Integrating Self-Service Kiosks into Healthcare Delivery Organizations

Self-service kiosks in healthcare delivery organizations (HDOs) have the potential to provide operational efficiencies and customer service benefits. Yet to date there has been little research on how organizations can effectively integrate these self-service technologies into the point-of-service to achieve these potential benefits. This research-in-progress study addresses this research gap by studying a multi-phase pilot project being conducted within an integrated U.S. healthcare system. The same kiosk hardware and software is being deployed within several outpatient clinics at four medical centers, and adoption by several interdependent user groups is needed to achieve administrative and clinical benefits. Qualitative research methods are used to analyze interview data collected from key stakeholders. Pre- and post- implementation findings are presented as well as a preliminary model that details influential variables specific to the HDO context

Choking on Sand: Diffuse Calcification of the Lungs from Pulmonary Alveolar Microlithiasis

INTRODUCTION: Widespread pulmonary calcification is a relatively uncommon finding in patients presenting with dyspnea; differential diagnosis is limited, particularly when accompanied by a diffuse “sandstorm” appearance on plain radiographs. Pulmonary alveolar microlithiasis (PAM) is an extremely rare genetic disease characterized by deposition of calcium phosphate microliths choking the alveoli and small airways. CASE DESCRIPTION: A 33-year-old female immigrant from the Mediterranean region presented for acute on chronic dyspnea. Her 10-year history of exertional dyspnea was punctuated by two days of acute, unremitting, exertional and resting dyspnea with associated fever, pleurisy, and anxiety. Initial room air oximetry was 68%, increasing to 92% on 2L supplemental oxygen. Exam showed cachexia, tachypnea without accessory muscle usage, and diffuse bronchial breath sounds. Laboratory evaluation revealed polycythemia, and computed tomography showed essentially complete lung opacification with diffuse confluent sand-type calcific opacities with air bronchograms. Extensive inpatient workup for a precipitating infectious or rheumatologic etiology of acute decline was largely fruitless, including blood and sputum cultures, atypical respiratory panel, fungal cultures, and autoimmune workup. Quantiferon gold testing was positive. Bronchoalveolar lavage showed scattered calcified concretions. She was discharged on supplemental oxygen to follow up with an interstitial lung disease specialist and complete latent tuberculosis treatment. She was unfortunately lost to follow up after returning to her home country. DISCUSSION: Lung tissue calcification can be organized into three main categories: metastatic calcification (i.e., deposition in normal tissue due to systemic disease); dystrophic calcification (i.e., deposition due to trauma or previously abnormal tissue), and PAM – a rare genetic mutation producing an abnormal type IIb sodium phosphate cotransporter in alveolar type II cells, from mutation of the SLC34A2 gene1. The dysfunctional cotransporter fails to clear phosphate from degraded surfactant, resulting in microlith accumulation, chronic inflammation, tissue destruction, pulmonary fibrosis, and respiratory failure2,3. PAM has been diagnosed in 65 countries and is most common in Asia. There is a spectrum of disease severity; some patients present asymptomatically, discovered based on incidental abnormal radiographs, and some present in respiratory failure. CT chest plus bronchoscopy with bonchoalveolar lavage is typically used for diagnosis. Clinical course varies but most patients progress to respiratory failure and cor pulmonale. Currently the only definitive treatment is lung transplantation1. Widespread or multifocal calcification is rare. When diffuse alveolar calcific disease is present, the differential should include metastatic pulmonary calcification and pulmonary alveolar microlithiasis. In our patient, progression of her underlying lung pathology was suspected as etiology of progressively worsening dyspnea.N

Emergency Department Utilization and Hierarchical Condition Category Risk Scores

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) introduced Comprehensive Primary Care Plus (CPC+) to improve the quality of primary care services nationwide. CPC+ utilization measures use a risk-adjustment model to predict utilization for different patient populations. Risk is determined using Hierarchical Condition Categories (HCCs), which are based on ICD-10 codes and patient demographics. Since patients with higher HCC scores are expected to have higher utilization rates, CMS uses these calculations to compare practices and categorize patients into “risk tiers,” which guide payments. OUSCM participates in CPC+ (Track 2). In order to track our patients’ emergency department utilization (EDU), search for patterns of use, and identify opportunities for quality improvement, we sought to determine (1) what associations exist between HCC risk tiers and patterns of EDU and (2) what patient characteristics are associated with HCC risk scores. METHODS: We analyzed cross-sectional CPC+ data for fiscal year 2018 provided by CMS. We performed multiple linear regression, Tukey’s method, and independent-samples t-tests to explore possible relationships between EDU, HCC risk score and associated risk tiers (range 1-5), and patient characteristics, such as dual-eligibility status and age. The study population included 906 Medicare-only and 1173 dual-eligible patients aged 18 years and older attributed to the OUSCM Internal Medicine (n=1122) or Family Medicine (n=957) practice. RESULTS: Our patient population had a median HCC risk score of 0.93 (CMS-reported Oklahoma median risk score = 0.74). We found that 56.4% of our patients were dual-eligible compared to the national average of 19.4%. Tukey multiple comparison test demonstrated significant differences between risk tiers and ED visits (p < .05). Dual-eligible patients had a higher average HCC risk score than Medicare-only patients (t(2072) = 8.491; p < .00001) and a higher average number of ED visits (t(2077) = 3.9577; p < .00001). Age was weakly correlated with HCC risk scores (r = .074, p = .0228). Density analysis of HCC scores by age revealed evidence of low-risk clustering for adults between 45 and 75 years of age. CONCLUSION: HCC risk tier classifications are predictive of EDU rates in our patient population. However, our overall HCC score was lower than anticipated given the complexity of our patient population. Dual-eligible status was associated with higher risk and EDU rates. However, age–typically an independent predictor of morbidity and mortality–was only weakly correlated with HCC scores, suggesting clinicians may be undercoding encounters for adults between the ages of 45 and 75 years, which decreases revenue.N

