Clinical informatics to improve quality of care: a population-based system for patients with diabetes mellitus

Background The prevalence of diabetes mellitus is increasing in the USA. However, control of intermediate outcome measures remains substandard. Recently, significant emphasis has been placed on the value of electronic medical records and informatics systems to improve the delivery of health care. Objective To determine whether a clinical informatics system improves care of patients with diabetes mellitus. Methods In this quality improvement pilot initiative, we identified 48 patients with diabetes mellitus who were due for their annual haemoglobin A1c (HbA1c), low-density lipoprotein (LDL) and microalbumin tests. Through our newly developed clinical informatics initiative, patients were reminded to schedule tests and a physician appointment. Seventy-five patients without reminders served as controls. Results A significant improvement in LDL control was achieved in the intervention group (35.4% vs 13.3%; P=0.004). The intervention group had a greater percentage of patients who underwent the three tests, and members of this group also showed greater control of haemoglobin A1c, but these differences were not statistically significant. Conclusions A clinical informatics system, used to deliver proactive, co-ordinated care to a population of patients with diabetes mellitus, can improve process and also quality outcome measures. Larger studies are needed to confirm these early findings

Do primary care providers who prescribe more opioids have higher patient panel satisfaction scores?

Objectives: Opioid prescribing in the United States has tripled since 1999. At the same time, there has been increasing attention to patient satisfaction. It has been suggested that providers concerned about patient satisfaction may be more likely to treat pain with opioids. We examined primary care providers’ opioid prescribing practices to determine if higher provider opioid prescribing was associated with higher patient satisfaction. Methods: For 77 primary care providers, we compared each provider’s opioid prescription count and amount prescribed to each provider’s patient panel satisfaction measures. Satisfaction measures were obtained from surveys following office visits and consisted of Likert-type scale answers concerning satisfaction for pain management and other provider satisfaction domains. Satisfaction surveys were generated independent of patient complaint of pain and had the aim of overall assessment of patient satisfaction with the provider and the healthcare system. We assessed the correlation between opioid prescribing and patient panel pain management satisfaction using linear regression models with and without adjustment for patient complexity. Results: We observed no statistically significant correlation between patient panel satisfaction with their provider and the quantity of opioids that the provider prescribed (R 2  = 0.006; p = 0.52). There was also no correlation between patient panel satisfaction and the number of opioid prescriptions written by their provider (R 2  = 0.005; p = 0.54). Additional multivariate analysis after adjusting for patient complexity also demonstrated no correlation of pain management satisfaction with opioids prescribed. Although the quantity of opioid prescriptions was not correlated with pain management satisfaction, several other patient satisfaction measures correlated significantly with pain management satisfaction. Conclusion: Primary care providers with a greater rate of opioid prescribing did not have higher patient panel satisfaction scores for pain management. In primary care, providers who want to improve patient satisfaction should focus on other components of patient care besides opioid-based pain management

Population health challenges in primary care: What are the unfinished tasks and who should do them?

Background: There are numerous recommendations from expert sources that help guide primary care providers in cancer screening, infectious disease screening, metabolic screening, monitoring of drug levels, and chronic disease management. Little is known about the potential effort needed for a healthcare system to address these recommendations, or the patient effort needed to complete the recommendations. Methods: For 73 recommended population healthcare items, we examined each of 28,742 patients in a primary care internal medicine practice to determine whether they were up-to-date on recommended screening, immunizations, counseling, and chronic disease management goals. We used a rule-based software tool that queries the medical record for diagnoses, dates, laboratory values, pathology reports, and other information used in creating the individualized recommendations. We counted the number of uncompleted recommendations by age groups and examined the healthcare staff needed to address the recommendations and the potential patient effort needed to complete the recommendations. Results: For the 28,742 patients, there were 127,273 uncompleted recommendations identified for population health management (mean recommendations per patient 4.36, standard deviation of 2.65, range of 0–17 recommendations per patient). The age group with the most incomplete recommendations was age of 50–65 years with 5.5 recommendations per patient. The 18–35 years age group had the fewest incomplete recommendations with 2.6 per patient. Across all age groups, initiation of these recommendations required high-level input (physician, nurse practitioner, or physician’s assistant) in 28%. To completely adhere to recommended services, a 1000-patient cross-section cohort would require a total of 464 procedures and 1956 lab tests. Conclusion: Providers and patients face a daunting number of tasks necessary to meet guideline-generated recommendations. We will need new approaches to address the burgeoning numbers of uncompleted recommendations

Comparable outcomes of outpatient remdesivir and sotrovimab among high-risk patients with mild to moderate COVID-19 during the omicron BA.1 surge

