+B and those who received L or S for unresectable HCC. Methods: Using data from the VHA National Corporate Data Warehouse (1/1/2017 - 12/31/2022), we conducted a retrospective cohort study in patients diagnosed with uHCC who initiated A+B after 2020 or initiated L or S after 2018. Child-Pugh (CP) scores were calculated using a previously validated algorithm. Kaplan-Meier and multivariable Cox regression methods were applied to compare overall survival (OS) between the groups. Results: We identified 405 eligible patients who received A+B, 453 received L, and 1,016 received S. Compared with patients receiving L or S, those treated with A+B had a higher proportion of CP A5 (47% and 35% vs. 54%, respectively; both p<0.05), a similar proportion of A6 (30% and 32% vs. 31%, p=0.683 and 0.681, respectively), a lower proportion of B7 (15% and 20% vs. 9%, respectively; both p<0.05), and a greater comorbidity burden as measured by the mean Charlson Comorbidity Index (CCI) (5.8 [L or S] vs 6.6 [A+B], both p<0.05). Median OS (mOS) was 12.8 months (95% CI: 10.6, 17.1) in the A+B cohort, compared to 9.5 months [95% CI: 7.8, 11.4] in the L cohort, and 8.0 months [95% CI: 7.1, 8.6] in the S cohort. In subgroup analyses, longer mOS was observed with A+B than with L or S in CP A patients and those with ALBI grades 1-2A; similar mOS was observed among those with more severe liver dysfunction (Table). In multivariable analysis, A + B was associated with a 26% lower risk of death relative to L (HR=0.74, 95% CI: 0.62-0.88) and 30% lower risk of death compared to S (HR = 0.70, 95%CI 0.60-0.82), both p<0.001. Conclusions: In a real-world VHA experience with A+B among diverse patient groups, a clinically notable survival benefit was observed with A+B compared to L or S. Future evaluations of the safety of using A+B in patients with greater liver dysfunction, including CP B and cirrhosis, are needed to evaluate the expanded use of A+B. [Table: see text]

Artificial Intelligence and Decision-Making in Healthcare: A Thematic Analysis of a Systematic Review of Reviews.

The use of artificial intelligence (AI), which can emulate human intelligence and enhance clinical results, has grown in healthcare decision-making due to the digitalization effects and the COVID-19 pandemic. The purpose of this study was to determine the scope of applications of AI tools in the decision-making process in healthcare service delivery networks. This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles. Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes. This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.

Using Agile Science for Rapid Innovation and Implementation of a New Care Model.

As industry consolidation leads to a growing number of large new healthcare delivery networks, patients and their clinicians are losing the important human-centric and relationship-based nature of medical care. The leadership of Hackensack Meridian Health (HMH), a New Jersey-based network of hospitals, research center, and medical school, made an organizational commitment to reverse such loss and restore the social nature of medicine. To attain that goal, HMH engaged both clinicians and administrators to confirm the demand for change, foster a collaborative culture design, and address the unique nature of the individual components in the HMH network. Efforts to transform the HMH care delivery model illustrate the effectiveness of Agile science and its problem-solving methods.

Characterizing Outpatient Classical Hematology Referrals at an Academic Healthcare System

