Rollei Df S 60 Se Software Update

Posted on

You might experience issues such as these when you try to print from your Mac or print from your iOS device:

  • You can't see your printer from your device, or you get a message that no printers were found.
  • You get a message that software for your device isn't available.
  • You have some other printing issue related to the software on your Mac or iOS device.

For help with an error light or other error condition on the printer itself, check the printer's documentation or contact its manufacturer.

If your printer is AirPrint-enabled

If your printer is AirPrint-enabled for printing from your Mac or iOS device, just make sure that it's connected to the same Wi-Fi network used by the Mac or iOS device.1

Create amazing videos with PowerDirector 365. Subscribe from $5.83/month.; PowerDVD 18 - Save 30% on the best media player for DVDs, Blu-ray discs & online content! Best deals up to 60% off for students & teachers. Rollei DF-S100 SE Film Scanner. PLUSTEK 2468106 Film Holder Kit for. Viewer and Convert 35mm Negative Film &Slide to Digital JPEG Save into SD Card, with Slide Mounts Feeder No Computer/Software Required. (SE) / 7300 / 7500i(Ai/SE) / 1x Film Strip and 1 x Mounted Slide Holder. Downloads Product Series Please Select Accessories AIS Autopilot BROADBAND 3G RADAR BROADBAND 4G RADAR Elite HDI / CHIRP Elite Ti2 Elite-Ti FishHunter GPS HALO Radar HDS (Gen1) HDS Carbon HDS Gen2 HDS Gen3 HDS LIVE HOOK HOOK X HOOK2 HOOK2 X LCX Series LMS Series Mark Mark & Elite NAC-1 Precision 9 compass SonarHub Sonichub StructureScan.

Rollei’s product range offers not only modern and durable video technology, but also practical, suitable photo accessories for professionals, ambitious amateur photographers, outdoor sports enthusiasts, pioneers, explorers and light artists. To download the latest software for your unit, go to our Software Updates page and scroll until you find the Series name of your software upgradeable Fish Finder or Accessory. Once you select the Series, select your model number. If you can't get your printer to work with your Mac, iPhone, iPad, or iPod touch, these steps might help. Firmware updates—such as for AirPort base stations—update the software on the printer or router, not the software on your Mac or iOS device. If the latest firmware from the manufacturer is several years old, the manufacturer might. SanDisk SecureAccess software is a fast, simple way to store and protect critical and sensitive files on any SanDisk USB flash drive. SwiftKey virtual keyboard app update boosts speed while.

Inch

If you still can't print, try any of these solutions:

  • Restart your Wi-Fi router. Then restart your printer.
  • Move your printer closer to your Wi-Fi router.
  • Update your printer and Wi-Fi router with the latest firmware from the manufacturer.2
  • Update the software for your Mac or iOS device.

If you're using a Mac and you still can't print, it might help to reset the printing system. Otherwise, contact the printer manufacturer for support.

If your printer isn't AirPrint-enabled

If you're printing from your Mac to a printer that isn't AirPrint-enabled:

  1. If your printer is connected to your Mac with a cable, disconnect the cable from your Mac.
  2. Turn off your printer.
  3. Get software updates for your Mac. Your Mac automatically downloads the latest software for most printers as part of these updates, so it's best not to install software from the printer manufacturer.
  4. Reconnect your printer to your Mac, if applicable.
  5. Turn on your printer and wait for it to finish starting up.
  6. Choose Apple () menu > System Preferences, then click Printers & Scanners.
  7. Select your printer in the list of devices.

