Cumulated time to chart closure: a novel electronic health record-derived metric associated with clinician burnout

Objective

We sought to determine whether average cumulated time to chart closure (CTCC), a novel construct to measure clinician workload burden, and electronic health record (EHR) measures were associated with a validated measure of burnout.

Materials and methods

Physicians at a large academic institution participated in a well-being survey that was linked to their EHR use data. CTCC was defined as the average time from the start of patient encounters to chart closure over a set of encounters. Established EHR use measures including daily total time in the EHR (EHR-Time8), time in the EHR outside scheduled hours, work outside of work (WOW8), and time spent on inbox (IB-Time8) were calculated. We examined the relationship between CTCC, EHR use metrics, and burnout using descriptive statistics and adjusted logistic regression models.

Results

We included data from 305 attendings, encompassing 242 432 ambulatory encounters (2021). Among them, 42% (128 physicians) experienced burnout. The median CTCC for all clinicians was 32.5 h. Unadjusted analyses revealed significant associations between CTCC, WOW8, IB-Time8, and burnout. In a final adjusted model, only CTCC remained statistically significant with an odds ratio estimate of 1.42 (95% CI, 1.00-2.01).

Discussion

These results suggest that CTCC is predictive of burnout and that purely measuring duration of interaction with the EHR itself is not sufficient to capture burnout.

Conclusion

Workload burden as manifested by average CTCC has the potential to be a practical, quantifiable measure that will allow for identification of clinicians at risk of burnout and to assess the success of interventions designed to address burnout.

Differences in Care Team Response to Patient Portal Messages by Patient Race and Ethnicity

Importance

The COVID-19 pandemic was associated with substantial growth in patient portal messaging. Higher message volumes have largely persisted, reflecting a new normal. Prior work has documented lower message use by patients who belong to minoritized racial and ethnic groups, but research has not examined differences in care team response to messages. Both have substantial ramifications on resource allocation and care access under a new care paradigm with portal messaging as a central channel for patient-care team communication.

Objective

To examine differences in how care teams respond to patient portal messages sent by patients from different racial and ethnic groups.

Design, Setting, and Participants

In a cross-sectional design in a large safety-net health system, response outcomes from medical advice message threads sent from January 1, 2021, through November 24, 2021, from Asian, Black, Hispanic, and White patients were compared, controlling for patient and message thread characteristics. Asian, Black, Hispanic, and White patients with 1 or more adult primary care visits at Boston Medical Center in calendar year 2020 were included. Data analysis was conducted from June 23, 2022, through December 21, 2023.

Exposure

Patient race and ethnicity.

Main Outcomes and Measures

Rates at which medical advice request messages were responded to by care teams and the types of health care professionals that responded.

Results

A total of 39 043 patients were included in the sample: 2006 were Asian, 21 600 were Black, 7185 were Hispanic, and 8252 were White. A total of 22 744 (58.3%) patients were women and mean (SD) age was 50.4 (16.7) years. In 2021, these patients initiated 57 704 medical advice request message threads. When patients who belong to minoritized racial and ethnic groups sent these messages, the likelihood of receiving any care team response was similar, but the types of health care professionals that responded differed. Black patients were 3.95 percentage points (pp) less likely (95% CI, -5.34 to -2.57 pp; P < .001) to receive a response from an attending physician, and 3.01 pp more likely (95% CI, 1.76-4.27 pp; P < .001) to receive a response from a registered nurse, corresponding to a 17.4% lower attending response rate. Similar, but smaller, differences were observed for Asian and Hispanic patients.

Conclusions and Relevance

The findings of this study suggest lower prioritization of patients who belong to minoritized racial and ethnic groups during triaging. Understanding and addressing these disparities will be important for improving care equity and informing health care delivery support algorithms.

Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings

Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS:  We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care. CONCLUSION:  Actionable solutions identified to address core categories of EHR metric implementation challenges include: (1) maintaining broad stakeholder engagement, (2) reaching agreement on standardized measure definitions across vendors, (3) integrating clinician perspectives, and (4) addressing cognitive and EHR burden. Building upon the momentum of this workshop's outputs offers promise for overcoming barriers to implementing EHR use metrics.

