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Economou-Zavlanos NJ, Bessias S, Cary MP, Bedoya AD, Goldstein BA, Jelovsek JE, O’Brien CL, Walden N, Elmore M, Parrish AB, Elengold S, Lytle KS, Balu S, Lipkin ME, Shariff AI, Gao M, Leverenz D, Henao R, Ming DY, Gallagher DM, Pencina MJ, Poon EG. Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J Am Med Inform Assoc 2024; 31:705-713. [PMID: 38031481 PMCID: PMC10873841 DOI: 10.1093/jamia/ocad221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 10/06/2023] [Accepted: 11/03/2023] [Indexed: 12/01/2023] Open
Abstract
OBJECTIVE The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion. MATERIALS AND METHODS Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution. RESULTS An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center. DISCUSSION By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution. CONCLUSIONS We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations.
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Affiliation(s)
| | - Sophia Bessias
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
| | - Michael P Cary
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
- Duke University School of Nursing, Durham, NC 27710, United States
| | - Armando D Bedoya
- Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
| | - Benjamin A Goldstein
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States
| | - John E Jelovsek
- Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, NC 27710, United States
| | - Cara L O’Brien
- Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
| | - Nancy Walden
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
| | - Matthew Elmore
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
| | - Amanda B Parrish
- Office of Regulatory Affairs and Quality, Duke University School of Medicine, Durham, NC 27705, United States
| | - Scott Elengold
- Office of Counsel, Duke University, Durham, NC 27701, United States
| | - Kay S Lytle
- Duke University School of Nursing, Durham, NC 27710, United States
- Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States
| | - Suresh Balu
- Duke Institute for Health Innovation, Duke University, Durham, NC 27701, United States
| | - Michael E Lipkin
- Department of Urology, Duke University School of Medicine, Durham, NC 27710, United States
| | - Afreen Idris Shariff
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
- Duke Endocrine-Oncology Program, Duke University Health System, Durham, NC 27710, United States
| | - Michael Gao
- Duke Institute for Health Innovation, Duke University, Durham, NC 27701, United States
| | - David Leverenz
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
| | - Ricardo Henao
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States
- Department of Bioengineering, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | - David Y Ming
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
- Duke Department of Pediatrics, Duke University Health System, Durham, NC 27705, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, United States
| | - David M Gallagher
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
| | - Michael J Pencina
- Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States
| | - Eric G Poon
- Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States
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Uthappa DM, Ellett TL, Nyarko T, Rikhi A, Parente VM, Ming DY, White MJ. Interfacility Transfer Outcomes Among Children With Complex Chronic Conditions: Associations Between Patient-Level and Hospital-Level Factors and Transfer Outcomes. Hosp Pediatr 2024; 14:e91-e97. [PMID: 38213279 PMCID: PMC10823183 DOI: 10.1542/hpeds.2023-007425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
OBJECTIVES Determine patient- and referring hospital-level predictors of transfer outcomes among children with 1 or more complex chronic conditions (CCCs) transferred to a large academic medical center. METHODS We conducted a retrospective chart review of 2063 pediatric inpatient admissions from 2017 to 2019 with at least 1 CCC defined by International Classification of Diseases, Tenth Revision codes. Charts were excluded if patients were admitted via any route other than transfer from a referring hospital's emergency department or inpatient ward. Patient-level factors were race/ethnicity, payer, and area median income. Hospital-level factors included the clinician type initiating transfer and whether the referring-hospital had an inpatient pediatric ward. Transfer outcomes were rapid response within 24 hours of admission, Pediatric Early Warning Score at admission, and hours to arrival. Regression analyses adjusted for age were used to determine association between patient- and hospital-level predictors with transfer outcomes. RESULTS There were no significant associations between patient-level predictors and transfer outcomes. Hospital-level adjusted analyses indicated that transfers from hospitals without inpatient pediatrics wards had lower odds of ICU admission during hospitalization (odds ratio, 0.46; 95% confidence interval, 0.22-0.97) and shorter transfer times (β-coefficient, -2.54; 95% CI, -3.60 to -1.49) versus transfers from hospitals with inpatient pediatrics wards. There were no significant associations between clinician type and transfer outcomes. CONCLUSIONS For pediatric patients with CCCs, patient-level predictors were not associated with clinical outcomes. Transfers from hospitals without inpatient pediatric wards were less likely to require ICU admission and had shorter interfacility transfer times compared with those from hospitals with inpatient pediatrics wards.
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Affiliation(s)
| | | | | | - Aruna Rikhi
- Duke Clinical Research Institute, Durham, North Carolina
| | | | - David Y. Ming
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, North Carolina
- Division of Hospital Medicine, Department of Pediatrics
- Division of General Internal Medicine, Department of Medicine, Duke University Medical Center, Durham, North Carolina
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Feeney C, Chandler M, Platt A, Sun S, Setji N, Ming DY. Impact of a hospital service for adults with chronic childhood-onset disease: A propensity weighted analysis. J Hosp Med 2023; 18:1082-1091. [PMID: 37933708 DOI: 10.1002/jhm.13234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/08/2023]
Abstract
BACKGROUND Young adults with chronic childhood-onset diseases (CCOD) transitioning care from pediatrics to adult care are at high risk for readmission after hospital discharge. At our institution, we have implemented an inpatient service, the Med-Peds (MP) line, to improve transitions to adult care and reduce hospital utilization by young adults with CCOD. OBJECTIVE This study aimed to assess the effect of the MP line on length of stay (LOS) and 30-day readmission rates compared to other inpatient services. METHODS This was an observational, retrospective cohort analysis of patients admitted to the MP line compared to other hospital service lines over a 2-year period. To avoid potential confounding by indication for admission to the MP line, propensity score weighting methods were used. RESULTS The MP line cared for 302 patients with CCOD from June 2019 to July 2021. Compared to other service lines, there was a 33% reduction in relative risk of 30-day readmission (26.9% compared to 40.3%, risk ratio = 0.67, 95% confidence interval [CI] 0.55-0.81). LOS was 10% longer for the MP line (event time ratio (ETR): 1.10 95% CI 1.0-1.21) with median LOS 4.8 versus 4.5 days. Patients with sickle cell disease had less of a reduction in 30-day readmissions and longer LOS. CONCLUSION Hospitalization for young adults with CCOD on a MP service line was associated with lower 30-day readmission rates and longer LOS than hospitalization on other services. Further research is needed to assess which components of the line most contribute to decreased utilization.
