The effect of health information technology implementation in Veterans Health Administration hospitals on patient outcomes

A Novel Use of Bar Code Medication Administration Data to Assess Nurse Staffing and Workload

OBJECTIVE

The aim of the study is to introduce an innovative use of bar code medication administration (BCMA) data, medication pass analysis, that allows for the examination of nurse staffing and workload using data generated during regular nursing workflow.

METHODS

Using 1 year (October 1, 2014-September 30, 2015) of BCMA data for 11 acute care units in one Veterans Affairs Medical Center, we determined the peak time for scheduled medications and included medications scheduled for and administered within 2 hours of that time in analyses. We established for each staff member their daily peak-time medication pass characteristics (number of patients, number of peak-time scheduled medications, duration, start time), generated unit-level descriptive statistics, examined staffing trends, and estimated linear mixed-effects models of duration and start time.

RESULTS

As the most frequent (39.7%) scheduled medication time, 9:00 was the peak-time medication pass; 98.3% of patients (87.3% of patient-days) had a 9:00 medication. Use of nursing roles and number of patients per staff varied across units and over time. Number of patients, number of medications, and unit-level factors explained significant variability in registered nurse (RN) medication pass duration (conditional R2  = 0.237; marginal R2  = 0.199; intraclass correlation = 0.05). On average, an RN and a licensed practical nurse (LPN) with four patients, each with six medications, would be expected to take 70 and 74 minutes, respectively, to complete the medication pass. On a unit with median 10 patients per LPN, the median duration (127 minutes) represents untimely medication administration on more than half of staff days. With each additional patient assigned to a nurse, average start time was earlier by 4.2 minutes for RNs and 1.4 minutes for LPNs.

CONCLUSION

Medication pass analysis of BCMA data can provide health systems a means for assessing variations in staffing, workload, and nursing practice using data generated during routine patient care activities.

Outcomes of health information technology utilization in nursing homes: Do implementation processes matter?

We examined several outcomes of health information technology utilization in nursing homes and how the processes used to implement health information technology affected these outcomes. We hypothesized that one type of health information technology, electronic medical records, will improve efficiency and quality-related outcomes, and that the use of effective implementation processes and change leadership strategies will improve these outcomes. We tested these hypotheses by creating an original survey based on the case study literature, which we sent to the top executives of nursing homes in seven US states. The administrators reported that electronic medical record adoption led to moderately positive efficiency and quality outcomes, but its adoption was unrelated to objective quality indicators obtained from regulatory agencies. Improved electronic medical record implementation processes, however, were positively related to administrator-reported efficiency and quality outcomes and to decreased deficiency citations at the next regulatory visit to the nursing home. Change leadership processes did not matter as much as technological implementation processes.

Advocating for Greater Usability in Clinical Technologies: The Role of the Practicing Nurse

Health care, especially ICUs, rely on multiple types of technology to promote the best patient outcomes. Unfortunately, too often these technologies are poorly designed, causing errors, additional workload, and unnecessary frustration. The purpose of this article is to (1) empower nurses with the needed usability and usability testing vocabulary to identify and articulate clinical technology usability problems and (2) provide ideas on ways nurses can advocate to have an impact on positive change related to technology usability within a health care organization.

Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study

Background

Little is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.

Objective

To understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.

Methods

Informed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.

Results

The study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.

Conclusions

The study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.

Health Information Technology (HIT) Adaptation: Refocusing on the Journey to Successful HIT Implementation

In past years, policies and regulations required hospitals to implement advanced capabilities of certified electronic health records (EHRs) in order to receive financial incentives. This has led to accelerated implementation of health information technologies (HIT) in health care settings. However, measures commonly used to evaluate the success of HIT implementation, such as HIT adoption, technology acceptance, and clinical quality, fail to account for complex sociotechnical variability across contexts and the different trajectories within organizations because of different implementation plans and timelines. We propose a new focus, HIT adaptation, to illuminate factors that facilitate or hinder the connection between use of the EHR and improved quality of care as well as to explore the trajectory of changes in the HIT implementation journey as it is impacted by frequent system upgrades and optimizations. Future research should develop instruments to evaluate the progress of HIT adaptation in both its longitudinal design and its focus on adaptation progress rather than on one cross-sectional outcome, allowing for more generalizability and knowledge transfer.

