Kidney transplant cases in US: study of determinants of variance in hospital charges and inpatient care.

We investigate the factors that influence the variance in hospital charges and inpatient care for kidney transplant cases in the US. Using the AHRQ's (Agency for Healthcare Research and Quality) HCUP's (Hospital Cost and Utilization Project) NIS (National Inpatient Sample) database, we find that variance in hospital charges and inpatient care is driven by patient demographics and hospital variables. We find that variance in hospital charges and inpatient care is determined by patient-specific factors including age, gender, race, and income, and hospital factors such as size, type, and location. Our results provide a deeper understanding of the non-clinical factors that impact hospital charges and inpatient care for kidney transplant patients.

The Impact of Early Brain-Dead Donor Detection in the Emergency Department on the Organ Donation Process in Iran.

We aimed to assess the impact of hospital characteristics on the outcomes of detected possible brain-dead donors, in our organ procurement network in Iran. Data was collected through twice-daily calls with 57 hospitals' intensive care units and emergency departments over 1 year. The donation team got involved when there was suspicion of brain death before the hospital officially declared it. The data was categorized by hospital size, presence of neurosurgery/trauma departments, ownership, and referral site. Out of 813 possible donors, 315 were declared brain dead, and 203 were eligible for donation. After conducting family interviews (consent rate: 62.2%), 102 eligible donors became actual donors (conversion rate: 50.2%). While hospital ownership and the presence of trauma/neurosurgery care did not affect donation, early referral from the emergency department had a positive effect. Therefore, we strongly recommend prioritizing possible donor identification in emergency rooms and involving the organ donation team as early as possible. The use of twice-daily calls for donor identification likely contributed to the consistency in donation rates across hospitals, as this approach involves the donation team earlier and mitigates the impact of hospital characteristics. Early detection of possible donors from the emergency department is crucial in improving donation rates.

Do Quality Measures or Hospital Characteristics Predict Readmission Penalties for Hip and Knee Arthroplasty?

BACKGROUND: Quality rating systems exist to grade the value of care provided by hospitals, but the extent to which these rating systems correlate with patient outcomes is unclear. The association of quality rating systems and hospital characteristics with excess readmission penalties for total hip arthroplasty (THA) and total knee arthroplasty (TKA) was studied. METHODS: The fiscal year 2022 Inpatient Prospective Payment System final rule was used to identify 2,286 hospitals subject to the Hospital Readmissions Reduction Program. Overall, 6 hospital quality rating systems and 5 hospital characteristics were obtained. These factors were analyzed to determine the effect on hospital penalties for THA and TKA excess readmissions. RESULTS: Hospitals that achieved a higher Medicare Overall Hospital Quality Star Rating demonstrated a significantly lower likelihood of receiving THA and TKA readmission penalties (Cramer's V = 0.236 and Rp = -0.233; P < .001 for both). Hospitals ranked among the US News & World Report's top 50 best hospitals for orthopaedics were significantly less likely to be penalized (V = 0.042; P = .043). The remaining 4 quality rating systems were not associated with readmission penalties. Penalization was more likely for hospitals with fewer THA and TKA discharges (Rp = -0.142; P < .001), medium-sized institutions (100 to 499 beds; V = 0.075; P = .002), teaching hospitals (V = 0.049; P = .019), and safety net hospitals (V = 0.043; P = .039). Penalization was less likely for West and Midwest hospitals (V = 0.112; P < .001). CONCLUSIONS: A higher Overall Hospital Quality Star Rating and recognition among the US News & World Report's top 50 orthopaedic hospitals were associated with a reduced likelihood of THA and TKA readmission penalties. The other 4 widely accepted quality rating systems did not correlate with readmission penalties. Teaching and safety net hospitals may be biased toward higher readmission rates.

Association of hospital and market characteristics with 30-day readmission rates from 2009 to 2015.