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Affiliation(s)
- Colby Feeney
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Mark Chandler
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Alyssa Platt
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Shifeng Sun
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Noppon Setji
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - David Y Ming
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
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Ming DY, Wong W, Jones KA, Antonelli RC, Gujral N, Gonzales S, Rogers U, Ratliff W, Shah N, King HA. Feasibility of Implementation of a Mobile Digital Personal Health Record to Coordinate Care for Children and Youth With Special Health Care Needs in Primary Care: Protocol for a Mixed Methods Study. JMIR Res Protoc 2023; 12:e46847. [PMID: 37728977 PMCID: PMC10551780 DOI: 10.2196/46847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Electronic health record (EHR)-integrated digital personal health records (PHRs) via Fast Healthcare Interoperability Resources (FHIR) are promising digital health tools to support care coordination (CC) for children and youth with special health care needs but remain widely unadopted; as their adoption grows, mixed methods and implementation research could guide real-world implementation and evaluation. OBJECTIVE This study (1) evaluates the feasibility of an FHIR-enabled digital PHR app for CC for children and youth with special health care needs, (2) characterizes determinants of implementation, and (3) explores associations between adoption and patient- or family-reported outcomes. METHODS This nonrandomized, single-arm, prospective feasibility trial will test an FHIR-enabled digital PHR app's use among families of children and youth with special health care needs in primary care settings. Key app features are FHIR-enabled access to structured data from the child's medical record, families' abilities to longitudinally track patient- or family-centered care goals, and sharing progress toward care goals with the child's primary care provider via a clinician dashboard. We shall enroll 40 parents or caregivers of children and youth with special health care needs to use the app for 6 months. Inclusion criteria for children and youth with special health care needs are age 0-16 years; primary care at a participating site; complex needs benefiting from CC; high hospitalization risk in the next 6 months; English speaking; having requisite technology at home (internet access, Apple iOS mobile device); and an active web-based EHR patient portal account to which a parent or caregiver has full proxy access. Digital prescriptions will be used to disseminate study recruitment materials directly to eligible participants via their existing EHR patient portal accounts. We will apply an intervention mixed methods design to link quantitative and qualitative (semistructured interviews and family engagement panels with parents of children and youth with special health care needs) data and characterize implementation determinants. Two CC frameworks (Pediatric Care Coordination Framework; Patient-Centered Medical Home) and 2 evaluation frameworks (Consolidated Framework for Implementation Research; Technology Acceptance Model) provide theoretical foundations for this study. RESULTS Participant recruitment began in fall 2022, before which we identified >300 potentially eligible patients in EHR data. A family engagement panel in fall 2021 generated formative feedback from family partners. Integrated analysis of pretrial quantitative and qualitative data informed family-centered enhancements to study procedures. CONCLUSIONS Our findings will inform how to integrate an FHIR-enabled digital PHR app for children and youth with special health care needs into clinical care. Mixed methods and implementation research will help strengthen implementation in diverse clinical settings. The study is positioned to advance knowledge of how to use digital health innovations for improving care and outcomes for children and youth with special health care needs and their families. TRIAL REGISTRATION ClinicalTrials.gov NCT05513235; https://clinicaltrials.gov/study/NCT05513235. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/46847.
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Affiliation(s)
- David Y Ming
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Willis Wong
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States
| | - Kelley A Jones
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Richard C Antonelli
- Department of Pediatrics, Boston Children's Hospital, Harvard School of Medicine, Boston, MA, United States
| | - Nitin Gujral
- Innovation and Digital Health Accelerator, Boston Children's Hospital, Boston, MA, United States
| | - Sarah Gonzales
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Ursula Rogers
- AI Health, Duke University School of Medicine, Durham, NC, United States
| | - William Ratliff
- Duke Institute for Health Innovation, Duke University School of Medicine, Durham, NC, United States
| | - Nirmish Shah
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Heather A King
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veteran Affairs Health Care System, Durham, NC, United States
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Ming DY, Zhao C, Tang X, Chung RJ, Rogers UA, Stirling A, Economou-Zavlanos NJ, Goldstein BA. Predictive Modeling to Identify Children With Complex Health Needs At Risk for Hospitalization. Hosp Pediatr 2023; 13:357-369. [PMID: 37092278 PMCID: PMC10158078 DOI: 10.1542/hpeds.2022-006861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
BACKGROUND Identifying children at high risk with complex health needs (CCHN) who have intersecting medical and social needs is challenging. This study's objectives were to (1) develop and evaluate an electronic health record (EHR)-based clinical predictive model ("model") for identifying high-risk CCHN and (2) compare the model's performance as a clinical decision support (CDS) to other CDS tools available for identifying high-risk CCHN. METHODS This retrospective cohort study included children aged 0 to 20 years with established care within a single health system. The model development/validation cohort included 33 months (January 1, 2016-September 30, 2018) and the testing cohort included 18 months (October 1, 2018-March 31, 2020) of EHR data. Machine learning methods generated a model that predicted probability (0%-100%) for hospitalization within 6 months. Model performance measures included sensitivity, positive predictive value, area under receiver-operator curve, and area under precision-recall curve. Three CDS rules for identifying high-risk CCHN were compared: (1) hospitalization probability ≥10% (model-predicted); (2) complex chronic disease classification (using Pediatric Medical Complexity Algorithm [PMCA]); and (3) previous high hospital utilization. RESULTS Model development and testing cohorts included 116 799 and 27 087 patients, respectively. The model demonstrated area under receiver-operator curve = 0.79 and area under precision-recall curve = 0.13. PMCA had the highest sensitivity (52.4%) and classified the most children as high risk (17.3%). Positive predictive value of the model-based CDS rule (19%) was higher than CDS based on the PMCA (1.9%) and previous hospital utilization (15%). CONCLUSIONS A novel EHR-based predictive model was developed and validated as a population-level CDS tool for identifying CCHN at high risk for future hospitalization.
