Patient Portal Message Volume and Time Spent on the EHR: an Observational Study of Primary Care Clinicians.

BACKGROUND: As patient-initiated messaging rises, identifying variation in message volume and its relationship to clinician workload is essential. OBJECTIVE: To describe the association between variation in message volume over time and time spent on the electronic health record (EHR) outside of scheduled hours. DESIGN: Retrospective cohort study. PARTICIPANTS: Primary care clinicians at Cleveland Clinic Health System. MAIN MEASURES: We categorized clinicians according to their number of quarterly incoming medical advice messages (i.e., message volume) between January 2019 and December 2021 using group-based trajectory modeling. We assessed change in quarterly messages and outpatient visits between October-December 2019 (Q4) and October-December 2021 (Q12). The primary outcome was time outside of scheduled hours spent on the EHR. We used mixed effects logistic regression to describe the association between incoming portal messages and time spent on the EHR by clinician messaging group and at the clinician level. KEY RESULTS: Among the 150 clinicians, 31% were in the low-volume group (206 messages per quarter per clinician), 47% were in the moderate-volume group (505 messages), and 22% were in the high-volume group (840 messages). Mean quarterly messages increased from 340 to 695 (p < 0.001) between Q4 and Q12; mean quarterly outpatient visits fell from 711 to 575 (p = 0.005). While time spent on the EHR outside of scheduled hours increased modestly for all clinicians, this did not significantly differ by message group. Across all clinicians, each additional 10 messages was associated with an average of 12 min per quarter of additional time spent on the EHR (p < 0.001). CONCLUSIONS: Message volume increased substantially over the study period and varied by group. While messages were associated with additional time spent on the EHR outside of scheduled hours, there was no significant difference in time spent on the EHR between the high and low message volume groups.

Association of patient characteristics and insurance type with anti-obesity medications prescribing and fills.

AIM: To characterize factors associated with the receipt of anti-obesity medication (AOM) prescription and fill. MATERIALS AND METHODS: This retrospective cohort study used electronic health records from 1 January 2015 to 30 June 2023, in a large health system in Ohio and Florida. Adults with a body mass index ≥30 kg/m2 who attended ≥1 weight-management programme or had an initial AOM prescription between 1 July 2015 and 31 December 2022, were included. The main measures were a prescription for an AOM (naltrexone-bupropion, orlistat, phentermine-topiramate, liraglutide 3.0 mg and semaglutide 2.4 mg) and an AOM fill during the study follow-up. RESULTS: We identified 50 678 adults, with a mean body mass index of 38 ± 8 kg/m2 and follow-up of 4.7 ± 2.4 years. Only 8.0% of the cohort had AOM prescriptions and 4.4% had filled prescriptions. In the multivariable analyses, being a man, Black, Hispanic and other race/ethnicity (vs. White), Medicaid, traditional Medicare, Medicare Advantage, self-pay and other insurance types (vs. private insurance) and fourth quartile of the area deprivation index (vs. first quartile) were associated with lower odds of a new prescription. Hispanic ethnicity, being a man, Medicaid, traditional Medicare and Medicare Advantage insurance types, liraglutide and orlistat (vs. naltrexone-buproprion) were associated with lower odds of AOM fill, while phentermine-topiramate was associated with higher odds. Among privately insured individuals, the insurance carrier was associated with both the odds of AOM prescription and fill. CONCLUSIONS: Significant disparities exist in access to AOM both at the prescribing stage and getting the prescription filled based on patient characteristics and insurance type.

Healthcare and Social Needs Assessment and Response Quality Among Black Men.