Objectives: The US government implemented the Hospital Readmission Reduction Program on 1 October 2012 to reduce readmission rates through financial penalties to hospitals with excessive readmissions. We conducted a pooled cross-sectional analysis of US hospitals from 2009 to 2015 to determine the association of the Hospital Readmission Reduction Program with 30-day readmissions. Methods: We utilized multivariable linear regression with year and state fixed effects. The model was adjusted for hospital and market characteristics lagged by 1 year. Interaction effects of hospital and market characteristics with the Hospital Readmission Reduction Program indicator variable was also included to assess whether associations of Hospital Readmission Reduction Program with 30-day readmissions differed by these characteristics. Results: In multivariable adjusted analysis, the main effect of the Hospital Readmission Reduction Program was a 3.80 percentage point (p < 0.001) decrease in readmission rates in 2013-2015 relative to 2009-2012. Hospitals with lower readmission rates overall included not-for-profit and government hospitals, medium and large hospitals, those in markets with a larger percentage of Hispanic residents, and population 65 years and older. Higher hospital readmission rates were observed among those with higher licensed practical nurse staffing ratio, larger Medicare and Medicaid share, and less competition. Statistically significant interaction effects between hospital/market characteristics and the Hospital Readmission Reduction Program on the outcome of 30-day readmission rates were present. Teaching hospitals, rural hospitals, and hospitals in markets with a higher percentage of residents who were Black experienced larger decreases in readmission rates. Hospitals with larger registered nurse staffing ratios and in markets with higher uninsured rate and percentage of residents with a high school education or greater experienced smaller decreases in readmission rates. Conclusion: Findings of the current study support the effectiveness of the Hospital Readmission Reduction Program but also point to the need to consider the ability of hospitals to respond to penalties and incentives based on their characteristics during policy development.

Hospital Variation in Mortality and Failure to Rescue after Surgery for High-Risk Neonatal Diagnoses.

INTRODUCTION: A large proportion of postoperative mortality after pediatric surgery occurs among neonates with specific high-risk diagnoses. The extent to which there is hospital-level mortality variation among patients with these diagnoses and whether this variation is associated with differences in failure to rescue (FTR) is unclear. METHODS: The Pediatric Health Information System® database (2012-2020) was used to identify patients who underwent surgery for eight high-risk neonatal diagnoses: gastroschisis; volvulus; necrotizing enterocolitis; intestinal atresia; meconium peritonitis; tracheoesophageal fistula; congenital diaphragmatic hernia; and perinatal intestinal perforation. Hospitals were stratified into tertiles of reliability-adjusted inpatient mortality rates (lower than average mortality - tertile 1 [T1]; higher than average mortality - tertile 3 [T3]). Multivariable hierarchical regression was used to evaluate the association between hospital-level, reliability-adjusted mortality and FTR. RESULTS: Overall, 20,838 infants were identified across 48 academic, pediatric hospitals. Adjusted hospital mortality rates ranged from 4.0% (95% CI, 0.0-8.2) to 16.3% (12.2-20.4). Median case volume (range, 80-1,238) and number of NICU beds (range, 24-126) were not significantly different across hospital tertiles. Compared to the hospitals with the lowest postoperative mortality (T1), the odds of FTR were significantly higher in hospitals with the highest (T3) postoperative mortality (odds ratio 1.97 [1.50-2.59]). CONCLUSIONS: Significant variation in neonatal hospital mortality for high-risk diagnoses does not appear to be explained by hospital structural characteristics. Rather, difference in FTR suggests quality improvement interventions targeting early recognition and management of postoperative complications could improve surgical quality and safety for high-risk neonatal care.

Measuring Patient Experience and Patient Satisfaction-How Are We Doing It and Why Does It Matter? A Comparison of European and U.S. American Approaches.