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Affiliation(s)
- David Y. Ming
- Departments of Pediatrics
- Medicine
- Population Health Sciences
| | | | - Xinghong Tang
- Janssen Research & Development, LLC, Raritan, New Jersey
| | | | - Ursula A. Rogers
- Duke AI Health, Duke University School of Medicine, Durham, North Carolina
| | - Andrew Stirling
- Duke AI Health, Duke University School of Medicine, Durham, North Carolina
| | | | - Benjamin A. Goldstein
- Departments of Pediatrics
- Population Health Sciences
- Biostatistics & Bioinformatics, and
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Frush JM, Ming DY, Crego N, Paden ME, Jones-Hepler B, Misiewicz R, Jarrett VA, Docherty SL. Caregiver Perspectives on Telemedicine for Postdischarge Care for Children With Medical Complexity: A Qualitative Study. J Pediatr Health Care 2023:S0891-5245(22)00358-3. [PMID: 36670018 DOI: 10.1016/j.pedhc.2022.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/29/2022] [Indexed: 01/20/2023]
Abstract
INTRODUCTION The objectives of this study were to describe the perspectives of caregivers of children with medical complexity on telemedicine video visits (TMVV) for posthospitalization care and determine whether TMVV may be a viable alternative to in-person follow-up. METHOD Our qualitative descriptive study included semistructured telephone interviews with 12 caregivers. Data analysis was conducted using an adapted Colaizzi's descriptive phenomenological method for thematic construction. RESULTS Results were organized into four themes describing caregivers' experiences with TMVV: (1) promoted caregiver self-efficacy and sense of independence; (2) TMVV as convenient, cost-effective, comprehensive, and acceptable; (3) supported caregiver decision-making and problem-solving; and (4) fostered delivery of family-centered care. DISCUSSION Although in-person visits are necessary for some circumstances, TMVV can serve as a convenient and acceptable alternative for posthospitalization follow-up in children with medical complexity. Overall, caregivers in this study were satisfied with the quality of care and individualized experience of TMVV.
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Affiliation(s)
- Jennifer M Frush
- Jennifer M. Frush, Housestaff, Department of Emergency Medicine, Boston Medical Center, Boston, MA.
| | - David Y Ming
- David Y. Ming, Associate Professor, Department of Pediatrics, Department of Medicine, and Department of Population Health, School of Medicine, Duke University, Durham, NC
| | - Nancy Crego
- Nancy Crego, Assistant Professor, School of Nursing, Duke University, Durham, NC
| | - Mary E Paden
- Mary E. Paden, Consulting Associate, School of Nursing, Duke University, Durham, NC
| | - Bonnie Jones-Hepler
- Bonnie Jones-Hepler, PhD Student, School of Nursing, Duke University, Durham, NC
| | - Remi Misiewicz
- Remi Misiewicz, PhD Student, School of Nursing, Duke University, Durham, NC
| | - Valerie A Jarrett
- Valerie A. Jarrett, Program Coordinator, Department of Pediatrics, Duke University School of Medicine, Durham, NC
| | - Sharron L Docherty
- Sharron L. Docherty, Associate Professor, Department of Pediatrics, Duke University School of Medicine, and Duke University School of Nursing, Durham, NC
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Sandhu S, deJong NA, Crew C, Hurewitz S, Prattipati S, Nguyen D, Huang R, Morreale MC, Cleveland S, Lail J, Moore C, Ming DY. Catalyzing Cross-Sector Collaboration: Lessons from a Virtual Pediatric Complex Care Coalition. Prog Community Health Partnersh 2023; 17:295-305. [PMID: 37462558 DOI: 10.1353/cpr.2023.a900210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
BACKGROUND Children with complex health needs (CCHN) have intersecting medical, behavioral health, and social needs. Unfortunately, fragmentation across health and social services sectors often results in uncoordinated care for CCHN and their families. OBJECTIVE The purpose of this article is to describe the creation of a statewide cross-sector partnership, the Children's Complex Care Coalition of North Carolina, to identify and act on opportunities for system-level improvements in the care of CCHN. METHODS We applied a virtual community engagement approach to form an advisory committee of cross-sector collaborators; systematically identify priorities most important and urgent to collaborators for improving systems of care; and host a series of virtual convenings involving more than 90 attendees from across the state to operationalize collaborator-identified priorities into actionable next steps. LESSONS LEARNED Key facilitators of success for the Children's Complex Care Coalition of North Carolina partnership were investing time in building trusting relationships, particularly with families of CCHN, and aligning goals and priorities with existing local and regional efforts. Challenges included incorporating traditionally under-represented perspectives, right-sizing virtual convening attendance and number of topics covered, and navigating technological difficulties in a virtual environment. CONCLUSIONS Health systems can catalyze the formation of cross-sector coalitions and community partnerships to advance complex care. Virtual convenings with interactive activities and participatory structures can be an efficient medium to connect coalition members and elicit actionable recommendations for system-level improvements that address the needs of community members.
