Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 patients' EHRs. Our results suggest that the physicians logged an average of 3.08 hours on office visits and 3.17 hours on desktop medicine each day. Desktop medicine consists of activities such as communicating with patients through a secure patient portal, responding to patients' online requests for prescription refills or medical advice, ordering tests, sending staff messages, and reviewing test results. Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocated HHS Public AccessAuthor manuscript Health Aff (Millwood). Author manuscript; available in PMC 2017 August 07. Author Manuscript Author ManuscriptAuthor Manuscript Author Manuscript to desktop medicine. Staffing and scheduling in the physician's office, as well as provider payment models for primary care practice, should account for these desktop medicine efforts.Physician time is a key resource in health services delivery. Understanding how physicians spend their clinical time is essential, given the need to understand practical capacity; guide staffing, scheduling, and support models in the physician's office; and improve the accuracy of payment for physician services. Fee-for-service payments are intended to reflect resources (captured as relative value units, or RVUs) used before, during, and after clinical encounters associated with face-to-face ambulatory care visits. 1-3 Questions have been raised about whether the reports underlying the RVU estimates are accurate and representative of true physician effort in providing patient care services. In the age of electronic health records (EHRs) with patient portals, patients often request services (such as prescription refills and medical advice) online, without face-to-face visits. Physician effort in addressing these online requests was absent from the original RVU calculations. [1][2][3] In addition to physician reports of their own efforts, 2,4,5 researchers have used time-andmotion studies 6 and video 7 and audio recordings. 8 While these methods capture significant physician effort, 6,9-11 they are costly to use and often evaluate only a limited number of physicians. Even the resource-based relative values scale (RBRVS) was built, for some specialties, on survey responses to vignettes from about twenty physicians. 1 This scale is still the chief tool used to determine the periodic updates to the Medicare Fee Schedule. Furthermore, concerns about the Hawthorne effect preclude ongoing, broad-based direct observa...

BackgroundPeripheral arterial disease (PAD) is a growing problem with few available therapies. Cilostazol is the only FDA-approved medication with a class I indication for intermittent claudication, but carries a black box warning due to concerns for increased cardiovascular mortality. To assess the validity of this black box warning, we employed a novel text-analytics pipeline to quantify the adverse events associated with Cilostazol use in a clinical setting, including patients with congestive heart failure (CHF).Methods and ResultsWe analyzed the electronic medical records of 1.8 million subjects from the Stanford clinical data warehouse spanning 18 years using a novel text-mining/statistical analytics pipeline. We identified 232 PAD patients taking Cilostazol and created a control group of 1,160 PAD patients not taking this drug using 1∶5 propensity-score matching. Over a mean follow up of 4.2 years, we observed no association between Cilostazol use and any major adverse cardiovascular event including stroke (OR = 1.13, CI [0.82, 1.55]), myocardial infarction (OR = 1.00, CI [0.71, 1.39]), or death (OR = 0.86, CI [0.63, 1.18]). Cilostazol was not associated with an increase in any arrhythmic complication. We also identified a subset of CHF patients who were prescribed Cilostazol despite its black box warning, and found that it did not increase mortality in this high-risk group of patients.ConclusionsThis proof of principle study shows the potential of text-analytics to mine clinical data warehouses to uncover ‘natural experiments’ such as the use of Cilostazol in CHF patients. We envision this method will have broad applications for examining difficult to test clinical hypotheses and to aid in post-marketing drug safety surveillance. Moreover, our observations argue for a prospective study to examine the validity of a drug safety warning that may be unnecessarily limiting the use of an efficacious therapy.

Background Understanding of cancer outcomes is limited by data fragmentation. We analyzed the information yielded by integrating breast cancer data from three sources: electronic medical records (EMRs) of two healthcare systems and the state registry. Methods We extracted diagnostic test and treatment data from EMRs of all breast cancer patients treated from 2000–2010 in two independent California institutions: a community-based practice (Palo Alto Medical Foundation) and an academic medical center (Stanford University). We incorporated records from the population-based California Cancer Registry (CCR), and then linked EMR-CCR datasets of Community and University patients. Results We initially identified 8210 University patients and 5770 Community patients; linked datasets revealed a 16% patient overlap, yielding 12,109 unique patients. The proportion of all Community patients, but not University patients, treated at both institutions increased with worsening cancer prognostic factors. Before linking datasets, Community patients appeared to receive less intervention than University patients (mastectomy: 37.6% versus 43.2%; chemotherapy: 35% versus 41.7%; magnetic resonance imaging (MRI): 10% versus 29.3%; genetic testing: 2.5% versus 9.2%). Linked Community and University datasets revealed that patients treated at both institutions received substantially more intervention (mastectomy: 55.8%; chemotherapy: 47.2%; MRI: 38.9%; genetic testing: 10.9%; p<0.001 for each three-way institutional comparison). Conclusion Data linkage identified 16% of patients who were treated in two healthcare systems and who, despite comparable prognostic factors, received far more intensive treatment than others. By integrating complementary data from EMRs and population-based registries, we obtained a more comprehensive understanding of breast cancer care and factors that drive treatment utilization.

BACKGROUND Routinely recommended screening for breast, cervical, and colorectal cancers can significantly reduce mortality from these types of cancer, yet screening is underutilized among Asians. Surveys rely on self-report and often are underpowered for analysis by Asian ethnicities. Electronic health records include validated (as opposed to recall-based) rates of cancer screening. In this paper we seek to better understand cancer screening patterns in a population of insured Asian Americans. METHODS We calculated rates of compliance with cervical, breast, and colorectal cancer screening among Asians from an EHR population, and compared them to non-Hispanic whites. We performed multivariable modeling to evaluate potential predictors (at the provider- and patient- level) of screening completion among Asian patients. RESULTS Aggregation of Asian subgroups masked heterogeneity in screening rates. Asian Indians and Native Hawaiians and Pacific Islanders had the lowest rates of screening in our sample, well below that of non-Hispanic whites. In multivariable analyses, screening completion was negatively associated with patient-physician language discordance for mammography (OR:0.81 95% CI:0.71–0.92) and colorectal cancer screening (OR:0.79 CI:0.72–0.87) and positively associated with patient-provider gender concordance for mammography (OR:1.16 CI:1.00–1.34) and cervical cancer screening (OR:1.66 CI:1.51–1.82). Additionally, patient enrollment in online health services increased mammography (OR:1.32 CI:1.20–1.46) and cervical cancer screening (OR:1.31 CI:1.24–1.37). CONCLUSIONS Language- and gender- concordant primary care providers, and culturally tailored online health resources may help improve preventive cancer screening in Asian patient populations. IMPACT This study demonstrates how use of EHR data can inform investigations of primary prevention practices within the healthcare delivery setting.

Although there was greater use of RS for patients who sought care in more than one health care setting, use of chemotherapy followed RS guidance in University and Community health care systems. These results suggest that precision medicine may help optimize cancer treatment across health care settings.