To understand Black men's healthcare and social needs and determine if the resources that healthcare systems offer meet expectations. We surveyed men who had previously participated in at least one Minority Men's Health Fair in Cleveland, Ohio. In this descriptive study, we spoke with men up to three times (i.e., phases) between May and October 2020 by email and/or telephone. Phase 1 was a needs assessment survey. Phase 2 involved outreach to those who identified a need to provide a resource. Phase 3 determined whether the resource met individuals' needs. We described the demographic characteristics of the survey respondents, the percentage of men reporting a need and wanting a resource, and whether the resource resolved their need. Of the 768 men contacted, 275 completed the survey (36% response rate). The majority of respondents were 50-69 years old, identified as Black, and had at least a bachelor's degree. Eighty-five percent reported a need, of which wellness, financial, and healthcare access were among the top-reported needs. Among the men identifying a need, 35% were interested in a resource. Resources that were provided for employment, behavioral health, oral health, vision, or wellness needs were deemed insufficient. A few individuals reported that resources for food/personal hygiene, financial support, health care access, annual health screening, and medication met their needs. Among men with healthcare and social needs, only a fraction were interested in a resource, and fewer reported that the resource met their needs. These results warrant a greater understanding of what constitutes a resolution of healthcare and social needs from patients' perspectives.

Long-term Outcomes of a 1-year Hypertension Quality Improvement Initiative in a Large Health System.

BACKGROUND: Understanding whether practices retain outcomes attained during a quality improvement (QI) initiative can inform resource allocation. OBJECTIVE: We report blood pressure (BP) control and medication intensification in the 3 years after a 2016 QI initiative ended. RESEARCH DESIGN: Retrospective cohort. SUBJECTS: Adults with a diagnosis of hypertension who had a primary care visit in a large-integrated health system between 2015 and 2019. MEASURES: We report BP control (<140/90 mm Hg) at the last reading of each year. We used a multilevel regression to identify the adjusted propensity to receive medication intensification among patients with an elevated BP in the first half of the year. To examine variation, we identified the average predicted probability of control for each practice. Finally, we grouped practices by the proportion of their patients whose BP was controlled in 2016: lowest performing (<75%), middle (≥75%-<85%), and highest performing (≥85%). RESULTS: The dataset contained 184,981 patients. From 2015 to 2019, the percentage of patients in control increased from 74% to 82%. In 2015, 38% of patients with elevated BP received medication intensification. This increased to 44% in 2016 and 50% in 2019. Practices varied in average BP control (from 62% to 91% in 2016 and 68% to 90% in 2019). All but one practice had a substantial increase from 2015 to 2016. Most maintained the gains through 2019. Higher-performing practices were more likely to intensify medications than lower-performing practices. CONCLUSIONS: Most practices maintained gains 3 years after the QI program ended. Low-performing practices should be the focus of QI programs.

Health-Related Social Needs: Which Patients Respond to Screening and Who Receives Resources?

BACKGROUND: Health systems are screening patients for health-related social needs (HRSN) but the optimal approach is unknown. OBJECTIVE: To describe the variation in responding to an HRSN questionnaire delivered via patient portal, and whether referral to and resources provided by social workers differed by response status. DESIGN: Retrospective observational study. PARTICIPANTS: Primary care patients with a visit between June 2020 and January 2022. INTERVENTION: HRSN questionnaire MAIN MEASURES: We identified each patient's index visit (e.g., date of their first questionnaire response for responders or their first visit within the study period for non-responders). Through the EHR, we identified patients' demographic characteristics. We linked the area deprivation index (ADI) to each patient and grouped patients into quintiles. We used multilevel logistic regressions to identify characteristics associated with responding to the questionnaire and, for responders, reporting a need. We also determined if responder status was associated with receiving a social worker referral or receiving a resource. We included patient demographics and ADI quintile as fixed variables and practice site as a random variable. KEY RESULTS: Our study included 386,997 patients, of which 51% completed at least one HRSN questionnaire question. Patients with Medicaid insurance (AOR: 0.62, 95%CI: 0.61, 0.64) and those who lived in higher ADI neighborhoods had lower adjusted odds of responding (AOR: 0.76, 95% CI: 0.75, 0.78 comparing quintile 5 to quintile 1). Of responders, having Medicaid insurance (versus private) increased the adjusted odds of reporting each of the HRSN needs by two- to eightfold (p < 0.01). Patients who completed a questionnaire (versus non-responders) had similar adjusted odds of receiving a referral (AOR: 0.91, 95% CI: 0.80, 1.02) and receiving a resource from a SW (AOR: AOR: 1.18, 95%CI: 0.79, 1.77). CONCLUSION: HRSN questionnaire responses may not accurately represent the needs of patients, especially when delivered solely via patient portal.