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Ming DY, Jones KA, White MJ, Pritchard JE, Hammill BG, Bush C, Jackson GL, Raman SR. Healthcare Utilization for Medicaid-Insured Children with Medical Complexity: Differences by Sociodemographic Characteristics. Matern Child Health J 2022; 26:2407-2418. [PMID: 36198851 PMCID: PMC10026355 DOI: 10.1007/s10995-022-03543-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To compare differences in healthcare utilization and costs for Medicaid-insured children with medical complexity (CMC) by race/ethnicity and rurality. METHODS Retrospective cohort of North Carolina (NC) Medicaid claims for children 3-20 years old with 3 years continuous Medicaid coverage (10/1/2015-9/30/2018). Exposures were medical complexity, race/ethnicity, and rurality. Three medical complexity levels were: without chronic disease, non-complex chronic disease, and complex chronic disease; the latter were defined as CMC. Race/ethnicity was self-reported in claims; we defined rurality by home residence ZIP codes. Utilization and costs were summarized for 1 year (10/1/2018-9/30/2019) by complexity level classification and categorized as acute care (hospitalization, emergency [ED]), outpatient care (primary, specialty, allied health), and pharmacy. Per-complexity group utilization rates (per 1000 person-years) by race/ethnicity and rurality were compared using adjusted rate ratios (ARR). RESULTS Among 859,166 Medicaid-insured children, 118,210 (13.8%) were CMC. Among CMC, 36% were categorized as Black non-Hispanic, 42.7% White non-Hispanic, 14.3% Hispanic, and 35% rural. Compared to White non-Hispanic CMC, Black non-Hispanic CMC had higher hospitalization (ARR = 1.12; confidence interval, CI 1.08-1.17) and ED visit (ARR = 1.17; CI 1.16-1.19) rates; Hispanic CMC had lower ED visit (ARR = 0.77; CI 0.75-0.78) and hospitalization rates (ARR = 0.79; CI 0.73-0.84). Black non-Hispanic and Hispanic CMC had lower outpatient visit rates than White non-Hispanic CMC. Rural CMC had higher ED (ARR = 1.13; CI 1.11-1.15) and lower primary care utilization rates (ARR = 0.87; CI 0.86-0.88) than urban CMC. DISCUSSION Healthcare utilization varied by race/ethnicity and rurality for Medicaid-insured CMC. Further studies should investigate mechanisms for these variations and expand higher value, equitable care delivery for CMC.
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Affiliation(s)
- David Y Ming
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
- Department of Pediatrics, Duke University School of Medicine, Box 102376, Durham, NC, 27710, USA.
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
| | - Kelley A Jones
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Michelle J White
- Department of Pediatrics, Duke University School of Medicine, Box 102376, Durham, NC, 27710, USA
| | - Jessica E Pritchard
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Bradley G Hammill
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | | | - George L Jackson
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
- Department of Family Medicine and Community Health, Duke University School of Medicine, Durham, NC, USA
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Sudha R Raman
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
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Feeney CD, Platt A, Rhodes J, Marcantonio Y, Patel-Nguyen S, White T, Wilson JA, Pendergast J, Ming DY. Redesigning Care of Hospitalized Young Adults With Chronic Childhood-Onset Disease. Cureus 2022; 14:e27898. [PMID: 36110484 PMCID: PMC9464098 DOI: 10.7759/cureus.27898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 08/11/2022] [Indexed: 11/22/2022] Open
Abstract
Background Young adults with chronic childhood-onset disease (CCOD) are routinely admitted to internal medicine hospitalist services, yet most lack transition preparation to adult care. Providers and patients feel the strain of admissions to adult services in part due to their medical and social complexity. Methods We performed a descriptive study of a care redesign project for young adults with CCOD hospitalized at a large, tertiary care academic hospital. We describe the process of implementation of the Med-Peds (MP) service line and characterize patients cared for by the service. We measured and analyzed patient demographics, process implementation, healthcare screening, and healthcare utilization data. Results During the 16 months of the study period, 254 patients were cared for by the MP service line, accounting for 385 hospitalizations. The most common CCODs were sickle cell disease (22.4%) and type 1 diabetes (14.6%). The majority (76%) of patients completed transition readiness assessment, and 38.6% completed social determinant of health (SDH) screening during their admission. Patients had high prevalence of SDH with 66.7% having an unmet social need. The average length of stay was 6.6 days and the average 30-day readmission rate was 20.0%. Conclusions There is opportunity to redesign the inpatient care of young adult patients with CCOD. The MP service line is a care model that can be integrated into existing hospital medicine teams with MP physicians. Hospitals should consider redesigning care for young adults with CCOD to meet the transitional and social needs unique to this patient population.