Telehealth Policy, Practice, and Education: a Position Statement of the Society of General Internal Medicine

Telehealth services, specifically telemedicine audio-video and audio-only patient encounters, expanded dramatically during the COVID-19 pandemic through temporary waivers and flexibilities tied to the public health emergency. Early studies demonstrate significant potential to advance the quintuple aim (patient experience, health outcomes, cost, clinician well-being, and equity). Supported well, telemedicine can particularly improve patient satisfaction, health outcomes, and equity. Implemented poorly, telemedicine can facilitate unsafe care, worsen disparities, and waste resources. Without further action from lawmakers and agencies, payment will end for many telemedicine services currently used by millions of Americans at the end of 2024. Policymakers, health systems, clinicians, and educators must decide how to support, implement, and sustain telemedicine, and long-term studies and clinical practice guidelines are emerging to provide direction. In this position statement, we use clinical vignettes to review relevant literature and highlight where key actions are needed. These include areas where telemedicine must be expanded (e.g., to support chronic disease management) and where guidelines are needed (e.g., to prevent inequitable offering of telemedicine services and prevent unsafe or low-value care). We provide policy, clinical practice, and education recommendations for telemedicine on behalf of the Society of General Internal Medicine. Policy recommendations include ending geographic and site restrictions, expanding the definition of telemedicine to include audio-only services, establishing appropriate telemedicine service codes, and expanding broadband access to all Americans. Clinical practice recommendations include ensuring appropriate telemedicine use (for limited acute care situations or in conjunction with in-person services to extend longitudinal care relationships), that the choice of modality be done through patient-clinician shared decision-making, and that health systems design telemedicine services through community partnerships to ensure equitable implementation. Education recommendations include developing telemedicine-specific educational strategies for trainees that align with accreditation body competencies and providing educators with protected time and faculty development resources.

Personalized hypertension treatment recommendations by a data-driven model

BACKGROUND

Hypertension is a prevalent cardiovascular disease with severe longer-term implications. Conventional management based on clinical guidelines does not facilitate personalized treatment that accounts for a richer set of patient characteristics.

METHODS

Records from 1/1/2012 to 1/1/2020 at the Boston Medical Center were used, selecting patients with either a hypertension diagnosis or meeting diagnostic criteria (≥ 130 mmHg systolic or ≥ 90 mmHg diastolic, n = 42,752). Models were developed to recommend a class of antihypertensive medications for each patient based on their characteristics. Regression immunized against outliers was combined with a nearest neighbor approach to associate with each patient an affinity group of other patients. This group was then used to make predictions of future Systolic Blood Pressure (SBP) under each prescription type. For each patient, we leveraged these predictions to select the class of medication that minimized their future predicted SBP.

RESULTS

The proposed model, built with a distributionally robust learning procedure, leads to a reduction of 14.28 mmHg in SBP, on average. This reduction is 70.30% larger than the reduction achieved by the standard-of-care and 7.08% better than the corresponding reduction achieved by the 2nd best model which uses ordinary least squares regression. All derived models outperform following the previous prescription or the current ground truth prescription in the record. We randomly sampled and manually reviewed 350 patient records; 87.71% of these model-generated prescription recommendations passed a sanity check by clinicians.

CONCLUSION

Our data-driven approach for personalized hypertension treatment yielded significant improvement compared to the standard-of-care. The model implied potential benefits of computationally deprescribing and can support situations with clinical equipoise.

OUP accepted manuscript

Objective

To develop predictive models of coronavirus disease 2019 (COVID-19) outcomes, elucidate the influence of socioeconomic factors, and assess algorithmic racial fairness using a racially diverse patient population with high social needs.

Materials and Methods

Data included 7,102 patients with positive (RT-PCR) severe acute respiratory syndrome coronavirus 2 test at a safety-net system in Massachusetts. Linear and nonlinear classification methods were applied. A score based on a recurrent neural network and a transformer architecture was developed to capture the dynamic evolution of vital signs. Combined with patient characteristics, clinical variables, and hospital occupancy measures, this dynamic vital score was used to train predictive models.