BACKGROUND: Healthcare systems and delivery networks are experiencing an overwhelming number of Classical Hematology (CH) referrals. In our network, patients referred for CH consultation are facing increasing wait times and a shortage of available clinicians. In response to these workforce challenges, our institution is collaborating with advanced practice providers (APPs) to evaluate new patients using a tiered system that matches consults with corresponding years of clinical experience. This model is in use at one clinical site but its potential benefit when implemented across the entire network is unknown. To better inform this initiative, we sought to identify the most common diagnoses for outpatient CH referrals, determine the complexity level of these consults, and identify opportunities for alternative patient scheduling workflows. METHODS: A list of all new outpatient CH referrals evaluated in the Yale Smilow Cancer Network in Connecticut from 2019-2021 was compiled. ICD-10 codes assigned from each new patient encounter were combined into general diagnosis categories including iron deficiency anemia, other anemias, and thrombosis. After the 3 most common diagnoses were identified, 30 new patients evaluated in 2021 were randomly selected from each diagnosis group for manual chart review. Manual review focused on the details of each patient case and assigned a diagnosis level (Table 1). Diagnosis levels were matched with APP years of experience, ranging from level 1 (consults that could be evaluated within the first few years of practice) to level 3 (cases requiring more extensive experience or physician evaluation). These levels were predetermined by a committee of senior level CH physicians in the Smilow network. RESULTS: Based on grouped ICD diagnosis codes, the 3 most common CH referrals to our network from 2019-2021 were anemia (excluding iron deficiency, with an average of 22.4% of all new referrals), iron deficiency anemia (21.2%), and thrombosis (13.2%). Combined, these 3 diagnoses accounted for 56.8% of all incoming new referrals. Manual chart review of the anemia group showed that 3 patients had iron deficiency anemia with a diagnosis level of 1. After excluding these 3 patients, 1/27 (3.7%) anemia patients were level 1, 9/27 (33.3%) were level 2, and 17/27 (63.0%) patients were level 3 (Figure 1). In the iron deficiency group, after accounting for the 3 additional patients transferred from the anemia group, 16/33 (48.5%) were level 1, 7/33 (21.2%) were level 2, and 10/33 (30.3%) were level 3. In the thrombosis group, 12/30 (40.0%) patients were level 2, and 18/30 (60.0%) were level 3. 18.9% of all reviewed charts were level 1, 31.1% were level 2, and 50.0% were level 3. CONCLUSIONS: Manual chart review of the most common CH referrals (anemia, iron deficiency anemia, thrombosis) showed heterogeneity in diagnosis level. Thrombosis and anemia (excluding iron deficiency) had a higher proportion of more complex cases. In contrast, iron deficiency anemia contained a substantial number of level 1 cases (approximately 50% of all iron deficiency referrals). At one of our clinical sites, CH trained APPs have been evaluating new consults using the tiered system described within this study. Patients are then seen in follow-up by a collaborating physician. Manual chart review showed that 50% of consults in the 3 most common referral categories were either level 1 or 2, representing a substantial patient population that could be evaluated by an APP for initial consultation. In addition to increasing trainee and physician recruitment, implementing this model on a network-wide scale may be an invaluable strategy to address the current CH workforce shortage. Our study also identified that iron deficiency contained a large proportion of level 1 cases. This may be a consult population that is particularly amenable to non-traditional triage and evaluation algorithms. Strategies to consider include eConsultations to facilitate faster evaluation and iron infusions when indicated, or specialized provider and clinic creation. Our institution is piloting the use of triage algorithms to identify these uncomplicated iron deficiency cases and further optimize consult workflows.

Use of Community SARS-CoV-2 Case Counts and Instantaneous Reproductive Number to Predict Short-Term COVID-19 Hospital Admission Volumes.

The severe acute respiratory syndrome (SARS-CoV-2) pandemic and high hospitalization rates placed a tremendous strain on hospital resources, necessitating the use of models to predict hospital volumes and the associated resource requirements. Complex epidemiologic models have been developed and published, but many require continued adjustment of input parameters. We developed a simplified model for short-term bed need predictions that self-adjusts to changing patterns of disease in the community and admission rates. The model utilizes public health data on community new case counts for SARS-CoV-2 and projects anticipated hospitalization rates. The model was retrospectively evaluated after the second wave of SARS-CoV-2 in New York, New York (October 2020-April 2021) for its accuracy in predicting numbers of coronavirus disease 2019 (COVID-19) admissions 3, 5, 7, and 10 days into the future, comparing predicted admissions with actual admissions for each day at a large integrated health-care delivery network. The mean absolute percent error of the model was found to be low when evaluated across the entire health system, for a single region of the health system or for a single large hospital (6.1%-7.6% for 3-day predictions, 9.2%-10.4% for 5-day predictions, 12.4%-13.2% for 7-day predictions, and 17.1%-17.8% for 10-day predictions).