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Sandhu S, Ming DY, Crew C, Morreale MC, Cleveland S, Lail J, deJong NA. Identifying Priorities to Improve the System of Care for Children With Complex Health Needs in North Carolina: Process and Outcomes of Systematic Stakeholder Engagement. Acad Pediatr 2022; 22:1041-1048. [PMID: 35091096 PMCID: PMC9314463 DOI: 10.1016/j.acap.2022.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 01/12/2022] [Accepted: 01/16/2022] [Indexed: 11/01/2022]
Abstract
OBJECTIVE Children with complex health needs (CCHN) have both medical (eg, chronic conditions) and health-related social needs (eg, potentially adverse social determinants of health) that require ongoing health care and support from multiple community service providers. National standards developed for populations defined by health needs (CYSHCN) provide a framework for stakeholders to plan system-level improvements in care delivery for CCHN, but improvement efforts should reflect the priorities of their families and providers. This article describes a process of prioritizing system-level efforts to improve the health and well-being of CCHN and families in North Carolina (NC), using systematic stakeholder engagement and modified Delphi expert ratings. METHODS We surveyed stakeholders with experience caring for CCHN using an open-ended, 3-item instrument to identify opportunities to improve systems of care. Using directed qualitative content analysis, we synthesized responses into a master list of potential improvement topics. Using a modified Delphi approach, a 16-member advisory committee rated all topics for importance and urgency, on 9-point Likert scales over 2 rounds; then ratings for each topic were ranked (low, medium, high) to establish relative priority. RESULTS Forty seven individuals from 31 counties around NC provided survey responses, yielding 59 improvement topics in 10 domains. Through the modified Delphi method process, 21 topics (36%) received the highest rankings, largely representing access to community- and home-based services, equity, and enhancement of the pediatric workforce. CONCLUSIONS Priorities identified by stakeholders will inform advocacy, policy, and improvement efforts. Next steps for the coalition include developing improvement projects to implement stakeholder-recommended actions for the highest-priority topics.
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Affiliation(s)
- Sahil Sandhu
- Duke-Margolis Center for Health Policy, 100 Fuqua Drive, Box 90120, Durham, North Carolina 27708, USA
| | - David Y. Ming
- Departments of Pediatrics, Medicine, and Population Health Sciences, Duke University School of Medicine, DUMC Box 100800, Durham, North Carolina, USA
| | - Carter Crew
- Children’s Health and Discovery Initiative, Duke University School of Medicine, 701 Main Street Durham, North Carolina 27701, USA
| | - Madlyn C. Morreale
- Legal Aid of North Carolina, 224 S. Dawson St., Raleigh, North Carolina 27601, USA,Department of Pediatrics, UNC School of Medicine, 231 MacNider Hall, CB 7225, 321 S. Columbia Street, Chapel Hill, North Carolina 27599, USA
| | - Shea Cleveland
- Family Resource Center South Atlantic Family to Family Health Information Center, Derrick W. Byrd. 3825 Barrett Drive. Suite 104. Raleigh, North Carolina 27609, USA,Family Support Network of North Carolina, 325 Pittsboro St, UNC Campus Box 3550, Chapel Hill, North Carolina 27599, USA
| | - Jennifer Lail
- Jennifer Lail, LLC, 511 S Mangum St #1096, Durham, North Carolina 27701, USA
| | - Neal A. deJong
- Department of Pediatrics, UNC School of Medicine, 231 MacNider Hall, CB 7225, 321 S. Columbia Street, Chapel Hill, North Carolina 27599, USA
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11
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Lian T, Reid H, Rader A, Dewitt-Feldman S, Hezarkhani E, Gu E, Scott M, Kutzer K, Sandhu S, Crowder C, Ito K, Eisenson H, Bettger JP, Shaw RJ, Lewinski AA, Ming DY, Bosworth HB, Zullig LL, Batch BC, Drake C. A Tailored SMS Text Message Based Intervention to Facilitate Patient Access to Referred Community-Based Social Needs Resources: Protocol for a Feasibility and Acceptability Pilot (Preprint). JMIR Res Protoc 2022; 11:e37316. [PMID: 36222790 PMCID: PMC9597426 DOI: 10.2196/37316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 08/18/2022] [Accepted: 08/30/2022] [Indexed: 11/15/2022] Open
Abstract
Background Health care providers are increasingly screening patients for unmet social needs (eg, food, housing, transportation, and social isolation) and referring patients to relevant community-based resources and social services. Patients’ connection to referred services is often low, however, suggesting the need for additional support to facilitate engagement with resources. SMS text messaging presents an opportunity to address barriers related to contacting resources in an accessible, scalable, and low-cost manner. Objective In this multi-methods pilot study, we aim to develop an automated SMS text message–based intervention to promote patient connection to referred social needs resources within 2 weeks of the initial referral and to evaluate its feasibility and patient acceptability. This protocol describes the intervention, conceptual underpinnings, study design, and evaluation plan to provide a detailed illustration of how SMS technology can complement current social needs screening and referral practice patterns without disrupting care. Methods For this pilot prospective cohort study, this SMS text message–based intervention augments an existing social needs screening, referral, and navigation program at a federally qualified health center. Patients who received at least one referral for any identified unmet social need are sent 2 rounds of SMS messages over 2 weeks. The first round consists of 5-10 messages that deliver descriptions of and contact information for the referred resources. The second round consists of 2 messages that offer a brief reminder to contact the resources. Participants will evaluate the intervention via a survey and a semistructured interview, informed by an adapted technology acceptance model. Rapid qualitative and thematic analysis will be used to extract themes from the responses. Primary outcomes are implementation feasibility and patient acceptability. Secondary outcomes relate to intervention effectiveness: self-reported attempt to connect and successful connection to referred resources 2 weeks after the initial referral encounter. Results The study received regulatory approval in May 2021, and we anticipate enrolling 15-20 participants for this initial pilot. Conclusions This protocol presents detailed implementation methods about a novel automated SMS intervention for social care integration within primary care. By sharing the study protocol early, we intend to facilitate the development and adoption of similar tools across different clinical settings, as more health care providers seek to address the unmet social needs of patients. Study findings will provide practical insights into the design and implementation of SMS text message–based interventions to improve social and medical care coordination. International Registered Report Identifier (IRRID) DERR1-10.2196/37316
