Effect of electronic records on mortality among patients in hospital and primary healthcare settings: a systematic review and meta-analyses

Background

Electronic medical records or electronic health records, collectively called electronic records, have significantly transformed the healthcare system and service provision in our world. Despite a number of primary studies on the subject, reports are inconsistent and contradictory about the effects of electronic records on mortality. Therefore, this review examined the effect of electronic records on mortality.

Methods

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guideline. Six databases: PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, and Google Scholar, were searched from February 20 to October 25, 2023. Studies that assessed the effect of electronic records on mortality and were published between 1998 and 2022 were included. Joanna Briggs Institute quality appraisal tool was used to assess the methodological quality of the studies. Narrative synthesis was performed to identify patterns across studies. Meta-analysis was conducted using fixed effect and random-effects models to estimate the pooled effect of electronic records on mortality. Funnel plot and Egger's regression test were used to assess for publication bias.

Results

Fifty-four papers were found eligible for the systematic review, of which 42 were included in the meta-analyses. Of the 32 studies that assessed the effect of electronic health record on mortality, eight (25.00%) reported a statistically significant reduction in mortality, 22 (68.75%) did not show a statistically significant difference, and two (6.25%) studies reported an increased risk of mortality. Similarly, among the 22 studies that determined the effect of electronic medical record on mortality, 12 (54.55%) reported a statistically significant reduction in mortality, and ten (45.45%) studies didn't show a statistically significant difference. The fixed effect and random effects on mortality were OR = 0.95 (95% CI: 0.93-0.97) and OR = 0.94 (95% CI: 0.89-0.99), respectively. The associated I-squared was 61.5%. Statistical tests indicated that there was no significant publication bias among the studies included in the meta-analysis.

Conclusion

Despite some heterogeneity among the studies, the review indicated that the implementation of electronic records in inpatient, specialized and intensive care units, and primary healthcare facilities seems to result in a statistically significant reduction in mortality. Maturity level and specific features may have played important roles.

Systematic Review Registration

PROSPERO (CRD42023437257).

Effects of health information technology on patient outcomes: a systematic review

OBJECTIVE

To systematically review studies assessing the effects of health information technology (health IT) on patient safety outcomes.

MATERIALS AND METHODS

The authors employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement methods. MEDLINE, Cumulative Index to Nursing Allied Health (CINAHL), EMBASE, and Cochrane Library databases, from 2001 to June 2012, were searched. Descriptive and comparative studies were included that involved use of health IT in a clinical setting and measured effects on patient safety outcomes.

RESULTS

Data on setting, subjects, information technology implemented, and type of patient safety outcomes were all abstracted. The quality of the studies was evaluated by 2 independent reviewers (scored from 0 to 10). A total of 69 studies met inclusion criteria. Quality scores ranged from 1 to 9. There were 25 (36%) studies that found benefit of health IT on direct patient safety outcomes for the primary outcome measured, 43 (62%) studies that either had non-significant or mixed findings, and 1 (1%) study for which health IT had a detrimental effect. Neither the quality of the studies nor the rate of randomized control trials performed changed over time. Most studies that demonstrated a positive benefit of health IT on direct patient safety outcomes were inpatient, single-center, and either cohort or observational trials studying clinical decision support or computerized provider order entry.

DISCUSSION AND CONCLUSION

Many areas of health IT application remain understudied and the majority of studies have non-significant or mixed findings. Our study suggests that larger, higher quality studies need to be conducted, particularly in the long-term care and ambulatory care settings.

Impact of the Electronic Medical Record on Mortality, Length of Stay, and Cost in the Hospital and ICU: A Systematic Review and Metaanalysis

OBJECTIVE

To evaluate effects of health information technology in the inpatient and ICU on mortality, length of stay, and cost. Methodical evaluation of the impact of health information technology on outcomes is essential for institutions to make informed decisions regarding implementation.

DATA SOURCES

EMBASE, Scopus, Medline, the Cochrane Review database, and Web of Science were searched from database inception through July 2013. Manual review of references of identified articles was also completed.

STUDY SELECTION

Selection criteria included a health information technology intervention such as computerized physician order entry, clinical decision support systems, and surveillance systems, an inpatient setting, and endpoints of mortality, length of stay, or cost. Studies were screened by three reviewers. Of the 2,803 studies screened, 45 met selection criteria (1.6%).

DATA EXTRACTION

Data were abstracted on the year, design, intervention type, system used, comparator, sample sizes, and effect on outcomes. Studies were abstracted independently by three reviewers.

DATA SYNTHESIS

There was a significant effect of surveillance systems on in-hospital mortality (odds ratio, 0.85; 95% CI, 0.76-0.94; I=59%). All other quantitative analyses of health information technology interventions effect on mortality and length of stay were not statistically significant. Cost was unable to be quantitatively evaluated. Qualitative synthesis of studies of each outcome demonstrated significant study heterogeneity and small clinical effects.

