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Jurczuk M, Thakar R, Carroll FE, Phillips L, van der Meulen J, Gurol-Urganci I, Sevdalis N. Design and management considerations for control groups in hybrid effectiveness-implementation trials: Narrative review & case studies. FRONTIERS IN HEALTH SERVICES 2023; 3:1059015. [PMID: 36926502 PMCID: PMC10012616 DOI: 10.3389/frhs.2023.1059015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/06/2023] [Indexed: 03/12/2023]
Abstract
Hybrid effectiveness-implementation studies allow researchers to combine study of a clinical intervention's effectiveness with study of its implementation with the aim of accelerating the translation of evidence into practice. However, there currently exists limited guidance on how to design and manage such hybrid studies. This is particularly true for studies that include a comparison/control arm that, by design, receives less implementation support than the intervention arm. Lack of such guidance can present a challenge for researchers both in setting up but also in effectively managing participating sites in such trials. This paper uses a narrative review of the literature (Phase 1 of the research) and comparative case study of three studies (Phase 2 of the research) to identify common themes related to study design and management. Based on these, we comment and reflect on: (1) the balance that needs to be struck between fidelity to the study design and tailoring to emerging requests from participating sites as part of the research process, and (2) the modifications to the implementation strategies being evaluated. Hybrid trial teams should carefully consider the impact of design selection, trial management decisions, and any modifications to implementation processes and/or support on the delivery of a controlled evaluation. The rationale for these choices should be systematically reported to fill the gap in the literature.
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Affiliation(s)
- Magdalena Jurczuk
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Ranee Thakar
- Obstetrics & Gynaecology, Croydon University Hospitals NHS Trust, London, United Kingdom
| | - Fran E Carroll
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Lizzie Phillips
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Maternity Services, University Hospital Plymouth NHS Trust, Plymouth, United Kingdom
| | - Jan van der Meulen
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ipek Gurol-Urganci
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nick Sevdalis
- Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, United Kingdom
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Nathalie H, Steele V, Miguel M, Laura M, Brigit H, Andrea B, Cohen Deborah J, DeVoe Jennifer E. Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study. BMC Health Serv Res 2021; 21:1186. [PMID: 34717616 PMCID: PMC8557589 DOI: 10.1186/s12913-021-07195-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 10/19/2021] [Indexed: 11/21/2022] Open
Abstract
Background Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. Methods In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. Results Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621–1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013–1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009–1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. Conclusions A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. Trial registration This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262.
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Affiliation(s)
- Huguet Nathalie
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.
| | - Valenzuela Steele
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Marino Miguel
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.,Division of Biostatistics, School of Public Health, Oregon Health & Science University - Portland State University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Moreno Laura
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Hatch Brigit
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.,Research Department, OCHIN Inc, 1881 SW Naito Pkwy, Portland, OR, 97201, USA
| | - Baron Andrea
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - J Cohen Deborah
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - E DeVoe Jennifer
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
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Rogers JR, Lee J, Zhou Z, Cheung YK, Hripcsak G, Weng C. Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review. J Am Med Inform Assoc 2021; 28:144-154. [PMID: 33164065 DOI: 10.1093/jamia/ocaa224] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 08/11/2020] [Accepted: 09/02/2020] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE Real-world data (RWD), defined as routinely collected healthcare data, can be a potential catalyst for addressing challenges faced in clinical trials. We performed a scoping review of database-specific RWD applications within clinical trial contexts, synthesizing prominent uses and themes. MATERIALS AND METHODS Querying 3 biomedical literature databases, research articles using electronic health records, administrative claims databases, or clinical registries either within a clinical trial or in tandem with methodology related to clinical trials were included. Articles were required to use at least 1 US RWD source. All abstract screening, full-text screening, and data extraction was performed by 1 reviewer. Two reviewers independently verified all decisions. RESULTS Of 2020 screened articles, 89 qualified: 59 articles used electronic health records, 29 used administrative claims, and 26 used registries. Our synthesis was driven by the general life cycle of a clinical trial, culminating into 3 major themes: trial process tasks (51 articles); dissemination strategies (6); and generalizability assessments (34). Despite a diverse set of diseases studied, <10% of trials using RWD for trial process tasks evaluated medications or procedures (5/51). All articles highlighted data-related challenges, such as missing values. DISCUSSION Database-specific RWD have been occasionally leveraged for various clinical trial tasks. We observed underuse of RWD within conducted medication or procedure trials, though it is subject to the confounder of implicit report of RWD use. CONCLUSION Enhanced incorporation of RWD should be further explored for medication or procedure trials, including better understanding of how to handle related data quality issues to facilitate RWD use.