(1) Background: Patients' experiences and satisfaction with their treatment are becoming increasingly important in the context of quality assurance, but the measurement of these parameters is accompanied by several disadvantages such as poor cross-country comparability and methodological problems. The aim of this review is to describe and summarize the process of measuring, publishing, and utilizing patient experience and satisfaction data in countries with highly developed healthcare systems in Europe (Germany, Sweden, Finland, Norway, the United Kingdom) and the USA to identify possible approaches for improvement. (2) Methods: Articles published between 2000 and 2021 that address the topics described were identified. Furthermore, patient feedback in social media and the influence of sociodemographic and hospital characteristics on patient satisfaction and experience were evaluated. (3) Results: The literature reveals that all countries perform well in collecting patient satisfaction and experience data and making them publicly available. However, due to the use of various different questionnaires, comparability of the results is difficult, and consequences drawn from these data remain largely unclear. (4) Conclusions: Surveying patient experience and satisfaction with more unified as well as regularly updated questionnaires would be helpful to eliminate some of the described problems. Additionally, social media platforms must be considered as an increasingly important source to expand the range of patient feedback.

Effect of Hospital Characteristics on Performance of Pediatric Digit Replantation in the United States.

Introduction Utilize a national pediatric database to assess whether hospital characteristics such as location, teaching status, ownership, or size impact the performance of pediatric digit replantation following traumatic digit amputation in the United States. Materials and Methods The Kid's Inpatient Database (KID) was used to query pediatric traumatic digit amputations between 2000 and 2012. Ownership (private and public), teaching status (teaching and non-teaching), location (urban and rural), hospital type (general and children's), and size (large and small-medium) characteristics were evaluated. Replantations were then divided into those that required subsequent revision replantation or amputation. Fisher's exact tests and multivariable logistic regressions were performed with p <0.05 considered statistically significant. Results Overall, 1,015 pediatric patients were included for the digit replantation cohort. Hospitals that were privately owned, general, large, urban, or teaching had a significantly greater number of replantations than small-medium, rural, non-teaching, public, or children's hospitals. Privately owned (odds ratio [OR]: 1.80; 95% confidence interval [CI]: 1.06-3.06; p = 0.03) and urban (OR: 2.29; 95% CI: 1.41-3.73; p = 0.005) hospitals were significantly more likely to perform replantation. Urban (OR: 4.02; 95% CI: 1.90-8.47; p = 0.0003) and teaching (OR: 2.11; 95% CI: 1.17-3.83; p = 0.014) hospitals were significantly more likely to perform a revision procedure following primary replantation. Conclusion Private and urban hospitals were significantly more likely to perform replantation, but urban and teaching hospitals carried a greater number of revision procedures following replantation. Despite risk of requiring revision, the treatment of pediatric digit amputations in private, urban, and teaching centers provide the greatest likelihood for an attempt at replantation in the pediatric population. The study shows Level of Evidence III.

Variation in the Price of Head and Neck Surgical Oncology Procedures.

Health care costs can present a significant strain on patients with head and neck cancer. It remains unclear how much prices may vary among hospitals providing care and what factors lead to differences in prices of surgical procedures. A cross-sectional analysis of private payer-negotiated prices was performed for 10 commonly performed head and neck surgical oncology procedures. In total, 896 hospitals disclosed prices for at least 1 common head and neck surgical oncology procedure. Wide variation in negotiated surgical prices was identified. Across-center ratios ranged from 6.2 (partial glossectomy without primary closure) to 22.8 (excision of tongue lesion without closure). For-profit hospital ownership structure and geographic region outside of the northeast United States were associated with increased prices. For example, private payer-negotiated prices for direct laryngoscopy with biopsy were on average $2083 greater at for-profit hospitals when compared with nonprofit hospitals ($5215 vs $3132, P < .001). Further research comparing prices and outcomes is needed.

Factors Associated with Remote Patient Monitoring Services Provision by Hospitals and Health Care Systems in the United States.