Relationship Between Oral Temperature and Bacteremia in Hospitalized Patients.

BACKGROUND: Early recognition and treatment of bacteremia can be lifesaving. Fever is a well-known marker of bacteremia, but the predictive value of temperature has not been fully explored. OBJECTIVE: To describe temperature as a predictor of bacteremia and other infections. DESIGN: Retrospective review of electronic health record data. SETTING: A single healthcare system comprising 13 hospitals in the United States. PATIENTS: Adult medical patients admitted in 2017 or 2018 without malignancy or immunosuppression. MAIN MEASURES: Maximum temperature, bacteremia, influenza and skin and soft tissue (SSTI) infections based on blood cultures and ICD-10 coding. KEY RESULTS: Of 97,174 patients, 1,518 (1.6%) had bacteremia, 1,392 (1.4%) had influenza, and 3,280 (3.3%) had an SSTI. There was no identifiable temperature threshold that provided adequate sensitivity and specificity for bacteremia. Only 45% of patients with bacteremia had a maximum temperature ≥ 100.4˚F (38˚C). Temperature showed a U-shaped relationship with bacteremia with highest risk above 103˚F (39.4˚C). Positive likelihood ratios for influenza and SSTI also increased with temperature but showed a threshold effect at ≥ 101.0 ˚F (38.3˚C). The effect of temperature was similar but blunted for patients aged ≥ 65 years, who frequently lacked fever despite bacteremia. CONCLUSIONS: The majority of bacteremic patients had maximum temperatures below 100.4 ˚F (38.0˚C) and positive likelihood ratios for bacteremia increased with high temperatures above the traditional definition of fever. Efforts to predict bacteremia should incorporate temperature as a continuous variable.

Relationship Between Primary Care Providers' Perceptions of Alcohol Use Disorder And Pharmacotherapy Prescribing Rates.

AIMS: Acamprosate, naltrexone and disulfiram are underprescribed for alcohol use disorder (AUD) with marked variability among primary care providers (PCPs). We aimed to identify differences between high and low prescribers of medications for AUD (MAUD) with regard to knowledge, experiences, prioritization and attitudes. METHODS: We surveyed PCPs from a large healthcare system with at least 20 patients with AUD. Prescribing rates were obtained from the electronic health record (EHR). Survey responses were scored from strongly disagree (1) to strongly agree (5). Multiple imputation was used to generate attitude scores for 7 missing subjects. PCPs were divided into groups by the median prescribing rate and attitude. Comparisons were made using Wilcoxon rank-sum and regression. RESULTS: Of the 182 eligible PCPs, 68 (37.4%) completed the survey. Most indicated willingness to attend an educational course (57.4%). Compared with low prescribers, high prescribers viewed the effectiveness of medications more favorably (short term 4.0 vs 3.7, P = 0.02; long term 3.5 vs 3.2, P = 0.04) and were more likely to view prescribing as part of their job (3.9 vs 3.4, P = 0.04). PCPs with positive attitudes (72.4%, CI 60.9-83.8%) had a prescribing rate of 5.0% (CI 3.5-6.5%) compared to 1.9% (CI 0.5-3.4%) among those with negative attitudes (P = 0.028). When stratified by attitude, belief in effectiveness was associated with higher prescribing among PCPs with positive attitudes but not those with negative attitudes. CONCLUSIONS: PCPs indicated an interest in learning to prescribe MAUD. However, education alone may not be effective unless physicians have positive attitudes towards patients with AUD.

Primary care physician referral practices regarding BRCA1/2 genetic counseling in a major health system.