If your printer doesn't appear in the list of devices in Printers & Scanners preferences, click at the bottom of the list, then choose the command to add a printer or scanner. The window that opens offers more ways to find and add a printer, such as by IP address:

All of the GameBoy Advance roms can be downloaded for free. Enjoy your favourite Gameboy Advance games. We have put together a collection of 2498 GBA roms, which you can download for free. Using GBA emulator (download here) run your favourite games on your PC, Mac, iPhone or Android device. You can sort rom games by genre or region. Gameboy Advance / GBA Game Information. Play and Download Gameboy Advance ROMs for free in high quality. We have a curated list of all the retro GBA games for you to play online or download to play within an emulator on your computer. Download hacked roms gba games. Tags free download Pokemon hack resolute ROM Download Pokemon resolute ROM Download hack roms DOWNLOAD POKEMONRESOLUTE GBA ROM FREE. Download Pokemon GBA Rom Hacks for free. All games are pre-patched and the latest versions are be updated regularly. Requests done in 24 hours! Hacks General Information Genre None Selected Action Action > Beat 'Em Up Action > Fighting Action > Platformer Action > Shooter Action Adventure Adventure Application Boardgame Card Game Dating Sim Game Creation Other Puzzle Racing Role Playing Role Playing > Action RPG Screen Saver Simulation Sports Strategy Strategy > Turn Based Unknown.

If you still can't print, and your printer is connected via Wi-Fi:

  • Restart your Wi-Fi router. Then restart your printer.
  • Move your printer closer to your Wi-Fi router.
  • Update your printer and Wi-Fi router with the latest firmware from the manufacturer.2

Reset the printing system

If the issue continues, reset the printing system on your Mac. This removes all printers and scanners—including their print jobs and settings—from Printers & Scanners preferences.

  1. Choose Apple menu > System Preferences, then click Printers & Scanners.
  2. While holding down the Control key on your keyboard, click anywhere in the list of devices.
  3. Choose “Reset printing system” from the menu that appears:

Remove printer drivers

If the issue continues on your Mac after resetting the printing system, take these final steps to remove any currently installed printer drivers. These steps don't apply to AirPrint printers.

  1. From the menu bar in the Finder, choose Go > Go to Folder. Type /Library/Printers/ and click Go.
  2. The Printers folder opens. Choose Edit > Select All, which selects all items in the Printers folder.
  3. Choose File > New Folder with Selection, which puts all of the selected items into a new folder named New Folder With Items. To save storage space, you can delete this folder.

If the issue continues, contact the printer manufacturer for support.

1. In corporate environments, DNS records can be configured to allow AirPrint-enabled printers to appear across other networks instead of just the network used by the device you're printing from. You can also use configuration profiles in iOS to set up AirPrint printers.

2. Firmware updates—such as for AirPort base stations—update the software on the printer or router, not the software on your Mac or iOS device. If the latest firmware from the manufacturer is several years old, the manufacturer might have stopped supporting or updating your device. If so, you might need a more up-to-date printer or router.

N Engl J Med. Author manuscript; available in PMC 2013 Jun 22.
Published in final edited form as:
doi: 10.1056/NEJMsb1205420
NIHMSID: NIHMS469790
The publisher's final edited version of this article is available at N Engl J Med
See other articles in PMC that cite the published article.

Electronic health records (EHRs) are essential to improving patient safety. Hospitals and health care providers are implementing EHRs rapidly in response to the American Recovery and Reinvestment Act of 2009.2- The number of certified EHR vendors in the United States has increased from 605,6 to more than 10007 since mid-2008. Recent evidence has highlighted substantial and often unexpected risks resulting from the use of EHRs and other forms of health information technology.8- These concerns are compounded by the extraordinary pace of EHR development and implementation. Thus, the unique safety risks posed by the use of EHRs should be considered alongside the potential benefits of these systems.

At a time when institutions are focused heavily on achieving “meaningful use” requirements, we propose that clearer guidance be provided so that these institutions can align activities related to patient safety with the activities required to support a safe EHR-enabled health care system. A set of EHR-specific safety goals, modeled after the Joint Commission's National Patient Safety Goals, may provide organizations with areas of focus for sustained improvements in organizational infrastructure, processes, and culture as they adapt to new technology.