Purpose: To assess the factors associated with offering remote patient monitoring (RPM) services. Methods: We integrated three datasets: (1) 2019-2020 Area Health Resource Files, (2) 2019 American Community Survey, and (3) 2019 American Hospitals Association annual survey using county Federal Information Processing Standards code to evaluate associations between hospital characteristics and county-level demographic factors with provision of (1) post-discharge, (2) chronic care, (3) other RPM services, and (4) any of these three RPM service categories. These outcomes were analyzed using multi-level, mixed-effects multivariate logistic regression modeling to account for county-level clustering of hospitals. Findings: Among 3,381 hospitals, 1,354 (40.0%) provided any RPM services. Being part of a clinically integrated network (CIN) and private, non-profit (vs. public) ownership were respectively associated with 104.5% (95% confidence interval [CI]: 69.4-146.8%; p < 0.001) and 30.4% (95% CI: 2.5-66.0%; p = 0.031) higher odds of providing any RPM services. Critical access hospital (CAH) designation, for-profit (vs. public) ownership, and location in the South (vs. Northeast) were associated with significantly lowering odds of providing any RPM services by 36.2% (95% CI: 14.2-52.6%; p = 0.003), 70.1% (95% CI: 56.0-79.6%; p < 0.001), and 34.0% (95% CI: 2.8-55.1%; p = 0.035), respectively. Similar trends were found with the various RPM service categories. Conclusions: The factors most associated with provision of any RPM services were hospital-level factors. Specifically, being part of a CIN and private, non-profit ownership had the highest positive associations with offering RPM services whereas location in the South and CAH designation had the strongest negative associations. Further studies are needed to understand the reasons behind these associations.

Demystifying hospital charges for hospital readmissions in 2017 in the United States for psychosis (DRG = 885).

Existing research on hospital charges is primarily focused on hospital admissions, but not on hospital readmissions. Our research fills this gap. We utilize the 2017 Hospital Readmissions database from the Agency for Healthcare Research and Quality (AHRQ) to empirically study factors that impact hospital charges for hospital readmissions. We focus on psychosis (DRG = 885) which has 609,360 records in 2017 in the AHRQ database. We employ regression analyses using patient demographics, inpatient care variables, and hospital characteristics to explain variance in hospital charges. Results show that inpatient care (diagnoses, procedures, length of stay), hospital ownership, and younger patients result in higher hospital charges.

Correspondence: is there an association between centre volume and survival or neurological outcomes among out-of-hospital cardiac arrest patients?

This commentary discusses the findings of a study by Tsuchida et al. on the effect of annual hospital admissions of out-of-hospital cardiac arrest patients on survival and neurological outcomes in OHCA patients in the context of existing literature on the topic, and the implications on future studies investigating the volume-outcome relationship in cardiac arrest.

Association between hospital characteristics and 30-day mortality of patients hospitalized for acute myocardial infarction in Sichuan, China.

OBJECTIVE: Because acute myocardial infarction (AMI) is a major cause of death, China faces the challenge of improving its quality of care. This study provides context-specific evidence of association between 30-day mortality and hospital characteristics in China to extend the understanding of hospitalized AMI patients. METHODS: We conducted a retrospective cohort study of 67,619 hospitalized AMI patients at 372 tertiary and secondary hospitals in Sichuan, China, between January 1, 2018 and December 31, 2020. Using a hierarchical logistic regression model to control risk factors, we explored relationships among 30-day mortality, hospital level, AMI volume, and percutaneous coronary intervention (PCI) timeliness. Locally weighted scatterplot smoothing was used to observe the trends of 30-day mortality with increased AMI volume and PCI timeliness. RESULTS: After risk factor adjustment, the 30-day mortality model demonstrated that a lower hospital level and smaller AMI volume were associated with higher 30-day mortality (medium-volume: OR = 1.511, 95% CI (1.195, 1.910); small-volume: OR = 1.636, 95% CI (1.277, 2.096); other tertiary: OR = 1.190, 95% CI (1.037, 1.365); secondary: OR = 1.524, 95% CI (1.289, 1.800)). Similarly, 30-day mortality was higher for patients at hospitals with a low PCI timeliness (low timeliness: OR = 1.318, 95% CI (1.079, 1.610)). Scatterplot smoothing showed hospital 30-day mortality first reduced quickly and gradually stabilized with increased AMI volume and PCI timeliness. CONCLUSION: Patients admitted to tertiary grade A hospitals, large-volume hospitals, and high- or medium-timeliness hospitals were more likely to survive at 30 days. Policymakers should focus on improving the outcomes at hospitals without these characteristics.