Computable Clinical Phenotyping of Postacute Sequelae of COVID-19 in Pediatrics Using Real-World Data.

Many questions remain unanswered concerning the long-term effects of COVID-19 in children. In this report, we describe a computable phenotyping algorithm for identifying children and adolescents with post-acute sequelae of COVID-19 (PASC) and pilot this tool to characterize the clinical epidemiology of pediatric PASC in a large healthcare delivery network.

Patients' and physicians' gender and perspective on shared decision-making: A cross-sectional study from Dubai.

Delivering patient-centered care is a declared objective of many health delivery systems globally, especially in an era of value-based health care. It entails the active engagement of the patients in healthcare decisions related to their health, also known as shared decision making (SDM). Little is known about the role of gender in shaping the perspective of patients on their opportunity for engaging in SDM in the Arabian Gulf Region. The aim of this study is to investigate the role of gender in shaping patients' perspectives toward their opportunity for SDM in Dubai, UAE. This study utilized a cross-sectional survey consisting of sociodemographic questions and the 9-item Shared Decision-Making Questionnaire (SDM-Q-9). A total of 50 physicians (25 females and 25 males), practicing at a large private healthcare delivery network in Dubai, were recruited using convenience sampling. Ten patients of every recruited physician (5 male and 5 female) were surveyed (i.e., a total of 500 patients). Statistical analysis assessed the differences in patients' perceptions of physician SDM attitude scores by physicians' and patients' gender using independent t-test, ANOVA-test, and Chi-square analyses. A total of 50 physicians and 500 patients (250 male patients and 250 female patients) participated in this study. The odd of patients agreement was significantly lower for male physicians, compared to their female counterparts, on the following elements of SDM: the doctor precisely explaining the advantages and disadvantages of the treatment (OR = 0.55, 95%CI: 0.34-0.88, p = 0.012); the doctor helping them understand the information (OR = 0.47, 95%CI: 0.23-0.97, p = 0.038), the doctor asking about preferred treatment option (OR = 0.52, 95%CI: 0.35-0.77, p = 0.001), and the doctor thoroughly weighting the different treatment options (OR = 0.60, 95%CI: 0.41-0.90, p = 0.013). No significant associations were observed between patients' gender and their perception of their opportunity for SDM. Likewise, no significant associations were observed between the same or different physician-patient gender and patients' perception of physicians' SDM attitudes. Statistically significant associations were observed between physician-patient gender and preferred treatment option for patients (p = 0.012). Study findings suggest that while there were no differences in patients' perspective on SDM by the gender of patients, significant differences were observed by the gender of physicians. Female physicians, compared to their male counterparts, were more engaged in SDM, with both male and female patients. Male physician-female patient dyad received the lowest scores on SDM. This could be explained by the cultural, social, and religious sensitivities that infiltrate the physician-patient relationship in the Arab contexts. Despite the multi-cultural nature of the country, some female patients may still experience some discomfort in opening up and in discussion preferences with male physicians. For physicians, striking the right balance between assertiveness and SDM is necessary within the cultural context, especially among male providers. Offering targeted learning and development programs on the importance and practice of SDM is also necessary to ensure equitable opportunity for engagement in SDM for all patients irrespective of the gender of their provider.

Using an optimized generative model to infer the progression of complications in type 2 diabetes patients

