Patient feedback and evaluation measures of a physical activity initiative: Exercise is Medicine program.

BACKGROUND: Nearly half of American adults fail to meet national guidelines for physical activity (PA). As a major contributor to the development of preventable chronic diseases, insufficient PA is an important target for health behaviour interventions. Exercise is Medicine (EIM) aims to increase PA levels among primary care patients through routine PA evaluation, prescription, brief counselling, and referral to community resources. PA is treated as a vital sign with the goal of increasing PA levels in prescribed manageable doses. EIM is currently being implemented in UC San Diego Health System's primary care clinics. OBJECTIVE: (i) To collect and summarize patient perceptions of EIM and its components. (ii) To identify discrepancies between patient-reported feedback and primary care provider (PCP) documentation in corresponding visit notes in the electronic medical record (EMR). METHODS: Patient recall of EIM components was measured using a 10-item survey distributed via MyChart. PCP documentation of EIM was tracked in the EMR system. RESULTS: Patient feedback (n = 316) about EIM components was positive and reinforced patients' confidence in their ability to increase PA. Approximately 70% of patients reported having a PA discussion with their PCP at their most recent visit, but only approximately 21% of these discussions were documented by PCPs using the preprogrammed smartphrase in the EMR. CONCLUSION: Overall, patients reported positive perceptions of EIM. While patient perceptions of EIM suggested that PA discussions with PCPs are happening during the majority of visits, PCP documentation fell behind. Documentation via smartphrase may need to be modified for physicians to use.

The Exercise is Medicine (EIM) program encourages primary care patients to increase their weekly physical activity (PA). The program includes an initial PA evaluation, prescription, counselling, and referral to community resources. EIM is currently active at UC San Diego Health System's primary care clinics. In this study, patient feedback of program components is collected and physician documentation in the electronic medical records system is evaluated. Overall, feedback was positive with patients reporting high levels of self-confidence in their ability to increase their weekly PA. Patients indicated that PA was discussed at roughly 70% of all recent visits. However, physician documentation indicated that PA was discussed at approximately 21% of all recent visits. Although PA was successfully addressed, documentation may need to be modified to more accurately reflect EIM program usage.

Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record.

We describe the development and design of a smartphone app-based system to create inpatient progress notes using voice, commercial automatic speech recognition software, with text processing to recognize spoken voice commands and format the note, and integration with a commercial EHR. This new system fits hospital rounding workflow and was used to support a randomized clinical trial testing whether use of voice to create notes improves timeliness of note availability, note quality, and physician satisfaction with the note creation process. The system was used to create 709 notes which were placed in the corresponding patient's EHR record. The median time from pressing the Send button to appearance of the formatted note in the Inbox was 8.8 min. It was generally very reliable, accepted by physician users, and secure. This approach provides an alternative to use of keyboard and templates to create progress notes and may appeal to physicians who prefer voice to typing.

Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

BACKGROUND: Physician and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology. OBJECTIVE: The objective of the study is to gain insight into interprofessional care by developing a computational metric to identify similarities, related concepts and differences in physician and nurse work. METHODS: 58 physician discharge summaries and the corresponding nurse plans of care were transformed into Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). MedLEE, a Natural Language Processing (NLP) program, extracted "physician terms" from free-text physician summaries. The nursing plans of care were constructed using the HANDS© nursing documentation software. HANDS© utilizes structured terminologies: nursing diagnosis (NANDA-I), outcomes (NOC), and interventions (NIC) to create "nursing terms". The physician's and nurse's terms were compared using the UMLS network for relatedness, overlaying the physician and nurse terms for comparison. Our overarching goal is to provide insight into the care, by innovatively applying graph algorithms to the UMLS network. We reveal the relationships between the care provided by each professional that is specific to the patient level. RESULTS: We found that only 26% of patients had synonyms (identical UMLS CUIs) between the two professions' documentation. On average, physicians' discharge summaries contain 27 terms and nurses' documentation, 18. Traversing the UMLS network, we found an average of 4 terms related (distance less than 2) between the professions, leaving most concepts as unrelated between nurse and physician care. CONCLUSION: Our hypothesis that physician's and nurse's practice domains are markedly different is supported by the preliminary, quantitative evidence we found. Leveraging the UMLS network and graph traversal algorithms, allows us to compare and contrast nursing and physician care on a single patient, enabling a more complete picture of patient care. We can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession.

Using voice to create inpatient progress notes: effects on note timeliness, quality, and physician satisfaction.