Does Geographic Location Affect the Quality of Care? The Difference in Readmission Rates Between the Border and Non-Border Hospitals in Texas.

Purpose: Previous literature has limited empirical evidence describing the association between border location and readmission rates among hospitals in the U.S.-Mexico border region. Thus, our study explores this novel connection in Texas border hospitals using a non-experimental longitudinal study design. Materials and Methods: Using longitudinal panel data (2013~2016) drawn from the American Hospital Association Annual Survey Database, Hospital Compare, and Area Health Resource File, a random-effects linear regression analysis was performed to quantify the impact of border location on the readmission rates of the same sample at multiple timed points. Results: We found a positive relationship between border location and 30-day hospital readmission rates for heart failure and pneumonia in Texas. Border hospitals in Texas had approximately a 4.17% higher heart failure readmission rate and a 3.46% higher pneumonia readmission rate than non-border hospitals. We also identified several hospital organizational and market factors associated (eg, registered nurse [RN]-to-patient ratio) with hospital readmission rates. Conclusion: The results suggest that improving RN staffing levels can be the most feasible action to lower the readmission rates among border Texas hospitals. Decreasing readmission rates by increasing RN staffing levels would also help them avoid reimbursement reduction under the Hospital Readmission Reduction Program (HRRP) and enhance overall health in Texas border communities. Further, to improve border health in Texas, decision-makers in state and local governments must consider incentivizing border hospitals to improve RN staffing levels and modulating the market factors affecting hospital readmission rates that are mostly beyond the control of hospitals.

Exploring Factors Associated With the Work Hours of Attending Physicians Working in Hospitals.

BACKGROUND: Long work hours for physicians not only harm the health of physicians, but also endanger patient safety. Compared with resident physicians, attending physicians-especially hospital-employed attending physicians-assume more responsibilities but has not gotten enough attention. The purpose of this study was to explore whether a hospital's geographic location and emergency care responsibility might influence the number of hours worked. METHODS: The respondents of 2365 attending physicians from 152 hospitals in the 2018 survey of Taiwan physician work hours were used as the data source. The total work hour per week and its components, the regular scheduled shift and three types of on-call shifts, were used as outcome variables. Hospital geographic location and emergency care responsibility were the independent variables. The multilevel random effect model was employed to examine the study objective after adjusting for clinical specialty, hospital teaching status, and ownership. RESULTS: The average number of total working hours was 69.09 hours per week; the regular scheduled shift was account for 75% of total work hours. The results showed the total work hours were only varied by the level of hospital's emergency care responsibility. However, the results also demonstrated the hours of duty shifts were varied by hospital's geographic location and emergency care responsibility. The results of the multilevel random effect model revealed that the hospital's emergency care responsibility was the factor consistently associated with attending physician's work hour, no matter the total work hours or its composition. CONCLUSION: In this study, we explored how a hospital's location and its level of emergency care responsibility were associated with physicians' work hours for each type of shift. Our findings offer an opportunity to review the rationality of physician workforce allocation, and financial incentives and administrative measures could be the next steps for balancing the work hours of attending physicians.

"Our Patients Are Different": Predictors of Seclusion and Restraint in 31 Psychiatric Hospitals.

