Chronic Care Model Research Articles

Refining the Implementation of a Hub-and-Spoke Model for TelePain Through Qualitative Inquiry

The hub-and-spoke telehealth model leverages centrally located providers who utilize telehealth technology to bring specialized care to medically underserved areas. This model has the potential to promote equitable access to healthcare. However, few studies address how to facilitate the adoption and implementation of hub-and-spoke telehealth. We examined spoke site providers’ experiences with TelePain, a national hub-and-spoke model of interdisciplinary chronic pain care, with a focus on improving future implementation. We conducted semi-structured individual interviews (20–45 min) with 27 VA spoke site providers via teleconferencing between August 2020 and February 2021. Interview transcripts were coded in Atlas.ti 8.0 using deductive (identified a priori and used to build the interview guide) and inductive (emerging) codes. Our analysis identified the following themes stressed by the spoke sites: (1) spoke sites needed to envision how TelePain services would work at their site before deciding to adopt; (2) TelePain implementation needed to fit into local existing care processes; (3) hub sites needed to understand spoke sites’ context (e.g., via needs assessment) to tailor the services accordingly, and (4) hub-and-spoke sites needed to establish bidirectional communication. Our findings provide a practical guide to improve future rollout of hub-and-spoke telehealth models. Recommendations focus on the role of the hub site in promoting program adoption by (1) developing a clear and detailed marketing plan and (2) considering how the program can be adapted to fit the local spoke site context. To improve implementation, hub-and-spoke sites must establish ongoing and consistent bidirectional communication; this is particularly critical in the everchanging post-peak pandemic healthcare system. An important next step is the development of recommendations and guidelines for implementing hub-and-spoke telehealth, as well as examining pain outcomes for patients touched by this program.

Predictors and outcomes in primary depression care (POKAL) – a research training group develops an innovative approach to collaborative care

BackgroundThe interdisciplinary research training group (POKAL) aims to improve care for patients with depression and multimorbidity in primary care.POKAL includes nine projects within the framework of the Chronic Care Model (CCM). In addition, POKAL will train young (mental) health professionals in research competences within primary care settings. POKAL will address specific challenges in diagnosis (reliability of diagnosis, ignoring suicidal risks), in treatment (insufficient patient involvement, highly fragmented care and inappropriate long-time anti-depressive medication) and in implementation of innovations (insufficient guideline adherence, use of irrelevant patient outcomes, ignoring relevant context factors) in primary depression care.MethodsIn 2021 POKAL started with a first group of 16 trainees in general practice (GPs), pharmacy, psychology, public health, informatics, etc. The program is scheduled for at least 6 years, so a second group of trainees starting in 2024 will also have three years of research-time. Experienced principal investigators (PIs) supervise all trainees in their specific projects. All projects refer to the CCM and focus on the diagnostic, therapeutic, and implementation challenges.ResultsThe first cohort of the POKAL research training group will develop and test new depression-specific diagnostics (hermeneutical strategies, predicting models, screening for suicidal ideation), treatment (primary-care based psycho-education, modulating factors in depression monitoring, strategies of de-prescribing) and implementation in primary care (guideline implementation, use of patient-assessed data, identification of relevant context factors). Based on those results the second cohort of trainees and their PIs will run two major trials to proof innovations in primary care-based a) diagnostics and b) treatment for depression.ConclusionThe research and training programme POKAL aims to provide appropriate approaches for depression diagnosis and treatment in primary care.

Effective coverage of diabetes and hypertension: an analysis of Thailand’s national insurance database 2016–2019

ObjectivesThis study assesses effective coverage of diabetes and hypertension in Thailand during 2016–2019.DesignMixed method, analysis of National health insurance database 2016–2019 and in-depth interviews.SettingBeneficiaries of Universal Coverage Scheme residing outside...

A New Look at Barriers to Clinical Care Among Appalachian Residents Living With Diabetes.