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Affiliation(s)
- Tyler Lian
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
| | - Hadley Reid
- School of Medicine, Duke University, Durham, NC, United States
| | - Abigail Rader
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
| | | | - Elmira Hezarkhani
- Trinity College of Arts & Science, Duke University, Durham, NC, United States
| | - Elizabeth Gu
- Trinity College of Arts & Science, Duke University, Durham, NC, United States
| | - Malik Scott
- Trinity College of Arts & Science, Duke University, Durham, NC, United States
| | - Kate Kutzer
- Trinity College of Arts & Science, Duke University, Durham, NC, United States
| | - Sahil Sandhu
- Trinity College of Arts & Science, Duke University, Durham, NC, United States
| | | | - Kristin Ito
- Lincoln Community Health Center, Durham, NC, United States
| | - Howard Eisenson
- Lincoln Community Health Center, Durham, NC, United States
- Department of Family Medicine and Community Health, Duke University School of Medicine, Durham, NC, United States
| | - Janet Prvu Bettger
- Department of Orthopaedic Surgery, Duke University School of Medicine, Durham, NC, United States
| | - Ryan J Shaw
- Duke University School of Nursing, Durham, NC, United States
| | - Allison A Lewinski
- Duke University School of Nursing, Durham, NC, United States
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Medical Center, Durham, NC, United States
| | - David Y Ming
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States
| | - Hayden B Bosworth
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Medical Center, Durham, NC, United States
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Leah L Zullig
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Medical Center, Durham, NC, United States
| | - Bryan C Batch
- Department of Medicine, Division of Endocrinology, Duke University School of Medicine, Durham, NC, United States
| | - Connor Drake
- Department of Population Health Science, Duke University School of Medicine, Durham, NC, United States
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Medical Center, Durham, NC, United States
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12
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Ming DY, Li T, Ross MH, Frush J, He J, Goldstein BA, Jarrett V, Krohl N, Docherty SL, Turley CB, Bosworth HB. Feasibility of Post-hospitalization Telemedicine Video Visits for Children With Medical Complexity. J Pediatr Health Care 2022; 36:e22-e35. [PMID: 34879986 DOI: 10.1016/j.pedhc.2021.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/01/2021] [Accepted: 10/03/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVES To evaluate feasibility and acceptability of post-hospitalization telemedicine video visits (TMVV) during hospital-to-home transitions for children with medical complexity (CMC); and explore associations with hospital utilization, caregiver self-efficacy (CSE), and family self-management (FSM). METHOD This non-randomized pilot study assigned CMC (n=28) to weekly TMVV for four weeks post-hospitalization; control CMC (n=20) received usual care without telemedicine. Feasibility was measured by time to connection and proportion of TMVV completed; acceptability was measured by parent-reported surveys. Pre/post-discharge changes in CSE, FSM, and hospital utilization were assessed. RESULTS 64 TMVV were completed; 82 % of patients completed 1 TMVV; 54 % completed four TMVV. Median time to TMVV connection was 1 minute (IQR=2.5). Parents reported high acceptability of TMVV (mean 6.42; 1 -7 scale). CSE and FSM pre/post-discharge were similar for both groups; utilization declined in both groups post-discharge. DISCUSSION Post-hospitalization TMVV for CMC were feasible and acceptable during hospital-to-home transitions.
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13
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Ming DY, Jones KA, Sainz E, Tkach H, Stewart A, Cram A, Morreale MC, Dizon S, deJong NA. Feasibility of implementing systematic social needs assessment for children with medical complexity. Implement Sci Commun 2021; 2:130. [PMID: 34802465 PMCID: PMC8606226 DOI: 10.1186/s43058-021-00237-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 11/05/2021] [Indexed: 11/21/2022] Open
Abstract
Background Children with medical complexity (CMC) have inter-related health and social needs; however, interventions to identify and respond to social needs have not been adapted for CMC. The objective of this study was to evaluate the feasibility of implementing social needs screening and assessment within pediatric complex care programs. Methods We implemented systematic social needs assessment for CMC (SSNAC) at two tertiary care centers in three phases: (1) pre-implementation, (2) implementation, and (3) implementation monitoring. We utilized a multifaceted implementation package consisting of discrete implementation strategies within each phase. In phase 1, we adapted questions from evidence-informed screening tools into a 21-item SSNAC questionnaire, and we used published frameworks to inform implementation readiness and process. In phases 2–3, clinical staff deployed the SSNAC questionnaire to parents of CMC in-person or by phone as part of usual care and adapted to local clinical workflows. Staff used shared decision-making with parents and addressed identified needs by providing information about available resources, offering direct assistance, and making referrals to community agencies. Implementation outcomes included fidelity, feasibility, acceptability, and appropriateness. Results Observations from clinical staff characterized fidelity to use of the SSNAC questionnaire, assessment template, and shared decision-making for follow-up on unmet social needs. Levels of agreement (5-point Likert scale; 1 = completely disagree; 5 = completely agree) rated by staff for key implementation outcomes were moderate to high for acceptability (mean = 4.7; range = 3–5), feasibility (mean = 4.2; range = 3–5), and appropriateness (mean = 4.6; range = 4-5). 49 SSNAC questionnaires were completed with a 91% response rate. Among participating parents, 37 (76%) reported ≥ 1 social need, including food/nutrition benefits (41%), housing (18%), and caregiver needs (29%). Staff responses included information provision (41%), direct assistance (30%), and agency referral (30%). Conclusions It was feasible for tertiary care center-based pediatric complex care programs to implement a standardized social needs assessment for CMC to identify and address parent-reported unmet social needs. Supplementary Information The online version contains supplementary material available at 10.1186/s43058-021-00237-3.