Background: Research in recent years has demonstrated that the use of coercive measures such as seclusion and restraint differs very much between hospitals within a country. In 2015, a central register for all coercive measures in the German federal state of Baden-Wuerttemberg has been established for 32 hospitals treating involuntary patients. The objective of the present study was to identify factors that determine the differences between these hospitals. Methods: Data on coercive measures and diagnoses from the central register in 2015-2017 were linked with structural data of the 32 hospitals and their supply areas. Results: On average, coercive measures were applied in 6.7% of cases (SD = 2.8%; Min-Max = 0.35-12.0%). The proportion of affected cases was significantly correlated with the proportion of involuntary patients (r = 0.56), the proportion of cases with affective or neurotic, stress-related and somatoform disorders (r = -0.42), number of hospital beds (r = 0.44), a sheltered home associated with the hospital (r = 0.43) and number of addiction counseling centers per 100,000 inhabitants in the service area (r = -0.39). The final regression model only included the proportion of involuntary cases as a significant predictor (standardized beta = 0.55, adjusted R 2 = 0.27). Conclusions: The predominating part of the considerable variance observed between hospitals could not be explained by structural variables. The proportion of involuntary patients had a significant impact, but a considerable amount of unexplained variance due to different practices within psychiatric hospitals remains.

Patient demographics as determinants of where they go for hospitalization, what inpatient care they get, and what they are charged: A national study.

This study focuses on the impact of race, income, age, and gender on hospital charges in the US. The data include 28,133 discharge records for appendectomies from a stratified sample of 4,584 hospitals in the HCUP's (Hospital Cost and Utilization Project) NIS (National Inpatient Sample) database. Results show that race, income, and age were significant determinants of hospital charges. Gender was not significantly related to the variance in hospital charges. Additionally, hospital variables (ownership/control region, teaching status, size, and primary expected payer) had statistically significant effects on hospital charges. We conclude with implications for clinicians, hospital administrators, and policy makers.

Hospital Geographic Location and Unexpected Complications in term Newborns in Florida.

INTRODUCTION: Birth trauma rates in term of neonates is a quality measure used by the Joint Commission. In the United States birth trauma rates occurs at a rate of 37 per 1000 live births and are on the decline. However, this decline has been significantly lower among term neonates born in rural facilities. There is a critical lack of evidence toward the influence geographical risk factors has on birth trauma rates for neonatal patients. We sought to measure rural community and hospital characteristics associated with birth trauma. METHODS: A retrospective longitudinal study design was used to examine inpatient medical discharge data across 103 hospitals of neonates at birth from 2013 to 2018. Discharge data was linked to the American Hospital Association annual survey. We used a multi-level mixed effect model to investigate the relationship between individual and hospital-level attributes associated with increased risk of birth trauma among neonatal patients. RESULTS: We found that rural hospitals were 3.99 times (p < 0.001) more likely to experience higher birth trauma than urban hospitals. Medium sized hospitals were 2.11 times (p < 0.001) more likely to experience higher birth trauma. Hospitals who indicate having a safety culture were more likely (p < 0.05) to have high rates of birth trauma. DISCUSSION: Neonates born at rural hospitals, were more likely to experience a birth-related injury. Policy strategies focusing on improving health care quality in rural areas are critical to mitigating this increased risk of birth trauma. Further research is required to assess how physician characteristics may impact birth trauma rates.

Impact of Hospital Characteristics on Mandibular Distraction Osteogenesis Outcomes Among Patients With Pierre Robin Sequence Utilizing a National Inpatient Database.