Abstract Studies conducted prior to SARS-CoV-2 Omicron demonstrated that sotrovimab and remdesivir reduced hospitalization among high-risk outpatients with mild to moderate COVID-19. However, their effectiveness has not been directly compared. This study examined all high-risk outpatients with mild to moderate COVID-19 who received either remdesivir or sotrovimab at Mayo Clinic during the Omicron BA.1 surge from January to March 2022. COVID-19-related hospitalization or death within 28 days were compared between the two treatment groups. Among 3257 patients, 2158 received sotrovimab and 1099 received remdesivir. Patients treated with sotrovimab were younger and had lower comorbidity but were more likely to be immunocompromised than remdesivir-treated patients. The majority (89%) had received at least one dose of COVID-19 vaccine. COVID-19-related hospitalization (1.5% and 1.0% in remdesivir and sotrovimab, respectively, p = .15) and mortality within 28 days (0.4% in both groups, p = .82) were similarly low. A propensity score weighted analysis demonstrated no significant difference in the outcomes between the two groups. We demonstrated favorable outcomes that were not significantly different between patients treated with remdesivir or sotrovimab

High rates of cancer screening among dialysis patients seen in primary care a cohort study

Routine preventive cancer screening is not recommended for patients with end-stage renal disease (ESRD)11 Notable abbreviations: primary care (PC), End Stage Renal Disease (ESRD), United States Renal Data System (USRDS). due to their limited life expectancy. The current extent of cancer screening in this population is unknown. Primary care (PC) reminder systems or performance incentives may encourage indiscriminate cancer screening. We compared rates of cancer screening in patients with ESRD, with and without PC visits. This is a retrospective cohort study using United States Renal Data System (USRDS) billing data and electronic medical record data. Patients aged ≥18 years starting dialysis from 2001 to 2008, Midwest regional dialysis network were categorized with or without a PC visit (defined as an office visit in family practice, internal medicine, pediatrics, geriatrics or preventive medicine during the first two years of dialysis). Cancer screening was based on Current Procedural Terminology codes in USRDS. We identified 2512 incident dialysis patients (60% men, median age 65y). Cancer screening rates were more frequent among those seen in PC: 38% vs 19% (P = 0.0002), for breast; 18% vs 10% (P = 0.047) for cervical; 13% versus 8% (P = 0.024) for prostate; and 18% vs 9% (P = 0.0002) for colon cancer. Multivariable analyses found that those with PC were more likely to be screened after adjusting for age, sex, and comorbidities.In our practice, cancer screening rates among chronic dialysis patients are lower than those previously reported for our general population (64% for breast cancer). However, a sizeable proportion of our ESRD population does receive cancer screening, especially those still seen in primary care. Keywords: Breast cancer screening, Cervical cancer screening, Colon cancer screening, Dialysis, ESRD, Preventive screening, Prostate cancer screenin

Protocol for the <it>Osteoporosis Choice </it>trial. A pilot randomized trial of a decision aid in primary care practice

Abstract Background Bisphosphonates can reduce fracture risk in patients with osteoporosis, but many at-risk patients do not start or adhere to these medications. The aims of this study are to: (1) preliminarily evaluate the effect of an individualized 10-year osteoporotic fracture risk calculator and decision aid (OSTEOPOROSIS CHOICE) for postmenopausal women at risk for osteoporotic fractures; and (2) assess the feasibility and validity (i.e., absence of contamination) of patient-level randomization (vs. cluster randomization) in pilot trials of decision aid efficacy. Methods/Design This is a protocol for a parallel, 2-arm, randomized trial to compare an intervention group receiving OSTEOPOROSIS CHOICE to a control group receiving usual primary care. Postmenopausal women with bone mineral density T-scores of STEOPOROSIS CHOICE on five outcomes: (a) patient knowledge regarding osteoporosis risk factors and treatment; (b) quality of the decision-making process for both the patient and clinician; (c) patient and clinician acceptability and satisfaction with the decision aid; (d) rate of bisphosphonate use and adherence, and (e) trial processes (e.g., ability to recruit participants, collect patient outcomes). To capture these outcomes, we will use patient and clinician surveys following each visit and video recordings of the clinical encounters. These video recordings will also allow us to determine the extent to which clinicians previously exposed to the decision aid were able to recreate elements of the decision aid with control patients (i.e., contamination). Pharmacy prescription profiles and follow-up phone interviews will assess medication start and adherence at 6 months. Discussion This pilot trial will provide evidence of feasibility, validity of patient randomization, and preliminary efficacy of a novel approach -- decision aids -- to improving medication adherence for postmenopausal women at risk of osteoporotic fractures. The results will inform the design of a larger trial that could provide more precise estimates of the efficacy of the decision aid. Trial registration Clinical Trials.gov Identifier: NCT00578981</p