CONCLUSIONS

Electronic interventions were not shown to have a substantial effect on mortality, length of stay, or cost. This may be due to the small number of studies that were able to be aggregately analyzed due to the heterogeneity of study populations, interventions, and endpoints. Better evidence is needed to identify the most meaningful ways to implement and use health information technology and before a statement of the effect of these systems on patient outcomes can be made.

Measuring value for money: a scoping review on economic evaluation of health information systems

Objective

To explore how key components of economic evaluations have been included in evaluations of health information systems (HIS), to determine the state of knowledge on value for money for HIS, and provide guidance for future evaluations.

Materials and methods

We searched databases, previously collected papers, and references for relevant papers published from January 2000 to June 2012. For selection, papers had to: be a primary study; involve a computerized system for health information processing, decision support, or management reporting; and include an economic evaluation. Data on study design and economic evaluation methods were extracted and analyzed.

Results

Forty-two papers were selected and 33 were deemed high quality (scores ≥8/10) for further analysis. These included 12 economic analyses, five input cost analyses, and 16 cost-related outcome analyses. For HIS types, there were seven primary care electronic medical records, six computerized provider order entry systems, five medication management systems, five immunization information systems, four institutional information systems, three disease management systems, two clinical documentation systems, and one health information exchange network. In terms of value for money, 23 papers reported positive findings, eight were inconclusive, and two were negative.

Conclusions

We found a wide range of economic evaluation papers that were based on different assumptions, methods, and metrics. There is some evidence of value for money in selected healthcare organizations and HIS types. However, caution is needed when generalizing these findings. Better reporting of economic evaluation studies is needed to compare findings and build on the existing evidence base we identified.

The costs of adverse drug events in community hospitals

BACKGROUND

Adverse drug events (ADEs) occur often in hospitals, causing high morbidity and a longer length of stay (LOS), and are costly. However, most studies on the impact of ADEs have been conducted in tertiary referral centers, which are systematically different than community hospitals, where the bulk of care is delivered, and most available data about ADE costs in any setting are dated. Costs in community settings are generally lower than in academic hospitals, and the costs of ADEs might be as well. To assess the additional costs and LOS associated with patients with ADEs, a multicenter retrospective cohort study was conducted in six community hospitals with 100 to 300 beds in Massachusetts during a 20-month observation period (January 2005-August 2006).

METHODS

A random sample of 2,100 patients (350 patients per study site) was drawn from a pool of 109,641 patients treated within the 20-month observation period. Unadjusted and adjusted cost of ADEs as well as LOS were calculated.

RESULTS

ADEs were associated with an increased adjusted cost of $3,420 and an adjusted increase in length of stay (LOS) of 3.15 days. For preventable ADEs, the respective figures were +$3,511 and +3.37 days. The severity of the ADE was also associated with higher costs--the costs were +$2,852 for significant ADEs (LOS +2.77 days), +$3,650 for serious ADEs (LOS +3.47 days), and +$8,116 for life-threatening ADEs (LOS +5.54 days, all p < .001).

CONCLUSIONS

ADEs in community hospitals cost more than $3,000 dollars on average and an average increase of LOS of 3.1 days--increments that were similar to previous estimates from academic institutions. The LOS increase was actually greater. A number of approaches, including computerized provider order entry and bar coding, have the potential to improve medication safety.

The economics of health information technology in medication management: a systematic review of economic evaluations

OBJECTIVE

To conduct a systematic review and synthesis of the evidence surrounding the cost-effectiveness of health information technology (HIT) in the medication process.

MATERIALS AND METHODS

Peer-reviewed electronic databases and gray literature were searched to identify studies on HIT used to assist in the medication management process. Articles including an economic component were reviewed for further screening. For this review, full cost-effectiveness analyses, cost-utility analyses and cost-benefit analyses, as well as cost analyses, were eligible for inclusion and synthesis.

RESULTS

The 31 studies included were heterogeneous with respect to the HIT evaluated, setting, and economic methods used. Thus the data could not be synthesized, and a narrative review was conducted. Most studies evaluated computer decision support systems in hospital settings in the USA, and only five of the studied performed full economic evaluations.

DISCUSSION

Most studies merely provided cost data; however, useful economic data involves far more input. A full economic evaluation includes a full enumeration of the costs, synthesized with the outcomes of the intervention.

CONCLUSION

The quality of the economic literature in this area is poor. A few studies found that HIT may offer cost advantages despite their increased acquisition costs. However, given the uncertainty that surrounds the costs and outcomes data, and limited study designs, it is difficult to reach any definitive conclusion as to whether the additional costs and benefits represent value for money. Sophisticated concurrent prospective economic evaluations need to be conducted to address whether HIT interventions in the medication management process are cost-effective.