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1.
J Gen Intern Med ; 35(Suppl 2): 788-795, 2020 11.
Article in English | MEDLINE | ID: mdl-32875505

ABSTRACT

BACKGROUND: Clinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs). OBJECTIVE: To assess the impact of previously effective CDS on antibiotic-prescribing rates for ARIs when adapted and implemented in diverse primary care settings. DESIGN: Cluster randomized clinical trial (RCT) implementing a CDS tool designed to guide evidence-based evaluation and treatment of streptococcal pharyngitis and pneumonia. SETTING: Two large academic health system primary care networks with a mix of providers. PARTICIPANTS: All primary care practices within each health system were invited. All providers within participating clinic were considered a participant. Practices were randomized selection to a control or intervention group. INTERVENTIONS: Intervention practice providers had access to an integrated clinical prediction rule (iCPR) system designed to determine the risk of bacterial infection from reason for visit of sore throat, cough, or upper respiratory infection and guide evidence-based evaluation and treatment. MAIN OUTCOME(S): Change in overall antibiotic prescription rates. MEASURE(S): Frequency, rates, and type of antibiotics prescribed in intervention and controls groups. RESULTS: 33 primary care practices participated with 541 providers and 100,573 patient visits. Intervention providers completed the tool in 6.9% of eligible visits. Antibiotics were prescribed in 35% and 36% of intervention and control visits, respectively, showing no statistically significant difference. There were also no differences in rates of orders for rapid streptococcal tests (RR, 0.94; P = 0.11) or chest X-rays (RR, 1.01; P = 0.999) between groups. CONCLUSIONS: The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This has implications for the generalizability of CDS tools as they are adapted to heterogeneous clinical contexts. TRIAL REGISTRATION: Clinicaltrials.gov (NCT02534987). Registered August 26, 2015 at https://clinicaltrials.gov.


Subject(s)
Decision Support Systems, Clinical , Respiratory Tract Infections , Anti-Bacterial Agents/therapeutic use , Humans , Practice Patterns, Physicians' , Primary Health Care , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/drug therapy , Respiratory Tract Infections/epidemiology
2.
Stud Health Technol Inform ; 264: 1155-1158, 2019 Aug 21.
Article in English | MEDLINE | ID: mdl-31438106

ABSTRACT

Changing physician behaviors is difficult. Electronic health record (EHR) clinical decision support (CDS) offers an opportunity to promote guideline adherence. Behavioral economics (BE) has shown success as an approach to supporting evidence-based decision-making with little additional cognitive burden. We applied a user-centered approach to incorporate BE "nudges" into a CDS module in two "vanguard" sites utilizing: (1) semi-structured interviews with key informants (n = 8); (2) a design thinking workshop; and (3) semi-structured group interviews with clinicians. In the 133 day development phase at two clinics, the navigator section fired 299 times for 27 unique clinicians. The inbasket refill alert fired 124 times for 22 clinicians. Fifteen prescriptions for metformin were written by 11 clinicians. Our user-centered approach yielded a BE-driven CDS module with relatively high utilization by clinicians. Next steps include the addition of two modules and continued tracking of utilization, and assessment of clinical impact of the module.


Subject(s)
Decision Support Systems, Clinical , Electronic Health Records , Decision Making , Economics, Behavioral , Humans
3.
NPJ Digit Med ; 2: 13, 2019.
Article in English | MEDLINE | ID: mdl-31304362

ABSTRACT

Academic medical centers (AMCs) today prioritize digital innovation. In efforts to develop and disseminate the best technology for their institutions, challenges arise in organizational structure, cross-disciplinary collaboration, and creative and agile problem solving that are essential for successful implementation. To address these challenges, the Digital DesignLab was created at NYU Langone Health to provide structured processes for assessing and supporting the capacity for innovative digital development in our research and clinical community. Digital DesignLab is an enterprise level, multidisciplinary, digital development team that guides faculty and student innovators through a digital development "pipeline", which consists of intake, discovery, bootcamp, development. It also provides a framework for digital health innovation and dissemination at the institution. This paper describes the Digital DesignLab's creation and processes, and highlights key lessons learned to support digital health innovation at AMCs.