In the United States, diabetes is the seventh leading cause of death and continues to rise in prevalence, with type 2 diabetes accounting for 90-95% of all cases. Rates of diabetes in Kentucky, and, in particular, the Appalachian region, are among the highest in the nation and are increasing faster than the national average. Despite this disproportionate burden, barriers to clinical appointment attendance have not been fully explored in this population. This article examines the association among perceived barriers to clinical attendance, glycemic control, and diabetes self-care as part of an ongoing study. We used a 25-item checklist developed using the Chronic Care Model to assess participants' barriers to clinic attendance. Glycemic control was assessed via A1C measurement. Diabetes self-care was assessed using the Summary of Diabetes Self-Care Activities measure. At the time of analysis, 123 of the 356 participants (34.6%) did not report any barriers to clinic attendance. For the remainder, the major reported barriers included forgetting appointments, inability to afford medicines or other treatment, and placing faith above medical care. The average A1C was 7.7%, and the average diabetes self-care summary score was 17.1 out of 35 points (with higher values indicating better self-care). Missing clinic appointments is associated with lower health outcomes, especially in vulnerable populations. This study can help educate clinic staff on perceived barriers to type 2 diabetes management among people with diabetes in Appalachia.

Sustainability of the Collaborative Chronic Care Model in Outpatient Mental Health Teams Three Years Post-Implementation: A Qualitative Analysis.

Our goal was to investigate the sustainability of care practices that are consistent with the collaborative chronic care model (CCM) in nine outpatient mental health teams located within US Department of Veterans Affairs (VA) medical centers, three to four years after the completion of CCM implementation. We conducted qualitative interviews (N = 30) with outpatient mental health staff from each of the nine teams. We based our directed content analysis on the six elements of the CCM. We found variable sustainability of CCM-based care processes across sites. Some care processes, such as delivery of evidence-based psychotherapies (EBPs) and use of measurement-based care (MBC) to guide clinic decision-making, were robustly maintained or even expanded within participating teams. In contrast, other care processes-which had in some cases been developed with considerable effort-had not been sustained. For example, care manager roles were diminished in scope or eliminated completely in response to workload pressures, frontline care needs, or the COVID-19 pandemic. Similarly, processes for engaging Veterans more fully in decision-making had generally been scaled back. Leadership support in the form of adequate team staffing and time to conduct team meetings were seen as crucial for sustaining CCM-consistent care. Given the potential impact of leadership turnover on sustainability in mental health, future efforts to implement CCM-based mental health care should strive to involve multiple leaders in implementation and sustainment efforts, lest one key departure undo years of implementation work. Our results also suggest that implementing CCM processes may best be conceptualized as a partnership across multiple levels of medical center leadership.

Nurse-led Telehealth Intervention for Rehabilitation (Telerehabilitation) Among Community-Dwelling Patients With Chronic Diseases: Systematic Review and Meta-analysis.