EHR implementation is still highly heterogeneous across health care systems and providers, and this heterogeneity leads to equally variable implications for patient safety. For instance, the priorities for patient safety in an organization in the midst of an EHR rollout differ from those of an organization that has used a fully integrated EHR system for 5 or more years. To account for the variation in the stages of implementation and levels of complexity across clinical practice settings, we propose a three-phase framework for the development of EHR-specific patient-safety goals (e-PSGs). The first phase of the framework, aimed at all EHR users but especially at recent and future adopters, includes goals to mitigate risks that are unique and specific to technology (e.g., technology that is unsafe owing to unavailable or malfunctioning hardware or software). The second phase addresses issues created by the failure to use technology appropriately or by misuse of technology. The final phase focuses on the use of technology to monitor health care processes and outcomes and identify potential safety issues before they can harm patients. This framework can lay the foundation for the development of e-PSGs within the context of EHR-enabled health care.

Goals

Phase 1: Address Safety Concerns Unique to EHR Technology

Device failures and both natural and man-made disasters are inevitable. The potential consequences of an EHR failure become of increasing concern as large-scale EHR systems are deployed across multiple facilities within a health care system, often across a wide geographic area. These broadly distributed systems may be tightly coupled and lightning fast, but that also means that a malfunction can rapidly affect not only a single department or institution but possibly an entire community.17 Furthermore, because the operations of such systems are often decentralized and relatively opaque to end users,18 problems evade easy detection and solution. In a recent example, on April 21, 2010, one third of the hospitals in Rhode Island were forced to postpone elective surgeries and divert non–life-threatening emergencies19 when an erroneous automatic antivirus software update set off a chain of events that caused “uncontrolled [computer] restarts and loss of networking functionality.”20 A potential e-PSG, therefore, should be to reduce the effect of EHR downtime on clinical operations and patient safety. Table 1 lists some of the activities that organizations could undertake to achieve this goal.

Table 1

Framework for Potential EHR-Related National Patient Safety Goals.*

Potential GoalRationaleSuggestions to Achieve the Goal
Phase 1: Address safety concerns unique to EHR technology
Reduce the effect of EHR downtime on patient safetyA robust computing infrastructure should include a plan that accounts for times when the computer is unexpectedly unavailableMaintain backup paper forms for orders and clinical documentation in clinical areas
Use clearly marked, easily activated, password-protected, read-only backup systems that contain the most recent clinical results and orders
Ensure complete, encrypted, daily, off-site storage of all patient data
Use redundant hardware (e.g., database servers) for mission-critical applications
Maintain uninterrupted power supplies capable of maintaining computer operations until generators come online
Develop downtime (and reactivation) policies and procedures to put plans into operation and to train personnel in the use of these plans
Report EHR uptime rates to the organization's board of directors (or its equivalent) on a regular basis
Reduce miscommunication of data transmitted between different components of EHRsMiscommunication can be problematic when sending remotely generated, “asynchronous” orders through multiple components of an EHR systemMandate regression testing (i.e., testing to ensure that intended changes are correct and did not corrupt any other parts of the system) of all mission-critical applications after every modification
Reduce the number of interfaces between mission-critical systems (e.g., between CPOE and pharmacy-management systems) developed by different software vendors
Phase 2: Mitigate safety concerns arising from failure to use EHRs appropriately
Mandate CPOE for all orders of medications, laboratory tests, and radiologic testsCPOE with advanced CDS has been shown to reduce errors of omission and commissionCreate order sets for the most common condition-, task-, and service-specific clinical scenarios21,22
Make clinician log-in privileges conditional on training and testing in order entry
Develop measurements for the safe and effective use of CPOE23
Report CPOE rates to the organization's board of directors (or its equivalent) on a regular basis
Reduce alert fatigueAlerts with low specificity result in a high rate of clinician overrides24 and lead to “alert fatigue”; clinicians thus may inadvertently ignore important informationImplement drug-drug interaction, checking only for life-threatening combinations25
Focus CDS interventions on key organizational safety goals26
Ensure that timing, content, and delivery of CDS interventions are appropriate to recipients and workflows26
Monitor the number and override rate of all alerts27
Report alert override rates to the organization's board of directors (or its equivalent) on a regular basis
Enter all medications, allergies, diagnostic test results, and clinical problems as structured or coded data
Structured data are needed to realize the full potential of computer-generated CDS (e.g.,checks for drug allergies, automated notification of abnormal test results,28 and reminders about drug-condition interactions29)Use standard clinical vocabularies
Implement two-way, system–system interfaces with all ancillary information systems both within and outside the organization to facilitate the capture and use of coded data30
Develop order entry31 templates
Phase 3: Use EHRs to monitor and improve patient safety
Use EHR-based “triggers” to monitor, identify, and report potential safety issues and events16
Current incident-reporting systems capture a small proportion of events or only specific types of events32; safety trends cannot be measured reliably at present
Identify high-risk target conditions within specific clinical contexts (e.g., administration of a medication used as an antidote, as in the administration of naloxone in an acute care unit33)
Develop search criteria to identify these conditions (e.g., patients in need of particular tests, follow-up actions, or patients undergoing specific safety events)
Query the EHR regularly to detect events on the basis of search criteria
Assign staff to take action on identified events
*CDS denotes clinical-decision support, CPOE computer-based provider order entry, and EHR electronic health record.