BackgroundPeople live a long time in pre-diabetes/early diabetes without a formal diagnosis or management. Heterogeneity of progression coupled with deficiencies in electronic health records related to incomplete data, discrete events, and irregular event intervals make identification of pre-diabetes and critical points of diabetes progression challenging.MethodsWe utilized longitudinal electronic health records of 9298 patients with type 2 diabetes or prediabetes from 2005 to 2016 from a large regional healthcare delivery network in China. We optimized a generative Markov-Bayesian-based model to generate 5000 synthetic illness trajectories. The synthetic data were manually reviewed by endocrinologists.ResultsWe build an optimized generative progression model for type 2 diabetes using anchor information to reduce the number of parameters learning in the third layer of the model from Oleft(Ntimes Wright) to Oleft((N-C)times Wright), where N is the number of clinical findings, W is the number of complications, C is the number of anchors. Based on this model, we infer the relationships between progression stages, the onset of complication categories, and the associated diagnoses during the whole progression of type 2 diabetes using electronic health records.DiscussionOur findings indicate that 55.3% of single complications and 31.8% of complication patterns could be predicted early and managed appropriately to potentially delay (as it is a progressive disease) or prevented (by lifestyle modifications that keep patient from developing/triggering diabetes in the first place).ConclusionsThe full type 2 diabetes patient trajectories generated by the chronic disease progression model can counter a lack of real-world evidence of desired longitudinal timeframe while facilitating population health management.

Implementation of large-scale laboratory-based detection of COVID-19 in the Veterans Health Administration, March 2020 – February 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented numerous operational challenges to healthcare delivery networks responsible for implementing large scale detection of Coronavirus Disease 2019 (COVID-19), the infection caused by SARS-CoV-2. We describe testing performance, review data quality metrics, and summarize experiences during the scale up of laboratory-based detection of COVID-19 in the Veterans Health Administration, the largest healthcare system in the United States. During March 2020 to February 2021, we observed rapid increase in testing volume, decreases in test turnaround time, improvements in testing of hospitalized persons, changes in test positivity, and varying utilization of different tests. Though performance metrics improved over time, surges challenged testing capacity and data quality remained suboptimal. Future planning efforts should focus on fortifying supply chains for consumables and equipment repair, optimizing distribution of testing workload across laboratories, and improving informatics to accurately monitor operations and intent for testing during a public health emergency.

Discordance between Treatment Guideline Recommendations and Real-World Practice in a Group of Large Integrated Delivery Networks for Venous Thromboembolism (VTE) Patients: A Closer Look at VTE Patients with Cancer

