Approaches in configuring Clinical Decision Support (CDS) System
The development of an effective CDS system to facilitate the healthcare delivery of a chain of hospitals and outpatient clinics warrants the systematic incorporation of clinical guidelines, documentation templates, patient summaries, HPI and medication history recording tools, condition-specific orders and diagnostic support system across the electronic health record (EHR) (CMS, CLINICAL DECISION SUPPORT:More Than Just ‘Alerts’ Tipsheet, 2014). The association of these approaches in EHR is warranted in the context of incorporating the entire aspects of patient care to facilitate the patient outcomes across the clinical settings. The EHR across clinical settings requires the effective incorporation of the research findings in the context of enhancing the scope of improvement in medical-decision making by the healthcare professionals (Fiks, 2011). The mapping of the significant clinical information for physicians is required in EHR with the objective of saving the precious time of the clinician users in searching the required information. The customization of various decision support systems in EHR necessarily warranted in facilitating the configuration of an effective healthcare plan for the treated patients. The effective systematization of the flow of healthcare information in accordance with the healthcare priorities required in the context of mitigating challenges faced by the physicians in accessing the clinical information. The unnecessary interventions and hindrances in EHR that affect the flow of information retrieval, require an effective reduction for saving the time of clinicians in configuring the healthcare interventions. Alternatively, modification of information flow recommended for the clinicians in the context of surpassing errors in medical-decision making. For example, an alert on drug allergy or drug-drug interaction might require cancellation by the physicians in a scenario when there is minimal scope of a drug allergy in the treated patient or when patient might not exhibit any history of allergy or clinical complications in relation to the administered drugs. Furthermore, an indication related to the probable drug reaction with reference to patient’s history requires simplified presentation in EHR for its effective consideration by the healthcare-provider. The EHR interface should allow the systematic accomplishment of medication chart by the physician and provide the appropriate parameters for registering the dosage regimen and its mode of administration in the context of reducing the scope of medication errors during the pharmacotherapeutic interventions (Fiks, 2011). The EHR system must be configured in such a manner that the data entry system should not ask for the incorporation of unnecessary information which is out of context and not required in relation to the clinical scenario. The regular evaluation and monitoring of the EHR required for increasing the precision of the CDS system. The organization of regular feedback sessions with the associated clinicians and healthcare teams is necessarily required for exploring the scope of improvement in the CDS system. The regular maintenance of the CDS system required in the context of overcoming the short or long – term glitches in the context of improving the scope of systematized flow of clinical information for improving patient outcomes (Fiks, 2011).
Prioritization of the Efforts of CDS Team
Payment Rates Tied to Quality Measures
Members of the CDS team require undertaking proactive efforts in terms of linking the pattern of provider payments to the quality of healthcare services across the clinical setting (AHRQ, 2009). CDS teams require taking assistance from the renowned insurances like Aetna and Blue Cross in implementing the e-prescribing programs in electronic health records across the clinical facilities (HRSA, 2016). Implementation of pay-for-performance programs across the clinical settings is warranted in the context of encouraging providers in utilizing e-prescribing interface for elevating the quality of healthcare outcomes. The incorporation of pay-for-performance metrics, including the standard reminders and alerts assists the physicians in accurately configuring the prescription regimen in accordance with the clinical scenario for the affected patients (AHRQ, 2009). Medicare conventions have effectively linked the performance of the healthcare settings and hospitals with their revenue cycle management. Therefore, with the effective improvement of healthcare measures through e-prescription modules, the scope of enhancement of payment rates of hospitals increases considerably (Medicare.gov, 2016).
CDS Interventions that meet Meaningful Use Requirements
Meaningful use requirements for CDS warrant the incorporation of referential details, reminders and patient specific information that remain accessible to the concerned physicians and healthcare professionals at any specific point of care across the hospital environment (Ash, et al., 2012). Other significant CDS measures that advocate the utilization of meaningful use criteria attribute to clinical decision support strategies for dealing with the high risk clinical conditions. The incorporation of effective tools and techniques for the efficient evaluation of drug-allergy and drug-drug interaction scenarios restrains the physicians in terms of prescribing inappropriate medication regimen to the patient population (CMS, 2012).