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Affiliation(s)
- David Y Ming
- Department of Pediatrics, DUMC, Duke University School of Medicine, Box 3352, Durham, NC, 27710, USA. .,Department of Medicine, Duke University School of Medicine, 2301 Erwin Rd, Durham, NC, 27710, USA. .,Department of Population Health Sciences, Duke University School of Medicine, 215 Morris St, Durham, NC, 27701, USA.
| | - Kelley A Jones
- Department of Population Health Sciences, Duke University School of Medicine, 215 Morris St, Durham, NC, 27701, USA
| | - Elizabeth Sainz
- Department of Pediatrics, DUMC, Duke University School of Medicine, Box 3352, Durham, NC, 27710, USA
| | - Heidie Tkach
- Department of Pediatrics, University of North Carolina School of Medicine, 260 MacNider Building, CB#7220, Chapel Hill, NC, 27599, USA
| | - Amy Stewart
- Department of Pediatrics, University of North Carolina School of Medicine, 260 MacNider Building, CB#7220, Chapel Hill, NC, 27599, USA
| | - Ashley Cram
- University of North Carolina School of Public Health, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Madlyn C Morreale
- Department of Pediatrics, University of North Carolina School of Medicine, 260 MacNider Building, CB#7220, Chapel Hill, NC, 27599, USA.,Legal Aid of North Carolina, 224 S. Dawson St, Raleigh, NC, 27601, USA
| | - Samantha Dizon
- Department of Pediatrics, DUMC, Duke University School of Medicine, Box 3352, Durham, NC, 27710, USA.,Department of Medicine, Duke University School of Medicine, 2301 Erwin Rd, Durham, NC, 27710, USA
| | - Neal A deJong
- Department of Pediatrics, University of North Carolina School of Medicine, 260 MacNider Building, CB#7220, Chapel Hill, NC, 27599, USA
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14
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Sandhu S, deJong NA, Ming DY. Strategies for Reimagining Complex Care. J Gen Intern Med 2021; 36:2856-2857. [PMID: 34173201 PMCID: PMC8390575 DOI: 10.1007/s11606-021-06956-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 05/27/2021] [Indexed: 11/25/2022]
Affiliation(s)
- Sahil Sandhu
- Duke-Margolis Center for Health Policy, Durham, NC, USA
| | - Neal A deJong
- Department of Pediatrics, UNC School of Medicine, Chapel Hill, NC, USA
| | - David Y Ming
- Departments of Medicine, Pediatrics, and Population Health Sciences, Duke University School of Medicine, DUMC Box 102376, Durham, NC, 27710, USA.
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15
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Ross MH, Parnell LS, Spears TG, Ming DY. Telemedicine Video Visits for Children with Medical Complexity in a Structured Clinical Complex Care Program. Glob Pediatr Health 2020; 7:2333794X20952196. [PMID: 33150195 PMCID: PMC7585889 DOI: 10.1177/2333794x20952196] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/30/2020] [Accepted: 07/26/2020] [Indexed: 12/03/2022] Open
Affiliation(s)
| | | | | | - David Y Ming
- Duke University School of Medicine, Durham, NC, USA
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16
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Ming DY, Ehlenbach ML, Falco C, Coller RJ. The Intersection of Complex Care and Hospital Medicine: Opportunities to Advance Health for Chronically Ill Populations. Hosp Pediatr 2020; 10:715-718. [PMID: 32718930 DOI: 10.1542/hpeds.2020-0079] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Affiliation(s)
- David Y Ming
- Departments of Medicine and Pediatrics, School of Medicine, Duke University, Durham, North Carolina;
| | - Mary L Ehlenbach
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin; and
| | - Carla Falco
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas
| | - Ryan J Coller
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin; and
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17
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Ming DY, Jackson GL, Sperling J, Gray M, Wyman Roth N, Spears T, Parente V, Bosworth H. Mobile Complex Care Plans to Enhance Parental Engagement for Children With Medical Complexity. Clin Pediatr (Phila) 2019; 58:34-41. [PMID: 30295060 DOI: 10.1177/0009922818805241] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Care plans can reduce care fragmentation for children with medical complexity (CMC); however, implementation is challenging. Mobile health innovations could improve implementation. This mixed methods study's objectives were to (1) evaluate feasibility of mobile complex care plans (MCCPs) for CMC enrolled in a complex care program and (2) study MCCPs' impact on parent engagement, parent experience, and care coordination. MCCPs were individualized, updated quarterly, integrated within the electronic health record, and visible on parents' mobile devices via an online portal. In 1 year (September 1, 2016, to August 31, 2017), 94% of eligible patients (n = 47) received 162 MCCPs. Seventy-four percent of parents (n = 35) reviewed MCCPs online. Forty-six percent of these parents (n = 16) sent a follow-up message, and the care team responded within 8 hours (median time = 7.2 hours). In interviews, parents identified MCCPs as an important reference and communication tool. MCCPs for CMC in a complex care program were feasible, facilitated parental engagement, and delivered timely communication.