Results

Hospitalizations can be predicted with an area under the receiver-operating characteristic curve (AUC) of 92% using symptoms, hospital occupancy, and patient characteristics, including social determinants of health. Parsimonious models to predict intensive care, mechanical ventilation, and mortality that used the most recent labs and vitals exhibited AUCs of 92.7%, 91.2%, and 94%, respectively. Early predictive models, using labs and vital signs closer to admission had AUCs of 81.1%, 84.9%, and 92%, respectively.

Discussion

The most accurate models exhibit racial bias, being more likely to falsely predict that Black patients will be hospitalized. Models that are only based on the dynamic vital score exhibited accuracies close to the best parsimonious models, although the latter also used laboratories.

Conclusions

This large study demonstrates that COVID-19 severity may accurately be predicted using a score that accounts for the dynamic evolution of vital signs. Further, race, social determinants of health, and hospital occupancy play an important role.

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital

Background

To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an “opt-out” electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle evaluations guided by the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) compilation.

Methods

We identified stakeholders affected by implementation and conducted a local needs assessment starting 6 months-pre-launch. We then conducted two rapid-cycle evaluations during the first 6 months post-implementation. The CFIR informed survey and interview guide development, data collection, assessment of barriers and facilitators, and selection of ERIC strategies to implement and adapt the intervention.

Results

Key themes were: (1) Understanding the hospital's priority to improving tobacco performance metrics was critical in gaining leadership buy-in (CFIR Domain: Outer setting; Construct: External Policy and Incentives). (2) CFIR-based rapid-cycle evaluations allowed us to recognize implementation challenges early and select ERIC strategies clustering into 3 broad categories (conducting needs assessment; developing stakeholder relationships; training and educating stakeholders) to make real-time adaptations, creating an acceptable clinical workflow. (3) Minimizing clinician burden allowed the successful implementation of the TTC service. (4) Demonstrating improved 6-month quit rates and tobacco performance metrics were key to sustaining the program.

Conclusions

Rapid-cycle evaluations to gather pre-implementation and early-implementation data, focusing on modifiable barriers and facilitators, allowed us to develop and refine the intervention to improve acceptability, adoption, and sustainability, enabling us to improve tobacco performance metrics in a short timeline. Future directions include spreading rapid-cycle evaluations to promote implementation of inpatient tobacco treatment programs to other settings and assessing long-term sustainability and return on investment of these programs.

Effectiveness of an Opt-Out Electronic Heath Record-Based Tobacco Treatment Consult Service at an Urban Safety Net Hospital

BACKGROUND

To address the burden of tobacco use in underserved populations, our safety net hospital developed a tobacco treatment intervention consisting of an "opt-out" electronic health record-based best practice alert + order set, which triggers consultation to an inpatient tobacco treatment consult (TTC) service for all hospitalized smokers.

RESEARCH QUESTION

We sought to understand if the intervention would increase patient-level outcomes (receipt of tobacco treatment during hospitalization and at discharge; 6-month smoking abstinence) and improve hospital-wide performance on tobacco treatment metrics.

DESIGN AND METHODS

We conducted two retrospective quasi-experimental analyses to examine effectiveness of the TTC service. Using a pragmatic design and multivariable logistic regression, we compared patient-level outcomes of receipt of nicotine replacement therapy and 6-month quit rates between smokers seen by the service (n = 505) and eligible smokers not seen because of time constraints (n = 680) between July 2016 and December 2016. In addition, we conducted an interrupted time series analysis to examine the effect of the TTC service on hospital-level performance measures, comparing reported Joint Commission measure rates for inpatient (Tob-2) and postdischarge (Tob-3) tobacco treatment preimplementation (January 2015-June 2016) vs postimplementation (July 2016-December 2017) of the intervention.

RESULTS

Compared with inpatient smokers not seen by the TTC service, smokers seen by the TTC service had higher odds of receiving nicotine replacement during hospitalization (260 of 505 [51.5%] vs 244 of 680 [35.9%]; adjusted ORs [AOR], 1.93 [95% CI, 1.5-2.45]) and at discharge (164 of 505 [32.5%] vs 84 of 680 [12.4%]; AOR, 3.41 [95% CI, 2.54-4.61]), as well as higher odds of 6-month smoking abstinence (75 of 505 [14.9%] vs 68 of 680 [10%]; AOR, 1.48 [95% CI, 1.03-2.12]). Hospital-wide, the intervention was associated with a change in slope trends for Tob-3 (P < .01), but not for Tob-2.