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Affiliation(s)
- James R Rogers
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Junghwan Lee
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Ziheng Zhou
- Institute of Human Nutrition, Columbia University, New York, New York, USA
| | - Ying Kuen Cheung
- Department of Biostatistics, Columbia University, New York, New York, USA, and
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York, USA.,Medical Informatics Services, New York-Presbyterian Hospital, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
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A Practice-Based Research Network (PBRN) Roadmap for Evaluating COVID-19 in Community Health Centers: A Report From the OCHIN PBRN. J Am Board Fam Med 2020; 33:774-778. [PMID: 32989072 PMCID: PMC7908821 DOI: 10.3122/jabfm.2020.05.200053] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 06/15/2020] [Accepted: 06/18/2020] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Primary care practice-based research networks (PBRNs) are critical laboratories for generating evidence from real-world settings, including studying natural experiments. Primary care's response to the novel coronavirus-19 (COVID-19) pandemic is arguably the most impactful natural experiment in our lifetime. EVALUATING THE IMPACT OF COVID-19: We briefly describe the OCHIN PBRN of community health centers (CHCs), its partnership with implementation scientists, and how we are leveraging this infrastructure and expertise to create a rapid research response evaluating how CHCs across the country responded to the COVID-19 pandemic. COVID-19 RESEARCH ROADMAP: Our research agenda focuses on asking: How has care delivery in CHCs changed due to COVID-19? What impact has COVID-19 had on the delivery of preventive services in CHCs? Which PBRN services (e.g., data surveillance, training, evidence synthesis) are most impactful to real-world practices? What decision-making strategies were used in the PBRN and its practices to make real-time changes in response to the pandemic? What critical factors in successfully and sustainably transforming primary care are illuminated by pandemic-driven changes? DISCUSSION AND CONCLUSIONS PBRNs enable real-world evaluation of practice change and natural experiments, and thus are ideal laboratories for implementation science research. We present a real-time example of how a PBRN Implementation Laboratory activated a response to study a historic natural experiment, to help other PBRNs charting a course through this pandemic.
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Adnan H, Adnan SM, Deng K, Yang C, Zhao W, Li K. Variation in insurance-mortality relationship amid macroeconomic shifts: a study of SEER female-specific cancer patients in USA. Public Health 2020; 185:130-138. [DOI: 10.1016/j.puhe.2020.03.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 01/05/2020] [Accepted: 03/12/2020] [Indexed: 12/25/2022]
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Hatch B, Tillotson C, Huguet N, Marino M, Baron A, Nelson J, Sumic A, Cohen D, E DeVoe J. Implementation and adoption of a health insurance support tool in the electronic health record: a mixed methods analysis within a randomized trial. BMC Health Serv Res 2020; 20:428. [PMID: 32414376 PMCID: PMC7227079 DOI: 10.1186/s12913-020-05317-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 05/11/2020] [Indexed: 11/10/2022] Open
Abstract
Background In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies. Methods CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016–April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research. Results The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p < 0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization. Conclusions Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC’s perceived relative advantage of the tool was the primary driver of decisions to implement the tool. Trial registration ClinicalTrials.gov: NCT02355262, Posted February 4, 2015.
