Management of Healthcare - Essay Example

MANAGEMENT OF HEALTHCARE Name Institution Introduction To ensure quality and safe healthcare across the world, quality medical records remain the ultimate pivot (Brooks, 2013). Poor documentation and hence ineffective communication has occasionally been cited as a major contributing factor in the prevalence of adverse medical related events world over. This is the reason as to why the Department of Health - State for Western Australia (2012) observes that Clinical documentation remains a vital component in the quest by health practitioners to ensure safety and quality of patient care in addition to contributing towards medical research and delivery of healthcare that is based on evidence. The production of accurate clinical documentation entails the consistent capture of transparent information on patient care- this forms the core in the work of any competent clinician (Brooks, 2013). Gay et al. (2013) opines that to ensure complete documentation, care plans and discharge summaries should be keenly filled and kept properly for ease of retrieval when making references. For clinically relevant information to be captured, the following aspects need to be included: outpatient department notes, progress notes, anesthetic records, discharge planning, diagnosis, examination and patient’s medical history. One of the upcoming and effective ways of managing the health service, according to Brooks (2013), is through the Activity Based Funding (ABF).This method has been proved to provide the ultimate solution in ensuring efficiency in the flow of health resources based on the degree of patient needs. ABF relies on timely and accurate patient information to guarantee quality and safe healthcare. The governments, as well as clinicians, are able to make deliberate but informed decisions on how and where to deliver healthcare (Gay et al., 2013). Relevance, Sequence of the Coding Process According to the Department of Health- State for Western Australia (2012) coding in a clinical process entails the review and abstraction of information from medical records based on information that has already been documented. It is this clinical information, which is later translated into a code. Information coded includes but not limited to: therapeutic and diagnostic procedures performed during a clinical operation; principal as well as other primary diagnosis; co-morbidities that are relevant to the admission in addition to possible complications (Brooks, 2013). Basically, accurate documentation is key in ensuring the success of clinical coding-the clinical coder is able to translate information into a detailed yet clear and simple series of numerical or alphanumerical code in an attempt to reflect a comprehensive clinical picture. Majorly, to ensure success in information coding, the clinical coders use International Statistical Classification of Diseases and Related Health Problems which includes the classification of diseases based on the World Health Organization publication (ICD-10) coupled with current and respective medical classifications. Coding entails the professional documentation, by a qualified physician, of the particular aspects of a disease for the purposes of classification (Himagine Solutions, 2015). The coding process involves a number of stages. To start with, once a patient is allowed to leave the hospital (discharged) a clinical coder takes the initiative of translating the patient’s information into codes that serve to describe the diagnosis of the patient as well as the care accorded. Usually, this is realized in a standard format using two main classification systems – OPCS 4 meant for interventions and ICD-10 that is preferred for purposes of diagnosis. Secondly, the clinical coder goes ahead to record the diagnoses) and the accompanying intervention codes onto the localized) hospital system – PAS (Patient’s Administration System). Fundamentally, PAS is the hospital computer system that records patient information as such is bound to change from one hospital to another. Particulars of the patient like date of admission or discharge and age are clearly captured. An extract is then obtained from PAS and the providers submit it in a standardized format referred to as commissioning datasets (CDS) to SUS (Secondary Uses Service) database. The CDS monitors the sequence of activities in a given hospital and supports transactions (Payments by Results) through the National Datasets Service. In this case, SUS, is essentially the largest activity and nationalized database (Department of Health, England (2013).Moreover, with thousands of codes developed with the sole aim of managing diagnoses and interventions, it would be understandable to imagine of the complexity of making payments at this level. In view of this difficult scenario, a simple methodology has already been crafted through which diagnoses and corresponding interventions are collated into a small number of groupings that facilitate the setting of workable and sensible tariffs (Caston and Layman, 2006). As Himagine Solutions (2015) observes coding plays a very important role especially in matters of billing clients. In fact, so critical is the coding process that a good number of hospitals would eventually lose large sums of money simply out of the inability to capture complete and accurate data for their patients. For instance, the failure to code additional diagnosis accorded to particular patient results in a much lower DRG and consequently loss of revenue due to the healthcare provider. The work of clinical coders can never be underestimated and this calls for support from healthcare executives however much they may fail to grasp the significance of the coding process. DRG and MDC DRGs have been used commonly for inpatient classification systems (Himagine Solutions, 2015). The system was first developed in USA specifically Yale University where it was meant to aid in identification of variations in quality of healthcare and performance (VolEschen, 2012). The DRGs provide an effective and efficient way in relating the number as well as the type of delicate inpatients served in a given hospital to the corresponding resources that would be required to comfortably attend to these patients. DRGs aim at grouping patients into categories that are not only homogenous with respect to resource utilization but also clinically meaningful. Through the DRG system, all the sensitive diagnoses and accompanying procedures are carefully coded based on the episodes of the individual patients admitted. It is from the combination of codes that the grouper software is used to assign each episode to a DRG. In clinical medicine, the DRG has a number of uses: retrospective analysis of data for the purposes of research; identification of