OBJECTIVES: We describe the evaluation of a system to create hospital progress notes using voice and electronic health record integration to determine if note timeliness, quality, and physician satisfaction are improved. MATERIALS AND METHODS: We conducted a randomized controlled trial to measure effects of this new method of writing inpatient progress notes, which evolved over time, on important outcomes. RESULTS: Intervention subjects created 709 notes and control subjects created 1143 notes. When adjusting for clustering by provider and secular trends, there was no significant difference between the intervention and control groups in the time between when patients were seen on rounds and when progress notes were viewable by others (95% confidence interval -106.9 to 12.2 min). There were no significant differences in physician satisfaction or note quality between intervention and control. DISCUSSION: Though we did not find support for the superiority of this system (Voice-Generated Enhanced Electronic Note System [VGEENS]) for our 3 primary outcomes, if notes are created using voice during or soon after rounds they are available within 10 min. Shortcomings that likely influenced subject satisfaction include the early state of our VGEENS and the short interval for system development before the randomized trial began. CONCLUSION: VGEENS permits voice dictation on rounds to create progress notes and can reduce delay in note availability and may reduce dependence on copy/paste within notes. Timing of dictation determines when notes are available. Capturing notes in near-real-time has potential to apply NLP and decision support sooner than when notes are typed later in the day, and to improve note accuracy.

The Impact of Implementation of a Clinically Integrated Problem-Based Neonatal Electronic Health Record on Documentation Metrics, Provider Satisfaction, and Hospital Reimbursement: A Quality Improvement Project.

BACKGROUND: A goal of effective electronic health record provider documentation platforms is to provide an efficient, concise, and comprehensive notation system that will effectively reflect the clinical course, including the diagnoses, treatments, and interventions. OBJECTIVE: The aim is to fully redesign and standardize the provider documentation process, seeking improvement in documentation based on ongoing All Patient Refined Diagnosis Related Group-based coding records, while maintaining noninferiority comparing provider satisfaction to our existing documentation process. We estimated the fiscal impact of improved documentation based on changes in expected hospital payments. METHODS: Employing a multidisciplinary collaborative approach, we created an integrated clinical platform that captures data entry from the obstetrical suite, delivery room, neonatal intensive care unit (NICU) nursing and respiratory therapy staff. It provided the sole source for hospital provider documentation in the form of a history and physical exam, daily progress notes, and discharge summary. Health maintenance information, follow-up appointments, and running contemporaneous updated hospital course information have selected shared entry and common viewing by the NICU team. The interventions were to (1) improve provider awareness of appropriate documentation through a provider education handout and follow-up group discussion and (2) fully redesign and standardize the provider documentation process building from the native Epic-based software. The measures were (1) hospital coding department review of all NICU admissions and 3M All Patient Refined Diagnosis Related Group-based calculations of severity of illness, risk of mortality, and case mix index scores; (2) balancing measure: provider time utilization case study and survey; and (3) average expected hospital payment based on acuity-based clinical logic algorithm and payer mix. RESULTS: We compared preintervention (October 2015-October 2016) to postintervention (November 2016-May 2017) time periods and saw: (1) significant improvement in All Patient Refined Diagnosis Related Group-derived severity of illness, risk of mortality, and case mix index (monthly average severity of illness scores increased by 11.1%, P=.008; monthly average risk of mortality scores increased by 13.5%, P=.007; and monthly average case mix index scores increased by 7.7%, P=.009); (2) time study showed increased time to complete history and physical and progress notes and decreased time to complete discharge summary (history and physical exam: time allocation increased by 47%, P=.05; progress note: time allocation increased by 91%, P<.001; discharge summary: time allocation decreased by 41%, P=.03); (3) survey of all providers: overall there was positive provider perception of the new documentation process based on a survey of the provider group; (4) significantly increased hospital average expected payments: comparing the preintervention and postintervention study periods, there was a US $14,020 per month per patient increase in average expected payment for hospital charges (P<.001). There was no difference in payer mix during this time period. CONCLUSIONS: A problem-based NICU documentation electronic health record more effectively improves documentation without dissatisfaction by the participating providers and improves hospital estimations of All Patient Refined Diagnosis Related Group-based revenue.

Coding for quality measurement: the relationship between hospital structural characteristics and coding accuracy from the perspective of quality measurement.

This study examines the relationship between hospital structural characteristics and coding accuracy from the perspective of quality measurement. To measure coding accuracy for quality measurement, the study utilizes the "present on admission" indicator, a data element in the New York state hospital administrative database. This data element is used by hospitals across New York state to indicate if a particular secondary diagnosis is "present on admission," "not present on admission," or "uncertain." Since the accurate distinction between comorbidities (present at admission) and complications (not present at admission,) is critical for risk adjustment in comparative hospital quality reports, this study uses the occurrence of the value "uncertain" in the "present on admission" indicator as the primary measure of coding accuracy. A lower occurrence of the value "uncertain" is considered to be reflective of better coding accuracy. Moreover, since coding accuracy of the "present on admission" indicator links back to the accuracy of physician documentation, a focus on the occurrence of the value "uncertain," also helps gain insight into physician documentation efficacy within the facility. By utilizing this approach, therefore, the study serves the twin purpose of 1) addressing the gap in the literature with respect to large-scale studies of "coding for quality," and 2) providing insight into the structural characteristics of institutions that are likely facing organizational challenges of physician documentation from the perspective of quality measurement.