Chronic diseases are putting huge pressure on health care systems. Nurses are widely recognized as one of the competent health care providers who offer comprehensive care to patients during rehabilitation after hospitalization. In recent years, telerehabilitation has opened a new pathway for nurses to manage chronic diseases at a distance; however, it remains unclear which chronic disease patients benefit the most from this innovative delivery mode. This study aims to summarize current components of community-based, nurse-led telerehabilitation programs using the chronic care model; evaluate the effectiveness of nurse-led telerehabilitation programs compared with traditional face-to-face rehabilitation programs; and compare the effects of telerehabilitation on patients with different chronic diseases. A systematic review and meta-analysis were performed using 6 databases for articles published from 2015 to 2021. Studies comparing the effectiveness of telehealth rehabilitation with face-to-face rehabilitation for people with hypertension, cardiac diseases, chronic respiratory diseases, diabetes, cancer, or stroke were included. Quality of life was the primary outcome. Secondary outcomes included physical indicators, self-care, psychological impacts, and health-resource use. The revised Cochrane risk of bias tool for randomized trials was employed to assess the methodological quality of the included studies. A meta-analysis was conducted using a random-effects model and illustrated with forest plots. A total of 26 studies were included in the meta-analysis. Telephone follow-ups were the most commonly used telerehabilitation delivery approach. Chronic care model components, such as nurses-patient communication, self-management support, and regular follow-up, were involved in all telerehabilitation programs. Compared with traditional face-to-face rehabilitation groups, statistically significant improvements in quality of life (cardiac diseases: standard mean difference [SMD] 0.45; 95% CI 0.09 to 0.81; P=.01; heterogeneity: X21=1.9; I2=48%; P=.16; chronic respiratory diseases: SMD 0.18; 95% CI 0.05 to 0.31; P=.007; heterogeneity: X22=1.7; I2=0%; P=.43) and self-care (cardiac diseases: MD 5.49; 95% CI 2.95 to 8.03; P<.001; heterogeneity: X25=6.5; I2=23%; P=.26; diabetes: SMD 1.20; 95% CI 0.55 to 1.84; P<.001; heterogeneity: X24=46.3; I2=91%; P<.001) were observed in the groups that used telerehabilitation. For patients with any of the 6 targeted chronic diseases, those with hypertension and diabetes experienced significant improvements in their blood pressure (systolic blood pressure: MD 10.48; 95% CI 2.68 to 18.28; P=.008; heterogeneity: X21=2.2; I2=54%; P=0.14; diastolic blood pressure: MD 1.52; 95% CI -10.08 to 13.11, P=.80; heterogeneity: X21=11.5; I2=91%; P<.001), and hemoglobin A1c (MD 0.19; 95% CI -0.19 to 0.57 P=.32; heterogeneity: X24=12.4; I2=68%; P=.01) levels. Despite these positive findings, telerehabilitation was found to have no statistically significant effect on improving patients' anxiety level, depression level, or hospital admission rate. This review showed that telerehabilitation programs could be beneficial to patients with chronic disease in the community. However, better designed nurse-led telerehabilitation programs are needed, such as those involving the transfer of nurse-patient clinical data. The heterogeneity between studies was moderate to high. Future research could integrate the chronic care model with telerehabilitation to maximize its benefits for community-dwelling patients with chronic diseases. International Prospective Register of Systematic Reviews CRD42022324676; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=324676.

De impact van Covid-19 op chronische zorg volgens zorgverleners: een kwalitatieve studie bij eerstelijnspraktijken in België

The impact of COVID-19 on chronic care according to providers: a qualitative study among primary care practices in Belgium The COVID-19 pandemic affects the processes of routine care for chronic patients. A better understanding helps to increase the resilience of the health system and to prepare it adequately for next waves of the pandemic. A qualitative study was conducted in 16 primary care practices: 6 solo working, 4 monodisciplinary and 7 multidisciplinary. Using semi-structured video interviews, 21 people (doctors, nurses, dieticians) were interrogated. A thematic analysis was performed using the domains of the chronic care model (CCM). Three themes emerged: changes in health care organization, risk stratification and self-management support. All participating practices reported drastic changes in organization with a collective shift towards COVID-19 care and a reduction of chronic care activities, less consultations, and staff responsible for self-management support put on hold. A transition to digital support did not occur. Few practitioners had a systematic approach to identify and contact high-risk patients for early follow-up. A practice with a pre-established structured team collaboration managed to continue most chronic care elements. Generally, practitioners expected no effects of the temporary disruption for patients, although they expressed concern about patients already poorly regulated. The findings in this article show a disruption of the delivery of chronic care in the Belgian primary care context. In such contexts, the establishment of the CCM can facilitate the continuity of care in times of a crisis. Short-term actions should be directed to facilitate the identification of high-risk patients and to develop a practice organization plan to organize chronic care and to use digital channels for support, especially with regard to vulnerable patients, during next waves of the epidemic.

Overcoming barriers to implementing new guideline-directed therapies for chronic kidney disease.

