Prediction Accuracy With Electronic Medical Records Versus Administrative Claims.

OBJECTIVE: The objective of this study was to evaluate the incremental predictive power of electronic medical record (EMR) data, relative to the information available in more easily accessible and standardized insurance claims data. DATA AND METHODS: Using both EMR and Claims data, we predicted outcomes for 118,510 patients with 144,966 hospitalizations in 8 hospitals, using widely used prediction models. We use cross-validation to prevent overfitting and tested predictive performance on separate data that were not used for model training. MAIN OUTCOMES: We predict 4 binary outcomes: length of stay (≥7 d), death during the index admission, 30-day readmission, and 1-year mortality. RESULTS: We achieve nearly the same prediction accuracy using both EMR and claims data relative to using claims data alone in predicting 30-day readmissions [area under the receiver operating characteristic curve (AUC): 0.698 vs. 0.711; positive predictive value (PPV) at top 10% of predicted risk: 37.2% vs. 35.7%], and 1-year mortality (AUC: 0.902 vs. 0.912; PPV: 64.6% vs. 57.6%). EMR data, especially from the first 2 days of the index admission, substantially improved prediction of length of stay (AUC: 0.786 vs. 0.837; PPV: 58.9% vs. 55.5%) and inpatient mortality (AUC: 0.897 vs. 0.950; PPV: 24.3% vs. 14.0%). Results were similar for sensitivity, specificity, and negative predictive value across alternative cutoffs and for using alternative types of predictive models. CONCLUSION: EMR data are useful in predicting short-term outcomes. However, their incremental value for predicting longer-term outcomes is smaller. Therefore, for interventions that are based on long-term predictions, using more broadly available claims data is equally effective.

Digitally enabled asynchronous remote medical management of anxiety and depression: A cohort study.

OBJECTIVE: To evaluate the clinical outcomes of a remote mental health program for managing anxiety and depression, primarily using asynchronous digital communication. METHODS: This retrospective cohort study examined U.S. adults seeking remote care for anxiety and depression from January 2021 to May 2022. The program involves clinician-led assessment, patient education, medication management, and ongoing monitoring, primarily via text. Anxiety and depression were measured using Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) scores. Outcomes examined were changes in scores, 50% score improvement rate, and remission rate (score <5) at 1, 3, and 6 months. RESULTS: During the period evaluated, 11,844 program participants met the inclusion criteria. Most were female (n = 8328, 70.3%); their age ranged from 18-82 years (median 31 years). At baseline, median PHQ-9 and GAD-7 scores were 13 (IQR 9-17); 67% and 69% met score criteria for depression and anxiety, respectively. Most participants (80%) were prescribed a selective serotonin reuptake inhibitor (SSRI). By one month, average PHQ-9 and GAD-7 scores decreased significantly by 9.2 and 9.1 points (both p < .01). At 1-month follow-up, the 50% score improvement rate was 66% for PHQ-9 and 69% GAD-7 (p < .01). Scores continued to decrease with follow-up. At 3 months, over half achieved remission (percent [95% CI]: 52% [51-54] for anxiety, 53% [52-55] for depression). Similar improvement was observed at 6 months and in sensitivity analyses accounting for loss to follow-up. CONCLUSIONS: Use of a remote mental health program with digital tools was associated with significant clinical improvement in anxiety and depression. Challenges remain in maintaining patient engagement and ensuring appropriate care quality monitoring in digital mental health programs. Additional research comparing remote digital care to traditional in-person models is warranted. Studies should examine long-term outcomes, optimal care protocols, and the challenges to integrating these programs into existing healthcare systems and ensuring equitable access.

Do urgent care centers reduce Medicare spending?

We ask how urgent care centers (UCCs) impact healthcare costs and utilization among nearby Medicare beneficiaries. When residents of a zip code are first served by a UCC, total Medicare spending rises while mortality remains flat. In the sixth year after entry, 4.2% of the Medicare beneficiaries in a zip code that is served use a UCC, and the average per-capita annual Medicare spending in the zip code increases by $268, implying an incremental spending increase of $6,335 for each new UCC user. UCC entry is also associated with a significant increase in hospital stays and increased hospital spending accounts for half of the total increase in annual spending. These results raise the possibility that, on balance, UCCs increase costs by steering patients to hospitals.