PURPOSE: The United States Preventive Services Task Force recommends primary care physicians refer patients at high risk for BRCA1/2 mutations to genetic testing when appropriate. The objective of our study was to describe referrals for BRCA1/2 testing in a large integrated health system and to assess factors associated with referral. METHODS: This retrospective cohort study includes female patients between 18 and 50 years who had a primary care visit in the Cleveland Clinic Health System between 2010 and 2019. We used multivariable logistic regression to estimate differences in the odds of a woman being referred for BRCA1/2 testing by patient factors and referring physician specialty. We also assessed variation in referrals by physicians. RESULTS: Among 279,568 women, 5% were high risk. Of those, 22% were referred for testing. Black patients were significantly less likely to be referred than white patients (aOR 0.87; 95% CI 0.77, 0.98) and Jewish patients were more likely to be referred than non-Jewish patients (aOR 2.13; 95% CI 1.68, 2.70). Patients primarily managed by OB/GYN were significantly more likely to be referred than those cared for via Internal/Family Medicine (aOR 1.45; 95% CI 1.30, 1.61). Less than a quarter of primary care physicians ever referred a patient for testing. CONCLUSION: The majority of primary care patients at high risk for a BRCA1/2 mutation were not referred for testing, and over a decade, most physicians never referred a single patient. Internal/Family Medicine physicians, in particular, need support in identifying and referring women who could benefit from testing.

Reduced Cognitive Burden and Increased Focus: A Mixed-methods Study Exploring How Implementing Scribes Impacted Physicians.

BACKGROUND: Understanding how medical scribes impact care delivery can inform decision-makers who must balance the cost of hiring scribes with their contribution to alleviating clinician burden. OBJECTIVE: The objective of this study was to understand how scribes impacted provider efficiency and satisfaction. DESIGN: This was mixed-methods study. PARTICIPANTS: Internal and family medicine clinicians were included. MEASURES: We administered structured surveys and conducted unstructured interviews with clinicians who adopted scribes. We collected average days to close charts and quantity of after-hours clinical work in the 6 months before and after implementation using electronic health record data. We conducted a difference in difference (DID) analysis using a multilevel Poisson regression. RESULTS: Three themes emerged from the interviews: (1) charting time is less after training; (2) clinicians wanted to continue working with scribes; and (3) scribes did not reduce the overall inbox burden. In the 6-month survey, 76% of clinicians endorsed that working with a scribe improved work satisfaction versus 50% at 1 month. After implementation, days to chart closure decreased [DID=0.38 fewer days; 95% confidence interval (CI): -0.61, -0.15] the average minutes worked after hours on clinic days decreased (DID=-11.5 min/d; 95% CI: -13.1, -9.9) as did minutes worked on nonclinical days (DID=-24.9 min/d; 95% CI: -28.1, -21.7). CONCLUSIONS: Working with scribes was associated with reduced time to close charts and reduced time using the electronic health record, markers of efficiency. Increased satisfaction accrued once scribes had experience.

Patient Perspectives on Self-Monitoring of Blood Glucose When not Using Insulin: a Cross-sectional Survey.

BACKGROUND: Professional societies have recommended against use of self-monitoring blood glucose (SMBG) in non-insulin-treated type 2 diabetes (NITT2D) to control blood sugar levels, but patients are still monitoring. OBJECTIVE: To understand patients' motivation to monitor their blood sugar, and whether they would stop if their physician suggested it. DESIGN: Cross-sectional in-person and electronic survey conducted between 2018 and 2020. PARTICIPANTS: Adults with type 2 diabetes not using insulin who self-monitor their blood sugar. MAIN MEASURES: The survey included questions about frequency and reason for using SMBG, and the impact of SMBG on quality of life and worry. It also asked, "If your doctor said you could stop checking your blood sugar, would you?" We categorized patients based on whether they would stop. To identify the characteristics independently associated with desire to stop SMBG, we performed a logistic regression using backward stepwise selection. KEY RESULTS: We received 458 responses. The common reasons for using SMBG included the doctor wanted the patient to check (67%), desire to see the number (65%), and desire to see if their medications were working (61%). Forty-eight percent of respondents stated that using SMBG reduced their worry about their diabetes and 61% said it increased their quality of life. Fifty percent would stop using SMBG if given permission. In the regression model, respondents who said that they check their blood sugar levels because "I was told to" were more likely to want to stop (AOR: 1.69, 95%CI: 1.11, 2.58). Those that used SMBG due to habit and to understand their diabetes better had lower odds of wanting to stop (AOR: 0.33, 95%CI: 0.18-0.62; AOR: 0.60, 95%CI: 0.39-0.93, respectively). CONCLUSIONS: Primary care physicians should discuss patients' reasons for using SMBG and offer them the option of discontinuing.

