Dataset Information

Errors in Electronic Health Record-Based Data Query of Statin Prescriptions in Patients With Coronary Artery Disease in a Large, Academic, Multispecialty Clinic Practice.

ABSTRACT: BACKGROUND:With the recent implementation of the Medicare Quality Payment Program, providers face increasing accountability for delivering high-quality care. Such pay-for-performance programs aim to leverage systematic data captured by electronic health record (EHR) systems to measure performance; however, the fidelity of EHR query for assessing performance has not been validated compared with manual chart review. We sought to determine whether our institution's methodology of EHR query could accurately identify cases in which providers failed to prescribe statins for eligible patients with coronary artery disease. METHODS AND RESULTS:A total of 9459 patients with coronary artery disease were seen at least twice at the Emory Clinic between July 2014 and June 2015, of whom 1338 (14.1%, 95% confidence interval 13.5-14.9%) had no statin prescription or exemption per EHR query. A total of 120 patient cases were randomly selected and reviewed by 2 physicians for further adjudication. Of the 120 cases initially classified as statin prescription failures, only 21 (17.5%; 95% confidence interval, 11.7-25.3%) represented true failure following physician review. CONCLUSIONS:Sole reliance on EHR data query to measure quality metrics may lead to significant errors in assessing provider performance. Institutions should be cognizant of these potential sources of error, provide support to medical providers, and form collaborative data management teams to promote and improve meaningful use of EHRs. We propose actionable steps to improve the accuracy of EHR data query that require hypothesis testing and prospective validation in future studies.

SUBMITTER: Shin EY

PROVIDER: S-EPMC6015411 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Errors in Electronic Health Record-Based Data Query of Statin Prescriptions in Patients With Coronary Artery Disease in a Large, Academic, Multispecialty Clinic Practice.

Shin Eric Y EY Ochuko Patricia P Bhatt Kunal K Howard Brian B McGorisk Gerard G Delaney Linda L Langdon Kristan K Khosravanipour Marjan M Nambi Andiran A AA Grahovec Allison A Morris Douglas C DC Castellano Penny Z PZ Shaw Leslee J LJ Sperling Laurence S LS Goyal Abhinav A

Journal of the American Heart Association 20180412 8

<h4>Background</h4>With the recent implementation of the Medicare Quality Payment Program, providers face increasing accountability for delivering high-quality care. Such pay-for-performance programs aim to leverage systematic data captured by electronic health record (EHR) systems to measure performance; however, the fidelity of EHR query for assessing performance has not been validated compared with manual chart review. We sought to determine whether our institution's methodology of EHR query ...[more]

PMID: 29650707

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Project description:ImportanceAs health information transparency increases, patients more often seek their health data. More than 44 million patients in the US can now readily access their ambulatory visit notes online, and the practice is increasing abroad. Few studies have assessed documentation errors that patients identify in their notes and how these may inform patient engagement and safety strategies.ObjectiveTo assess the frequency and types of errors identified by patients who read open ambulatory visit notes.Design, setting, and participantsIn this survey study, a total of 136?815 patients at 3 US health care organizations with open notes, including 79 academic and community ambulatory care practices, received invitations to an online survey from June 5 to October 20, 2017. Patients who had at least 1 ambulatory note and had logged onto the portal at least once in the past 12 months were included. Data analysis was performed from July 3, 2018, to April 27, 2020.ExposuresAccess to ambulatory care open notes through patient portals for up to 7 years (2010-2017).Main outcomes and measuresProportion of patients reporting a mistake and how serious they perceived the mistake to be, factors associated with finding errors characterized by patients as serious, and categories of patient-reported errors.ResultsOf 136?815 patients who received survey invitations, 29?656 (21.7%) responded and 22?889 patients (mean [SD] age, 55.16 [15.96] years; 14 447 [63.1%] female; 18 301 [80.0%] white) read 1 or more notes in the past 12 months and completed error questions. Of these patients, 4830 (21.1%) reported a perceived mistake and 2043 (42.3%) reported that the mistake was serious (somewhat serious: 1563 [32.4%]; very serious: 480 [9.9%]). In multivariable analysis, female patients (relative risk [RR], 1.79; 95% CI, 1.72-1.85), more educated patients (RR, 1.38; 95% CI, 1.29-1.48), sicker patients (RR, 1.89; 95% CI, 1.84-1.94), those aged 45 to 64 years (RR, 2.23; 95% CI, 2.06-2.42), those 65 years or older (RR, 2.00; 95% CI, 1.73-2.32), and those who read more than 1 note (2-3 notes: RR, 1.82; 95% CI, 1.34-2.47; ?4 notes: RR, 3.09; 95% CI, 2.02-4.73) were more likely to report a mistake that they found to be serious compared with their reference groups. After categorization of patient-reported very serious mistakes, those specifically mentioning the word diagnosis or describing a specific error in current or past diagnoses were most common (98 of 356 [27.5%]), followed by inaccurate medical history (85 of 356 [23.9%]), medications or allergies (50 of 356 [14.0%]), and tests, procedures, or results (30 of 356 [8.4%]). A total of 23 (6.5%) reflected notes reportedly written on the wrong patient. Of 433 very serious errors, 255 (58.9%) included at least 1 perceived error potentially associated with the diagnostic process (eg, history, physical examination, tests, referrals, and communication).Conclusions and relevanceIn this study, patients who read ambulatory notes online perceived mistakes, a substantial proportion of which they found to be serious. Older and sicker patients were twice as likely to report a serious error compared with younger and healthier patients, indicating important safety and quality implications. Sharing notes with patients may help engage them to improve record accuracy and health care safety together with practitioners.