Background: For patients with VTE, current American Society of Hematology (ASH) guideline panel suggests using direct oral anticoagulants (DOACs) over vitamin K antagonists (VKAs) where VKAs are required to be bridged with a parenteral anticoagulant (PAC). For patients with VTE and cancer, current guidelines recommend DOACs over low molecular weight heparin (LMWH) and LMWH over unfractionated heparin (heparin) for the initial treatment of VTE. Limited evidence is available about the patterns of anticoagulant treatment for VTE in routine clinical practice of large healthcare delivery networks in the United States (US) and whether the VTE treatments are aligned with current guidelines. This study aimed to assess real-world anticoagulant treatment patterns among VTE patients using harmonized electronic health record (EHR) data from four Integrated Delivery Networks (IDNs) in the US.Methods: This was a retrospective, longitudinal, multicenter, cohort study using harmonized EHR data from both inpatient and outpatient settings. The study population included adult patients prescribed DOACs, warfarin, and/or PAC therapy as inpatient or outpatient treatment within ≤30 days of VTE diagnosis, between June 2015 through May 2018. Data from the four IDNs was pooled to describe demographic characteristics and treatment patterns among VTE patients overall and by subgroups.Results: A total of 10,527 patients who were treated with OACs after VTE diagnosis were included for analysis. The mean (SD) age was 61.9 (5.98) years, with 46.1% aged 65 or older. More than half (53.2%) were female, and White patients comprised the majority (74.4%), followed by African American patients (22.8%). Obese and morbidly obese patients comprised 39.1% and 16.1% of patients, respectively. Among all VTE patients, warfarin-only (n=3545; 33.7%) was the most commonly used OAC treatment, followed by warfarin + PAC (n=3128; 29.7%), rivaroxaban-only (n=1357; 12.9%), rivaroxaban + PAC (n=853; 8.1%), apixaban + PAC (n=839; 8.0%), apixaban-only (n=762; 7.2%), and Other OAC (n=357; 3.4%) (Table 1). When stratifying VTE patients by age, gender, race and BMI, some variations in OAC treatment were observed. Among both older (≥65 years) and younger (<65 years) patients, warfarin-only was most commonly used, then warfarin + PAC. Warfarin-only was more commonly used among obese (36.3%) and morbidly obese (40.4%) patients than non-obese (29.8%) patients. OAC treatment patterns were generally comparable among men and women. Among White patients, approximately equal proportions of patients received warfarin + PAC (31.9%) and warfarin-only (31.0%). However, among African-American patients, a higher proportion of patients used warfarin-only (40.9%) vs. warfarin + PAC (24.5%).Patterns of anticoagulant treatments including OACs and/or parental anticoagulants among VTE patients with cancer were further analyzed (Figure 1). Among VTE patients with cancer (n=3657), heparin had the highest use (26.7%), then enoxaparin (22.7%); approximately the same proportion of cancer patients received warfarin-only (16.0%) and warfarin + PAC (16.9%). Of DOACs, rivaroxaban-only was the most commonly used treatment (4.9%), then apixaban + PAC (3.5%), and lastly, rivaroxaban + PAC (3.4%) among cancer patients.Conclusion: Current VTE treatment guidelines recommend warfarin to be bridged with PAC, however, warfarin-only therapy remained the most used treatment option followed by warfarin + PAC. While rivaroxaban and apixaban are not required to be bridged with PAC, such practices were observed for a large proportion of apixaban- and rivaroxaban-treated VTE patients. VTE treatment among patients with cancer was not completely aligned with current guidelines, as heparin was more commonly used than LMWH (enoxaparin). Our findings suggest greater efforts are needed to improve anticoagulant treatment practices among VTE patients. [Display omitted] DisclosuresDhamane: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Rosenblatt: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Jiang: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Guo: Bristol Myers Squibb: Ended employment in the past 24 months. Dorsch: Agency for Health Research and Quality: Research Funding; National Institutes of Health/National Institute of Aging: Research Funding; American Health Association Health IT Research Network: Research Funding; Janssen Pharmaceuticals: Honoraria; Bristol Myers Squibb/Pfizer: Research Funding; Amgen: Research Funding. Luo: Pfizer Inc: Current Employment, Current equity holder in publicly-traded company.

Apixaban vs. Warfarin in Atrial Fibrillation Patients With Chronic Kidney Disease.

Background and Objectives: Real-world evidence of apixaban treatment in patients with chronic kidney disease remains scarce. This study aimed to compare the relative risk of stroke or systemic embolism (SE) and major bleeding between apixaban and warfarin in atrial fibrillation (AF) patients with different degrees of kidney function.Design, Setting, Participants, and Measurements: We evaluated newly diagnosed AF patients between 2004 and 2018, who were receiving apixaban or warfarin. Electronic medical record data were collected from a large healthcare delivery network in Taiwan. The outcomes of hospitalization for stroke/SE and major bleeding were compared with propensity-score matched apixaban and warfarin cohorts. Stratified analyses according to initial apixaban dose (standard dose of 10 mg/day vs. lower dose of 2.5–5.0 mg/day) and baseline estimated glomerular filtration rate were performed.Results: Each cohort involved 1,625 matched patients. Apixaban was significantly associated with a lower risk of stroke/SE (adjusted hazard ratio [aHR]: 0.74; 95% confidence interval [CI]:0.57–0.97; p = 0.03). The risk of major bleeding was not increased whether in standard doses (aHR: 0.66; 95% CI: 0.45–0.96; p = 0.03) or reduced doses (aHR, 0.84; 95% CI, 0.63–1.12; p = 0.23) of apixaban. Regarding kidney function, apixaban reduced the risk of stroke/SE by 37% in those with an eGFR of <30 ml/min/1.73 m2 (aHR: 0.63; 95% CI: 0.40–0.98; p = 0.04).Conclusions: Compared to warfarin, apixaban is associated with a reduced risk of stroke/SE and is consistent with a subset of AF patients with eGFR <30 ml/min/1.73 m2. Both standard and reduced doses of apixaban showed lower risk of major bleeding than those of warfarin.

