Longitudinal Study of Comorbidities and Clinical Outcomes in Persons with Gallstone Disease Using Electronic Health Records.

BACKGROUND: Gallstone disease (GSD) is common and leads to significant morbidity, mortality, and health care utilization in the USA. We examined comorbidities and clinical outcomes among persons with GSD using electronic health records (EHR). METHODS: In this retrospective study of 1,381,004 adults, GSD was defined by ICD-9 code 574 or ICD-10 code K80 using Optum® longitudinal EHR from January 2007 to March 2021. We obtained diagnosis, procedure, prescription, and vital sign records and evaluated associations between demographics, comorbidities, and medications with cholecystectomy, digestive cancers, and mortality. RESULTS: Among persons with GSD, 30% had a cholecystectomy and were more likely to be women, White, and younger, and less likely to have comorbidities, except for obesity, gastroesophageal reflux disease (GERD), abdominal pain, hyperlipidemia, and pancreatitis. Among persons with GSD, 2.2% had a non-colorectal digestive cancer diagnosis during follow-up and risk was 40% lower among persons with a cholecystectomy. Non-colorectal digestive cancer predictors included older age, male sex, non-White race-ethnicity, lower BMI, other cancers, diabetes, chronic liver disease, pancreatitis, GERD, and abdominal pain. Among persons with GSD, mortality was 15.1% compared with 9.7% for the whole EHR sample. Persons with a cholecystectomy had 40% lower mortality risk and mortality predictors included older age, male sex, Black race, lower BMI, and most comorbidities. CONCLUSIONS: In this EHR analysis of persons with GSD, 30% had a cholecystectomy. Mortality was higher compared with the whole EHR sample. Persons with cholecystectomy were less likely to have non-colorectal digestive cancer or to die.

Readmission and Mortality After Hospitalization With Acute Kidney Injury.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) carries high rates of morbidity and mortality. This study quantified various short- and long-term outcomes after hospitalization with AKI. STUDY DESIGN: Retrospective propensity score (PS)-matched cohort study. SETTING & PARTICIPANTS: Optum Clinformatics, a national claims database, was used to identify patients hospitalized with and without an AKI discharge diagnosis between January 2007 and September 2020. EXPOSURE: Among patients with prior continuous enrollment for at least 2years without AKI hospitalization, 471,176 patients hospitalized with AKI were identified and PS-matched to 471,176 patients hospitalized without AKI. OUTCOME(S): All-cause and selected-cause rehospitalizations and mortality 90 and 365 days after index hospitalization. ANALYTICAL APPROACH: After PS matching, rehospitalization and death incidences were estimated using the cumulative incidence function method and compared using Gray's test. The association of AKI hospitalization with each outcome was tested using Cox models for all-cause mortality and, with mortality as competing risk, cause-specific hazard modeling for all-cause and selected-cause rehospitalization. Overall and stratified analyses were performed to evaluate for interaction between an AKI hospitalization and preexisting chronic kidney disease (CKD). RESULTS: After PS matching, AKI was associated with higher rates of rehospitalization for any cause (hazard ratio [HR], 1.62; 95% CI, 1.60-1.65), end-stage renal disease (HR, 6.21; 95% CI, 1.04-36.92), heart failure (HR, 2.81; 95% CI, 2.66, 2.97), sepsis (HR, 2.62; 95% CI, 2.49-2.75), pneumonia (HR, 1.47; 95% CI, 1.37-1.57), myocardial infarction (HR, 1.48; 95% CI, 1.33-1.65), and volume depletion (HR, 1.64; 95% CI, 1.37-1.96) at 90 days after discharge compared with the group without AKI, with similar findings at 365 days. Mortality rate was higher in the group with AKI than in the group without AKI at 90 (HR, 2.66; 95% CI, 2.61-2.72) and 365 days (HR, 2.11; 95% CI, 2.08-2.14). The higher risk of outcomes persisted when participants were stratified by CKD status (P<0.01). LIMITATIONS: Causal associations between AKI and the reported outcomes cannot be inferred. CONCLUSIONS: AKI during hospitalization in patients with and without CKD is associated with increased risk of 90- and 365-day all-cause/selected-cause rehospitalization and death.

Identifying the Prescribing Physician in US Healthcare Claims Data.

BACKGROUND: Identifying the prescribing physician may be essential in studies that use health care claims databases but often there is no single consistent physician identifier (ID) available that spans an entire database and no standard methods have emerged to address this issue. METHODS: Unique Drug Enforcement Administration (DEA) numbers (N=36,721) were identified from the pharmacy claims of a cohort of postmenopausal (55+) initiators of osteoporosis medications (2008-2011) in the United Healthcare database. The proportion of times a Provider ID appeared at least once on the outpatient medical service claims (OMSCs) in the 14 days before a new prescription (Rx) out of the total number of new Rxs for each DEA was calculated and the Provider ID with the highest proportion was considered the most likely match to the DEA. We used regression models to evaluate how characteristics of OMSCs (N=36,721) related to the probability that the provider would be the prescribing physician on a proximal pharmacy claim for each patient (N=20,058). RESULTS: A total of 37,448,056 new Rxs and 132,135,673 OMSCs were associated with the DEAs. Family and general practitioner, hospitalist, and osteoporosis diagnoses were strong predictors of a match. Our models had sensitivities ranging from 81.9% to 82.8% and specificities ranging from 52.4% to 53.5%. CONCLUSIONS: Our algorithms were good at identifying matches for the prescribing physician according to our reference standard but may have included some false positives. Predicted probabilities from our models could be used in other databases where physician IDs are unavailable to help identify the prescriber.