For the first time in many years, guideline-directed drug therapies have emerged that offer substantial cardiorenal benefits, improved quality of life and longevity in patients with chronic kidney disease (CKD) and type 2 diabetes. These treatment options include sodium-glucose cotransporter-2 inhibitors, nonsteroidal mineralocorticoid receptor antagonists and glucagon-like peptide-1 receptor agonists. However, despite compelling evidence from multiple clinical trials, their uptake has been slow in routine clinical practice, reminiscent of the historical evolution of angiotensin-converting enzyme inhibitor and angiotensin II receptor blocker use. The delay in implementation of these evidence-based therapies highlights the many challenges to optimal CKD care, including: (i) clinical inertia; (ii) low CKD awareness; (iii) suboptimal kidney disease education among patients and providers; (iv) lack of patient and community engagement; (v) multimorbidity and polypharmacy; (vi) challenges in the primary care setting; (vii) fragmented CKD care; (viii) disparities in underserved populations; (ix) lack of public policy focused on health equity; and (x) high drug prices. These barriers to optimal cardiorenal outcomes can be ameliorated by a multifaceted approach, using the Chronic Care Model framework, to include patient and provider education, patient self-management programs, shared decision making, electronic clinical decision support tools, quality improvement initiatives, clear practice guidelines, multidisciplinary and collaborative care, provider accountability, and robust health information technology. It is incumbent on the global kidney community to take on a multidimensional perspective of CKD care by addressing patient-, community-, provider-, healthcare system- and policy-level barriers.

Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium

BackgroundTo assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape.MethodsBased on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets.ResultsTo address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level.ConclusionIn this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices.

The Yale Roadmap for Health Psychology and Integrated Cardiovascular Care.

Cardiovascular disease remains the leading cause of morbidity and mortality in industrialized nations. Many patients living with chronic cardiovascular disease suffer from complex multimorbidities requiring high-intensity care and behavioral risk factor management, and about a third copresent with a mental health disorder. These comanifestations are extremely taxing for patients and our health care system, complicate treatment, and increase the risk of adverse health outcomes. Health psychology emerged in response to a need for specialists who could design, deliver, and test evidence-based approaches to manage behavioral risk factors and the mental health burden of chronic diseases. We aimed to conduct a state-of-the-art review as to how health psychology emerged as a key specialty in delivering integrated care for cardiovascular populations, and to review challenges and opportunities that lie ahead of further integration of the specialty for integrated cardiovascular care. As our health care system embraces more patient-centered care and big data science to detect at-risk patients and predict outcomes, health psychologists should be at the forefront to apply their expertise and demonstrate their value in designing and applying intervention models to improve outcomes. We first review challenges, then illustrate this framework using the Wagner chronic care model, present business case considerations, and conclude with an action agenda to promote the integration of health psychology as a cotreating specialty into cardiovascular care. To provide direction for this undertaking, we present a roadmap for the field of health psychology to sustainably extend existing holistic, integrated approaches in cardiovascular care. To lessen the burden and improve outcomes in cardiovascular disease, care must shift away from siloed delivery models that are focused on traditional atherosclerotic risk factors to holistic, integrated approaches that address biological, psychological, social, and behavioral factors relevant to cardiovascular disease. Using the presented roadmap, health psychology can play a major role to address these needs of integrated cardiovascular care. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Clinical complexity and diabetes: a multidimensional approach for the management of cardiorenal metabolic syndrome

Diabetes mellitus (DM) is one of the fastest-growing health emergencies of the 21st century, and one of the chronic diseases with the highest socio-economic impact on health care systems. DM is the main cause of chronic kidney disease, and is associated with a significant increase in cardiovascular risk and clinical and care complexity. The presence of a constellation of cardiac, metabolic, and renal diseases, in a complex patient with DM, constitutes the CardioRenal Metabolic Syndrome (CRMS). The management of these patients should include a paradigm shift from a reactive strategy to a proactive approach, and the integration of territorial, hospital and social assistance services according to the Chronic Care Model (CCM). Complexity science suggests an alternative model in which disease and health arise from complex, dynamic, and unique interactions among the different components of the overall system. The hospital should be viewed as a highly specialized hub of the chronic care system, which interacts with the outpatient specialist and primary care. In order to create effective communication among territorial care units and highly specialized hospitals, levels of clinical complexity are here proposed and included in a multidimensional management model for the complex patient with diabetes and cardiorenal comorbidity.