Factors Impacting Physician Referral To and Patient Attendance at Weight Management Programs Within a Large Integrated Health System.

BACKGROUND: Identifying which patients receive referrals to and which ones attend weight management programs can provide insights into how physicians manage obesity. OBJECTIVE: To describe patient factors associated with referrals, which primarily reflect physician priorities, and attendance, which reflects patient priorities. We also examine the influence of the individual physician by comparing adjusted rates of referral and attendance across physicians. DESIGN: Retrospective cohort study. PARTICIPANTS: Adults with a body mass index (BMI) ≥ 30 kg/m2 who had a primary care visit between 2015 and 2018 at a large integrated health system MAIN MEASURES: Referrals and visits to programs were collected from the EHR in 2019 and analyzed in 2019-2020. Multilevel logistic regression models were used to identify the association between patient characteristics and (1) receiving a referral, and (2) attending a visit after a referral. We compared physicians' adjusted probabilities of referring patients and of their patients attending a visit. KEY RESULTS: Our study included 160,163 adults, with a median BMI of 35 kg/m2. Seventeen percent of patients received ≥ 1 referral and 29% of those attended a visit. The adjusted odds of referral increased 57% for patients with a BMI 35-39 (versus 30-34) and 32% for each comorbidity (p < 0.01). Attending a visit was less strongly associated with BMI (aOR 1.18 for 35-39 versus 30-34, 95% CI 1.09-1.27) and not at all with comorbidity. For the physician-level analysis, the adjusted probability of referral had a much wider range (0 to 83%; mean = 19%) than did the adjusted probability of attendance (range 27 to 34%). CONCLUSIONS: Few patients attended a weight management program. Physicians vary greatly in their probability of referring patients to programs but not in their patients' probability of attending.

Shared Medical Appointments and Prediabetes: The Power of the Group.

Shared medical appointments, which allow greater access to care and provide peer support, may be an effective treatment modality for prediabetes. We used a retrospective propensity-matched cohort analysis to compare patients attending a prediabetes shared medical appointment to usual care. Primary outcome was patient's weight change over 24 months. Secondary outcomes included change in hemoglobin A1c, low density lipoprotein, and systolic blood pressure. The shared medical appointments group lost more weight (2.88 kg vs 1.29 kg, P = .003), and achieved greater reduction in hemoglobin A1c (-0.87% vs +0.87%, P = .001) and systolic blood pressure (-4.35 mmHg vs +0.52 mmHg, P = .044). The shared medical appointment model can be effective in treating prediabetes.

Do patients who have newly identified prediabetes lose weight in the following year?