Safety can also be compromised as a result of miscommunication between the components of an EHR system. For example, it is not uncommon fors workflow or thought process must be used judiciously. Many organizations turn on alerts with low specificity, which results in high rates of clinician over-ride. Frequent overrides are associated with “alert fatigue,” which can lead clinicians to inadvertently ignore important information. Thus, another potential e-PSG could be to reduce alert fatigue. Alerts with override rates above a certain threshold should be discontinued or modified to increase their specificity. Similarly, hard stops (i.e., when users cannot proceed with the desired action) must be used only for the most egregious errors. Having such a goal will stimulate a multidisciplinary approach to reducing alerts that involves engaging cognitive scientists, human-factors engineers, and informaticians (i.e., scientists trained to work on the sociotechnical issues of information and communications technologies,) to work on these complex issues with clinicians (Table 1).

Third, although there is increased safety associated with integrating free text, dictated reports, radiographic images, and other test results into EHRs (including improved legibility and rapid access), many institutions are not currently coding some of the critical data needed to maximize safety. The lack of structured or coded data prevents the system from being able to provide the user with meaningful feedback or interpretation (i.e., an alert regarding the use of lisinopril will not be generated if a patient's history of captopril-related angioedema has not been entered as coded allergen data). Therefore, to realize the full safety benefits of complex CDS tools (e.g., checks for drug allergies, automatic notification of abnormal test results, or reminders related to drug-condition interactions [e.g., a warning on the use of isotretinoin in patients who are pregnant]), another e-PSG could focus on ensuring that critical data on medications, allergies, diagnostic test results, and clinical problems are entered as structured or coded data in the EHR

Phase 3: Use Ehrs To Monitor And Improve Patient Safety

To achieve the goals of many national initiatives to improve patient safety and to facilitate the prevention of safety events, electronic data must be used to help detect, manage, and learn from potential safety events in near real-time. The stakeholders include the Agency for Healthcare Research and Quality (AHRQ), the Joint Commission, and the recently formed Partnership for Patients.50 In the current methods used to measure safety events, there is an overreliance on incident reports, which detect only a small proportion of events. In contrast, systems can be programmed to automatically detect easily overlooked and underreported errors of omission, such as patients who are overdue for medication monitoring, patients who lack appropriate surveillance after treatment, and patients who are not provided with follow-up care after receiving abnormal laboratory or radiologic tests results. EHR-based trigger approaches can also be used to detect errors of commission related to preventable adverse drug events, postoperative complications, and misidentification of patients. Organizations must leverage EHRs to facilitate rapid detection of common errors (including EHR-related errors), to monitor the occurrence of high-priority safety events, and to more reliably track trends over time. EHRs could also play a role in improving the existing infrastructure of reporting to patient-safety organizations by facilitating the generation of data files describing particular safety events (e.g., using the AHRQ common format version 1.2).55 Thus, an e-PSG could relate to the use of the EHR to monitor, identify, and report potential safety issues and events. This would make detection and reporting more efficient and help shift resources toward investigation and action.