Project description:BackgroundPrescribing error represent a significant source of preventable harm to patients. Prescribing errors at discharge, including omission of pre-admission medications (PAM), are particularly harmful as they frequently propagate following discharge. This study assesses the impact of an educational intervention and introduction of an electronic patient record (EPR) in the same centre on omission of PAM at discharge using a pragmatic design. A survey of newly qualified doctors is used to contextualise findings.MethodsDischarge prescriptions and discharge summaries were reviewed at discharge, and compared to admission medicine lists, using a paper-based chart system. Discrepancies were noted, using Health Information and Quality Authority guidelines for discharge prescribing. An educational intervention was conducted. Further review of discharge prescriptions and discharge summaries took place. Following introduction of an EPR, review of discharge summaries and discharge prescriptions was repeated. A survey was administered to recently qualified doctors (interns), and analysed using descriptive statistics and thematic analysis.ResultsOmission of PAM as prescribed or discontinued items at discharge occurs frequently. An educational intervention did not significantly change prescribing error rates (U = 1255.5, p = 0.206). EPR introduction did significantly reduce omission of PAM on discharge prescribing (U = 694, p < 0.001), however there was also a reduction in the rate of deliberate discontinuation of PAM at discharge (U = 1237.5, p = 0.007). Survey results demonstrated that multiple sources are required to develop a discharge prescription. Time pressure, access to documentation and lack of admission medicine reconciliation are frequently cited causes of discharge prescribing error.ConclusionThis study verified passive educational interventions alone do not improve discharge prescribing. Introduction of EPR improved discharge prescribing, but negatively impacted deliberate discontinuation of PAM at discharge. This is attributable to reduced access to key sources of information used in formulating discharge prescriptions, and separation of the discontinuation function from the prescribing function on the EPR discharge application.

Project description:BackgroundPrescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact.ObjectiveEvaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters.DesignDifference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to controls in Pennsylvania (PA) from 1 year prior to the implementation of a NJ state prescribing limit (May 2016-May 2017) to 10 months after (May 2017-March 2018).ParticipantsAdults with new opioid prescriptions in an academic health system with practices in PA and NJ.InterventionsState 5-day opioid prescribing limit plus health system and health system EMR alert.Main measuresChanges in morphine milligram equivalents (MME) and tablet quantity per prescription, refills, and encounters, adjusted for patient and prescriber characteristics.Key resultsThere were a total of 678 new prescriptions in NJ and 4638 in PA. Prior to the intervention, median MME/prescription was 225 mg in NJ and 150 mg in PA, and median quantity was 30 tablets in both. After implementation, median MME/prescription was 150 mg in both states, and median quantity was 20 in NJ and 30 in PA. In the adjusted model, there was a greater decrease in mean MME and tablet quantity in NJ relative to PA after implementation of the policy plus alert (- 82.99 MME/prescription, 95% CI - 148.15 to - 17.84 and - 10.41 tabs/prescription, 95% CI - 19.70 to - 1.13). There were no significant differences in rates of refills or encounters at 30 days based on exposure to the interventions.ConclusionsImplementation of a prescribing limit and EMR alert was associated with an approximately 22% greater decrease in opioid dose per new prescription in NJ compared with controls in PA. The combination of prescribing limits and alerts may be an effective strategy to influence prescriber behavior.

Dataset Information

Errors in Electronic Health Record-Based Data Query of Statin Prescriptions in Patients With Coronary Artery Disease in a Large, Academic, Multispecialty Clinic Practice.

Publications

Errors in Electronic Health Record-Based Data Query of Statin Prescriptions in Patients With Coronary Artery Disease in a Large, Academic, Multispecialty Clinic Practice.

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