Conditions required to ensure successful detection and management of mild cognitive impairment in primary care: A Delphi consultation study in China.

ObjectiveDetection and management of mild cognitive impairment (MCI) in primary care has been recognized internationally as one of the strategies that can be employed to delay the development of dementia. However, little is known about what role primary care should play. This study aimed to develop a checklist of conditions necessary for successfully detecting and managing mild cognitive impairment in primary care in China.MethodsThis study employed the Delphi method to establish expert consensus on the conditions required for successfully detecting and managing MCI in primary care in China. Twenty-four experts who specialized in general practice, public health, neuropsychology, or community health service management rated the importance of pre-defined conditions (44 items measuring providers' preparedness, patient engagement, and system support in line with the Chronic Care Model). The degree of consensus among the experts was measured using four indicators: median ≥ 4, mean ≥3.5, Co-efficient of Variance < 0.25, and retention in the checklist required ≥ 80% agreement with a rating of important or essential. The checklist and descriptions of the conditions were revised according to the experts' feedback and then sent out for repeated consultations along with a summary of the results of the previous round of consultations. Consensus was achieved after the second round of consultations, which was completed by 22 of the experts.ResultsThe experts endorsed a checklist of 47 conditions required for successful detection and management of MCI in primary care in China. These conditions were categorized into four domains: prepared general practitioners (17 items), engaged patients (15 items), organizational efforts (11 items), and environmental support (4 items).ConclusionsSuccessful detection and management of MCI in primary care in China requires a dedicated and competent workforce of general practitioners, as well as the engagement of patients and family caregivers. Adequate support from healthcare organizations, health system arrangements, and the broader society is needed to enable effective interactions between general practitioners and patients and efficient delivery of the services required to detect and manage MCI.

The ‘Service Transformation Outline’ toolkit to assist in the design, comparison and replication of integrated care programmes

PurposeThe author is introducing a toolkit that can assist stakeholders to design, compare and replicate integrated care programmes, by making explicit their view on the transformations of care and cure services, according to a structured template. The purpose of this paper is to address this issue.Design/methodology/approachThe toolkit is made of two elements: a classification and a template. The author adopted a step-wise approach of semantic modelling to work out three layers of a classification in the domain of integration needs related to care and cure services. The third layer consists of 23 non-overlapping classes that fully cover that semantic domain. The classes are used to build a template to elicit the stakeholder's standpoint about the transformations involved in the deployment of a programme. The result is the «Outline» of the programme.FindingsSo far, in eight years the author applied the toolkit to 100+ programmes either to design, simulate or evaluate them, either to compare them to similar ones in the same or in different jurisdictions, and we refined the description of the classes according to that experience.Research limitations/implicationsThe objective of the toolkit is not to provide solutions, but to stimulate reflections on the transformations involved in a programme and their practical consequences in a precise context. In fact, the Outlines cannot be generalized: they are conceived to reflect the perspective of the stakeholders and thus are intrinsically subjective; in addition, they must be contingent, as they must depend on the local context in the particular timeframe. In case of similar initiatives in other localities, the Outlines must be filled in again by the local stakeholders; however, a subsequent comparison could help to explore similarities and motivated differences.Practical implicationsIdeally the stakeholders should use the Outline of the actual transformations in a programme as a reference to mediate between the principles and the methodologies provided by the «Models» and «Conceptual Frameworks» in the literature (e.g. Chronic Care Model, Rainbow Model, Development Model of Integrated Care Patient-Centered Medical Home and Maturity Models) and the deeper studies using the specific tools developed in their disciplines (e.g. on information modelling, process modelling, cost–benefit analysis and health technology assessment). The toolkit could have its role also in a multi-annual roadmap made of a sequence of programmes to cope with the urgent challenges on ageing, social changes and technological evolution, in synergy with regulations, budget, context maturity, critical success factors and local priorities.Originality/valueThe author argues that the approach of the structured Outline is unique, as the scoring mechanism to assess the relevance of the transformation within each class on the overall change brought by the whole programme into the health systems.