Primary care provider perceptions and use of a novel medication reconciliation technology

Background Although medication reconciliation (MR) can reduce medication discrepancies, it is challenging to operationalise. Consequently, we developed a health information technology (HIT) to collect a patient medication history and make it available to the primary care (PC) provider. We deployed a self-service kiosk in a PC clinic that permits patients to indicate a medication adherence history. Patient responses are immediately viewable in the legacy electronic health record. This paper describes a survey developed to assess PC provider perceptions of our HIT and HIT implementation effectiveness. Methods We developed and administered a survey to all PC providers to assess technology implementation effectiveness. The survey included scales measuring (1) user attitudes towards MR, (2) perceptions of our HIT and (3) the local organisational climate for implementation. We also assessed the consistency and quality of tool use. Results Nearly 90% of PC providers responded to the survey and 58% indicated that they were familiar with the technology and had seen the tool output. Most providers believed that MR represented an important safety intervention, although 43% did not believe that they had the necessary resources to manage discrepancies. Composite scale scores for the 58% of respondents familiar with the HIT indicate that the majority favoured our tool over usual care. However, composite scale scores suggest that the climate for implementation at our facility was suboptimal. Overall, the quality and consistency of tool use among providers was very heterogeneous. Conclusions A patient self-service kiosk offers an efficientmechanismto collect amedication adherence history; provider survey responses indicate that they appreciated and used the MR kiosk output. Nonetheless, opportunities exist to improve data displays and embed decision support to facilitate discrepancy management

Improving Outpatient Follow-Up After Hospitalization

Introduction: Hospital readmission is costly, in both patient quality of life and healthcare expenditures. Timely post-discharge follow-up has shown to reduce preventable readmissions. Efforts should be aimed at improving coordination of follow-ups. The aim of this quality improvement project was to increase post-hospital discharge follow-up by 20% for academic primary care patients admitted to a local tertiary care hospital by June 2020. This QI project was conducted at St. John Medical Center and the OU Internal Medicine Clinic utilizing Plan-Do-Study-Act methodology (PDSA). Patients admitted to OU inpatient teams who also designated OU Internal Medicine as their PCP were included in the study. An EMR query was utilized to measure follow-ups completed within 14 days of discharge. A process map was made, showing intervention points. Gap Analysis/Scatter Diagram was used to show points of largest impact. Methods: PDSA #1: Senior residents were given access to AllScripts (the clinic EMR scheduling program) to directly schedule patient follow-up appointments within 14 days of discharge. Follow-up appointments were included in patients’ discharge paperwork.    PDSA #2: Prior to discharge, patients were screened by care managers for a follow-up home visit. If appropriate, a multidisciplinary team of providers conducted an onsite follow-up visit within 14 days of discharge. Results: After PDSA #1: Residents surveyed after the first PDSA cycle admitted feeling overwhelmed with additional tasks and inconsistently scheduled appointments in AllScripts. In addition, EMR review demonstrated a high no-show rate for patients with follow-up appointments. Due to these results, we sought alternative options. After PDSA #2: Three patients were visited in their homes for an onsite 14-day follow-up appointment. Unfortunately, this process was put on hold given the COVID outbreak. At baseline, 31.6% of patients discharged from the hospital attended post-discharge follow-up visit within 14 days. This percentage declined to 29.2% after our interventions. Conclusion: The low rate of hospital discharge appointments within two weeks of discharge indicates that many patients are lacking crucial follow-up care. This project found that having residents enter appointments directly into AllScripts and performing home visits within 14 days of discharge made no difference in the overall rate of successful post-discharge follow-up visits. Weaknesses of this study include but are not limited to the gap of data between July 2019 and March 2020 and the small number of home visits that were performed. This project confirms the concern that unless new approaches to significant post-discharge follow-up barriers are considered, increasing the percentage of successful follow-up appointments will remain a difficult task

Differential Perceptions of What Constitutes a Medical Error Associated with Electronic Medical Records

Perceptions of errors associated with healthcare information technology (HIT) often depend on the context and position of the viewer. HIT vendors posit very different causes of errors than clinicians, implementation teams, or IT staff. Even within the same hospital, members of departments and services often implicate other departments. Organizations may attribute errors to external care partners that refer patients, such as nursing homes or outside clinics. Also, the various clinical roles within an organization (e.g., physicians, nurses, pharmacists) can conceptualize errors and their root causes differently. Overarching all these perceptual factors, the definitions, mechanisms, and incidence of HIT-related errors are remarkably conflictual. There is neither a universal standard for defining or counting these errors. This paper attempts to enumerate and clarify the issues related to differential perceptions of medical errors associated with HIT. It then suggests solutions