So Happy Together: A Scoping Review on Effectiveness of Inter-Organizational Care Delivery Networks

While inter-organizational networks are widely recognized as a mode of organization to address the wicked problems in health care, we have a limited understanding of what makes these networks effective. This is imperative to keep health care delivery of high value (i.e. affordable and of high quality). In this study, we therefore performed a scoping review of the empirical literature that describes factors that influence the effectiveness of health care delivery networks. Our search yielded 3061 unique papers, of which 12 met our inclusion criteria. Much of the excluded literature studied different types of networks that did not seek to lower cost or improve quality, or lacked an explicit methodological approach. Included studies additionally lack robust theoretical foundation. Studies typically operationalize network effectiveness as a process measure, such as the degree of collaboration, rather than outcome measures. Furthermore, effectiveness is mostly measured as the perception of network members rather than actual goal attainment. Notably, coopting the operational level receives more attention in the health care literature, while the context remains underreported. To fully understand the factors influencing network effectiveness, there is need for more theoretically and methodologically robust research connecting perceived effectiveness, measured effectiveness, and the factors influencing network effectiveness.

Enhancing Hospital Performance: the role of interfirm dynamic capabilities from the information processing view

ABSTRACT In today’s increasingly volatile world, organisations including healthcare providers need interfirm dynamic capabilities to make timely responses to supply chains changes. There has been a wealth of literature on dynamic capabilities; however, very few are at interfirm level and even fewer are conducted in the healthcare industry. Grounded in information processing view, this study contributes to the literature by examining interfirm dynamic capabilities in the context of healthcare delivery networks. It proposes the interfirm dynamic capabilities as a form of information processing capability with five dimensions: sensing, learning, coordination, collective mind and partner development. Using data collected from healthcare delivery networks, this study explores the impact of interfirm dynamic capabilities on hospitals’ performance. The findings suggest that the fit between a healthcare delivery network's interfirm dynamic capabilities and information processing requirements will improve its operational capabilities, which will lead to better performance.

Improving performance intelligence for governing an integrated health and social care delivery network: a case study on the Amsterdam Noord district

BackgroundA guiding principle of a successful integrated health and social care delivery network is to establish a governance approach based on learning, grounded in a data and knowledge infrastructure. The ‘Krijtmolen Alliantie’ is a network of health and social care providers with the ambition to realize such a performance intelligence driven governance model in line with the Triple Aim. This study seeks to identify what performance intelligence is available and how it can be improved.MethodsThis case study was conducted in the district of Amsterdam Noord, the Netherlands, and employed 23 semi-structured interviews with stakeholders in health and social care, a feasibility analysis of available administrative data, and a reflection meeting with board members of the ‘Krijtmolen Alliantie’. Information needs for performance intelligence by the stakeholders were mapped and a data landscape of the district covered by the network was drafted. Finally, in the reflection meeting with board members of the ‘Krijtmolen Alliantie’ the information needs and data landscape were aligned with governing needs, resulting in priority domains around which to strengthen the data infrastructure for governance of the integrated health and social care delivery network.ResultsThe ‘Krijtmolen Alliantie’ encompasses a network of providers with a diverse range of catchment areas. There are indicators on population health and welfare, however they have limited actionability for providers due to a misalignment with their respective catchment areas. There is a barrier in data exchange between health and social care providers. It is difficult to construct one indicator for per capita cost in the Dutch health data infrastructure as health and social care are subdivided in financing siloes. Priority domains for improvement of performance intelligence for the ‘Krijtmolen Alliantie’ are: 1) Per capita and per patient cost data integration that would allow combined accountability through aligning financial incentives to facilitate integrated care, and 2) combined patient experience and outcome measures to reflect network quality of care and patient experience performance.ConclusionAvailable performance intelligence lacks actionability for the governance of integrated care networks. Our recommendation is to align performance intelligence with the regional governance responsibilities of stakeholders for health and social care delivery.