Application of the Three-Phase e-PSG Framework

Lowe S 60 Inch Bathroom Vanities

Given that only 48% of all eligible hospitals and only 20% of eligible physicians have currently attested to achieving stage 1 of the CMS meaningful use criteria,56 the development and application of e-PSGs could partially address the Institute of Medicine's recent recommendation to create an EHR safety action and surveillance plan.8 The recommendations of such a plan should be tailored to the stage of EHR implementation. Recent adopters of EHRs could focus on the goals presented in phase 1 of our safety framework, making sure that the technology is safe to use, whereas organizations that have already achieved stage 1 meaningful-use criteria and have been using EHRs for several years could aim for goals from all three phases. Measurements related to e-PSGs would allow nationwide tracking and benchmarking of EHR-related safety performance. Policymakers and EHR vendors could collaborate on the development and certification of automated methods to measure and report new indicators annually from meaningful use certified EHRs in eligible hospitals. Examples of potential measures for e-PSGs might include EHR uptime rate (e.g., minutes the EHR was available to clinicians divided by number of minutes in a year), CPOE rate (e.g., number of orders electronically entered divided by the total number of orders during the year), and alert override rate (e.g., number of point-of-care alerts ignored divided by the total number of point-of-care alerts generated).

These goals will also need to be reviewed regularly and updated as needed in accordance with national priorities and research on EHR-related patient safety. In addition, many strategies not addressed in this article could be considered as recommendations or good clinical practices and progress in a stepwise fashion to future e-PSGs.

Summary

To create a coordinated, consistent, national strategy that will address the safety issues posed by EHRs, we propose that a concerted effort be made to improve health care safety in the context of technology use. This effort should address preventable risks that may hamper endeavors to create a safer EHR-enabled health care system. Further discussion and consensus among national agencies (e.g., the Office of the National Coordinator for Health Information Technology [ONC], the AHRQ, the Joint Commission, the Centers for Medicare and Medicaid Services) is clearly necessary for the adoption of future national patient-safety goals specific to EHR use. However, this approach must be given immediate priority considering the rapid pace of EHR adoption and the resulting changes in our nation's health care system. National EHR-related patient-safety goals are needed to address current problems with existing EHR implementations and failures to leverage current EHR capabilities. For instance, the ONC has recently taken several important steps in this direction with release of the revised 2014 EHR certification criteria (e.g., emphasis on user-centered design and application of quality management systems in the EHR design and development process). Such efforts should be expanded in the future. Goals must be technically feasible, financially prudent, and practically achievable within current constraints and be accompanied by specific guidance on achieving them. Input on these goals must be sought not only from EHR developers and clinical end users but also from cognitive scientists, human-factors engineers, graphic designers, and informaticians with expertise in patient safety in complex health care environments. Creating unique EHR-related national patient-safety goals will provide new momentum for patient-safety initiatives in an EHR-enabled health system.

Acknowledgments

Supported by a Strategic Health IT Advanced Research Projects (SHARP) Program contract from the ONC (10510592) (to Dr. Sittig); a career-development award from the National Institutes of Health (K23CA125585) (to Dr. Singh); the Veterans Affairs (VA) National Center for Patient Safety; the Agency for Health Care Research and Quality (R18HS017820); and the Houston VA Health Services Research and Development Center of Excellence (HFP90-020). These sources had no role in the preparation, review, or approval of this article.

We thank Michael Shabot, M.D., Eric Thomas, M.D., M.P.H., and Robert Murphy, M.D., for their comments on an earlier version of this article; and Annie Bradford, Ph.D., for assistance with the editing of an earlier version of the manuscript.

Footnotes

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or any of the funding agencies listed below.