Adoption and utilization of device-assisted telemedicine.

We estimate the effect of adopting a digital device for performing medical exams at home during telehealth visits. We match visits of adopters and non-adopters who used the same virtual care clinic but without the device and compare healthcare utilization after the matched visits. We find that device adoption, partially offset by decreased use of other primary care modalities, results in a 12% higher utilization rate of primary care and increased use of antibiotics. But - particularly among adults - adoption lowers the use of urgent care, the emergency room, and hospital care, resulting in no increase in total cost.

Drug Diffusion Through Peer Networks: The Influence of Industry Payments.

Pharmaceutical companies market to physicians through individual detailing accompanied by monetary or in-kind transfers. Large compensation payments to a small number of physicians account for most of this promotional spending. Studying US promotional payments and prescriptions for anticoagulant drugs, we investigate how peer influence broadens the payments' reach. Following a compensation payment, prescriptions for the marketed drug increase by both the paid physician and the paid physician's peers. Payments increase prescriptions to both recommended and contraindicated patients. Over three years, marketed anticoagulant prescriptions rose 23 percent due to payments, with peer spillovers contributing a quarter of the increase.

Sex Differences in the Pattern of Patient Referrals to Male and Female Surgeons.

Importance: Studies have found that female surgeons have fewer opportunities to perform highly remunerated operations, a circumstance that contributes to the sex-based pay gap in surgery. Procedures performed by surgeons are, in part, determined by the referrals they receive. In the US and Canada, most practicing physicians who provide referrals are men. Whether there are sex-based differences in surgical referrals is unknown. Objective: To examine whether physicians' referrals to surgeons are influenced by the sex of the referring physician and/or surgeon. Design, Setting, and Participants: This cross-sectional, population-based study used administrative databases to identify outpatient referrals to surgeons in Ontario, Canada, from January 1, 1997, to December 31, 2016, with follow-up to December 31, 2018. Data analysis was performed from April 7, 2019, to May 14, 2021. Exposures: Referring physician sex. Main Outcomes and Measures: This study compared the proportion of referrals (overall and those referrals that led to surgery) made by male and female physicians to male and female surgeons to assess associations between surgeon, referring physician, or patient characteristics and referral decisions. Discrete choice modeling was used to examine the extent to which sex differences in referrals were associated with physicians' preferences for same-sex surgeons. Results: A total of 39 710 784 referrals were made by 44 893 physicians (27 792 [61.9%] male) to 5660 surgeons (4389 [77.5%] male). Female patients made up a greater proportion of referrals to female surgeons than to male surgeons (76.8% vs 55.3%, P < .001). Male surgeons accounted for 77.5% of all surgeons but received 87.1% of referrals from male physicians and 79.3% of referrals from female physicians. Female surgeons less commonly received procedural referrals than male surgeons (25.4% vs 33.0%, P < .001). After adjusting for patient and referring physician characteristics, male physicians referred a greater proportion of patients to male surgeons than did female physicians; differences were greatest among referrals from other surgeons (rate ratio, 1.14; 95% CI, 1.13-1.16). Female physicians had a 1.6% (95% CI, 1.4%-1.9%) greater odds of same-sex referrals, whereas male physicians had a 32.0% (95% CI, 31.8%-32.2%) greater odds of same-sex referrals; differences did not attenuate over time. Conclusions and Relevance: In this cross-sectional, population-based study, male physicians appeared to have referral preferences for male surgeons; this disparity is not narrowing over time or as more women enter surgery. Such preferences lead to lower volumes of and fewer operative referrals to female surgeons and are associated with sex-based inequities in medicine.

Supply-side variation in the use of emergency departments.

We study the role of person- and place-specific factors in explaining geographic variation in emergency department utilization using detailed data on 150,000 patients who moved regions within Israel. We document that about half of the destination-origin differences in the average emergency department utilization rate across districts translates to the change (up or down) in movers' propensity to visit the emergency department. In contrast, we find no change in the probability of having a hospital admission through the emergency department. Similar results are obtained in a complementary event study, which uses hospital entry as a source of variation. The results from both approaches suggest that supply-side variation in emergency department access affects only the less severe cases-for which close substitutes likely exist-and that variation across emergency physicians in their propensity to admit patients is not explained by place-specific factors, such as differences in incentives, capacity, or diagnostic quality.