INTERPRETATION

The "opt-out" electronic health record-based TTC service at our large safety net hospital was effective at improving both patient-level outcomes and hospital-level performance metrics, and could be implemented at other safety net hospitals that care for hard-to-reach smokers.

Using normalisation process theory to understand workflow implications of decision support implementation across diverse primary care settings

BACKGROUND

Effective implementation of technologies into clinical workflow is hampered by lack of integration into daily activities. Normalisation process theory (NPT) can be used to describe the kinds of 'work' necessary to implement and embed complex new practices. We determined the suitability of NPT to assess the facilitators, barriers and 'work' of implementation of two clinical decision support (CDS) tools across diverse care settings.

METHODS

We conducted baseline and 6-month follow-up quantitative surveys of clinic leadership at two academic institutions' primary care clinics randomised to the intervention arm of a larger study. The survey was adapted from the NPT toolkit, analysing four implementation domains: sense-making, participation, action, monitoring. Domains were summarised among completed responses (n=60) and examined by role, institution, and time.

RESULTS

The median score for each NPT domain was the same across roles and institutions at baseline, and decreased at 6 months. At 6 months, clinic managers' participation domain (p=0.003), and all domains for medical directors (p<0.003) declined. At 6 months, the action domain decreased among Utah respondents (p=0.03), and all domains decreased among Wisconsin respondents (p≤0.008).

CONCLUSIONS

This study employed NPT to longitudinally assess the implementation barriers of new CDS. The consistency of results across participant roles suggests similarities in the work each role took on during implementation. The decline in engagement over time suggests the need for more frequent contact to maintain momentum. Using NPT to evaluate this implementation provides insight into domains which can be addressed with participants to improve success of new electronic health record technologies.

TRIAL REGISTRATION NUMBER

NCT02534987.

Study protocol for targeted interventions to prevent chronic low back pain in high-risk patients: A multi-site pragmatic cluster randomized controlled trial (TARGET Trial)

BACKGROUND

Low back pain (LBP) is one of the most prevalent and potentially disabling conditions for which people seek health care. Patients, providers, and payers agree that greater effort is needed to prevent acute LBP from transitioning to chronic LBP.

METHODS AND STUDY DESIGN

The TARGET (Targeted Interventions to Prevent Chronic Low Back Pain in High-Risk Patients) Trial is a primary care-based, multisite, cluster randomized, pragmatic trial comparing guideline-based care (GBC) to GBC + referral to Psychologically Informed Physical Therapy (PIPT) for patients presenting with acute LBP and identified as high risk for persistent disabling symptoms. Study sites include primary care clinics within each of five geographical regions in the United States, with clinics randomized to either GBC or GBC + PIPT. Acute LBP patients at all clinics are risk stratified (high, medium, low) using the STarT Back Tool. The primary outcomes are the presence of chronic LBP and LBP-related functional disability determined by the Oswestry Disability Index at 6 months. Secondary outcomes are LBP-related processes of health care and utilization of services over 12 months, determined through electronic medical records. Study enrollment began in May 2016 and concluded in June 2018. The trial was powered to include at least 1860 high-risk patients in the randomized controlled trial cohort. A prospective observational cohort of approximately 6900 low and medium-risk acute LBP patients was enrolled concurrently.

DISCUSSION

The TARGET pragmatic trial aims to establish the effectiveness of the stratified approach to acute LBP intervention targeting high-risk patients with GBC and PIPT.

TRIAL REGISTRATION

ClinicalTrials.govNCT02647658 Registered Jan. 6, 2016.

Problem-oriented charting: A review

Problem-oriented charting is form of medical documentation that organizes patient data by a diagnosis or problem. In this review, we discuss the history and current use of problem-oriented charting by critically evaluating the literature on the topic. We provide insights with regard to our own institutional use of problem-oriented charting and potential opportunities for research.

Design and implementation of electronic health record integrated clinical prediction rules (iCPR): a randomized trial in diverse primary care settings

Background

Clinical prediction rules (CPRs) represent a method of determining individual patient risk to help providers make more accurate decisions at the point of care. Well-validated CPRs are underutilized but may decrease antibiotic overuse for acute respiratory infections. The integrated clinical prediction rules (iCPR) study builds on a previous single clinic study to integrate two CPRs into the electronic health record and assess their impact on practice. This article discusses study design and implementation of a multicenter cluster randomized control trial of the iCPR clinical decision support system, including the tool adaptation, usability testing, staff training, and implementation study to disseminate iCPR at multiple clinical sites across two health care systems.