4.
Article in English | MEDLINE | ID: mdl-30820339

ABSTRACT

BACKGROUND: Current guidelines recommend less aggressive target hemoglobin A1c (HbA1c) levels based on older age and lower life expectancy for older adults with diabetes. The effectiveness of electronic health record (EHR) clinical decision support (CDS) in promoting guideline adherence is undermined by alert fatigue and poor workflow integration. Integrating behavioral economics (BE) and CDS tools is a novel approach to improving adherence to guidelines while minimizing clinician burden. METHODS: We will apply a systematic, user-centered design approach to incorporate BE "nudges" into a CDS module and will perform user testing in two "vanguard" sites. To accomplish this, we will conduct (1) semi-structured interviews with key informants (n = 8), (2) a 2-h, design-thinking workshop to derive and refine initial module ideas, and (3) semi-structured group interviews at each site with clinic leaders and clinicians to elicit feedback on three proposed nudge module components (navigator section, inbasket refill protocol, medication preference list). Detailed field notes will be summarized by module idea and usability theme for rapid iteration. Frequency of firing and user action taken will be assessed in the first month of implementation via EHR reporting to confirm that module components and related reporting are working as expected as well as assess utilization. To assess the utilization and feasibility of the new tools and generate estimates of clinician compliance with the Choosing Wisely guideline for diabetes management in older adults, a 6-month, single-arm pilot study of the BE-EHR module will be conducted in six outpatient primary care clinics. DISCUSSION: We hypothesize that a low burden, user-centered approach to design will yield a BE-driven, CDS module with relatively high utilization by clinicians. The resulting module will establish a platform for exploring the ability of BE concepts embedded within the EHR to affect guideline adherence for other use cases.

5.
JMIR Hum Factors ; 5(4): e11048, 2018 Dec 19.
Article in English | MEDLINE | ID: mdl-30567688

ABSTRACT

BACKGROUND: Design thinking and human-centered design approaches have become increasingly common in health care literature, particularly in relation to health information technology (HIT), as a pathway toward the development of usable, diffusible tools and processes. There is a need in academic medical centers tasked with digital innovation for a comprehensive process model to guide development that incorporates current industry trends, including design thinking and lean and agile approaches to digital development. OBJECTIVE: This study aims to describe the foundations and phases of our model for user-centered HIT development. METHODS: Based on our experience, we established an integrated approach and rigorous process for HIT development that leverages design thinking and lean and agile strategies in a pragmatic way while preserving methodological integrity in support of academic research goals. RESULTS: A four-phased pragmatic process model was developed for user-centered digital development in HIT. CONCLUSIONS: The model for user-centered HIT development that we developed is the culmination of diverse innovation projects and represents a multiphased, high-fidelity process for making more creative, flexible, efficient, and effective tools. This model is a critical step in building a rigorous approach to HIT design that incorporates a multidisciplinary, pragmatic perspective combined with academic research practices and state-of-the-art approaches to digital product development to meet the unique needs of health care.

6.
JMIR Hum Factors ; 5(4): e10721, 2018 Nov 28.
Article in English | MEDLINE | ID: mdl-30487119

ABSTRACT

BACKGROUND: Technology is increasingly embedded into the full spectrum of health care. This movement has benefited from the application of software development practices such as usability testing and agile development processes. These practices are frequently applied in both commercial or operational and academic settings. However, the relative importance placed on rapid iteration, validity, reproducibility, generalizability, and efficiency differs between the 2 settings and the needs and objectives of academic versus pragmatic usability evaluations. OBJECTIVE: This paper explores how usability evaluation typically varies on key dimensions in pragmatic versus academic settings that impact the rapidity, validity, and reproducibility of findings and proposes a hybrid approach aimed at satisfying both pragmatic and academic objectives. METHODS: We outline the characteristics of pragmatic versus academically oriented usability testing in health care, describe the tensions and gaps resulting from differing contexts and goals, and present a model of this hybrid process along with 2 case studies of digital development projects in which we demonstrate this integrated approach to usability evaluation. RESULTS: The case studies presented illustrate design choices characteristic of our hybrid approach to usability evaluation. CONCLUSIONS: Designed to leverage the strengths of both pragmatically and academically focused usability studies, a hybrid approach allows new development projects to efficiently iterate and optimize from usability data as well as preserves the ability of these projects to produce deeper insights via thorough qualitative analysis to inform further tool development and usability research by way of academically focused dissemination.

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