treatment trends across different states, facilitates cost-recovery initiatives in health systems, ensures continuous improvement in the quality of services offered; provides a means of comparison for different hospitals handling patients with similar conditions and also assists in delineation of roles. In making the DRG assignments, reference is made to the ICD-10 Codes that form part of clinical documentation – the clinical coder enters the care episodes into the hospital’s computerized systems from where the software, DRG grouper, considers the codes entered in addition to other related patient information with the aim of assigning the DRGs to the definite inpatient episode. Normally, a version 6.0(AR-DRG) is incorporated into 698 AR-DRGs which are consequently organized into Major Diagnostic Categories(MDCs) – and this is, more often than not, based on the body systems (Brooks, 2013). Each of the MDCs is known to contain three partitions – medical DRGs, surgical and other definitions Department of Health - State for Western Australia (2012). The absence or presence of an operating room or even non-operating room procedures plays a vital role in assigning of particular records to any of the partitions. Further, it is important to note that, other than the codes ICD-10-AM, there are other variables with a bearing on DRG assignment. Such variables include but are not limited to: legal status of the mental health, acceptable weights for infants aged less than one year, separation mode, duration of stay and sex of the patient. Casemix in Healthcare Funding Casemix is one of the important ways through which the world’s health system can be organized for efficiency and effectiveness with a view to providing quality healthcare in any society (Department of Health - State for Western Australia, 2012). The term ‘casemix’ is used in reference to the range and type of patients (normally a composition of different cases) that are attended to by a particular hospital or any other healthcare service provider. Casemix enables clinician to categorize, classify and even keep count of the diverse range of healthcare provided in all public hospitals. The importance of casemix among clinicians cannot be underestimated because it impacts on the funding of health services and consequently there is need for an accurate picture with regard to service provision. Besides, casemix impacts on the constitution of workforce in service delivery and also on future plans in provision of clinical services – majorly, this is based on information on the current as well as projected future healthcare needs of the community (VolEschen, 2012). The casemix system provides a rare way of comparing and describing healthcare service providers and consequently assists in the management and planning of healthcare systems. The data obtained through casemix is used to facilitate clinical research, financial management, identification of disease trends and epidemiological patterns; reviews on consumption of resources; planning for workforce and available facilities; monitoring the quality of care accorded to patients; and making of informed comparisons between the different available facilities and states. It is through the casemix system that activity based funding (ABF) framework has been introduced (Gay et al., 2013). The casemix classification system puts patients into groups that are clinically meaningful by way of using similar resources with regard to healthcare. In so doing, the clinical activities as well as quality and cost-effectiveness in a range of hospitals can be compared with a better degree of accuracy. Diagnosis, Procedures, ICD-10 and DRGs ICD-10 is a brainchild of the World Health Organization and was developed to replace the then ICD-9 (Grant & Mullin, 2014). Basically, ICD-10 is meant to give reports on diagnoses, symptoms or any signs already captured in the patient’s medical record. It therefore, follows that ICD-10 has had a major impacting on the day-to-day activities among laboratories, nurses, physicians, office administrators, staff billing and reimbursements, medical IT personnel etc. Principal diagnosis is in essence what is established after a careful study and consequently does influence the episode of care recommended for a patent in a given hospital. Importantly, an in-depth evaluation of the study comes in handy as it is mainly responsible for the episode of care occasioned. Evaluation, in this case, examines the outcome of diagnostic test carried out during the entire episode. However, it does exclude the information gathered from consecutive outpatient attendances or succeeding admissions. It is important to note that the procedure takes care of diagnostic as well as therapeutic operations that are carried out on an inpatient. Such procedures are also coded based on each and every individual patient admitted then the combination of these codes for various episodes guides the subsequent assignment to DRG using grouper software. Conclusion There is no doubt that the world needs continuous and concerted efforts to refine and enhance the efficiency of medical care programs. Such initiatives will go a long way in improving the accuracy with which payments are made and captured in healthcare institutions. After the collection of mortality and morbidity data, through ICD, it will be easy to translate disease diagnoses, and related clinical challenges hence enhance ease of storage, quick retrieval and analysis of available data. Further, and most importantly, it will be quite easy to interpret and compare clinical information from different geographical regions at any given point it time. In sum, proper storage of medical information coupled with ease of storage will surely herald a new era in enhancing the quality healthcare among humanity! References Brooks, P. (2013). ICD-9-CM/ICD-10-PCS. (2nd ed.). Baltimore, Maryland Casto, A. & Layman, E. (2006). Principles of Healthcare Reimbursement. (3rd ed.). American Health Information Management Association, Chicago, Illinois Jennings Department of Health- State for Western Australia (2012). Clinical Casemix Handbook (1st ed.). Department of Health,Western Australia European Observatory on Healthcare System Series (2007). Funding Healthcare: Options for Europe (1st ed.) Open University Press, Buckingham Grant, T. & Mullin, R. (2014). Development of the ICD-10 Procedure Coding System (2 nd ed.) International Classification of Diseases Serling, R. (2015). Developing a New Approach to Palliative Care Funding (1st ed.) NHS, England VolEschen, K. (2012). Transitioning to ICD-10. (1st ed.) Department of Health and Human Services World Health Organization (2014). International Statistical Classification of Diseases and Related Health Problems (5th ed.) University Press, Geneva Read More