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Affiliation(s)
- David Y Ming
- 1 Department of Pediatrics, Division of Pediatric Hospital Medicine, Duke University School of Medicine, Durham, NC, USA.,2 Department of Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, NC, USA
| | - George L Jackson
- 2 Department of Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, NC, USA.,3 Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.,4 Center for Health Services Research in Primary Care, Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Jessica Sperling
- 5 Social Science Research Institute (SSRI), Education and Human Development Incubator (EHDi), Duke University, Durham, NC, USA
| | - Megan Gray
- 5 Social Science Research Institute (SSRI), Education and Human Development Incubator (EHDi), Duke University, Durham, NC, USA
| | - Noelle Wyman Roth
- 5 Social Science Research Institute (SSRI), Education and Human Development Incubator (EHDi), Duke University, Durham, NC, USA
| | - Tracy Spears
- 6 Department of Pediatrics, Division of Quantitative Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Victoria Parente
- 1 Department of Pediatrics, Division of Pediatric Hospital Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Hayden Bosworth
- 3 Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.,4 Center for Health Services Research in Primary Care, Durham Veterans Affairs Health Care System, Durham, NC, USA.,7 Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
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Clay AS, Ming DY, Knudsen NW, Engle DL, Grochowski CO, Andolsek KM, Chudgar SM. CaPOW! Using Problem Sets in a Capstone Course to Improve Fourth-Year Medical Students' Confidence in Self-Directed Learning. Acad Med 2017; 92:380-384. [PMID: 27119334 DOI: 10.1097/acm.0000000000001193] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
PROBLEM Despite the importance of self-directed learning (SDL) in the field of medicine, individuals are rarely taught how to perform SDL or receive feedback on it. Trainee skill in SDL is limited by difficulties with self-assessment and goal setting. APPROACH Ninety-two graduating fourth-year medical students from Duke University School of Medicine completed an individualized learning plan (ILP) for a transition-to-residency Capstone course in spring 2015 to help foster their skills in SDL. Students completed the ILP after receiving a personalized report from a designated faculty coach detailing strengths and weaknesses on specific topics (e.g., pulmonary medicine) and clinical skills (e.g., generating a differential diagnosis). These were determined by their performance on 12 Capstone Problem Sets of the Week (CaPOWs) compared with their peers. Students used transitional-year milestones to self-assess their confidence in SDL. OUTCOMES SDL was successfully implemented in a Capstone course through the development of required clinically oriented problem sets. Coaches provided guided feedback on students' performance to help them identify knowledge deficits. Students' self-assessment of their confidence in SDL increased following course completion. However, students often chose Capstone didactic sessions according to factors other than their CaPOW performance, including perceived relevance to planned specialty and session timing. NEXT STEPS Future Capstone curriculum changes may further enhance SDL skills of graduating students. Students will receive increased formative feedback on their CaPOW performance and be incentivized to attend sessions in areas of personal weakness.
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Affiliation(s)
- Alison S Clay
- A.S. Clay is assistant professor of surgery and medicine, Duke University School of Medicine, Durham, North Carolina. D.Y. Ming is assistant professor of medicine and pediatrics, Duke University School of Medicine, Durham, North Carolina. N.W. Knudsen is professor of anesthesiology, Duke University School of Medicine, Durham, Durham, North Carolina. D.L. Engle is director of assessment and evaluation, Duke University School of Medicine, Durham, North Carolina. C.O. Grochowski is associate dean for curricular affairs, Duke University School of Medicine, Durham, North Carolina. K.M. Andolsek is professor of community and family medicine, Duke University School of Medicine, Durham, North Carolina. S.M. Chudgar is assistant professor of medicine, Duke University School of Medicine, Durham, North Carolina
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Ming DY, Chen LF, Miller BA, Anderson DJ. The impact of depth of infection and postdischarge surveillance on rate of surgical-site infections in a network of community hospitals. Infect Control Hosp Epidemiol 2012; 33:276-82. [PMID: 22314065 DOI: 10.1086/664053] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To describe the epidemiology of surgical-site infections (SSIs) in community hospitals and to explore the impact of depth of SSI, healthcare location at the time of diagnosis, and variations in surveillance practices on the overall rate of SSI. DESIGN Retrospective cohort study. SETTING Thirty-seven community hospitals in the southeastern United States. PATIENTS Consecutive sample of patients undergoing surgical procedures between July 1, 2007, and December 31, 2008. METHODS ANOVA was used to compare rates of SSIs, and the F test was used to compare the distribution of rates of SSIs. Wilcoxon Signed Rank test [corrected] was used to test for differences in performance rankings of hospitals. RESULTS Following 177,706 surgical procedures, 1,919 SSIs were identified (incidence, 1.08 per 100 procedures). Sixty-four percent (1,223 of 1,919) of these were identified as complex SSIs; 87% of the complex SSIs were diagnosed in inpatient settings. The median proportion of superficial-incisional SSIs was 37% (interquartile range, 29.6%-49.5%). Postdischarge SSI surveillance was variable, with 58% of responding hospitals using surgeon letters. As reporting focus was narrowed from all SSIs to complex SSIs (incidence, 0.69 per 100 procedures) and, finally, to complex SSIs diagnosed in the inpatient setting (incidence, 0.51 per 100 procedures), variance in rates changed significantly ([Formula: see text]). Performance ranking of individual hospitals, based on rates of SSIs, differed significantly, depending on the reporting method utilized ([Formula: see text]). CONCLUSIONS Inconsistent reporting methods focused on variable depths of infection and healthcare location at time of diagnosis significantly impact rates of SSI, distribution of rates of SSI, and hospital comparative-performance rankings. We believe that public reporting of SSI rates should be limited to complex SSIs diagnosed in the inpatient setting.
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Affiliation(s)
- David Y Ming
- Duke University Medical Center, Duke Program for Infection Prevention and Healthcare Epidemiology, Duke Infection Control Outreach Network (DICON), Duke University Prevention Epicenter Program, Durham, NC 27710, USA
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Abstract
Paraquat is an herbicide that is highly toxic to humans. Pediatric ingestion has become uncommon in the United States because of preventative efforts. We report here an unintentional, fatal paraquat ingestion by an 8-year-old child. Storage in an inappropriate container, confusion between herbicide trade names, nonspecific symptoms, and a delay in follow-up produced challenges in the diagnosis. In the absence of a clear history of ingestion, paraquat poisoning should be suspected in children who develop skin and mucous membrane burns, gastrointestinal symptoms, acute kidney injury, and respiratory failure.
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Affiliation(s)
- Jerome G Chen
- Department of Pediatrics, Duke University Medical Center, DUMC Box 3046, Durham, NC 27710, USA.
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