BACKGROUND: Identifying a window of opportunity when patients are motivated to lose weight might improve the effectiveness of weight loss counseling. The onset of chronic disease could create such a window. OBJECTIVE: To determine whether identifying prediabetes was associated with subsequent weight loss. METHODS: Our retrospective cohort study included adults with obesity and a primary care visit between 2015 and 2017. Data were collected and analysed in 2019/2020. We compared patients who developed prediabetes [haemoglobin A1c (HbA1c) ≥5.7 and <6.5] to patients with a normal HbA1c (<5.7). We ran linear regression models to identify the association between identifying prediabetes and percent body mass index (BMI) change at 6 and 12 months. The adjusted model controlled for demographic characteristics at baseline, Charlson comorbidity score, and metformin, antipsychotic, antidepressant and antiobesity medication prescribed in either the first 3 months (for the 6-month outcome) or first 9 months (for 12-month outcome) and clustering within physician. RESULTS: Of 11 290 participants, 43% developed prediabetes. At 6 months, 15% of the prediabetes group lost ≥5% of their BMI compared with 13% of the comparison group. The results were similar at 12 months with 18% of the prediabetes group losing ≥5% of their BMI compared with 17%. The prediabetes group lost a higher percentage of their BMI (ß = -0.7% versus -0.3% at 6 months and ß = -0.5% versus 0.01% at 12 months). CONCLUSIONS: While the percent of BMI change was small, patients with newly identified prediabetes lost more weight than a comparison group.

Patients Desire Personalized, Specific, and Continuous Advice on Weight Management.

OBJECTIVE: To deliver effective care, healthcare systems should understand patients' preferences for weight management across a spectrum of needs. Our objective was to describe patients' perceptions of what helps or hinders weight loss and maintenance. METHODS: Semistructured interviews were conducted with patients who accessed weight management services at a large integrated health system in 2018. The interview guide was developed and iteratively refined through a literature search and by consulting experts. Questions included the respondent's weight history, interactions with the health system, and current health status. The analysis used a grounded theory approach, and each transcript was double-coded in 2019. Codes were sorted into themes. All discrepancies were resolved through team discussion. RESULTS: Fifteen patients were interviewed. The majority of respondents (87%) reported multiple weight loss attempts. Three themes were identified. First, advice should be matched to a patient's knowledge and prior experience (eg, using bariatric deck cards). As patients progressed, clinician advice also needed to advance (eg, explaining how to expand food options instead of defining a healthy diet). Second, respondents had a variety of motivating factors, and understanding where motivation is generated from can inform how to design a weight management approach. Third, patients need continual and long-term advice. Some respondents feared becoming ineligible for services if their weight dropped too much. CONCLUSIONS: Health systems can support patients by developing processes for identifying the extent of a patient's knowledge and giving personalized advice based on the patient's preferences and experiences. Reassessing needs at defined intervals may help patients attain and sustain their goals.

Association Between Pain, Blood Pressure, and Medication Intensification in Primary Care: an Observational Study.

BACKGROUND: Treating hypertension is important but physicians often do not intensify blood pressure (BP) treatment in the setting of pain. OBJECTIVE: To identify whether reporting pain is associated with (1) elevated BP at the same visit, (2) medication intensification, and (3) elevated BP at the subsequent visit. DESIGN: Retrospective cohort SETTING: Integrated health system PARTICIPANTS: Adults seen in primary care EXPOSURE: Pain status based on numerical scale: mild (1-3), moderate (4-6), or severe (≥ 7). MAIN MEASURES: We defined elevated BP as ≥ 140/80 mmHg and medication intensification as increasing the dose or adding a new antihypertensive medication. Multilevel regression models were used to find the association between pain and (1) elevated BP at the index visit; (2) medication intensification at the index visit; and (3) elevated BP at the subsequent visit. Models adjusted for demographics, chronic conditions, and clustering within physician. In the third model, we adjusted for initial systolic BP as well. KEY RESULTS: Our population included 56,322 patients; 3155 (6%) reported mild pain, 5050 (9%) reported moderate pain, and 4647 (8%) reported severe pain at the index visit. Compared with no pain, the adjusted odds ratios of elevated BP were 1.38 (95% CI: 1.28-1.48) for severe pain, 1.06 (95% CI: 0.99-1.14) for moderate pain, and 1.02 (95% CI: 0.93-1.12) for mild pain. Adjusted odds ratios of medication intensification at the index visit were 0.65 (95% CI: 0.54-0.80) for mild pain, 0.61 (95% CI: 0.52-0.72) for moderate pain, and 0.55 (95% CI: 0.47-0.64) for severe pain. Among patients with elevated BP at the index visit, reporting pain at the index visit was not associated with elevated BP at the subsequent visit. CONCLUSIONS: When patients reported pain, physicians were less likely to intensify antihypertensive treatment; nevertheless, patients reporting pain were not more likely to have elevated BP at the subsequent visit.