Methods

The iCPR tool is based on two well-validated CPRs, one for strep pharyngitis and one for pneumonia. The iCPR tool uses the reason for visit to trigger a risk calculator. Provider completion of the risk calculator provides a risk score, which is linked to an order set. Order sets guide evidence-based care and include progress note documentation, tests, prescription medications, and patient instructions. The iCPR tool was refined based on interviews with providers, medical assistants, and clinic managers, and two rounds of usability testing. “Near live” usability testing with simulated patients was used to ensure that iCPR fit into providers’ clinical workflows. Thirty-three Family Medicine and General Internal Medicine primary care clinics were recruited at two institutions. Clinics were randomized to academic detailing about strep pharyngitis and pneumonia diagnosis and treatment (control) or academic detailing plus use of the iCPR tool (intervention). The primary outcome is the difference in antibiotic prescribing rates between the intervention and control groups with secondary outcomes of difference in rapid strep and chest x-ray ordering. Use of the components of the iCPR will also be assessed.

Discussion

The iCPR study uses a strong user-centered design and builds on the previous initial study, to assess whether CPRs integrated in the electronic health record can change provider behavior and improve evidence-based care in a broad range of primary care clinics.

Trial registration

Clinicaltrials.gov (NCT02534987)

The impact of health insurance reform on insurance instability

We investigated the impact of the 2006 Massachusetts health care reform on insurance coverage and stability among minority and underserved women. We examined 36 months of insurance claims among 1,946 women who had abnormal cancer screening at six community health centers pre-(2004-2005) and post-(2007-2008) insurance reform. We examined frequency of switches in insurance coverage as measures of longitudinal insurance instability. On the date of their abnormal cancer screening test, 36% of subjects were publicly insured and 31% were uninsured. Post-reform, the percent ever uninsured declined from 39% to 29% (p .001) and those consistently uninsured declined from 23% to 16%. To assess if insurance instability changed between the pre- and post-reform periods, we conducted Poisson regression models, adjusted for patient demographics and length of time in care. These revealed no significant differences from the pre- to post-reform period in annual rates of insurance switches, incident rate ratio 0.98 (95%- CI 0.88-1.09). Our analysis is limited by changes in the populations in the pre- and post-reform period and inability to capture care outside of the health system network. Insurance reform increased stability as measured by decreasing uninsured rates without increasing insurance switches.

The impact of insurance coverage during insurance reform on diagnostic resolution of cancer screening abnormalities

We examined the impact of Massachusetts insurance reform on the care of women at six community health centers with abnormal breast and cervical cancer screening to investigate whether stability of insurance coverage was associated with more timely diagnostic resolution. We conducted Cox proportional hazards models to predict time from cancer screening to diagnostic resolution, examining the impact of 1) insurance status at time of screening abnormality, 2) number of insurance switches over a three-year period, and 3) insurance history over a three-year period. We identified 1,165 women with breast and 781 with cervical cancer screening abnormalities. In the breast cohort, Medicaid insurance at baseline, continuous public insurance, and losing insurance predicted delayed resolution. We did not find these effects in the cervical cohort. These data provide evidence that stability of health insurance coverage with insurance reform nationally may improve timely care after abnormal cancer screening in historically underserved women.

Using electronic health record clinical decision support is associated with improved quality of care

OBJECTIVES

To determine whether clinical decision support (CDS) is associated with improved quality indicators and whether disabling CDS negatively affects these.

STUDY DESIGN/METHODS

Using the 2006-2009 National Ambulatory and National Hospital Ambulatory Medical Care Surveys, we performed logistic regression to analyze adult primary care visits for the association between the use of CDS (problem lists, preventive care reminders, lab results, lab range notifications, and drug-drug interaction warnings) and quality measures (blood pressure control, cancer screening, health education, influenza vaccination, and visits related to adverse drug events).