Study of Health in Primary Care of the Amazonas Population: Protocol for an Observational Study on Diabetes Management in Brazil.

BackgroundChanges in the profiles of patients have significant impacts on the health care system. Diabetes mellitus type 2 (T2DM) prevention and management should be studied in different contexts.ObjectiveThe Study of Health in Primary Care for the Amazonas Population (SAPPA) primarily aims to describe T2DM prevention and management actions offered by primary health care settings in Brazil and whether the care delivered is consistent with the chronic care model (CCM). Second, the study aims to examine the impact of T2DM management actions on health and lifestyle, and third, to understand how sociodemographic characteristics, health, and subjective outcomes impact diabetes management.MethodsAs part of this observational study, managers and health professionals complete a questionnaire containing information about T2DM prevention and management actions and CCM dimensions. During in-home visits, patients are asked about their health, lifestyle, sociodemographics, diabetes care, and subjective variables.ResultsA total of 34 managers, 1560 professional health workers, and 955 patients will be recruited. The data collection will be completed in October 2022.ConclusionsThe SAPPA is an observational study that intends to understand the T2DM management process in primary health care, including planning, execution, reach, and impact on patient motivation and adherence.International Registered Report Identifier (IRRID)DERR1-10.2196/37572

Challenges in detecting and managing mild cognitive impairment in primary care: a focus group study in Shanghai, China

IntroductionDetection of mild cognitive impairment (MCI) is essential in slowing progression to dementia. Primary care plays a vital role in detecting and managing MCI. The chronic care model (CCM) provides...

Chronic disease care integration into primary care services in sub-Saharan Africa: a ‘best fit’ framework synthesis and new conceptual model

ObjectiveTo examine the relevance of existing chronic care models to the integration of chronic disease care into primary care services in sub-Saharan Africa and determine whether additional context-specific model elements...

Validation and the Reliability of the ACIC Questionnaire in the Primary Health Care Setting: a Study from Bosnia and Herzegovina.

The aim of this study was to carry out the cultural adaptation and validation of the Assessment of Chronic Illness Care questionnaire (ACIC) in the Republika Srpska, Bosnia and Herzegovina. A validation study was conducted in two randomly selected primary health care centers in the Republika Srpska, Bosnia and Herzegovina, during March and April 2016. The study participants were all physicians working in family medicine departments during the study. Translation of the ACIC questionnaire version 3.5 was performed following the guidelines of the World Health Organization. The validity and reliability of the questionnaire were tested with face validity, construct validity, and internal consistency. The questionnaire was distributed to 66 family physicians. Missing values were negligible, therefore the criteria for factor analysis were met. Exploratory factor analysis confirmed that the questionnaire measured one factor. The Cronbach alpha coefficient (0.970) showed the excellent level of internal consistency of the questionnaire. The intraclass correlation coefficient (0.802) confirmed the good reliability of the questionnaire. The ACIC questionnaire can be used to assess the quality of chronic care in family medicine practice in Bosnia and Herzegovina. Further research is needed to explore how changes in healthcare care delivery impact changes in the Chronic Care Model domain.

Current and Emerging Trends in Diabetes Care and Education: 2021 National Practice and Workforce Survey.