The Impact of Systematic Depression Screening in Primary Care on Depression Identification and Treatment in a Large Health Care System: A Cohort Study.

BACKGROUND: Unless implementation of systematic depression screening is associated with timely treatment, quality measures based on screening are unlikely to improve outcomes. OBJECTIVE: To assess the impact of integrating systematic depression screening with clinical decision support on depression identification and treatment. DESIGN: Retrospective pre-post study. PARTICIPANTS: Adults with a primary care visit within a large integrated health system in 2016 were included. Adults diagnosed with depression in 2015 or prior to their initial primary care visit in 2016 were excluded. INTERVENTION: Initiation of systematic screening using the Patient Health Questionnaire (PHQ) which began in mid-2016. MAIN MEASURES: Depression diagnosis was based on ICD codes. Treatment was defined as (1) antidepressant prescription, (2) referral, or (3) evaluation by a behavioral health specialist. We used an adjusted linear regression model to identify whether the percentage of visits with a depression diagnosis was different before versus after implementation of systematic screening. An adjusted multilevel regression model was used to evaluate the association between screening and odds of treatment. KEY RESULTS: Our study population included 259,411 patients. After implementation, 59% of patients underwent screening. Three percent scored as having moderate to severe depression. The rate of depression diagnosis increased by 1.2% immediately after systematic screening (from 1.7 to 2.9%). The percent of patients with diagnosed depression who received treatment within 90 days increased from 64% before to 69% after implementation (p < 0.01) and the adjusted odds of treatment increased by 20% after implementation (AOR 1.20, 95% CI 1.12-1.28, p < 0.01). CONCLUSIONS: Implementing systematic depression screening within a large health care system led to high rates of screening and increased rates of depression diagnosis and treatment.

Attitudes of High Versus Low Antibiotic Prescribers in the Management of Upper Respiratory Tract Infections: a Mixed Methods Study.

IMPORTANCE: Inappropriate antibiotic use for upper respiratory tract infections (URTIs) is an ongoing problem in primary care. There is extreme variation in the prescribing practices of individual physicians, which cannot be explained by clinical factors. OBJECTIVE: To identify factors associated with high and low prescriber status for management of URTIs in primary care practice. DESIGN AND PARTICIPANTS: Exploratory sequential mixed-methods design including interviews with primary care physicians in a large health system followed by a survey. Twenty-nine physicians participated in the qualitative interviews. Interviews were followed by a survey in which 109 physicians participated. MAIN MEASURES: Qualitative interviews were used to obtain perspectives of high and low prescribers on factors that influenced their decision making in the management of URTIs. A quantitative survey was created based on qualitative interviews and responses compared to actual prescribing rates. An assessment of self-prescribing pattern relative to their peers was also conducted. RESULTS: Qualitative interviews identified themes such as clinical factors (patient characteristics, symptom duration, and severity), nonclinical factors (physician-patient relationship, concern for patient satisfaction, preference and expectation, time pressure), desire to follow evidence-based medicine, and concern for adverse effects to influence prescribing. In the survey, reported concern regarding antibiotic side effects and the desire to practice evidence-based medicine were associated with lower prescribing rates whereas reported concern for patient satisfaction and patient demand were associated with high prescribing rates. High prescribers were generally unaware of their high prescribing status. CONCLUSIONS AND RELEVANCE: Physicians report that nonclinical factors frequently influence their decision to prescribe antibiotics for URTI. Physician concerns regarding antibiotic side effects and patient satisfaction are important factors in the decision-making process. Changes in the health system addressing both physicians and patients may be necessary to attain desired prescribing levels.

The Effect of Starting the Protein-Sparing Modified Fast on Weight Change over 5 years.