OBJECTIVES: This study collected national inpatient data to investigate the impact of hospital specialty and size on patient outcomes following mandibular distraction osteogenesis (MDO). DESIGN: Kids' Inpatient Database was used to identify patients less than 12 months of age with Pierre Robin sequence (PRS) who underwent MDO in one of the following years: 2006, 2009, and 2012. SETTING: Inpatient database from the United States. PARTICIPANTS: Two hundred seventy-six patients with PRS underwent MDO with 134 (48.6%) identified as nonsyndromic and 142 (51.4%) as syndromic. INTERVENTIONS: Mandibular distraction osteogenesis. MAIN OUTCOME MEASURES: Length of hospital stay, adjunct airway and nutritional interventions and disposition. RESULTS: The average length of stay was 24 and 30 days for patients with nonsyndromic and syndromic PRS, respectively (P = .066). Patients with a syndromic as compared to nonsyndromic diagnosis had a higher incidence of gastrostomy tube placement (21.8 vs 12.7%, P = .045). Univariate analysis showed that a lower proportion of patients at children's hospitals as compared to non-children's hospitals necessitated 1 or more airway or nutrition-related intervention (19/148 [12.8%] vs 31/127 [24.4%]; P = .012) and had a lower incidence of a nonroutine discharge (transfer or patient death; 7.4% vs 40.0% nonroutine; P < .001). Multivariable analysis additionally revealed that patients at children's hospitals were less likely to discharge nonroutine (OR = 0.07, 95% CI: 0.02-0.32). CONCLUSIONS: Results from this national cohort demonstrated that at children-specific hospitals patients with PRS were less likely to require additional airway and nutritional procedures and more likely to discharge to home.

Hospital robotic use for colorectal cancer care.

The use of robotic surgery for colorectal cancer continues to increase. However, not all organizations offer patients the option of robotic intervention. This study seeks to understand organizational characteristics associated with the utilization of robotic surgery for colorectal cancer. We conducted a retrospective study of hospitals identified in the United States, State of Florida Inpatient Discharge Dataset, and linked data for those hospitals with the American Hospital Association Survey, Area Health Resource File and the Health Community Health Assessment Resource Tool Set. The study population included all robotic surgeries for colorectal cancer patients in 159 hospitals from 2013 to 2015. Logistic regressions identifying organizational, community, and combined community and organizational variables were utilized to determine associations. Results indicate that neither hospital competition nor disease burden in the community was associated with increased odds of robotic surgery use. However, per capita income (OR 1.07 95% CI 1.02, 1.12), average total margin (OR 1.01, 95% CI 1.001, 1.02) and large-sized hospitals compared to small hospitals (OR: 5.26, 95% CI 1.13, 24.44) were associated with increased odds of robotic use. This study found that market conditions within the U.S. State of Florida are not primary drivers of hospital use of robotic surgery. The ability for the population to pay for such services, and the hospital resources available to absorb the expense of purchasing the required equipment, appear to be more influential.

Hospital Characteristics Associated with Certified EHR Adoption among US Psychiatric Hospitals.

OBJECTIVE: The aim of this study was to explore the relationship between hospital characteristics and certified electronic health record (EHR) adoption in psychiatric hospitals in the US. METHODS: Data were drawn from the American Hospital Association Annual Survey Database and the Centers for Medicare and Medicaid Services Hospital Compare data sets in 2016. Binary logistic regression analysis and χ 2 tests were performed to examine the relationship between certified EHR adoption and hospital characteristics. RESULTS: Of 1,059 psychiatric hospitals in the US, 502 (47.4%) have adopted certified EHR technology. Large hospitals (OR 2.29, 95% CI 1.52-3.44; p<0.001), not-for-profit hospitals (OR 1.74, 95% CI 1.22-2.49; p=0.008), and hospitals participating in a network (OR 1.78, 95% CI 1.34-2.37; p<0.001) were more likely to adopt certified EHRs. Hospitals in the northeast were less likely to implement certified EHRs compared to other regions. However, there was no significant association found between EHR utilization and system affiliation, urban location, teaching status, or participation of health-maintenance organizations and preferred provider organizations. CONCLUSION: The study results suggested variations in EHR adoption according to hospital location, size, ownership, and network participation. This study fills a gap in previous work on certified EHR adoption that focused exclusively on general hospitals, but overlooked psychiatric hospitals. Future policies designed to influence the implementation of certified EHRs should take into consideration how hospital size, ownership, and network-affiliation status affect certified EHR adoption among psychiatric hospitals.