Publication of comparative effectiveness research has not increased in high-impact medical journals, 2004-2013.

OBJECTIVE: To explore the impact of increasing interest and investment in patient-centered research, this study sought to describe patterns of comparative effectiveness research (CER) and patient-reported outcomes (PROs) in pharmacologic intervention studies published in widely read medical journals from 2004-2013. DESIGN AND SETTING: We identified 2335 articles published in five widely read medical journals from 2004-2013 with ≥1 intervention meeting the US Food and Drug Administration's definitions for a drug, biologic, or vaccine. Six trained reviewers extracted characteristics from a 20% random sample of articles (468 studies). We calculated the proportion of studies with CER and PROs. Trends were summarized using locally-weighted means and 95% confidence intervals. RESULTS: Of the 468 sampled studies, 30% used CER designs and 33% assessed PROs. The proportion of studies using CER designs did not meaningfully increase over the study period. However, we observed an increase in the use of PROs. CONCLUSIONS: Among pharmacological intervention studies published in widely read medical journals from 2004-2013, we identified no increase in CER. Randomized, placebo-controlled trials continue to be the dominant study design for assessing pharmacologic interventions. Increasing trends in PRO use may indicate greater acceptance of these outcomes as evidence for clinical benefit.

Comparison of study designs used to detect and characterize pharmacogenomic interactions in nonexperimental studies: a simulation study.

OBJECTIVES: Adverse drug reactions are common, serious, difficult to predict, and may be influenced by genetics, prompting the increasing popularity of pharmacogenomic studies. Many pharmacogenomic studies are conducted in nonexperimental settings, yet little is known about the influence of confounding by contraindication. We, therefore, compared the two designs [the overall population (OPD) and the treated-only (TOD) design] by simulating a pharmacogenomic study of the ECG QT interval (QT). METHODS: Simulations were informed by data from the Atherosclerosis Risk in Communities Study and a literature review examining QT, QT-prolonging drug use, and modification by single nucleotide polymorphisms (SNP). Drug treatment was assigned on the basis of age, sex, and QTlong, representing confounding by contraindication. QT was simulated as a function of drug treatment, one SNP, the drug-SNP interaction, and clinical covariates. RESULTS: Failure to adjust for confounding by contraindication produced a varying degree of bias in the OPD, whereas the TOD was biased by the SNP main effect. For example, in the OPD, the false-positive proportion for the drug-SNP interaction was 5% across the range of SNP main effects (0-10 ms), but increased to 19% without adjusting for confounding by contraindication. In the TOD, the false-positive proportion increased to 89% with SNP main effects greater than 4 ms, although bias was reduced by 39% with adjustment for covariates affected by the SNP. CONCLUSION: The potential for bias from confounding by contraindication (OPD) should be weighed against bias from SNP main effects (TOD) when selecting the study design that best suits the given context.

Risk of fractures requiring hospitalization after an initial prescription for zolpidem, alprazolam, lorazepam, or diazepam in older adults.

OBJECTIVES: To determine whether zolpidem is a safer alternative to benzodiazepines. DESIGN: Retrospective cohort study. SETTING: Community based. PARTICIPANTS: Health maintenance organization members with an initial prescription for zolpidem (n = 43,343), alprazolam (n = 103,790), lorazepam (n = 150,858), or diazepam (n = 93,618). MEASUREMENTS: Zolpidem and benzodiazepine prescriptions were identified from pharmacy databases. Rates of nonvertebral fractures and hip fractures requiring hospitalization were compared before and after an initial prescription for each treatment, adjusting for confounders using doubly robust estimation. RESULTS: In patients aged 65 and older, the rates of nonvertebral fractures and dislocations were similar in the pre- treatment intervals. The rate ratios (RRs) for the 90-day posttreatment interval relative to the pretreatment interval were 2.55 (95% confidence interval (CI) = 1.78-3.65; P < .001) for zolpidem, 1.14 (95% CI = 0.80-1.64; P = .42) for alprazolam, 1.53 (95% CI = 1.23-1.91; P < .001) for lorazepam, and 1.97 (95% CI = 1.22-3.18; P = .01) for diazepam. The ratio of RRs (RRR)-the RR in the posttreatment period adjusted for the corresponding RR in the pretreatment period-were 2.23 (95% CI = 1.36-3.66; P = .006) for zolpidem relative to alprazolam, 1.68 (95% CI = 1.12-2.53; P = .02) for zolpidem relative to lorazepam, and 1.29 (95% CI = 0.72-2.30; P = .32) for zolpidem relative to diazepam. The RRs decreased with time from the initial prescription (trend P < .001), as would be expected if the association is causal. CONCLUSION: In older adults, the risk of injury with zolpidem exceeded that with alprazolam and lorazepam and was similar to that with diazepam. If the associations are causal, then the high incidence of these fractures implies that these treatment induce a substantial number of fractures and consequential costs. Further study of the association is imperative.