RESULTS

There were an estimated 900 million outpatient primary care visits to clinics with EHRs from 2006-2009; 97% involved CDS, 77% were missing at least 1 CDS, and 15% had at least 1 CDS disabled. The presence of CDS was associated with improved blood pressure control (86% vs 82%; OR 1.3; 95% CI, 1.1-1.5) and more visits not related to adverse drug events (99.9% vs 99.8%; OR 3.0; 95% CI, 1.3-7.3); these associations were also present when comparing practices with CDS against practices that had disabled CDS. Electronic problem lists were associated with increased odds of having a visit with controlled blood pressure (86% vs 80%; OR 1.4; 95% CI, 1.3-1.6). Lab result notification was associated with increased odds of ordering cancer screening (15% vs 10%; OR 1.5; 95% CI, 1.03-2.2).

CONCLUSIONS

The use of CDS was associated with improvement in some quality indicators. Not having at least 1 CDS was common; disabling CDS was infrequent. This suggests that meaningful use standards may improve national quality indicators and health outcomes, once fully implemented.

Barriers to patient portal access among veterans receiving home-based primary care: a qualitative study

BACKGROUND

Electronic, or web-based, patient portals can improve patient satisfaction, engagement and health outcomes and are becoming more prevalent with the advent of meaningful use incentives. However, adoption rates are low, particularly among vulnerable patient populations, such as those patients who are home-bound with multiple comorbidities. Little is known about how these patients view patient portals or their barriers to using them.

OBJECTIVE

To identify barriers to and facilitators of using My HealtheVet (MHV), the United States Department of Veterans Affairs (VA) patient portal, among Veterans using home-based primary care services.

DESIGN

Qualitative study using in-depth semi-structured interviews. We conducted a content analysis informed by grounded theory.

PARTICIPANTS

Fourteen Veterans receiving home-based primary care, surrogates of two of these Veterans, and three home-based primary care (HBPC) staff members.

KEY RESULTS

We identified five themes related to the use of MHV: limited knowledge; satisfaction with current HBPC care; limited computer and Internet access; desire to learn more about MHV and its potential use; and value of surrogates acting as intermediaries between Veterans and MHV.

CONCLUSIONS

Despite their limited knowledge of MHV and computer access, home-bound Veterans are interested in accessing MHV and using it as an additional point of care. Surrogates are also potential users of MHV on behalf of these Veterans and may have different barriers to and benefits from use.

Racial differences in cancer screening with electronic health records and electronic preventive care reminders

BACKGROUND

Health information technology (HIT) can increase preventive care. There are hopes and fears about the impact of HIT on racial disparities in cancer screening.

OBJECTIVE

To determine whether electronic health records (EHRs) or electronic preventive care reminders (e-reminders) modify racial differences in cancer screening order rates.

DESIGN

Using the 2006-2010 National Ambulatory and National Hospital Ambulatory Medical Care Surveys, we measured (1) visit-based differences in rates of age-appropriate breast, cervical and colon cancer screening orders between white and non-white subjects at primary care visits with and without EHRs, and, at visits with EHRs, with and without e-reminders, and (2) whether EHRs or e-reminders modified these differences.

MAIN OUTCOMES

Mammography (N=45,380); Pap smears (N=73,348); and sigmoidoscopy/colonoscopy (N=50,955) orders.

RESULTS

Among an estimated 2.4 billion US adult primary care visits, orders for screening for breast, cervical or colon cancer did not differ between clinics with and without EHRs or e-reminders. There was no difference in screening orders between non-white and white patients for breast (aOR=1.1; 95% CI 0.9 to 1.4) or cervical cancer (aOR=1.2; 95% CI 1.0 to 1.3). For colon cancer, non-white patients were more likely to receive screening orders than white patients overall (aOR=1.5; 95% CI 1.1 to 2.0), at visits with EHRs (aOR=1.8; 95% CI 1.1 to 2.8) and at visits with e-reminders (aOR=2.1; 95% CI 1.2 to 3.7). EHRs or e-reminders did not modify racial differences in cancer screening rates.

CONCLUSIONS

In this visit-based analysis, non-white patients had higher colon cancer screening order rates than white patients. Despite hopes and fears about HIT, EHRs and e-reminders did not ameliorate or exacerbate racial differences in cancer screening order rates.