Usability and Workflow Evaluation of "RhEumAtic Disease activitY" (READY). A Mobile Application for Rheumatology Patients and Providers

BACKGROUND

RhEumAtic Disease activitY (READY) is a mobile health (mHealth) application that aims to create a shared platform integrating data from both patients and physicians, with a particular emphasis on arthritis disease activity.

METHODS

We made READY available on an iPad and pilot implemented it at a rheumatology outpatient clinic. We conducted 1) a usability evaluation study to explore patients' and physicians' interactions with READY, and 2) a time motion study (TMS) to observe the clinical workflow before and after the implementation.

RESULTS

A total of 33 patients and 15 physicians participated in the usability evaluation. We found usability problems in navigation, data entry, pain assessment, documentation, and instructions along with error messages. Despite these issues, 25 (75,76%) patients reported they liked READY. Physicians provided mixed feedback because they were concerned about the impact of READY on clinical workflow. Six physicians participated in the TMS. We observed 47 patient visits (44.72 hours) in the pre-implementation phase, and 42 patient visits (37.82 hours) in the post-implementation phase. We found that patients spent more time on READY than paper (4.39mins vs. 2.26mins), but overall, READY did not delay the workflow (pre = 52.08 mins vs. post = 45.46 mins). This time difference may be compensated with READY eliminating a workflow step for the staff.

CONCLUSION

Patients preferred READY to paper documents. Many found it easier to input information because of the larger font size and the ease of 'tapping' rather than writing-out or circling answers. Even though patients spent more time on READY than using paper documents, the longer usage of READY was mainly due to when troubleshooting was needed. Most patients did not have problems after receiving initial support from the staff. This study not only enabled improvements to the software but also serves as good reference for other researchers or institutional decision makers who are interested in implementing such a technology.

Adverse inpatient outcomes during the transition to a new electronic health record system: observational study

OBJECTIVE

 To assess the short term association of inpatient implementation of electronic health records (EHRs) with patient outcomes of mortality, readmissions, and adverse safety events.

DESIGN

 Observational study with difference-in-differences analysis.

SETTING

 Medicare, 2011-12.

PARTICIPANTS

 Patients admitted to 17 study hospitals with a verifiable "go live" date for implementation of inpatient EHRs during 2011-12, and 399 control hospitals in the same hospital referral region.

MAIN OUTCOME MEASURES

 All cause readmission within 30 days of discharge, all cause mortality within 30 days of admission, and adverse safety events as defined by the patient safety for selected indicators (PSI)-90 composite measure among Medicare beneficiaries admitted to one of these hospitals 90 days before and 90 days after implementation of the EHRs (n=28 235 and 26 453 admissions), compared with the control group of all contemporaneous admissions to hospitals in the same hospital referral region (n=284 632 and 276 513 admissions). Analyses were adjusted for beneficiaries' sociodemographic and clinical characteristics.

RESULTS

 Before and after implementation, characteristics of admissions were similar in both study and control hospitals. Among study hospitals, unadjusted 30 day mortality (6.74% to 7.15%, P=0.06) and adverse safety event rates (10.5 to 11.4 events per 1000 admissions, P=0.34) did not significantly change after implementation of EHRs. There was an unadjusted decrease in 30 day readmission rates, from 19.9% to 19.0% post-implementation (P=0.02). In difference-in-differences analysis, however, there was no significant change in any outcome between pre-implementation and post-implementation periods (all P≥0.13).

CONCLUSIONS

 Despite concerns that implementation of EHRs might adversely impact patient care during the acute transition period, we found no overall negative association of such implementation on short term inpatient mortality, adverse safety events, or readmissions in the Medicare population across 17 US hospitals.

Toward a More Robust and Efficient Usability Testing Method of Clinical Decision Support for Nurses Derived From Nursing Electronic Health Record Data

PURPOSE

To develop methods for rapid and simultaneous design, testing, and management of multiple clinical decision support (CDS) features to aid nurse decision-making.

METHODS

We used quota sampling, think-aloud and cognitive interviews, and deductive and inductive coding of synchronized audio video data and archival libraries.

FINDINGS

Our methods and organizational tools allowed us to rapidly improve the usability, understandability, and usefulness of CDS in a generalizable sample of practicing nurses.

CONCLUSIONS

The method outlined allows the rapid integration of nursing terminology based electronic health record data into routine workflow and holds strong potential for improving patient outcomes.

IMPLICATIONS FOR NURSING PRACTICE

The methods and organizational tools for development of multiple CDS system features can be used to translate knowledge into practice.