References

1. Blumenthal D, Glaser JP. Information technology comes to medicine. N Engl J Med. 2007;356:2527–34. [PubMed] [Google Scholar]
2. CMS Medicare and Medicaid EHR incentive programs, and the Office of the National Coordinator for Health IT, Certified Health IT Products List. data.gov, 2012 ( https://explore.data.gov/d/eybk-7w2b)
3. Tagalicod R, Anthony R, Kahn J. Medicare & Medicaid EHR Incentive Programs. 2012http://healthit.hhs.gov/portal/server.pt/document/956320/ehr_incentiveprogramanalysis_1_10_12_pdf.
4. Blumenthal D. Stimulating the adoption of health information technology. N Engl J Med. 2009;360:1477–9. [PubMed] [Google Scholar]
5. CCHIT certified ambulatory EHR. Certification Commission for Healthcare Information Technology. 20072007http://web.archive.org/web/20090123165327/http://cchit.org/choose/http://cchit.org/choose/ambulatory/2007/index.asp.
6. CCHIT certified inpatient EHR. Certification Commission for Healthcare Information Technology, 2007. 2007http://web.archive.org/web/20090221100419/http://cchit.org/choose/inpatient/2007/index.asp.
7. Certified health IT product list. Office of the National Coordinator for Health Information Technology. http://oncchpl.force.com/ehrcert.
8. Institute of Medicine. Health IT and patient safety: building safer systems for better care. Washington, DC: National Academies Press; 2012. [Google Scholar]
9. Myers RB, Jones SL, Sittig DF. Review of reported clinical information system adverse events in US Food and Drug Administration databases. Appl Clin Inform. 2011;2:63–74.[PMC free article] [PubMed] [Google Scholar]
10. Harrington L, Kennerly D, Johnson C. Safety issues related to the electronic medical record (EMR): synthesis of the literature from the last decade, 2000–2009. J Healthc Manag. 2011;56:31–44. [PubMed] [Google Scholar]
11. Magrabi F, Ong MS, Runciman W, Coiera E. Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc. 2012;19:45–53.[PMC free article] [PubMed] [Google Scholar]
12. Warm D, Edwards P. Classifying health information technology patient safety related incidents — an approach used in Wales. Appl Clin Inform. 2012;3:248–57.[PMC free article] [PubMed] [Google Scholar]
13. Radecki RP, Sittig DF. Application of electronic health records to the Joint Commission's 2011 National Patient Safety Goals. JAMA. 2011;306:92–3. [PubMed] [Google Scholar]
14. Kilbridge P. Computer crash — lessons from a system failure. N Engl J Med. 2003;348:881–2. [PubMed] [Google Scholar]
15. Sittig DF, Singh H. Defining health information technology-related errors: new developments since To Err Is Human. Arch Intern Med. 2011;171:1281–4.[PMC free article] [PubMed] [Google Scholar]
16. Jha AK, Classen DC. Getting moving on patient safety — harnessing electronic data for safer care. N Engl J Med. 2011 [PubMed] [Google Scholar]
17. Perrow C. Normal accidents: living with high-risk technologies. Princeton, NJ: Princeton University Press; 1999. [Google Scholar]
18. The Menlo report: ethical principles guiding information and communication technology research. 2011 Sep 15;http://www.cyber.st.dhs.gov/wp-content/uploads/2011/12/MenloPrinciplesCORE-20110915-r560.pdf.
19. National Public radio. Anti-virus program update wreaks havoc with PCs. 2010 Apr 21;http://www.npr.org/templates/story/story.php?storyId=126168997&sc=17&f=1001.
20. Patel N. Botched McAfee update shutting down corporate XP machines worldwide. Engadget.com. 2010 Apr 21;www.engadget.com/2010/04/21/mcafee-update–shutting-down-xp-machines/
21. Sittig DF, Ash JS, Jiang Z, Osheroff JA, Shabot MM. Lessons from “Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2006;118:797–801. [PubMed] [Google Scholar]