The purpose of the National Practice Survey is to understand current trends related to the diabetes care and education specialist's integration into the full care team beyond formal diabetes self-management education and support services. The 2021 National Practice Survey (NPS2021) contained 61 questions for all respondents with an additional 56 questions pertaining to specific diabetes care and education segments. An anonymous survey was administered online to respondents who are diabetes care and education specialists or a part of the diabetes care team. Email lists were obtained from the Association of Diabetes Care & Education Specialists (ADCES) and the Certification Board for Diabetes Care and Education (CBDCE). Approximately 39,258 emails were sent, and 3357 were undeliverable, with 3797 surveys completed between February 9 to April 6, 2021, resulting in an 11% response rate. The response rate may have been affected by the COVID-19 public health emergency. Diabetes care and education specialists represent an interprofessional specialty of nurses, dietitians, physicians, pharmacists, health educators, and others. Many respondents reported holding either certification as a Certified Diabetes Care and Education Specialist (CDCES) or being Board Certified in Advanced Diabetes Management (BC-ADM). In addition, there appears to be a slight increase in those trained as a Lifestyle Coach to provide the National Diabetes Prevention Program (CDC Recognized National DPP) compared to NPS2017. Most respondents reported being Caucasian/White (84%), followed by Hispanic or Latinx (7%) and African American/Black and Asian/Asian American (at 4% each), like in previous surveys. Respondents reported diverse care delivery models, including traditional and nontraditional services, and expanded models of care such as population health/risk stratification models, the Chronic Care Model, Accountable Care Organizations, managed care, and others. The NPS2021 describes DCES workforce opportunities and challenges. Identifying and addressing those that impact the specialty's sustainability, diversity, and growth will guide strategies for the future workforce and their practice settings. Opportunities identified include embracing diabetes community care coordinators for person-centered delivery of care and education services and supporting frontline health care team members to increase competence and expertise in the prevention of type 2 diabetes, diabetes care, and education/support for related chronic diseases. In addition, as health care evolves, it creates opportunities for the DCESs to demonstrate a broader, key role as part of the diabetes care team.

The Effect of Educational Intervention Based on Chronic Care Model on the Management of Hypertension

The Effect of Educational Intervention Based on Chronic Care Model on the Management of Hypertension

A replicable, open-source, data integration method to support national practice-based research & quality improvement systems

ObjectivesThe Epilepsy Learning Healthcare System (ELHS) was created in 2018 to address measurable improvements in outcomes for people with epilepsy. However, fragmentation of data systems has been a major barrier for reporting and participation. In this study, we aimed to test the feasibility of an open-source Data Integration (DI) method that connects real-life clinical data to national research and quality improvement (QI) systems. MethodsThe ELHS case report forms were programmed as EPIC SmartPhrases at Mass General Brigham (MGB) in December 2018 and subsequently as EPIC SmartForms in June 2021 to collect actionable, standardized, structured epilepsy data in the electronic health record (EHR) for subsequent pull into the external national registry of the ELHS. Following the QI methodology in the Chronic Care Model, 39 providers, epileptologists and neurologists, incorporated the ELHS SmartPhrase into their clinical workflow, focusing on collecting diagnosis of epilepsy, seizure type according to the International League Against Epilepsy, seizure frequency, date of last seizure, medication adherence and side effects. The collected data was stored in the Enterprise Data Warehouse (EDW) without integration with external systems. We developed and validated a DI method that extracted the data from EDW using structured query language and later preprocessed using text mining. We used the ELHS data dictionary to match fields in the preprocessed notes to obtain the final structured dataset with seizure control information. For illustration, we described the data curated from the care period of 12/2018–12/2021. ResultsThe cohort comprised a total of 1806 patients with a mean age of 43 years old (SD: 17.0), where 57% were female, 80% were white, and 84% were non-Hispanic/Latino. Using our DI method, we automated the data mining, preprocessing, and exporting of the structured dataset into a local database, to be weekly accessible to clinicians and quality improvers. During the period of SmartPhrase implementation, there were 5168 clinic visits logged by providers documenting each patient’s seizure type and frequency. During this period, providers documented 59% patients having focal seizures, 35% having generalized seizures and 6% patients having another type. Of the cohort, 45% patients had private insurance. The resulting structured dataset was bulk uploaded via web interface into the external national registry of the ELHS. ConclusionsStructured data can be feasibly extracted from text notes of epilepsy patients for weekly reporting to a national learning healthcare system.