BACKGROUND: Ketogenic diets have been highlighted as a way to lose weight while experiencing reduced hunger. The protein-sparing modified fast (PSMF) induces ketosis but may be difficult to maintain. OBJECTIVE: To track weight loss for individuals initiating PSMF versus all other diets (e.g., balanced, high protein) for up to 5 years. DESIGN: Retrospective cohort study PARTICIPANTS: Adults who discussed the PSMF with a clinician between 2007 and 2014 INTERVENTION: Initiating the PSMF diet versus other diets MEASURES: The main outcome was percent weight change up to 5 years. Demographic and health data were collected using electronic health records. We fit regression models including age, sex, race, insurance, new medication prescriptions, and specialist visit to identify the effect of PSMF diet on percent weight change. We grouped patients by percent weight change at each year (≥ 5% loss, 4% loss to 4% gain, ≥ 5% gain) and used Pearson χ2 tests to compare proportions. RESULTS: Of 1,403 eligible patients, 879 (63%) started the PSMF. The PSMF group was slightly younger (52 vs. 54 years, p < 0.01) and had a higher body mass index (41.9 kg/m2 vs. 40.4 kg/m2, p < 0.001). In the adjusted analysis, the PSMF group averaged 3% more weight loss than the other group over the 5-year follow-up (95% CI - 3.5, - 2.0, p < 0.001). PSMF patients lost more weight initially, but by year 4, there was no difference between diets (1.6% versus 1.3%, PSMF versus other diets, p = 0.12). Patients starting the PSMF were more likely to experience ≥ 5% weight loss at 1 year (55% vs 20%, p < 0.001) and 3 years (33% vs. 23% p < 0.05), but not 5 years (34% vs 29%, p = 0.16, PSMF versus other diets, respectively). CONCLUSIONS: In clinical practice, the PSMF achieves rapid weight loss in the first 6 months, but only a small percentage of patients maintained significant weight loss long term.

The Six-Clicks Mobility Measure: A Useful Tool for Predicting Discharge Disposition.

OBJECTIVE: To assess the predictive capabilities of 2 measures of functional mobility, the 6-clicks score and the Braden scale mobility score. We also identified the additional predictive value of adding electronic health record data (demographics, laboratory data, and vital signs) to each model. DESIGN: Cohort study. SETTING: A large integrated health system. PARTICIPANTS: Patients ≥18 years of age (N=17,022) admitted to the inpatient medical service of one of 8 hospitals. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Predictive measures were patient demographics, laboratory values, vital signs, and functional mobility as measured by the 6-clicks score within the first 48 hours of hospital admission. Our outcome was discharge destination (home vs other). RESULTS: Our final sample included 19,963 records. Patients were discharged alive from 19,698 admissions. The majority were women (n=11,729, 59%) with a mean age of 73 (standard deviation, 15.3) years. Patients' initial 6-clicks score had moderate discrimination for discharge destination (c-statistic of 0.78) and outperformed the Braden score (c-statistic of 0.68). Electronic health record data alone had poor discrimination (c-statistic of 0.66) and added little to the model of 6-clicks alone (adjusted c-statistic increased from 0.78 to 0.80). CONCLUSION: Functional mobility measured via 6-clicks within 48 hours of admission can help identify patients who are likely to go home, facilitating early discharge planning.

Physicians' Views of Self-Monitoring of Blood Glucose in Patients With Type 2 Diabetes Not on Insulin.

This qualitative study examines to what extent and why physicans still prescribe self-monitoring of blood glucose (SMBG) in patients with non-insulin-treated type 2 diabetes (NITT2D) when the evidence shows it increases cost without improving hemoglobin A1c (HbA1c), general well being, or health-related quality of life. Semistructured phone interviews with 17 primary care physicians indicated that the majority continue to recommend routine self-monitoring of blood glucose due to a compelling belief in its ability to promote the lifestyle changes needed for glycemic control. Targeting physician beliefs about the effectiveness of self-monitoring of blood glucose, and designing robust interventions accordingly, may help reduce this practice.