22. Wright A, Feblowitz JC, Pang JE, et al. Use of order sets in inpatient computerized provider order entry systems: a comparative analysis of usage patterns at seven sites. Int J Med Inform Assoc. 2012;81:733–45.[PMC free article] [PubMed] [Google Scholar]
23. Sittig DF, Campbell E, Guappone K, Dykstra R, Ash JS. Recommendations for monitoring and evaluation of in-patient Computer-based Provider Order Entry systems: results of a Delphi survey. AMIA Annu Symp Proc. 2007:671–5.[PMC free article] [PubMed] [Google Scholar]
24. Lin CP, Payne TH, Nichol WP, Hoey PJ, Anderson CL, Gen-nari JH. Evaluating clinical decision support systems: monitoring CPOE order check override rates in the Department of Veterans Affairs' computerized patient record system. J Am Med Inform Assoc. 2008;15:620–6.[PMC free article] [PubMed] [Google Scholar]
25. Phansalkar S, Desai AA, Bell D, et al. High-priority drug-drug interactions for use in electronic health records. J Am Med Inform Assoc. 2012 Apr 26; Epub ahead of print. [PMC free article] [PubMed] [Google Scholar]
26. Sittig DF, Teich JM, Osheroff JA, Singh H. Improving clinical quality indicators through electronic health records: it takes more than just a reminder. Pediatrics. 2009;124:375–7.[PMC free article] [PubMed] [Google Scholar]
27. Osheroff JA, Teich JM, Levick D, et al. Improving outcomes with clinical decision support: an implementer's guide. 2nd. Chicago: Healthcare Information and Management Systems Society; 2012. [Google Scholar]
28. Kuperman GJ, Teich JM, Tanasijevic MJ, et al. Improving response to critical laboratory results with automation: results of a randomized controlled trial. J Am Med Inform Assoc. 1999;6:512–22.[PMC free article] [PubMed] [Google Scholar]
Update
29. Gandhi TK, Zuccotti G, Lee TH. Incomplete care — on the trail of flaws in the system. N Engl J Med. 2011;365:486–8. [PubMed] [Google Scholar]
30. American Society of Health System Pharmacists. ASHP guidelines on pharmacy planning for implementation of computerized provider-order entry systems in hospitals and health systems. Am J Health Syst Pharmacol. 2011;68(6):e9–e31. [PubMed] [Google Scholar]
31. Haynes K, Linkin DR, Fishman NO, et al. Effectiveness of an information technology intervention to improve prophylactic antibacterial use in the postoperative period. J Am Med Inform Assoc. 2011;18:164–8.[PMC free article] [PubMed] [Google Scholar]
32. Shojania KG. The elephant of patient safety: what you see depends on how you look. Jt Comm J Qual Patient Saf. 2010;36:399–401. [PubMed] [Google Scholar]
33. Classen DC, Lloyd RC, Provost L, Griffin FA, Resar R. Development and evaluation of the Institute for Healthcare Improvement Global Trigger Tool. J Patient Saf. 2008;4:169–77.[Google Scholar]
34. Hamblin JF, Bwitit PT, Moriarty HT. Pathology results in the electronic health record. Electronic Journal of Health Informatics. 2010;5(2) 2010;5(2)e15. http://www.ejhi.net/ojs/index.php/ejhi/article/view/131. [Google Scholar]
35. Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Health Care. 2010;19(3):i68–i74.[PMC free article] [PubMed] [Google Scholar]
36. Singh H, Wilson L, Petersen LA, et al. Improving follow-up of abnormal cancer screens using electronic health records: trust but verify test result communication. BMC Med Inform Decis Mak. 2009;9:49.[PMC free article] [PubMed] [Google Scholar]
37. Singh H, Mani S, Espadas D, Petersen N, Franklin V, Petersen LA. Prescription errors and outcomes related to inconsistent information transmitted through computerized order entry: a prospective study. Arch Intern Med. 2009;169:982–9.[PMC free article] [PubMed] [Google Scholar]
38. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA. 2005;293:1197–203. [PubMed] [Google Scholar]