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Affiliation(s)
- Brigit Hatch
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA. .,OCHIN, 1881 SW Naito Parkway, Portland, OR, 97201, USA.
| | | | - Nathalie Huguet
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA
| | - Miguel Marino
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA
| | - Andrea Baron
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA
| | - Joan Nelson
- OCHIN, 1881 SW Naito Parkway, Portland, OR, 97201, USA
| | | | - Deborah Cohen
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA
| | - Jennifer E DeVoe
- Oregon Health & Science University, 3405 SW Perimeter Court, Portland, OR, 97239, USA.,OCHIN, 1881 SW Naito Parkway, Portland, OR, 97201, USA
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Adnan H, Adnan SM, Deng K, Yang C, Hou Y, Ngo Nkondjock VR, Li K. Macroeconomic environment and insurance-mortality relationship: An analysis of gender-based disparity among non-elderly adult patients of melanoma and lung cancer. Eur J Cancer Care (Engl) 2020; 29:e13229. [PMID: 32011788 DOI: 10.1111/ecc.13229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 12/23/2019] [Accepted: 01/13/2020] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Cancer patients exhibit disparity in mortality risks across demographic divisions as well as insurance groups. The effects of macroeconomic environment also vary for such strata. This study analyses the gaps between mortality risks for male and female cancer patients with and without insurance and examines how such gaps transform over time with macroeconomic shifts. METHODS Demographic, clinical and treatment records of 45,750 melanoma and 91,157 lung cancer patients diagnosed in 2007-2009 and 2011-2013 were extracted from Surveillance, Epidemiology and End Results (SEER) database. Kaplan-Meier test was applied to ascertain survival probability of each insurance group, while Cox proportional hazard model was used to assess relative mortality risk for Medicaid and uninsured patients, for the whole data as well as separately for both time periods and genders. RESULTS Both the hazard ratios and change thereof over time are greater for female patients without insurance, than for male patients. More than any insurance-gender subgroup, uninsured female patients of melanoma have much increased hazard ratios, from 1.41 [95% confidence interval (CI), 1.04-1.92] to 2.22 [95% CI, 1.67-2.94]. CONCLUSION Despite diagnostic improvements and technology advancements, the adverse effects of macroeconomic crisis are associated with increased relative mortality risks for cancer patients without insurance, more for women than men.
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Affiliation(s)
- Humara Adnan
- Harbin Medical University, Harbin, China.,COMSATS University Islamabad, Islamabad, Pakistan
| | | | - Kui Deng
- Harbin Medical University, Harbin, China
| | | | - Yan Hou
- Harbin Medical University, Harbin, China
| | | | - Kang Li
- Harbin Medical University, Harbin, China
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Cottrell EK, Gold R, Likumahuwa S, Angier H, Huguet N, Cohen DJ, Clark KD, Gottlieb LM, DeVoe JE. Using Health Information Technology to Bring Social Determinants of Health into Primary Care: A Conceptual Framework to Guide Research. J Health Care Poor Underserved 2019; 29:949-963. [PMID: 30122675 DOI: 10.1353/hpu.2018.0071] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Several recent national initiatives have called for increased efforts to integrate social determinants of health (SDH) into health care settings using health information technology (HIT). However, there is limited evidence to guide the implementation of these recommendations in practice. Research is needed to understand what SDH information is most important to collect, how SDH information can be used to inform clinical care and referrals, and ultimately, whether and how integrating SDH screening and action into primary care affects individual and population health. We recently proposed a conceptual framework to illustrate how HIT can be used to bring SDH information into primary care. In this paper, we describe how we are putting this conceptual model into practice within the OCHIN network of community health centers by highlighting examples of ongoing research, identifying knowledge gaps, and outlining a roadmap of future research to move the field forward.