Perspectives of Health Care Providers in an Integrated Health Care Delivery Network on Inpatient Electronic Consultation (e-Consult) Use During the COVID-19 Pandemic.

A large academic hospital system (Allegheny Health Network) introduced inpatient electronic consultations (e-Consults) during the COVID-19 crisis. Providers were invited to complete an anonymous survey on their perceptions of e-Consults. Descriptive statistics were used to analyze Likert-scale data. Cronbach’s alpha was used to assess internal consistency. Ninety-five providers completed the survey. Requesting and consulting providers agreed that e-Consults were easy to use (100% and 96.2%, respectively). Both groups also concurred that e-Consults either decreased or did not significantly impact their workload (81% and 74%, respectively) and that training was appropriate (77.8% and 86.8%, respectively). The advantage and barrier selected most frequently by specialists was “timelier completion of the consult versus in-person” and “inadequate information to complete the consult,” respectively. The disadvantage selected most frequently by requesting physicians was “lack of communication between providers.” Open-ended comments were categorized into themes. Concerns were raised regarding whether provider–provider communication via this platform offered enough information to make recommendations compared to traditional encounters. The perceived benefits and barriers of e-Consults should be further explored with the goal of improving patient care delivery and provider satisfaction.

Integrating E-Prescribing and Pharmacy Claims Data for Predictive Modeling: Comparing Costs and Utilization of Health Plan Members Who Fill Their Initial Medications with Those Who Do Not.

Nonfilling of prescribed medications is a worldwide problem of serious concern. Studies of health care costs and utilization associated with medication nonadherence frequently rely on claims data and usually focus on patients with specific conditions. Past studies also have little agreement on whether higher medication costs associated with higher adherence can reduce downstream health care consumption. To (a) compare the characteristics between people with and without complete medication initiations from a general population and (b) quantify the effect of medication initiation on health care utilization and expenditures with propensity score weighting. We conducted a retrospective cohort study using 2012 and 2013 electronic health records (EHR) and insurance claims data from an integrated health care delivery network. We included 43,097 eligible primary care patients in the study. Annual medication fill rates of initial prescriptions in 2012 were defined as the number of filled prescriptions from claims divided by the number of e-prescriptions from EHRs, while excluding all refills. A claim was considered filled if (a) EHR and claims records were from the same drug class; (b) claims occurred between the date of a current EHR order and that of the next EHR order of the same class; and (c) the maximum fill rate was 100%. The 6 annual outcomes included total costs, medical costs, pharmacy costs, being a high-cost "outlier" (in top 5%), having 1 or more hospitalizations, and having 1 or more emergency department (ED) visits. Individuals were classified as either having completed all medication initiations (100% annual filling rate for initiations) or not. We used propensity score weighting to control for baseline differences between complete and incomplete initial fillers. We adopted linear and logistic regressions to model costs and binary utilization indicators for the same year (concurrently) and next year (prospectively). Approximately 42% of the study sample had complete medication initiations (100% filling rate), while the remaining 58% had incomplete initiations. Individuals who fully filled initial prescriptions had lower comorbidity burden and consumed fewer health care resources. After applying propensity score weighting and controlling for variables such as the number of prescription orders, patients with complete medication initiations had lower overall and medical costs, concurrently and prospectively (e.g., $751 and $252 less for annual total costs). Complete medication initiation fillers were also less likely to have concurrent health care utilization (OR = 0.78, 95% CI = 0.68-0.90 for hospitalization; OR = 0.77, 95% CI = 0.72-0.82 for ED admissions) but no difference in prospective utilization other than for ED visits (OR = 0.93, 95% CI = 0.87-0.99). Identifying the subpopulation of patients with incomplete medication initiations (i.e., filling less than 100% of initial prescriptions) is a pragmatic approach for population health management programs to align resources and potentially contain cost and utilization. No outside funding supported this study. This study applied the Adjusted Clinical Group (ACG) case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of this study, the goal of the study was not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. Chang, Kharrazi, and Weiner receive a portion of their salary support from this revenue. Chang is also a part-time consultant for Monument Analytics, a health care consultancy whose clients include the life sciences industry, as well as plaintiffs in opioid litigation. Alexander is past Chair of FDA's Peripheral and Central Nervous System Advisory Committee; has served as a paid advisor to IQVIA; is a co-founding Principal and equity holder in Monument Analytics; and is a member of OptumRx's National P&T Committee. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The other authors have nothing to disclose.