Rollei Df S 60 Se Software Update Issues

39. Wetterneck TB, Walker JM, Blosky MA, et al. Factors contributing to an increase in duplicate medication order errors after CPOE implementation. J Am Med Inform Assoc. 2011;18:774–82.[PMC free article] [PubMed] [Google Scholar]
40. McCoy AB, Waitman LR, Lewis JB, et al. A framework for evaluating the appropriateness of clinical decision support alerts and responses. J Am Med Inform Assoc. 2012;19:346–52.[PMC free article] [PubMed] [Google Scholar]

S60

41. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363:501–4. [PubMed] [Google Scholar]
42. Paterno MD, Maviglia SM, Gorman PN, et al. Tiering drug-drug interaction alerts by severity increases compliance rates. J Am Med Inform Assoc. 2009;16:40–6.[PMC free article] [PubMed] [Google Scholar]
43. Sittig DF, Singh H. Rights and responsibilities of users of electronic health records. CMAJ. 2012;184:1479–83.[PMC free article] [PubMed] [Google Scholar]
44. Gardner RM, Overhage JM, Steen EB, et al. Core content for the subspecialty of clinical informatics. J Am Med Inform Assoc. 2009;16:153–7.[PMC free article] [PubMed] [Google Scholar]

S-60 Helicopter

45. Kulikowski CA, Shortliffe EH, Currie LM, et al. AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline. J Am Med Inform Assoc. 2012 Jun 21; Epub ahead of print. [PMC free article] [PubMed] [Google Scholar]
46. Powsner SM, Wyatt JC, Wright P. Opportunities for and challenges of computerisation. Lancet. 1998;352:1617–22. [PubMed] [Google Scholar]
47. Wright A, Sittig DF, Ash JS, et al. Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems. J Am Med Inform Assoc. 2011;18:232–42.[PMC free article] [PubMed] [Google Scholar]
48. Kuperman GJ, Gandhi TK, Bates DW. Effective drug-allergy checking: methodological and operational issues. J Biomed Inform. 2003;36:70–9. [PubMed] [Google Scholar]
49. Wright A, Goldberg H, Hongsermeier T, Middleton B. A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007;14:489–96.[PMC free article] [PubMed] [Google Scholar]
50. HealthCare.gov. Partnership for patients: better care, lower costs. http://www.healthcare.gov/compare/partnership-for-patients.

Rollei Df S 60 Se Software Update Download

51. Singh H, Thomas EJ, Mani S, et al. Timely follow-up of abnormal diagnostic imaging test results in an outpatient setting: are electronic medical records achieving their potential? Arch Intern Med. 2009;169:1578–86.[PMC free article] [PubMed] [Google Scholar]
52. Nwulu U, Nirantharakumar K, Odesanya R, McDowell SE, Coleman JJ. Improvement in the detection of adverse drug events by the use of electronic health and prescription records: an evaluation of two trigger tools. Eur J Clin Pharmacol. 2012 Jun 17; Epub ahead of print. [PubMed] [Google Scholar]
53. Griffin FA, Classen DC. Detection of adverse events in surgical patients using the Trigger Tool approach. Qual Saf Health Care. 2008;17:253–8. [PubMed] [Google Scholar]
54. Adelman JS, Kalkut GE, Schechter CB, et al. Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. J Am Med Inform Assoc. 2012 Jun 29; Epub ahead of print. [PMC free article] [PubMed] [Google Scholar]
55. The Patient Safety Organization Privacy Protection Center (PSOPPC) home page ( https://www.psoppc.org/web/patientsafety.
56. More than 100,000 health care providers paid for using electronic health records: CMS and ONC surpass 2012 goals for EHR adoption and use Press release of the. Centers for Medicare & Medicaid Services; Jun 19, 2012. http://tinyurl.com/CMS-EHR-Users. [Google Scholar]
57. Singh H, Classen DC, Sittig DF. Creating an oversight infrastructure for electronic health record-related patient safety hazards. J Patient Saf. 2011;7:169–74.[PMC free article] [PubMed] [Google Scholar]
58. Department of Health and Human Services, Office of the Secretary. 45 CFR Part 170, RIN 0991–AB82 — Health information technology: standards, implementation specifications, and certification criteria for electronic health record technology, 2014 edition; revisions to the Permanent Certification Program for Health Information Technology. Fed Regist. 2012;77(171):54163–260. [PubMed] [Google Scholar]