Readmissions for Congestive Heart Failure and other Care Events for which Payers are increasingly not Reimbursing
Centers for Medicare and Medicaid services (CMS) prescribe various outcome measures for the hospital readmissions related to the clinical conditions including congestive heart failure, MI and pneumonia (CMS, 2015). These measures focus on the effective elevation of the quality of clinical interventions and reduction in the risk of morbidity of the affected patients. Therefore, appropriate patient safety indicators require deployment through the CDS system across the healthcare settings for evaluation and subsequent reporting of the adverse clinical manifestations due to which the patients affected with life threatening and debilitating conditions seek readmission in the hospitals as well as the clinical settings (CMS, 2015). Clinical complications leading to the readmission of patients across the clinical settings require reporting through the appropriate ICD-10-CM codes to the insurance companies in the context of claiming reimbursement of the administered clinical services that the insurance companies rarely consider for payment in routine scenarios. The incorporation of these ICD-10-CM codes and their effective mapping with the clinical morbidities and co-morbid states in CDS through EHR necessarily required for the precise reporting of adverse clinical conditions (requiring readmission) across the clinical settings.
Areas Identified as Institutional Priorities for Clinical Improvement
The institutional priorities and evidence-based approaches for maintaining the CDS system in the context of establishing clinical improvement advocate the development of systematic methods for the effective deployment of the CDS system across the healthcare settings. The CDS system across the institutions requires effective governance (by experienced and qualified healthcare professionals) for evaluating the precision of therapeutic interventions and diagnostic approaches for elevating the healthcare outcomes (Wright, et al., 2010). Regular governance of the CDS structure assists the healthcare teams in identifying the potential flaws in the decision support system for their earliest rectification. The effective linkage of the CDS system with the financial incentives requires prioritization in the context of encouraging the healthcare professionals in utilizing the CDS system for improving the quality of clinical interventions and associated healthcare goals (Wright, et al., 2010). Attributes including the awareness of CDS system’s workflow, regular up-gradation of the content, evaluation of the clinical outcomes of CDS system, maintenance of high quality and integrated data and effective dissemination of clinical information between the healthcare professionals require systematic prioritization by the healthcare settings in establishing a dynamic CDS system (Wright, et al., 2010).
References
AHRQ. (2009). Clinical Decision Support Systems: State of the Art. USA: AHRQ. Retrieved from https://healthit.ahrq.gov/sites/default/files/docs/page/09-0069-EF_1.pdf
Ash, J. S., McCormack, J. L., Sittig, D. F., Wright, A., McMullen, C., & Bates, D. W. (2012). Standard practices for computerized clinical decision support in community hospitals: a national survey. JAMIA, 19(6), 980-987.
CMS. (2012). Eligible Professional Use Core Measures. USA: CMS.
CMS. (2014). CLINICAL DECISION SUPPORT:More Than Just ‘Alerts’ Tipsheet. USA: CMS. Retrieved from https://www.cms.gov/regulations-and-guidance/legislation/EHRincentiveprograms/downloads/clinicaldecisionsupport_tipsheet-.pdf
CMS. (2015, 09 29). Outcome Measures. Retrieved from https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/hospitalqualityinits/outcomemeasures.html
Fiks, A. G. (2011). Designing Computerized Decision Support That Works for Clinicians and Families. Current Problems in Pediatric and Adolescent Health Care, 60-88.
HRSA. (2016). Is there help available for the financing of e-prescribing systems? Retrieved 09 05, 2016, from http://www.hrsa.gov/healthit/toolbox/HealthITAdoptiontoolbox/ElectronicPrescribing/financingsystem.html
Medicare.gov. (2016). Hospital Value-Based Purchasing. Retrieved 09 05, 2016, from https://www.medicare.gov/hospitalcompare/Data/hospital-vbp.html
Wright, A., Phansalkar, S., Bloomrosen, M., Jenders, R. A., Bobb, A. M., Halamka, J. D., . . . Bates, D. W. (2010). Best Practices in Clinical Decision Support. Applied Clinical Informatics, 331-345. doi:10.4338/ACI-2010-05-RA-0031