Trends in Atrial Fibrillation Incidence Rates Within an Integrated Health Care Delivery System, 2006 to 2018

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and multiple studies have reported increasing AF incidence rates over time, although the underlying explanations remain unclear. To estimate AF incidence rates from 2006 to 2018 in a community-based setting and to investigate possible explanations for increasing AF by evaluating the changing features of incident AF cases and the pool of patients at risk for AF over time. This cohort study included 500 684 patients who received primary care and other health care services for more than 2 years through a single integrated health care delivery network in Pennsylvania. Data collection was conducted from January 2003 to December 2018. The base study population had no documentation of AF in the electronic medical record for at least 2 years prior to baseline. Data analysis was conducted from May to December 2019. Incident AF cases were identified through diagnostic codes recorded at inpatient or outpatient encounters. Age- and sex-adjusted AF incidence rates were estimated by calendar year from 2006 to 2018 both overall and across subgroups, including according to diagnostic setting (inpatient vs outpatient) and priority (primary vs secondary diagnosis). Among 514 293 patients meeting criteria for the base study population, the mean (SD) age at baseline was 47 (18) years and 282 103 (54.9%) were women; 13 609 (2.6%) met AF diagnostic criteria on or prior to the baseline date and were excluded. Among 500 684 patients free of AF at baseline, standardized AF incidence rates from 2006 to 2018 increased from 4.74 (95% CI, 4.58-4.90) to 6.82 (95% CI, 6.65-7.00) cases per 1000 person-years, increasing significantly over time (P < .001). Incidence rates increased in all age and sex subgroups, although absolute rate increases were largest among those aged 85 years or older. The fraction of incident AF cases among individuals aged 85 years or older increased from 135 of 1075 (12.6%) in 2006 to 451 of 2427 (18.6%) in 2017. Patients with incident AF were more likely over time to have high body mass index (1351 of 3389 patients [39.9%] in 2006-2008 vs 4504 of 9214 [48.9%] in 2015-2018; P < .001), hypertension (2764 [81.6%] in 2006-2008 vs 7937 [86.1%] in 2015-2018; P < .001), and ischemic stroke (328 [9.7%] in 2006-2008 vs 1455 [15.8%] in 2015-2018; P < .001), but less likely to have coronary artery disease (1533 [45.2%] in 2006-2008 vs 3810 [41.4%] in 2015-2018; P < .001). Among 22 077 new cases of AF, 9146 (41.4%) were diagnosed as inpatients and 5731 (26.0%) as the primary diagnosis. Incidence rates of AF increased significantly in all diagnostic setting and priority pairings (eg, inpatient, primary: rate ratio, 1.07; 95% CI, 1.06-1.08; P < .001). Among patients at risk for AF, high BMI and hypertension increased over time (BMI: 71 433 of 198 245 [36.0%] in 2007 to 130 218 of 282 270 [46.1%] in 2017; hypertension: 79 977 [40.3%] in 2007 to 134 404 [47.6%] in 2017). Documentation of short-term ECG increased over time (23 297 of 207 349 [11.2%] in 2008 to 45 027 [16.0%] in 2017); however, long-term ECG monitoring showed no change (1871 [0.9%] in 2007 to 4036 [1.4%] in 2017). In this community-based study, AF incidence rates increased significantly during the study period. Concurrent increases were observed in AF risk factors in the at-risk population and short-term ECG use.