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DeVoe JE, Hoopes M, Nelson CA, Cohen DJ, Sumic A, Hall J, Angier H, Marino M, O'Malley JP, Gold R. Electronic health record tools to assist with children's insurance coverage: a mixed methods study. BMC Health Serv Res 2018; 18:354. [PMID: 29747644 PMCID: PMC5946500 DOI: 10.1186/s12913-018-3159-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 04/26/2018] [Indexed: 11/11/2022] Open
Abstract
Background Children with health insurance have increased access to healthcare and receive higher quality care. However, despite recent initiatives expanding children’s coverage, many remain uninsured. New technologies present opportunities for helping clinics provide enrollment support for patients. We developed and tested electronic health record (EHR)-based tools to help clinics provide children’s insurance assistance. Methods We used mixed methods to understand tool adoption, and to assess impact of tool use on insurance coverage, healthcare utilization, and receipt of recommended care. We conducted intent-to-treat (ITT) analyses comparing pediatric patients in 4 intervention clinics (n = 15,024) to those at 4 matched control clinics (n = 12,227). We conducted effect-of-treatment-on-the-treated (ETOT) analyses comparing intervention clinic patients with tool use (n = 2240) to intervention clinic patients without tool use (n = 12,784). Results Tools were used for only 15% of eligible patients. Qualitative data indicated that tool adoption was limited by: (1) concurrent initiatives that duplicated the work associated with the tools, and (2) inability to obtain accurate insurance coverage data and end dates. The ITT analyses showed that intervention clinic patients had higher odds of gaining insurance coverage (adjusted odds ratio [aOR] = 1.32, 95% confidence interval [95%CI] 1.14–1.51) and lower odds of losing coverage (aOR = 0.77, 95%CI 0.68–0.88), compared to control clinic patients. Similarly, ETOT findings showed that intervention clinic patients with tool use had higher odds of gaining insurance (aOR = 1.83, 95%CI 1.64–2.04) and lower odds of losing coverage (aOR = 0.70, 95%CI 0.53–0.91), compared to patients without tool use. The ETOT analyses also showed higher rates of receipt of return visits, well-child visits, and several immunizations among patients for whom the tools were used. Conclusions This pragmatic trial, the first to evaluate EHR-based insurance assistance tools, suggests that it is feasible to create and implement tools that help clinics provide insurance enrollment support to pediatric patients. While ITT findings were limited by low rates of tool use, ITT and ETOT findings suggest tool use was associated with better odds of gaining and keeping coverage. Further, ETOT findings suggest that use of such tools may positively impact healthcare utilization and quality of pediatric care. Trial registration ClinicalTrials.gov, NCT02298361; retrospectively registered on November 5, 2014. Electronic supplementary material The online version of this article (10.1186/s12913-018-3159-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jennifer E DeVoe
- OCHIN, Inc., 1881 SW Naito Parkway, Portland, OR, 97201, USA.,Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | - Megan Hoopes
- OCHIN, Inc., 1881 SW Naito Parkway, Portland, OR, 97201, USA
| | | | - Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | | | - Jennifer Hall
- Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | - Heather Angier
- Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | - Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | - Jean P O'Malley
- Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Road, Mail Code FM, Portland, OR, 97239, USA
| | - Rachel Gold
- OCHIN, Inc., 1881 SW Naito Parkway, Portland, OR, 97201, USA.,Kaiser Permanente Northwest Center for Health Research, 3800 N Interstate Avenue, Portland, OR, 97211, USA
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DeVoe J, Angier H, Hoopes M, Gold R. A new role for primary care teams in the United States after "Obamacare:" Track and improve health insurance coverage rates. Fam Med Community Health 2016; 4:63-67. [PMID: 28966926 PMCID: PMC5617364 DOI: 10.15212/fmch.2016.0117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after "Obamacare," primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.
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Affiliation(s)
| | | | | | - Rachel Gold
- Kaiser Permanente Center for Health Research Northwest Region, Portland, OR, USA
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